Unnamed: 0 int64 0 350k | level_0 int64 0 351k | ApplicationNumber int64 9.75M 96.1M | ArtUnit int64 1.6k 3.99k | Abstract stringlengths 1 8.37k | Claims stringlengths 3 292k | abstract-claims stringlengths 68 293k | TechCenter int64 1.6k 3.9k |
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6,500 | 6,500 | 14,609,006 | 2,178 | An electronic device includes a touch-sensitive surface and a display. The device displays, on the display, a first user interface. The device detects a gesture on the touch-sensitive surface. The gesture includes movement of a contact in a respective direction on the touch-sensitive surface. In response to detecting the gesture: in accordance with a determination that the movement of the contact is entirely on a first portion of the touch-sensitive surface, the device performs an operation in the first user interface that corresponds to the gesture; and in accordance with a determination that the movement of the contact is entirely on a second portion of the touch-sensitive surface, the device replaces display of the first user interface with display of a second user interface different from the first user interface. | 1. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with a display, a touch-sensitive surface, cause the device to:
display, on the display, a first user interface; detect a gesture on the touch-sensitive surface, wherein the gesture includes movement of a contact in a respective direction on the touch-sensitive surface; and in response to detecting the gesture:
in accordance with a determination that the movement of the contact is entirely on a first portion of the touch-sensitive surface, perform an operation in the first user interface that corresponds to the gesture; and
in accordance with a determination that the movement of the contact is entirely on a second portion of the touch-sensitive surface, replace display of the first user interface with display of a second user interface different from the first user interface. 2. The computer readable storage medium of claim 1, wherein:
the first portion of the touch-sensitive surface is collocated with at least a sub-region of the display; and the second portion of the touch-sensitive surface is separate from the display. 3. The computer readable storage medium of claim 1, wherein:
the first portion of the touch-sensitive surface is a touchscreen display; and the second portion of the touch-sensitive surface is a touch-sensitive surface adjacent to the touchscreen display. 4. The computer readable storage medium of claim 1, wherein the first user interface is part of a first application and the second user interface is not part of the first application. 5. The computer readable storage medium of claim 1, wherein:
the first user interface is a first screen of a multi-screen application launch user interface; the operation in the first user interface includes displaying a second screen in the multi-screen user interface; and the second user interface is a user interface of an application launched from the multi-screen application launch user interface. 6. The computer readable storage medium of claim 1, wherein the second user interface is an application launch user interface. 7. The computer readable storage medium of claim 1, wherein the second user interface is part of a second application and the first user interface is not part of the second application. 8. The computer readable storage medium of claim 1, wherein replacing display of the first user interface with display of a second user interface different from the first user interface includes switching from a first application to a second application. 9. The computer readable storage medium of claim 1, wherein replacing display of the first user interface with display of a second user interface different from the first user interface includes launching a second application associated with the gesture that was not active prior to detecting the gesture. 10. The computer readable storage medium of claim 1, wherein, for movement of the contact that is entirely on the second portion of the touch-sensitive surface:
in accordance with a determination that the respective direction is a first direction, the second interface corresponds to a second application; and in accordance with a determination that the respective direction is a second direction different from the first direction, the second interface corresponds to a third application different from the second application. 11. The computer readable storage medium of claim 1, wherein the operation in the first user interface includes translating a portion of the first user interface in accordance with the gesture. 12. The computer readable storage medium of claim 1, wherein the operation in the first user interface includes switching between pages of a multi-page user interface in accordance with the gesture. 13. The computer readable storage medium of claim 1, wherein the operation in the first user interface includes moving a user interface object on a canvas in the first user interface in accordance with the gesture. 14. The computer readable storage medium of claim 1, wherein the operation in the first user interface includes selecting content displayed in the first user interface in accordance with the gesture. 15. The computer readable storage medium of claim 1, wherein:
the operation in the first user interface includes initiating a content modification operation; and the computer readable storage medium includes instructions which cause the device to, after initiating the content modification operation, display a confirmation user interface for confirming or canceling the content modification operation. 16. An electronic device, comprising:
a display; a touch-sensitive surface; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for:
displaying, on the display, a first user interface;
detecting a gesture on the touch-sensitive surface, wherein the gesture includes movement of a contact in a respective direction on the touch-sensitive surface; and
in response to detecting the gesture:
in accordance with a determination that the movement of the contact is entirely on a first portion of the touch-sensitive surface, performing an operation in the first user interface that corresponds to the gesture; and
in accordance with a determination that the movement of the contact is entirely on a second portion of the touch-sensitive surface, replacing display of the first user interface with display of a second user interface different from the first user interface. 17. A method, comprising:
at an electronic device with a touch-sensitive surface and a display:
displaying, on the display, a first user interface;
detecting a gesture on the touch-sensitive surface, wherein the gesture includes movement of a contact in a respective direction on the touch-sensitive surface; and
in response to detecting the gesture:
in accordance with a determination that the movement of the contact is entirely on a first portion of the touch-sensitive surface, performing an operation in the first user interface that corresponds to the gesture; and
in accordance with a determination that the movement of the contact is entirely on a second portion of the touch-sensitive surface, replacing display of the first user interface with display of a second user interface different from the first user interface. | An electronic device includes a touch-sensitive surface and a display. The device displays, on the display, a first user interface. The device detects a gesture on the touch-sensitive surface. The gesture includes movement of a contact in a respective direction on the touch-sensitive surface. In response to detecting the gesture: in accordance with a determination that the movement of the contact is entirely on a first portion of the touch-sensitive surface, the device performs an operation in the first user interface that corresponds to the gesture; and in accordance with a determination that the movement of the contact is entirely on a second portion of the touch-sensitive surface, the device replaces display of the first user interface with display of a second user interface different from the first user interface.1. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with a display, a touch-sensitive surface, cause the device to:
display, on the display, a first user interface; detect a gesture on the touch-sensitive surface, wherein the gesture includes movement of a contact in a respective direction on the touch-sensitive surface; and in response to detecting the gesture:
in accordance with a determination that the movement of the contact is entirely on a first portion of the touch-sensitive surface, perform an operation in the first user interface that corresponds to the gesture; and
in accordance with a determination that the movement of the contact is entirely on a second portion of the touch-sensitive surface, replace display of the first user interface with display of a second user interface different from the first user interface. 2. The computer readable storage medium of claim 1, wherein:
the first portion of the touch-sensitive surface is collocated with at least a sub-region of the display; and the second portion of the touch-sensitive surface is separate from the display. 3. The computer readable storage medium of claim 1, wherein:
the first portion of the touch-sensitive surface is a touchscreen display; and the second portion of the touch-sensitive surface is a touch-sensitive surface adjacent to the touchscreen display. 4. The computer readable storage medium of claim 1, wherein the first user interface is part of a first application and the second user interface is not part of the first application. 5. The computer readable storage medium of claim 1, wherein:
the first user interface is a first screen of a multi-screen application launch user interface; the operation in the first user interface includes displaying a second screen in the multi-screen user interface; and the second user interface is a user interface of an application launched from the multi-screen application launch user interface. 6. The computer readable storage medium of claim 1, wherein the second user interface is an application launch user interface. 7. The computer readable storage medium of claim 1, wherein the second user interface is part of a second application and the first user interface is not part of the second application. 8. The computer readable storage medium of claim 1, wherein replacing display of the first user interface with display of a second user interface different from the first user interface includes switching from a first application to a second application. 9. The computer readable storage medium of claim 1, wherein replacing display of the first user interface with display of a second user interface different from the first user interface includes launching a second application associated with the gesture that was not active prior to detecting the gesture. 10. The computer readable storage medium of claim 1, wherein, for movement of the contact that is entirely on the second portion of the touch-sensitive surface:
in accordance with a determination that the respective direction is a first direction, the second interface corresponds to a second application; and in accordance with a determination that the respective direction is a second direction different from the first direction, the second interface corresponds to a third application different from the second application. 11. The computer readable storage medium of claim 1, wherein the operation in the first user interface includes translating a portion of the first user interface in accordance with the gesture. 12. The computer readable storage medium of claim 1, wherein the operation in the first user interface includes switching between pages of a multi-page user interface in accordance with the gesture. 13. The computer readable storage medium of claim 1, wherein the operation in the first user interface includes moving a user interface object on a canvas in the first user interface in accordance with the gesture. 14. The computer readable storage medium of claim 1, wherein the operation in the first user interface includes selecting content displayed in the first user interface in accordance with the gesture. 15. The computer readable storage medium of claim 1, wherein:
the operation in the first user interface includes initiating a content modification operation; and the computer readable storage medium includes instructions which cause the device to, after initiating the content modification operation, display a confirmation user interface for confirming or canceling the content modification operation. 16. An electronic device, comprising:
a display; a touch-sensitive surface; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for:
displaying, on the display, a first user interface;
detecting a gesture on the touch-sensitive surface, wherein the gesture includes movement of a contact in a respective direction on the touch-sensitive surface; and
in response to detecting the gesture:
in accordance with a determination that the movement of the contact is entirely on a first portion of the touch-sensitive surface, performing an operation in the first user interface that corresponds to the gesture; and
in accordance with a determination that the movement of the contact is entirely on a second portion of the touch-sensitive surface, replacing display of the first user interface with display of a second user interface different from the first user interface. 17. A method, comprising:
at an electronic device with a touch-sensitive surface and a display:
displaying, on the display, a first user interface;
detecting a gesture on the touch-sensitive surface, wherein the gesture includes movement of a contact in a respective direction on the touch-sensitive surface; and
in response to detecting the gesture:
in accordance with a determination that the movement of the contact is entirely on a first portion of the touch-sensitive surface, performing an operation in the first user interface that corresponds to the gesture; and
in accordance with a determination that the movement of the contact is entirely on a second portion of the touch-sensitive surface, replacing display of the first user interface with display of a second user interface different from the first user interface. | 2,100 |
6,501 | 6,501 | 15,336,717 | 2,179 | Improving content descriptions and interaction efficiency by the dynamic enrichment of communication items is disclosed herein. A communication enrichment system receives a communication item, such as an email, for display within an application user interface. The system extracts enrichment details from the communication items. The communication enrichment system utilizes the enrichment details for querying one or more data sources and obtains any enrichment items relating to the enrichment details. Further, the communications items are modified to include the enrichment items to provide additional information, actions, functionality, or visual identifies to provide an enriched user interface. Accordingly, the communication enrichment system improves the efficiency of the communication client to visually identify the substance of the communication item and execute/perform any functionality associated with a communication item without opening the communication item. | 1. A method for providing dynamic enrichment of communication items, comprising:
receiving a communication item to display within an application user interface; extracting enrichment details from the communication item; querying one or more data sources for enrichment items relating to the enrichment details; retrieving the enrichment items relating to the enrichment details, the enrichment items identifying one or more of:
a visual indicator that provides a visual representation associated with the communication item;
a status indication that identifies a status associated with the communication item; or
a control that relates to an action or functionality associated with the communication item; and
modifying the communication item with the enrichment icons. 2. The method of claim 1, wherein the enrichment icons provide a visual representation of the communication item. 3. The method of claim 2, wherein the visual representation identifies a summary of the communication item. 4. The method of claim 2, wherein the visual representation identifies an intent of the communication item. 5. The method of claim 2, wherein the enrichment icons are dynamically updated based on a current context. 6. The method of claim 1, wherein the enrichment icons are configured to visually identify the substance of the communication item without opening the communication item. 7. The method of claim 1, wherein the enrichment icons are configured to visually identify a functionality associated with the communication item. 8. A computing device for providing automatic enrichment of content with contextually relevant information, comprising:
a processing unit; and a memory, including computer readable instructions, which when executed by the processing unit is operable to:
receive a communication item to display within an application user interface;
extract enrichment details from the communication item;
query one or more data sources for enrichment items relating to the enrichment details;
retrieve the enrichment items relating to the enrichment details, the enrichment items identifying one or more of:
a visual indicator that provides a visual representation associated with the communication item;
a status indication that identifies a status associated with the communication item; or
a control that relates to an action or functionality associated with the communication item; and
modify the communication item with the enrichment icons. 9. The computing device of claim 8, wherein the enrichment icons provide a visual representation of the communication item. 10. The computing device of claim 9, wherein the visual representation identifies a summary of the communication item. 11. The computing device of claim 9, wherein the visual representation identifies an intent of the communication item. 12. The computing device of claim 9, wherein the enrichment icons are dynamically updated based on a current context. 13. The computing device of claim 8, wherein the enrichment icons are configured to visually identify the substance of the communication item without opening the communication item. 14. The computing device of claim 8, wherein the enrichment icons are configured to visually identify the intent of the communication item without opening the communication item. 15. The computing device of claim 8, wherein the enrichment icons are configured to visually identify a functionality associated with the communication item. 16. A computer readable storage device including computer readable instructions, which when executed by a processing unit is operable to:
receiving a communication item to display within an application user interface; extracting enrichment details from the communication item; querying one or more data sources for enrichment items relating to the enrichment details; retrieving the enrichment items relating to the enrichment details, the enrichment items identifying one or more of:
a visual indicator that provides a visual representation associated with the communication item;
a status indication that identifies a status associated with the communication item; or
a control that relates to an action or functionality associated with the communication item; and
modifying the communication item with the enrichment icons. 17. The computer readable storage device of claim 16, wherein the enrichment icons are dynamically updated based on a current context. 18. The computer readable storage device of claim 16, wherein the enrichment icons are configured to visually identify the substance of the communication item without opening the communication item. 19. The computer readable storage device of claim 16, wherein the enrichment icons are configured to visually identify the intent of the communication item without opening the communication item. 20. The computer readable storage device of claim 16, wherein the enrichment icons are configured to visually identify a functionality associated with the communication item. | Improving content descriptions and interaction efficiency by the dynamic enrichment of communication items is disclosed herein. A communication enrichment system receives a communication item, such as an email, for display within an application user interface. The system extracts enrichment details from the communication items. The communication enrichment system utilizes the enrichment details for querying one or more data sources and obtains any enrichment items relating to the enrichment details. Further, the communications items are modified to include the enrichment items to provide additional information, actions, functionality, or visual identifies to provide an enriched user interface. Accordingly, the communication enrichment system improves the efficiency of the communication client to visually identify the substance of the communication item and execute/perform any functionality associated with a communication item without opening the communication item.1. A method for providing dynamic enrichment of communication items, comprising:
receiving a communication item to display within an application user interface; extracting enrichment details from the communication item; querying one or more data sources for enrichment items relating to the enrichment details; retrieving the enrichment items relating to the enrichment details, the enrichment items identifying one or more of:
a visual indicator that provides a visual representation associated with the communication item;
a status indication that identifies a status associated with the communication item; or
a control that relates to an action or functionality associated with the communication item; and
modifying the communication item with the enrichment icons. 2. The method of claim 1, wherein the enrichment icons provide a visual representation of the communication item. 3. The method of claim 2, wherein the visual representation identifies a summary of the communication item. 4. The method of claim 2, wherein the visual representation identifies an intent of the communication item. 5. The method of claim 2, wherein the enrichment icons are dynamically updated based on a current context. 6. The method of claim 1, wherein the enrichment icons are configured to visually identify the substance of the communication item without opening the communication item. 7. The method of claim 1, wherein the enrichment icons are configured to visually identify a functionality associated with the communication item. 8. A computing device for providing automatic enrichment of content with contextually relevant information, comprising:
a processing unit; and a memory, including computer readable instructions, which when executed by the processing unit is operable to:
receive a communication item to display within an application user interface;
extract enrichment details from the communication item;
query one or more data sources for enrichment items relating to the enrichment details;
retrieve the enrichment items relating to the enrichment details, the enrichment items identifying one or more of:
a visual indicator that provides a visual representation associated with the communication item;
a status indication that identifies a status associated with the communication item; or
a control that relates to an action or functionality associated with the communication item; and
modify the communication item with the enrichment icons. 9. The computing device of claim 8, wherein the enrichment icons provide a visual representation of the communication item. 10. The computing device of claim 9, wherein the visual representation identifies a summary of the communication item. 11. The computing device of claim 9, wherein the visual representation identifies an intent of the communication item. 12. The computing device of claim 9, wherein the enrichment icons are dynamically updated based on a current context. 13. The computing device of claim 8, wherein the enrichment icons are configured to visually identify the substance of the communication item without opening the communication item. 14. The computing device of claim 8, wherein the enrichment icons are configured to visually identify the intent of the communication item without opening the communication item. 15. The computing device of claim 8, wherein the enrichment icons are configured to visually identify a functionality associated with the communication item. 16. A computer readable storage device including computer readable instructions, which when executed by a processing unit is operable to:
receiving a communication item to display within an application user interface; extracting enrichment details from the communication item; querying one or more data sources for enrichment items relating to the enrichment details; retrieving the enrichment items relating to the enrichment details, the enrichment items identifying one or more of:
a visual indicator that provides a visual representation associated with the communication item;
a status indication that identifies a status associated with the communication item; or
a control that relates to an action or functionality associated with the communication item; and
modifying the communication item with the enrichment icons. 17. The computer readable storage device of claim 16, wherein the enrichment icons are dynamically updated based on a current context. 18. The computer readable storage device of claim 16, wherein the enrichment icons are configured to visually identify the substance of the communication item without opening the communication item. 19. The computer readable storage device of claim 16, wherein the enrichment icons are configured to visually identify the intent of the communication item without opening the communication item. 20. The computer readable storage device of claim 16, wherein the enrichment icons are configured to visually identify a functionality associated with the communication item. | 2,100 |
6,502 | 6,502 | 14,651,281 | 2,198 | At least one aspect of the present disclosure describes a content optimization system using probability factors including a rule management module, a content generation module, and a content evaluation module. The rule management module maintains a set of rules for content generation, the set of rules comprising a rule on probability factor, the rule on probability factor specifying a statistical probability that a piece of content expresses a particular value of a selected content attribute. The content generation module is operative to generate a plurality of pieces of content based on the set of rules, the plurality of pieces of content designed with a particular optimization objective. The content evaluation module is operative to evaluate content performance on reaching the particular optimization objective based on data acquired when the plurality of pieces of content are displayed, and the content evaluation module is further operative to determine an aggregated performance data for the selected content attribute having the particular value based on the evaluated content performance. | 1. A method for content optimization, comprising:
receiving a rule on probability factor, the rule on probability factor specifying a statistical probability that a piece of content expresses a particular value of a selected content attribute; generating a plurality of pieces of content in accordance with the rule on probability factor; collecting content performance data of the plurality of pieces of content when the plurality of pieces of content are in use; determining, by a processor, an aggregated performance data for the selected content attribute having the particular value based on the content performance data of the plurality of pieces of content; and modifying, by the processor, the rule on probability factor based on the aggregated performance data. 2. The method of claim 1, wherein the selected content attribute is an attribute of a content element, an attribute of a relationship, an attribute of a size or position adjustment, or an attribute of a transition. 3. The method of claim 2, wherein the rule on probability factor specifies a statistical probability that a piece of content expresses a particular value of an attribute of a relationship. 4. The method of claim 3, further comprising:
modifying, by the processor, a second rule on probability factor based on the aggregated performance data, the second rule on probability factor specifying a statistical probability that a piece of content expresses a particular value of an attribute of a size or position adjustment within the relationship. 5. The method of claim 1, further comprising:
determining, by the processor, a deviation value for aggregated performance data the selected content attribute based on the content performance data of the plurality of pieces of content, wherein the modifying step comprises modifying the rule on probability factor based on both the aggregated performance data and the deviation value for the aggregated performance data for the selected content attribute. 6. The method of claim 1, further comprising:
receiving a set of rules for content generation; identifying a changeable content attribute based on the set of rules for content generation; and composing, by the processor, one or more rules on probability factor for the changeable content attribute. 7. The method of claim 6, wherein the composing step comprises composing the one or more rules on probability factor to assign an equal probability to each value of a set of selected values for the changeable content attribute. 8. A content optimization system, comprising:
a rule management module maintaining a set of rules for content generation, the set of rules comprising a rule on probability factor, the rule on probability factor specifying a statistical probability that a piece of content expresses a particular value of a selected content attribute; a content generation module operative to generate a plurality of pieces of content based on the set of rules, the plurality of pieces of content designed with a particular optimization objective; and a content evaluation module operative to evaluate content performance on reaching the particular optimization objective based on data acquired when the plurality of pieces of content are displayed, wherein the content evaluation module is further operative to determine an aggregated performance data for the selected content attribute having the particular value based on the evaluated content performance, wherein the rule management module is operative to amend the rule on probability factor based on the aggregated content performance data. 9. The system of claim 8, wherein the selected content attribute is an attribute of a content element, an attribute of a relationship, an attribute of a metric adjustment, or an attribute of a transition. 10. The system of claim 8, wherein the content evaluation module is further operative to determine a deviation value for the aggregated performance data for the selected content attribute based on the content performance data of the plurality of pieces of content, and
wherein the rule management module is further operative to modify the rule on probability factor based on both the aggregated performance data and the deviation value for the aggregated performance data for the selected content attribute. 11. The system of claim 8, wherein the rule management module is further operative to identify a changeable content attribute based on the set of rules for content generation and compose a rule on probability factor for the changeable content attribute. 12. The system of claim 11, wherein the rule management module is further operative to compose one or more rules on probability factor, wherein the one or more composed rules on probability factor assign an equal probability to each value of a set of selected values for the changeable content attribute. 13. A method comprising:
receiving a first rule on probability factor and a second rule on probability factor, the first rule on probability factor defining a statistical probability that a piece of content expresses a first value of a selected content attribute, the second rule on probability factor defining a statistical probability that a piece of content expresses a second value of the selected content attribute, the second value being different from the first value; generating a plurality of pieces of content in accordance with the first rule on probability factor and the second rule on probability factor; collecting content performance data of the plurality of pieces of content when the plurality of pieces of content are in use; determining, by a processor, a first aggregated performance data for the first value of the selected content attribute based on the content performance data of the plurality of pieces of content; determining, by the processor, a second aggregated performance data for the second value of the selected content attribute based on the content performance data of the plurality of pieces of content; and modifying, by the processor, the first rule on probability factor and the second rule on probability factor based on both the first aggregated performance data and the second aggregated performance data. 14. The method of claim 13, wherein the selected content attribute is an attribute of a content element, an attribute of a relationship, an attribute of a metric adjustment, or an attribute of a transition. 15. The method of claim 13, further comprising:
determining, by the processor, a deviation value for the first aggregated performance data for the selected content attribute based on the content performance data of the plurality of pieces of content, wherein the modifying step comprises modifying the first rule on probability factor based on both the first aggregated performance data and the deviation value for the first aggregated performance data for the selected content attribute. | At least one aspect of the present disclosure describes a content optimization system using probability factors including a rule management module, a content generation module, and a content evaluation module. The rule management module maintains a set of rules for content generation, the set of rules comprising a rule on probability factor, the rule on probability factor specifying a statistical probability that a piece of content expresses a particular value of a selected content attribute. The content generation module is operative to generate a plurality of pieces of content based on the set of rules, the plurality of pieces of content designed with a particular optimization objective. The content evaluation module is operative to evaluate content performance on reaching the particular optimization objective based on data acquired when the plurality of pieces of content are displayed, and the content evaluation module is further operative to determine an aggregated performance data for the selected content attribute having the particular value based on the evaluated content performance.1. A method for content optimization, comprising:
receiving a rule on probability factor, the rule on probability factor specifying a statistical probability that a piece of content expresses a particular value of a selected content attribute; generating a plurality of pieces of content in accordance with the rule on probability factor; collecting content performance data of the plurality of pieces of content when the plurality of pieces of content are in use; determining, by a processor, an aggregated performance data for the selected content attribute having the particular value based on the content performance data of the plurality of pieces of content; and modifying, by the processor, the rule on probability factor based on the aggregated performance data. 2. The method of claim 1, wherein the selected content attribute is an attribute of a content element, an attribute of a relationship, an attribute of a size or position adjustment, or an attribute of a transition. 3. The method of claim 2, wherein the rule on probability factor specifies a statistical probability that a piece of content expresses a particular value of an attribute of a relationship. 4. The method of claim 3, further comprising:
modifying, by the processor, a second rule on probability factor based on the aggregated performance data, the second rule on probability factor specifying a statistical probability that a piece of content expresses a particular value of an attribute of a size or position adjustment within the relationship. 5. The method of claim 1, further comprising:
determining, by the processor, a deviation value for aggregated performance data the selected content attribute based on the content performance data of the plurality of pieces of content, wherein the modifying step comprises modifying the rule on probability factor based on both the aggregated performance data and the deviation value for the aggregated performance data for the selected content attribute. 6. The method of claim 1, further comprising:
receiving a set of rules for content generation; identifying a changeable content attribute based on the set of rules for content generation; and composing, by the processor, one or more rules on probability factor for the changeable content attribute. 7. The method of claim 6, wherein the composing step comprises composing the one or more rules on probability factor to assign an equal probability to each value of a set of selected values for the changeable content attribute. 8. A content optimization system, comprising:
a rule management module maintaining a set of rules for content generation, the set of rules comprising a rule on probability factor, the rule on probability factor specifying a statistical probability that a piece of content expresses a particular value of a selected content attribute; a content generation module operative to generate a plurality of pieces of content based on the set of rules, the plurality of pieces of content designed with a particular optimization objective; and a content evaluation module operative to evaluate content performance on reaching the particular optimization objective based on data acquired when the plurality of pieces of content are displayed, wherein the content evaluation module is further operative to determine an aggregated performance data for the selected content attribute having the particular value based on the evaluated content performance, wherein the rule management module is operative to amend the rule on probability factor based on the aggregated content performance data. 9. The system of claim 8, wherein the selected content attribute is an attribute of a content element, an attribute of a relationship, an attribute of a metric adjustment, or an attribute of a transition. 10. The system of claim 8, wherein the content evaluation module is further operative to determine a deviation value for the aggregated performance data for the selected content attribute based on the content performance data of the plurality of pieces of content, and
wherein the rule management module is further operative to modify the rule on probability factor based on both the aggregated performance data and the deviation value for the aggregated performance data for the selected content attribute. 11. The system of claim 8, wherein the rule management module is further operative to identify a changeable content attribute based on the set of rules for content generation and compose a rule on probability factor for the changeable content attribute. 12. The system of claim 11, wherein the rule management module is further operative to compose one or more rules on probability factor, wherein the one or more composed rules on probability factor assign an equal probability to each value of a set of selected values for the changeable content attribute. 13. A method comprising:
receiving a first rule on probability factor and a second rule on probability factor, the first rule on probability factor defining a statistical probability that a piece of content expresses a first value of a selected content attribute, the second rule on probability factor defining a statistical probability that a piece of content expresses a second value of the selected content attribute, the second value being different from the first value; generating a plurality of pieces of content in accordance with the first rule on probability factor and the second rule on probability factor; collecting content performance data of the plurality of pieces of content when the plurality of pieces of content are in use; determining, by a processor, a first aggregated performance data for the first value of the selected content attribute based on the content performance data of the plurality of pieces of content; determining, by the processor, a second aggregated performance data for the second value of the selected content attribute based on the content performance data of the plurality of pieces of content; and modifying, by the processor, the first rule on probability factor and the second rule on probability factor based on both the first aggregated performance data and the second aggregated performance data. 14. The method of claim 13, wherein the selected content attribute is an attribute of a content element, an attribute of a relationship, an attribute of a metric adjustment, or an attribute of a transition. 15. The method of claim 13, further comprising:
determining, by the processor, a deviation value for the first aggregated performance data for the selected content attribute based on the content performance data of the plurality of pieces of content, wherein the modifying step comprises modifying the first rule on probability factor based on both the first aggregated performance data and the deviation value for the first aggregated performance data for the selected content attribute. | 2,100 |
6,503 | 6,503 | 14,871,040 | 2,161 | A system, method, and processor readable medium for processing data in a knowledge management system gathers information content and transmits a work request for the information content gathered. The information content may be registered with a K-map and assigned a unique document identifier. A work queue processes the work requests. The processed information may then be transmitted to another work queue for further processing. Further processing may include categorization, full-text indexing, metrics extraction or other process. Control messages may be transmitted to one or more users providing a status of the work request. The information may be analyzed and further indexed. A progress statistics report may be generated for each of the processes performed on the document. The progress statistics may be provided in a record. A shared access to a central data structure representing the metrics history and taxonomy may be provided for all work queues via a CORBA service. | 1-19. (canceled) 20. A computer-implemented method, comprising:
identifying, using a computer hardware system, a match between:
(i) a content of a document stored within one or more data repositories, and
(ii) an affinity of a user;
modifying, based upon the match, a knowledge map; and gathering, using the knowledge map and from the one or more data repositories, one or more documents with contents that match the affinity of the user; 21. The method of claim 20, further comprising
organizing the one or more gathered documents into categories. 22. The method of claim 20, wherein
the one or more data repositories are non-web based data repositories. 23. The method of claim 20, wherein
at least one of the one or more data repositories is selected by the user. 24. The method of claim 20, further comprising
notifying the user that the one or more documents with contents that match the affinity of the user have been gathered. 25. The method of claim 20, wherein
the knowledge map includes a map of all information stored in the one or more data repositories. 26. The method of claim 20, wherein
the knowledge map includes categories of information stored in the one or more data repositories. 27. The method of claim 20, wherein
the knowledge map includes a full-text index of information stored in the one or more data repositories. 28. The method of claim 20, wherein
the knowledge map includes metrics information for information stored in the one or more data repositories. 29. A computer hardware system, comprising:
at least one hardware processor, wherein the at least one hardware processor is configured to initiate and/or perform:
identifying a match between:
(i) a content of a document stored within one or more data repositories, and
(ii) an affinity of a user;
modifying, based upon the match, a knowledge map; and
gathering, using the knowledge map and from the one or more data repositories, one or more documents with contents that match the affinity of the user. 30. The system of claim 29, wherein the at least one hardware processor is further configured to initiate and/or perform
organizing the one or more gathered documents into categories. 31. The system of claim 29, wherein
the one or more data repositories are non-web based data repositories. 32. The system of claim 29, wherein
at least one of the one or more data repositories is selected by the user. 33. The system of claim 29, wherein the at least one hardware processor is further configured to initiate and/or perform
notifying the user that the one or more documents with contents that match the affinity of the user have been gathered. 34. The system of claim 29, wherein
the knowledge map includes a map of all information stored in the one or more data repositories. 35. The system of claim 29, wherein
the knowledge map includes categories of information stored in the one or more data repositories. 36. The system of claim 29, wherein
the knowledge map includes a full-text index of information stored in the one or more data repositories. 37. The system of claim 29, wherein
the knowledge map includes metrics information for information stored in the one or more data repositories. | A system, method, and processor readable medium for processing data in a knowledge management system gathers information content and transmits a work request for the information content gathered. The information content may be registered with a K-map and assigned a unique document identifier. A work queue processes the work requests. The processed information may then be transmitted to another work queue for further processing. Further processing may include categorization, full-text indexing, metrics extraction or other process. Control messages may be transmitted to one or more users providing a status of the work request. The information may be analyzed and further indexed. A progress statistics report may be generated for each of the processes performed on the document. The progress statistics may be provided in a record. A shared access to a central data structure representing the metrics history and taxonomy may be provided for all work queues via a CORBA service.1-19. (canceled) 20. A computer-implemented method, comprising:
identifying, using a computer hardware system, a match between:
(i) a content of a document stored within one or more data repositories, and
(ii) an affinity of a user;
modifying, based upon the match, a knowledge map; and gathering, using the knowledge map and from the one or more data repositories, one or more documents with contents that match the affinity of the user; 21. The method of claim 20, further comprising
organizing the one or more gathered documents into categories. 22. The method of claim 20, wherein
the one or more data repositories are non-web based data repositories. 23. The method of claim 20, wherein
at least one of the one or more data repositories is selected by the user. 24. The method of claim 20, further comprising
notifying the user that the one or more documents with contents that match the affinity of the user have been gathered. 25. The method of claim 20, wherein
the knowledge map includes a map of all information stored in the one or more data repositories. 26. The method of claim 20, wherein
the knowledge map includes categories of information stored in the one or more data repositories. 27. The method of claim 20, wherein
the knowledge map includes a full-text index of information stored in the one or more data repositories. 28. The method of claim 20, wherein
the knowledge map includes metrics information for information stored in the one or more data repositories. 29. A computer hardware system, comprising:
at least one hardware processor, wherein the at least one hardware processor is configured to initiate and/or perform:
identifying a match between:
(i) a content of a document stored within one or more data repositories, and
(ii) an affinity of a user;
modifying, based upon the match, a knowledge map; and
gathering, using the knowledge map and from the one or more data repositories, one or more documents with contents that match the affinity of the user. 30. The system of claim 29, wherein the at least one hardware processor is further configured to initiate and/or perform
organizing the one or more gathered documents into categories. 31. The system of claim 29, wherein
the one or more data repositories are non-web based data repositories. 32. The system of claim 29, wherein
at least one of the one or more data repositories is selected by the user. 33. The system of claim 29, wherein the at least one hardware processor is further configured to initiate and/or perform
notifying the user that the one or more documents with contents that match the affinity of the user have been gathered. 34. The system of claim 29, wherein
the knowledge map includes a map of all information stored in the one or more data repositories. 35. The system of claim 29, wherein
the knowledge map includes categories of information stored in the one or more data repositories. 36. The system of claim 29, wherein
the knowledge map includes a full-text index of information stored in the one or more data repositories. 37. The system of claim 29, wherein
the knowledge map includes metrics information for information stored in the one or more data repositories. | 2,100 |
6,504 | 6,504 | 16,248,967 | 2,153 | A Personal Memory Drive provides a system using memory and its database and kept in their personal possession. The database is segregated by firewalls to partition information into a public, a semi-private, a private section using firewalls. A PC accessed by the drive partitions the computer into segments thereby shadowing the drive segments. The drive allows private, local, and global databases to be searched and the results of the search snippets can be provided to the user. This search activity can be occurring during active conversations with others. The search analysis can also use sentence diagramming to partition the dialogue. The returned snippets can be filtered and processed by brain sensors coupled to the user. The device can aid the user where these search snippets can be used to enhance the conversation where some individuals of the party would not be aware of the aided help given to the user. | 1. A Personal Memory Drive for a conversation comprising:
a personal memory drive coupled to an owner; wherein the personal memory drive is configured to transmit search terms extracted from the conversation to at least one database and is configured to receive search results from the at least one database; and a text to speech translator configured to convert the search results to a search result speech, wherein of the search result speech, at least one snippet is configured to be heard by the owner. 2. The apparatus of claim 1, wherein
the snippet is configured to be generated during the conversation between the owner and others. 3. The apparatus of claim 1, wherein
the snippet is configured to be heard by the owner during a period of silence in the conversation or during a period of concentration of the owner that is sensed by a brain wave transducer in the personal memory drive that is in contact with an ear canal of the owner. 4. The apparatus of claim 1, wherein
the personal memory drive is inserted within an ear canal of the owner, wherein the personal memory drive can be hidden from view. 5. The apparatus of claim 1, wherein
the at least one database is selected from the group consisting of a private database available only to the owner, a public database available to other users selected by the owner and an Internet database available to anyone. 6. The apparatus of claim 1, wherein
the personal memory drive is configured to communicate with other personal memory drives owned by other users, other PCs, and the Internet. 7. The apparatus of claim 1, further comprising:
at least one local search engine configured to search at least one local memory, wherein the at least one local memory is configured to have at least one local database; and at least one local server serving the at least one local database. 8. The apparatus of claim 1, wherein
a dialogue of the conversation is heard by the owner; a reply to the dialogue is thought out by the owner after integrating both the dialogue and the at least one snippet from the total search speech, wherein the reply is added to the conversation by the owner. 9. A Personal Memory Drive (PMD) comprising:
a private memory drive coupled to an owner; and a public memory drive wirelessly coupled to the private memory drive, wherein the public memory drive is configured to transmit search terms to the Internet extracted from a conversation and is configured to receive global search results from the Internet, wherein the public memory drive is configured to transmit the search terms to a public database and is configured to receive public search results from the public database, wherein the private memory drive is configured to transmit the search terms to a private database and is configured to receive private search results from the private database, wherein the public and global search results received by the public memory drive are transmitted to the private memory drive, wherein all search results are combined into a total search result; and a text to speech translator configured to convert the total search result to a total search speech, wherein of the total search speech, at least one snippet is configured to be heard by the owner. 10. The apparatus of claim 9, wherein
the snippet is configured to be generated during the conversation between the owner and others. 11. The apparatus of claim 9, wherein
the snippet is configured to be heard by the owner during a period of silence in the conversation or during a period of concentration of the owner that is sensed by a brain wave transducer that is in contact with an ear canal of the owner in the personal memory drive. 12. The apparatus of claim 9, wherein
the private memory drive is inserted within an ear canal of the owner, wherein the private memory drive can be hidden from view. 13. The apparatus of claim 9, wherein
the conversation is occurring between the owner and at least one other person selected from the group consisting of a person sharing a room with the owner, a person sharing a telephone call with the owner and a person not aware the owner is being aided by the PMD. 14. The apparatus of claim 9, wherein
the personal memory drive is configured to communicate with other personal memory drives owned by other users, other PCs, and the Internet. 15. The apparatus of claim 9, further comprising:
at least one local search engine configured to search at least one local memory, wherein the at least one local memory is configured to have at least one local database; and at least one local server serving the at least one local database. 16. The apparatus of claim 9, wherein
a dialogue of the conversation is heard by the owner; a reply to the dialogue is thought out by the owner after integrating both the dialogue and the at least one snippet from the total search speech, wherein the reply is added to the conversation by the owner. 17. A method of an owner of a Personal Memory Drive (PMD) and the PMD both responding to a conversation comprising, the steps of:
listening to a dialogue of a conversation performed by the owner; thinking about a reply to the dialogue performed by the owner; configuring a speech to text device of the PMD to translate the dialogue into text; selecting search terms from the text of the dialogue performed by the PMD; searching in at least one database for the search terms performed by the PMD; queuing a result of the searching into a queue database performed by the PMD; selecting at least one snippet from the queue database performed by the PMD; configuring a text to speech device of the PMD to translate the at least one snippet into a search result dialogue; providing the search result dialogue to the owner; integrating at least one thought between that of thinking about the reply to the dialogue and the search result dialogue provided to the owner by the PMD; and replying to the dialogue of the conversation using a result of integrating the at least one thought. 18. The method of claim 17, wherein
the conversation is occurring between the owner and at least one other person selected from the group consisting of a person sharing a room with the owner, a person sharing a telephone call with the owner and a person not aware the owner is being aided by the PMD. 19. The method of claim 17, wherein
the at least one database is selected from the group consisting of a private database, available only to the owner, a public database available to other users selected by the owner and a database of the Internet available to anyone 20. The method of claim 17, wherein
the at least one snippet is configured to be heard by the owner during a period of silence in a conversation or during a period of concentration of the owner that is sensed by a brain wave transducer that is in contact with an ear canal of the owner in the PMD. | A Personal Memory Drive provides a system using memory and its database and kept in their personal possession. The database is segregated by firewalls to partition information into a public, a semi-private, a private section using firewalls. A PC accessed by the drive partitions the computer into segments thereby shadowing the drive segments. The drive allows private, local, and global databases to be searched and the results of the search snippets can be provided to the user. This search activity can be occurring during active conversations with others. The search analysis can also use sentence diagramming to partition the dialogue. The returned snippets can be filtered and processed by brain sensors coupled to the user. The device can aid the user where these search snippets can be used to enhance the conversation where some individuals of the party would not be aware of the aided help given to the user.1. A Personal Memory Drive for a conversation comprising:
a personal memory drive coupled to an owner; wherein the personal memory drive is configured to transmit search terms extracted from the conversation to at least one database and is configured to receive search results from the at least one database; and a text to speech translator configured to convert the search results to a search result speech, wherein of the search result speech, at least one snippet is configured to be heard by the owner. 2. The apparatus of claim 1, wherein
the snippet is configured to be generated during the conversation between the owner and others. 3. The apparatus of claim 1, wherein
the snippet is configured to be heard by the owner during a period of silence in the conversation or during a period of concentration of the owner that is sensed by a brain wave transducer in the personal memory drive that is in contact with an ear canal of the owner. 4. The apparatus of claim 1, wherein
the personal memory drive is inserted within an ear canal of the owner, wherein the personal memory drive can be hidden from view. 5. The apparatus of claim 1, wherein
the at least one database is selected from the group consisting of a private database available only to the owner, a public database available to other users selected by the owner and an Internet database available to anyone. 6. The apparatus of claim 1, wherein
the personal memory drive is configured to communicate with other personal memory drives owned by other users, other PCs, and the Internet. 7. The apparatus of claim 1, further comprising:
at least one local search engine configured to search at least one local memory, wherein the at least one local memory is configured to have at least one local database; and at least one local server serving the at least one local database. 8. The apparatus of claim 1, wherein
a dialogue of the conversation is heard by the owner; a reply to the dialogue is thought out by the owner after integrating both the dialogue and the at least one snippet from the total search speech, wherein the reply is added to the conversation by the owner. 9. A Personal Memory Drive (PMD) comprising:
a private memory drive coupled to an owner; and a public memory drive wirelessly coupled to the private memory drive, wherein the public memory drive is configured to transmit search terms to the Internet extracted from a conversation and is configured to receive global search results from the Internet, wherein the public memory drive is configured to transmit the search terms to a public database and is configured to receive public search results from the public database, wherein the private memory drive is configured to transmit the search terms to a private database and is configured to receive private search results from the private database, wherein the public and global search results received by the public memory drive are transmitted to the private memory drive, wherein all search results are combined into a total search result; and a text to speech translator configured to convert the total search result to a total search speech, wherein of the total search speech, at least one snippet is configured to be heard by the owner. 10. The apparatus of claim 9, wherein
the snippet is configured to be generated during the conversation between the owner and others. 11. The apparatus of claim 9, wherein
the snippet is configured to be heard by the owner during a period of silence in the conversation or during a period of concentration of the owner that is sensed by a brain wave transducer that is in contact with an ear canal of the owner in the personal memory drive. 12. The apparatus of claim 9, wherein
the private memory drive is inserted within an ear canal of the owner, wherein the private memory drive can be hidden from view. 13. The apparatus of claim 9, wherein
the conversation is occurring between the owner and at least one other person selected from the group consisting of a person sharing a room with the owner, a person sharing a telephone call with the owner and a person not aware the owner is being aided by the PMD. 14. The apparatus of claim 9, wherein
the personal memory drive is configured to communicate with other personal memory drives owned by other users, other PCs, and the Internet. 15. The apparatus of claim 9, further comprising:
at least one local search engine configured to search at least one local memory, wherein the at least one local memory is configured to have at least one local database; and at least one local server serving the at least one local database. 16. The apparatus of claim 9, wherein
a dialogue of the conversation is heard by the owner; a reply to the dialogue is thought out by the owner after integrating both the dialogue and the at least one snippet from the total search speech, wherein the reply is added to the conversation by the owner. 17. A method of an owner of a Personal Memory Drive (PMD) and the PMD both responding to a conversation comprising, the steps of:
listening to a dialogue of a conversation performed by the owner; thinking about a reply to the dialogue performed by the owner; configuring a speech to text device of the PMD to translate the dialogue into text; selecting search terms from the text of the dialogue performed by the PMD; searching in at least one database for the search terms performed by the PMD; queuing a result of the searching into a queue database performed by the PMD; selecting at least one snippet from the queue database performed by the PMD; configuring a text to speech device of the PMD to translate the at least one snippet into a search result dialogue; providing the search result dialogue to the owner; integrating at least one thought between that of thinking about the reply to the dialogue and the search result dialogue provided to the owner by the PMD; and replying to the dialogue of the conversation using a result of integrating the at least one thought. 18. The method of claim 17, wherein
the conversation is occurring between the owner and at least one other person selected from the group consisting of a person sharing a room with the owner, a person sharing a telephone call with the owner and a person not aware the owner is being aided by the PMD. 19. The method of claim 17, wherein
the at least one database is selected from the group consisting of a private database, available only to the owner, a public database available to other users selected by the owner and a database of the Internet available to anyone 20. The method of claim 17, wherein
the at least one snippet is configured to be heard by the owner during a period of silence in a conversation or during a period of concentration of the owner that is sensed by a brain wave transducer that is in contact with an ear canal of the owner in the PMD. | 2,100 |
6,505 | 6,505 | 15,790,210 | 2,119 | Systems and methods for controlling adhesive application are disclosed. The systems and methods may include a controller and one or more sensors configured to measure an amount of adhesive applied to a plurality of substrates by a pump, detect a number of the substrates, determine an amount of adhesive applied per substrate, compare the adhesive applied per substrate to a target value, and adjust a pressure of the pump based on the comparison. The sensor(s) may include one or more of a valve sensor coupled to an adhesive supply, a flow rate sensor coupled to a manifold, a flow rate sensor coupled to one or more hoses, and a flow rate sensors coupled to a gun. | 1. A method for controlling adhesive application, the method comprising:
measuring an amount of adhesive applied to a plurality of substrates by a pump; detecting a number of the substrates; determining an amount of adhesive applied per substrate; comparing the adhesive applied per substrate to a target value; and adjusting a pressure of the pump based on the comparison. 2. The method of claim 1, wherein measuring the amount of adhesive applied includes detecting opening of a valve of a supply. 3. The method of claim 1, wherein measuring the amount of adhesive applied includes detecting a flow rate of the adhesive with a flow sensor. 4. The method of claim 3, wherein detecting the flow rate includes detecting the flow rate in a manifold. 5. The method of claim 3, wherein detecting the flow rate includes detecting the flow rate in a hose in communication with an applicator. 6. The method of claim 1, wherein detecting the number of the substrates includes detecting a number of the substrates on a conveyor belt passing a sensor. 7. The method of claim 1, further comprising receiving the target value with a user interface. 8. A control system for controlling adhesive application, the system comprising:
a first sensor configured to measure an amount of adhesive applied to a plurality of substrates by a pump; a second sensor configured to detect a number of the substrates; a controller in communication with the first sensor and the second sensor, the controller being configured to:
determine an amount of adhesive applied per substrate;
compare the adhesive applied per substrate to a target value; and
adjust a pressure of the pump based on the comparison. 9. The system of claim 8, wherein the first sensor is configured to detect opening of a valve of a supply to measure the amount of the adhesive applied. 10. The system of claim 8, wherein the first sensor is configured to detect a flow rate of the adhesive to measure the amount of the adhesive applied. 11. The system of claim 10, wherein the first sensor is configured to detect the flow rate in a manifold. 12. The system of claim 10, wherein the first sensor is configured to detect the flow rate in a hose in communication with an applicator. 13. The system of claim 8, wherein the second sensor is configured to detect a number of the substrates on a conveyor belt. 14. The system of claim 8, further including a user interface configured to receive the target value. 15. A non-transitory computer-readable medium storing instructions which, when executed, cause one or more processors to perform a process for controlling adhesive application, the process comprising:
measuring an amount of adhesive applied to a plurality of substrates by a pump; detecting a number of the substrates; determining an amount of adhesive applied per substrate; comparing the adhesive applied per substrate to a target value; and adjusting a pressure of the pump based on the comparison. 16. The medium of claim 15, wherein measuring the amount of adhesive applied includes detecting opening of a valve of a supply. 17. The medium of claim 15, wherein measuring the amount of adhesive applied includes detecting a flow rate of the adhesive with a flow sensor. 18. The medium of claim 17, wherein detecting the flow rate includes detecting the flow rate in a manifold. 19. The medium of claim 17, wherein detecting the flow rate includes detecting the flow rate in a hose in communication with an applicator. 20. The medium of claim 15, wherein detecting the number of the substrates includes detecting a number of the substrates on a conveyor belt passing a sensor. | Systems and methods for controlling adhesive application are disclosed. The systems and methods may include a controller and one or more sensors configured to measure an amount of adhesive applied to a plurality of substrates by a pump, detect a number of the substrates, determine an amount of adhesive applied per substrate, compare the adhesive applied per substrate to a target value, and adjust a pressure of the pump based on the comparison. The sensor(s) may include one or more of a valve sensor coupled to an adhesive supply, a flow rate sensor coupled to a manifold, a flow rate sensor coupled to one or more hoses, and a flow rate sensors coupled to a gun.1. A method for controlling adhesive application, the method comprising:
measuring an amount of adhesive applied to a plurality of substrates by a pump; detecting a number of the substrates; determining an amount of adhesive applied per substrate; comparing the adhesive applied per substrate to a target value; and adjusting a pressure of the pump based on the comparison. 2. The method of claim 1, wherein measuring the amount of adhesive applied includes detecting opening of a valve of a supply. 3. The method of claim 1, wherein measuring the amount of adhesive applied includes detecting a flow rate of the adhesive with a flow sensor. 4. The method of claim 3, wherein detecting the flow rate includes detecting the flow rate in a manifold. 5. The method of claim 3, wherein detecting the flow rate includes detecting the flow rate in a hose in communication with an applicator. 6. The method of claim 1, wherein detecting the number of the substrates includes detecting a number of the substrates on a conveyor belt passing a sensor. 7. The method of claim 1, further comprising receiving the target value with a user interface. 8. A control system for controlling adhesive application, the system comprising:
a first sensor configured to measure an amount of adhesive applied to a plurality of substrates by a pump; a second sensor configured to detect a number of the substrates; a controller in communication with the first sensor and the second sensor, the controller being configured to:
determine an amount of adhesive applied per substrate;
compare the adhesive applied per substrate to a target value; and
adjust a pressure of the pump based on the comparison. 9. The system of claim 8, wherein the first sensor is configured to detect opening of a valve of a supply to measure the amount of the adhesive applied. 10. The system of claim 8, wherein the first sensor is configured to detect a flow rate of the adhesive to measure the amount of the adhesive applied. 11. The system of claim 10, wherein the first sensor is configured to detect the flow rate in a manifold. 12. The system of claim 10, wherein the first sensor is configured to detect the flow rate in a hose in communication with an applicator. 13. The system of claim 8, wherein the second sensor is configured to detect a number of the substrates on a conveyor belt. 14. The system of claim 8, further including a user interface configured to receive the target value. 15. A non-transitory computer-readable medium storing instructions which, when executed, cause one or more processors to perform a process for controlling adhesive application, the process comprising:
measuring an amount of adhesive applied to a plurality of substrates by a pump; detecting a number of the substrates; determining an amount of adhesive applied per substrate; comparing the adhesive applied per substrate to a target value; and adjusting a pressure of the pump based on the comparison. 16. The medium of claim 15, wherein measuring the amount of adhesive applied includes detecting opening of a valve of a supply. 17. The medium of claim 15, wherein measuring the amount of adhesive applied includes detecting a flow rate of the adhesive with a flow sensor. 18. The medium of claim 17, wherein detecting the flow rate includes detecting the flow rate in a manifold. 19. The medium of claim 17, wherein detecting the flow rate includes detecting the flow rate in a hose in communication with an applicator. 20. The medium of claim 15, wherein detecting the number of the substrates includes detecting a number of the substrates on a conveyor belt passing a sensor. | 2,100 |
6,506 | 6,506 | 15,638,046 | 2,173 | A flexible layout system is disclosed herein that improves infinite scrolling capabilities and other animations in software calendars. In an implementation, a time period of a viewport in a user interface may change relative to a panel in a calendar. As the viewport changes, a mapping component informs other components of a new time period coming into view in the view port as a result of a scrolling event. The mapping component may also respond to requests from another component with layout information for the visual representation of the new time period (e.g. position and dimension). In this manner, the responsibility for determining layout information is encapsulated. | 1. A computing apparatus comprising:
one or more computer readable storage media; a processing system operatively coupled with the one or more computer readable storage media; and program instructions stored on the one or more computer readable storage media and comprising a plurality of components of an application for animating a calendar in a user interface to the application; wherein the plurality of components comprises a mapping component that, when executed by the processing system as a time period of a viewport of the user interface changes relative to a panel in the calendar, directs the processing system to at least:
inform other components of the plurality of components of a new time period coming into view in the view port as a result of a navigation event in the user interface;
receive requests from at least one other component of the plurality of components for layout information mapped to the new time period; and
respond to the requests with the layout information for displaying a visual representation of the new time period in the panel. 2. The computing apparatus of claim 1 wherein the one other component of the plurality of components comprises a layout component that directs the processing system to submit the requests for the layout information to the mapping component and directs the processing system to instruct a panel build component to build the visual representation of the new time period in accordance with the layout information. 3. The computing apparatus of claim 2 wherein the other components of the plurality of components comprise a data loader component that directs the processing system to produce new view data to be expressed through controls in the visual representation of the new time period. 4. The computing apparatus of claim 3 wherein the other components of the plurality of components further comprise a synchronizer component that directs the processing system to synchronize the new view data with the controls and to pass the new time period to the layout component. 5. The computing apparatus of claim 4 wherein the layout information comprises a position for each of the controls in the panel and dimensions for each of the controls. 6. The computing apparatus of claim 1 wherein the mapping component further directs the processing system to maintain an anchor date and time that represents a date and time of a reference position in the view port. 7. The computing apparatus of claim 6 wherein the mapping component further directs the processing system to derive the new time period from the anchor date and time. 8. The computing apparatus of claim 1 wherein the navigation event comprises switching view modes while scrolling through the calendar in the user interface. 9. One or more computer readable storage media having program instructions stored thereon comprising a plurality of components of an application for animating a calendar in a user interface to the application;
wherein the plurality of components comprises a mapping component that, when executed by a processing system as a time period of a viewport of the user interface changes relative to a panel in the calendar, directs the processing system to at least:
inform other components of the plurality of components of a new time period coming into view in the view port as a result of a navigation event in the user interface;
receive requests from at least one other component of the plurality of components for layout information mapped to the new time period; and
respond to the requests with the layout information for displaying a visual representation of the new time period in the panel. 10. The one or more computer readable storage media of claim 9 wherein the one other component of the plurality of components comprises a layout component that directs the processing system to submit the requests for the layout information to the mapping component and directs the processing system to instruct a panel build component to build the visual representation of the new time period in accordance with the layout information. 11. The one or more computer readable storage media of claim 10 wherein the other components of the plurality of components comprise a data loader component that directs the processing system to produce new view data to be expressed through controls in the visual representation of the new time period. 12. The one or more computer readable storage media of claim 11 wherein the other components of the plurality of components further comprise a synchronizer component that directs the processing system to synchronize the new view data with the controls and to pass the new time period to the layout component. 13. The one or more computer readable storage media of claim 12 wherein the layout information comprises a position for each of the controls in the panel and dimensions for each of the controls. 14. The one or more computer readable storage media of claim 9 wherein the mapping component further directs the processing system to maintain an anchor date and time that represents a date and time of a reference position in the view port. 15. The one or more computer readable storage media us of claim 14 wherein the mapping component further directs the processing system to derive the new time period from the anchor date and time. 16. The one or more computer readable storage media of claim 9 wherein the navigation event comprises scrolling through the calendar in the user interface. 17. A method for animating a calendar in a user interface to an application as a time period of a viewport of the user interface changes relative to a panel in the calendar, the method comprising:
in a mapping component of the application, informing at least a view component of the application and a synchronizer component of the application of a new time period coming into view in the view port as a result of a scrolling event in the user interface; in the mapping component, receiving requests from at least a layout component of the application for layout information mapped to the new time period; and in the mapping component, responding to the requests with the layout information for displaying a visual representation of the new time period in the panel. 18. The method of claim 17 further comprising in the layout component submitting the requests for the layout information to the mapping component and requesting a surface system to handle the visual representation of the new time period in accordance with the layout information. 19. The method of claim 18 further comprising:
in a view component, producing new view data to be expressed through controls in the visual representation of the new time period; and
in a synchronizer component, synchronizing the new view data with the controls and passing the new time period to the layout component. 20. The method of claim 19 wherein the layout information comprises a position for each of the controls in the panel and dimensions for each of the controls and wherein the method further comprising:
in the mapping component, maintaining an anchor date and time that represents a date and time of a reference position in the view port; and
in the mapping component, deriving the new time period from the anchor date and time. | A flexible layout system is disclosed herein that improves infinite scrolling capabilities and other animations in software calendars. In an implementation, a time period of a viewport in a user interface may change relative to a panel in a calendar. As the viewport changes, a mapping component informs other components of a new time period coming into view in the view port as a result of a scrolling event. The mapping component may also respond to requests from another component with layout information for the visual representation of the new time period (e.g. position and dimension). In this manner, the responsibility for determining layout information is encapsulated.1. A computing apparatus comprising:
one or more computer readable storage media; a processing system operatively coupled with the one or more computer readable storage media; and program instructions stored on the one or more computer readable storage media and comprising a plurality of components of an application for animating a calendar in a user interface to the application; wherein the plurality of components comprises a mapping component that, when executed by the processing system as a time period of a viewport of the user interface changes relative to a panel in the calendar, directs the processing system to at least:
inform other components of the plurality of components of a new time period coming into view in the view port as a result of a navigation event in the user interface;
receive requests from at least one other component of the plurality of components for layout information mapped to the new time period; and
respond to the requests with the layout information for displaying a visual representation of the new time period in the panel. 2. The computing apparatus of claim 1 wherein the one other component of the plurality of components comprises a layout component that directs the processing system to submit the requests for the layout information to the mapping component and directs the processing system to instruct a panel build component to build the visual representation of the new time period in accordance with the layout information. 3. The computing apparatus of claim 2 wherein the other components of the plurality of components comprise a data loader component that directs the processing system to produce new view data to be expressed through controls in the visual representation of the new time period. 4. The computing apparatus of claim 3 wherein the other components of the plurality of components further comprise a synchronizer component that directs the processing system to synchronize the new view data with the controls and to pass the new time period to the layout component. 5. The computing apparatus of claim 4 wherein the layout information comprises a position for each of the controls in the panel and dimensions for each of the controls. 6. The computing apparatus of claim 1 wherein the mapping component further directs the processing system to maintain an anchor date and time that represents a date and time of a reference position in the view port. 7. The computing apparatus of claim 6 wherein the mapping component further directs the processing system to derive the new time period from the anchor date and time. 8. The computing apparatus of claim 1 wherein the navigation event comprises switching view modes while scrolling through the calendar in the user interface. 9. One or more computer readable storage media having program instructions stored thereon comprising a plurality of components of an application for animating a calendar in a user interface to the application;
wherein the plurality of components comprises a mapping component that, when executed by a processing system as a time period of a viewport of the user interface changes relative to a panel in the calendar, directs the processing system to at least:
inform other components of the plurality of components of a new time period coming into view in the view port as a result of a navigation event in the user interface;
receive requests from at least one other component of the plurality of components for layout information mapped to the new time period; and
respond to the requests with the layout information for displaying a visual representation of the new time period in the panel. 10. The one or more computer readable storage media of claim 9 wherein the one other component of the plurality of components comprises a layout component that directs the processing system to submit the requests for the layout information to the mapping component and directs the processing system to instruct a panel build component to build the visual representation of the new time period in accordance with the layout information. 11. The one or more computer readable storage media of claim 10 wherein the other components of the plurality of components comprise a data loader component that directs the processing system to produce new view data to be expressed through controls in the visual representation of the new time period. 12. The one or more computer readable storage media of claim 11 wherein the other components of the plurality of components further comprise a synchronizer component that directs the processing system to synchronize the new view data with the controls and to pass the new time period to the layout component. 13. The one or more computer readable storage media of claim 12 wherein the layout information comprises a position for each of the controls in the panel and dimensions for each of the controls. 14. The one or more computer readable storage media of claim 9 wherein the mapping component further directs the processing system to maintain an anchor date and time that represents a date and time of a reference position in the view port. 15. The one or more computer readable storage media us of claim 14 wherein the mapping component further directs the processing system to derive the new time period from the anchor date and time. 16. The one or more computer readable storage media of claim 9 wherein the navigation event comprises scrolling through the calendar in the user interface. 17. A method for animating a calendar in a user interface to an application as a time period of a viewport of the user interface changes relative to a panel in the calendar, the method comprising:
in a mapping component of the application, informing at least a view component of the application and a synchronizer component of the application of a new time period coming into view in the view port as a result of a scrolling event in the user interface; in the mapping component, receiving requests from at least a layout component of the application for layout information mapped to the new time period; and in the mapping component, responding to the requests with the layout information for displaying a visual representation of the new time period in the panel. 18. The method of claim 17 further comprising in the layout component submitting the requests for the layout information to the mapping component and requesting a surface system to handle the visual representation of the new time period in accordance with the layout information. 19. The method of claim 18 further comprising:
in a view component, producing new view data to be expressed through controls in the visual representation of the new time period; and
in a synchronizer component, synchronizing the new view data with the controls and passing the new time period to the layout component. 20. The method of claim 19 wherein the layout information comprises a position for each of the controls in the panel and dimensions for each of the controls and wherein the method further comprising:
in the mapping component, maintaining an anchor date and time that represents a date and time of a reference position in the view port; and
in the mapping component, deriving the new time period from the anchor date and time. | 2,100 |
6,507 | 6,507 | 15,857,948 | 2,163 | Embodiments of the present invention provide a method, system and computer program product for social media influencer orchestration. In an embodiment of the invention, a method for social media influencer orchestration includes detecting a social media posting, such as a short burst message, an image or a comment upon an image, to a social media channel through a computing device by a subject end user, monitoring the social media channel to determine an impact of the social media posting and querying a rules base with the determined impact to retrieve a recommendation corresponding to the determined impact. Thereafter, a prompt is rendered in the computing device with the recommendation. | 1. A method for social media influencer orchestration comprising:
detecting a social media posting to a social media channel through a computing device by a subject end user; monitoring the social media channel to determine an impact of the social media posting; querying a rules base with the determined impact to retrieve a recommendation corresponding to the determined impact; and, rendering a prompt in the computing device with the recommendation. 2. The method of claim 1, wherein the social media posting is a posting selected from the group consisting of a short burst message, an image, a video, a comment on an image and an image. 3. The method of claim 1, wherein the impact is a sentiment of one or more viewers of the social media posting computed based upon a textual analysis of a reply to the social media posting in the social media channel. 4. The method of claim 1, wherein the impact is a tone of the social media posting computed based upon a textual analysis of the social media posting. 5. The method of claim 1, wherein the impact is a quantified number of interactions with the social media posting in the social media channel. 6. The method of claim 1, wherein the recommendation is a modification of the social media posting replacing words associated with one emotion with words associated with a different emotion. 7. A social media data processing system adapted for social media influencer orchestration, the system comprising:
a host computing device with memory and at least one processor and a network adapter transmitting data over and receiving data from a communications link to the global Internet; at least one social media channel application executing in the memory of the device, the application comprising a configuration to receive data input in a user interface to the application and to post the data input as a social media posting to a corresponding social media channel disposed accessible over the communications link to the global Internet; and, a social media influencer module coupled to the at least one social media channel application, the module comprising program code enabled during execution in the device to detect a social media posting to the social media channel in the application, to monitor the social media channel to determine an impact of the social media posting, to query a rules base with the determined impact to retrieve a recommendation corresponding to the determined impact and to render a prompt in a display of the device with the recommendation. 8. The system of claim 7, wherein the social media posting is a posting selected from the group consisting of a short burst message, an image, a video, a comment on an image and an image. 9. The system of claim 7, wherein the impact is a sentiment of one or more viewers of the social media posting computed based upon a textual analysis of a reply to the social media posting in the social media channel. 10. The system of claim 7, wherein the impact is a tone of the social media posting computed based upon a textual analysis of the social media posting. 11. The system of claim 7, wherein the impact is a quantified number of interactions with the social media posting in the social media channel. 12. The system of claim 7, wherein the recommendation is a modification of the social media posting replacing words associated with one emotion with words associated with a different emotion. 13. The system of claim 7, wherein the rules base is disposed over the global Internet in a remote repository and accessed by the program code of the module by way of the communications link. 14. The system of claim 7, wherein the social media channel is monitored remotely from the device over the global Internet with the determined impact transmitted to the device through the communications link. 15. A computer program product for social media influencer orchestration, the computer program product including a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a device to cause the device to perform a method including:
detecting a social media posting to a social media channel through a computing device by a subject end user; monitoring the social media channel to determine an impact of the social media posting; querying a rules base with the determined impact to retrieve a recommendation corresponding to the determined impact; and, rendering a prompt in the computing device with the recommendation. 16. The computer program product of claim 15, wherein the social media posting is a posting selected from the group consisting of a short burst message, an image, a video, a comment on an image and an image. 17. The computer program product of claim 15, wherein the impact is a sentiment of one or more viewers of the social media posting computed based upon a textual analysis of a reply to the social media posting in the social media channel. 18. The computer program product of claim 15, wherein the impact is a tone of the social media posting computed based upon a textual analysis of the social media posting. 19. The computer program product of claim 15, wherein the impact is a quantified number of interactions with the social media posting in the social media channel. 20. The computer program product of claim 15, wherein the recommendation is a modification of the social media posting replacing words associated one emotion with words associated with a different emotion. | Embodiments of the present invention provide a method, system and computer program product for social media influencer orchestration. In an embodiment of the invention, a method for social media influencer orchestration includes detecting a social media posting, such as a short burst message, an image or a comment upon an image, to a social media channel through a computing device by a subject end user, monitoring the social media channel to determine an impact of the social media posting and querying a rules base with the determined impact to retrieve a recommendation corresponding to the determined impact. Thereafter, a prompt is rendered in the computing device with the recommendation.1. A method for social media influencer orchestration comprising:
detecting a social media posting to a social media channel through a computing device by a subject end user; monitoring the social media channel to determine an impact of the social media posting; querying a rules base with the determined impact to retrieve a recommendation corresponding to the determined impact; and, rendering a prompt in the computing device with the recommendation. 2. The method of claim 1, wherein the social media posting is a posting selected from the group consisting of a short burst message, an image, a video, a comment on an image and an image. 3. The method of claim 1, wherein the impact is a sentiment of one or more viewers of the social media posting computed based upon a textual analysis of a reply to the social media posting in the social media channel. 4. The method of claim 1, wherein the impact is a tone of the social media posting computed based upon a textual analysis of the social media posting. 5. The method of claim 1, wherein the impact is a quantified number of interactions with the social media posting in the social media channel. 6. The method of claim 1, wherein the recommendation is a modification of the social media posting replacing words associated with one emotion with words associated with a different emotion. 7. A social media data processing system adapted for social media influencer orchestration, the system comprising:
a host computing device with memory and at least one processor and a network adapter transmitting data over and receiving data from a communications link to the global Internet; at least one social media channel application executing in the memory of the device, the application comprising a configuration to receive data input in a user interface to the application and to post the data input as a social media posting to a corresponding social media channel disposed accessible over the communications link to the global Internet; and, a social media influencer module coupled to the at least one social media channel application, the module comprising program code enabled during execution in the device to detect a social media posting to the social media channel in the application, to monitor the social media channel to determine an impact of the social media posting, to query a rules base with the determined impact to retrieve a recommendation corresponding to the determined impact and to render a prompt in a display of the device with the recommendation. 8. The system of claim 7, wherein the social media posting is a posting selected from the group consisting of a short burst message, an image, a video, a comment on an image and an image. 9. The system of claim 7, wherein the impact is a sentiment of one or more viewers of the social media posting computed based upon a textual analysis of a reply to the social media posting in the social media channel. 10. The system of claim 7, wherein the impact is a tone of the social media posting computed based upon a textual analysis of the social media posting. 11. The system of claim 7, wherein the impact is a quantified number of interactions with the social media posting in the social media channel. 12. The system of claim 7, wherein the recommendation is a modification of the social media posting replacing words associated with one emotion with words associated with a different emotion. 13. The system of claim 7, wherein the rules base is disposed over the global Internet in a remote repository and accessed by the program code of the module by way of the communications link. 14. The system of claim 7, wherein the social media channel is monitored remotely from the device over the global Internet with the determined impact transmitted to the device through the communications link. 15. A computer program product for social media influencer orchestration, the computer program product including a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a device to cause the device to perform a method including:
detecting a social media posting to a social media channel through a computing device by a subject end user; monitoring the social media channel to determine an impact of the social media posting; querying a rules base with the determined impact to retrieve a recommendation corresponding to the determined impact; and, rendering a prompt in the computing device with the recommendation. 16. The computer program product of claim 15, wherein the social media posting is a posting selected from the group consisting of a short burst message, an image, a video, a comment on an image and an image. 17. The computer program product of claim 15, wherein the impact is a sentiment of one or more viewers of the social media posting computed based upon a textual analysis of a reply to the social media posting in the social media channel. 18. The computer program product of claim 15, wherein the impact is a tone of the social media posting computed based upon a textual analysis of the social media posting. 19. The computer program product of claim 15, wherein the impact is a quantified number of interactions with the social media posting in the social media channel. 20. The computer program product of claim 15, wherein the recommendation is a modification of the social media posting replacing words associated one emotion with words associated with a different emotion. | 2,100 |
6,508 | 6,508 | 16,048,884 | 2,183 | A data processing system includes multiple processing units all having access to a shared memory. A processing unit includes a processor core that executes memory access instructions including a fronting load instruction, wherein execution of the fronting load instruction generates a load request that specifies a load target address. The processing unit also includes reservation logic that records addresses in the shared memory for which the processor core has obtained reservations. In addition, the processing unit includes a read-claim state machine that, responsive to receipt of the load request and based on an address match for the load target address in the reservation logic, protects the load target address against access by any conflicting memory access request during a protection interval following servicing of the load request. | 1. A processing unit for a data processing system including multiple processing units all having access to a shared memory, said processing unit comprising:
a processor core that executes memory access instructions including a fronting load instruction, wherein execution of the fronting load instruction generates a load request that specifies a load target address; reservation logic that records addresses in the shared memory for which the processor core has obtained reservations; and a read-claim state machine that, responsive to receipt of the load request and based on an address match for the load target address in the reservation logic, protects the load target address against access by any conflicting memory access request during a protection interval following servicing of the load request. 2. The processing unit of claim 1, wherein:
the fronting load instruction is executed by a given hardware thread; the read-claim state machine, responsive to a matching load-reserve request of the given hardware thread that specifies the load target address, ends the protection interval. 3. The processing unit of claim 2, wherein:
the processing unit includes a plurality of read-claim state machines including the read-claim state machine; and the read-claim state machine remains in a busy state following servicing of the load request and services the load-reserve request. 4. The processing unit of claim 2, wherein:
the processor core, following execution of the fronting load instruction, executes in the given hardware thread a load-reserve instruction that generates the load-reserve request; and the reservation logic, responsive to the load-reserve request, establishes a reservation for the load target address. 5. The processing unit of claim 1, and further comprising a timer that determines a maximum duration of the protection interval. 6. The processing unit of claim 1, wherein the reservation logic includes a plurality of reservation registers that record addresses for which hardware threads of the processor core hold reservations. 7. The processing unit of claim 1, wherein the reservation logic further includes a history buffer that records addresses for which hardware threads of the processor core formerly held reservations. 8. A data processing system, comprising:
the multiple processing units, including the processing unit of claim 1; the shared memory; and a system interconnect communicatively coupling the shared memory and the multiple processing units. 9. A method of data processing in a processing unit of a data processing system including multiple processing units all having access to a shared memory, said method comprising:
a processor core executing memory access instructions including a fronting load instruction, wherein execution of the fronting load instruction generates a load request that specifies a load target address; recording, in reservation logic, addresses in the shared memory for which the processor core has obtained reservations; and responsive to receipt of the load request and based on an address match for the load target address in the reservation logic, a read-claim state machine protecting the load target address against access by any conflicting memory access request during a protection interval following servicing of the load request. 10. The method of claim 9, wherein:
the fronting load instruction is executed by a given hardware thread; the method further comprises the read-claim state machine, responsive to a matching load-reserve request of the given hardware thread that specifies the load target address, ending the protection interval. 11. The method of claim 10, wherein:
the processing unit includes a plurality of read-claim state machines including the read-claim state machine; and the method further comprising the read-claim state machine remaining in a busy state following servicing of the load request and servicing the load-reserve request. 12. The method of claim 10, and further comprising:
the processor core, following execution of the fronting load instruction, executing in the given hardware thread a load-reserve instruction that generates the load-reserve request; and the reservation logic, responsive to the load-reserve request, establishing a reservation for the load target address. 13. The method of claim 9, and further comprising determining a maximum duration of the protection interval by reference to a timer. 14. The method of claim 9, wherein the recording includes the reservation logic recording addresses for which hardware threads of the processor core hold reservations in a plurality of reservation registers. 15. The method of claim 9, wherein the recording includes recording in a history buffer addresses for which hardware threads of the processor core formerly held reservations. 16. A design structure tangibly embodied in a machine-readable storage device for designing, manufacturing, or testing an integrated circuit, the design structure comprising:
a processing unit for a multiprocessor data processing system including a shared memory, the processing unit including:
a processor core that executes memory access instructions including a fronting load instruction, wherein execution of the fronting load instruction generates a load request that specifies a load target address;
reservation logic that records addresses in the shared memory for which the processor core has obtained reservations; and
a read-claim state machine that, responsive to receipt of the load request and based on an address match for the load target address in the reservation logic, protects the load target address against access by any conflicting memory access request during a protection interval following servicing of the load request. 17. The design structure of claim 16, wherein:
the fronting load instruction is executed by a given hardware thread; the read-claim state machine, responsive to a matching load-reserve request of the given hardware thread that specifies the load target address, ends the protection interval. 18. The design structure of claim 17, wherein:
the processing unit includes a plurality of read-claim state machines including the read-claim state machine; and the read-claim state machine remains in a busy state following servicing of the load request and services the load-reserve request. 19. The design structure of claim 17, wherein:
the processor core, following execution of the fronting load instruction, executes in the given hardware thread a load-reserve instruction that generates the load-reserve request; and the reservation logic, responsive to the load-reserve request, establishes a reservation for the load target address. 20. The design structure of claim 16, wherein the reservation logic further includes a history buffer that records addresses for which hardware threads of the processor core formerly held reservations. | A data processing system includes multiple processing units all having access to a shared memory. A processing unit includes a processor core that executes memory access instructions including a fronting load instruction, wherein execution of the fronting load instruction generates a load request that specifies a load target address. The processing unit also includes reservation logic that records addresses in the shared memory for which the processor core has obtained reservations. In addition, the processing unit includes a read-claim state machine that, responsive to receipt of the load request and based on an address match for the load target address in the reservation logic, protects the load target address against access by any conflicting memory access request during a protection interval following servicing of the load request.1. A processing unit for a data processing system including multiple processing units all having access to a shared memory, said processing unit comprising:
a processor core that executes memory access instructions including a fronting load instruction, wherein execution of the fronting load instruction generates a load request that specifies a load target address; reservation logic that records addresses in the shared memory for which the processor core has obtained reservations; and a read-claim state machine that, responsive to receipt of the load request and based on an address match for the load target address in the reservation logic, protects the load target address against access by any conflicting memory access request during a protection interval following servicing of the load request. 2. The processing unit of claim 1, wherein:
the fronting load instruction is executed by a given hardware thread; the read-claim state machine, responsive to a matching load-reserve request of the given hardware thread that specifies the load target address, ends the protection interval. 3. The processing unit of claim 2, wherein:
the processing unit includes a plurality of read-claim state machines including the read-claim state machine; and the read-claim state machine remains in a busy state following servicing of the load request and services the load-reserve request. 4. The processing unit of claim 2, wherein:
the processor core, following execution of the fronting load instruction, executes in the given hardware thread a load-reserve instruction that generates the load-reserve request; and the reservation logic, responsive to the load-reserve request, establishes a reservation for the load target address. 5. The processing unit of claim 1, and further comprising a timer that determines a maximum duration of the protection interval. 6. The processing unit of claim 1, wherein the reservation logic includes a plurality of reservation registers that record addresses for which hardware threads of the processor core hold reservations. 7. The processing unit of claim 1, wherein the reservation logic further includes a history buffer that records addresses for which hardware threads of the processor core formerly held reservations. 8. A data processing system, comprising:
the multiple processing units, including the processing unit of claim 1; the shared memory; and a system interconnect communicatively coupling the shared memory and the multiple processing units. 9. A method of data processing in a processing unit of a data processing system including multiple processing units all having access to a shared memory, said method comprising:
a processor core executing memory access instructions including a fronting load instruction, wherein execution of the fronting load instruction generates a load request that specifies a load target address; recording, in reservation logic, addresses in the shared memory for which the processor core has obtained reservations; and responsive to receipt of the load request and based on an address match for the load target address in the reservation logic, a read-claim state machine protecting the load target address against access by any conflicting memory access request during a protection interval following servicing of the load request. 10. The method of claim 9, wherein:
the fronting load instruction is executed by a given hardware thread; the method further comprises the read-claim state machine, responsive to a matching load-reserve request of the given hardware thread that specifies the load target address, ending the protection interval. 11. The method of claim 10, wherein:
the processing unit includes a plurality of read-claim state machines including the read-claim state machine; and the method further comprising the read-claim state machine remaining in a busy state following servicing of the load request and servicing the load-reserve request. 12. The method of claim 10, and further comprising:
the processor core, following execution of the fronting load instruction, executing in the given hardware thread a load-reserve instruction that generates the load-reserve request; and the reservation logic, responsive to the load-reserve request, establishing a reservation for the load target address. 13. The method of claim 9, and further comprising determining a maximum duration of the protection interval by reference to a timer. 14. The method of claim 9, wherein the recording includes the reservation logic recording addresses for which hardware threads of the processor core hold reservations in a plurality of reservation registers. 15. The method of claim 9, wherein the recording includes recording in a history buffer addresses for which hardware threads of the processor core formerly held reservations. 16. A design structure tangibly embodied in a machine-readable storage device for designing, manufacturing, or testing an integrated circuit, the design structure comprising:
a processing unit for a multiprocessor data processing system including a shared memory, the processing unit including:
a processor core that executes memory access instructions including a fronting load instruction, wherein execution of the fronting load instruction generates a load request that specifies a load target address;
reservation logic that records addresses in the shared memory for which the processor core has obtained reservations; and
a read-claim state machine that, responsive to receipt of the load request and based on an address match for the load target address in the reservation logic, protects the load target address against access by any conflicting memory access request during a protection interval following servicing of the load request. 17. The design structure of claim 16, wherein:
the fronting load instruction is executed by a given hardware thread; the read-claim state machine, responsive to a matching load-reserve request of the given hardware thread that specifies the load target address, ends the protection interval. 18. The design structure of claim 17, wherein:
the processing unit includes a plurality of read-claim state machines including the read-claim state machine; and the read-claim state machine remains in a busy state following servicing of the load request and services the load-reserve request. 19. The design structure of claim 17, wherein:
the processor core, following execution of the fronting load instruction, executes in the given hardware thread a load-reserve instruction that generates the load-reserve request; and the reservation logic, responsive to the load-reserve request, establishes a reservation for the load target address. 20. The design structure of claim 16, wherein the reservation logic further includes a history buffer that records addresses for which hardware threads of the processor core formerly held reservations. | 2,100 |
6,509 | 6,509 | 13,656,225 | 2,174 | A method for manual intervention in a dialing process includes maintaining a list of records containing phone numbers in a database stored on a computer readable storage medium, receiving at a computer and from the user a click for each of the records within the list of records in the database stored on the computer readable storage medium, and storing on a computer readable storage medium a record of the click, an identity of the user performing the click, and an association between the click and one of the records within the list of records. For each click, the method provides for electronically communicating the corresponding phone number of one of the records within the list to a telecommunications system for dialing the phone number. The method may further include dialing the phone number using the telecommunications system. | 1. A method for manual intervention in a dialing process, the method comprising:
(a) maintaining a list of records containing phone numbers in a database stored on a computer readable storage medium; (b) receiving at a computer and from the user a click for each of the records within the list of records in the database stored on the computer readable storage medium; (c) storing on a computer readable storage medium a record of the click, an identity of the user performing the click, and an association between the click and one of the records within the list of records; (d) for each click electronically communicating the corresponding phone number of one of the records within the list to a telecommunications system for dialing the phone number. 2. The method of claim 1 further comprising dialing the phone number using the telecommunications system. 3. The method of claim 2 further comprising displaying an icon to the user and wherein the click for each of the records within the list of records is a click on the icon. 4. The method of claim 3 wherein the click is performed by positioning a mouse pointer on the click and depressing a button of a mouse. 5. The method of claim 4 wherein the phone numbers are phone numbers for unauthorized cell phones. 6. The method of claim 1 further comprising determining if phone numbers are unauthorized cell phone numbers, for phone numbers which are unauthorized cell phone numbers, placing the phone numbers in the list of records containing the phone numbers, and for phone numbers which are not unauthorized cell phone numbers sending the phone numbers directly to the telecommunications system. 7. The method of claim 1 further comprising providing a cloud-based service and providing a manual clicker application to the user through the cloud-based server wherein the cloud-based service provides for performing steps (a)-(d). 8. The method of claim 1 further comprising displaying to a user a number of clicks performed with the list. 9. The method of claim 8 further comprising displaying a number of clicks remaining to be performed with the list. 10. The method of claim 1 further comprising limiting the clicks to a maximum number of clicks. 11. A method for providing a cloud-based service to provide for manual intervention in a dialing process, the method comprising:
maintaining a list of records containing unauthorized phone numbers in a database stored on a computer readable storage medium; providing access to a manual clicker application through a server configured to access the database; providing a user interface to a user of the manual clicker application, the user interface configured to receive clicks from a user; receiving clicks from the user targeted at an icon of the user interface; storing within the database a record of each click from a user and associating each click from the user with one of the records and a corresponding unauthorized phone number; electronically communicating to a telecommunications system each of the corresponding unauthorized phone numbers after storing the record of each click. 12. The method of claim 11 further comprising dialing each of the corresponding unauthorized phone numbers using the telecommunications system. 13. The method of claim 11 wherein the clicks are performed by a user using a mouse. 14. The method of claim 11 further comprising displaying to a user a number of clicks performed with the list of records. 15. The method of claim 14 further comprising displaying to a user a number of clicks remaining to be performed with the list of records. 16. The method of claim 11 further comprising notifying the user when there has been a click for every one of the records in the list of records. 17. The method of claim 11 further comprising receiving a selection of the list by the user through the user interface. 18. The method of claim 11 further comprising determining if phone numbers are unauthorized cell phone numbers, for phone numbers which are unauthorized cell phone numbers, placing the unauthorized cell phone numbers in the list of records and for phone numbers which are not unauthorized cell phone numbers sending the phone numbers directly to the telecommunications system. | A method for manual intervention in a dialing process includes maintaining a list of records containing phone numbers in a database stored on a computer readable storage medium, receiving at a computer and from the user a click for each of the records within the list of records in the database stored on the computer readable storage medium, and storing on a computer readable storage medium a record of the click, an identity of the user performing the click, and an association between the click and one of the records within the list of records. For each click, the method provides for electronically communicating the corresponding phone number of one of the records within the list to a telecommunications system for dialing the phone number. The method may further include dialing the phone number using the telecommunications system.1. A method for manual intervention in a dialing process, the method comprising:
(a) maintaining a list of records containing phone numbers in a database stored on a computer readable storage medium; (b) receiving at a computer and from the user a click for each of the records within the list of records in the database stored on the computer readable storage medium; (c) storing on a computer readable storage medium a record of the click, an identity of the user performing the click, and an association between the click and one of the records within the list of records; (d) for each click electronically communicating the corresponding phone number of one of the records within the list to a telecommunications system for dialing the phone number. 2. The method of claim 1 further comprising dialing the phone number using the telecommunications system. 3. The method of claim 2 further comprising displaying an icon to the user and wherein the click for each of the records within the list of records is a click on the icon. 4. The method of claim 3 wherein the click is performed by positioning a mouse pointer on the click and depressing a button of a mouse. 5. The method of claim 4 wherein the phone numbers are phone numbers for unauthorized cell phones. 6. The method of claim 1 further comprising determining if phone numbers are unauthorized cell phone numbers, for phone numbers which are unauthorized cell phone numbers, placing the phone numbers in the list of records containing the phone numbers, and for phone numbers which are not unauthorized cell phone numbers sending the phone numbers directly to the telecommunications system. 7. The method of claim 1 further comprising providing a cloud-based service and providing a manual clicker application to the user through the cloud-based server wherein the cloud-based service provides for performing steps (a)-(d). 8. The method of claim 1 further comprising displaying to a user a number of clicks performed with the list. 9. The method of claim 8 further comprising displaying a number of clicks remaining to be performed with the list. 10. The method of claim 1 further comprising limiting the clicks to a maximum number of clicks. 11. A method for providing a cloud-based service to provide for manual intervention in a dialing process, the method comprising:
maintaining a list of records containing unauthorized phone numbers in a database stored on a computer readable storage medium; providing access to a manual clicker application through a server configured to access the database; providing a user interface to a user of the manual clicker application, the user interface configured to receive clicks from a user; receiving clicks from the user targeted at an icon of the user interface; storing within the database a record of each click from a user and associating each click from the user with one of the records and a corresponding unauthorized phone number; electronically communicating to a telecommunications system each of the corresponding unauthorized phone numbers after storing the record of each click. 12. The method of claim 11 further comprising dialing each of the corresponding unauthorized phone numbers using the telecommunications system. 13. The method of claim 11 wherein the clicks are performed by a user using a mouse. 14. The method of claim 11 further comprising displaying to a user a number of clicks performed with the list of records. 15. The method of claim 14 further comprising displaying to a user a number of clicks remaining to be performed with the list of records. 16. The method of claim 11 further comprising notifying the user when there has been a click for every one of the records in the list of records. 17. The method of claim 11 further comprising receiving a selection of the list by the user through the user interface. 18. The method of claim 11 further comprising determining if phone numbers are unauthorized cell phone numbers, for phone numbers which are unauthorized cell phone numbers, placing the unauthorized cell phone numbers in the list of records and for phone numbers which are not unauthorized cell phone numbers sending the phone numbers directly to the telecommunications system. | 2,100 |
6,510 | 6,510 | 16,007,672 | 2,196 | An aerosol delivery device comprising a control component and a communication interface is provided. The control component controls operation of at least one functional element of the aerosol delivery device in instances in which a flow of air through at least a portion of the at least one housing is detected. The communication interface is coupled to the control component and enables wireless communication. The control component further detects a predefined trigger, and automatically in response thereto, causes the communication interface to broadcast availability of the aerosol delivery device for connection with a capable wireless device. The predefined trigger includes at least one instance in which the flow of air is detected, and excludes user-actuation of any button on the aerosol delivery device. | 1. An aerosol delivery device comprising:
at least one housing; and contained within the at least one housing, a control component configured to control operation of at least one functional element of the aerosol delivery device in instances in which a flow of air through at least a portion of the at least one housing is detected; and a communication interface coupled to the control component and configured to enable wireless communication, wherein the control component is further configured to detect a predefined trigger, and automatically in response thereto, cause the communication interface to broadcast availability of the aerosol delivery device for connection with a capable wireless device, the predefined trigger including at least one instance in which the flow of air is detected, and excluding user-actuation of any button on the aerosol delivery device. 2. The aerosol delivery device of claim 1, wherein the trigger includes a predefined length of time between at least two instances in which the flow of air is detected. 3. The aerosol delivery device of claim 2, wherein the predefined length of time is no more than approximately 1,250 milliseconds between the at least two instances in which the flow of air is detected. 4. The aerosol delivery device of claim 1, wherein the trigger includes a predefined duration of an instance in which the flow of air is detected. 5. The aerosol delivery device of claim 4, wherein the predefined duration is between approximately 70 and 750 milliseconds. 6. The aerosol delivery device of claim 1, wherein the trigger includes a predefined number of instances in which the flow of air is detected. 7. The aerosol delivery device of claim 1 comprising a control body including the at least one housing, control component and communication interface, the control body being coupleable to a charging component and a cartridge, wherein the trigger further includes coupling of the control body to the charging component or cartridge. 8. The aerosol delivery device of claim 7, wherein the trigger further includes coupling of the control body to the cartridge, and the at least one instance is the first instance in which the flow of air is detected after the coupling of the control body to the cartridge. 9. The aerosol delivery device of claim 1, wherein the communication interface is a Bluetooth communication interface, and
wherein the communication interface being caused to broadcast availability includes the Bluetooth communication interface being caused to transmit an advertisement that includes information for connecting the Bluetooth communication interface with a capable Bluetooth-enabled device, and in at least one instance, bond with the capable Bluetooth-enabled device upon connection. 10. The aerosol delivery device of claim 9 comprising a control body including the at least one housing, control component and Bluetooth communication interface,
wherein the trigger further includes coupling of the control body to a cartridge, and the at least one instance is the first instance in which the flow of air is detected after the coupling of the control body to the cartridge, and
wherein the Bluetooth communication interface being caused to transmit the advertisement includes being caused to transmit the advertisement for a length of time no longer than a predetermined length of time after the first instance, and thereafter cease transmission of the advertisement. 11. A method of operation of an aerosol delivery device, the method comprising at the aerosol delivery device:
a control component controlling operation of at least one functional element of the aerosol delivery device in instances in which a flow of air through at least a portion of the at least one housing is detected; a communication interface enabling wireless communication; and the control component further detecting a predefined trigger, and automatically in response thereto, causing the communication interface to broadcast availability of the aerosol delivery device for connection with a capable wireless device, the predefined trigger including at least one instance in which the flow of air is detected, and excluding user-actuation of any button on the aerosol delivery device. 12. The method of claim 11, wherein the trigger includes a predefined length of time between at least two instances in which the flow of air is detected. 13. The method of claim 12, wherein the predefined length of time is no more than approximately 1,250 milliseconds between the at least two instances in which the flow of air is detected. 14. The method of claim 11, wherein the trigger includes a predefined duration of an instance in which the flow of air is detected. 15. The method of claim 14, wherein the predefined duration is between approximately 70 and 750 milliseconds. 16. The method of claim 11, wherein the trigger includes a predefined number of instances in which the flow of air is detected. 17. The method of claim 11, wherein the aerosol delivery device comprises a control body coupleable to a charging component and a cartridge, and wherein the trigger further includes coupling of the control body to the charging component or cartridge. 18. The method of claim 17, wherein the trigger further includes coupling of the control body to the cartridge, and the at least one instance is the first instance in which the flow of air is detected after the coupling of the control body to the cartridge. 19. The method of claim 11, wherein the communication interface is a Bluetooth communication interface, and
wherein the communication interface broadcasting availability includes the Bluetooth communication interface transmitting an advertisement that includes information for connecting the Bluetooth communication interface with a capable Bluetooth-enabled device, and in at least one instance, bonding with the capable Bluetooth-enabled device upon connection. 20. The method of claim 19, wherein the aerosol delivery device comprises a control body including the control component and Bluetooth communication interface, wherein the trigger further includes coupling of the control body to a cartridge, and the at least one instance is the first instance in which the flow of air is detected after the coupling of the control body to the cartridge, and
wherein the Bluetooth communication interface transmitting the advertisement includes transmitting the advertisement for a length of time no longer than a predetermined length of time after the first instance, and thereafter cease transmission of the advertisement. | An aerosol delivery device comprising a control component and a communication interface is provided. The control component controls operation of at least one functional element of the aerosol delivery device in instances in which a flow of air through at least a portion of the at least one housing is detected. The communication interface is coupled to the control component and enables wireless communication. The control component further detects a predefined trigger, and automatically in response thereto, causes the communication interface to broadcast availability of the aerosol delivery device for connection with a capable wireless device. The predefined trigger includes at least one instance in which the flow of air is detected, and excludes user-actuation of any button on the aerosol delivery device.1. An aerosol delivery device comprising:
at least one housing; and contained within the at least one housing, a control component configured to control operation of at least one functional element of the aerosol delivery device in instances in which a flow of air through at least a portion of the at least one housing is detected; and a communication interface coupled to the control component and configured to enable wireless communication, wherein the control component is further configured to detect a predefined trigger, and automatically in response thereto, cause the communication interface to broadcast availability of the aerosol delivery device for connection with a capable wireless device, the predefined trigger including at least one instance in which the flow of air is detected, and excluding user-actuation of any button on the aerosol delivery device. 2. The aerosol delivery device of claim 1, wherein the trigger includes a predefined length of time between at least two instances in which the flow of air is detected. 3. The aerosol delivery device of claim 2, wherein the predefined length of time is no more than approximately 1,250 milliseconds between the at least two instances in which the flow of air is detected. 4. The aerosol delivery device of claim 1, wherein the trigger includes a predefined duration of an instance in which the flow of air is detected. 5. The aerosol delivery device of claim 4, wherein the predefined duration is between approximately 70 and 750 milliseconds. 6. The aerosol delivery device of claim 1, wherein the trigger includes a predefined number of instances in which the flow of air is detected. 7. The aerosol delivery device of claim 1 comprising a control body including the at least one housing, control component and communication interface, the control body being coupleable to a charging component and a cartridge, wherein the trigger further includes coupling of the control body to the charging component or cartridge. 8. The aerosol delivery device of claim 7, wherein the trigger further includes coupling of the control body to the cartridge, and the at least one instance is the first instance in which the flow of air is detected after the coupling of the control body to the cartridge. 9. The aerosol delivery device of claim 1, wherein the communication interface is a Bluetooth communication interface, and
wherein the communication interface being caused to broadcast availability includes the Bluetooth communication interface being caused to transmit an advertisement that includes information for connecting the Bluetooth communication interface with a capable Bluetooth-enabled device, and in at least one instance, bond with the capable Bluetooth-enabled device upon connection. 10. The aerosol delivery device of claim 9 comprising a control body including the at least one housing, control component and Bluetooth communication interface,
wherein the trigger further includes coupling of the control body to a cartridge, and the at least one instance is the first instance in which the flow of air is detected after the coupling of the control body to the cartridge, and
wherein the Bluetooth communication interface being caused to transmit the advertisement includes being caused to transmit the advertisement for a length of time no longer than a predetermined length of time after the first instance, and thereafter cease transmission of the advertisement. 11. A method of operation of an aerosol delivery device, the method comprising at the aerosol delivery device:
a control component controlling operation of at least one functional element of the aerosol delivery device in instances in which a flow of air through at least a portion of the at least one housing is detected; a communication interface enabling wireless communication; and the control component further detecting a predefined trigger, and automatically in response thereto, causing the communication interface to broadcast availability of the aerosol delivery device for connection with a capable wireless device, the predefined trigger including at least one instance in which the flow of air is detected, and excluding user-actuation of any button on the aerosol delivery device. 12. The method of claim 11, wherein the trigger includes a predefined length of time between at least two instances in which the flow of air is detected. 13. The method of claim 12, wherein the predefined length of time is no more than approximately 1,250 milliseconds between the at least two instances in which the flow of air is detected. 14. The method of claim 11, wherein the trigger includes a predefined duration of an instance in which the flow of air is detected. 15. The method of claim 14, wherein the predefined duration is between approximately 70 and 750 milliseconds. 16. The method of claim 11, wherein the trigger includes a predefined number of instances in which the flow of air is detected. 17. The method of claim 11, wherein the aerosol delivery device comprises a control body coupleable to a charging component and a cartridge, and wherein the trigger further includes coupling of the control body to the charging component or cartridge. 18. The method of claim 17, wherein the trigger further includes coupling of the control body to the cartridge, and the at least one instance is the first instance in which the flow of air is detected after the coupling of the control body to the cartridge. 19. The method of claim 11, wherein the communication interface is a Bluetooth communication interface, and
wherein the communication interface broadcasting availability includes the Bluetooth communication interface transmitting an advertisement that includes information for connecting the Bluetooth communication interface with a capable Bluetooth-enabled device, and in at least one instance, bonding with the capable Bluetooth-enabled device upon connection. 20. The method of claim 19, wherein the aerosol delivery device comprises a control body including the control component and Bluetooth communication interface, wherein the trigger further includes coupling of the control body to a cartridge, and the at least one instance is the first instance in which the flow of air is detected after the coupling of the control body to the cartridge, and
wherein the Bluetooth communication interface transmitting the advertisement includes transmitting the advertisement for a length of time no longer than a predetermined length of time after the first instance, and thereafter cease transmission of the advertisement. | 2,100 |
6,511 | 6,511 | 14,997,447 | 2,124 | Systems and methods for forecasting the prominence of various attributes in a future subject matter area are disclosed. An attribute is determined based on inputs received by a computing system. A set of indicators is determined based on the attribute and features extracted from an existing document set. The prominence of the attribute in the existing document set is determined. A prominence estimate of the attribute in a future document set is determined. | 1. A prominence predictor system comprising one or more computing devices configured to:
extract an attribute from input received by the one or more computing devices; determine a prediction type based on the attribute; select a plurality of indicators based on the prediction type, each indicator comprising a set of features extracted from an existing document set comprising documents (i) semantically related to the attribute and (ii) published over a time interval beginning prior to and ending on or before a current date; model the prominence of the attribute in accordance with the plurality of indicators in the existing document set over the time interval using one or more statistical modeling techniques; estimate future prominence of the attribute based on the model in a future document set that do not currently exist relative to prominence of the attribute in the existing document set; and interactively present content relating to the estimated future prominence of the attribute by one or more output devices of the one or more computing devices. 2. The system of claim 1, wherein:
the attribute is associated with a feature extracted from at least one document of the existing document set, the attribute having a number of characteristics including an observed count of occurrences of the attribute in the existing document set, and the prediction type comprises a predicted count of occurrences of the attribute in the future document set based at least in part on the observed count of occurrences of the attribute in the existing document set. 3. The system of claim 1, wherein the set of indicators includes a subset of observable indicators having observed data extracted from the existing document set and a subset of derived indicators having derived data learned from the existing document set, the derived data being semantically determined from the observable data through the use of machine learning techniques. 4. The system of claim 1, wherein the one or more computing devices are further configured to determine a sentiment parameter for the attribute when the attribute is a term extracted from the documents of the existing document set, the sentiment parameter is indicative of whether an author of the term in the documents of the existing document set liked or disliked the attribute, the sentiment parameter being determined by analyzing each sentence containing the term in the existing set of documents. 5. The system of claim 1, wherein indicators of the set of indicators include static features having a single nominal value and dynamic features having data that changes as a function over time. 6. The system of claim 1, wherein to interactively present content further includes to determine the content output by the output devices based on the selected prediction type and the selected set of indicators used to determine the estimated future prominence, wherein the selected set of indicators are used to structure the content presented. 7. The system of claim 1, wherein the one or more computing devices are further configured to predict whether the estimated future prominence of the attribute will exceed a prominence threshold. 8. The system of claim 1, wherein the estimated future prominence includes data indicative of (i) the future prominence of the attribute over time and (ii) the future prominence of the attribute over a geospatial distribution. 9. The system of claim 1, wherein the prediction types include at least one of the following: a number of occurrences of the attribute in the future document set, a number of citations in the future document set to a document in the existing document set, a geospatial distribution of occurrences of the attribute in the future document set, a number of times the attribute is published in the future document set, and/or the number of patents issued in the future document set. 10. The system of claim 1, wherein the one or more computing devices are further configured to:
generate a geospatial model by dividing a geospatial area into a plurality regions; weight the connectedness between regions based on the number of documents co-authored by individuals from the regions; and determine a geospatial distribution of the attribute based on the occurrences of the attribute in each geospatial region and the connectedness between geospatial regions. 11. A method for predicting prominence of an attribute of at least one document of an existing document set in a future document set with a computing system having one or more computing devices, the method comprising:
extracting the attribute from input received by the computing system; based on the attribute, determining a prediction type; based on the prediction type, selecting a set of indicators, each indicator comprising a set of features extracted from the existing document set, the existing document set comprising documents (i) semantically related to the attribute and (ii) published over a time interval beginning prior to and ending on or before a current date; with the indicators, modeling prominence of the attribute in the existing document set over the time interval using one or more statistical modeling techniques; based on the model, estimating future prominence of the attribute in a set of documents that do not currently exist relative to prominence of the attribute in the existing document set; and interactively presenting content relating to the estimated future prominence of the attribute by one or more output devices of the computing system. 12. The method of claim 11, wherein selecting the set of indicators further includes selecting one indicator based on how predictive the selected indicator is of the prediction type and based on how much information the selected indicator conveys about the existing document set. 13. The method of claim 11, further comprising:
analyzing each sentence containing the attribute in the existing set of documents; and determining a sentiment parameter for the attribute, the sentiment parameter being indicative of whether an author of the term in the documents of the existing document set liked or disliked the attribute, the sentiment parameter being determined by analyzing each sentence containing the term in the existing set of documents. 14. A prominence predictor system comprising, embodied in one or more non-transitory machine accessible storage media, instructions configured to cause one or more computing devices to:
extract an attribute from input received by the one or more computing devices; based on the attribute, determine a prediction type; based on the prediction type, select a set of indicators, each indicator comprising a set of features extracted from an existing document set comprising documents (i) semantically related to the attribute and (ii) published over a time interval beginning prior to and ending on or before a current date; with the indicators, model prominence of the attribute in the existing document set over the time interval using one or more statistical modeling techniques; based on the model, estimate future prominence of the attribute in a future document set that do not currently exist relative to prominence of the attribute in the existing document set; and interactively present content relating to the estimated future prominence of the attribute by one or more output devices of the one or more computing devices. 15. The prominence predictor system of claim 12, further comprising instructions configured to:
analyze each sentence containing the attribute in the existing set of documents; and determine a sentiment parameter for the attribute, the sentiment parameter being indicative of whether an author of the term in the documents of the existing document set liked or disliked the attribute, the sentiment parameter being determined by analyzing each sentence containing the term in the existing set of documents. 16. The prominence predictor system of claim 12, further comprising instructions configured to predict whether the estimated future prominence of the attribute will exceed a prominence threshold. 17. The prominence predictor system of claim 12, further comprising instructions configured to (i) estimate the future prominence of the attribute over time and (ii) estimate the future prominence of the attribute over a geospatial distribution. 18. The prominence predictor system of claim 12, wherein:
the attribute is associated with a feature extracted from at least one document of the existing document set, the attribute having a number of characteristics including an observed count of occurrences of the attribute in the existing document set, and the prediction type comprises a predicted count of occurrences of the attribute in the future document set based at least in part on the observed count of occurrences of the attribute in the existing document set. 19. The prominence predictor system of claim 12, wherein the set of indicators includes a subset of observable indicators having observed data extracted from the existing document set and a subset of derived indicators having derived data learned from the existing document set, the derived data being semantically determined from the observable data through the use of machine learning techniques. 20. The prominence predictor system of claim 12, wherein indicators of the set of indicators include static features having a single nominal value and dynamic features having values that changes as a function over time. | Systems and methods for forecasting the prominence of various attributes in a future subject matter area are disclosed. An attribute is determined based on inputs received by a computing system. A set of indicators is determined based on the attribute and features extracted from an existing document set. The prominence of the attribute in the existing document set is determined. A prominence estimate of the attribute in a future document set is determined.1. A prominence predictor system comprising one or more computing devices configured to:
extract an attribute from input received by the one or more computing devices; determine a prediction type based on the attribute; select a plurality of indicators based on the prediction type, each indicator comprising a set of features extracted from an existing document set comprising documents (i) semantically related to the attribute and (ii) published over a time interval beginning prior to and ending on or before a current date; model the prominence of the attribute in accordance with the plurality of indicators in the existing document set over the time interval using one or more statistical modeling techniques; estimate future prominence of the attribute based on the model in a future document set that do not currently exist relative to prominence of the attribute in the existing document set; and interactively present content relating to the estimated future prominence of the attribute by one or more output devices of the one or more computing devices. 2. The system of claim 1, wherein:
the attribute is associated with a feature extracted from at least one document of the existing document set, the attribute having a number of characteristics including an observed count of occurrences of the attribute in the existing document set, and the prediction type comprises a predicted count of occurrences of the attribute in the future document set based at least in part on the observed count of occurrences of the attribute in the existing document set. 3. The system of claim 1, wherein the set of indicators includes a subset of observable indicators having observed data extracted from the existing document set and a subset of derived indicators having derived data learned from the existing document set, the derived data being semantically determined from the observable data through the use of machine learning techniques. 4. The system of claim 1, wherein the one or more computing devices are further configured to determine a sentiment parameter for the attribute when the attribute is a term extracted from the documents of the existing document set, the sentiment parameter is indicative of whether an author of the term in the documents of the existing document set liked or disliked the attribute, the sentiment parameter being determined by analyzing each sentence containing the term in the existing set of documents. 5. The system of claim 1, wherein indicators of the set of indicators include static features having a single nominal value and dynamic features having data that changes as a function over time. 6. The system of claim 1, wherein to interactively present content further includes to determine the content output by the output devices based on the selected prediction type and the selected set of indicators used to determine the estimated future prominence, wherein the selected set of indicators are used to structure the content presented. 7. The system of claim 1, wherein the one or more computing devices are further configured to predict whether the estimated future prominence of the attribute will exceed a prominence threshold. 8. The system of claim 1, wherein the estimated future prominence includes data indicative of (i) the future prominence of the attribute over time and (ii) the future prominence of the attribute over a geospatial distribution. 9. The system of claim 1, wherein the prediction types include at least one of the following: a number of occurrences of the attribute in the future document set, a number of citations in the future document set to a document in the existing document set, a geospatial distribution of occurrences of the attribute in the future document set, a number of times the attribute is published in the future document set, and/or the number of patents issued in the future document set. 10. The system of claim 1, wherein the one or more computing devices are further configured to:
generate a geospatial model by dividing a geospatial area into a plurality regions; weight the connectedness between regions based on the number of documents co-authored by individuals from the regions; and determine a geospatial distribution of the attribute based on the occurrences of the attribute in each geospatial region and the connectedness between geospatial regions. 11. A method for predicting prominence of an attribute of at least one document of an existing document set in a future document set with a computing system having one or more computing devices, the method comprising:
extracting the attribute from input received by the computing system; based on the attribute, determining a prediction type; based on the prediction type, selecting a set of indicators, each indicator comprising a set of features extracted from the existing document set, the existing document set comprising documents (i) semantically related to the attribute and (ii) published over a time interval beginning prior to and ending on or before a current date; with the indicators, modeling prominence of the attribute in the existing document set over the time interval using one or more statistical modeling techniques; based on the model, estimating future prominence of the attribute in a set of documents that do not currently exist relative to prominence of the attribute in the existing document set; and interactively presenting content relating to the estimated future prominence of the attribute by one or more output devices of the computing system. 12. The method of claim 11, wherein selecting the set of indicators further includes selecting one indicator based on how predictive the selected indicator is of the prediction type and based on how much information the selected indicator conveys about the existing document set. 13. The method of claim 11, further comprising:
analyzing each sentence containing the attribute in the existing set of documents; and determining a sentiment parameter for the attribute, the sentiment parameter being indicative of whether an author of the term in the documents of the existing document set liked or disliked the attribute, the sentiment parameter being determined by analyzing each sentence containing the term in the existing set of documents. 14. A prominence predictor system comprising, embodied in one or more non-transitory machine accessible storage media, instructions configured to cause one or more computing devices to:
extract an attribute from input received by the one or more computing devices; based on the attribute, determine a prediction type; based on the prediction type, select a set of indicators, each indicator comprising a set of features extracted from an existing document set comprising documents (i) semantically related to the attribute and (ii) published over a time interval beginning prior to and ending on or before a current date; with the indicators, model prominence of the attribute in the existing document set over the time interval using one or more statistical modeling techniques; based on the model, estimate future prominence of the attribute in a future document set that do not currently exist relative to prominence of the attribute in the existing document set; and interactively present content relating to the estimated future prominence of the attribute by one or more output devices of the one or more computing devices. 15. The prominence predictor system of claim 12, further comprising instructions configured to:
analyze each sentence containing the attribute in the existing set of documents; and determine a sentiment parameter for the attribute, the sentiment parameter being indicative of whether an author of the term in the documents of the existing document set liked or disliked the attribute, the sentiment parameter being determined by analyzing each sentence containing the term in the existing set of documents. 16. The prominence predictor system of claim 12, further comprising instructions configured to predict whether the estimated future prominence of the attribute will exceed a prominence threshold. 17. The prominence predictor system of claim 12, further comprising instructions configured to (i) estimate the future prominence of the attribute over time and (ii) estimate the future prominence of the attribute over a geospatial distribution. 18. The prominence predictor system of claim 12, wherein:
the attribute is associated with a feature extracted from at least one document of the existing document set, the attribute having a number of characteristics including an observed count of occurrences of the attribute in the existing document set, and the prediction type comprises a predicted count of occurrences of the attribute in the future document set based at least in part on the observed count of occurrences of the attribute in the existing document set. 19. The prominence predictor system of claim 12, wherein the set of indicators includes a subset of observable indicators having observed data extracted from the existing document set and a subset of derived indicators having derived data learned from the existing document set, the derived data being semantically determined from the observable data through the use of machine learning techniques. 20. The prominence predictor system of claim 12, wherein indicators of the set of indicators include static features having a single nominal value and dynamic features having values that changes as a function over time. | 2,100 |
6,512 | 6,512 | 15,851,075 | 2,171 | A computer-implemented process for graphical control of grid views, identifies within a graphical user interface (GUI) comprising a screen filled with an image in a current grid layout, a GUI handle exists in a first position. Responsive to dragging the GUI handle from the first position to a second position, further determining whether a first threshold is met. Responsive to determining that the first threshold is met, generating a new grid layout to fill the screen by dividing the screen into a first number of multiple images, using a single interactive gesture of dragging to change a size, aspect ratio and number of cells, on a fixed size screen. | 1. A computer-implemented process for graphical control of grid views, the computer-implemented method comprising:
identifying, within a graphical user interface (GUI) comprising a screen filled with an image in a current grid layout, a GUI handle exists in a first position; responsive to dragging the GUI handle from the first position to a second position, determining whether a first threshold is met; and responsive to determining that the first threshold is met, generating a new grid layout to fill the screen by dividing the screen into a first number of multiple images, wherein a single interactive gesture of dragging changes a size, aspect ratio and number of cells, on a fixed size screen. 2. The computer-implemented process of claim 1, wherein responsive to determining that the first threshold is met, further comprises:
receiving a set of values corresponding to current settings of a set of attributes used to generate a grid layout; generating the new grid layout to replace the current grid layout using the set of values corresponding to current settings of the set of attributes; and submitting the new grid layout to a rendering service of the graphical user interface. 3. The computer-implemented process of claim 2, wherein the set of values corresponding to current settings of a set of attributes used to generate the grid layout further comprises information representative of body parts including tissues, bones and organs, and an imaging technique including use of radiology, nuclear medicine and optical imaging associated with the image, wherein a techniques is selected from a set consisting of computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), a combination of positron emission tomography and computed tomography (PET-CT), Ultrasound and X-Ray. 4. The computer-implemented process of claim 1, wherein the size of the cells is automatically adjusted to one of equivalent size and non-uniform dimensions. 5. The computer-implemented process of claim 2, wherein an increment setting specifies for each threshold traversed that the new grid layout is changed from the current layout by one of an atomic unit, which maintains a proportional change and more than one unit. 6. The computer-implemented process of claim 1, wherein responsive to determining that the first threshold is met, generating the new grid layout by dividing the screen into a first number of multiple images further comprises predetermined limits to prevent underflow errors and illogical combinations. 7. The computer-implemented process of claim 2, wherein the set of attributes further comprises a size of a display area, a type of image being displayed, an increment setting, a first threshold and a vector, wherein the vector identifies a direction and a displacement from an origin and the type of image being displayed identifies a particular property of the image. 8. A data processing system for graphical control of grid views, the data processing system comprising:
a bus; a memory connected to the bus, wherein the memory contains computer executable instructions; a processor unit connected to the bus, wherein the processor unit executes the computer executable instructions to direct the data processing system to:
identify, within a graphical user interface (GUI) comprising a screen filled with an image in a current grid layout, a GUI handle exists in a first position;
responsive to dragging the GUI handle from the first position to a second position, determine whether a first threshold is met; and
responsive to determining that the first threshold is met, generate a new grid layout to fill the screen by dividing the screen into a first number of multiple images, wherein a single interactive gesture of dragging changes a size, aspect ratio and number of cells, on a fixed size screen. 9. The data processing system of claim 8, wherein the processor unit executes the computer executable instructions responsive to determining that the first threshold is met, further directs the data processing system to:
receive a set of values corresponding to current settings of a set of attributes used to generate a grid layout; generate the new grid layout to replace the current grid layout using the set of values corresponding to current settings of the set of attributes; and submit the new grid layout to a rendering service of the graphical user interface. 10. The data processing system of claim 9, wherein the set of values corresponding to current settings of a set of attributes used to generate the grid layout further comprises information representative of body parts including tissues, bones and organs, and an imaging technique including use of radiology, nuclear medicine and optical imaging associated with the image, wherein a techniques is selected from a set consisting of computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), a combination of positron emission tomography and computed tomography (PET-CT), Ultrasound and X-Ray. 11. The data processing system of claim 8, wherein the size of the cells is automatically adjusted to one of equivalent size and non-uniform dimensions. 12. The data processing system of claim 9, wherein an increment setting specifies for each threshold traversed that the new grid layout is changed from the current layout by one of an atomic unit, which maintains a proportional change and more than one unit. 13. The data processing system of claim 8, wherein the processor unit executes the computer executable instructions responsive to determining that the first threshold is met, further directs the data processing system to generate the new grid layout by dividing the screen into a first number of multiple images further comprises predetermined limits to prevent underflow errors and illogical combinations. 14. The data processing system of claim 9, wherein the set of attributes further comprises a size of a display area, a type of image being displayed, an increment setting, a first threshold and a vector, wherein the vector identifies a direction and a displacement from an origin and the type of image being displayed identifies a particular property of the image. 15. A computer program product for graphical control of grid views, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to:
identify, within a graphical user interface (GUI) comprising a screen filled with an image in a current grid layout, a GUI handle exists in a first position; responsive to dragging the GUI handle from the first position to a second position, determine whether a first threshold is met; and responsive to determining that the first threshold is met, generate a new grid layout to fill the screen by dividing the screen into a first number of multiple images, wherein a single interactive gesture of dragging changes a size, aspect ratio and number of cells, on a fixed size screen. 16. The computer program product of claim 15, wherein the program instructions executable by a computer responsive to determining that the first threshold is met, further comprise program instructions executable by a computer to cause the computer to:
receive a set of values corresponding to current settings of a set of attributes used to generate a grid layout; generate the new grid layout to replace the current grid layout using the set of values corresponding to current settings of the set of attributes; and submit the new grid layout to a rendering service of the graphical user interface. 17. The computer program product of claim 16, wherein the set of values corresponding to current settings of a set of attributes used to generate the grid layout further comprises information representative of body parts including tissues, bones and organs, and an imaging technique including use of radiology, nuclear medicine and optical imaging associated with the image, wherein a techniques is selected from a set consisting of computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), a combination of positron emission tomography and computed tomography (PET-CT), Ultrasound and X-Ray. 18. The computer program product of claim 15, wherein the size of the cells is automatically adjusted to one of equivalent size and non-uniform dimensions. 19. The computer program product of claim 16, wherein an increment setting specifies for each threshold traversed that the new grid layout is changed from the current layout by one of an atomic unit, which maintains a proportional change and more than one unit. 20. The computer program product of claim 15, wherein the program instructions executable by a computer responsive to determining that the first threshold is met, further comprise program instructions executable by a computer to cause the computer to:
generate the new grid layout by dividing the screen into a first number of multiple images further comprises predetermined limits to prevent underflow errors and illogical combinations. | A computer-implemented process for graphical control of grid views, identifies within a graphical user interface (GUI) comprising a screen filled with an image in a current grid layout, a GUI handle exists in a first position. Responsive to dragging the GUI handle from the first position to a second position, further determining whether a first threshold is met. Responsive to determining that the first threshold is met, generating a new grid layout to fill the screen by dividing the screen into a first number of multiple images, using a single interactive gesture of dragging to change a size, aspect ratio and number of cells, on a fixed size screen.1. A computer-implemented process for graphical control of grid views, the computer-implemented method comprising:
identifying, within a graphical user interface (GUI) comprising a screen filled with an image in a current grid layout, a GUI handle exists in a first position; responsive to dragging the GUI handle from the first position to a second position, determining whether a first threshold is met; and responsive to determining that the first threshold is met, generating a new grid layout to fill the screen by dividing the screen into a first number of multiple images, wherein a single interactive gesture of dragging changes a size, aspect ratio and number of cells, on a fixed size screen. 2. The computer-implemented process of claim 1, wherein responsive to determining that the first threshold is met, further comprises:
receiving a set of values corresponding to current settings of a set of attributes used to generate a grid layout; generating the new grid layout to replace the current grid layout using the set of values corresponding to current settings of the set of attributes; and submitting the new grid layout to a rendering service of the graphical user interface. 3. The computer-implemented process of claim 2, wherein the set of values corresponding to current settings of a set of attributes used to generate the grid layout further comprises information representative of body parts including tissues, bones and organs, and an imaging technique including use of radiology, nuclear medicine and optical imaging associated with the image, wherein a techniques is selected from a set consisting of computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), a combination of positron emission tomography and computed tomography (PET-CT), Ultrasound and X-Ray. 4. The computer-implemented process of claim 1, wherein the size of the cells is automatically adjusted to one of equivalent size and non-uniform dimensions. 5. The computer-implemented process of claim 2, wherein an increment setting specifies for each threshold traversed that the new grid layout is changed from the current layout by one of an atomic unit, which maintains a proportional change and more than one unit. 6. The computer-implemented process of claim 1, wherein responsive to determining that the first threshold is met, generating the new grid layout by dividing the screen into a first number of multiple images further comprises predetermined limits to prevent underflow errors and illogical combinations. 7. The computer-implemented process of claim 2, wherein the set of attributes further comprises a size of a display area, a type of image being displayed, an increment setting, a first threshold and a vector, wherein the vector identifies a direction and a displacement from an origin and the type of image being displayed identifies a particular property of the image. 8. A data processing system for graphical control of grid views, the data processing system comprising:
a bus; a memory connected to the bus, wherein the memory contains computer executable instructions; a processor unit connected to the bus, wherein the processor unit executes the computer executable instructions to direct the data processing system to:
identify, within a graphical user interface (GUI) comprising a screen filled with an image in a current grid layout, a GUI handle exists in a first position;
responsive to dragging the GUI handle from the first position to a second position, determine whether a first threshold is met; and
responsive to determining that the first threshold is met, generate a new grid layout to fill the screen by dividing the screen into a first number of multiple images, wherein a single interactive gesture of dragging changes a size, aspect ratio and number of cells, on a fixed size screen. 9. The data processing system of claim 8, wherein the processor unit executes the computer executable instructions responsive to determining that the first threshold is met, further directs the data processing system to:
receive a set of values corresponding to current settings of a set of attributes used to generate a grid layout; generate the new grid layout to replace the current grid layout using the set of values corresponding to current settings of the set of attributes; and submit the new grid layout to a rendering service of the graphical user interface. 10. The data processing system of claim 9, wherein the set of values corresponding to current settings of a set of attributes used to generate the grid layout further comprises information representative of body parts including tissues, bones and organs, and an imaging technique including use of radiology, nuclear medicine and optical imaging associated with the image, wherein a techniques is selected from a set consisting of computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), a combination of positron emission tomography and computed tomography (PET-CT), Ultrasound and X-Ray. 11. The data processing system of claim 8, wherein the size of the cells is automatically adjusted to one of equivalent size and non-uniform dimensions. 12. The data processing system of claim 9, wherein an increment setting specifies for each threshold traversed that the new grid layout is changed from the current layout by one of an atomic unit, which maintains a proportional change and more than one unit. 13. The data processing system of claim 8, wherein the processor unit executes the computer executable instructions responsive to determining that the first threshold is met, further directs the data processing system to generate the new grid layout by dividing the screen into a first number of multiple images further comprises predetermined limits to prevent underflow errors and illogical combinations. 14. The data processing system of claim 9, wherein the set of attributes further comprises a size of a display area, a type of image being displayed, an increment setting, a first threshold and a vector, wherein the vector identifies a direction and a displacement from an origin and the type of image being displayed identifies a particular property of the image. 15. A computer program product for graphical control of grid views, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to:
identify, within a graphical user interface (GUI) comprising a screen filled with an image in a current grid layout, a GUI handle exists in a first position; responsive to dragging the GUI handle from the first position to a second position, determine whether a first threshold is met; and responsive to determining that the first threshold is met, generate a new grid layout to fill the screen by dividing the screen into a first number of multiple images, wherein a single interactive gesture of dragging changes a size, aspect ratio and number of cells, on a fixed size screen. 16. The computer program product of claim 15, wherein the program instructions executable by a computer responsive to determining that the first threshold is met, further comprise program instructions executable by a computer to cause the computer to:
receive a set of values corresponding to current settings of a set of attributes used to generate a grid layout; generate the new grid layout to replace the current grid layout using the set of values corresponding to current settings of the set of attributes; and submit the new grid layout to a rendering service of the graphical user interface. 17. The computer program product of claim 16, wherein the set of values corresponding to current settings of a set of attributes used to generate the grid layout further comprises information representative of body parts including tissues, bones and organs, and an imaging technique including use of radiology, nuclear medicine and optical imaging associated with the image, wherein a techniques is selected from a set consisting of computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), a combination of positron emission tomography and computed tomography (PET-CT), Ultrasound and X-Ray. 18. The computer program product of claim 15, wherein the size of the cells is automatically adjusted to one of equivalent size and non-uniform dimensions. 19. The computer program product of claim 16, wherein an increment setting specifies for each threshold traversed that the new grid layout is changed from the current layout by one of an atomic unit, which maintains a proportional change and more than one unit. 20. The computer program product of claim 15, wherein the program instructions executable by a computer responsive to determining that the first threshold is met, further comprise program instructions executable by a computer to cause the computer to:
generate the new grid layout by dividing the screen into a first number of multiple images further comprises predetermined limits to prevent underflow errors and illogical combinations. | 2,100 |
6,513 | 6,513 | 16,242,275 | 2,196 | Exemplary methods, apparatuses, and systems include a client virtual machine processing a system call for a device driver to instruct a physical device to perform a function and transmitting the system call to an appliance virtual machine to execute the system call. The client virtual machine determines, in response to the system call, that an established connection with the appliance virtual machine has switched from a first protocol to a second protocol, the first and second protocols including a high-performance transmission protocol and Transmission Control Protocol and Internet Protocol (TCP/IP). The client virtual machine transmits the system call to the appliance virtual machine according to the second protocol. For example, the established connection may switch to the second protocol in response to the client virtual machine migrating to the first host device from a second host device. | 1. A computer implemented method, comprising processing a system call from an application running within a client virtual machine running on a first host device, wherein the processing includes:
determining that the system call is a request for a device driver to instruct a physical general-purpose graphics processing unit (GPGPU) or co-processor to perform a function and that the request is intended for a parallel computing framework library, wherein a first appliance virtual machine provides the parallel computing library and virtualization of the GPGPU or co-processor for a plurality of virtual machines including the client virtual machine;
and
transmitting, in response to determining that the system call is intended for the parallel computing framework library, the request from the client virtual machine to the first appliance virtual machine to execute the request via a guest device pass-through that communicates directly with the GPGPU or co-processor. 2. The computer implemented method of claim 1, further comprising, selecting, by the client virtual machine, the first appliance virtual machine based on a listing of one or more appliance virtual machines available to the client virtual machine. 3. The computer implemented method of claim 1, further comprising, selecting, the first appliance virtual machine based on one or more of (a) previous use of a one or more appliance virtual machines, (b) load balancing between available appliance virtual machines, (c) latency in response from the available appliance virtual machines, or (d) co-location within a same host device as the client virtual machine. 4. The computer implemented method of claim 1, further comprising, upon receiving, by the first appliance virtual machine the request from the client virtual machine, load balancing the request between one or more schedulers based on use of the GPGPU or the co-processor by the client virtual machine and other client virtual machines. 5. The computer implemented method of claim 1, further comprising, prior to the transmitting, determining, in response to the system call, that an established connection between the client virtual machine and the first appliance virtual machine has switched from a first protocol to a second protocol, the first and second protocols including a high-performance transmission protocol and a low-performance transmission protocol. 6. The computer implemented method of claim 5, further comprising:
determining that the second protocol has failed; and switching from the second protocol to a third protocol. 7. The computer implemented method of claim 5, wherein the established connection switches to the second protocol in response to the client virtual machine migrating to the first host device from a second host device. 8. The computer implemented method of claim 1, further comprising:
selecting, in response to a detected latency in the first appliance virtual machine processing the transmitted request, a second appliance virtual machine to be the recipient of requests for a device driver to instruct a physical device to perform a function. 9. A non-transitory computer-readable medium storing instructions, which when executed by a processing device, cause the processing device to perform method comprising:
processing a system call from an application running within a client virtual machine running on a first host device, wherein the processing includes
determining that the system call is a request for a device driver to instruct a physical general-purpose graphics processing unit (GPGPU) or co-processor to perform a function and that the request is intended for a parallel computing framework library, wherein a first appliance virtual machine provides the parallel computing library and virtualization of the GPGPU or co-processor for a plurality of virtual machines including the client virtual machine; and
transmitting, in response to determining that the system call is intended for the parallel computing framework library, the request from the client virtual machine to the first appliance virtual machine to execute the request via a guest device pass-through that communicates directly with the GPGPU or co-processor. 10. The non-transitory computer-readable medium of claim 9, the method further comprising, selecting, by the client virtual machine, the first appliance virtual machine based on a listing of one or more appliance virtual machines available to the client virtual machine. 11. The non-transitory computer-readable medium of claim 9, the method further comprising, selecting, the first appliance virtual machine based on one or more of (a) previous use of a one or more appliance virtual machines, (b) load balancing between available appliance virtual machines, (c) latency in response from the available appliance virtual machines, or (d) co-location within a same host device as the client virtual machine. 12. The non-transitory computer-readable medium of claim 9, the method further comprising, upon receiving, by the first appliance virtual machine the request from the client virtual machine, load balancing the request between one or more schedulers based on use of the GPGPU or the co-processor by the client virtual machine and other client virtual machines. 13. The non-transitory computer-readable medium of claim 9, the method further comprising, prior to the transmitting, determining, in response to the system call, that an established connection between the client virtual machine and the first appliance virtual machine has switched from a first protocol to a second protocol, the first and second protocols including a high-performance transmission protocol and a low-performance transmission protocol. 14. The non-transitory computer-readable medium of claim 13, the method further comprising:
determining that the second protocol has failed; and switching from the second protocol to a third protocol. 15. The non-transitory computer-readable medium of claim 13, wherein the established connection switches to the second protocol in response to the client virtual machine migrating to the first host device from a second host device. 16. The non-transitory computer-readable medium of claim 9, the method further comprising:
selecting, in response to a detected latency in the first appliance virtual machine processing the transmitted request, a second appliance virtual machine to be the recipient of requests for a device driver to instruct a physical device to perform a function. 17. An apparatus comprising:
a first host device including a physical processing device, wherein the physical processing device executes instructions that cause the apparatus to process a system call from an application running within a client virtual machine, wherein the processing includes
determining that the system call is a request for a device driver to instruct a physical general-purpose graphics processing unit (GPGPU) or co-processor to perform a function and that the request is intended for a parallel computing framework library, wherein a first appliance virtual machine provides the parallel computing library and virtualization of the GPGPU or co-processor for a plurality of virtual machines including the client virtual machine; and
transmitting, in response to determining that the system call is intended for the parallel computing framework library, the request from the client virtual machine to the first appliance virtual machine to execute the request via a guest device pass-through that communicates directly with the GPGPU or co-processor. 18. The apparatus of claim 17, the processing further comprising, selecting, by the client virtual machine, the first appliance virtual machine based on a listing of one or more appliance virtual machines available to the client virtual machine. 19. The apparatus of claim 17, the processing further comprising, selecting, the first appliance virtual machine based on one or more of (a) previous use of a one or more appliance virtual machines, (b) load balancing between available appliance virtual machines, (c) latency in response from the available appliance virtual machines, or (d) co-location within a same host device as the client virtual machine. 20. The apparatus of claim 17, the processing further comprising, upon receiving, by the first appliance virtual machine the request from the client virtual machine, load balancing the request between one or more schedulers based on use of the GPGPU or the co-processor by the client virtual machine and other client virtual machines. | Exemplary methods, apparatuses, and systems include a client virtual machine processing a system call for a device driver to instruct a physical device to perform a function and transmitting the system call to an appliance virtual machine to execute the system call. The client virtual machine determines, in response to the system call, that an established connection with the appliance virtual machine has switched from a first protocol to a second protocol, the first and second protocols including a high-performance transmission protocol and Transmission Control Protocol and Internet Protocol (TCP/IP). The client virtual machine transmits the system call to the appliance virtual machine according to the second protocol. For example, the established connection may switch to the second protocol in response to the client virtual machine migrating to the first host device from a second host device.1. A computer implemented method, comprising processing a system call from an application running within a client virtual machine running on a first host device, wherein the processing includes:
determining that the system call is a request for a device driver to instruct a physical general-purpose graphics processing unit (GPGPU) or co-processor to perform a function and that the request is intended for a parallel computing framework library, wherein a first appliance virtual machine provides the parallel computing library and virtualization of the GPGPU or co-processor for a plurality of virtual machines including the client virtual machine;
and
transmitting, in response to determining that the system call is intended for the parallel computing framework library, the request from the client virtual machine to the first appliance virtual machine to execute the request via a guest device pass-through that communicates directly with the GPGPU or co-processor. 2. The computer implemented method of claim 1, further comprising, selecting, by the client virtual machine, the first appliance virtual machine based on a listing of one or more appliance virtual machines available to the client virtual machine. 3. The computer implemented method of claim 1, further comprising, selecting, the first appliance virtual machine based on one or more of (a) previous use of a one or more appliance virtual machines, (b) load balancing between available appliance virtual machines, (c) latency in response from the available appliance virtual machines, or (d) co-location within a same host device as the client virtual machine. 4. The computer implemented method of claim 1, further comprising, upon receiving, by the first appliance virtual machine the request from the client virtual machine, load balancing the request between one or more schedulers based on use of the GPGPU or the co-processor by the client virtual machine and other client virtual machines. 5. The computer implemented method of claim 1, further comprising, prior to the transmitting, determining, in response to the system call, that an established connection between the client virtual machine and the first appliance virtual machine has switched from a first protocol to a second protocol, the first and second protocols including a high-performance transmission protocol and a low-performance transmission protocol. 6. The computer implemented method of claim 5, further comprising:
determining that the second protocol has failed; and switching from the second protocol to a third protocol. 7. The computer implemented method of claim 5, wherein the established connection switches to the second protocol in response to the client virtual machine migrating to the first host device from a second host device. 8. The computer implemented method of claim 1, further comprising:
selecting, in response to a detected latency in the first appliance virtual machine processing the transmitted request, a second appliance virtual machine to be the recipient of requests for a device driver to instruct a physical device to perform a function. 9. A non-transitory computer-readable medium storing instructions, which when executed by a processing device, cause the processing device to perform method comprising:
processing a system call from an application running within a client virtual machine running on a first host device, wherein the processing includes
determining that the system call is a request for a device driver to instruct a physical general-purpose graphics processing unit (GPGPU) or co-processor to perform a function and that the request is intended for a parallel computing framework library, wherein a first appliance virtual machine provides the parallel computing library and virtualization of the GPGPU or co-processor for a plurality of virtual machines including the client virtual machine; and
transmitting, in response to determining that the system call is intended for the parallel computing framework library, the request from the client virtual machine to the first appliance virtual machine to execute the request via a guest device pass-through that communicates directly with the GPGPU or co-processor. 10. The non-transitory computer-readable medium of claim 9, the method further comprising, selecting, by the client virtual machine, the first appliance virtual machine based on a listing of one or more appliance virtual machines available to the client virtual machine. 11. The non-transitory computer-readable medium of claim 9, the method further comprising, selecting, the first appliance virtual machine based on one or more of (a) previous use of a one or more appliance virtual machines, (b) load balancing between available appliance virtual machines, (c) latency in response from the available appliance virtual machines, or (d) co-location within a same host device as the client virtual machine. 12. The non-transitory computer-readable medium of claim 9, the method further comprising, upon receiving, by the first appliance virtual machine the request from the client virtual machine, load balancing the request between one or more schedulers based on use of the GPGPU or the co-processor by the client virtual machine and other client virtual machines. 13. The non-transitory computer-readable medium of claim 9, the method further comprising, prior to the transmitting, determining, in response to the system call, that an established connection between the client virtual machine and the first appliance virtual machine has switched from a first protocol to a second protocol, the first and second protocols including a high-performance transmission protocol and a low-performance transmission protocol. 14. The non-transitory computer-readable medium of claim 13, the method further comprising:
determining that the second protocol has failed; and switching from the second protocol to a third protocol. 15. The non-transitory computer-readable medium of claim 13, wherein the established connection switches to the second protocol in response to the client virtual machine migrating to the first host device from a second host device. 16. The non-transitory computer-readable medium of claim 9, the method further comprising:
selecting, in response to a detected latency in the first appliance virtual machine processing the transmitted request, a second appliance virtual machine to be the recipient of requests for a device driver to instruct a physical device to perform a function. 17. An apparatus comprising:
a first host device including a physical processing device, wherein the physical processing device executes instructions that cause the apparatus to process a system call from an application running within a client virtual machine, wherein the processing includes
determining that the system call is a request for a device driver to instruct a physical general-purpose graphics processing unit (GPGPU) or co-processor to perform a function and that the request is intended for a parallel computing framework library, wherein a first appliance virtual machine provides the parallel computing library and virtualization of the GPGPU or co-processor for a plurality of virtual machines including the client virtual machine; and
transmitting, in response to determining that the system call is intended for the parallel computing framework library, the request from the client virtual machine to the first appliance virtual machine to execute the request via a guest device pass-through that communicates directly with the GPGPU or co-processor. 18. The apparatus of claim 17, the processing further comprising, selecting, by the client virtual machine, the first appliance virtual machine based on a listing of one or more appliance virtual machines available to the client virtual machine. 19. The apparatus of claim 17, the processing further comprising, selecting, the first appliance virtual machine based on one or more of (a) previous use of a one or more appliance virtual machines, (b) load balancing between available appliance virtual machines, (c) latency in response from the available appliance virtual machines, or (d) co-location within a same host device as the client virtual machine. 20. The apparatus of claim 17, the processing further comprising, upon receiving, by the first appliance virtual machine the request from the client virtual machine, load balancing the request between one or more schedulers based on use of the GPGPU or the co-processor by the client virtual machine and other client virtual machines. | 2,100 |
6,514 | 6,514 | 15,898,183 | 2,133 | Examples of the present disclosure generally relate to integrated circuits, such as a system-on-chip (SoC), that include a memory subsystem. In some examples, an integrated circuit includes a first master circuit in a first power domain on a chip; a second master circuit in a second power domain on the chip; and a first memory controller in a third power domain on the chip. The first master circuit and the second master circuit each are configured to access memory via the first memory controller. The first power domain and the second power domain each are separate and independent from the third power domain. | 1. An integrated circuit comprising:
a first master circuit in a first power domain on a chip; a second master circuit in a second power domain on the chip; and a first memory controller in a third power domain on the chip, wherein the first master circuit and the second master circuit each are configured to access memory via the first memory controller, and wherein the first power domain and the second power domain each are separate and independent from the third power domain. 2. The integrated circuit of claim 1, wherein the first power domain is separate and independent from the second power domain. 3. The integrated circuit of claim 1, wherein the first memory controller is not included in a master circuit. 4. The integrated circuit of claim 1, wherein the first memory controller is in a physical block dedicated to the first memory controller. 5. The integrated circuit of claim 1 further comprising a configurable interconnect network on the chip, wherein the first master circuit and the second master circuit each are configured to access the memory via the first memory controller and the configurable interconnect network. 6. The integrated circuit of claim 5 further comprising a second memory controller in a fourth power domain on the chip, wherein the first master circuit and the second master circuit each are configured to access the memory via the second memory controller and the configurable interconnect network, and wherein the first power domain and the second power domain each are separate and independent from the fourth power domain. 7. The integrated circuit of claim 6, wherein:
the first memory controller accesses a first address range of the memory; the second memory controller accesses a second address range of the memory; and the first address range is distinct from the second address range. 8. The integrated circuit of claim 6, wherein the first memory controller and the second memory controller are configured to interleave access to the memory. 9. The integrated circuit of claim 5, wherein the first memory controller includes multiple ports connected to the configurable interconnect network. 10. The integrated circuit of claim 5, wherein the first memory controller is configured to enable handling multiple traffic classes via respective virtual channels of a physical channel of the configurable interconnect network. 11. A method of operating an integrated circuit, the method comprising:
selectively entering each of a plurality of master circuits of the integrated circuit into one of a plurality of power modes; and accessing memory by at least one of the plurality of master circuits via a first memory controller of the integrated circuit irrespective of the selected one of the plurality of power modes of each of the others of the plurality of master circuits, wherein the first memory controller is in a power domain separate from each respective power domain of the plurality of master circuits. 12. The method of claim 11, wherein the first memory controller is not included in a master circuit. 13. The method of claim 11, wherein accessing the memory by the at least one of the plurality of master circuits via the first memory controller comprises communicating between the at least one of the plurality of master circuits and the first memory controller via a configurable interconnect network of the integrated circuit. 14. The method of claim 13 further comprising accessing memory by at least one of the plurality of master circuits via a second memory controller of the integrated circuit and the configurable interconnect network, wherein the second memory controller is in a power domain separate from each respective power domain of the plurality of master circuits. 15. The method of claim 13, wherein communicating between the at least one of the plurality of master circuits and the first memory controller via the configurable interconnect network includes communicating between the at least one of the plurality of master circuits and the first memory controller via at least one of a plurality of virtual channels of a physical channel of the configurable interconnect network. 16. An integrated circuit comprising:
a processing system on a chip; programmable logic on the chip; a configurable interconnect network on the chip; a first memory controller on the chip, the processing system and the programmable logic each being communicatively coupled to the first memory controller via the configurable interconnect network, the processing system and the programmable logic each being configured to access memory via the first memory controller and the configurable interconnect network; and a management unit on the chip, the management unit being capable of controlling respective power modes of the processing system and the programmable logic independently of operation of the first memory controller. 17. The integrated circuit of claim 16, wherein:
the processing system is in a first power domain; the programmable logic is in a second power domain separate and independent from the first power domain; and the first memory controller is in a third power domain separate and independent from each of the first power domain and the second power domain. 18. The integrated circuit of claim 16 further comprising a second memory controller on the chip, the processing system and the programmable logic each being communicatively coupled to the second memory controller via the configurable interconnect network, the processing system and the programmable logic each being configured to access the memory via the second memory controller and the configurable interconnect network, the management unit being capable of controlling respective power modes of the processing system and the programmable logic independently of operation of the second memory controller. 19. The integrated circuit of claim 16, wherein the first memory controller comprises multiple ports connected to the configurable interconnect network. 20. The integrated circuit of claim 16, wherein:
the configurable interconnect network is operable to implement a plurality of virtual channels on a physical channel; and the first memory controller is configured to enable handling multiple traffic classes via respective ones of the plurality of virtual channels. | Examples of the present disclosure generally relate to integrated circuits, such as a system-on-chip (SoC), that include a memory subsystem. In some examples, an integrated circuit includes a first master circuit in a first power domain on a chip; a second master circuit in a second power domain on the chip; and a first memory controller in a third power domain on the chip. The first master circuit and the second master circuit each are configured to access memory via the first memory controller. The first power domain and the second power domain each are separate and independent from the third power domain.1. An integrated circuit comprising:
a first master circuit in a first power domain on a chip; a second master circuit in a second power domain on the chip; and a first memory controller in a third power domain on the chip, wherein the first master circuit and the second master circuit each are configured to access memory via the first memory controller, and wherein the first power domain and the second power domain each are separate and independent from the third power domain. 2. The integrated circuit of claim 1, wherein the first power domain is separate and independent from the second power domain. 3. The integrated circuit of claim 1, wherein the first memory controller is not included in a master circuit. 4. The integrated circuit of claim 1, wherein the first memory controller is in a physical block dedicated to the first memory controller. 5. The integrated circuit of claim 1 further comprising a configurable interconnect network on the chip, wherein the first master circuit and the second master circuit each are configured to access the memory via the first memory controller and the configurable interconnect network. 6. The integrated circuit of claim 5 further comprising a second memory controller in a fourth power domain on the chip, wherein the first master circuit and the second master circuit each are configured to access the memory via the second memory controller and the configurable interconnect network, and wherein the first power domain and the second power domain each are separate and independent from the fourth power domain. 7. The integrated circuit of claim 6, wherein:
the first memory controller accesses a first address range of the memory; the second memory controller accesses a second address range of the memory; and the first address range is distinct from the second address range. 8. The integrated circuit of claim 6, wherein the first memory controller and the second memory controller are configured to interleave access to the memory. 9. The integrated circuit of claim 5, wherein the first memory controller includes multiple ports connected to the configurable interconnect network. 10. The integrated circuit of claim 5, wherein the first memory controller is configured to enable handling multiple traffic classes via respective virtual channels of a physical channel of the configurable interconnect network. 11. A method of operating an integrated circuit, the method comprising:
selectively entering each of a plurality of master circuits of the integrated circuit into one of a plurality of power modes; and accessing memory by at least one of the plurality of master circuits via a first memory controller of the integrated circuit irrespective of the selected one of the plurality of power modes of each of the others of the plurality of master circuits, wherein the first memory controller is in a power domain separate from each respective power domain of the plurality of master circuits. 12. The method of claim 11, wherein the first memory controller is not included in a master circuit. 13. The method of claim 11, wherein accessing the memory by the at least one of the plurality of master circuits via the first memory controller comprises communicating between the at least one of the plurality of master circuits and the first memory controller via a configurable interconnect network of the integrated circuit. 14. The method of claim 13 further comprising accessing memory by at least one of the plurality of master circuits via a second memory controller of the integrated circuit and the configurable interconnect network, wherein the second memory controller is in a power domain separate from each respective power domain of the plurality of master circuits. 15. The method of claim 13, wherein communicating between the at least one of the plurality of master circuits and the first memory controller via the configurable interconnect network includes communicating between the at least one of the plurality of master circuits and the first memory controller via at least one of a plurality of virtual channels of a physical channel of the configurable interconnect network. 16. An integrated circuit comprising:
a processing system on a chip; programmable logic on the chip; a configurable interconnect network on the chip; a first memory controller on the chip, the processing system and the programmable logic each being communicatively coupled to the first memory controller via the configurable interconnect network, the processing system and the programmable logic each being configured to access memory via the first memory controller and the configurable interconnect network; and a management unit on the chip, the management unit being capable of controlling respective power modes of the processing system and the programmable logic independently of operation of the first memory controller. 17. The integrated circuit of claim 16, wherein:
the processing system is in a first power domain; the programmable logic is in a second power domain separate and independent from the first power domain; and the first memory controller is in a third power domain separate and independent from each of the first power domain and the second power domain. 18. The integrated circuit of claim 16 further comprising a second memory controller on the chip, the processing system and the programmable logic each being communicatively coupled to the second memory controller via the configurable interconnect network, the processing system and the programmable logic each being configured to access the memory via the second memory controller and the configurable interconnect network, the management unit being capable of controlling respective power modes of the processing system and the programmable logic independently of operation of the second memory controller. 19. The integrated circuit of claim 16, wherein the first memory controller comprises multiple ports connected to the configurable interconnect network. 20. The integrated circuit of claim 16, wherein:
the configurable interconnect network is operable to implement a plurality of virtual channels on a physical channel; and the first memory controller is configured to enable handling multiple traffic classes via respective ones of the plurality of virtual channels. | 2,100 |
6,515 | 6,515 | 16,170,371 | 2,184 | There is provided an apparatus for receiving a request from a master to access an input address. Coarse grain access circuitry stores and provides a reference to an area of an output address space in dependence on the input address. One or more fine grain access circuits, each store and provide a reference to a sub-area in the area of the output address space in dependence on the input address. The apparatus forwards the request from the coarse grain access circuitry to one of the one fine grain access circuits in dependence on the input address. | 1. An apparatus adapted to receive a request from a master to access an input address, the apparatus comprising:
coarse grain access circuitry to store and provide a reference to an area of an output address space in dependence on the input address; and one or more fine grain access circuits, each to store and provide a reference to a sub-area in the area of the output address space in dependence on the input address, wherein the apparatus is adapted to forward the request from the coarse grain access circuitry to one of the one fine grain access circuits in dependence on the input address. 2. An apparatus according to claim 1, wherein
in response to the coarse grain access circuitry lacking an entry corresponding with the input address, the coarse grain access circuitry is adapted to do at least one of the following: raise an error, and raise an interrupt. 3. An apparatus according to claim 1, wherein
in response to the fine grain access circuits lacking an entry corresponding with the input address, the fine grain access circuitry is adapted to do at least one of the following: raise an error, and raise an interrupt. 4. An apparatus according to claim 1, wherein
the master is one of a plurality of masters; the apparatus is adapted to receive the request from any of the plurality of masters; and each reference stored by the coarse grain access circuitry and each of the one or more fine grain access circuits is associated with one of the plurality of masters. 5. An apparatus according to claim 4, wherein
the coarse grain access circuitry is adapted to provide the reference to the area of the output address space in further dependence on the master. 6. An apparatus according to claim 4, wherein
each of the one or more fine grain access circuits is adapted to provide the reference to the sub-area in further dependence on the master. 7. An apparatus according to claim 4, wherein
the coarse grain access circuitry is adapted to provide different references for at least a subset of the plurality of masters in respect of the same input address. 8. An apparatus according to claim 4, wherein
one or more fine grain access circuits is adapted to provide different sub-areas for at least a subset of the plurality of masters in respect of the same input address. 9. An apparatus according to claim 1, wherein
a size of the sub-area is at most a size of the area. 10. An apparatus according to claim 1, comprising
allocation circuitry to generate a new entry, associate a new area of the output address space with the new entry, and provide the new entry to the coarse grain access circuitry before a request to access the new area is received. 11. An apparatus according to claim 1, comprising
allocation circuitry to generate a new entry, associate a new area of the output address space with the new entry, and provide the new entry to one of the one or more fine grain access circuits before a request to access the new area is received. 12. An apparatus according to claim 1, wherein
the input address is a virtual address or an intermediate physical address. 13. An apparatus according to claim 1, wherein
a size of the area is greater than 64 kB. 14. An apparatus according to claim 1, comprising:
a hierarchy of access circuits, comprising a plurality of n levels; a first of the n levels comprising the coarse grain access circuitry; a second of the n levels comprising the one or more fine grain access circuits, wherein a size of the area referenced by circuitry at each level decreases as level increases. 15. An apparatus according to claim 1, wherein
the request comprises a requested access type; at least one of the coarse grain access circuitry and the one or more fine grain access circuits is adapted to store the reference with one or more associated properties and to provide the reference in further dependence on the requested access type and the one or more associated properties. 16. An apparatus according to claim 15, wherein
the properties include one or more of: whether read access is permitted, whether write access is permitted, whether secure access is permitted, whether non-secure access is permitted, whether data access is permitted, whether instruction access is permitted, whether privileged access is permitted, whether unprivileged access is permitted, whether the access is cacheable, whether the access is uncacheable, whether the access is shareable, and whether the access is unsharable. 17. An apparatus according to claim 15, wherein
at least one of the coarse grain access circuitry and the fine grain access circuits modifies the requested access type in dependence on the requested access type and on one or more access translations. 18. An apparatus according to claim 1, wherein
at least one of the coarse grain access circuitry and fine grain access circuits is translation circuitry. 19. A method comprising:
receiving a request from a master to access an input address; providing, at coarse grain access circuitry, a reference to an area of an output address space in dependence on the input address; forwarding the request from the coarse grain access circuitry to a fine grain access circuit in dependence on the input address; and providing, at the fine grain access circuitry, a reference to a sub-area in the area of the output address space in dependence on the input address. 20. A computer program for controlling a host data processing apparatus to provide an instruction execution environment comprising:
receiver program logic adapted to receive a request from a master to access an input address; coarse grain access program logic adapted to store and provide a reference to an area of an output address data structure in dependence on the input address; and fine grain access program logic adapted to store and provide a reference to a sub-area in the area of the output address data structure in dependence on the input address, wherein the apparatus is adapted to forward the request from the coarse grain access program logic to part of the fine grain access program logic in dependence on the input address. | There is provided an apparatus for receiving a request from a master to access an input address. Coarse grain access circuitry stores and provides a reference to an area of an output address space in dependence on the input address. One or more fine grain access circuits, each store and provide a reference to a sub-area in the area of the output address space in dependence on the input address. The apparatus forwards the request from the coarse grain access circuitry to one of the one fine grain access circuits in dependence on the input address.1. An apparatus adapted to receive a request from a master to access an input address, the apparatus comprising:
coarse grain access circuitry to store and provide a reference to an area of an output address space in dependence on the input address; and one or more fine grain access circuits, each to store and provide a reference to a sub-area in the area of the output address space in dependence on the input address, wherein the apparatus is adapted to forward the request from the coarse grain access circuitry to one of the one fine grain access circuits in dependence on the input address. 2. An apparatus according to claim 1, wherein
in response to the coarse grain access circuitry lacking an entry corresponding with the input address, the coarse grain access circuitry is adapted to do at least one of the following: raise an error, and raise an interrupt. 3. An apparatus according to claim 1, wherein
in response to the fine grain access circuits lacking an entry corresponding with the input address, the fine grain access circuitry is adapted to do at least one of the following: raise an error, and raise an interrupt. 4. An apparatus according to claim 1, wherein
the master is one of a plurality of masters; the apparatus is adapted to receive the request from any of the plurality of masters; and each reference stored by the coarse grain access circuitry and each of the one or more fine grain access circuits is associated with one of the plurality of masters. 5. An apparatus according to claim 4, wherein
the coarse grain access circuitry is adapted to provide the reference to the area of the output address space in further dependence on the master. 6. An apparatus according to claim 4, wherein
each of the one or more fine grain access circuits is adapted to provide the reference to the sub-area in further dependence on the master. 7. An apparatus according to claim 4, wherein
the coarse grain access circuitry is adapted to provide different references for at least a subset of the plurality of masters in respect of the same input address. 8. An apparatus according to claim 4, wherein
one or more fine grain access circuits is adapted to provide different sub-areas for at least a subset of the plurality of masters in respect of the same input address. 9. An apparatus according to claim 1, wherein
a size of the sub-area is at most a size of the area. 10. An apparatus according to claim 1, comprising
allocation circuitry to generate a new entry, associate a new area of the output address space with the new entry, and provide the new entry to the coarse grain access circuitry before a request to access the new area is received. 11. An apparatus according to claim 1, comprising
allocation circuitry to generate a new entry, associate a new area of the output address space with the new entry, and provide the new entry to one of the one or more fine grain access circuits before a request to access the new area is received. 12. An apparatus according to claim 1, wherein
the input address is a virtual address or an intermediate physical address. 13. An apparatus according to claim 1, wherein
a size of the area is greater than 64 kB. 14. An apparatus according to claim 1, comprising:
a hierarchy of access circuits, comprising a plurality of n levels; a first of the n levels comprising the coarse grain access circuitry; a second of the n levels comprising the one or more fine grain access circuits, wherein a size of the area referenced by circuitry at each level decreases as level increases. 15. An apparatus according to claim 1, wherein
the request comprises a requested access type; at least one of the coarse grain access circuitry and the one or more fine grain access circuits is adapted to store the reference with one or more associated properties and to provide the reference in further dependence on the requested access type and the one or more associated properties. 16. An apparatus according to claim 15, wherein
the properties include one or more of: whether read access is permitted, whether write access is permitted, whether secure access is permitted, whether non-secure access is permitted, whether data access is permitted, whether instruction access is permitted, whether privileged access is permitted, whether unprivileged access is permitted, whether the access is cacheable, whether the access is uncacheable, whether the access is shareable, and whether the access is unsharable. 17. An apparatus according to claim 15, wherein
at least one of the coarse grain access circuitry and the fine grain access circuits modifies the requested access type in dependence on the requested access type and on one or more access translations. 18. An apparatus according to claim 1, wherein
at least one of the coarse grain access circuitry and fine grain access circuits is translation circuitry. 19. A method comprising:
receiving a request from a master to access an input address; providing, at coarse grain access circuitry, a reference to an area of an output address space in dependence on the input address; forwarding the request from the coarse grain access circuitry to a fine grain access circuit in dependence on the input address; and providing, at the fine grain access circuitry, a reference to a sub-area in the area of the output address space in dependence on the input address. 20. A computer program for controlling a host data processing apparatus to provide an instruction execution environment comprising:
receiver program logic adapted to receive a request from a master to access an input address; coarse grain access program logic adapted to store and provide a reference to an area of an output address data structure in dependence on the input address; and fine grain access program logic adapted to store and provide a reference to a sub-area in the area of the output address data structure in dependence on the input address, wherein the apparatus is adapted to forward the request from the coarse grain access program logic to part of the fine grain access program logic in dependence on the input address. | 2,100 |
6,516 | 6,516 | 15,184,679 | 2,143 | Disclosed are various approaches for generating a user interface in which data items are grouped together. Additionally, a bulk action can be taken by a user on a grouping of data items within the user interface. An example of such a user interface can be within an email client used to manage email messages. Email messages can be grouped according to a grouping factor and a bulk action can be taken on a grouping from within the user interface. | 1. A system for displaying email messages, comprising:
a client device comprising a processor and a memory; and a client application executable by the client device, the client application causing the client device to at least:
obtain a plurality of emails associated with a user account from an email server;
render the at least a subset of the plurality of emails in an inbox user interface, wherein the inbox user interface displays a visual reference to each of the at least a subset of the plurality of emails;
detect a particular gesture from an input device associated with the client device, the particular gesture being associated with a group user interface;
group another subset of the plurality of emails into respective groups based upon a grouping parameter, the other subset of emails including the at least a subset of the plurality of emails; and
render the group user interface in which the other subset of the plurality of emails is depicted in respective groups according to the grouping parameter. 2. The system of claim 1, wherein the grouping parameter comprises at least one time period. 3. The system of claim 2, wherein the at least one time period comprises a first time period corresponding to a most recent time period and at least one other time period corresponding to at least one earlier time period, wherein the most recent time period is smaller than the at least one earlier time period. 4. The system of claim 3, wherein the at least one earlier time period comprises a plurality of time periods and a respective size of each of the plurality of time periods is larger the more temporally removed from the most recent time period. 5. The system of claim 1, wherein the grouping parameter comprises a tag associated with respective ones of the plurality of email messages, a user group of a sender of respective ones of the plurality of email messages, or a location of a sender of respective ones of the plurality of email messages. 6. The system of claim 1, wherein the client application further causes the client device to at least:
detect a bulk action gesture in the group user interface on one of the respective groups, the bulk action gesture comprising a sliding gesture; generate a sliding animation in response to detecting the bulk action gesture; display an icon indicating a bulk action within the sliding animation; and perform a particular action on a respective plurality of emails associated with the one of the respective groups. 7. The system of claim 6, wherein the particular action comprises at least one of an archiving of the respective plurality of emails or deletion of the respective plurality of emails. 8. A method for performing a device posture assessment during authentication of a user, comprising:
obtaining a plurality of emails associated with a user account from an email server; rendering the at least a subset of the plurality of emails in an inbox user interface, wherein the inbox user interface displays a visual reference to each of the at least a subset of the plurality of emails; detecting a particular gesture from an input device associated with the client device, the particular gesture being associated with a group user interface; grouping another subset of the plurality of emails into respective groups based upon a grouping parameter, the other subset of emails including the at least a subset of the plurality of emails; and rendering the group user interface in which the other subset of the plurality of emails is depicted in respective groups according to the grouping parameter. 9. The method of claim 8, wherein the grouping parameter comprises at least one time period. 10. The method of claim 9, wherein the at least one time period comprises a first time period corresponding to a most recent time period and at least one other time period corresponding to at least one earlier time period, wherein the most recent time period is smaller than the at least one earlier time period. 11. The method of claim 10, wherein the at least one earlier time period comprises a plurality of time periods and a respective size of each of the plurality of time periods is larger the more temporally removed from the most recent time period. 12. The method of claim 8, wherein the grouping parameter comprises a tag associated with respective ones of the plurality of email messages, a user group of a sender of respective ones of the plurality of email messages, or a location of a sender of respective ones of the plurality of email messages. 13. The method of claim 8, further comprising:
detecting a bulk action gesture in the group user interface on one of the respective groups, the bulk action gesture comprising a sliding gesture; generating a sliding animation in response to detecting the bulk action gesture; displaying an icon indicating a bulk action within the sliding animation; and performing a particular action on a respective plurality of emails associated with the one of the respective groups, wherein the particular action comprises at least one of an archiving of the respective plurality of emails or deletion of the respective plurality of emails. 14. The method of claim 13, wherein the particular action comprises at least one of an archiving of the respective plurality of emails or deletion of the respective plurality of emails. 15. A non-transitory computer-readable medium comprising machine-readable instructions for displaying email messages on a client device, wherein when executed by a processor of the client device, the machine-readable instructions cause the client device to at least:
obtain a plurality of emails associated with a user account from an email server; render the at least a subset of the plurality of emails in an inbox user interface, wherein the inbox user interface displays a visual reference to each of the at least a subset of the plurality of emails; detect a particular gesture from an input device associated with the client device, the particular gesture being associated with a group user interface; group another subset of the plurality of emails into respective groups based upon a grouping parameter, the other subset of emails including the at least a subset of the plurality of emails; and render the group user interface in which the other subset of the plurality of emails is depicted in respective groups according to the grouping parameter. 16. The non-transitory computer-readable medium of claim 15, wherein the grouping parameter comprises at least one time period. 17. The non-transitory computer-readable medium of claim 16, wherein the at least one time period comprises a first time period corresponding to a most recent time period and at least one other time period corresponding to at least one earlier time period, wherein the most recent time period is smaller than the at least one earlier time period. 18. The non-transitory computer-readable medium of claim 17, wherein the at least one earlier time period comprises a plurality of time periods and a respective size of each of the plurality of time periods is larger the more temporally removed from the most recent time period. 19. The non-transitory computer-readable medium of claim 15, wherein the grouping parameter comprises a tag associated with respective ones of the plurality of email messages, a user group of a sender of respective ones of the plurality of email messages, or a location of a sender of respective ones of the plurality of email messages. 20. The non-transitory computer-readable medium of claim 15, the machine-readable instructions further causing the client device to at least:
detect a bulk action gesture in the group user interface on one of the respective groups, the bulk action gesture comprising a sliding gesture; generate a sliding animation in response to detecting the bulk action gesture; display an icon indicating a bulk action within the sliding animation; and perform a particular action on a respective plurality of emails associated with the one of the respective groups, wherein the particular action comprises at least one of an archiving of the respective plurality of emails or deletion of the respective plurality of emails. | Disclosed are various approaches for generating a user interface in which data items are grouped together. Additionally, a bulk action can be taken by a user on a grouping of data items within the user interface. An example of such a user interface can be within an email client used to manage email messages. Email messages can be grouped according to a grouping factor and a bulk action can be taken on a grouping from within the user interface.1. A system for displaying email messages, comprising:
a client device comprising a processor and a memory; and a client application executable by the client device, the client application causing the client device to at least:
obtain a plurality of emails associated with a user account from an email server;
render the at least a subset of the plurality of emails in an inbox user interface, wherein the inbox user interface displays a visual reference to each of the at least a subset of the plurality of emails;
detect a particular gesture from an input device associated with the client device, the particular gesture being associated with a group user interface;
group another subset of the plurality of emails into respective groups based upon a grouping parameter, the other subset of emails including the at least a subset of the plurality of emails; and
render the group user interface in which the other subset of the plurality of emails is depicted in respective groups according to the grouping parameter. 2. The system of claim 1, wherein the grouping parameter comprises at least one time period. 3. The system of claim 2, wherein the at least one time period comprises a first time period corresponding to a most recent time period and at least one other time period corresponding to at least one earlier time period, wherein the most recent time period is smaller than the at least one earlier time period. 4. The system of claim 3, wherein the at least one earlier time period comprises a plurality of time periods and a respective size of each of the plurality of time periods is larger the more temporally removed from the most recent time period. 5. The system of claim 1, wherein the grouping parameter comprises a tag associated with respective ones of the plurality of email messages, a user group of a sender of respective ones of the plurality of email messages, or a location of a sender of respective ones of the plurality of email messages. 6. The system of claim 1, wherein the client application further causes the client device to at least:
detect a bulk action gesture in the group user interface on one of the respective groups, the bulk action gesture comprising a sliding gesture; generate a sliding animation in response to detecting the bulk action gesture; display an icon indicating a bulk action within the sliding animation; and perform a particular action on a respective plurality of emails associated with the one of the respective groups. 7. The system of claim 6, wherein the particular action comprises at least one of an archiving of the respective plurality of emails or deletion of the respective plurality of emails. 8. A method for performing a device posture assessment during authentication of a user, comprising:
obtaining a plurality of emails associated with a user account from an email server; rendering the at least a subset of the plurality of emails in an inbox user interface, wherein the inbox user interface displays a visual reference to each of the at least a subset of the plurality of emails; detecting a particular gesture from an input device associated with the client device, the particular gesture being associated with a group user interface; grouping another subset of the plurality of emails into respective groups based upon a grouping parameter, the other subset of emails including the at least a subset of the plurality of emails; and rendering the group user interface in which the other subset of the plurality of emails is depicted in respective groups according to the grouping parameter. 9. The method of claim 8, wherein the grouping parameter comprises at least one time period. 10. The method of claim 9, wherein the at least one time period comprises a first time period corresponding to a most recent time period and at least one other time period corresponding to at least one earlier time period, wherein the most recent time period is smaller than the at least one earlier time period. 11. The method of claim 10, wherein the at least one earlier time period comprises a plurality of time periods and a respective size of each of the plurality of time periods is larger the more temporally removed from the most recent time period. 12. The method of claim 8, wherein the grouping parameter comprises a tag associated with respective ones of the plurality of email messages, a user group of a sender of respective ones of the plurality of email messages, or a location of a sender of respective ones of the plurality of email messages. 13. The method of claim 8, further comprising:
detecting a bulk action gesture in the group user interface on one of the respective groups, the bulk action gesture comprising a sliding gesture; generating a sliding animation in response to detecting the bulk action gesture; displaying an icon indicating a bulk action within the sliding animation; and performing a particular action on a respective plurality of emails associated with the one of the respective groups, wherein the particular action comprises at least one of an archiving of the respective plurality of emails or deletion of the respective plurality of emails. 14. The method of claim 13, wherein the particular action comprises at least one of an archiving of the respective plurality of emails or deletion of the respective plurality of emails. 15. A non-transitory computer-readable medium comprising machine-readable instructions for displaying email messages on a client device, wherein when executed by a processor of the client device, the machine-readable instructions cause the client device to at least:
obtain a plurality of emails associated with a user account from an email server; render the at least a subset of the plurality of emails in an inbox user interface, wherein the inbox user interface displays a visual reference to each of the at least a subset of the plurality of emails; detect a particular gesture from an input device associated with the client device, the particular gesture being associated with a group user interface; group another subset of the plurality of emails into respective groups based upon a grouping parameter, the other subset of emails including the at least a subset of the plurality of emails; and render the group user interface in which the other subset of the plurality of emails is depicted in respective groups according to the grouping parameter. 16. The non-transitory computer-readable medium of claim 15, wherein the grouping parameter comprises at least one time period. 17. The non-transitory computer-readable medium of claim 16, wherein the at least one time period comprises a first time period corresponding to a most recent time period and at least one other time period corresponding to at least one earlier time period, wherein the most recent time period is smaller than the at least one earlier time period. 18. The non-transitory computer-readable medium of claim 17, wherein the at least one earlier time period comprises a plurality of time periods and a respective size of each of the plurality of time periods is larger the more temporally removed from the most recent time period. 19. The non-transitory computer-readable medium of claim 15, wherein the grouping parameter comprises a tag associated with respective ones of the plurality of email messages, a user group of a sender of respective ones of the plurality of email messages, or a location of a sender of respective ones of the plurality of email messages. 20. The non-transitory computer-readable medium of claim 15, the machine-readable instructions further causing the client device to at least:
detect a bulk action gesture in the group user interface on one of the respective groups, the bulk action gesture comprising a sliding gesture; generate a sliding animation in response to detecting the bulk action gesture; display an icon indicating a bulk action within the sliding animation; and perform a particular action on a respective plurality of emails associated with the one of the respective groups, wherein the particular action comprises at least one of an archiving of the respective plurality of emails or deletion of the respective plurality of emails. | 2,100 |
6,517 | 6,517 | 15,183,226 | 2,177 | A computing device is described which has a memory storing text input by a user. The computing device has a processor which is configured to send the text to a prediction engine having been trained to predict images from text. The processor is configured to receive from the prediction engine, in response to the sent text, a plurality of predictions, each prediction comprising an image predicted as being relevant to the text. The processor is configured to insert a plurality of the images into the text on the basis of criteria comprising one or more of: ranks of the predictions, categories of the images, rules associated with one or more of the images, user input, a trigger word. The processor is configured to insert the plurality of images into the text sequentially, in an order corresponding to ranks of the predictions. | 1. A computing device comprising:
a memory storing text input by a user; a processor configured to send the text to a prediction engine having been trained to predict images from text; the processor configured to receive from the prediction engine, in response to the sent text, a plurality of predictions, each prediction comprising an image predicted as being relevant to the text; the processor configured to insert a plurality of the images into the text on the basis of criteria comprising one or more of: ranks of the predictions, categories of the images, rules associated with one or more of the images, user input, a trigger word; and wherein the processor is configured to insert the plurality of images into the text sequentially, in an order corresponding to ranks of the predictions. 2. The computing device of claim 1 wherein the processor is configured to insert the plurality of images into the text in a manner responsive to a single user interaction. 3. The computing device of claim 2 wherein the processor is configured to control the speed of the insertion of the plurality of images into the text according to the duration of the single user interaction. 4. The computing device of claim 1 wherein the processor is configured to insert the images into the text in an order based on the ranks of the predictions and based on categories of the images. 5. The computing device of claim 1 wherein the processor is configured to insert the images into the text with the positions of the inserted images relative to one another based on the ranks of the predictions. 6. The computing device of claim 1 wherein the processor is configured to insert the images into the text with the positions of the inserted images relative to one another based on the ranks of the predictions and based on categories of the images. 7. The computing device of claim 1 wherein the criteria comprise user input selecting an automated image insertion function. 8. The computing device of claim 7 wherein the processor is configured to insert the images only concurrently with the user input. 9. The computing device of claim 1 wherein the criteria comprise detection of a trigger word as part of the text. 10. The computing device of claim 1 wherein the predictions comprise at least one pair of co-occurring images, the prediction engine having been trained to predict pairs of co-occurring images. 11. The computing device of claim 1 wherein the criteria comprise one or more rules associated with an image, the processor being configured to access one or more rules from a memory for at least one of the predictions, and to insert the at least one predicted image into the text at a location selected using the one or more rules. 12. The computing device of claim 1 wherein the processor is configured to provide feedback to the user when insertion of the images is going to commence. 13. The computing device of claim 1 wherein the processor is configured to provide feedback to the user about progress of the insertion of the images. 14. The computing device of claim 1 wherein the predictions additionally comprise predicted words or predicted phrases, and wherein the processor is configured to offer for input predicted images associated with the predicted words or predicted phrases. 15. The computing device of claim 1 wherein the prediction engine is integral with the computing device. 16. A computing device comprising:
means for storing text input by a user; means for sending the text to a prediction engine having been trained to predict images from text; means for receiving from the prediction engine, in response to the sent text, a plurality of predictions, each prediction comprising an image predicted as being relevant to the text; and means for inserting a plurality of the images into the text sequentially in an order based on ranks of the predictions and on the basis of criteria comprising one or more of: ranks of the predictions, categories of the images, rules associated with one or more of the images, user input, a trigger word. 17. A computer-implemented method comprising:
storing, at a memory, text input by a user; sending the text to a prediction engine having been trained to predict words and images from text; receiving from the prediction engine, in response to the sent text, a plurality of images predicted as being relevant to the text, and one or more words predicted to follow the text input by the user; and inserting, using a processor, a plurality of the images into the text sequentially in an order based on ranks of the predictions. 18. The computer implemented method of claim 17 comprising insert the plurality of images into the text in a manner responsive to a single user interaction. 19. The computer implemented method of claim 17 comprising receiving user input selecting an automated image insertion function and inserting the images into the text after receiving the user input. 20. The computer implemented method of claim 17 comprising receiving user input and inserting the one or more images during the user input, and stopping inserting the one or more images when the user input ends. | A computing device is described which has a memory storing text input by a user. The computing device has a processor which is configured to send the text to a prediction engine having been trained to predict images from text. The processor is configured to receive from the prediction engine, in response to the sent text, a plurality of predictions, each prediction comprising an image predicted as being relevant to the text. The processor is configured to insert a plurality of the images into the text on the basis of criteria comprising one or more of: ranks of the predictions, categories of the images, rules associated with one or more of the images, user input, a trigger word. The processor is configured to insert the plurality of images into the text sequentially, in an order corresponding to ranks of the predictions.1. A computing device comprising:
a memory storing text input by a user; a processor configured to send the text to a prediction engine having been trained to predict images from text; the processor configured to receive from the prediction engine, in response to the sent text, a plurality of predictions, each prediction comprising an image predicted as being relevant to the text; the processor configured to insert a plurality of the images into the text on the basis of criteria comprising one or more of: ranks of the predictions, categories of the images, rules associated with one or more of the images, user input, a trigger word; and wherein the processor is configured to insert the plurality of images into the text sequentially, in an order corresponding to ranks of the predictions. 2. The computing device of claim 1 wherein the processor is configured to insert the plurality of images into the text in a manner responsive to a single user interaction. 3. The computing device of claim 2 wherein the processor is configured to control the speed of the insertion of the plurality of images into the text according to the duration of the single user interaction. 4. The computing device of claim 1 wherein the processor is configured to insert the images into the text in an order based on the ranks of the predictions and based on categories of the images. 5. The computing device of claim 1 wherein the processor is configured to insert the images into the text with the positions of the inserted images relative to one another based on the ranks of the predictions. 6. The computing device of claim 1 wherein the processor is configured to insert the images into the text with the positions of the inserted images relative to one another based on the ranks of the predictions and based on categories of the images. 7. The computing device of claim 1 wherein the criteria comprise user input selecting an automated image insertion function. 8. The computing device of claim 7 wherein the processor is configured to insert the images only concurrently with the user input. 9. The computing device of claim 1 wherein the criteria comprise detection of a trigger word as part of the text. 10. The computing device of claim 1 wherein the predictions comprise at least one pair of co-occurring images, the prediction engine having been trained to predict pairs of co-occurring images. 11. The computing device of claim 1 wherein the criteria comprise one or more rules associated with an image, the processor being configured to access one or more rules from a memory for at least one of the predictions, and to insert the at least one predicted image into the text at a location selected using the one or more rules. 12. The computing device of claim 1 wherein the processor is configured to provide feedback to the user when insertion of the images is going to commence. 13. The computing device of claim 1 wherein the processor is configured to provide feedback to the user about progress of the insertion of the images. 14. The computing device of claim 1 wherein the predictions additionally comprise predicted words or predicted phrases, and wherein the processor is configured to offer for input predicted images associated with the predicted words or predicted phrases. 15. The computing device of claim 1 wherein the prediction engine is integral with the computing device. 16. A computing device comprising:
means for storing text input by a user; means for sending the text to a prediction engine having been trained to predict images from text; means for receiving from the prediction engine, in response to the sent text, a plurality of predictions, each prediction comprising an image predicted as being relevant to the text; and means for inserting a plurality of the images into the text sequentially in an order based on ranks of the predictions and on the basis of criteria comprising one or more of: ranks of the predictions, categories of the images, rules associated with one or more of the images, user input, a trigger word. 17. A computer-implemented method comprising:
storing, at a memory, text input by a user; sending the text to a prediction engine having been trained to predict words and images from text; receiving from the prediction engine, in response to the sent text, a plurality of images predicted as being relevant to the text, and one or more words predicted to follow the text input by the user; and inserting, using a processor, a plurality of the images into the text sequentially in an order based on ranks of the predictions. 18. The computer implemented method of claim 17 comprising insert the plurality of images into the text in a manner responsive to a single user interaction. 19. The computer implemented method of claim 17 comprising receiving user input selecting an automated image insertion function and inserting the images into the text after receiving the user input. 20. The computer implemented method of claim 17 comprising receiving user input and inserting the one or more images during the user input, and stopping inserting the one or more images when the user input ends. | 2,100 |
6,518 | 6,518 | 16,026,670 | 2,117 | An embodiment of a method of detecting and correcting for spiraling in a downhole carrier includes: deploying the carrier in a borehole in an earth formation as part of a subterranean operation; acquiring time based data from at least one sensor disposed at the carrier; acquiring time and depth data, the time and depth data correlating time values with depths of the carrier; generating a depth based profile based on the time based data and the time and depth data; generating a frequency profile by transforming the depth based profile into the frequency domain; detecting a spiraling event based on an amplitude of the frequency profile; and taking corrective action based on detecting the spiraling event. | 1. A method of detecting and correcting for spiraling in a downhole carrier, the method comprising:
deploying the carrier in a borehole in an earth formation as part of a subterranean operation; collecting parameter data by measuring a parameter with at least one sensor disposed at the carrier; generating, from the parameter data, a spectrum; analyzing the spectrum to detect a spiraling event by identifying an amplitude of the spectrum that exceeds a threshold; and taking a corrective action based on detecting the spiraling event. 2. The method of claim 1, wherein the collected parameter data is depth based parameter data and the spectrum is generated from parameter data in a selected depth window. 3. The method of claim 1, wherein the spectrum is generated by a Fourier Transformation. 4. The method of claim 1, wherein the carrier is a drill string and the subterranean operation is drilling into the earth formation, and detecting the spiraling event includes evaluating at least one of a frequency, a wavelength, and a wavenumber of the spectrum that corresponds to the identified amplitude. 5. The method of claim 4, wherein the at least one of the frequency, the wavelength and the wavenumber corresponds to a distance along the carrier between a drill bit and a component that contacts a borehole wall during drilling. 6. The method of claim 1, further comprising generating a spectrogram, wherein the spectrogram comprises at least a first and a second spectrum. 7. The method of claim 1, wherein the amplitude correlates with an energy value, and the threshold is based on a total energy of the spectrum. 8. The method of claim 1, wherein the corrective action is selected from at least one of alerting a user and changing an operational parameter. 9. The method of claim 1, wherein detecting the spiraling event is performed while the carrier is deployed in the borehole during the subterranean operation. 10. The method of claim 1, wherein the parameter data is at least one of directional data and bending moment data. 11. The method of claim 1, further comprising estimating a deflection associated with the detected spiraling based on the parameter data. 12. The method of claim 1, further comprising applying a filter to the parameter data prior to generating the spectrum. 13. A system for detecting and correcting for spiraling in a downhole carrier, the system comprising:
a carrier configured to be deployed in a borehole in an earth formation as part of a subterranean operation; at least one sensor disposed at the carrier, the at least one sensor configured to collect parameter data; and a processor configured to perform:
generating from the parameter data a spectrum;
analyzing the spectrum to detect a spiraling event by identifying an amplitude of the spectrum that exceeds a threshold; and
taking a corrective action based on detecting the spiraling event. 14. The system of claim 13, wherein the collected parameter data is depth based parameter data and the spectrum is generated from parameter data in a selected depth window. 15. The system of claim 13, wherein the carrier is a drill string and the subterranean operation is drilling into the earth formation, and detecting the spiraling event includes evaluating at least one of a frequency, a wavelength, and a wavenumber of the spectrum that corresponds to the identified amplitude, the at least one frequency, wavelength, and wavenumber corresponding to a distance along the carrier between a drill bit and a component that contacts a borehole wall during drilling. 16. The system of claim 13, wherein
the amplitude correlates with an energy value, and the threshold is based on a total energy of the spectrum. 17. The system of claim 13, wherein the processor is configured to detect the spiraling event while the carrier is deployed in the borehole during the subterranean operation. 18. The system of claim 13, wherein the parameter data is at least one of directional data and bending moment data. 19. The system of claim 13, wherein the processor is further configured to estimate a deflection associated with the detected spiraling based on the parameter data. 20. The system of claim 13, wherein the processor is further configured to apply a filter to the parameter data prior to generating the spectrum. | An embodiment of a method of detecting and correcting for spiraling in a downhole carrier includes: deploying the carrier in a borehole in an earth formation as part of a subterranean operation; acquiring time based data from at least one sensor disposed at the carrier; acquiring time and depth data, the time and depth data correlating time values with depths of the carrier; generating a depth based profile based on the time based data and the time and depth data; generating a frequency profile by transforming the depth based profile into the frequency domain; detecting a spiraling event based on an amplitude of the frequency profile; and taking corrective action based on detecting the spiraling event.1. A method of detecting and correcting for spiraling in a downhole carrier, the method comprising:
deploying the carrier in a borehole in an earth formation as part of a subterranean operation; collecting parameter data by measuring a parameter with at least one sensor disposed at the carrier; generating, from the parameter data, a spectrum; analyzing the spectrum to detect a spiraling event by identifying an amplitude of the spectrum that exceeds a threshold; and taking a corrective action based on detecting the spiraling event. 2. The method of claim 1, wherein the collected parameter data is depth based parameter data and the spectrum is generated from parameter data in a selected depth window. 3. The method of claim 1, wherein the spectrum is generated by a Fourier Transformation. 4. The method of claim 1, wherein the carrier is a drill string and the subterranean operation is drilling into the earth formation, and detecting the spiraling event includes evaluating at least one of a frequency, a wavelength, and a wavenumber of the spectrum that corresponds to the identified amplitude. 5. The method of claim 4, wherein the at least one of the frequency, the wavelength and the wavenumber corresponds to a distance along the carrier between a drill bit and a component that contacts a borehole wall during drilling. 6. The method of claim 1, further comprising generating a spectrogram, wherein the spectrogram comprises at least a first and a second spectrum. 7. The method of claim 1, wherein the amplitude correlates with an energy value, and the threshold is based on a total energy of the spectrum. 8. The method of claim 1, wherein the corrective action is selected from at least one of alerting a user and changing an operational parameter. 9. The method of claim 1, wherein detecting the spiraling event is performed while the carrier is deployed in the borehole during the subterranean operation. 10. The method of claim 1, wherein the parameter data is at least one of directional data and bending moment data. 11. The method of claim 1, further comprising estimating a deflection associated with the detected spiraling based on the parameter data. 12. The method of claim 1, further comprising applying a filter to the parameter data prior to generating the spectrum. 13. A system for detecting and correcting for spiraling in a downhole carrier, the system comprising:
a carrier configured to be deployed in a borehole in an earth formation as part of a subterranean operation; at least one sensor disposed at the carrier, the at least one sensor configured to collect parameter data; and a processor configured to perform:
generating from the parameter data a spectrum;
analyzing the spectrum to detect a spiraling event by identifying an amplitude of the spectrum that exceeds a threshold; and
taking a corrective action based on detecting the spiraling event. 14. The system of claim 13, wherein the collected parameter data is depth based parameter data and the spectrum is generated from parameter data in a selected depth window. 15. The system of claim 13, wherein the carrier is a drill string and the subterranean operation is drilling into the earth formation, and detecting the spiraling event includes evaluating at least one of a frequency, a wavelength, and a wavenumber of the spectrum that corresponds to the identified amplitude, the at least one frequency, wavelength, and wavenumber corresponding to a distance along the carrier between a drill bit and a component that contacts a borehole wall during drilling. 16. The system of claim 13, wherein
the amplitude correlates with an energy value, and the threshold is based on a total energy of the spectrum. 17. The system of claim 13, wherein the processor is configured to detect the spiraling event while the carrier is deployed in the borehole during the subterranean operation. 18. The system of claim 13, wherein the parameter data is at least one of directional data and bending moment data. 19. The system of claim 13, wherein the processor is further configured to estimate a deflection associated with the detected spiraling based on the parameter data. 20. The system of claim 13, wherein the processor is further configured to apply a filter to the parameter data prior to generating the spectrum. | 2,100 |
6,519 | 6,519 | 15,297,172 | 2,196 | Example methods are provided for a first node to perform identifier (ID) allocation in a virtualized computing environment that includes a cluster formed by the first node and at least one second node. The method may comprise retrieving, from a pool of IDs associated with the cluster, a batch of IDs to a cache associated with the first node. The pool of IDs may be shared within the cluster and the batch of IDs retrieved for subsequent ID allocation by the first node. The method may also comprise, in response to receiving a request for ID allocation from an ID consumer, allocating one or more IDs from the batch of IDs in the cache to respective one or more objects for unique identification of the one or more objects across the cluster; and sending, to the ID consumer, a response that includes the allocated one or more IDs. | 1. A method for a first node to perform identifier (ID) allocation in a virtualized computing environment that includes a cluster formed by the first node and at least one second node, the method comprising:
retrieving, from a pool of IDs associated with the cluster, a batch of IDs to a cache associated with the first node, wherein the pool of IDs is shared by the first node and at least one second node in the cluster, and the batch of IDs is retrieved for subsequent ID allocation by the first node; and in response to receiving a request for ID allocation from an ID consumer, based on the request, allocating, from the batch of IDs in the cache, one or more IDs to respective one or more objects for unique identification of the one or more objects across the cluster; and sending, to the ID consumer, a response that includes the allocated one or more IDs. 2. The method of claim 1, wherein the allocating the one or more IDs comprises:
in response to determination that the cache is empty or insufficient to meet the request, retrieving a new batch of IDs from the pool of IDs to the cache prior to allocating the one or more IDs. 3. The method of claim 2, wherein the retrieving a new batch of IDs further comprises:
determining whether retrieval of the new batch of IDs from the pool is performed successfully; and in response o determination that the retrieval is performed successfully, updating the cache with the new batch of IDs; but otherwise, in response to determination that the retrieval is performed unsuccessfully, performing a backoff process prior to reattempting the retrieval. 4. The method of claim 3, wherein the determining that the retrieval is performed unsuccessfully comprises:
detecting an exception indicating that the pool of IDs is concurrently accessed by multiple threads executing on the first node, or multiple threads executing on the first node and at least one second node in the cluster. 5. The method of claim 3, wherein the determining that the retrieval is performed successfully comprises:
determining that an attribute associated with the pool of IDs is successfully updated to indicate a last value in the new batch of IDs retrieved from the pool of IDs. 6. The method of claim 1, wherein the allocating the one or more IDs comprises:
allocating the one or more IDs based on a minimum quantity between a first quantity requested by the request and a second quantity available in the cache. 7. The method of claim 1, wherein the allocating the one or more IDs comprises:
allocating the one or more IDs for unique identification of: one or more firewall rules; one or more network address translation (NAT) rules; one or more logical routers; or one or more logical switches in the virtualized computing environment. 8. A non-transitory computer-readable storage medium that includes a set of instructions which, in response to execution by a processor of a first node, cause the processor to perform a method of identifier (ID) allocation in a virtualized computing environment that includes a cluster formed by the first node and at least one second node, the method comprising:
retrieving, from a pool of IDs associated with the cluster, a batch of IDs to a cache associated with the first node, wherein the pool of IDs is shared by the first node and at least one second node in the cluster, and the batch of IDs is retrieved for subsequent ID allocation by the first node; and in response to receiving a request for ID allocation from an ID consumer,
based on the request, allocating, from the batch of IDs in the cache, one or more IDs to respective one or more objects for unique identification of the one or more objects across the cluster; and
sending, to the ID consumer, a response that includes the allocated one or more IDs. 9. The non-transitory computer-readable storage medium of claim 8, wherein the allocating the one or more IDs comprises:
in response to determination that the cache is empty or insufficient to meet the request, retrieving a new batch of IDs from the pool of IDs to the cache prior to allocating the one or more IDs. 10. The non-transitory computer-readable storage medium of claim 9, wherein the retrieving a new batch of IDs further comprises:
determining whether retrieval of the new batch of IDs from the pool is performed successfully; and in response to determination that the retrieval is performed successfully, updating the cache with the new batch of IDs; but otherwise, in response to determination that the retrieval is performed unsuccessfully, performing a backoff process prior to reattempting the retrieval. 11. The non-transitory computer-readable storage medium of claim 10, wherein the determining that the retrieval is performed unsuccessfully comprises:
detecting an exception indicating that the pool of IDs is concurrently accessed by multiple threads executing on the first node, or multiple threads executing on the first node and at least one second node in the cluster. 12. The non-transitory computer-readable storage medium of claim 10, wherein the determining that the retrieval is performed successfully comprises:
determining that an attribute associated with the pool of IDs is successfully updated to indicate a last value in the new batch of IDs retrieved from the pool of IDs. 13. The non-transitory computer-readable storage medium of claim 8, wherein the allocating the one or more IDs comprises:
allocating the one or more IDs based on a minimum quantity between a first quantity requested by the request and a second quantity available in the cache. 14. The non-transitory computer-readable storage medium of claim 8, wherein the allocating the one or more IDs comprises:
allocating the one or more IDs for unique identification of: one or more firewall rules; one or more network address translation (NAT) rules; one or more logical routers; or one or more logical switches in the virtualized computing environment. 15. A first node configured to perform identifier (ID) allocation in a virtualized computing environment that includes a cluster formed by the first node and at least one second node, the first node comprising:
a processor; a cache: and a non-transitory computer-readable medium having stored thereon instructions that, when executed by the processor, cause the processor to: retrieve, from a pool of IDs associated with the cluster, a batch of IDs to the cache, wherein the pool of IDs is shared by the first node and at least one second node in the cluster, and the batch of IDs is retrieved for subsequent ID allocation by the first node; and in response to receiving a request for ID allocation from an ID consumer,
based on the request, allocate, from the batch of IDs in the cache, one or more IDs to respective one or more objects for unique identification of the one or more objects across the cluster; and
send, to the ID consumer, a response that includes the allocated one or more IDs. 16. The first node of claim 15, wherein the instructions for allocating the one or more IDs cause the processor to:
in response to determination that the cache is empty or insufficient to meet the request, retrieve a new batch of IDs from the pool of IDs to the cache prior to allocating the one or more IDs. 17. The first node of claim 16, wherein the instructions for retrieving a new batch of IDs further cause the processor to:
determine whether retrieval of the new batch of IDs from the pool is performed successfully; and in response to determination that the retrieval is performed successfully, update the cache with the new batch of IDs; but otherwise, in response to determination that the retrieval is performed unsuccessfully, perform a backoff process prior to reattempting the retrieval. 18. The first node of claim 17, wherein the instructions for the determining that the retrieval is performed unsuccessfully cause the processor to:
detect an exception indicating that the pool of IDs is concurrently accessed by multiple threads executing on the first node, or multiple threads executing on the first node and at least one second node in the cluster. 19. The first node of claim 17, wherein the instructions for determining that the retrieval is performed successfully cause the processor to:
determine that an attribute associated with the pool of IDs is successfully updated to indicate a last value in the new batch of IDs retrieved from the pool of IDs. 20. The first node of claim 15, wherein the instructions for allocating the one or more IDs cause the processor to:
allocate the one or more IDs based on a minimum quantity between a first quantity requested by the request and a second quantity available in the cache. 21. The first node of claim 15, wherein the instructions for allocating the one or more IDs cause the processor to:
allocate the one or more IDs for unique identification of: one or more firewall rules; one or more network address translation (NAT) rules; one or more logical routers; or one or more logical switches in the virtualized computing environment. | Example methods are provided for a first node to perform identifier (ID) allocation in a virtualized computing environment that includes a cluster formed by the first node and at least one second node. The method may comprise retrieving, from a pool of IDs associated with the cluster, a batch of IDs to a cache associated with the first node. The pool of IDs may be shared within the cluster and the batch of IDs retrieved for subsequent ID allocation by the first node. The method may also comprise, in response to receiving a request for ID allocation from an ID consumer, allocating one or more IDs from the batch of IDs in the cache to respective one or more objects for unique identification of the one or more objects across the cluster; and sending, to the ID consumer, a response that includes the allocated one or more IDs.1. A method for a first node to perform identifier (ID) allocation in a virtualized computing environment that includes a cluster formed by the first node and at least one second node, the method comprising:
retrieving, from a pool of IDs associated with the cluster, a batch of IDs to a cache associated with the first node, wherein the pool of IDs is shared by the first node and at least one second node in the cluster, and the batch of IDs is retrieved for subsequent ID allocation by the first node; and in response to receiving a request for ID allocation from an ID consumer, based on the request, allocating, from the batch of IDs in the cache, one or more IDs to respective one or more objects for unique identification of the one or more objects across the cluster; and sending, to the ID consumer, a response that includes the allocated one or more IDs. 2. The method of claim 1, wherein the allocating the one or more IDs comprises:
in response to determination that the cache is empty or insufficient to meet the request, retrieving a new batch of IDs from the pool of IDs to the cache prior to allocating the one or more IDs. 3. The method of claim 2, wherein the retrieving a new batch of IDs further comprises:
determining whether retrieval of the new batch of IDs from the pool is performed successfully; and in response o determination that the retrieval is performed successfully, updating the cache with the new batch of IDs; but otherwise, in response to determination that the retrieval is performed unsuccessfully, performing a backoff process prior to reattempting the retrieval. 4. The method of claim 3, wherein the determining that the retrieval is performed unsuccessfully comprises:
detecting an exception indicating that the pool of IDs is concurrently accessed by multiple threads executing on the first node, or multiple threads executing on the first node and at least one second node in the cluster. 5. The method of claim 3, wherein the determining that the retrieval is performed successfully comprises:
determining that an attribute associated with the pool of IDs is successfully updated to indicate a last value in the new batch of IDs retrieved from the pool of IDs. 6. The method of claim 1, wherein the allocating the one or more IDs comprises:
allocating the one or more IDs based on a minimum quantity between a first quantity requested by the request and a second quantity available in the cache. 7. The method of claim 1, wherein the allocating the one or more IDs comprises:
allocating the one or more IDs for unique identification of: one or more firewall rules; one or more network address translation (NAT) rules; one or more logical routers; or one or more logical switches in the virtualized computing environment. 8. A non-transitory computer-readable storage medium that includes a set of instructions which, in response to execution by a processor of a first node, cause the processor to perform a method of identifier (ID) allocation in a virtualized computing environment that includes a cluster formed by the first node and at least one second node, the method comprising:
retrieving, from a pool of IDs associated with the cluster, a batch of IDs to a cache associated with the first node, wherein the pool of IDs is shared by the first node and at least one second node in the cluster, and the batch of IDs is retrieved for subsequent ID allocation by the first node; and in response to receiving a request for ID allocation from an ID consumer,
based on the request, allocating, from the batch of IDs in the cache, one or more IDs to respective one or more objects for unique identification of the one or more objects across the cluster; and
sending, to the ID consumer, a response that includes the allocated one or more IDs. 9. The non-transitory computer-readable storage medium of claim 8, wherein the allocating the one or more IDs comprises:
in response to determination that the cache is empty or insufficient to meet the request, retrieving a new batch of IDs from the pool of IDs to the cache prior to allocating the one or more IDs. 10. The non-transitory computer-readable storage medium of claim 9, wherein the retrieving a new batch of IDs further comprises:
determining whether retrieval of the new batch of IDs from the pool is performed successfully; and in response to determination that the retrieval is performed successfully, updating the cache with the new batch of IDs; but otherwise, in response to determination that the retrieval is performed unsuccessfully, performing a backoff process prior to reattempting the retrieval. 11. The non-transitory computer-readable storage medium of claim 10, wherein the determining that the retrieval is performed unsuccessfully comprises:
detecting an exception indicating that the pool of IDs is concurrently accessed by multiple threads executing on the first node, or multiple threads executing on the first node and at least one second node in the cluster. 12. The non-transitory computer-readable storage medium of claim 10, wherein the determining that the retrieval is performed successfully comprises:
determining that an attribute associated with the pool of IDs is successfully updated to indicate a last value in the new batch of IDs retrieved from the pool of IDs. 13. The non-transitory computer-readable storage medium of claim 8, wherein the allocating the one or more IDs comprises:
allocating the one or more IDs based on a minimum quantity between a first quantity requested by the request and a second quantity available in the cache. 14. The non-transitory computer-readable storage medium of claim 8, wherein the allocating the one or more IDs comprises:
allocating the one or more IDs for unique identification of: one or more firewall rules; one or more network address translation (NAT) rules; one or more logical routers; or one or more logical switches in the virtualized computing environment. 15. A first node configured to perform identifier (ID) allocation in a virtualized computing environment that includes a cluster formed by the first node and at least one second node, the first node comprising:
a processor; a cache: and a non-transitory computer-readable medium having stored thereon instructions that, when executed by the processor, cause the processor to: retrieve, from a pool of IDs associated with the cluster, a batch of IDs to the cache, wherein the pool of IDs is shared by the first node and at least one second node in the cluster, and the batch of IDs is retrieved for subsequent ID allocation by the first node; and in response to receiving a request for ID allocation from an ID consumer,
based on the request, allocate, from the batch of IDs in the cache, one or more IDs to respective one or more objects for unique identification of the one or more objects across the cluster; and
send, to the ID consumer, a response that includes the allocated one or more IDs. 16. The first node of claim 15, wherein the instructions for allocating the one or more IDs cause the processor to:
in response to determination that the cache is empty or insufficient to meet the request, retrieve a new batch of IDs from the pool of IDs to the cache prior to allocating the one or more IDs. 17. The first node of claim 16, wherein the instructions for retrieving a new batch of IDs further cause the processor to:
determine whether retrieval of the new batch of IDs from the pool is performed successfully; and in response to determination that the retrieval is performed successfully, update the cache with the new batch of IDs; but otherwise, in response to determination that the retrieval is performed unsuccessfully, perform a backoff process prior to reattempting the retrieval. 18. The first node of claim 17, wherein the instructions for the determining that the retrieval is performed unsuccessfully cause the processor to:
detect an exception indicating that the pool of IDs is concurrently accessed by multiple threads executing on the first node, or multiple threads executing on the first node and at least one second node in the cluster. 19. The first node of claim 17, wherein the instructions for determining that the retrieval is performed successfully cause the processor to:
determine that an attribute associated with the pool of IDs is successfully updated to indicate a last value in the new batch of IDs retrieved from the pool of IDs. 20. The first node of claim 15, wherein the instructions for allocating the one or more IDs cause the processor to:
allocate the one or more IDs based on a minimum quantity between a first quantity requested by the request and a second quantity available in the cache. 21. The first node of claim 15, wherein the instructions for allocating the one or more IDs cause the processor to:
allocate the one or more IDs for unique identification of: one or more firewall rules; one or more network address translation (NAT) rules; one or more logical routers; or one or more logical switches in the virtualized computing environment. | 2,100 |
6,520 | 6,520 | 13,723,396 | 2,159 | A computer-implemented system and method of sharing files between a link sharer and a link recipient over a network. A folder sharing link is generated in response to a request by a link sharer, where the link provides a link recipient the ability to modify the contents of the folder. In response to receiving an indication that the generated link has been activated by a link recipient, the system either automatically grants modification rights to the folder or requests manual approval from the link sharer to grant modification rights to the link recipient. Once modification rights have been granted, the system adds the shared folder to the link recipient's account within the context of a document management system. | 1. A computer-implemented method comprising:
a. receiving a request, from a link sharer, to generate a link that, when activated, facilitates providing modification rights to a folder of digital content; b. in response to said request, generating a link that, when activated by a link recipient, facilitates providing modification rights to said folder; c. receiving an indication that said link has been activated; and d. in response to receiving said indication, facilitating the provision of modification rights, to the link recipient, to said folder. 2. The computer-implemented method of claim 1, wherein said step of facilitating the provision of modification rights to said folder comprises providing modification rights to said folder. 3. The computer-implemented method of claim 1, wherein said step of receiving said request to generate a link comprises receiving said request from a link sharer. 4. The computer-implemented method of claim 3, wherein said link sharer in an owner of said folder. 5. The computer-implemented method of claim 4, wherein:
a. said step of receiving an indication comprises receiving said indication from a link recipient; and b. said step of facilitating the provision of modification rights to said folder comprises providing said link recipient with modification rights to said folder. 6. The computer-implemented method of claim 1, wherein said step of facilitating the provision of modification rights to said folder comprises:
a. automatically determining whether one or more access criteria are satisfied; and b. at least partially in response to determining that said one or more access criteria are satisfied, providing a user with modification rights to said folder. 7. The computer-implemented method of claim 6, further comprising:
a. determining whether one or more access criteria are satisfied; b. at least partially in response to determining that said one or more access criteria are not satisfied, requesting approval from said link sharer for modification rights to said folder; and c. at least partially in response to receiving said approval from said link sharer, providing said link recipient with modification rights to said folder. 8. The computer-implemented method of claim 1, wherein the one or more access criteria are selected from a group consisting of:
a. the link sharer and the link recipient are members of a common group on a social media web site; and b. the link recipient is within a list of contacts associated with the link sharer. 9. The computer-implemented method of claim 1, wherein the step of providing modification rights to said folder comprises adding the folder to a particular user's account within the context of a document management system. 10. The computer-implemented method of claim 9, wherein the document management system is a synched file sharing system. 11. The computer-implemented method of claim 1, wherein the modification rights include one or more rights selected from a group consisting of:
a. adding digital content to the folder; b. deleting digital content from the shared folder; and c. editing digital content that is stored within the shared folder. 12. A computer-implemented method of sharing files between a link sharer and a link recipient comprising the steps of:
a. in response to receiving a request to share a folder containing digital content, generating a link that, when activated, facilitates providing modification rights to said digital content in said folder; b. at least partially in response to receiving an indication that said folder sharing link has been activated, executing a step that is selected from a group consisting of:
i. automatically granting modification rights to the folder at least partially based on the satisfaction of at least one permission criterion; and
ii. requesting manual approval from a link sharer to provide modification rights to the shared folder. 13. The computer-implemented method of claim 12, wherein modification rights to said shared folder are granted to multiple link recipients within the context of a synched file sharing system. 14. The computer-implemented method of claim 12, wherein said at least one permission criterion is chosen from the group consisting of:
a. said link recipient belong to a common domain with said link sharer; b. said link recipient belonging to the same user-defined group as said link sharer; c. said link recipient's e-mail address being included in the link sharer's contact information; and d. said link recipient and said link sharer being registered users of the same file storage server system. 15. The computer-implemented method of claim 12, further comprising the step of notifying said link sharer when modification rights are granted to said link recipient. 16. The computer-implemented method of claim 12, wherein said modification rights include one or more rights selected from a group consisting of:
a. adding digital content to said folder; b. deleting digital content from said folder; and c. editing digital content in said folder. 17. The computer-implemented method of claim 12, further comprising the step of:
a. receiving a second indication that the link has been activated by a third user; and b. at least partially in response to receiving said second indication, executing a step that is selected from a group consisting of:
i. automatically granting modification rights to said folder; and
ii. requesting manual approval from said first user to grant modification rights to said folder. 18. The computer-implemented method of claim 17, wherein the step of automatically granting modification rights to said folder comprises adding said folder to said third user's account within the context of a document management system. 19. A computer-implemented method of sharing one or more files between users of a file management system, the one or more files being stored within a folder and the method comprising the steps of:
a. at least partially in response to a request from a first user, generating a link, wherein said link provides a recipient of the link modification rights to digital content contained within said folder; b. receiving an indication that said link has been activated by a second user; c. at least partially in response to receiving said indication, executing a step that is selected from a group consisting of:
i. automatically granting modification rights to said folder; and
ii. requesting manual approval from said first user to grant modification rights to said folder,
wherein the modification rights allow said second user the ability to edit digital content contained in said folder. 20. The computer-implemented method of claim 19, wherein said first user is an owner of said digital content. 21. The computer-implemented method of claim 19, wherein automatically granting modification rights further comprises the step of verifying that at least one permission criterion is met by said second user. 22. The computer-implemented method of claim 21, wherein said at least one permission criterion comprises verifying an identity of said second user. 23. The computer-implemented method of claim 19, wherein the step of granting modification rights to said folder comprises adding said folder to said second user's account within the context of a document management system. 24. The computer-implemented method of claim 19, further comprising the step of:
a. receiving an indication that the link has been activated by a third user; and b. at least partially in response to receiving said indication by said third user, executing a step that is selected from a group consisting of:
i. automatically granting modification rights to said folder; and
ii. requesting manual approval from said first user to grant modification rights to said folder. 25. The computer-implemented method of claim 25, wherein the step of automatically granting modification rights to said folder comprises adding said folder to said third user's account within the context of a document management system. 26. A system for providing modification rights to a linked file set, comprising at least one processor configured to:
a. receive a request to generate a link that, when activated, facilitates providing modification rights to a folder of digital content; b. in response to said request, generate a link that, when activated by a link recipient, facilitates providing modification rights to said folder; c. receive an indication that said link has been activated; and d. in response to receiving said indication, facilitate the provision of modification rights, to the link recipient, to said folder. | A computer-implemented system and method of sharing files between a link sharer and a link recipient over a network. A folder sharing link is generated in response to a request by a link sharer, where the link provides a link recipient the ability to modify the contents of the folder. In response to receiving an indication that the generated link has been activated by a link recipient, the system either automatically grants modification rights to the folder or requests manual approval from the link sharer to grant modification rights to the link recipient. Once modification rights have been granted, the system adds the shared folder to the link recipient's account within the context of a document management system.1. A computer-implemented method comprising:
a. receiving a request, from a link sharer, to generate a link that, when activated, facilitates providing modification rights to a folder of digital content; b. in response to said request, generating a link that, when activated by a link recipient, facilitates providing modification rights to said folder; c. receiving an indication that said link has been activated; and d. in response to receiving said indication, facilitating the provision of modification rights, to the link recipient, to said folder. 2. The computer-implemented method of claim 1, wherein said step of facilitating the provision of modification rights to said folder comprises providing modification rights to said folder. 3. The computer-implemented method of claim 1, wherein said step of receiving said request to generate a link comprises receiving said request from a link sharer. 4. The computer-implemented method of claim 3, wherein said link sharer in an owner of said folder. 5. The computer-implemented method of claim 4, wherein:
a. said step of receiving an indication comprises receiving said indication from a link recipient; and b. said step of facilitating the provision of modification rights to said folder comprises providing said link recipient with modification rights to said folder. 6. The computer-implemented method of claim 1, wherein said step of facilitating the provision of modification rights to said folder comprises:
a. automatically determining whether one or more access criteria are satisfied; and b. at least partially in response to determining that said one or more access criteria are satisfied, providing a user with modification rights to said folder. 7. The computer-implemented method of claim 6, further comprising:
a. determining whether one or more access criteria are satisfied; b. at least partially in response to determining that said one or more access criteria are not satisfied, requesting approval from said link sharer for modification rights to said folder; and c. at least partially in response to receiving said approval from said link sharer, providing said link recipient with modification rights to said folder. 8. The computer-implemented method of claim 1, wherein the one or more access criteria are selected from a group consisting of:
a. the link sharer and the link recipient are members of a common group on a social media web site; and b. the link recipient is within a list of contacts associated with the link sharer. 9. The computer-implemented method of claim 1, wherein the step of providing modification rights to said folder comprises adding the folder to a particular user's account within the context of a document management system. 10. The computer-implemented method of claim 9, wherein the document management system is a synched file sharing system. 11. The computer-implemented method of claim 1, wherein the modification rights include one or more rights selected from a group consisting of:
a. adding digital content to the folder; b. deleting digital content from the shared folder; and c. editing digital content that is stored within the shared folder. 12. A computer-implemented method of sharing files between a link sharer and a link recipient comprising the steps of:
a. in response to receiving a request to share a folder containing digital content, generating a link that, when activated, facilitates providing modification rights to said digital content in said folder; b. at least partially in response to receiving an indication that said folder sharing link has been activated, executing a step that is selected from a group consisting of:
i. automatically granting modification rights to the folder at least partially based on the satisfaction of at least one permission criterion; and
ii. requesting manual approval from a link sharer to provide modification rights to the shared folder. 13. The computer-implemented method of claim 12, wherein modification rights to said shared folder are granted to multiple link recipients within the context of a synched file sharing system. 14. The computer-implemented method of claim 12, wherein said at least one permission criterion is chosen from the group consisting of:
a. said link recipient belong to a common domain with said link sharer; b. said link recipient belonging to the same user-defined group as said link sharer; c. said link recipient's e-mail address being included in the link sharer's contact information; and d. said link recipient and said link sharer being registered users of the same file storage server system. 15. The computer-implemented method of claim 12, further comprising the step of notifying said link sharer when modification rights are granted to said link recipient. 16. The computer-implemented method of claim 12, wherein said modification rights include one or more rights selected from a group consisting of:
a. adding digital content to said folder; b. deleting digital content from said folder; and c. editing digital content in said folder. 17. The computer-implemented method of claim 12, further comprising the step of:
a. receiving a second indication that the link has been activated by a third user; and b. at least partially in response to receiving said second indication, executing a step that is selected from a group consisting of:
i. automatically granting modification rights to said folder; and
ii. requesting manual approval from said first user to grant modification rights to said folder. 18. The computer-implemented method of claim 17, wherein the step of automatically granting modification rights to said folder comprises adding said folder to said third user's account within the context of a document management system. 19. A computer-implemented method of sharing one or more files between users of a file management system, the one or more files being stored within a folder and the method comprising the steps of:
a. at least partially in response to a request from a first user, generating a link, wherein said link provides a recipient of the link modification rights to digital content contained within said folder; b. receiving an indication that said link has been activated by a second user; c. at least partially in response to receiving said indication, executing a step that is selected from a group consisting of:
i. automatically granting modification rights to said folder; and
ii. requesting manual approval from said first user to grant modification rights to said folder,
wherein the modification rights allow said second user the ability to edit digital content contained in said folder. 20. The computer-implemented method of claim 19, wherein said first user is an owner of said digital content. 21. The computer-implemented method of claim 19, wherein automatically granting modification rights further comprises the step of verifying that at least one permission criterion is met by said second user. 22. The computer-implemented method of claim 21, wherein said at least one permission criterion comprises verifying an identity of said second user. 23. The computer-implemented method of claim 19, wherein the step of granting modification rights to said folder comprises adding said folder to said second user's account within the context of a document management system. 24. The computer-implemented method of claim 19, further comprising the step of:
a. receiving an indication that the link has been activated by a third user; and b. at least partially in response to receiving said indication by said third user, executing a step that is selected from a group consisting of:
i. automatically granting modification rights to said folder; and
ii. requesting manual approval from said first user to grant modification rights to said folder. 25. The computer-implemented method of claim 25, wherein the step of automatically granting modification rights to said folder comprises adding said folder to said third user's account within the context of a document management system. 26. A system for providing modification rights to a linked file set, comprising at least one processor configured to:
a. receive a request to generate a link that, when activated, facilitates providing modification rights to a folder of digital content; b. in response to said request, generate a link that, when activated by a link recipient, facilitates providing modification rights to said folder; c. receive an indication that said link has been activated; and d. in response to receiving said indication, facilitate the provision of modification rights, to the link recipient, to said folder. | 2,100 |
6,521 | 6,521 | 15,335,011 | 2,165 | A musician discovery system is provided. The musician discovery system includes a first interface for displaying a plurality of musicians organized according to a musical characteristic. The system includes a second interface for presenting multimedia information about a first musician from the plurality of musicians displayed on the first interface. The system includes means for comparing a second plurality of musicians with the first musician using the multimedia information presented on the second interface about the first musician. Furthermore, the system includes a third interface for recommending a second musician from the second plurality of musicians based on the comparing means. | 1-20. (canceled) 21. A computer-assisted method for discovering musicians, comprising:
receiving an input for a first musician; determining a similarity score between the first musician and each of a plurality of further musicians, the similarity score for the first musician relative to each of the further musicians corresponding to a similarity between music of the first musician and music of the corresponding further musician; selecting a second musician and a third musician from the further musicians whose similarity scores are above a first threshold level; determining a popularity score for each of the second and third musicians, the popularity scores corresponding to a popularity rating of the second and third musicians in an external media source; and displaying the ones of the second and third musicians whose popularity scores are above a second threshold level. 22. The method of claim 21, wherein the popularity score is a product of a familiarity score and a factor, the familiarity score being indicative of a respective frequency in which each of the further musicians is identified in the external media source, the factor being a weighting value. 23. The method of claim 22, wherein the weighting value is based on a respective financial parameter of the further musicians. 24. The method of claim 22, wherein the weighting value is based on a respective musical genre of the further musicians. 25. The method of claim 21, wherein the ones of the second and third musicians whose popularity score are above the popularity threshold have a popularity score below a further popularity threshold, the further popularity threshold being greater than the popularity threshold. 26. The method of claim 21, further comprising:
determining a dissimilarity score between the first musician and the further musicians, the dissimilarity score indicative of a musical dissimilarity; selecting at least one fourth musician from the further musicians whose dissimilarity score is above a dissimilarity threshold; determining the popularity score for each of the at least one fourth musician; and displaying the at least one fourth musician whose popularity score is above the popularity threshold. 27. The method of claim 21, further comprising:
displaying first multimedia information of the first musician, the first multimedia information including at least one of a biography, a song, a photo, a blog, a video, and a tweet associated with the first musician. 28. The method of claim 21, further comprising:
displaying an advertisement associated with the first musician. 29. The method of claim 21, wherein the external media source is in communication with at least one of a music database, a website, a photo database, a search engine, and a video database. 30. A system for discovering musicians, comprising:
a transceiver receiving an input for a first musician; a processor determining a similarity score between the first musician and each of a plurality of further musicians, the similarity score for the first musician relative to each of the further musicians corresponding to a similarity between music of the first musician and music of the corresponding further musician, the processor selecting a second musician and a third musician from the further musicians whose similarity scores are above a first threshold level, the processor determining a popularity score for each of the second and third musicians, the popularity scores corresponding to a popularity rating of the second and third musicians in an external media source; and a display device the ones of the second and third musicians whose popularity scores are above a second threshold level. 31. The system of claim 30, wherein the popularity score is a product of a familiarity score and a factor, the familiarity score being indicative of a respective frequency in which each of the further musicians is identified in the external media source, the factor being a weighting value. 32. The system of claim 31, wherein the weighting value is based on a respective financial parameter of the further musicians. 33. The system of claim 31, wherein the weighting value is based on a respective musical genre of the further musicians. 34. The system of claim 30, wherein the ones of the second and third musicians whose popularity score are above the popularity threshold have a popularity score below a further popularity threshold, the further popularity threshold being greater than the popularity threshold. 35. The system of claim 30, wherein the processor further determines a dissimilarity score between the first musician and the further musicians, the dissimilarity score indicative of a musical dissimilarity, the processor further selects at least one fourth musician from the further musicians whose dissimilarity score is above a dissimilarity threshold, the processor further determines the popularity score for each of the at least one fourth musician, and wherein the display device further displays the at least one fourth musician whose popularity score is above the popularity threshold. 36. The system of claim 30, wherein the display device further displays first multimedia information of the first musician, the first multimedia information including at least one of a biography, a song, a photo, a blog, a video, and a tweet associated with the first musician. 37. The system of claim 30, wherein the display device further displays an advertisement associated with the first musician. 38. The system of claim 30, wherein the external media source is in communication with at least one of a music database, a website, a photo database, a search engine, and a video database. | A musician discovery system is provided. The musician discovery system includes a first interface for displaying a plurality of musicians organized according to a musical characteristic. The system includes a second interface for presenting multimedia information about a first musician from the plurality of musicians displayed on the first interface. The system includes means for comparing a second plurality of musicians with the first musician using the multimedia information presented on the second interface about the first musician. Furthermore, the system includes a third interface for recommending a second musician from the second plurality of musicians based on the comparing means.1-20. (canceled) 21. A computer-assisted method for discovering musicians, comprising:
receiving an input for a first musician; determining a similarity score between the first musician and each of a plurality of further musicians, the similarity score for the first musician relative to each of the further musicians corresponding to a similarity between music of the first musician and music of the corresponding further musician; selecting a second musician and a third musician from the further musicians whose similarity scores are above a first threshold level; determining a popularity score for each of the second and third musicians, the popularity scores corresponding to a popularity rating of the second and third musicians in an external media source; and displaying the ones of the second and third musicians whose popularity scores are above a second threshold level. 22. The method of claim 21, wherein the popularity score is a product of a familiarity score and a factor, the familiarity score being indicative of a respective frequency in which each of the further musicians is identified in the external media source, the factor being a weighting value. 23. The method of claim 22, wherein the weighting value is based on a respective financial parameter of the further musicians. 24. The method of claim 22, wherein the weighting value is based on a respective musical genre of the further musicians. 25. The method of claim 21, wherein the ones of the second and third musicians whose popularity score are above the popularity threshold have a popularity score below a further popularity threshold, the further popularity threshold being greater than the popularity threshold. 26. The method of claim 21, further comprising:
determining a dissimilarity score between the first musician and the further musicians, the dissimilarity score indicative of a musical dissimilarity; selecting at least one fourth musician from the further musicians whose dissimilarity score is above a dissimilarity threshold; determining the popularity score for each of the at least one fourth musician; and displaying the at least one fourth musician whose popularity score is above the popularity threshold. 27. The method of claim 21, further comprising:
displaying first multimedia information of the first musician, the first multimedia information including at least one of a biography, a song, a photo, a blog, a video, and a tweet associated with the first musician. 28. The method of claim 21, further comprising:
displaying an advertisement associated with the first musician. 29. The method of claim 21, wherein the external media source is in communication with at least one of a music database, a website, a photo database, a search engine, and a video database. 30. A system for discovering musicians, comprising:
a transceiver receiving an input for a first musician; a processor determining a similarity score between the first musician and each of a plurality of further musicians, the similarity score for the first musician relative to each of the further musicians corresponding to a similarity between music of the first musician and music of the corresponding further musician, the processor selecting a second musician and a third musician from the further musicians whose similarity scores are above a first threshold level, the processor determining a popularity score for each of the second and third musicians, the popularity scores corresponding to a popularity rating of the second and third musicians in an external media source; and a display device the ones of the second and third musicians whose popularity scores are above a second threshold level. 31. The system of claim 30, wherein the popularity score is a product of a familiarity score and a factor, the familiarity score being indicative of a respective frequency in which each of the further musicians is identified in the external media source, the factor being a weighting value. 32. The system of claim 31, wherein the weighting value is based on a respective financial parameter of the further musicians. 33. The system of claim 31, wherein the weighting value is based on a respective musical genre of the further musicians. 34. The system of claim 30, wherein the ones of the second and third musicians whose popularity score are above the popularity threshold have a popularity score below a further popularity threshold, the further popularity threshold being greater than the popularity threshold. 35. The system of claim 30, wherein the processor further determines a dissimilarity score between the first musician and the further musicians, the dissimilarity score indicative of a musical dissimilarity, the processor further selects at least one fourth musician from the further musicians whose dissimilarity score is above a dissimilarity threshold, the processor further determines the popularity score for each of the at least one fourth musician, and wherein the display device further displays the at least one fourth musician whose popularity score is above the popularity threshold. 36. The system of claim 30, wherein the display device further displays first multimedia information of the first musician, the first multimedia information including at least one of a biography, a song, a photo, a blog, a video, and a tweet associated with the first musician. 37. The system of claim 30, wherein the display device further displays an advertisement associated with the first musician. 38. The system of claim 30, wherein the external media source is in communication with at least one of a music database, a website, a photo database, a search engine, and a video database. | 2,100 |
6,522 | 6,522 | 15,844,480 | 2,199 | An asynchronous method is implemented in a manner that reduces the amount of runtime overhead needed to execute the asynchronous method. The data elements needed to suspend an asynchronous method to await completion of an asynchronous operation, to resume the asynchronous method at a resumption point, and to provide a completion status of the caller of the asynchronous method are consolidated into one or two reusable objects. An asynchronous method may be associated with a distinct object pool of reusable objects. The size of a pool and the total size of all pools can be configured statically or dynamically based on runtime conditions. | 1. A system, comprising:
at least one processor and a memory; a program including at least one asynchronous method, the asynchronous method configured to suspend execution in order to await completion of an asynchronous operation; at least one object pool for the at least one asynchronous method, the at least one object pool including one or more reusable objects, the at least one object pool situated in a non-garbage-collected heap; and executable code including instructions that when executed on the at least one processor performs actions that:
consolidate state data needed to suspend and resume execution of the asynchronous method at a resumption point upon completion of an asynchronous operation;
store the state data in a select one of the one or more reusable objects from the object pool of the asynchronous method; and
suspend execution of the asynchronous method to await completion of the asynchronous operation. 2. The system of claim 1, wherein the executable code includes further instructions that when executed on the at least one processor performs actions that:
resume execution of the asynchronous method from the resumption point; and return the select reusable object to the at least one object pool. 3. The system of claim 1, further comprising a compiler that detects an await expression in the asynchronous method and transforms the await expression into the executable code. 4. The system of claim 1, wherein the executable code includes further instructions that when executed on the at least one processor performs actions that:
perform the consolidation of the state data when the asynchronous method awaits completion of an asynchronous operation a first time. 5. The system of claim 1, further comprising an object pool manager that sets
a cumulative limit to a number of reusable objects in all object pools used in the program. 6. The system of claim 1, further comprising an object pool manager that sets a size of the at least one object pool based on previous executions of the program. 7. The system of claim 1, further comprising an object pool manager that dynamically alters a size of the at least one object pool based on memory usage during execution of the program. 8. A method implemented on a computing device having at least one processor and a memory, the method comprising:
obtaining a reusable object from an object pool, the object pool associated with an asynchronous method, the reusable object previously allocated at runtime from a non-garbage-collected heap portion of the memory; consolidating state data needed to suspend and resume execution of an asynchronous method into the reusable object, the asynchronous method configured to be suspended to await completion of the asynchronous operation; suspending execution of the asynchronous method until completion of the asynchronous operation; and releasing execution control back to a caller of the asynchronous method. 9. The method of claim 8, further comprising:
upon completion of the asynchronous operation:
restoring the state data from the reusable object;
releasing the reusable object back to the object pool; and
resuming execution of the asynchronous method at the resumption point. 10. The method of claim 8, further comprising:
wherein the state data includes a state machine structure, an execution context object, a task object, and an action delegate object. 11. The method of claim 8, wherein obtaining a reusable object from the object pool further comprises:
in the event the object pool does not have an available reusable object, allocating a reusable object. 12. The method of claim 8, wherein obtaining a reusable object from the object pool further comprises:
in the event the object pool does not have an available reusable object, awaiting return of an available reusable object. 13. The method of claim 8, wherein obtaining a reusable object from the object pool further comprises:
setting a limit of a number of reusable objects in the object pool based on previous executions of the program. 14. The method of claim 8, wherein obtaining a reusable object from the object pool further comprises:
dynamically increasing a number of reusable objects in the object pool based on current runtime conditions. 15. A computing device, comprising:
at least one processor communicatively coupled to a memory; and wherein the at least one processor is configured to:
maintain one or more reusable objects in an object pool, a reusable object previously allocated at runtime, the object pool for an asynchronous method;
determine that the asynchronous method needs to be suspended to await completion of an asynchronous operation;
consolidate state data needed to suspend and resume execution of the asynchronous method upon completion of the asynchronous operation into a select one of the one or more reusable objects;
suspend execution of the asynchronous method and return execution control back to a caller of the asynchronous method;
upon completion of the asynchronous operation, restore the state data at the resumption point, release the select reusable object back to the object pool, and resume execution of the asynchronous method at the resumption point. 16. The computing device of claim 15, wherein the at least one processor is further configured to:
set a limit on a number of reusable objects in all object pools used in the program. 17. The computing device of claim 15, wherein the at least one processor is further configured to:
dynamically increase a number of reusable objects in the object pool based on runtime conditions. 18. The computing device of claim 15, wherein the at least one processor is configured to:
set a limit of a number of reusable objects in the object pool based on one or more previous executions of the program. 19. The computing device of claim 15, wherein the at least one processor is configured to:
in the event the object pool does not have a reusable object readily available, configure a callback to provide a notification when a reusable object is available. 20. The computing device of claim 15, wherein the at least one processor is configured to:
in the event the object pool does not have a readily available reusable object, allocate a reusable object. | An asynchronous method is implemented in a manner that reduces the amount of runtime overhead needed to execute the asynchronous method. The data elements needed to suspend an asynchronous method to await completion of an asynchronous operation, to resume the asynchronous method at a resumption point, and to provide a completion status of the caller of the asynchronous method are consolidated into one or two reusable objects. An asynchronous method may be associated with a distinct object pool of reusable objects. The size of a pool and the total size of all pools can be configured statically or dynamically based on runtime conditions.1. A system, comprising:
at least one processor and a memory; a program including at least one asynchronous method, the asynchronous method configured to suspend execution in order to await completion of an asynchronous operation; at least one object pool for the at least one asynchronous method, the at least one object pool including one or more reusable objects, the at least one object pool situated in a non-garbage-collected heap; and executable code including instructions that when executed on the at least one processor performs actions that:
consolidate state data needed to suspend and resume execution of the asynchronous method at a resumption point upon completion of an asynchronous operation;
store the state data in a select one of the one or more reusable objects from the object pool of the asynchronous method; and
suspend execution of the asynchronous method to await completion of the asynchronous operation. 2. The system of claim 1, wherein the executable code includes further instructions that when executed on the at least one processor performs actions that:
resume execution of the asynchronous method from the resumption point; and return the select reusable object to the at least one object pool. 3. The system of claim 1, further comprising a compiler that detects an await expression in the asynchronous method and transforms the await expression into the executable code. 4. The system of claim 1, wherein the executable code includes further instructions that when executed on the at least one processor performs actions that:
perform the consolidation of the state data when the asynchronous method awaits completion of an asynchronous operation a first time. 5. The system of claim 1, further comprising an object pool manager that sets
a cumulative limit to a number of reusable objects in all object pools used in the program. 6. The system of claim 1, further comprising an object pool manager that sets a size of the at least one object pool based on previous executions of the program. 7. The system of claim 1, further comprising an object pool manager that dynamically alters a size of the at least one object pool based on memory usage during execution of the program. 8. A method implemented on a computing device having at least one processor and a memory, the method comprising:
obtaining a reusable object from an object pool, the object pool associated with an asynchronous method, the reusable object previously allocated at runtime from a non-garbage-collected heap portion of the memory; consolidating state data needed to suspend and resume execution of an asynchronous method into the reusable object, the asynchronous method configured to be suspended to await completion of the asynchronous operation; suspending execution of the asynchronous method until completion of the asynchronous operation; and releasing execution control back to a caller of the asynchronous method. 9. The method of claim 8, further comprising:
upon completion of the asynchronous operation:
restoring the state data from the reusable object;
releasing the reusable object back to the object pool; and
resuming execution of the asynchronous method at the resumption point. 10. The method of claim 8, further comprising:
wherein the state data includes a state machine structure, an execution context object, a task object, and an action delegate object. 11. The method of claim 8, wherein obtaining a reusable object from the object pool further comprises:
in the event the object pool does not have an available reusable object, allocating a reusable object. 12. The method of claim 8, wherein obtaining a reusable object from the object pool further comprises:
in the event the object pool does not have an available reusable object, awaiting return of an available reusable object. 13. The method of claim 8, wherein obtaining a reusable object from the object pool further comprises:
setting a limit of a number of reusable objects in the object pool based on previous executions of the program. 14. The method of claim 8, wherein obtaining a reusable object from the object pool further comprises:
dynamically increasing a number of reusable objects in the object pool based on current runtime conditions. 15. A computing device, comprising:
at least one processor communicatively coupled to a memory; and wherein the at least one processor is configured to:
maintain one or more reusable objects in an object pool, a reusable object previously allocated at runtime, the object pool for an asynchronous method;
determine that the asynchronous method needs to be suspended to await completion of an asynchronous operation;
consolidate state data needed to suspend and resume execution of the asynchronous method upon completion of the asynchronous operation into a select one of the one or more reusable objects;
suspend execution of the asynchronous method and return execution control back to a caller of the asynchronous method;
upon completion of the asynchronous operation, restore the state data at the resumption point, release the select reusable object back to the object pool, and resume execution of the asynchronous method at the resumption point. 16. The computing device of claim 15, wherein the at least one processor is further configured to:
set a limit on a number of reusable objects in all object pools used in the program. 17. The computing device of claim 15, wherein the at least one processor is further configured to:
dynamically increase a number of reusable objects in the object pool based on runtime conditions. 18. The computing device of claim 15, wherein the at least one processor is configured to:
set a limit of a number of reusable objects in the object pool based on one or more previous executions of the program. 19. The computing device of claim 15, wherein the at least one processor is configured to:
in the event the object pool does not have a reusable object readily available, configure a callback to provide a notification when a reusable object is available. 20. The computing device of claim 15, wherein the at least one processor is configured to:
in the event the object pool does not have a readily available reusable object, allocate a reusable object. | 2,100 |
6,523 | 6,523 | 14,801,067 | 2,178 | Non-limiting examples of the present disclosure describe a collaborative communication system that may interface with one or more command resources. The collaborative communication system may comprise at least one memory and at least one processor operatively connected with the memory to execute operations. In response to command input being received during authoring in a user interface of the collaborative communication system, a query is processed and passed to a command resource. The query comprises parameters of the command input and a context associated with the authoring. A response is received from the command resource based on the parameters of the command input and the context. The response may comprise result data and parameters for interacting with the collaborative communication system. The result data is presented in the user interface of the collaborative communication system. Other examples are also described. | 1. A collaborative communication system comprising:
a memory; and at least one processor operatively connected with the memory, the processor executing operations that comprise:
in response to command input being received during authoring in a user interface of the collaborative communication system, processing a query based on the received input by passing the query to a command resource, wherein the query comprises parameters of the command input and a context associated with the authoring,
receiving a response from the command resource based on the parameters of the command input and the context, wherein the response comprises result data and parameters for interacting with the collaborative communication system, and
presenting the result data in the user interface. 2. The collaborative communication system according to claim 1, wherein the operations further comprise identifying the command input based on receipt of a trigger from a user. 3. The collaborative communication system according to claim 1, wherein the presenting of the result data further comprises inserting the result data into a communication being authored in the user interface of the collaborative communication system. 4. The collaborative communication system according to claim 1, wherein the parameters for interacting with the collaborative communication system received from the command resource comprise a parameter indicating how to utilize the result data in presentation by the user interface, and the collaborative communication system presents the result data in accordance with the parameter passed by the command resource. 5. The collaborative communication system according to claim 1, wherein the command input is triggered from a UI widget the user interacts with in the collaborative communication system. 6. The collaborative communication system according to claim 5, wherein the operations further comprising processing a second query associated with the received input by passing the query to a command resource in response to the command input being updated, wherein the second query comprises parameters for the updated command input. 7. The collaborative communication system according to claim 6, wherein the operations further comprising receiving a second response from the command resource based on the parameters of the updated command input and the context associated with the authoring, wherein the second response comprises updated result data and parameters for interacting with the collaborative communication system. 8. The collaborative communication system according to claim 7, wherein the operations further comprising presenting the updated result data in the user interface, and in response to receiving a selection corresponding with the result data, inserting selected result data inline into a communication being authored in the user interface of the collaborative communication system. 9. A computer-readable storage device including executable instructions, that when executed on at least one processor, causing the processor to perform a process comprising:
receiving registration data of a command handler from an external resource for a command that is executable in a collaborative communication service, wherein the registration data comprises parameters defining a command associated with the command handler; storing the registration data in a storage for the collaborative communication service; in response to receiving declaration of input in the collaborative communication service, utilizing the parameters defining the command to determine whether the input triggers the command handler; and in response to determining that the input triggers the command handler, presenting the stored command handler for display in a user interface of the collaborative communication service. 10. The computer-readable storage device according to claim 9, wherein the presenting of the stored command handler displays an auto-completed command handler in response to determining that the input triggers the command handler. 11. The computer-readable storage device according to claim 9, where the process further comprises receiving, from the external resource, an update to the registration data of the command handler, and updating the stored registration data based on the received update to the registration data. 12. A computer-implemented method comprising:
in response to command input being received during authoring in a user interface of a collaborative communication service, transmitting, to an external resource, a first query that comprises parameters of the command input and a context associated with the authoring; receiving a first response from the external resource based on the parameters of the command input and the context, wherein the first response comprises result data and parameters for interacting with the collaborative communication service; presenting the result data in the user interface; in response to update to the command input, transmitting, to the external resource, a second query that comprises parameters of the updated command input; receiving a second response from the external resource based on the parameters of the command input and the context provided by the first query, wherein the second response received comprises updated result data; and presenting the updated result data in the user interface. 13. The computer-implemented method according to claim 12, further comprising registering, in a storage associated with the collaborative communication service, data associated with a command handler received from the external resource for a command that is executable in the collaborative communication service, wherein the registered data comprises parameters defining the command associated with the command handler. 14. The computer-implemented method according to claim 13, further comprising in response to the command input being received, utilizing the parameters of the registered data to determine whether the command input triggers the command handler, and in response to determining that the command input triggers the command handler, presenting the command handler for display in the user interface. 15. The computer-implemented method according to claim 14, wherein the presenting of the stored command handler further comprises displaying an auto-completed command handler in response to determining that the command input triggers the command handler. 16. The computer-implemented method according to claim 13, further comprising updating, in the storage associated with the collaborative communication service, the registered data corresponding to the command handler. 17. The computer-implemented method according to claim 16, further comprising in response to the command input being received, utilizing the parameters of the updated registered data to determine whether the command input triggers the command handler, and in response to determining that the command input triggers the command handler, presenting the command handler for display in the user interface. 18. The computer-implemented method according to claim 12, further comprising identifying the command input based on receipt of a trigger from a user, wherein the trigger is an input of at least one of an entered character, number, symbol, word, and selected item in the user interface. 19. The computer-implemented method according to claim 12, wherein the presenting of the result data further comprises inserting the result data inline into a communication being authored in the user interface. 20. The computer-implemented method according to claim 19, wherein the presenting of the updated result data further comprises replacing the result data in the communication with the updated result data. | Non-limiting examples of the present disclosure describe a collaborative communication system that may interface with one or more command resources. The collaborative communication system may comprise at least one memory and at least one processor operatively connected with the memory to execute operations. In response to command input being received during authoring in a user interface of the collaborative communication system, a query is processed and passed to a command resource. The query comprises parameters of the command input and a context associated with the authoring. A response is received from the command resource based on the parameters of the command input and the context. The response may comprise result data and parameters for interacting with the collaborative communication system. The result data is presented in the user interface of the collaborative communication system. Other examples are also described.1. A collaborative communication system comprising:
a memory; and at least one processor operatively connected with the memory, the processor executing operations that comprise:
in response to command input being received during authoring in a user interface of the collaborative communication system, processing a query based on the received input by passing the query to a command resource, wherein the query comprises parameters of the command input and a context associated with the authoring,
receiving a response from the command resource based on the parameters of the command input and the context, wherein the response comprises result data and parameters for interacting with the collaborative communication system, and
presenting the result data in the user interface. 2. The collaborative communication system according to claim 1, wherein the operations further comprise identifying the command input based on receipt of a trigger from a user. 3. The collaborative communication system according to claim 1, wherein the presenting of the result data further comprises inserting the result data into a communication being authored in the user interface of the collaborative communication system. 4. The collaborative communication system according to claim 1, wherein the parameters for interacting with the collaborative communication system received from the command resource comprise a parameter indicating how to utilize the result data in presentation by the user interface, and the collaborative communication system presents the result data in accordance with the parameter passed by the command resource. 5. The collaborative communication system according to claim 1, wherein the command input is triggered from a UI widget the user interacts with in the collaborative communication system. 6. The collaborative communication system according to claim 5, wherein the operations further comprising processing a second query associated with the received input by passing the query to a command resource in response to the command input being updated, wherein the second query comprises parameters for the updated command input. 7. The collaborative communication system according to claim 6, wherein the operations further comprising receiving a second response from the command resource based on the parameters of the updated command input and the context associated with the authoring, wherein the second response comprises updated result data and parameters for interacting with the collaborative communication system. 8. The collaborative communication system according to claim 7, wherein the operations further comprising presenting the updated result data in the user interface, and in response to receiving a selection corresponding with the result data, inserting selected result data inline into a communication being authored in the user interface of the collaborative communication system. 9. A computer-readable storage device including executable instructions, that when executed on at least one processor, causing the processor to perform a process comprising:
receiving registration data of a command handler from an external resource for a command that is executable in a collaborative communication service, wherein the registration data comprises parameters defining a command associated with the command handler; storing the registration data in a storage for the collaborative communication service; in response to receiving declaration of input in the collaborative communication service, utilizing the parameters defining the command to determine whether the input triggers the command handler; and in response to determining that the input triggers the command handler, presenting the stored command handler for display in a user interface of the collaborative communication service. 10. The computer-readable storage device according to claim 9, wherein the presenting of the stored command handler displays an auto-completed command handler in response to determining that the input triggers the command handler. 11. The computer-readable storage device according to claim 9, where the process further comprises receiving, from the external resource, an update to the registration data of the command handler, and updating the stored registration data based on the received update to the registration data. 12. A computer-implemented method comprising:
in response to command input being received during authoring in a user interface of a collaborative communication service, transmitting, to an external resource, a first query that comprises parameters of the command input and a context associated with the authoring; receiving a first response from the external resource based on the parameters of the command input and the context, wherein the first response comprises result data and parameters for interacting with the collaborative communication service; presenting the result data in the user interface; in response to update to the command input, transmitting, to the external resource, a second query that comprises parameters of the updated command input; receiving a second response from the external resource based on the parameters of the command input and the context provided by the first query, wherein the second response received comprises updated result data; and presenting the updated result data in the user interface. 13. The computer-implemented method according to claim 12, further comprising registering, in a storage associated with the collaborative communication service, data associated with a command handler received from the external resource for a command that is executable in the collaborative communication service, wherein the registered data comprises parameters defining the command associated with the command handler. 14. The computer-implemented method according to claim 13, further comprising in response to the command input being received, utilizing the parameters of the registered data to determine whether the command input triggers the command handler, and in response to determining that the command input triggers the command handler, presenting the command handler for display in the user interface. 15. The computer-implemented method according to claim 14, wherein the presenting of the stored command handler further comprises displaying an auto-completed command handler in response to determining that the command input triggers the command handler. 16. The computer-implemented method according to claim 13, further comprising updating, in the storage associated with the collaborative communication service, the registered data corresponding to the command handler. 17. The computer-implemented method according to claim 16, further comprising in response to the command input being received, utilizing the parameters of the updated registered data to determine whether the command input triggers the command handler, and in response to determining that the command input triggers the command handler, presenting the command handler for display in the user interface. 18. The computer-implemented method according to claim 12, further comprising identifying the command input based on receipt of a trigger from a user, wherein the trigger is an input of at least one of an entered character, number, symbol, word, and selected item in the user interface. 19. The computer-implemented method according to claim 12, wherein the presenting of the result data further comprises inserting the result data inline into a communication being authored in the user interface. 20. The computer-implemented method according to claim 19, wherein the presenting of the updated result data further comprises replacing the result data in the communication with the updated result data. | 2,100 |
6,524 | 6,524 | 14,998,325 | 2,144 | Techniques for an ink experience with images are discussed herein. In various implementations, an image is displayed via an image management application for viewing and/or editing images. In conjunction with interaction scenarios provided via the application, an inking mode for adding inked annotations to the image is enabled. Input to apply one or more inked annotations to the image is obtained, such as via finger touches on a touchscreen, drawing with a stylus, camera-based gestures, or other natural input mechanisms. Responsive to obtaining the input, data blocks corresponding to the one or more inked annotations are appended to an image file as additional data blocks for the image. | 1. A system comprising:
a display; and one or more processors in communication with the display, the one or more processors configured to:
display an image on the display via a viewing application;
enable an inking mode for adding inked annotations to the image, the inking mode supporting addition of annotations to at least front side and back side representations of the image;
obtain input to apply one or more inked annotations to the image; and
append data blocks corresponding to the one or more inked annotations as additional data blocks for the image. 2. The system as described in claim 1, wherein the data blocks corresponding to the one or more inked annotations includes indications of locations for the inked annotations. 3. The system as described in claim 1, wherein the viewing application is configured to animate transitions between the front side and back side representations of the image. 4. The system as described in claim 1, wherein the inking mode further supports association of one or more note elements with the image and creation of inked annotations on the note elements. 5. The system as described in claim 1, wherein the inked annotations are stored a vector objects that enable repositioning within the image, resizing, recoloring, and deletion of the inked annotations. 6. The system as described in claim 1, wherein the original image is not altered by inked annotations added to the image. 7. The system as described in claim 1, wherein ink data blocks for the inked annotations are appended to image data for the image as input of the ink content occurs. 8. The system as described in claim 1, wherein the one or more processors are further configured to:
enable inking for different views of the image including one or more of the image body, margins, a back side of the image, or note pages added to the image; provide navigation controls to switch back and forth between the different view; render visual transitions responsive to navigation between the views; and provide a toggle control to selectively show or hide inked annotations added to the different views. 9. The system as described in claim 1, wherein the one or more processors are further configured to:
apply handwriting recognition to inked annotations added to the image; extract keywords corresponding to the inked annotations; and store the keywords as metadata for the image. 10. The system as described in claim 9, wherein the one or more processors are further configured to:
enable keyword based photo management operations using the extracted keywords including one or a combination of searching, filtering, categorizing, and sorting. 11. The system as described in claim 9, wherein the one or more processors are further configured to:
prior to storing the keywords, expose recognized keywords via a visual element to facilitate review and confirmation of the keywords, wherein the storing of the keywords as metadata for the image occurs responsive to confirmation via the visual element. 12. The system as described in claim 11, wherein the one or more processors are further configured to:
provide via the visual element functionality to edit the recognized keywords, accept the keywords, or reject the keywords. 13. The system as described in claim 1, wherein inked annotations are saved automatically without an explicit selection of a save command. 14. The system as described in claim 1, wherein the inked annotations are usable by applications that support inking features and do not interfere with handling of images by applications that do not support inking features. 15. The system as described in claim 1, wherein rendering of the inked annotations is bypassed in thumbnail views and other views of the image that result in illegible representations of the inked annotations. 16. A computer-implemented method, comprising:
displaying an image via a viewing application; enabling an inking mode for adding inked annotations to the image including enabling inking for different views of the image including representations of the image body, margins, a back side of the image, and note pages added to the image; obtaining input to apply one or more inked annotations to the image; and appending data blocks corresponding to the one or more inked annotations as additional data blocks for the image. 17. The computer-implemented method of claim 16, further comprising:
applying handwriting recognition to inked annotations added to the image displayed via the viewing application; extracting keywords corresponding to the inked annotations; storing the keywords as metadata for the image; and enabling keyword based photo management operations using the extracted keywords including one or a combination of searching, filtering, categorizing, and sorting. 18. The computer-implemented method of claim 17, further comprising:
applying the handwriting recognition to recognize keywords corresponding to the inked annotations in real-time as the input to add the inked annotations is obtained; exposing recognized keywords via a visual element to facilitate review and confirmation of the keywords; and providing via the visual element functionality to edit the recognized keywords, accept the keywords, and reject the keywords. 19. The computer-implemented method of claim 16, further comprising:
providing navigation controls to switch back and forth between the different views; and rendering visual transitions responsive to navigation between the views. 20. One or more computer-readable storage media storing computer-executable instructions that, responsive to execution by a computing device, cause the computing device to perform operations comprising:
exposing an image as an inkable canvas via a viewer that supports inking; enabling inking for different views of the image including one or more of the image body, margins, a back side of the image, or note pages added to the image; providing navigation controls to switch back and forth between the different views; rendering visual transitions responsive to navigation between the views; and providing a toggle control to selectively show or hide inked annotations added to the different views. | Techniques for an ink experience with images are discussed herein. In various implementations, an image is displayed via an image management application for viewing and/or editing images. In conjunction with interaction scenarios provided via the application, an inking mode for adding inked annotations to the image is enabled. Input to apply one or more inked annotations to the image is obtained, such as via finger touches on a touchscreen, drawing with a stylus, camera-based gestures, or other natural input mechanisms. Responsive to obtaining the input, data blocks corresponding to the one or more inked annotations are appended to an image file as additional data blocks for the image.1. A system comprising:
a display; and one or more processors in communication with the display, the one or more processors configured to:
display an image on the display via a viewing application;
enable an inking mode for adding inked annotations to the image, the inking mode supporting addition of annotations to at least front side and back side representations of the image;
obtain input to apply one or more inked annotations to the image; and
append data blocks corresponding to the one or more inked annotations as additional data blocks for the image. 2. The system as described in claim 1, wherein the data blocks corresponding to the one or more inked annotations includes indications of locations for the inked annotations. 3. The system as described in claim 1, wherein the viewing application is configured to animate transitions between the front side and back side representations of the image. 4. The system as described in claim 1, wherein the inking mode further supports association of one or more note elements with the image and creation of inked annotations on the note elements. 5. The system as described in claim 1, wherein the inked annotations are stored a vector objects that enable repositioning within the image, resizing, recoloring, and deletion of the inked annotations. 6. The system as described in claim 1, wherein the original image is not altered by inked annotations added to the image. 7. The system as described in claim 1, wherein ink data blocks for the inked annotations are appended to image data for the image as input of the ink content occurs. 8. The system as described in claim 1, wherein the one or more processors are further configured to:
enable inking for different views of the image including one or more of the image body, margins, a back side of the image, or note pages added to the image; provide navigation controls to switch back and forth between the different view; render visual transitions responsive to navigation between the views; and provide a toggle control to selectively show or hide inked annotations added to the different views. 9. The system as described in claim 1, wherein the one or more processors are further configured to:
apply handwriting recognition to inked annotations added to the image; extract keywords corresponding to the inked annotations; and store the keywords as metadata for the image. 10. The system as described in claim 9, wherein the one or more processors are further configured to:
enable keyword based photo management operations using the extracted keywords including one or a combination of searching, filtering, categorizing, and sorting. 11. The system as described in claim 9, wherein the one or more processors are further configured to:
prior to storing the keywords, expose recognized keywords via a visual element to facilitate review and confirmation of the keywords, wherein the storing of the keywords as metadata for the image occurs responsive to confirmation via the visual element. 12. The system as described in claim 11, wherein the one or more processors are further configured to:
provide via the visual element functionality to edit the recognized keywords, accept the keywords, or reject the keywords. 13. The system as described in claim 1, wherein inked annotations are saved automatically without an explicit selection of a save command. 14. The system as described in claim 1, wherein the inked annotations are usable by applications that support inking features and do not interfere with handling of images by applications that do not support inking features. 15. The system as described in claim 1, wherein rendering of the inked annotations is bypassed in thumbnail views and other views of the image that result in illegible representations of the inked annotations. 16. A computer-implemented method, comprising:
displaying an image via a viewing application; enabling an inking mode for adding inked annotations to the image including enabling inking for different views of the image including representations of the image body, margins, a back side of the image, and note pages added to the image; obtaining input to apply one or more inked annotations to the image; and appending data blocks corresponding to the one or more inked annotations as additional data blocks for the image. 17. The computer-implemented method of claim 16, further comprising:
applying handwriting recognition to inked annotations added to the image displayed via the viewing application; extracting keywords corresponding to the inked annotations; storing the keywords as metadata for the image; and enabling keyword based photo management operations using the extracted keywords including one or a combination of searching, filtering, categorizing, and sorting. 18. The computer-implemented method of claim 17, further comprising:
applying the handwriting recognition to recognize keywords corresponding to the inked annotations in real-time as the input to add the inked annotations is obtained; exposing recognized keywords via a visual element to facilitate review and confirmation of the keywords; and providing via the visual element functionality to edit the recognized keywords, accept the keywords, and reject the keywords. 19. The computer-implemented method of claim 16, further comprising:
providing navigation controls to switch back and forth between the different views; and rendering visual transitions responsive to navigation between the views. 20. One or more computer-readable storage media storing computer-executable instructions that, responsive to execution by a computing device, cause the computing device to perform operations comprising:
exposing an image as an inkable canvas via a viewer that supports inking; enabling inking for different views of the image including one or more of the image body, margins, a back side of the image, or note pages added to the image; providing navigation controls to switch back and forth between the different views; rendering visual transitions responsive to navigation between the views; and providing a toggle control to selectively show or hide inked annotations added to the different views. | 2,100 |
6,525 | 6,525 | 13,961,263 | 2,159 | Selective processing of items having embedded delay actions includes receiving an item to process containing a delay action, processing the item using a delay action process, wherein the delay action process includes exploring dynamically generated server-side content of the item received, by recognizing when a wait occurs for a server process, and performing one of a wait for a predetermined period of time, or circumventing an actual wait, to generate a result and returns the result to a requester. | 1. A computer-implemented process for selective processing of items having embedded delay actions, the computer-implemented process comprising:
receiving an item to process containing a delay action; processing the item using a delay action process using a processor, wherein the delay action process comprises exploring dynamically generated server-side content of the item received, by recognizing when a wait occurs for a server process, and performing one of a wait for a predetermined period of time, or circumventing an actual wait, to generate a result; and returning the result to a requester. 2. The computer-implemented process of claim 1 wherein receiving an item to process containing a delay action further comprises:
loading a document object model of a current item;
executing an event handler action; and
determining whether a delay action is specified in the document object model. 3. The computer-implemented process of claim 1 wherein processing the item using a delay action process further comprises:
responsive to a determination that a delay action is specified in a document object model, executing a function associated with the delay action to capture a new document object model;
responsive to a determination that the document object model before execution of the function is equivalent to the new document object model after execution of the function, determining whether a process waited for a timeout;
responsive to a determination that the process did not wait for the timeout, waiting a time specified in the timeout;
executing the function associated with the delay action to capture the new document object model;
determining whether the document object model before execution of the function is equivalent to the new document object model after execution of the function; and
responsive to a determination that the document object model before execution of the function is not equivalent to the new document object model after execution of the function, processing the document object model. 4. The computer-implemented process of claim 1 wherein receiving an item to process containing a delay action further comprises:
receiving a preselected set of items, wherein each item contains one or more delay actions embedded therein. 5. The computer-implemented process of claim 3 further comprising:
determining whether there are more delay actions to process in the document object model;
responsive to a determination that there are no more delay actions to process in the document object model, determining whether there are more JavaScript actions to process;
responsive to a determination that there are more JavaScript actions to process, executing a next JavaScript; and
processing the document object model. 6. The computer-implemented process of claim 1 wherein receiving an item to process containing a delay action further comprises:
detecting in the item to identify a server side technology being used; and
selecting a predefined callback method according to the identified server side technology, wherein reliance on the delay action is obviated. 7. The computer-implemented process of claim 1 wherein receiving an item to process containing a delay action further comprises:
monitoring predetermined function calls to identify an item to process containing the delay action; and
assuming the delay action is not used for server side content processing when no such call is indicated. 8. A computer program product for selective processing of items having embedded delay actions, the computer program product comprising:
a computer recordable storage media containing computer program code stored thereon, wherein the computer program code is executable by a processor to perform a method comprising: receiving, using the processor, an item to process containing a delay action; processing, using the processor, the item using a delay action process, wherein the delay action process comprises exploring dynamically generated server-side content of the item received, by recognizing when a wait occurs for a server process, and performing one of a wait for a predetermined period of time, or circumventing an actual wait, to generate a result; and returning, using the processor, the result to a requester. 9. The computer program product of claim 8 wherein receiving an item to process containing a delay action further comprises:
loading a document object model of a current item;
executing an event handler action; and
determining whether a delay action is specified in the document object model. 10. The computer program product of claim 8 wherein processing the item using a delay action process further comprises:
responsive to a determination that a delay action is specified in a document object model, executing a function associated with the delay action to capture a new document object model;
responsive to a determination that the document object model before execution of the function is equivalent to the new document object model after execution of the function, determining whether a process waited for a timeout;
responsive to a determination that the process did not wait for the timeout, waiting a time specified in the timeout;
executing the function associated with the delay action to capture the new document object model;
determining whether the document object model before execution of the function is equivalent to the new document object model after execution of the function; and
responsive to a determination that the document object model before execution of the function is not equivalent to the new document object model after execution of the function, processing the document object model. 11. The computer program product of claim 8 wherein receiving an item to process containing a delay action further comprises:
receiving a preselected set of items, wherein each item contains one or more delay actions embedded therein. 12. The computer program product of claim 10 wherein the method further comprises:
determining whether there are more delay actions to process in the document object model;
responsive to a determination that there are no more delay actions to process in the document object model, determining whether there are more JavaScript actions to process;
responsive to a determination that there are more JavaScript actions to process, executing a next JavaScript; and
processing the document object model. 13. The computer program product of claim 8 wherein receiving an item to process containing a delay action further comprises:
detecting in the item to identify a server side technology being used; and
selecting a predefined callback method according to the identified server side technology, wherein reliance on the delay action is obviated. 14. The computer program product of claim 8 wherein receiving an item to process containing a delay action further comprises:
monitoring predetermined function calls to identify an item to process containing the delay action; and
assuming the delay action is not used for server side content processing when no such call is indicated. 15. A system for selective processing of items having embedded delay actions, the apparatus comprising:
a processor programmed to initiate executable operations comprising: receiving an item to process containing a delay action; processing the item using a delay action process, wherein the delay action process comprises exploring dynamically generated server-side content of the item received, by recognizing when a wait occurs for a server process, and performing one of a wait for a predetermined period of time, or circumventing an actual wait, to generate a result; and returning the result to a requester. 16. The system of claim 15 wherein receiving an item to process containing a delay action further comprises:
loading a document object model of a current item;
executing an event handler action; and
determining whether a delay action is specified in the document object model. 17. The system of claim 15 wherein processing the item using a delay action process further comprises:
responsive to a determination that a delay action is specified in a document object model, executing a function associated with the delay action to capture a new document object model;
responsive to a determination that the document object model before execution of the function is equivalent to the new document object model after execution of the function, determining whether a process waited for a timeout;
responsive to a determination that the process did not wait for the timeout, waiting a time specified in the timeout;
executing the function associated with the delay action to capture the new document object model;
determining whether the document object model before execution of the function is equivalent to the new document object model after execution of the function;
responsive to a determination that the document object model before execution of the function is not equivalent to the new document object model after execution of the function, processing the document object model. 18. The system of claim 15 wherein receiving an item to process containing a delay action further comprises:
receiving a preselected set of items, wherein each item contains one or more delay actions embedded therein. 19. The system of claim 17 wherein the processor is further programmed to initiate executable operations comprising:
determining whether there are more delay actions to process in the document object model;
responsive to a determination that there are no more delay actions to process in the document object model, determining whether there are more JavaScript actions to process;
responsive to a determination that there are more JavaScript actions to process, executing a next JavaScript; and
processing the document object model. 20. The system of claim 15 wherein receiving an item to process containing a delay action further comprises:
detecting in the item a server side technology being used; and
selecting a predefined callback method according to the identified server side technology, wherein reliance on the delay action is obviated. | Selective processing of items having embedded delay actions includes receiving an item to process containing a delay action, processing the item using a delay action process, wherein the delay action process includes exploring dynamically generated server-side content of the item received, by recognizing when a wait occurs for a server process, and performing one of a wait for a predetermined period of time, or circumventing an actual wait, to generate a result and returns the result to a requester.1. A computer-implemented process for selective processing of items having embedded delay actions, the computer-implemented process comprising:
receiving an item to process containing a delay action; processing the item using a delay action process using a processor, wherein the delay action process comprises exploring dynamically generated server-side content of the item received, by recognizing when a wait occurs for a server process, and performing one of a wait for a predetermined period of time, or circumventing an actual wait, to generate a result; and returning the result to a requester. 2. The computer-implemented process of claim 1 wherein receiving an item to process containing a delay action further comprises:
loading a document object model of a current item;
executing an event handler action; and
determining whether a delay action is specified in the document object model. 3. The computer-implemented process of claim 1 wherein processing the item using a delay action process further comprises:
responsive to a determination that a delay action is specified in a document object model, executing a function associated with the delay action to capture a new document object model;
responsive to a determination that the document object model before execution of the function is equivalent to the new document object model after execution of the function, determining whether a process waited for a timeout;
responsive to a determination that the process did not wait for the timeout, waiting a time specified in the timeout;
executing the function associated with the delay action to capture the new document object model;
determining whether the document object model before execution of the function is equivalent to the new document object model after execution of the function; and
responsive to a determination that the document object model before execution of the function is not equivalent to the new document object model after execution of the function, processing the document object model. 4. The computer-implemented process of claim 1 wherein receiving an item to process containing a delay action further comprises:
receiving a preselected set of items, wherein each item contains one or more delay actions embedded therein. 5. The computer-implemented process of claim 3 further comprising:
determining whether there are more delay actions to process in the document object model;
responsive to a determination that there are no more delay actions to process in the document object model, determining whether there are more JavaScript actions to process;
responsive to a determination that there are more JavaScript actions to process, executing a next JavaScript; and
processing the document object model. 6. The computer-implemented process of claim 1 wherein receiving an item to process containing a delay action further comprises:
detecting in the item to identify a server side technology being used; and
selecting a predefined callback method according to the identified server side technology, wherein reliance on the delay action is obviated. 7. The computer-implemented process of claim 1 wherein receiving an item to process containing a delay action further comprises:
monitoring predetermined function calls to identify an item to process containing the delay action; and
assuming the delay action is not used for server side content processing when no such call is indicated. 8. A computer program product for selective processing of items having embedded delay actions, the computer program product comprising:
a computer recordable storage media containing computer program code stored thereon, wherein the computer program code is executable by a processor to perform a method comprising: receiving, using the processor, an item to process containing a delay action; processing, using the processor, the item using a delay action process, wherein the delay action process comprises exploring dynamically generated server-side content of the item received, by recognizing when a wait occurs for a server process, and performing one of a wait for a predetermined period of time, or circumventing an actual wait, to generate a result; and returning, using the processor, the result to a requester. 9. The computer program product of claim 8 wherein receiving an item to process containing a delay action further comprises:
loading a document object model of a current item;
executing an event handler action; and
determining whether a delay action is specified in the document object model. 10. The computer program product of claim 8 wherein processing the item using a delay action process further comprises:
responsive to a determination that a delay action is specified in a document object model, executing a function associated with the delay action to capture a new document object model;
responsive to a determination that the document object model before execution of the function is equivalent to the new document object model after execution of the function, determining whether a process waited for a timeout;
responsive to a determination that the process did not wait for the timeout, waiting a time specified in the timeout;
executing the function associated with the delay action to capture the new document object model;
determining whether the document object model before execution of the function is equivalent to the new document object model after execution of the function; and
responsive to a determination that the document object model before execution of the function is not equivalent to the new document object model after execution of the function, processing the document object model. 11. The computer program product of claim 8 wherein receiving an item to process containing a delay action further comprises:
receiving a preselected set of items, wherein each item contains one or more delay actions embedded therein. 12. The computer program product of claim 10 wherein the method further comprises:
determining whether there are more delay actions to process in the document object model;
responsive to a determination that there are no more delay actions to process in the document object model, determining whether there are more JavaScript actions to process;
responsive to a determination that there are more JavaScript actions to process, executing a next JavaScript; and
processing the document object model. 13. The computer program product of claim 8 wherein receiving an item to process containing a delay action further comprises:
detecting in the item to identify a server side technology being used; and
selecting a predefined callback method according to the identified server side technology, wherein reliance on the delay action is obviated. 14. The computer program product of claim 8 wherein receiving an item to process containing a delay action further comprises:
monitoring predetermined function calls to identify an item to process containing the delay action; and
assuming the delay action is not used for server side content processing when no such call is indicated. 15. A system for selective processing of items having embedded delay actions, the apparatus comprising:
a processor programmed to initiate executable operations comprising: receiving an item to process containing a delay action; processing the item using a delay action process, wherein the delay action process comprises exploring dynamically generated server-side content of the item received, by recognizing when a wait occurs for a server process, and performing one of a wait for a predetermined period of time, or circumventing an actual wait, to generate a result; and returning the result to a requester. 16. The system of claim 15 wherein receiving an item to process containing a delay action further comprises:
loading a document object model of a current item;
executing an event handler action; and
determining whether a delay action is specified in the document object model. 17. The system of claim 15 wherein processing the item using a delay action process further comprises:
responsive to a determination that a delay action is specified in a document object model, executing a function associated with the delay action to capture a new document object model;
responsive to a determination that the document object model before execution of the function is equivalent to the new document object model after execution of the function, determining whether a process waited for a timeout;
responsive to a determination that the process did not wait for the timeout, waiting a time specified in the timeout;
executing the function associated with the delay action to capture the new document object model;
determining whether the document object model before execution of the function is equivalent to the new document object model after execution of the function;
responsive to a determination that the document object model before execution of the function is not equivalent to the new document object model after execution of the function, processing the document object model. 18. The system of claim 15 wherein receiving an item to process containing a delay action further comprises:
receiving a preselected set of items, wherein each item contains one or more delay actions embedded therein. 19. The system of claim 17 wherein the processor is further programmed to initiate executable operations comprising:
determining whether there are more delay actions to process in the document object model;
responsive to a determination that there are no more delay actions to process in the document object model, determining whether there are more JavaScript actions to process;
responsive to a determination that there are more JavaScript actions to process, executing a next JavaScript; and
processing the document object model. 20. The system of claim 15 wherein receiving an item to process containing a delay action further comprises:
detecting in the item a server side technology being used; and
selecting a predefined callback method according to the identified server side technology, wherein reliance on the delay action is obviated. | 2,100 |
6,526 | 6,526 | 15,224,848 | 2,163 | A set of conversations taking place by users within a geographic location are identified. Keywords for a conversation under analysis, in that geographic location, are identified based on a frequency with which terms are used in the conversation under analysis and in the related conversations. The keywords are automatically added as searchable terms corresponding to the conversation under analysis, and a communication system is controlled to notify client components of the keywords. | 1. A computing system, comprising:
a location-based conversation system that generates a conversation display indicative of user messages, in a first location-based conversation, received from user devices in a geographic location corresponding to the first location-based conversation; keyword generator logic that repeatedly detects keywords for the first location-based conversation based on a first usage frequency of linguistic units in the user messages in the first location-based conversation and based on a usage frequency of the linguistic units in other, related, location-based conversations; and keyword output logic that communicates the keywords to a data store storing the user messages in the first location-based conversation. 2. The computing system of claim 1 wherein each of the location-based conversations has a geographic location identifier identifying a corresponding geographic location. 3. The computing system of claim 2 wherein the keyword generator logic comprises:
geographically related conversation identifier configured to identify the related location-based conversations as location-based conversations having the same geographic location identifier as the first location-based conversation. 4. The computing system of claim 3 wherein the keyword generator logic comprises:
a message identifier that identifies a subset of the user messages in the first location-based conversation for which the first usage frequency is determined. 5. The computing system of claim 4 wherein the message identifier is configured to identify the subset of user messages as a set of most recently received user messages. 6. The computing system of claim 1 wherein the keyword generator logic comprises:
an operation detector configured to detect when the keywords are to be detected for the first location-based conversation. 7. The computing system of claim 6 wherein the operation detector comprises:
a new message detector configured to detect when a new user message is received in the first location-based conversation, the operation detector being configured to detect that the keywords are to be detected for the first location-based conversation when the new message detector detects that n new user messages are received in the first location-based conversation since the keywords were last detected. 8. The computing system of claim 4 wherein the keyword identifier logic comprises:
conversation parsing logic configured to parse the subset of user messages in the first location-based conversation into a first set of linguistic units; and
term frequency generator logic configured to determine the first usage frequency for each of the linguistic units. 9. The computing system of claim 8 wherein the conversation parsing logic is configured to parse the geographically related conversations into linguistic units and wherein the keyword identifier logic comprises:
inverse conversation frequency generator logic configured to identify the usage frequency in the geographically related conversations for the linguistic units in the geographically related conversations. 10. The computing system of claim 1 wherein the first location-based conversation includes a corresponding title and further comprising:
title generator logic configured to modify the title of the first location-based conversation based on the keywords. 11. The computing system of claim 10 wherein the title generator logic comprises:
comparison logic configured to compare a current title corresponding to the first location-based conversation to the keywords; and
title adjustment logic configured to adjust the current title based on the comparison. 12. A computer implemented method, comprising:
generating a conversation display indicative of user messages, in a first location-based conversation, received from user devices in a geographic location corresponding to the first location-based conversation; repeatedly detecting keywords for the first location-based conversation based on a first usage frequency of linguistic units in the user messages in the first location-based conversation and based on a usage frequency of the linguistic units in other, related, location-based conversations; and communicating the keywords to user devices in the geographic location corresponding to the first location-based conversation. 13. The computer implemented method of claim 12 wherein each of the location-based conversations has a geographic location identifier identifying a corresponding geographic location, and wherein detecting keywords comprises:
identifying the related location-based conversations as location-based conversations having the same geographic location identifier as the first location-based conversation. 14. The computer implemented method of claim 13 wherein detecting keywords comprises:
identifying a subset of the user messages in the first location-based conversation; and
identify the first usage frequency based on the identified subset of user messages. 15. The computer implemented method of claim 14 and further comprising:
detecting when a new user message is received in the first location-based conversation; and
detecting that the keywords are to be detected for the first location-based conversation when n new user messages are received in the first location-based conversation since the keywords were last detected. 16. The computer implemented method of claim 14 wherein detecting keywords comprises:
parsing the subset of user messages in the first location-based conversation into a first set of linguistic units; and
determining the first usage frequency for each linguistic unit in the first set of linguistic units;
parsing the geographically related conversations into linguistic units; and
identifying the usage frequency in the geographically related conversations for the first set of linguistic units in the geographically related conversations. 17. The computer implemented method of claim 12 wherein the first location-based conversation includes a corresponding title and further comprising:
modifying the title of the first location-based conversation based on the keywords. 18. The computer implemented method of claim 17 wherein modifying the title comprises:
comparing a current title corresponding to the first location-based conversation to the keywords; and
adjusting the current title based on the comparison. 19. A computing system, comprising:
a location-based conversation system that generates a conversation display indicative of user messages, in a first location-based conversation, received from user devices in a geographic location corresponding to the first location-based conversation, the first location-based conversation having a corresponding location identifier identifying the geographic location; a geographically related conversation identifier configured to identify related location-based conversations as location-based conversations having a same geographic location identifier as the first location-based conversation; and keyword generator logic that repeatedly detects keywords for the first location-based conversation based on a first usage frequency of linguistic units in the user messages in the first location-based conversation and based on a usage frequency of the linguistic units in the related location-based conversations; and keyword output logic that communicates the keywords to a data store for the first location-based conversation. 20. The computing system of claim 19 wherein the first location-based conversation includes a corresponding title and further comprising:
title generator logic configured to modify the title of the first location-based conversation based on the keywords. | A set of conversations taking place by users within a geographic location are identified. Keywords for a conversation under analysis, in that geographic location, are identified based on a frequency with which terms are used in the conversation under analysis and in the related conversations. The keywords are automatically added as searchable terms corresponding to the conversation under analysis, and a communication system is controlled to notify client components of the keywords.1. A computing system, comprising:
a location-based conversation system that generates a conversation display indicative of user messages, in a first location-based conversation, received from user devices in a geographic location corresponding to the first location-based conversation; keyword generator logic that repeatedly detects keywords for the first location-based conversation based on a first usage frequency of linguistic units in the user messages in the first location-based conversation and based on a usage frequency of the linguistic units in other, related, location-based conversations; and keyword output logic that communicates the keywords to a data store storing the user messages in the first location-based conversation. 2. The computing system of claim 1 wherein each of the location-based conversations has a geographic location identifier identifying a corresponding geographic location. 3. The computing system of claim 2 wherein the keyword generator logic comprises:
geographically related conversation identifier configured to identify the related location-based conversations as location-based conversations having the same geographic location identifier as the first location-based conversation. 4. The computing system of claim 3 wherein the keyword generator logic comprises:
a message identifier that identifies a subset of the user messages in the first location-based conversation for which the first usage frequency is determined. 5. The computing system of claim 4 wherein the message identifier is configured to identify the subset of user messages as a set of most recently received user messages. 6. The computing system of claim 1 wherein the keyword generator logic comprises:
an operation detector configured to detect when the keywords are to be detected for the first location-based conversation. 7. The computing system of claim 6 wherein the operation detector comprises:
a new message detector configured to detect when a new user message is received in the first location-based conversation, the operation detector being configured to detect that the keywords are to be detected for the first location-based conversation when the new message detector detects that n new user messages are received in the first location-based conversation since the keywords were last detected. 8. The computing system of claim 4 wherein the keyword identifier logic comprises:
conversation parsing logic configured to parse the subset of user messages in the first location-based conversation into a first set of linguistic units; and
term frequency generator logic configured to determine the first usage frequency for each of the linguistic units. 9. The computing system of claim 8 wherein the conversation parsing logic is configured to parse the geographically related conversations into linguistic units and wherein the keyword identifier logic comprises:
inverse conversation frequency generator logic configured to identify the usage frequency in the geographically related conversations for the linguistic units in the geographically related conversations. 10. The computing system of claim 1 wherein the first location-based conversation includes a corresponding title and further comprising:
title generator logic configured to modify the title of the first location-based conversation based on the keywords. 11. The computing system of claim 10 wherein the title generator logic comprises:
comparison logic configured to compare a current title corresponding to the first location-based conversation to the keywords; and
title adjustment logic configured to adjust the current title based on the comparison. 12. A computer implemented method, comprising:
generating a conversation display indicative of user messages, in a first location-based conversation, received from user devices in a geographic location corresponding to the first location-based conversation; repeatedly detecting keywords for the first location-based conversation based on a first usage frequency of linguistic units in the user messages in the first location-based conversation and based on a usage frequency of the linguistic units in other, related, location-based conversations; and communicating the keywords to user devices in the geographic location corresponding to the first location-based conversation. 13. The computer implemented method of claim 12 wherein each of the location-based conversations has a geographic location identifier identifying a corresponding geographic location, and wherein detecting keywords comprises:
identifying the related location-based conversations as location-based conversations having the same geographic location identifier as the first location-based conversation. 14. The computer implemented method of claim 13 wherein detecting keywords comprises:
identifying a subset of the user messages in the first location-based conversation; and
identify the first usage frequency based on the identified subset of user messages. 15. The computer implemented method of claim 14 and further comprising:
detecting when a new user message is received in the first location-based conversation; and
detecting that the keywords are to be detected for the first location-based conversation when n new user messages are received in the first location-based conversation since the keywords were last detected. 16. The computer implemented method of claim 14 wherein detecting keywords comprises:
parsing the subset of user messages in the first location-based conversation into a first set of linguistic units; and
determining the first usage frequency for each linguistic unit in the first set of linguistic units;
parsing the geographically related conversations into linguistic units; and
identifying the usage frequency in the geographically related conversations for the first set of linguistic units in the geographically related conversations. 17. The computer implemented method of claim 12 wherein the first location-based conversation includes a corresponding title and further comprising:
modifying the title of the first location-based conversation based on the keywords. 18. The computer implemented method of claim 17 wherein modifying the title comprises:
comparing a current title corresponding to the first location-based conversation to the keywords; and
adjusting the current title based on the comparison. 19. A computing system, comprising:
a location-based conversation system that generates a conversation display indicative of user messages, in a first location-based conversation, received from user devices in a geographic location corresponding to the first location-based conversation, the first location-based conversation having a corresponding location identifier identifying the geographic location; a geographically related conversation identifier configured to identify related location-based conversations as location-based conversations having a same geographic location identifier as the first location-based conversation; and keyword generator logic that repeatedly detects keywords for the first location-based conversation based on a first usage frequency of linguistic units in the user messages in the first location-based conversation and based on a usage frequency of the linguistic units in the related location-based conversations; and keyword output logic that communicates the keywords to a data store for the first location-based conversation. 20. The computing system of claim 19 wherein the first location-based conversation includes a corresponding title and further comprising:
title generator logic configured to modify the title of the first location-based conversation based on the keywords. | 2,100 |
6,527 | 6,527 | 15,084,183 | 2,196 | A method, computing device and computer program product are provided to establish and maintain resource availability. Methods may include generating a representation of a resource availability schedule including at least one resource entry, where each resource entry includes a resource identification, a date, a location, a start time, and a finish time. Generating the representation may include: dividing the availability for each resource for each date and location into at least one continuous time period of availability, where no continuous time period of availability for a resource is represented by more than one resource entry; and generating a resource entry for each continuous time period. Methods may include: processing a request to schedule a resource, the request including a requested resource identifier, date, start time, finish time, and location; identifying a resource entry corresponding to the request; and modifying the resource entry to remove the time period of the request. | 1. A computing device comprising processing circuitry configured to:
generate a representation of a resource availability schedule comprising at least one resource entry, wherein each resource entry comprises a resource identification, a date, a location, a start time, and a finish time, and wherein the processing circuitry configured to generate the representation comprises processing circuitry configured to:
divide the availability for each resource for each date and location into at least one continuous time period of availability, wherein no continuous time period of availability for a resource is represented by more than one resource entry; and
generate a resource entry for each continuous time period;
process a request to schedule a resource, the request comprising a requested resource identifier, date, start time, finish time, and location; identify a resource entry corresponding to the request; and modify the resource entry to remove the time period of the request. 2. The computing device of claim 1, wherein in response to a request to schedule a resource comprising a start time equating to the start time of the resource entry corresponding to the request, the processing circuitry configured to modify the resource entry comprises processing circuitry configured to modify the resource entry start time to become the finish time of the request. 3. The computing device of claim 2, wherein in response to a request to schedule a resource comprising a finish time equating to the finish time of the resource entry corresponding to the request, the processing circuitry configured to modify the resource entry comprises processing circuitry configured to modify the resource entry finish time to become the start time of the request. 4. The computing device of claim 3, wherein in response to a request to schedule a resource comprising a start time that does not equate to the start time of the resource entry corresponding to the request, and the request comprises a finish time that does not equate to the finish time of the resource entry corresponding to the request, the processing circuitry configured to modify the resource entry comprises processing circuitry to divide the resource entry corresponding to the request into a first resource entry and a second resource entry, wherein the first resource entry comprises a start time equating to the start time of the resource entry corresponding to the request and a finish time equating to the start time of the request, and wherein the second resource entry comprises a start time equating to the finish time of the request and a finish time equating to the finish time of the resource entry corresponding to the request. 5. The computing device of claim 1, wherein in response to a request to cancel a scheduled event for a resource, the computing device further comprises processing circuitry configured to append a time period of the scheduled event to a resource entry for which the time period is continuous. 6. The computing device of claim 1, wherein the processing circuitry configured to process the request to schedule a resource comprises processing circuitry configured to receive a request comprising a resource identification, and at least one of a date range, a time duration, a time range, or acceptable locations, and the processing circuitry configured to process the request comprises processing circuitry configured to establish available time periods corresponding to the request. 7. The computing device of claim 6, further comprising processing circuitry configured to:
present the available time periods corresponding to the request; receive a selection from the available time periods; and process the selected request to schedule a resource for the selected time period. 8. A method comprising:
generating a representation of a resource availability schedule comprising at least one resource entry, wherein each resource entry comprises a resource identification, a date, a location, a start time, and a finish time, wherein generating the representation comprises:
dividing the availability for each resource for each date and location into at least one continuous time period of availability, wherein no continuous time period of availability for a resource is represented by more than one resource entry; and
generating a resource entry for each continuous time period;
processing a request to schedule a resource, the request comprising a requested resource identifier, date, start time, finish time, and location; identifying a resource entry corresponding to the request; and modifying the resource entry to remove the time period of the request. 9. The method of claim 8, wherein in response to a request to schedule a resource comprising a start time equating to the start time of the resource entry corresponding to the request, modifying the resource entry comprises modifying the resource entry start time to become the finish time of the request. 10. The method of claim 9, wherein in response to a request to schedule a resource comprising a finish time equating to the finish time of the resource entry corresponding to the request, modifying the resource entry comprises modifying the resource entry finish time to become the start time of the request. 11. The method of claim 10, wherein in response to a request to schedule a resource comprising a start time that does not equate to the start time of the resource entry corresponding to the request, and the request comprises a finish time that does not equate to the finish time of the resource entry corresponding to the request, modifying the resource entry comprises dividing the resource entry corresponding to the request into a first resource entry and a second resource entry, wherein the first resource entry comprises a start time equating to the start time of the resource entry corresponding to the request and a finish time equating to the start time of the request, and wherein the second resource entry comprises a start time equating to the finish time of the request and a finish time equating to the finish time of the resource entry corresponding to the request. 12. The method of claim 8, wherein in response to a request to cancel a scheduled event for a resource, appending a time period of the scheduled event to a resource entry for which the time period is continuous. 13. The method of claim 8, wherein processing the request to schedule a resource comprises receiving a request comprising a resource identification, and at least one of a date range, a time duration, a time range, or acceptable locations, and processing the request comprises establishing available time periods corresponding to the request. 14. The method of claim 13, further comprising:
causing presentation of the available time periods corresponding to the request; receiving a selection from the available time periods; and processing the selected request to schedule a resource for the selected time period. 15. A computer program product comprising a non-transitory computer readable storage medium having program code portions stored therein, the program code portions configured, upon execution, to:
generate a representation of a resource availability schedule comprising at least one resource entry, wherein each resource entry comprises a resource identification, a date, a location, a start time, and a finish time, and wherein the processing circuitry configured to generate the representation comprises processing circuitry configured to:
divide the availability for each resource for each date and location into at least one continuous time period of availability, wherein no continuous time period of availability for a resource is represented by more than one resource entry; and
generate a resource entry for each continuous time period;
process a request to schedule a resource, the request comprising a requested resource identifier, date, start time, finish time, and location; identify a resource entry corresponding to the request; and modify the resource entry to remove the time period of the request. 16. The computer program product of claim 15, wherein in response to a request to schedule a resource comprising a start time equating to the start time of the resource entry corresponding to the request, the program code portions configured to modify the resource entry comprise program code portions configured to modify the resource entry start time to become the finish time of the request. 17. The computer program product of claim 16, wherein in response to a request to schedule a resource comprising a finish time equating to the finish time of the resource entry corresponding to the request, the program code instructions configured to modify the resource entry comprise program code instructions configured to modify the resource entry finish time to become the start time of the request. 18. The computer program product of claim 17, wherein in response to a request to schedule a resource comprising a start time that does not equate to the start time of the resource entry corresponding to the request, and the request comprises a finish time that does not equate to the finish time of the resource entry corresponding to the request, the program code instructions configured to modify the resource entry comprise program code instructions to divide the resource entry corresponding to the request into a first resource entry and a second resource entry, wherein the first resource entry comprises a start time equating to the start time of the resource entry corresponding to the request and a finish time equating to the start time of the request, and wherein the second resource entry comprises a start time equating to the finish time of the request and a finish time equating to the finish time of the resource entry corresponding to the request. 19. The computer program product of claim 15, wherein in response to a request to cancel a scheduled event for a resource, the computer program product further comprises program code instructions configured to append a time period of the scheduled event to a resource entry for which the time period is continuous. 20. The computer program product of claim 15, wherein the program code instructions configured to process the request to schedule a resource comprise program code instructions configured to receive a request comprising a resource identification, and at least one of a date range, a time duration, a time range, or acceptable locations, and the program code instructions configured to process the request comprise program code instructions configured to establish available time periods corresponding to the request. | A method, computing device and computer program product are provided to establish and maintain resource availability. Methods may include generating a representation of a resource availability schedule including at least one resource entry, where each resource entry includes a resource identification, a date, a location, a start time, and a finish time. Generating the representation may include: dividing the availability for each resource for each date and location into at least one continuous time period of availability, where no continuous time period of availability for a resource is represented by more than one resource entry; and generating a resource entry for each continuous time period. Methods may include: processing a request to schedule a resource, the request including a requested resource identifier, date, start time, finish time, and location; identifying a resource entry corresponding to the request; and modifying the resource entry to remove the time period of the request.1. A computing device comprising processing circuitry configured to:
generate a representation of a resource availability schedule comprising at least one resource entry, wherein each resource entry comprises a resource identification, a date, a location, a start time, and a finish time, and wherein the processing circuitry configured to generate the representation comprises processing circuitry configured to:
divide the availability for each resource for each date and location into at least one continuous time period of availability, wherein no continuous time period of availability for a resource is represented by more than one resource entry; and
generate a resource entry for each continuous time period;
process a request to schedule a resource, the request comprising a requested resource identifier, date, start time, finish time, and location; identify a resource entry corresponding to the request; and modify the resource entry to remove the time period of the request. 2. The computing device of claim 1, wherein in response to a request to schedule a resource comprising a start time equating to the start time of the resource entry corresponding to the request, the processing circuitry configured to modify the resource entry comprises processing circuitry configured to modify the resource entry start time to become the finish time of the request. 3. The computing device of claim 2, wherein in response to a request to schedule a resource comprising a finish time equating to the finish time of the resource entry corresponding to the request, the processing circuitry configured to modify the resource entry comprises processing circuitry configured to modify the resource entry finish time to become the start time of the request. 4. The computing device of claim 3, wherein in response to a request to schedule a resource comprising a start time that does not equate to the start time of the resource entry corresponding to the request, and the request comprises a finish time that does not equate to the finish time of the resource entry corresponding to the request, the processing circuitry configured to modify the resource entry comprises processing circuitry to divide the resource entry corresponding to the request into a first resource entry and a second resource entry, wherein the first resource entry comprises a start time equating to the start time of the resource entry corresponding to the request and a finish time equating to the start time of the request, and wherein the second resource entry comprises a start time equating to the finish time of the request and a finish time equating to the finish time of the resource entry corresponding to the request. 5. The computing device of claim 1, wherein in response to a request to cancel a scheduled event for a resource, the computing device further comprises processing circuitry configured to append a time period of the scheduled event to a resource entry for which the time period is continuous. 6. The computing device of claim 1, wherein the processing circuitry configured to process the request to schedule a resource comprises processing circuitry configured to receive a request comprising a resource identification, and at least one of a date range, a time duration, a time range, or acceptable locations, and the processing circuitry configured to process the request comprises processing circuitry configured to establish available time periods corresponding to the request. 7. The computing device of claim 6, further comprising processing circuitry configured to:
present the available time periods corresponding to the request; receive a selection from the available time periods; and process the selected request to schedule a resource for the selected time period. 8. A method comprising:
generating a representation of a resource availability schedule comprising at least one resource entry, wherein each resource entry comprises a resource identification, a date, a location, a start time, and a finish time, wherein generating the representation comprises:
dividing the availability for each resource for each date and location into at least one continuous time period of availability, wherein no continuous time period of availability for a resource is represented by more than one resource entry; and
generating a resource entry for each continuous time period;
processing a request to schedule a resource, the request comprising a requested resource identifier, date, start time, finish time, and location; identifying a resource entry corresponding to the request; and modifying the resource entry to remove the time period of the request. 9. The method of claim 8, wherein in response to a request to schedule a resource comprising a start time equating to the start time of the resource entry corresponding to the request, modifying the resource entry comprises modifying the resource entry start time to become the finish time of the request. 10. The method of claim 9, wherein in response to a request to schedule a resource comprising a finish time equating to the finish time of the resource entry corresponding to the request, modifying the resource entry comprises modifying the resource entry finish time to become the start time of the request. 11. The method of claim 10, wherein in response to a request to schedule a resource comprising a start time that does not equate to the start time of the resource entry corresponding to the request, and the request comprises a finish time that does not equate to the finish time of the resource entry corresponding to the request, modifying the resource entry comprises dividing the resource entry corresponding to the request into a first resource entry and a second resource entry, wherein the first resource entry comprises a start time equating to the start time of the resource entry corresponding to the request and a finish time equating to the start time of the request, and wherein the second resource entry comprises a start time equating to the finish time of the request and a finish time equating to the finish time of the resource entry corresponding to the request. 12. The method of claim 8, wherein in response to a request to cancel a scheduled event for a resource, appending a time period of the scheduled event to a resource entry for which the time period is continuous. 13. The method of claim 8, wherein processing the request to schedule a resource comprises receiving a request comprising a resource identification, and at least one of a date range, a time duration, a time range, or acceptable locations, and processing the request comprises establishing available time periods corresponding to the request. 14. The method of claim 13, further comprising:
causing presentation of the available time periods corresponding to the request; receiving a selection from the available time periods; and processing the selected request to schedule a resource for the selected time period. 15. A computer program product comprising a non-transitory computer readable storage medium having program code portions stored therein, the program code portions configured, upon execution, to:
generate a representation of a resource availability schedule comprising at least one resource entry, wherein each resource entry comprises a resource identification, a date, a location, a start time, and a finish time, and wherein the processing circuitry configured to generate the representation comprises processing circuitry configured to:
divide the availability for each resource for each date and location into at least one continuous time period of availability, wherein no continuous time period of availability for a resource is represented by more than one resource entry; and
generate a resource entry for each continuous time period;
process a request to schedule a resource, the request comprising a requested resource identifier, date, start time, finish time, and location; identify a resource entry corresponding to the request; and modify the resource entry to remove the time period of the request. 16. The computer program product of claim 15, wherein in response to a request to schedule a resource comprising a start time equating to the start time of the resource entry corresponding to the request, the program code portions configured to modify the resource entry comprise program code portions configured to modify the resource entry start time to become the finish time of the request. 17. The computer program product of claim 16, wherein in response to a request to schedule a resource comprising a finish time equating to the finish time of the resource entry corresponding to the request, the program code instructions configured to modify the resource entry comprise program code instructions configured to modify the resource entry finish time to become the start time of the request. 18. The computer program product of claim 17, wherein in response to a request to schedule a resource comprising a start time that does not equate to the start time of the resource entry corresponding to the request, and the request comprises a finish time that does not equate to the finish time of the resource entry corresponding to the request, the program code instructions configured to modify the resource entry comprise program code instructions to divide the resource entry corresponding to the request into a first resource entry and a second resource entry, wherein the first resource entry comprises a start time equating to the start time of the resource entry corresponding to the request and a finish time equating to the start time of the request, and wherein the second resource entry comprises a start time equating to the finish time of the request and a finish time equating to the finish time of the resource entry corresponding to the request. 19. The computer program product of claim 15, wherein in response to a request to cancel a scheduled event for a resource, the computer program product further comprises program code instructions configured to append a time period of the scheduled event to a resource entry for which the time period is continuous. 20. The computer program product of claim 15, wherein the program code instructions configured to process the request to schedule a resource comprise program code instructions configured to receive a request comprising a resource identification, and at least one of a date range, a time duration, a time range, or acceptable locations, and the program code instructions configured to process the request comprise program code instructions configured to establish available time periods corresponding to the request. | 2,100 |
6,528 | 6,528 | 14,929,143 | 2,159 | In a production environment, an entry is logged in a log journal to represent a read operation on a record of a file. A problematic transaction in a batch job is selected and set of operations performed by the problematic transaction is intercepted. The set includes a combination of read, write, update, delete operations, and operations that use external resources. A window of entries is determined in the log journal where the entry is a beginning entry in the window and an ending entry is a last entry captured in the log journal before detecting the error. From the window, those entries are filtered that correspond to the record. A final value of the record is copied from the production environment to a development environment and rolled back in the development environment to an initial value stored in the beginning entry. The problematic transaction is performed in the development environment. | 1. A method comprising:
logging, in a production environment, an entry in a log journal, the entry representing a read operation performed on a record of a file, the file being listed in a master file of a batch job; selecting a problematic transaction in the batch job; intercepting, for the problematic transaction, a set of operations performed by the problematic transaction, the set of operations comprising a combination of the read operation, a write operation, an update operation, and a delete operation; determining a window of entries in the log journal, wherein the entry is a beginning entry in the window of entries and an ending entry is a last entry captured in the log journal before detecting the error; filtering from the window of entries those entries that correspond to the record; copying, from the production environment to a development environment, a final value of the record; rolling back, in the development environment, the final value to an initial value stored in the beginning entry; and performing the problematic transaction in the development environment. 2. The method of claim 1, further comprising:
copying, from the production environment to the development environment, an external resource used in the problematic transaction. 3. The method of claim 1, further comprising:
including, from a set of records in a set of files in the production environment, in the development environment only a subset of records from a subset of files that are touched by an operation in the problematic transaction, the development environment including the record in the file; and setting for each record in the subset of records, a corresponding initial value, each corresponding initial value being present in the corresponding record from the subset of records at a time of the beginning entry. 4. The method of claim 1, wherein the determining is responsive to finding that the record is absent in the development environment. 5. The method of claim 1, wherein the intercepting occurs in a debug session in the production environment. 6. The method of claim 1, wherein the selecting is responsive to detecting an error in the production environment. 7. The method of claim 1, further comprising:
logging an additional entry in the log journal, the additional entry corresponding to at least one of the update operation, the write operation, and the delete operation. 8. The method of claim 1, wherein the method is embodied in a computer program product comprising one or more computer-readable storage devices and computer-readable program instructions which are stored on the one or more computer-readable storage devices and executed by one or more processors. 9. The method of claim 1, wherein the method is embodied in a computer system comprising one or more processors, one or more computer-readable memories, one or more computer-readable storage devices and program instructions which are stored on the one or more computer-readable storage devices for execution by the one or more processors via the one or more memories and executed by the one or more processors. 10. A computer program product comprising one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices, the stored program instructions comprising:
program instructions to log, in a production environment, an entry in a log journal, the entry representing a read operation performed on a record of a file, the file being listed in a master file of a batch job; program instructions to select a problematic transaction in the batch job; program instructions to intercept, for the problematic transaction, a set of operations performed by the problematic transaction, the set of operations comprising a combination of the read operation, a write operation, an update operation, and a delete operation; program instructions to determine a window of entries in the log journal, wherein the entry is a beginning entry in the window of entries and an ending entry is a last entry captured in the log journal before detecting the error; program instructions to filter from the window of entries those entries that correspond to the record; program instructions to copy, from the production environment to a development environment, a final value of the record; program instructions to roll back, in the development environment, the final value to an initial value stored in the beginning entry; and program instructions to perform the problematic transaction in the development environment. 11. The computer program product of claim 10, the stored program instructions further comprising:
program instructions to copy, from the production environment to the development environment, an external resource used in the problematic transaction. 12. The computer program product of claim 10, the stored program instructions further comprising:
program instructions to include, from a set of records in a set of files in the production environment, in the development environment only a subset of records from a subset of files that are touched by an operation in the problematic transaction, the development environment including the record in the file; and program instructions to set for each record in the subset of records, a corresponding initial value, each corresponding initial value being present in the corresponding record from the subset of records at a time of the beginning entry. 13. The computer program product of claim 10, wherein the window of entries in the log journal are determined in response to finding that the record is absent in the development environment. 14. The computer program product of claim 10, wherein intercepting the set of operations performed by the problematic transaction occurs in a debug session in the production environment. 15. The computer program product of claim 10, wherein selecting the problematic transaction in the batch job is responsive to detecting an error in the production environment. 16. The computer program product of claim 10, the stored program instructions further comprising:
program instructions to log an additional entry in the log journal, the additional entry corresponding to at least one of the update operation, the write operation, and the delete operation. 17. A computer system comprising one or more processors, one or more computer-readable memories, and one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, the stored program instructions comprising:
program instructions to log, in a production environment, an entry in a log journal, the entry representing a read operation performed on a record of a file, the file being listed in a master file of a batch job; program instructions to select a problematic transaction in the batch job; program instructions to intercept, for the problematic transaction, a set of operations performed by the problematic transaction, the set of operations comprising a combination of the read operation, a write operation, an update operation, and a delete operation; program instructions to determine a window of entries in the log journal, wherein the entry is a beginning entry in the window of entries and an ending entry is a last entry captured in the log journal before detecting the error; program instructions to filter from the window of entries those entries that correspond to the record; program instructions to copy, from the production environment to a development environment, a final value of the record; program instructions to roll back, in the development environment, the final value to an initial value stored in the beginning entry; and program instructions to perform the problematic transaction in the development environment. 18. The computer system of claim 17, the stored program instructions further comprising:
program instructions to copy, from the production environment to the development environment, an external resource used in the problematic transaction. 19. The computer system of claim 17, the stored program instructions further comprising:
program instructions to include, from a set of records in a set of files in the production environment, in the development environment only a subset of records from a subset of files that are touched by an operation in the problematic transaction, the development environment including the record in the file; and program instructions to set for each record in the subset of records, a corresponding initial value, each corresponding initial value being present in the corresponding record from the subset of records at a time of the beginning entry. 20. The computer system of claim 17, wherein the window of entries in the log journal are determined in response to finding that the record is absent in the development environment. | In a production environment, an entry is logged in a log journal to represent a read operation on a record of a file. A problematic transaction in a batch job is selected and set of operations performed by the problematic transaction is intercepted. The set includes a combination of read, write, update, delete operations, and operations that use external resources. A window of entries is determined in the log journal where the entry is a beginning entry in the window and an ending entry is a last entry captured in the log journal before detecting the error. From the window, those entries are filtered that correspond to the record. A final value of the record is copied from the production environment to a development environment and rolled back in the development environment to an initial value stored in the beginning entry. The problematic transaction is performed in the development environment.1. A method comprising:
logging, in a production environment, an entry in a log journal, the entry representing a read operation performed on a record of a file, the file being listed in a master file of a batch job; selecting a problematic transaction in the batch job; intercepting, for the problematic transaction, a set of operations performed by the problematic transaction, the set of operations comprising a combination of the read operation, a write operation, an update operation, and a delete operation; determining a window of entries in the log journal, wherein the entry is a beginning entry in the window of entries and an ending entry is a last entry captured in the log journal before detecting the error; filtering from the window of entries those entries that correspond to the record; copying, from the production environment to a development environment, a final value of the record; rolling back, in the development environment, the final value to an initial value stored in the beginning entry; and performing the problematic transaction in the development environment. 2. The method of claim 1, further comprising:
copying, from the production environment to the development environment, an external resource used in the problematic transaction. 3. The method of claim 1, further comprising:
including, from a set of records in a set of files in the production environment, in the development environment only a subset of records from a subset of files that are touched by an operation in the problematic transaction, the development environment including the record in the file; and setting for each record in the subset of records, a corresponding initial value, each corresponding initial value being present in the corresponding record from the subset of records at a time of the beginning entry. 4. The method of claim 1, wherein the determining is responsive to finding that the record is absent in the development environment. 5. The method of claim 1, wherein the intercepting occurs in a debug session in the production environment. 6. The method of claim 1, wherein the selecting is responsive to detecting an error in the production environment. 7. The method of claim 1, further comprising:
logging an additional entry in the log journal, the additional entry corresponding to at least one of the update operation, the write operation, and the delete operation. 8. The method of claim 1, wherein the method is embodied in a computer program product comprising one or more computer-readable storage devices and computer-readable program instructions which are stored on the one or more computer-readable storage devices and executed by one or more processors. 9. The method of claim 1, wherein the method is embodied in a computer system comprising one or more processors, one or more computer-readable memories, one or more computer-readable storage devices and program instructions which are stored on the one or more computer-readable storage devices for execution by the one or more processors via the one or more memories and executed by the one or more processors. 10. A computer program product comprising one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices, the stored program instructions comprising:
program instructions to log, in a production environment, an entry in a log journal, the entry representing a read operation performed on a record of a file, the file being listed in a master file of a batch job; program instructions to select a problematic transaction in the batch job; program instructions to intercept, for the problematic transaction, a set of operations performed by the problematic transaction, the set of operations comprising a combination of the read operation, a write operation, an update operation, and a delete operation; program instructions to determine a window of entries in the log journal, wherein the entry is a beginning entry in the window of entries and an ending entry is a last entry captured in the log journal before detecting the error; program instructions to filter from the window of entries those entries that correspond to the record; program instructions to copy, from the production environment to a development environment, a final value of the record; program instructions to roll back, in the development environment, the final value to an initial value stored in the beginning entry; and program instructions to perform the problematic transaction in the development environment. 11. The computer program product of claim 10, the stored program instructions further comprising:
program instructions to copy, from the production environment to the development environment, an external resource used in the problematic transaction. 12. The computer program product of claim 10, the stored program instructions further comprising:
program instructions to include, from a set of records in a set of files in the production environment, in the development environment only a subset of records from a subset of files that are touched by an operation in the problematic transaction, the development environment including the record in the file; and program instructions to set for each record in the subset of records, a corresponding initial value, each corresponding initial value being present in the corresponding record from the subset of records at a time of the beginning entry. 13. The computer program product of claim 10, wherein the window of entries in the log journal are determined in response to finding that the record is absent in the development environment. 14. The computer program product of claim 10, wherein intercepting the set of operations performed by the problematic transaction occurs in a debug session in the production environment. 15. The computer program product of claim 10, wherein selecting the problematic transaction in the batch job is responsive to detecting an error in the production environment. 16. The computer program product of claim 10, the stored program instructions further comprising:
program instructions to log an additional entry in the log journal, the additional entry corresponding to at least one of the update operation, the write operation, and the delete operation. 17. A computer system comprising one or more processors, one or more computer-readable memories, and one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, the stored program instructions comprising:
program instructions to log, in a production environment, an entry in a log journal, the entry representing a read operation performed on a record of a file, the file being listed in a master file of a batch job; program instructions to select a problematic transaction in the batch job; program instructions to intercept, for the problematic transaction, a set of operations performed by the problematic transaction, the set of operations comprising a combination of the read operation, a write operation, an update operation, and a delete operation; program instructions to determine a window of entries in the log journal, wherein the entry is a beginning entry in the window of entries and an ending entry is a last entry captured in the log journal before detecting the error; program instructions to filter from the window of entries those entries that correspond to the record; program instructions to copy, from the production environment to a development environment, a final value of the record; program instructions to roll back, in the development environment, the final value to an initial value stored in the beginning entry; and program instructions to perform the problematic transaction in the development environment. 18. The computer system of claim 17, the stored program instructions further comprising:
program instructions to copy, from the production environment to the development environment, an external resource used in the problematic transaction. 19. The computer system of claim 17, the stored program instructions further comprising:
program instructions to include, from a set of records in a set of files in the production environment, in the development environment only a subset of records from a subset of files that are touched by an operation in the problematic transaction, the development environment including the record in the file; and program instructions to set for each record in the subset of records, a corresponding initial value, each corresponding initial value being present in the corresponding record from the subset of records at a time of the beginning entry. 20. The computer system of claim 17, wherein the window of entries in the log journal are determined in response to finding that the record is absent in the development environment. | 2,100 |
6,529 | 6,529 | 14,853,973 | 2,125 | Methods and arrangements for cognitively processing image content. At least one image is accessed, wherein the at least one image comprises a compilation of objects. A plurality of verbal cues are received from a user relating to the at least one image, and the at least one received verbal cue is parsed. Using the parsed verbal cues, at least one object is identified in the compilation of objects, and at least one of the verbal cues related to the identified object is classified. A response to the user is generated, wherein the response comprises a natural language acknowledgement based on the classifying of the at least one verbal cue. Other variants and embodiments are broadly contemplated herein. | 1. A method of cognitively processing image content, said method comprising:
utilizing at least one processor to execute computer code that performs the steps of: accessing at least one image, wherein the at least one image comprises a compilation of objects; receiving a plurality of verbal cues from a user relating to the at least one image; parsing the plurality of received verbal cues; identifying, using the parsed verbal cues, at least one object in the compilation of objects; classifying at least one of the verbal cues related to the identified object; and generating a response to the user, wherein the response comprises a natural language acknowledgement based on the classifying of the at least one of the verbal cues. 2. The method according to claim 1, wherein said identifying comprises using a Semantic Entity-Relation Graph (SERG). 3. The method according to claim 1, wherein the classifying utilizes a corpus. 4. The method according to claim 1, wherein the generating a response comprises generating a Semantic Entity Relation Graph for at least one of the compilation of objects. 5. The method according to claim 4, wherein the generating further comprises modifying the Semantic Entity Relation Graph to generate a final Semantic Entity Relation Graph. 6. The method according to claim 4, wherein said generating a response comprises retrieval of a corresponding answer from said Semantic Entity Relation Graph. 7. The method according to claim 1, wherein the plurality of images is obtained from a video. 8. The method according to claim 1, wherein said classifying comprises using a classifier trained via a final Semantic Entity Related Graph and external ontology. 9. The method according to claim 1, wherein said parsing comprises using a semantic parser. 10. The method of claim 1, wherein the plurality of verbal cues relates to shopping for the at least one of the compilation of objects. 11. The method of claim 10, wherein the plurality of verbal cues relates to attributes of one the objects in said compilation of objects wherein the attributes are selected from the group consisting of colors, shapes, sizes, and brands. 12. The method according to claim 1, wherein said identifying the at least one of the objects comprises using spatial relation of the compilation of objects in the image. 13. The method according to claim 4, wherein said generating a response comprises utilizing a knowledge cartridge wherein the knowledge cartridge comprises a corpus, at least one Semantic Entity Relation Graph, and at least one website; and
wherein the knowledge cartridge is updated via machine learning. 14. An apparatus for cognitively processing image content, said apparatus comprising:
at least one processor; and a computer readable storage medium having computer readable program code embodied therewith and executable by the at least one processor, the computer readable program code comprising: computer readable program code configured to assess at least one image, wherein each trajectory comprises a compilation of objects; computer readable program code configured to receive a plurality of verbal cues from a user relating to the at least one image; computer readable program code configured to parse the plurality of received verbal cues; computer readable program code configured to identify, using the parsed verbal cues, at least one object in the compilation of objects; computer readable program code configured to classify at least one of the verbal cues related to the identified object; and computer readable program code configured to generate a response to the user, wherein the response comprises a natural language acknowledgement based on the classifying of the at least one of the verbal cues. 15. A computer program product for cognitively processing image content, said computer program product comprising:
a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: a computer readable program code configured to assess at least one image, wherein each trajectory comprises a compilation of objects; computer readable program code configured to receive a plurality of verbal cues from a user relating to the at least one image; computer readable program code configured to parse the plurality of received verbal cues; computer readable program code configured to identify, using the parsed verbal cues, at least one object in the compilation of objects; computer readable program code configured to classify at least one of the verbal cues related to the identified object; and computer readable program code configured to generate a response to the user, wherein the response comprises a natural language acknowledgement based on the classifying of the at least one of the verbal cues. 16. The computer program product according to claim 15, wherein the identifying comprises using a Semantic Entity-Relation Graph. 17. The computer program product according to claim 15, wherein the classifying utilizes a corpus. 18. The computer program product according to claim 15, wherein the generating a response comprises generating a Semantic Entity-Relation Graph for at least one of the compilation of objects. 19. The computer program product according to claim 15, wherein the identifying the at least one of the objects comprises using spatial relation of the compilation of objects in the image. 20. A method comprising:
accessing at least one image, wherein the at least one image comprises at least one purchasable object; receiving at least one verbal question from a user relating to the at least one image, wherein the at least one verbal question relates to shopping for the purchasable object; utilizing a Semantic Entity-Relation Graph on the image of the purchasable object and the at least one verbal question, wherein the Semantic-Entity-Relation graph parses the at least one verbal question and searches a corpus for at least one object similar to the purchasable object; and thereupon generating a natural language response to the verbal question regarding the purchasable object. | Methods and arrangements for cognitively processing image content. At least one image is accessed, wherein the at least one image comprises a compilation of objects. A plurality of verbal cues are received from a user relating to the at least one image, and the at least one received verbal cue is parsed. Using the parsed verbal cues, at least one object is identified in the compilation of objects, and at least one of the verbal cues related to the identified object is classified. A response to the user is generated, wherein the response comprises a natural language acknowledgement based on the classifying of the at least one verbal cue. Other variants and embodiments are broadly contemplated herein.1. A method of cognitively processing image content, said method comprising:
utilizing at least one processor to execute computer code that performs the steps of: accessing at least one image, wherein the at least one image comprises a compilation of objects; receiving a plurality of verbal cues from a user relating to the at least one image; parsing the plurality of received verbal cues; identifying, using the parsed verbal cues, at least one object in the compilation of objects; classifying at least one of the verbal cues related to the identified object; and generating a response to the user, wherein the response comprises a natural language acknowledgement based on the classifying of the at least one of the verbal cues. 2. The method according to claim 1, wherein said identifying comprises using a Semantic Entity-Relation Graph (SERG). 3. The method according to claim 1, wherein the classifying utilizes a corpus. 4. The method according to claim 1, wherein the generating a response comprises generating a Semantic Entity Relation Graph for at least one of the compilation of objects. 5. The method according to claim 4, wherein the generating further comprises modifying the Semantic Entity Relation Graph to generate a final Semantic Entity Relation Graph. 6. The method according to claim 4, wherein said generating a response comprises retrieval of a corresponding answer from said Semantic Entity Relation Graph. 7. The method according to claim 1, wherein the plurality of images is obtained from a video. 8. The method according to claim 1, wherein said classifying comprises using a classifier trained via a final Semantic Entity Related Graph and external ontology. 9. The method according to claim 1, wherein said parsing comprises using a semantic parser. 10. The method of claim 1, wherein the plurality of verbal cues relates to shopping for the at least one of the compilation of objects. 11. The method of claim 10, wherein the plurality of verbal cues relates to attributes of one the objects in said compilation of objects wherein the attributes are selected from the group consisting of colors, shapes, sizes, and brands. 12. The method according to claim 1, wherein said identifying the at least one of the objects comprises using spatial relation of the compilation of objects in the image. 13. The method according to claim 4, wherein said generating a response comprises utilizing a knowledge cartridge wherein the knowledge cartridge comprises a corpus, at least one Semantic Entity Relation Graph, and at least one website; and
wherein the knowledge cartridge is updated via machine learning. 14. An apparatus for cognitively processing image content, said apparatus comprising:
at least one processor; and a computer readable storage medium having computer readable program code embodied therewith and executable by the at least one processor, the computer readable program code comprising: computer readable program code configured to assess at least one image, wherein each trajectory comprises a compilation of objects; computer readable program code configured to receive a plurality of verbal cues from a user relating to the at least one image; computer readable program code configured to parse the plurality of received verbal cues; computer readable program code configured to identify, using the parsed verbal cues, at least one object in the compilation of objects; computer readable program code configured to classify at least one of the verbal cues related to the identified object; and computer readable program code configured to generate a response to the user, wherein the response comprises a natural language acknowledgement based on the classifying of the at least one of the verbal cues. 15. A computer program product for cognitively processing image content, said computer program product comprising:
a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: a computer readable program code configured to assess at least one image, wherein each trajectory comprises a compilation of objects; computer readable program code configured to receive a plurality of verbal cues from a user relating to the at least one image; computer readable program code configured to parse the plurality of received verbal cues; computer readable program code configured to identify, using the parsed verbal cues, at least one object in the compilation of objects; computer readable program code configured to classify at least one of the verbal cues related to the identified object; and computer readable program code configured to generate a response to the user, wherein the response comprises a natural language acknowledgement based on the classifying of the at least one of the verbal cues. 16. The computer program product according to claim 15, wherein the identifying comprises using a Semantic Entity-Relation Graph. 17. The computer program product according to claim 15, wherein the classifying utilizes a corpus. 18. The computer program product according to claim 15, wherein the generating a response comprises generating a Semantic Entity-Relation Graph for at least one of the compilation of objects. 19. The computer program product according to claim 15, wherein the identifying the at least one of the objects comprises using spatial relation of the compilation of objects in the image. 20. A method comprising:
accessing at least one image, wherein the at least one image comprises at least one purchasable object; receiving at least one verbal question from a user relating to the at least one image, wherein the at least one verbal question relates to shopping for the purchasable object; utilizing a Semantic Entity-Relation Graph on the image of the purchasable object and the at least one verbal question, wherein the Semantic-Entity-Relation graph parses the at least one verbal question and searches a corpus for at least one object similar to the purchasable object; and thereupon generating a natural language response to the verbal question regarding the purchasable object. | 2,100 |
6,530 | 6,530 | 15,489,045 | 2,161 | A method and system for managing three-dimensional massive model visualization data sets. The method comprises compiling a vehicle list of vehicles for which the three-dimensional massive model visualization data sets are to be built. The method automatically builds the three-dimensional massive model visualization data sets for vehicles in the vehicle list using a computer system. The method stores the three-dimensional massive model visualization data sets in a group of repositories. The method distributes the three-dimensional massive model visualization data sets for displaying massive model visualizations for the vehicles using the three-dimensional massive model visualization data sets on client devices. The method may selectively update a three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date. | 1. A method for managing three-dimensional massive model visualization data sets, the method comprising:
compiling a list of objects for which the three-dimensional massive model visualization data sets are to be built; automatically building the three-dimensional massive model visualization data sets for the objects in the list using a computer system; storing the three-dimensional massive model visualization data sets in a group of repositories; distributing the three-dimensional massive model visualization data sets for displaying massive model visualizations for the objects using the three-dimensional massive model visualization data sets on client devices; and receiving user input of a request for selectively updating a three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date. 2. The method of claim 1, wherein selectively updating the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date comprises:
updating the three-dimensional massive model visualization data set located on the group of repositories. 3. The method of claim 1 further comprising:
selectively updating the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date when the user input is received through updating the three-dimensional massive model visualization data set located on a client device by downloading information to rebuild the three-dimensional massive model visualization data set. 4. The method of claim 3 further comprising:
updating the three-dimensional massive model visualization data set located on the client device when the user input is received by downloading all of a newest three-dimensional massive model data set from a repository. 5. The method of claim 3 further comprising:
updating the three-dimensional massive model visualization data set located on the client device when the user input is received by rebuilding a first portion of the three-dimensional massive model visualization data set on the client device that is out-of-date while a second portion of the three-dimensional massive model visualization data set is unchanged. 6. The method of claim 1 further comprising:
selectively updating the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date when the user input is received by updating the three-dimensional massive model visualization data set on a client device by at least one of masking a first group of models or adding a second group of models. 7. The method of claim 3 further comprising:
updating the three-dimensional massive model visualization data set located on the client device when the user input is received by rebuilding of all of the three-dimensional massive model visualization data set on the client device that is out-of-date. 8. The method of claim 1 further comprising:
displaying the massive model visualizations for the objects on the client devices using the three-dimensional massive model visualization data sets. 9. The method of claim 1 further comprising:
displaying a massive model visualization for a given object from the list of objects that are displayable using the three-dimensional massive model visualization data sets stored in the group of repositories in the computer system, to thereby display a given configuration of an object from the list of objects. 10. The method of claim 1, wherein the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets represents an instance of an object. 11. The method of claim 1, wherein the objects are selected from at least one of a mobile platform, a stationary platform, a land-based structure, an aquatic-based structure, a space-based structure, an aircraft, a surface ship, a tank, a personnel carrier, a train, a spacecraft, a space station, a satellite, a submarine, an automobile, a power plant, a bridge, a dam, a house, a manufacturing facility, and a building. 12. A method of displaying three-dimensional massive model visualization data sets on a client device, the method comprising:
displaying a vehicle list of vehicles displayable that are on the client device; downloading a three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets corresponding to a vehicle selected from the vehicle list from a group of repositories in a computer system; and displaying a massive model visualization of the vehicle using the three-dimensional massive model visualization data set downloaded to the client device. 13. The method of claim 12 further comprising:
selectively updating the three-dimensional massive model visualization data set prior to displaying the massive model visualization of the vehicle using the three-dimensional massive model visualization data set downloaded to the client device when the three-dimensional massive model visualization data set is out-of-date and when a user input is received to update the three-dimensional massive model visualization data set. 14. The method of claim 13 further comprising:
comparing time stamps between the three-dimensional massive model visualization data set located on the client device with a source copy of the three-dimensional massive model visualization data set on a repository. 15. The method of claim 13, wherein selectively updating the three-dimensional massive model visualization data set when the three-dimensional massive model visualization data set is out-of-date and when the user input is received to update the three-dimensional massive model visualization data set comprises:
updating the three-dimensional massive model visualization data set located on the group of repositories in the computer system when the user input is received to update the three-dimensional massive model visualization data set. 16. The method of claim 13, wherein selectively updating the three-dimensional massive model visualization data set when the three-dimensional massive model visualization data set is out-of-date and when the user input is received to update the three-dimensional massive model visualization data set comprises:
updating the three-dimensional massive model visualization data set located on the client device when the user input is received to update the three-dimensional massive model visualization data set. 17. The method of claim 16, wherein updating the three-dimensional massive model visualization data set located on the client device when the user input is received to update the three-dimensional massive model visualization data set comprises:
downloading all of a newest three-dimensional massive model visualization data set from a repository when the user input is received to update the three-dimensional massive model visualization data set. 18. The method of claim 16, wherein updating the three-dimensional massive model visualization data set located on the client device when the user input is received to update the three-dimensional massive model visualization data set comprises:
rebuilding a first portion of the three-dimensional massive model visualization data set on the client device that is out-of-date while a second portion of the three-dimensional massive model visualization data set is unchanged when the user input is received to update the three-dimensional massive model visualization data set. 19. The method of claim 13, wherein selectively updating the three-dimensional massive model visualization data set when the three-dimensional massive model visualization data set is out-of-date and when the user input is received to update the three-dimensional massive model visualization data set comprises:
updating the three-dimensional massive model visualization data set on the client device by at least one of masking a first group of models or adding a second group of models when the user input is received to update the three-dimensional massive model visualization data set. 20. The method of claim 12, wherein the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets represents an instance of a vehicle. 21. A three-dimensional massive model visualization data sets system comprising:
a computer system; and a data set manager in the computer system, wherein the data set manager is configured to compile a vehicle list of vehicles for which three-dimensional massive model visualization data sets are to be built; automatically build the three-dimensional massive model visualization data sets for vehicles in the vehicle list using the computer system; store the three-dimensional massive model visualization data sets in a group of repositories; distribute the three-dimensional massive model visualization data sets for displaying massive model visualizations for the vehicles using the three-dimensional massive model visualization data sets on client devices; and receive user input of a request for selectively updating a three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date. 22. The three-dimensional massive model visualization data sets system of claim 21 further comprising:
a client device local to a user that requests a three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets from the group of repositories for displaying a three-dimensional massive model visualization for the vehicles. 23. The three-dimensional massive model visualization data sets system of claim 21, wherein, the data set manager is configured to update the three-dimensional massive model visualization data set located on model the group of repositories when the three-dimensional massive model visualization data set is out-of-date. 24. The three-dimensional massive model visualization data sets system of claim 22, wherein the client device is configured to selectively update the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date when the user input is received through updating the three-dimensional massive model visualization data set located on the client device by downloading information to rebuild the three-dimensional massive model visualization data set. 25. The three-dimensional massive model visualization data sets system of claim 24, wherein the client device is configured to rebuild all of the three-dimensional massive model visualization data set on the client device when the user input is received. 26. The three-dimensional massive model visualization data sets system of claim 24, wherein the client device is configured to rebuild a first portion of the three-dimensional massive model visualization data set on the client device that is out-of-date while a second portion of the three-dimensional massive model visualization data set is unchanged on the client device when the user input is received. 27. The three-dimensional massive model visualization data sets system of claim 22, wherein the client device is configured to update the three-dimensional massive model visualization data set on a client device by at least one of masking a first group of models or adding a second group of models when the user input is received. 28. The three-dimensional massive model visualization data sets system of claim 24, wherein the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets represents an instance of a vehicle. | A method and system for managing three-dimensional massive model visualization data sets. The method comprises compiling a vehicle list of vehicles for which the three-dimensional massive model visualization data sets are to be built. The method automatically builds the three-dimensional massive model visualization data sets for vehicles in the vehicle list using a computer system. The method stores the three-dimensional massive model visualization data sets in a group of repositories. The method distributes the three-dimensional massive model visualization data sets for displaying massive model visualizations for the vehicles using the three-dimensional massive model visualization data sets on client devices. The method may selectively update a three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date.1. A method for managing three-dimensional massive model visualization data sets, the method comprising:
compiling a list of objects for which the three-dimensional massive model visualization data sets are to be built; automatically building the three-dimensional massive model visualization data sets for the objects in the list using a computer system; storing the three-dimensional massive model visualization data sets in a group of repositories; distributing the three-dimensional massive model visualization data sets for displaying massive model visualizations for the objects using the three-dimensional massive model visualization data sets on client devices; and receiving user input of a request for selectively updating a three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date. 2. The method of claim 1, wherein selectively updating the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date comprises:
updating the three-dimensional massive model visualization data set located on the group of repositories. 3. The method of claim 1 further comprising:
selectively updating the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date when the user input is received through updating the three-dimensional massive model visualization data set located on a client device by downloading information to rebuild the three-dimensional massive model visualization data set. 4. The method of claim 3 further comprising:
updating the three-dimensional massive model visualization data set located on the client device when the user input is received by downloading all of a newest three-dimensional massive model data set from a repository. 5. The method of claim 3 further comprising:
updating the three-dimensional massive model visualization data set located on the client device when the user input is received by rebuilding a first portion of the three-dimensional massive model visualization data set on the client device that is out-of-date while a second portion of the three-dimensional massive model visualization data set is unchanged. 6. The method of claim 1 further comprising:
selectively updating the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date when the user input is received by updating the three-dimensional massive model visualization data set on a client device by at least one of masking a first group of models or adding a second group of models. 7. The method of claim 3 further comprising:
updating the three-dimensional massive model visualization data set located on the client device when the user input is received by rebuilding of all of the three-dimensional massive model visualization data set on the client device that is out-of-date. 8. The method of claim 1 further comprising:
displaying the massive model visualizations for the objects on the client devices using the three-dimensional massive model visualization data sets. 9. The method of claim 1 further comprising:
displaying a massive model visualization for a given object from the list of objects that are displayable using the three-dimensional massive model visualization data sets stored in the group of repositories in the computer system, to thereby display a given configuration of an object from the list of objects. 10. The method of claim 1, wherein the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets represents an instance of an object. 11. The method of claim 1, wherein the objects are selected from at least one of a mobile platform, a stationary platform, a land-based structure, an aquatic-based structure, a space-based structure, an aircraft, a surface ship, a tank, a personnel carrier, a train, a spacecraft, a space station, a satellite, a submarine, an automobile, a power plant, a bridge, a dam, a house, a manufacturing facility, and a building. 12. A method of displaying three-dimensional massive model visualization data sets on a client device, the method comprising:
displaying a vehicle list of vehicles displayable that are on the client device; downloading a three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets corresponding to a vehicle selected from the vehicle list from a group of repositories in a computer system; and displaying a massive model visualization of the vehicle using the three-dimensional massive model visualization data set downloaded to the client device. 13. The method of claim 12 further comprising:
selectively updating the three-dimensional massive model visualization data set prior to displaying the massive model visualization of the vehicle using the three-dimensional massive model visualization data set downloaded to the client device when the three-dimensional massive model visualization data set is out-of-date and when a user input is received to update the three-dimensional massive model visualization data set. 14. The method of claim 13 further comprising:
comparing time stamps between the three-dimensional massive model visualization data set located on the client device with a source copy of the three-dimensional massive model visualization data set on a repository. 15. The method of claim 13, wherein selectively updating the three-dimensional massive model visualization data set when the three-dimensional massive model visualization data set is out-of-date and when the user input is received to update the three-dimensional massive model visualization data set comprises:
updating the three-dimensional massive model visualization data set located on the group of repositories in the computer system when the user input is received to update the three-dimensional massive model visualization data set. 16. The method of claim 13, wherein selectively updating the three-dimensional massive model visualization data set when the three-dimensional massive model visualization data set is out-of-date and when the user input is received to update the three-dimensional massive model visualization data set comprises:
updating the three-dimensional massive model visualization data set located on the client device when the user input is received to update the three-dimensional massive model visualization data set. 17. The method of claim 16, wherein updating the three-dimensional massive model visualization data set located on the client device when the user input is received to update the three-dimensional massive model visualization data set comprises:
downloading all of a newest three-dimensional massive model visualization data set from a repository when the user input is received to update the three-dimensional massive model visualization data set. 18. The method of claim 16, wherein updating the three-dimensional massive model visualization data set located on the client device when the user input is received to update the three-dimensional massive model visualization data set comprises:
rebuilding a first portion of the three-dimensional massive model visualization data set on the client device that is out-of-date while a second portion of the three-dimensional massive model visualization data set is unchanged when the user input is received to update the three-dimensional massive model visualization data set. 19. The method of claim 13, wherein selectively updating the three-dimensional massive model visualization data set when the three-dimensional massive model visualization data set is out-of-date and when the user input is received to update the three-dimensional massive model visualization data set comprises:
updating the three-dimensional massive model visualization data set on the client device by at least one of masking a first group of models or adding a second group of models when the user input is received to update the three-dimensional massive model visualization data set. 20. The method of claim 12, wherein the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets represents an instance of a vehicle. 21. A three-dimensional massive model visualization data sets system comprising:
a computer system; and a data set manager in the computer system, wherein the data set manager is configured to compile a vehicle list of vehicles for which three-dimensional massive model visualization data sets are to be built; automatically build the three-dimensional massive model visualization data sets for vehicles in the vehicle list using the computer system; store the three-dimensional massive model visualization data sets in a group of repositories; distribute the three-dimensional massive model visualization data sets for displaying massive model visualizations for the vehicles using the three-dimensional massive model visualization data sets on client devices; and receive user input of a request for selectively updating a three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date. 22. The three-dimensional massive model visualization data sets system of claim 21 further comprising:
a client device local to a user that requests a three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets from the group of repositories for displaying a three-dimensional massive model visualization for the vehicles. 23. The three-dimensional massive model visualization data sets system of claim 21, wherein, the data set manager is configured to update the three-dimensional massive model visualization data set located on model the group of repositories when the three-dimensional massive model visualization data set is out-of-date. 24. The three-dimensional massive model visualization data sets system of claim 22, wherein the client device is configured to selectively update the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets when the three-dimensional massive model visualization data set is out-of-date when the user input is received through updating the three-dimensional massive model visualization data set located on the client device by downloading information to rebuild the three-dimensional massive model visualization data set. 25. The three-dimensional massive model visualization data sets system of claim 24, wherein the client device is configured to rebuild all of the three-dimensional massive model visualization data set on the client device when the user input is received. 26. The three-dimensional massive model visualization data sets system of claim 24, wherein the client device is configured to rebuild a first portion of the three-dimensional massive model visualization data set on the client device that is out-of-date while a second portion of the three-dimensional massive model visualization data set is unchanged on the client device when the user input is received. 27. The three-dimensional massive model visualization data sets system of claim 22, wherein the client device is configured to update the three-dimensional massive model visualization data set on a client device by at least one of masking a first group of models or adding a second group of models when the user input is received. 28. The three-dimensional massive model visualization data sets system of claim 24, wherein the three-dimensional massive model visualization data set in the three-dimensional massive model visualization data sets represents an instance of a vehicle. | 2,100 |
6,531 | 6,531 | 16,044,176 | 2,196 | The disclosure provides an approach for eliminating issues associated with the use of an L2 extension and ARP calls after migrating a virtual machine from one host to another host. The approach involves placing nodes within a network within their own subnetworks, each subnetwork having an IP address range of one address. Placing nodes into subnets of one avoids intra-subnet forwarding, eliminating the need for ARP calls and for L2 extensions. | 1. A method of migrating a virtual machine (VM) from a first host to a second host, the first host located within a computer system, the computer system comprising a plurality of routers, the method comprising:
assigning the VM to a first network, by a first controller, wherein the first network has an address range of one address, and wherein the first controller manages a routing table for substantially all routers of the plurality of routers; migrating the VM from the first host to the second host; and updating a first routing table of a first router, by the first controller, to reflect a location of the VM at the second host, wherein the first router is one of the plurality of routers. 2. The method of claim 1, wherein the first host and the second host are located in a first data center, and wherein the first controller is configured to centrally manage routing tables of routers within the first data center, and wherein the first controller is a distributed controller located on a plurality of hosts within the computer system. 3. The method of claim 1, wherein the first host is located in a first data center, the second host is located in a second data center, the second data center comprising a second router, the method further comprising:
updating a second routing table of the second router, by the first controller, to reflect the location of the VM at the second host. 4. The method of claim 1, wherein the first host is located in a first data center, the second host is located in a second data center, the second data center comprising a second router, the method further comprising:
notifying a second controller, by the first controller, of the location of the VM at the second host; and updating a second routing table of the second router, by the second controller, to reflect the location of the VM at the second host. 5. The method of claim 1, wherein the VM transmits substantially all outgoing packets of the VM to the first router. 6. The method of claim 1, wherein subsequent to completion of the migrating, the VM does not transmit an announcement of its new location to a switch. 7. The method of claim 1, wherein the migrating does not include migrating over a Layer 2 (L2) extension. 8. A non-transitory computer readable medium comprising instructions to be executed in a processor of a computer system, the instructions when executed in the processor cause the computer system to carry out a method of migrating a virtual machine (VM) from a first host to a second host, the first host located within a computer system, the computer system comprising a plurality of routers, the method comprising:
assigning the VM to a first network, by a first controller, wherein the first network has an address range of one address, and wherein the first controller manages a routing table for substantially all routers of the plurality of souters; migrating the VM from the first host to the second host; and updating a first routing table of a first router, by the first controller, to reflect a location of the VM at the second host, wherein the first controller is a distributed controller located on a plurality of hosts within the computer system. 9. The non-transitory computer readable medium of claim 8, wherein the first host and the second host are located in a first data center, and wherein the first controller is configured to centrally manage routing tables of routers within the first data center. 10. The non-transitory computer readable medium of claim 8, wherein the first host is located in a first data center, the second host is located in a second data center, the second data center comprising a second router, the method further comprising:
updating a second routing table of the second router, by the first controller, to reflect the location of the VM at the second host. 11. The non-transitory computer readable medium of claim 8, wherein the first host is located in a first data center, the second host is located in a second data center, the second data center comprising a second router, the method further comprising:
notifying a second controller, by the first controller, of the location of the VM at the second host; and updating a second routing table of the second router, by the second controller, to reflect the location of the VM at the second host. 12. The non-transitory computer readable medium of claim 8, wherein the VM transmits substantially all outgoing packets of the VM to the first router. 13. The non-transitory computer readable medium of claim 8, wherein subsequent to completion of the migrating, the VM does not transmit an announcement of its new location to a switch. 14. The non-transitory computer readable medium of claim 8, wherein the migrating does not include migrating over a Layer 2 (L2) extension. 15. A computer system comprising:
a VM and a first host; a first network; a plurality of routers comprising a first router, the first router comprising a first routing table; a first controller, wherein the first controller manages a routing table for substantially all routers of the plurality of routers; and at least one processor, wherein the at least one processor is programmed to carry out a method of migrating a virtual machine (VM) from the first host to a second host, said method comprising:
assigning the VM to the first network, by the first controller, wherein the first network has an address range of one address;
migrating the VM from the first host to the second host; and
updating the first routing table of the first router, by the first controller, to reflect a location of the VM at the second host. 16. The computer system of claim 15, wherein the first host and the second host are located in a first data center, and wherein the first controller is configured to centrally manage routing tables of routers within the first data center. 17. The computer system of claim 15, wherein the first host is located in a first data center, the second host is located in a second data center, the second data center comprising a second router, the method further comprising:
updating a second routing table of the second router, by the first controller, to reflect the location of the VM at the second host. 18. The computer system of claim 15, wherein the first host is located in a first data center, the second host is located in a second data center, the second data center comprising a second router, the method further comprising:
notifying a second controller, by the first controller, of the location of the VM at the second host; and updating a second routing table of the second router, by the second central controller, to reflect the location of the VM at the second host. 19. The computer system of claim 15, wherein subsequent to completion of the migrating, the VM does not transmit an announcement of its new location to a switch. 20. The computer system of claim 15, wherein the migrating does not include migrating over a Layer 2 (L2) extension. | The disclosure provides an approach for eliminating issues associated with the use of an L2 extension and ARP calls after migrating a virtual machine from one host to another host. The approach involves placing nodes within a network within their own subnetworks, each subnetwork having an IP address range of one address. Placing nodes into subnets of one avoids intra-subnet forwarding, eliminating the need for ARP calls and for L2 extensions.1. A method of migrating a virtual machine (VM) from a first host to a second host, the first host located within a computer system, the computer system comprising a plurality of routers, the method comprising:
assigning the VM to a first network, by a first controller, wherein the first network has an address range of one address, and wherein the first controller manages a routing table for substantially all routers of the plurality of routers; migrating the VM from the first host to the second host; and updating a first routing table of a first router, by the first controller, to reflect a location of the VM at the second host, wherein the first router is one of the plurality of routers. 2. The method of claim 1, wherein the first host and the second host are located in a first data center, and wherein the first controller is configured to centrally manage routing tables of routers within the first data center, and wherein the first controller is a distributed controller located on a plurality of hosts within the computer system. 3. The method of claim 1, wherein the first host is located in a first data center, the second host is located in a second data center, the second data center comprising a second router, the method further comprising:
updating a second routing table of the second router, by the first controller, to reflect the location of the VM at the second host. 4. The method of claim 1, wherein the first host is located in a first data center, the second host is located in a second data center, the second data center comprising a second router, the method further comprising:
notifying a second controller, by the first controller, of the location of the VM at the second host; and updating a second routing table of the second router, by the second controller, to reflect the location of the VM at the second host. 5. The method of claim 1, wherein the VM transmits substantially all outgoing packets of the VM to the first router. 6. The method of claim 1, wherein subsequent to completion of the migrating, the VM does not transmit an announcement of its new location to a switch. 7. The method of claim 1, wherein the migrating does not include migrating over a Layer 2 (L2) extension. 8. A non-transitory computer readable medium comprising instructions to be executed in a processor of a computer system, the instructions when executed in the processor cause the computer system to carry out a method of migrating a virtual machine (VM) from a first host to a second host, the first host located within a computer system, the computer system comprising a plurality of routers, the method comprising:
assigning the VM to a first network, by a first controller, wherein the first network has an address range of one address, and wherein the first controller manages a routing table for substantially all routers of the plurality of souters; migrating the VM from the first host to the second host; and updating a first routing table of a first router, by the first controller, to reflect a location of the VM at the second host, wherein the first controller is a distributed controller located on a plurality of hosts within the computer system. 9. The non-transitory computer readable medium of claim 8, wherein the first host and the second host are located in a first data center, and wherein the first controller is configured to centrally manage routing tables of routers within the first data center. 10. The non-transitory computer readable medium of claim 8, wherein the first host is located in a first data center, the second host is located in a second data center, the second data center comprising a second router, the method further comprising:
updating a second routing table of the second router, by the first controller, to reflect the location of the VM at the second host. 11. The non-transitory computer readable medium of claim 8, wherein the first host is located in a first data center, the second host is located in a second data center, the second data center comprising a second router, the method further comprising:
notifying a second controller, by the first controller, of the location of the VM at the second host; and updating a second routing table of the second router, by the second controller, to reflect the location of the VM at the second host. 12. The non-transitory computer readable medium of claim 8, wherein the VM transmits substantially all outgoing packets of the VM to the first router. 13. The non-transitory computer readable medium of claim 8, wherein subsequent to completion of the migrating, the VM does not transmit an announcement of its new location to a switch. 14. The non-transitory computer readable medium of claim 8, wherein the migrating does not include migrating over a Layer 2 (L2) extension. 15. A computer system comprising:
a VM and a first host; a first network; a plurality of routers comprising a first router, the first router comprising a first routing table; a first controller, wherein the first controller manages a routing table for substantially all routers of the plurality of routers; and at least one processor, wherein the at least one processor is programmed to carry out a method of migrating a virtual machine (VM) from the first host to a second host, said method comprising:
assigning the VM to the first network, by the first controller, wherein the first network has an address range of one address;
migrating the VM from the first host to the second host; and
updating the first routing table of the first router, by the first controller, to reflect a location of the VM at the second host. 16. The computer system of claim 15, wherein the first host and the second host are located in a first data center, and wherein the first controller is configured to centrally manage routing tables of routers within the first data center. 17. The computer system of claim 15, wherein the first host is located in a first data center, the second host is located in a second data center, the second data center comprising a second router, the method further comprising:
updating a second routing table of the second router, by the first controller, to reflect the location of the VM at the second host. 18. The computer system of claim 15, wherein the first host is located in a first data center, the second host is located in a second data center, the second data center comprising a second router, the method further comprising:
notifying a second controller, by the first controller, of the location of the VM at the second host; and updating a second routing table of the second router, by the second central controller, to reflect the location of the VM at the second host. 19. The computer system of claim 15, wherein subsequent to completion of the migrating, the VM does not transmit an announcement of its new location to a switch. 20. The computer system of claim 15, wherein the migrating does not include migrating over a Layer 2 (L2) extension. | 2,100 |
6,532 | 6,532 | 15,713,587 | 2,138 | A memory device includes an array of 2T1C DRAM cells and a memory controller. The DRAM cells are arranged as a plurality of rows and columns of DRAM cells. The memory controller is internal to the memory device and is coupled to the array of DRAM cells. The memory controller is capable of receiving commands input to the memory device and is responsive to the received commands to control row-major access and column-major access to the array of DRAM cells. In one embodiment, each transistor of a memory cell includes a terminal directly coupled to a storage node of the capacitor. In another embodiment, a first transistor of a memory cell includes a terminal directly coupled to a storage node of the capacitor, and a second transistor of the 2T1C memory cell includes a gate terminal directly coupled to the storage node of the capacitor. | 1. A memory device, comprising:
an array of a plurality of dynamic random access memory (DRAM) cells, the array arranged as a plurality of rows of DRAM cells and a plurality of columns of DRAM cells; and a memory controller internal to the memory device and coupled to the array of DRAM cells, the memory controller capable of receiving commands input to the memory device and being responsive to the received commands to control row-major access and column-major access to the array of DRAM cells. 2. The memory device of claim 1, wherein the array of the plurality of DRAM cells further comprises a plurality of row bit lines and a plurality of column bit lines, each respective row bit line being coupled to DRAM cells in a corresponding row, and each respective column bit line being coupled to DRAM cells in a corresponding column,
the memory device further comprising: a row buffer coupled to the plurality of row bit lines; and a column buffer coupled to the plurality of column bit lines, wherein the memory controller internal to the memory device is further coupled to the row buffer and the column buffer and is configured to control operation of the row buffer and the column buffer in response to the received commands. 3. The memory device of claim 2, further comprising a precharge circuit coupled to each row line and each column bit line. 4. The memory device of claim 2, wherein the memory device is part of a dual in-line memory module (DIMM). 5. The memory device of claim 1, wherein each DRAM cell comprises a two-transistor, one capacitor (2T1C) memory cell. 6. The memory device of claim 5, wherein each transistor of the 2T1C memory cell comprises a terminal directly coupled to a storage node of the capacitor. 7. The memory device of claim 5, wherein a first transistor of the 2T1C memory cell comprises a terminal directly coupled to a storage node of the capacitor, and a second transistor of the 2T1C memory cell comprises a gate terminal directly coupled to the storage node of the capacitor. 8. A memory device, comprising:
an array of a plurality of dynamic random access memory (DRAM) cells, the array arranged to comprise a plurality of rows of DRAM cells and a plurality of columns of DRAM cells, the array of the plurality of DRAM cells further comprising a plurality of row wordline driver lines and a plurality of column wordline driver lines, each row wordline driver line being coupled to a corresponding DRAM cell in a row of DRAM cells, and each column wordline driver line being coupled to a corresponding DRAM cell in a column of DRAM cells; a plurality of row wordline drivers, each row wordline driver being coupled to a corresponding DRAM cell in a row of DRAM cells; a plurality of column wordline drivers, each column wordline driver being coupled to a corresponding DRAM cell in a column of DRAM cells; and a memory controller internal to the memory device and coupled to the plurality of row wordline drivers and the plurality of column wordline drivers, the memory controller capable of receiving commands input to the memory device and being responsive to the received commands to control the plurality of row wordline drivers and the plurality of column wordline drivers to provide access to the array of DRAM cells. 9. The memory device of claim 8, wherein the array of the plurality of DRAM cells further comprises a plurality of row bit lines and a plurality of column bit lines, each respective row bit line being coupled to DRAM cells in a corresponding row, and each respective column bit line being coupled to DRAM cells in a corresponding column,
the memory device further comprising: a row buffer coupled to the plurality of row bit lines; and a column buffer coupled to the plurality of column bit lines, wherein the memory controller internal to the memory device is further coupled to the row buffer and the column buffer and is configured to control operation of the row buffer and the column buffer in response to the received commands. 10. The memory device of claim 9, further comprising a precharge circuit coupled to each row line and each column bit line. 11. The memory device of claim 9, wherein the memory device is part of a dual in-line memory module (DIMM). 12. The memory device of claim 8, wherein each DRAM cell comprises a two-transistor, one capacitor (2T1C) memory cell. 13. The memory device of claim 12, wherein each transistor of the 2T1C memory cell comprises a terminal directly coupled to a first terminal of the capacitor. 14. The memory device of claim 12, wherein a first transistor of the 2T1C memory cell comprises a terminal directly coupled to a first terminal of the capacitor, and a second transistor of the 2T1C memory cell comprises a gate terminal directly coupled to the first terminal of the capacitor. 15. A memory module, comprising:
an array of a plurality of dynamic random access memory (DRAM) cells, the array arranged as a plurality of rows of DRAM cells and a plurality of columns of DRAM cells; and a memory controller internal to the memory module and coupled to the array of DRAM cells, the memory controller capable of receiving commands input to the memory module and being responsive to the received commands to control row-major access and column-major access to the array of DRAM cells the memory module comprising a dual in-line memory module (DIMM) form factor. 16. The memory module of claim 15, wherein the array of the plurality of DRAM cells further comprises a plurality of row bit lines and a plurality of column bit lines, each respective row bit line being coupled to DRAM cells in a corresponding row, and each respective column bit line being coupled to DRAM cells in a corresponding column,
the memory module further comprising: a row buffer coupled to the plurality of row bit lines; and a column buffer coupled to the plurality of column bit lines, wherein the memory controller internal to the memory module is further coupled to the row buffer and the column buffer and is configured to control operation of the row buffer and the column buffer in response to the received commands. 17. The memory module of claim 16, further comprising a precharge circuit coupled to each row line and each column bit line. 18. The memory module of claim 15, wherein each DRAM cell comprises a two-transistor, one capacitor (2T1C) memory cell. 19. The memory module of claim 18, wherein each transistor of the 2T1C memory cell comprises a terminal directly coupled to a storage node of the capacitor. 20. The memory module of claim 18, wherein a first transistor of the 2T1C memory cell comprises a terminal directly coupled to a storage node of the capacitor, and a second transistor of the 2T1C memory cell comprises a gate terminal directly coupled to the storage node of the capacitor. | A memory device includes an array of 2T1C DRAM cells and a memory controller. The DRAM cells are arranged as a plurality of rows and columns of DRAM cells. The memory controller is internal to the memory device and is coupled to the array of DRAM cells. The memory controller is capable of receiving commands input to the memory device and is responsive to the received commands to control row-major access and column-major access to the array of DRAM cells. In one embodiment, each transistor of a memory cell includes a terminal directly coupled to a storage node of the capacitor. In another embodiment, a first transistor of a memory cell includes a terminal directly coupled to a storage node of the capacitor, and a second transistor of the 2T1C memory cell includes a gate terminal directly coupled to the storage node of the capacitor.1. A memory device, comprising:
an array of a plurality of dynamic random access memory (DRAM) cells, the array arranged as a plurality of rows of DRAM cells and a plurality of columns of DRAM cells; and a memory controller internal to the memory device and coupled to the array of DRAM cells, the memory controller capable of receiving commands input to the memory device and being responsive to the received commands to control row-major access and column-major access to the array of DRAM cells. 2. The memory device of claim 1, wherein the array of the plurality of DRAM cells further comprises a plurality of row bit lines and a plurality of column bit lines, each respective row bit line being coupled to DRAM cells in a corresponding row, and each respective column bit line being coupled to DRAM cells in a corresponding column,
the memory device further comprising: a row buffer coupled to the plurality of row bit lines; and a column buffer coupled to the plurality of column bit lines, wherein the memory controller internal to the memory device is further coupled to the row buffer and the column buffer and is configured to control operation of the row buffer and the column buffer in response to the received commands. 3. The memory device of claim 2, further comprising a precharge circuit coupled to each row line and each column bit line. 4. The memory device of claim 2, wherein the memory device is part of a dual in-line memory module (DIMM). 5. The memory device of claim 1, wherein each DRAM cell comprises a two-transistor, one capacitor (2T1C) memory cell. 6. The memory device of claim 5, wherein each transistor of the 2T1C memory cell comprises a terminal directly coupled to a storage node of the capacitor. 7. The memory device of claim 5, wherein a first transistor of the 2T1C memory cell comprises a terminal directly coupled to a storage node of the capacitor, and a second transistor of the 2T1C memory cell comprises a gate terminal directly coupled to the storage node of the capacitor. 8. A memory device, comprising:
an array of a plurality of dynamic random access memory (DRAM) cells, the array arranged to comprise a plurality of rows of DRAM cells and a plurality of columns of DRAM cells, the array of the plurality of DRAM cells further comprising a plurality of row wordline driver lines and a plurality of column wordline driver lines, each row wordline driver line being coupled to a corresponding DRAM cell in a row of DRAM cells, and each column wordline driver line being coupled to a corresponding DRAM cell in a column of DRAM cells; a plurality of row wordline drivers, each row wordline driver being coupled to a corresponding DRAM cell in a row of DRAM cells; a plurality of column wordline drivers, each column wordline driver being coupled to a corresponding DRAM cell in a column of DRAM cells; and a memory controller internal to the memory device and coupled to the plurality of row wordline drivers and the plurality of column wordline drivers, the memory controller capable of receiving commands input to the memory device and being responsive to the received commands to control the plurality of row wordline drivers and the plurality of column wordline drivers to provide access to the array of DRAM cells. 9. The memory device of claim 8, wherein the array of the plurality of DRAM cells further comprises a plurality of row bit lines and a plurality of column bit lines, each respective row bit line being coupled to DRAM cells in a corresponding row, and each respective column bit line being coupled to DRAM cells in a corresponding column,
the memory device further comprising: a row buffer coupled to the plurality of row bit lines; and a column buffer coupled to the plurality of column bit lines, wherein the memory controller internal to the memory device is further coupled to the row buffer and the column buffer and is configured to control operation of the row buffer and the column buffer in response to the received commands. 10. The memory device of claim 9, further comprising a precharge circuit coupled to each row line and each column bit line. 11. The memory device of claim 9, wherein the memory device is part of a dual in-line memory module (DIMM). 12. The memory device of claim 8, wherein each DRAM cell comprises a two-transistor, one capacitor (2T1C) memory cell. 13. The memory device of claim 12, wherein each transistor of the 2T1C memory cell comprises a terminal directly coupled to a first terminal of the capacitor. 14. The memory device of claim 12, wherein a first transistor of the 2T1C memory cell comprises a terminal directly coupled to a first terminal of the capacitor, and a second transistor of the 2T1C memory cell comprises a gate terminal directly coupled to the first terminal of the capacitor. 15. A memory module, comprising:
an array of a plurality of dynamic random access memory (DRAM) cells, the array arranged as a plurality of rows of DRAM cells and a plurality of columns of DRAM cells; and a memory controller internal to the memory module and coupled to the array of DRAM cells, the memory controller capable of receiving commands input to the memory module and being responsive to the received commands to control row-major access and column-major access to the array of DRAM cells the memory module comprising a dual in-line memory module (DIMM) form factor. 16. The memory module of claim 15, wherein the array of the plurality of DRAM cells further comprises a plurality of row bit lines and a plurality of column bit lines, each respective row bit line being coupled to DRAM cells in a corresponding row, and each respective column bit line being coupled to DRAM cells in a corresponding column,
the memory module further comprising: a row buffer coupled to the plurality of row bit lines; and a column buffer coupled to the plurality of column bit lines, wherein the memory controller internal to the memory module is further coupled to the row buffer and the column buffer and is configured to control operation of the row buffer and the column buffer in response to the received commands. 17. The memory module of claim 16, further comprising a precharge circuit coupled to each row line and each column bit line. 18. The memory module of claim 15, wherein each DRAM cell comprises a two-transistor, one capacitor (2T1C) memory cell. 19. The memory module of claim 18, wherein each transistor of the 2T1C memory cell comprises a terminal directly coupled to a storage node of the capacitor. 20. The memory module of claim 18, wherein a first transistor of the 2T1C memory cell comprises a terminal directly coupled to a storage node of the capacitor, and a second transistor of the 2T1C memory cell comprises a gate terminal directly coupled to the storage node of the capacitor. | 2,100 |
6,533 | 6,533 | 14,061,837 | 2,182 | A single instruction multiple thread (SIMT) processor 2 includes execution circuitry 6, prefetch circuitry 12 and prefetch strategy selection circuitry 14. The prefetch strategy selection circuitry serves to detect one or more characteristics of a stream of program instructions that are being executed to identify whether or not a given data access instruction within a program will be executed a plurality of times. The prefetch strategy to use is selected from a plurality of selectable prefetch strategy in dependence upon the detection of such characteristics. | 1. Apparatus for processing data comprising:
instruction execution circuitry configured to execute in parallel a plurality of threads of program execution, each of said plurality of threads corresponding to a stream of program instructions; prefetch circuitry configured to prefetch data values from memory addresses within a memory in accordance with a selected prefetch strategy that is one of a plurality of selectable prefetch strategies; and prefetch strategy selecting circuitry coupled to said instruction execution circuitry and to said prefetch circuitry and configured:
(i) to detect one or more characteristics of said stream of program instructions indicative of a probability that a given data access instruction within a program will be executed a plurality of times; and
(ii) to select said selected prefetch strategy from among said plurality of selectable prefetch strategies in dependence upon said one or more characteristics. 2. Apparatus as claimed in claim 1, wherein each of said plurality of threads executes in lockstep a common sequence of program instructions. 3. Apparatus as claimed in claim 2, wherein said instruction execution circuitry includes instruction decoder circuitry shared between said plurality of threads. 4. Apparatus as claimed in claim 2, wherein each of said plurality of threads executes without data dependence between said plurality of threads. 5. Apparatus as claimed in claim 1, wherein said instruction execution circuitry is configured to perform fine-grained multithreading. 6. Apparatus as claimed in claim 1, wherein said stream of program instructions has a normal forward execution order in which successive program instructions are executed in turn and said one or more characteristics include execution of a backward branch instruction to a target instruction located before said backward branch instruction relative to said normal forward execution order. 7. Apparatus as claimed in claim 1, wherein said one or more characteristics include execution of a program loop. 8. Apparatus as claimed in claim 1, wherein said stream of program instructions correspond to a given thread that is one of a plurality of threads of program instructions and said one or more characteristics include that said given thread includes greater that a threshold number of program instructions that are executed before termination of said given thread. 9. Apparatus as claimed in claim 1, wherein said prefetch strategy selecting circuitry includes lookup circuitry configured to detect repeated execution within one of said plurality of threads of said given data access instruction. 10. Apparatus as claimed in claim 9, wherein said lookup circuitry is Bloom filter circuitry. 11. Apparatus as claimed in claim 1, wherein said plurality of selectable prefetch strategies include:
(i) a short-running strategy adapted to predict data values to prefetch when said stream of program instructions does not contain a given data access instruction executed a plurality of times; and (ii) a long-running strategy adapted to predict data values to prefetch when said stream of program instructions does contain a given data access instruction executed a plurality of times. 12. Apparatus as claimed in claim 11, wherein said prefetch strategy selecting circuitry is configured to selected said short-running strategy as a default strategy and switch to said long-running strategy upon detection of said one or more characteristics. 13. Apparatus for processing data comprising:
instruction execution means for executing in parallel a plurality of threads of program execution, each of said plurality of threads corresponding to a stream of program instructions; prefetch means for prefetching data values from memory addresses within a memory in accordance with a selected prefetch strategy that is one of a plurality of selectable prefetch strategies; and prefetch strategy selecting means, coupled to said instruction execution means and to said prefetch means, for:
(i) detecting one or more characteristics of said stream of program instructions indicative of a probability that a given data access instruction within a program will be executed a plurality of times; and
(ii) selecting said selected prefetch strategy from among said plurality of selectable prefetch strategies in dependence upon said one or more characteristics. 14. A method of processing data, said method comprising the steps of:
executing in parallel a plurality of threads of program execution, each of said plurality of threads corresponding to a stream of program instructions; prefetching data values from memory addresses within a memory in accordance with a selected prefetch strategy that is one of a plurality of selectable prefetch strategies; detecting one or more characteristics of said stream of program instructions indicative of a probability that a given data access instruction within a program will be executed a plurality of times; and selecting said selected prefetch strategy from among said plurality of selectable prefetch strategies in dependence upon said one or more characteristics. | A single instruction multiple thread (SIMT) processor 2 includes execution circuitry 6, prefetch circuitry 12 and prefetch strategy selection circuitry 14. The prefetch strategy selection circuitry serves to detect one or more characteristics of a stream of program instructions that are being executed to identify whether or not a given data access instruction within a program will be executed a plurality of times. The prefetch strategy to use is selected from a plurality of selectable prefetch strategy in dependence upon the detection of such characteristics.1. Apparatus for processing data comprising:
instruction execution circuitry configured to execute in parallel a plurality of threads of program execution, each of said plurality of threads corresponding to a stream of program instructions; prefetch circuitry configured to prefetch data values from memory addresses within a memory in accordance with a selected prefetch strategy that is one of a plurality of selectable prefetch strategies; and prefetch strategy selecting circuitry coupled to said instruction execution circuitry and to said prefetch circuitry and configured:
(i) to detect one or more characteristics of said stream of program instructions indicative of a probability that a given data access instruction within a program will be executed a plurality of times; and
(ii) to select said selected prefetch strategy from among said plurality of selectable prefetch strategies in dependence upon said one or more characteristics. 2. Apparatus as claimed in claim 1, wherein each of said plurality of threads executes in lockstep a common sequence of program instructions. 3. Apparatus as claimed in claim 2, wherein said instruction execution circuitry includes instruction decoder circuitry shared between said plurality of threads. 4. Apparatus as claimed in claim 2, wherein each of said plurality of threads executes without data dependence between said plurality of threads. 5. Apparatus as claimed in claim 1, wherein said instruction execution circuitry is configured to perform fine-grained multithreading. 6. Apparatus as claimed in claim 1, wherein said stream of program instructions has a normal forward execution order in which successive program instructions are executed in turn and said one or more characteristics include execution of a backward branch instruction to a target instruction located before said backward branch instruction relative to said normal forward execution order. 7. Apparatus as claimed in claim 1, wherein said one or more characteristics include execution of a program loop. 8. Apparatus as claimed in claim 1, wherein said stream of program instructions correspond to a given thread that is one of a plurality of threads of program instructions and said one or more characteristics include that said given thread includes greater that a threshold number of program instructions that are executed before termination of said given thread. 9. Apparatus as claimed in claim 1, wherein said prefetch strategy selecting circuitry includes lookup circuitry configured to detect repeated execution within one of said plurality of threads of said given data access instruction. 10. Apparatus as claimed in claim 9, wherein said lookup circuitry is Bloom filter circuitry. 11. Apparatus as claimed in claim 1, wherein said plurality of selectable prefetch strategies include:
(i) a short-running strategy adapted to predict data values to prefetch when said stream of program instructions does not contain a given data access instruction executed a plurality of times; and (ii) a long-running strategy adapted to predict data values to prefetch when said stream of program instructions does contain a given data access instruction executed a plurality of times. 12. Apparatus as claimed in claim 11, wherein said prefetch strategy selecting circuitry is configured to selected said short-running strategy as a default strategy and switch to said long-running strategy upon detection of said one or more characteristics. 13. Apparatus for processing data comprising:
instruction execution means for executing in parallel a plurality of threads of program execution, each of said plurality of threads corresponding to a stream of program instructions; prefetch means for prefetching data values from memory addresses within a memory in accordance with a selected prefetch strategy that is one of a plurality of selectable prefetch strategies; and prefetch strategy selecting means, coupled to said instruction execution means and to said prefetch means, for:
(i) detecting one or more characteristics of said stream of program instructions indicative of a probability that a given data access instruction within a program will be executed a plurality of times; and
(ii) selecting said selected prefetch strategy from among said plurality of selectable prefetch strategies in dependence upon said one or more characteristics. 14. A method of processing data, said method comprising the steps of:
executing in parallel a plurality of threads of program execution, each of said plurality of threads corresponding to a stream of program instructions; prefetching data values from memory addresses within a memory in accordance with a selected prefetch strategy that is one of a plurality of selectable prefetch strategies; detecting one or more characteristics of said stream of program instructions indicative of a probability that a given data access instruction within a program will be executed a plurality of times; and selecting said selected prefetch strategy from among said plurality of selectable prefetch strategies in dependence upon said one or more characteristics. | 2,100 |
6,534 | 6,534 | 14,985,670 | 2,124 | A plurality of corpora is received from one or more sources. A separate model is trained on each corpus of the plurality of corpora. The models for the plurality of corpora are merged into a joint model using parameter interpolation. The models for each corpus of the plurality of corpora are retrained separately using the joint model. A single model is created based on the retrained models. | 1. A method, comprising the steps of:
receiving a plurality of corpora from one or more sources; training a separate model on each corpus of the plurality of corpora; merging the models for the plurality of corpora into a joint model using parameter interpolation; retraining the models separately for each corpus of the plurality of corpora using the joint model; and creating a single model based on the retrained models; wherein the steps are performed by at least one processor device coupled to a memory. 2. The method of claim 1, wherein the single model is a language model for use in a speech decoding process. 3. The method of claim 1, wherein training a separate model on each corpus comprises training exponential n-gram models. 4. The method of claim 1, wherein the training step comprises applying an Alternative Direction Method of Multipliers framework. 5. The method of claim 1, further comprising determining a log linear weight for each corpus of the plurality of corpora. 6. The method of claim 5, wherein merging the models comprises taking a weighted sum of a plurality of parameters across the plurality of corpora. 7. The method of claim 6, further comprising interpolating the plurality of parameters to create the joint model. 8. The method of claim 1, wherein retraining the models comprises using the joint model as a Gaussian prior. 9. The method of claim 1, wherein creating the single model comprises repeating the training, merging and retraining steps. 10. The method of claim 9, wherein the steps are repeated until convergence of a held-out perplexity. 11. An apparatus comprising:
a memory and a processor operatively coupled to the memory and configured to implement the steps of:
receiving a plurality of corpora from one or more sources;
training a separate model on each corpus of the plurality of corpora;
merging the models for the plurality of corpora into a joint model using parameter interpolation;
retraining the models separately for each corpus of the plurality of corpora using the joint model; and
creating a single model based on the retrained models. 12. The method of claim 11, wherein the single model is a language model for use in a speech decoding process. 13. The method of claim 11, wherein the training a separate model on each corpus comprises training exponential n-gram models. 14. The method of claim 11, wherein the training step comprises applying an Alternative Direction Method of Multipliers framework. 15. The method of claim 11, further comprising determining a log linear weight for each corpus of the plurality of corpora. 16. The method of claim 15, wherein merging the models comprises taking a weighted sum of a plurality of parameters across the plurality of corpora. 17. The method of claim 16, further comprising interpolating the plurality of parameters to create the joint model. 18. The method of claim 11, wherein retraining the models comprises using the joint model as a Gaussian prior. 19. The method of claim 11, wherein creating the single model comprises repeating the training, merging and retraining steps. 20. A computer program product comprising a computer readable storage medium for storing computer readable program code which, when executed, causes a computer to:
receive a plurality of corpora from one or more sources; train a separate model on each corpus of the plurality of corpora; merge the models for the plurality of corpora into a joint model using parameter interpolation; retrain the models separately for each corpus of the plurality of corpora using the joint model; and create a single model based on the retrained models. | A plurality of corpora is received from one or more sources. A separate model is trained on each corpus of the plurality of corpora. The models for the plurality of corpora are merged into a joint model using parameter interpolation. The models for each corpus of the plurality of corpora are retrained separately using the joint model. A single model is created based on the retrained models.1. A method, comprising the steps of:
receiving a plurality of corpora from one or more sources; training a separate model on each corpus of the plurality of corpora; merging the models for the plurality of corpora into a joint model using parameter interpolation; retraining the models separately for each corpus of the plurality of corpora using the joint model; and creating a single model based on the retrained models; wherein the steps are performed by at least one processor device coupled to a memory. 2. The method of claim 1, wherein the single model is a language model for use in a speech decoding process. 3. The method of claim 1, wherein training a separate model on each corpus comprises training exponential n-gram models. 4. The method of claim 1, wherein the training step comprises applying an Alternative Direction Method of Multipliers framework. 5. The method of claim 1, further comprising determining a log linear weight for each corpus of the plurality of corpora. 6. The method of claim 5, wherein merging the models comprises taking a weighted sum of a plurality of parameters across the plurality of corpora. 7. The method of claim 6, further comprising interpolating the plurality of parameters to create the joint model. 8. The method of claim 1, wherein retraining the models comprises using the joint model as a Gaussian prior. 9. The method of claim 1, wherein creating the single model comprises repeating the training, merging and retraining steps. 10. The method of claim 9, wherein the steps are repeated until convergence of a held-out perplexity. 11. An apparatus comprising:
a memory and a processor operatively coupled to the memory and configured to implement the steps of:
receiving a plurality of corpora from one or more sources;
training a separate model on each corpus of the plurality of corpora;
merging the models for the plurality of corpora into a joint model using parameter interpolation;
retraining the models separately for each corpus of the plurality of corpora using the joint model; and
creating a single model based on the retrained models. 12. The method of claim 11, wherein the single model is a language model for use in a speech decoding process. 13. The method of claim 11, wherein the training a separate model on each corpus comprises training exponential n-gram models. 14. The method of claim 11, wherein the training step comprises applying an Alternative Direction Method of Multipliers framework. 15. The method of claim 11, further comprising determining a log linear weight for each corpus of the plurality of corpora. 16. The method of claim 15, wherein merging the models comprises taking a weighted sum of a plurality of parameters across the plurality of corpora. 17. The method of claim 16, further comprising interpolating the plurality of parameters to create the joint model. 18. The method of claim 11, wherein retraining the models comprises using the joint model as a Gaussian prior. 19. The method of claim 11, wherein creating the single model comprises repeating the training, merging and retraining steps. 20. A computer program product comprising a computer readable storage medium for storing computer readable program code which, when executed, causes a computer to:
receive a plurality of corpora from one or more sources; train a separate model on each corpus of the plurality of corpora; merge the models for the plurality of corpora into a joint model using parameter interpolation; retrain the models separately for each corpus of the plurality of corpora using the joint model; and create a single model based on the retrained models. | 2,100 |
6,535 | 6,535 | 15,394,790 | 2,124 | Methods and systems for accelerated training of a machine learning based model for semiconductor applications are provided. One method for training a machine learning based model includes acquiring information for non-nominal instances of specimen(s) on which a process is performed. The machine learning based model is configured for performing simulation(s) for the specimens. The machine learning based model is trained with only information for nominal instances of additional specimen(s). The method also includes re-training the machine learning based model with the information for the non-nominal instances of the specimen(s) thereby performing transfer learning of the information for the non-nominal instances of the specimen(s) to the machine learning based model. | 1. A system configured to train a machine learning based model, comprising:
one or more computer subsystems; and one or more components executed by the one or more computer subsystems, wherein the one or more components comprise:
a machine learning based model configured for performing one or more simulations for specimens, wherein the machine learning based model is trained with only information for nominal instances of one or more of the specimens;
wherein the one or more computer subsystems are configured for:
acquiring information for non-nominal instances of one or more of the specimens on which a process is performed; and
re-training the machine learning based model with the information for the non-nominal instances of the one or more of the specimens thereby performing transfer learning of the information for the non-nominal instances of the one or more of the specimens to the machine learning based model. 2. The system of claim 1, wherein performing the one or more simulations comprises generating one or more simulated images for one of the specimens, and wherein the one or more simulated images illustrate how the one of the specimens appears in one or more actual images of the one of the specimens generated by an imaging system. 3. The system of claim 2, wherein the imaging system is an optical based imaging system. 4. The system of claim 2, wherein the imaging system is an electron beam based imaging system. 5. The system of claim 1, wherein performing the one or more simulations comprises generating one or more simulated measurements for one of the specimens, and wherein the one or more simulated measurements represent output generated for the one of the specimens by a metrology system. 6. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens. 7. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, and wherein the one or more specimens comprise one or more actual specimens on which the process is performed with two or more different values of one or more parameters of the process. 8. The system of claim 7, wherein the process is performed with the two or more different values of the one or more parameters of the process in a process window qualification method. 9. The system of claim 7, wherein the process is performed with the two or more different values of the one or more parameters of the process in a process window qualification method designed for overlay margin determination. 10. The system of claim 7, wherein the process is performed with the two or more different values of the one or more parameters of the process in a focus exposure matrix method. 11. The system of claim 1, wherein the acquired information is generated from synthetic design data for the one or more specimens produced by an electronic design automation tool. 12. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, and wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design. 13. The system of claim 12, wherein the one or more components further comprise an inception module configured for altering the design to create the synthetic defects in the design. 14. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design, and wherein the information for the non-nominal instances comprises output generated by an imaging or metrology system for the one or more specimens on which the synthetic defects are printed. 15. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design, wherein the information for the non-nominal instances comprises output of another model, and wherein the output of the other model represents the one or more specimens on which the synthetic defects are printed. 16. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design, wherein the information for the non-nominal instances comprises output of another model, and wherein the output of the other model illustrates how the one or more specimens on which the synthetic defects are printed appear in one or more actual images of the specimen generated by an imaging system. 17. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design, wherein the information for the non-nominal instances comprises output of another model, and wherein the output of the other model represents output generated by a metrology system for the one or more specimens on which the synthetic defects are printed. 18. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design, wherein the information for the non-nominal instances comprises output of another model, wherein the output of the other model represents output generated by another system for the one or more specimens on which the synthetic defects are printed, and wherein the other model is a deep generative model. 19. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design, and wherein the information for the non-nominal instances comprises the altered design. 20. The system of claim 1, wherein the one or more components further comprise a deep generative model configured to create the information for the nominal instances of the one or more specimens. 21. The system of claim 1, wherein the nominal instances of the one or more specimens comprise natural scene images. 22. The system of claim 1, wherein the nominal instances of the one or more specimens comprise more than one type of data. 23. The system of claim 1, wherein the machine learning based model is a discriminative model. 24. The system of claim 1, wherein the machine learning based model is a neural network. 25. The system of claim 1, wherein the machine learning based model is a convolution and deconvolution neural network. 26. The system of claim 1, wherein the one or more components further comprise one or more additional components, wherein the re-training is performed using the one or more additional components, and wherein the one or more additional components comprise a common mother network for all layers on the specimens, a grand common mother network for all layers on the specimens, an adversarial network, a deep adversarial generative network, an adversarial autoencoder, a Bayesian Neural Network, a component configured for a variational Bayesian method, a ladder network, or some combination thereof. 27. The system of claim 1, wherein the re-training comprises transferring all weights of convolutional layers of the trained machine learning based method and fine tuning weights of fully connected layers of the trained machine learning based method. 28. The system of claim 1, further comprising an electron beam based imaging subsystem configured to generate electron beam images of the specimens, wherein the one or more computer subsystems are further configured for receiving the electron beam images from the electron beam based imaging subsystem. 29. The system of claim 1, further comprising an optical based imaging subsystem configured to generate optical images of the specimens, wherein the one or more computer subsystems are further configured for receiving the optical images from the optical based imaging subsystem. 30. The system of claim 1, further comprising an inspection subsystem configured to generate output for the specimens, wherein the one or more computer subsystems are further configured for receiving the output from the inspection subsystem and detecting defects on the specimens based on the output. 31. The system of claim 1, further comprising a defect review subsystem configured to generate output for defects detected on the specimens, wherein the one or more computer subsystems are further configured for receiving the output from the defect review subsystem and determining properties of the defects detected on the specimens based on the output. 32. The system of claim 1, further comprising a metrology subsystem configured to generate output for the specimens, wherein the one or more computer subsystems are further configured for receiving the output from the metrology subsystem and determining properties of the specimens based on the output. 33. The system of claim 1, further comprising a semiconductor fabrication subsystem configured to perform one or more fabrication processes on the specimens. 34. The system of claim 1, wherein the specimens comprise wafers. 35. The system of claim 1, wherein the specimen comprise reticles. 36. A non-transitory computer-readable medium, storing program instructions executable on one or more computer systems for performing a computer-implemented method for training a machine learning based model, wherein the computer-implemented method comprises:
acquiring information for non-nominal instances of one or more specimens on which a process is performed, wherein a machine learning based model is configured for performing one or more simulations for the specimens, and wherein the machine learning based model is trained with only information for nominal instances of one or more additional specimens; and re-training the machine learning based model with the information for the non-nominal instances of the one or more specimens thereby performing transfer learning of the information for the non-nominal instances of the one or more specimens to the machine learning based model, wherein said acquiring and said re-training are performed by the one or more computer systems, wherein one or more components are executed by the one or more computer systems, and wherein the one or more components comprise the machine learning based model. 37. A computer-implemented method for training a machine learning based model, comprising:
acquiring information for non-nominal instances of one or more specimens on which a process is performed, wherein a machine learning based model is configured for performing one or more simulations for the specimens, and wherein the machine learning based model is trained with only information for nominal instances of one or more additional specimens; and re-training the machine learning based model with the nformation for the non-nominal instances of the one or more specimens thereby performing transfer learning of the information for the non-nominal instances of the one or more specimens to the machine learning based model, wherein said acquiring and said re-training are performed by one or more computer systems, wherein one or more components are executed by the one or more computer systems, and wherein the one or more components comprise the machine learning based model. | Methods and systems for accelerated training of a machine learning based model for semiconductor applications are provided. One method for training a machine learning based model includes acquiring information for non-nominal instances of specimen(s) on which a process is performed. The machine learning based model is configured for performing simulation(s) for the specimens. The machine learning based model is trained with only information for nominal instances of additional specimen(s). The method also includes re-training the machine learning based model with the information for the non-nominal instances of the specimen(s) thereby performing transfer learning of the information for the non-nominal instances of the specimen(s) to the machine learning based model.1. A system configured to train a machine learning based model, comprising:
one or more computer subsystems; and one or more components executed by the one or more computer subsystems, wherein the one or more components comprise:
a machine learning based model configured for performing one or more simulations for specimens, wherein the machine learning based model is trained with only information for nominal instances of one or more of the specimens;
wherein the one or more computer subsystems are configured for:
acquiring information for non-nominal instances of one or more of the specimens on which a process is performed; and
re-training the machine learning based model with the information for the non-nominal instances of the one or more of the specimens thereby performing transfer learning of the information for the non-nominal instances of the one or more of the specimens to the machine learning based model. 2. The system of claim 1, wherein performing the one or more simulations comprises generating one or more simulated images for one of the specimens, and wherein the one or more simulated images illustrate how the one of the specimens appears in one or more actual images of the one of the specimens generated by an imaging system. 3. The system of claim 2, wherein the imaging system is an optical based imaging system. 4. The system of claim 2, wherein the imaging system is an electron beam based imaging system. 5. The system of claim 1, wherein performing the one or more simulations comprises generating one or more simulated measurements for one of the specimens, and wherein the one or more simulated measurements represent output generated for the one of the specimens by a metrology system. 6. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens. 7. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, and wherein the one or more specimens comprise one or more actual specimens on which the process is performed with two or more different values of one or more parameters of the process. 8. The system of claim 7, wherein the process is performed with the two or more different values of the one or more parameters of the process in a process window qualification method. 9. The system of claim 7, wherein the process is performed with the two or more different values of the one or more parameters of the process in a process window qualification method designed for overlay margin determination. 10. The system of claim 7, wherein the process is performed with the two or more different values of the one or more parameters of the process in a focus exposure matrix method. 11. The system of claim 1, wherein the acquired information is generated from synthetic design data for the one or more specimens produced by an electronic design automation tool. 12. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, and wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design. 13. The system of claim 12, wherein the one or more components further comprise an inception module configured for altering the design to create the synthetic defects in the design. 14. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design, and wherein the information for the non-nominal instances comprises output generated by an imaging or metrology system for the one or more specimens on which the synthetic defects are printed. 15. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design, wherein the information for the non-nominal instances comprises output of another model, and wherein the output of the other model represents the one or more specimens on which the synthetic defects are printed. 16. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design, wherein the information for the non-nominal instances comprises output of another model, and wherein the output of the other model illustrates how the one or more specimens on which the synthetic defects are printed appear in one or more actual images of the specimen generated by an imaging system. 17. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design, wherein the information for the non-nominal instances comprises output of another model, and wherein the output of the other model represents output generated by a metrology system for the one or more specimens on which the synthetic defects are printed. 18. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design, wherein the information for the non-nominal instances comprises output of another model, wherein the output of the other model represents output generated by another system for the one or more specimens on which the synthetic defects are printed, and wherein the other model is a deep generative model. 19. The system of claim 1, wherein the non-nominal instances comprise instances of defects on the one or more specimens, wherein the defects comprise one or more synthetic defects generated by altering a design for the one or more specimens to create the synthetic defects in the design, and wherein the information for the non-nominal instances comprises the altered design. 20. The system of claim 1, wherein the one or more components further comprise a deep generative model configured to create the information for the nominal instances of the one or more specimens. 21. The system of claim 1, wherein the nominal instances of the one or more specimens comprise natural scene images. 22. The system of claim 1, wherein the nominal instances of the one or more specimens comprise more than one type of data. 23. The system of claim 1, wherein the machine learning based model is a discriminative model. 24. The system of claim 1, wherein the machine learning based model is a neural network. 25. The system of claim 1, wherein the machine learning based model is a convolution and deconvolution neural network. 26. The system of claim 1, wherein the one or more components further comprise one or more additional components, wherein the re-training is performed using the one or more additional components, and wherein the one or more additional components comprise a common mother network for all layers on the specimens, a grand common mother network for all layers on the specimens, an adversarial network, a deep adversarial generative network, an adversarial autoencoder, a Bayesian Neural Network, a component configured for a variational Bayesian method, a ladder network, or some combination thereof. 27. The system of claim 1, wherein the re-training comprises transferring all weights of convolutional layers of the trained machine learning based method and fine tuning weights of fully connected layers of the trained machine learning based method. 28. The system of claim 1, further comprising an electron beam based imaging subsystem configured to generate electron beam images of the specimens, wherein the one or more computer subsystems are further configured for receiving the electron beam images from the electron beam based imaging subsystem. 29. The system of claim 1, further comprising an optical based imaging subsystem configured to generate optical images of the specimens, wherein the one or more computer subsystems are further configured for receiving the optical images from the optical based imaging subsystem. 30. The system of claim 1, further comprising an inspection subsystem configured to generate output for the specimens, wherein the one or more computer subsystems are further configured for receiving the output from the inspection subsystem and detecting defects on the specimens based on the output. 31. The system of claim 1, further comprising a defect review subsystem configured to generate output for defects detected on the specimens, wherein the one or more computer subsystems are further configured for receiving the output from the defect review subsystem and determining properties of the defects detected on the specimens based on the output. 32. The system of claim 1, further comprising a metrology subsystem configured to generate output for the specimens, wherein the one or more computer subsystems are further configured for receiving the output from the metrology subsystem and determining properties of the specimens based on the output. 33. The system of claim 1, further comprising a semiconductor fabrication subsystem configured to perform one or more fabrication processes on the specimens. 34. The system of claim 1, wherein the specimens comprise wafers. 35. The system of claim 1, wherein the specimen comprise reticles. 36. A non-transitory computer-readable medium, storing program instructions executable on one or more computer systems for performing a computer-implemented method for training a machine learning based model, wherein the computer-implemented method comprises:
acquiring information for non-nominal instances of one or more specimens on which a process is performed, wherein a machine learning based model is configured for performing one or more simulations for the specimens, and wherein the machine learning based model is trained with only information for nominal instances of one or more additional specimens; and re-training the machine learning based model with the information for the non-nominal instances of the one or more specimens thereby performing transfer learning of the information for the non-nominal instances of the one or more specimens to the machine learning based model, wherein said acquiring and said re-training are performed by the one or more computer systems, wherein one or more components are executed by the one or more computer systems, and wherein the one or more components comprise the machine learning based model. 37. A computer-implemented method for training a machine learning based model, comprising:
acquiring information for non-nominal instances of one or more specimens on which a process is performed, wherein a machine learning based model is configured for performing one or more simulations for the specimens, and wherein the machine learning based model is trained with only information for nominal instances of one or more additional specimens; and re-training the machine learning based model with the nformation for the non-nominal instances of the one or more specimens thereby performing transfer learning of the information for the non-nominal instances of the one or more specimens to the machine learning based model, wherein said acquiring and said re-training are performed by one or more computer systems, wherein one or more components are executed by the one or more computer systems, and wherein the one or more components comprise the machine learning based model. | 2,100 |
6,536 | 6,536 | 15,898,037 | 2,165 | In an aspect, provided is a method comprising receiving a data model, partitioning a first table in the data model into a first plurality of blocks of rows, generating a first plurality of indexlets, the first plurality of indexlets comprising a first plurality bidirectional indexes, each of the first plurality of bidirectional indexes being generated based on a corresponding one of the first plurality of blocks of rows. | 1. A method comprising:
receiving a data model; partitioning a first table in the data model into a first plurality of blocks of rows; generating a first plurality of indexlets, the first plurality of indexlets comprising a first plurality bidirectional indexes, each of the first plurality of bidirectional indexes being generated based on a corresponding one of the first plurality of blocks of rows. 2. The method of claim 1, wherein the first plurality of indexlets are associated with a bidirectional global attribute list. 3. The method of claim 2, wherein the bidirectional global attribute list comprises a plurality of references, each of the plurality of references associating a respective one of a plurality of attributes to those of the first plurality of blocks that include the respective one of the plurality of attributes. 4. The method of claim 3, wherein the plurality references comprise a plurality of hash references. 5. The method of claim 4, wherein the plurality of references comprise a plurality of hash references. 6. The method of claim 1, further comprising:
partitioning a second table in the data model into a second plurality of blocks of rows; generating a second plurality of indexlets, the second plurality of indexlets comprising a second plurality bidirectional indexes, each of the second plurality of bidirectional indexes being generated based on a corresponding one of the second plurality of blocks of rows. 7. The method of claim 5, further comprising generating an attribute-to-attribute index. 8. The method of claim 7, wherein the attribute-to-attribute index comprises a plurality of associations between a first plurality of attributes in the first table and a second plurality of attributes in a second table. 9. The method of claim 1, wherein partitioning the first table in the data model into the first plurality of blocks of rows is based on a predefined block size. 10. The method of claim 1, wherein the first plurality of indexlets facilitate a parallelized operation applied to the data model. 11. A system comprising:
at least one computing device configured to at least:
receive a data model;
partition a first table in the data model into a first plurality of blocks of rows;
generate a first plurality of indexlets, the first plurality of indexlets comprising a first plurality bidirectional indexes, each of the first plurality of bidirectional indexes being generated based on a corresponding one of the first plurality of blocks of rows. 12. The system of claim 11, wherein the first plurality of indexlets are associated with a bidirectional global attribute list. 13. The system of claim 12, wherein the bidirectional global attribute list comprises a plurality of references, each of the plurality of references associating a respective one of a plurality of attributes to those of the first plurality of blocks that include the respective one of the plurality of attributes. 14. The system of claim 13, wherein the plurality of references comprise a plurality of hash references. 15. The system of claim 14, wherein the plurality of references comprise a plurality of hash references. 16. The system of claim 1, wherein the at least one computing device is further configured to at least:
partition a second table in the data model into a second plurality of blocks of rows; generate a second plurality of indexlets, the second plurality of indexlets comprising a second plurality bidirectional indexes, each of the second plurality of bidirectional indexes being generated based on a corresponding one of the second plurality of blocks of rows. 17. The system of claim 15, wherein the at least one computing device is further configured to generate an attribute-to-attribute index. 18. The system of claim 17, wherein the attribute-to-attribute index comprises a plurality of associations between a first plurality of attributes in the first table and a second plurality of attributes in a second table. 19. The system of claim 11, wherein partitioning the first table in the data model into the first plurality of blocks of rows is based on a predefined block size. 20. The system of claim 11, wherein the first plurality of indexlets facilitate a parallelized operation applied to the data model. | In an aspect, provided is a method comprising receiving a data model, partitioning a first table in the data model into a first plurality of blocks of rows, generating a first plurality of indexlets, the first plurality of indexlets comprising a first plurality bidirectional indexes, each of the first plurality of bidirectional indexes being generated based on a corresponding one of the first plurality of blocks of rows.1. A method comprising:
receiving a data model; partitioning a first table in the data model into a first plurality of blocks of rows; generating a first plurality of indexlets, the first plurality of indexlets comprising a first plurality bidirectional indexes, each of the first plurality of bidirectional indexes being generated based on a corresponding one of the first plurality of blocks of rows. 2. The method of claim 1, wherein the first plurality of indexlets are associated with a bidirectional global attribute list. 3. The method of claim 2, wherein the bidirectional global attribute list comprises a plurality of references, each of the plurality of references associating a respective one of a plurality of attributes to those of the first plurality of blocks that include the respective one of the plurality of attributes. 4. The method of claim 3, wherein the plurality references comprise a plurality of hash references. 5. The method of claim 4, wherein the plurality of references comprise a plurality of hash references. 6. The method of claim 1, further comprising:
partitioning a second table in the data model into a second plurality of blocks of rows; generating a second plurality of indexlets, the second plurality of indexlets comprising a second plurality bidirectional indexes, each of the second plurality of bidirectional indexes being generated based on a corresponding one of the second plurality of blocks of rows. 7. The method of claim 5, further comprising generating an attribute-to-attribute index. 8. The method of claim 7, wherein the attribute-to-attribute index comprises a plurality of associations between a first plurality of attributes in the first table and a second plurality of attributes in a second table. 9. The method of claim 1, wherein partitioning the first table in the data model into the first plurality of blocks of rows is based on a predefined block size. 10. The method of claim 1, wherein the first plurality of indexlets facilitate a parallelized operation applied to the data model. 11. A system comprising:
at least one computing device configured to at least:
receive a data model;
partition a first table in the data model into a first plurality of blocks of rows;
generate a first plurality of indexlets, the first plurality of indexlets comprising a first plurality bidirectional indexes, each of the first plurality of bidirectional indexes being generated based on a corresponding one of the first plurality of blocks of rows. 12. The system of claim 11, wherein the first plurality of indexlets are associated with a bidirectional global attribute list. 13. The system of claim 12, wherein the bidirectional global attribute list comprises a plurality of references, each of the plurality of references associating a respective one of a plurality of attributes to those of the first plurality of blocks that include the respective one of the plurality of attributes. 14. The system of claim 13, wherein the plurality of references comprise a plurality of hash references. 15. The system of claim 14, wherein the plurality of references comprise a plurality of hash references. 16. The system of claim 1, wherein the at least one computing device is further configured to at least:
partition a second table in the data model into a second plurality of blocks of rows; generate a second plurality of indexlets, the second plurality of indexlets comprising a second plurality bidirectional indexes, each of the second plurality of bidirectional indexes being generated based on a corresponding one of the second plurality of blocks of rows. 17. The system of claim 15, wherein the at least one computing device is further configured to generate an attribute-to-attribute index. 18. The system of claim 17, wherein the attribute-to-attribute index comprises a plurality of associations between a first plurality of attributes in the first table and a second plurality of attributes in a second table. 19. The system of claim 11, wherein partitioning the first table in the data model into the first plurality of blocks of rows is based on a predefined block size. 20. The system of claim 11, wherein the first plurality of indexlets facilitate a parallelized operation applied to the data model. | 2,100 |
6,537 | 6,537 | 14,976,638 | 2,166 | According to some embodiments, a communication port may receive electronic messages containing business intelligence elements, key figures, and a stream of big data. A smart analytics platform may automatically execute a context determination tool, an expert knowledge tool, and a data interpretation tool using the business intelligence elements, key figures, and stream of big data. The smart analytics platform may then render a smart analytics interface display on a remote user device via a distributed communication network. The smart analytics interface display may, for example, include outputs of the context determination tool, expert knowledge tool, and data interpretation tool. | 1. A system to improve a user data interface associated with a distributed communication network, comprising:
(a) a communication port to receive electronic messages containing business intelligence elements, key figures, and a stream of big data; (b) a user interface to exchange information with a remote user device associated with a user; and (c) a smart analytics platform, coupled to the communication port and the user interface, programmed to:
(i) access the business intelligence elements, key figures, and stream of big data,
(ii) automatically execute a context determination tool utilizing meta-data associated with at least one of the business intelligence elements, key figures, and stream of big data,
(iii) automatically execute an expert knowledge tool to process the business intelligence elements, key figures, and stream of big data,
(iv) automatically execute a data interpretation tool on the business intelligence elements, key figures, and stream of big data, and
(v) render a smart analytics interface display on the remote user device via the distributed communication network, the smart analytics interface display including outputs of the context determination tool, expert knowledge tool, and data interpretation tool. 2. The system of claim 1, wherein the context determination tool leverages received information by adding additional facts or values, reduces information noise, and suggests related elements based on available contextual information. 3. The system of claim 1, wherein the expert knowledge tool comprises internal, generic best-practices algorithms. 4. The system of claim 3, wherein the algorithms are associated with at least one of: outlier analysis, trend identification, and a plan versus actual comparison. 5. The system of claim 1, wherein the expert knowledge tool comprises external domain expertise to model domain specific rules. 6. The system of claim 1, wherein the data interpretation tool determines hidden correlations, patterns, or drivers associated with an enterprise. 7. The system of claim 6, wherein the data interpretation tool operates based at least in part on an enterprise role associated with the user. 8. The system of claim 6, wherein the data interpretation tool is configured to perform one of the following tasks: explain a business meaning of a specific key figure, explain an impact a specific key figure has on an enterprise, explain the consequences of a specific key figure, explain at least one decision that needs to be made along with a set of options associated with that decision, explain at least one next logical analysis step, suggest related reports or key figures, and propose other business aspects that may be associated with a specific key figure. 9. The system of claim 6, wherein the data interpretation tool is configured to receive from the user a request for increased data interpretation and, responsive to the received request, provide additional support information. 10. The system of claim 6, wherein the data interpretation tool includes a visual focus component, a comprehension component, and a textual conclusion component. 11. The system of claim 10, wherein the visual focus component is associated with a heat map. 12. The system of claim 10, wherein the comprehension component brings multiple perspectives of analysis by providing an overview to explain a specific key figure, suggesting dimensions via a relationship analyzer, accessing pre-determined dimensions and key figures, and summarizing findings. 13. The system of claim 12, wherein the summarized findings are provided to the user in human readable language. 14. A method implemented by a computing system in response to execution of program code by a processor of the computing system, the method to improve a user data interface associated with a distributed computer network and comprising:
receiving, via a communication port, electronic messages containing business intelligence elements, key figures, and a stream of big data; accessing, by a computer processor of a smart analytics platform, the business intelligence elements, key figures, and stream of big data; automatically executing, by the computer processor of the smart analytics platform, a context determination tool utilizing meta-data associated with at least one of the business intelligence elements, key figures, and stream of big data; automatically executing, by the computer processor of the smart analytics platform, an expert knowledge tool to process the business intelligence elements, key figures, and stream of big data; automatically executing, by the computer processor of the smart analytics platform, a data interpretation tool on the business intelligence elements, key figures, and stream of big data; and rendering a smart analytics interface display on the remote user device via the distributed communication network, the smart analytics interface display including outputs of the context determination tool, expert knowledge tool, and data interpretation tool. 15. The method of claim 14, wherein the context determination tool leverages received information by adding additional facts or values, reduces information noise, and suggests related elements based on available contextual information. 16. The method of claim 14, wherein the expert knowledge tool comprises internal, generic best-practices algorithms associated with at least one of: outlier analysis, trend identification, and a plan versus actual comparison. 17. The method of claim 14, wherein the data interpretation tool determines hidden correlations, patterns, or drivers associated with an enterprise based at least in part on an enterprise role associated with the user. 18. The method of claim 14, wherein the data interpretation tool includes a visual focus component associated with a heat map, a comprehension component, and a textual conclusion component. 19. A non-transitory medium storing processor-executable program code, the program code executable by a processor of a computing device to improve a user data interface associated with a distributed communication network by:
receiving, via a communication port, electronic messages containing business intelligence elements, key figures, and a stream of big data; accessing, by a computer processor of a smart analytics platform, the business intelligence elements, key figures, and stream of big data; automatically executing, by the computer processor of the smart analytics platform, a context determination tool utilizing meta-data associated with at least one of the business intelligence elements, key figures, and stream of big data; automatically executing, by the computer processor of the smart analytics platform, an expert knowledge tool to process the business intelligence elements, key figures, and stream of big data; automatically executing, by the computer processor of the smart analytics platform, a data interpretation tool on the business intelligence elements, key figures, and stream of big data; and rendering a smart analytics interface display on the remote user device via the distributed communication network, the smart analytics interface display including outputs of the context determination tool, expert knowledge tool, and data interpretation tool. 20. The medium of claim 19, wherein the context determination tool leverages received information by adding additional facts or values, reduces information noise, and suggests related elements based on available contextual information. 21. The medium of claim 19, wherein the expert knowledge tool comprises internal, generic best-practices algorithms associated with at least one of: outlier analysis, trend identification, and a plan versus actual comparison. 22. The medium of claim 19, wherein the data interpretation tool determines hidden correlations, patterns, or drivers associated with an enterprise based at least in part on an enterprise role associated with the user. 23. The medium of claim 19, wherein the data interpretation tool includes a visual focus component associated with a heat map, a comprehension component, and a textual conclusion component. | According to some embodiments, a communication port may receive electronic messages containing business intelligence elements, key figures, and a stream of big data. A smart analytics platform may automatically execute a context determination tool, an expert knowledge tool, and a data interpretation tool using the business intelligence elements, key figures, and stream of big data. The smart analytics platform may then render a smart analytics interface display on a remote user device via a distributed communication network. The smart analytics interface display may, for example, include outputs of the context determination tool, expert knowledge tool, and data interpretation tool.1. A system to improve a user data interface associated with a distributed communication network, comprising:
(a) a communication port to receive electronic messages containing business intelligence elements, key figures, and a stream of big data; (b) a user interface to exchange information with a remote user device associated with a user; and (c) a smart analytics platform, coupled to the communication port and the user interface, programmed to:
(i) access the business intelligence elements, key figures, and stream of big data,
(ii) automatically execute a context determination tool utilizing meta-data associated with at least one of the business intelligence elements, key figures, and stream of big data,
(iii) automatically execute an expert knowledge tool to process the business intelligence elements, key figures, and stream of big data,
(iv) automatically execute a data interpretation tool on the business intelligence elements, key figures, and stream of big data, and
(v) render a smart analytics interface display on the remote user device via the distributed communication network, the smart analytics interface display including outputs of the context determination tool, expert knowledge tool, and data interpretation tool. 2. The system of claim 1, wherein the context determination tool leverages received information by adding additional facts or values, reduces information noise, and suggests related elements based on available contextual information. 3. The system of claim 1, wherein the expert knowledge tool comprises internal, generic best-practices algorithms. 4. The system of claim 3, wherein the algorithms are associated with at least one of: outlier analysis, trend identification, and a plan versus actual comparison. 5. The system of claim 1, wherein the expert knowledge tool comprises external domain expertise to model domain specific rules. 6. The system of claim 1, wherein the data interpretation tool determines hidden correlations, patterns, or drivers associated with an enterprise. 7. The system of claim 6, wherein the data interpretation tool operates based at least in part on an enterprise role associated with the user. 8. The system of claim 6, wherein the data interpretation tool is configured to perform one of the following tasks: explain a business meaning of a specific key figure, explain an impact a specific key figure has on an enterprise, explain the consequences of a specific key figure, explain at least one decision that needs to be made along with a set of options associated with that decision, explain at least one next logical analysis step, suggest related reports or key figures, and propose other business aspects that may be associated with a specific key figure. 9. The system of claim 6, wherein the data interpretation tool is configured to receive from the user a request for increased data interpretation and, responsive to the received request, provide additional support information. 10. The system of claim 6, wherein the data interpretation tool includes a visual focus component, a comprehension component, and a textual conclusion component. 11. The system of claim 10, wherein the visual focus component is associated with a heat map. 12. The system of claim 10, wherein the comprehension component brings multiple perspectives of analysis by providing an overview to explain a specific key figure, suggesting dimensions via a relationship analyzer, accessing pre-determined dimensions and key figures, and summarizing findings. 13. The system of claim 12, wherein the summarized findings are provided to the user in human readable language. 14. A method implemented by a computing system in response to execution of program code by a processor of the computing system, the method to improve a user data interface associated with a distributed computer network and comprising:
receiving, via a communication port, electronic messages containing business intelligence elements, key figures, and a stream of big data; accessing, by a computer processor of a smart analytics platform, the business intelligence elements, key figures, and stream of big data; automatically executing, by the computer processor of the smart analytics platform, a context determination tool utilizing meta-data associated with at least one of the business intelligence elements, key figures, and stream of big data; automatically executing, by the computer processor of the smart analytics platform, an expert knowledge tool to process the business intelligence elements, key figures, and stream of big data; automatically executing, by the computer processor of the smart analytics platform, a data interpretation tool on the business intelligence elements, key figures, and stream of big data; and rendering a smart analytics interface display on the remote user device via the distributed communication network, the smart analytics interface display including outputs of the context determination tool, expert knowledge tool, and data interpretation tool. 15. The method of claim 14, wherein the context determination tool leverages received information by adding additional facts or values, reduces information noise, and suggests related elements based on available contextual information. 16. The method of claim 14, wherein the expert knowledge tool comprises internal, generic best-practices algorithms associated with at least one of: outlier analysis, trend identification, and a plan versus actual comparison. 17. The method of claim 14, wherein the data interpretation tool determines hidden correlations, patterns, or drivers associated with an enterprise based at least in part on an enterprise role associated with the user. 18. The method of claim 14, wherein the data interpretation tool includes a visual focus component associated with a heat map, a comprehension component, and a textual conclusion component. 19. A non-transitory medium storing processor-executable program code, the program code executable by a processor of a computing device to improve a user data interface associated with a distributed communication network by:
receiving, via a communication port, electronic messages containing business intelligence elements, key figures, and a stream of big data; accessing, by a computer processor of a smart analytics platform, the business intelligence elements, key figures, and stream of big data; automatically executing, by the computer processor of the smart analytics platform, a context determination tool utilizing meta-data associated with at least one of the business intelligence elements, key figures, and stream of big data; automatically executing, by the computer processor of the smart analytics platform, an expert knowledge tool to process the business intelligence elements, key figures, and stream of big data; automatically executing, by the computer processor of the smart analytics platform, a data interpretation tool on the business intelligence elements, key figures, and stream of big data; and rendering a smart analytics interface display on the remote user device via the distributed communication network, the smart analytics interface display including outputs of the context determination tool, expert knowledge tool, and data interpretation tool. 20. The medium of claim 19, wherein the context determination tool leverages received information by adding additional facts or values, reduces information noise, and suggests related elements based on available contextual information. 21. The medium of claim 19, wherein the expert knowledge tool comprises internal, generic best-practices algorithms associated with at least one of: outlier analysis, trend identification, and a plan versus actual comparison. 22. The medium of claim 19, wherein the data interpretation tool determines hidden correlations, patterns, or drivers associated with an enterprise based at least in part on an enterprise role associated with the user. 23. The medium of claim 19, wherein the data interpretation tool includes a visual focus component associated with a heat map, a comprehension component, and a textual conclusion component. | 2,100 |
6,538 | 6,538 | 14,491,477 | 2,124 | Text is received from a first user. The text is associated with an electronic communication tool for communication to a second user. Candidate answers are generated based on the text using a question answering system. At least one of the candidate answers is provided to the first user. | 1. A method comprising:
receiving text from a first user, the text associated with an electronic communication tool for communication to a second user; generating candidate answers based on the text using a question answering system; and providing at least one of the candidate answers to the first user. 2. The method of claim 1, wherein the text is received prior to the first user communicating the text to the second user. 3. The method of claim 1, further comprising:
calculating confidence scores for the candidate answers; and selecting the at least one candidate answers based on the confidence scores. 4. The method of claim 3, further comprising:
providing, to the first user, respective confidence scores for the at least one candidate answers. 5. The method of claim 3, further comprising:
determining at least one of the confidence scores exceeds a specified value; and blocking a communication attempt of the text to the second user in response to the determining at least one of the confidence scores exceeds the specified value. 6. The method of claim 3, wherein the providing the at least one candidate answers to the first user occurs in response to determining at least one of the confidence scores exceeds a specified value. 7. The method of claim 1, wherein the electronic communication tool is an instant messaging program. | Text is received from a first user. The text is associated with an electronic communication tool for communication to a second user. Candidate answers are generated based on the text using a question answering system. At least one of the candidate answers is provided to the first user.1. A method comprising:
receiving text from a first user, the text associated with an electronic communication tool for communication to a second user; generating candidate answers based on the text using a question answering system; and providing at least one of the candidate answers to the first user. 2. The method of claim 1, wherein the text is received prior to the first user communicating the text to the second user. 3. The method of claim 1, further comprising:
calculating confidence scores for the candidate answers; and selecting the at least one candidate answers based on the confidence scores. 4. The method of claim 3, further comprising:
providing, to the first user, respective confidence scores for the at least one candidate answers. 5. The method of claim 3, further comprising:
determining at least one of the confidence scores exceeds a specified value; and blocking a communication attempt of the text to the second user in response to the determining at least one of the confidence scores exceeds the specified value. 6. The method of claim 3, wherein the providing the at least one candidate answers to the first user occurs in response to determining at least one of the confidence scores exceeds a specified value. 7. The method of claim 1, wherein the electronic communication tool is an instant messaging program. | 2,100 |
6,539 | 6,539 | 14,146,814 | 2,176 | A method and/or computer program product provides client-side personalization of websites. A client and a web server are provided with a description language infrastructure that provides classifying categories for web content. A browser locally defines user preferences for web content as description language classifying categories for web content. Web content is requested and received from the web server as a response, which includes the requested web content and a markup with description language information specifying all alternatives of classifying categories for web content fragments of the web content. The classifying categories are locally filtered for web content fragments of the web content based on said locally defined user preference. A personalized subset of the web content is displayed based on the locally defined user preferences. | 1. A method for client-side personalization of websites, the method comprising:
providing both a client and a web server with a description language infrastructure that provides classifying categories for web content; locally defining, via a browser, user preferences for web content as description language classifying categories for web content; requesting, by one or more processors, web content from said web server; receiving, by one or more processors, a response from said web server, wherein said response comprises said requested web content and a markup with description language information specifying all alternatives of classifying categories for web content fragments of said web content; locally filtering, by one or more processors, said classifying categories for web content fragments of said web content based on said locally defined user preferences; and displaying a personalized subset of said web content based on said locally defined user preferences. 2. The method according to claim 1, wherein said locally defined user preferences are stored in a local storage of said client. 3. The method according to claim 1, wherein said locally defined user preferences are compared with said classifying categories for web content fragments of said web content during filtering, and wherein only web content fragments of said web content with a correlating classifying category is part of said personalized subset of said displayed web content. 4. The method according to claim 1, wherein said description language infrastructure is configured as extended media query infrastructure providing attributes and values to classify categories for web content. 5. The method according to claim 1, wherein said markup comprises categorized content information, wherein said categorized content information flags each web content fragment, and wherein said categorized content information identifies which user preference said web content fragment addresses. 6. The method according to claim 5, wherein said content information flags alternative web content fragments for different user preferences. 7. The method according to claim 1, wherein said user preferences comprise pre-defined parameters like age, gender and/or category of interest, and additional custom-parameters. 8. The method according to claim 1, wherein said web server presents parameters for defining user preferences to said client that said web server supports. 9. A network environment comprising:
at least one client and at least one web server, wherein said at least one client and said at least one web server both comprise a description language infrastructure that provides classifying categories for web content; a browser on said at least one client, wherein said browser locally defines user preferences for web content as description language classifying categories; wherein said at least one web server stores defined markups with description language information reflecting all alternatives of classifying categories for web content fragments used in said at least one web server; wherein said at least one client requests web content from said at least one web server and receives a response from said at least one web server, wherein said response comprises said requested web content and markup with description language information specifying all alternatives of classifying categories for web content fragments of said requested web content; wherein said browser processes said markup and locally filters said classifying categories for web content fragments of said web content based on said locally defined user preferences; and a display, wherein the display displays a personalized subset of said web content based on said locally defined user preferences. 10. The network environment according to claim 9, wherein said description language infrastructure is configured as extended media query infrastructure providing attributes and values to classify categories for web content. 11. The network environment according to claim 9, wherein said at least one client comprises a user interface configured to edit parameters reflecting said user preferences and usable by said description language infrastructure, and wherein said user interface displays an input mask to a user interface to specify parameters for personalization preferences at said at least one client device. 12. The network environment according to claim 10, wherein said browser comprises a media query plugin performing a local website analysis to detect habits and interests of a user. 13. The network environment according to claim 12, wherein said media query plugin analyzes said habits and interest of said user to automatically define said user preferences. 14. A computer program product for client-side personalization of websites, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising:
providing both a client and a web server with a description language infrastructure that provides classifying categories for web content; locally defining, via a browser, user preferences as description language classifying categories for web content; requesting, by one or more processors, web content from said web server; receiving a response from said web server, wherein said response comprises said requested web content and a markup with description language information specifying all alternatives of classifying categories for web content fragments of said web content; locally filtering, by one or more processors, said classifying categories for web content fragments of said web content based on said locally defined user preferences; and displaying a personalized subset of said web content based on said locally defined user preferences. 15. The computer program product of claim 14, wherein said locally defined user preferences are stored in a local storage of said client. 16. The computer program product of claim 14, wherein said locally defined user preferences are compared with said classifying categories for web content fragments of said web content during filtering; and only web content fragments of said web content with a correlating classifying category is part of said personalized subset of said displayed web content. 17. The computer program product of claim 14, wherein said description language infrastructure is configured as extended media query infrastructure providing attributes and/or values to classify categories for web content. 18. The computer program product of claim 14, wherein said markup comprises categorized content information, wherein said categorized content information flags each web content fragment, and wherein said categorized content information identifies which user preference said web content fragment addresses. 19. The computer program product of claim 18, wherein said content information flags alternative web content fragments for different user preferences. 20. The computer program product of claim 14, wherein said web server presents parameters for defining user preferences to said client that said web server supports. | A method and/or computer program product provides client-side personalization of websites. A client and a web server are provided with a description language infrastructure that provides classifying categories for web content. A browser locally defines user preferences for web content as description language classifying categories for web content. Web content is requested and received from the web server as a response, which includes the requested web content and a markup with description language information specifying all alternatives of classifying categories for web content fragments of the web content. The classifying categories are locally filtered for web content fragments of the web content based on said locally defined user preference. A personalized subset of the web content is displayed based on the locally defined user preferences.1. A method for client-side personalization of websites, the method comprising:
providing both a client and a web server with a description language infrastructure that provides classifying categories for web content; locally defining, via a browser, user preferences for web content as description language classifying categories for web content; requesting, by one or more processors, web content from said web server; receiving, by one or more processors, a response from said web server, wherein said response comprises said requested web content and a markup with description language information specifying all alternatives of classifying categories for web content fragments of said web content; locally filtering, by one or more processors, said classifying categories for web content fragments of said web content based on said locally defined user preferences; and displaying a personalized subset of said web content based on said locally defined user preferences. 2. The method according to claim 1, wherein said locally defined user preferences are stored in a local storage of said client. 3. The method according to claim 1, wherein said locally defined user preferences are compared with said classifying categories for web content fragments of said web content during filtering, and wherein only web content fragments of said web content with a correlating classifying category is part of said personalized subset of said displayed web content. 4. The method according to claim 1, wherein said description language infrastructure is configured as extended media query infrastructure providing attributes and values to classify categories for web content. 5. The method according to claim 1, wherein said markup comprises categorized content information, wherein said categorized content information flags each web content fragment, and wherein said categorized content information identifies which user preference said web content fragment addresses. 6. The method according to claim 5, wherein said content information flags alternative web content fragments for different user preferences. 7. The method according to claim 1, wherein said user preferences comprise pre-defined parameters like age, gender and/or category of interest, and additional custom-parameters. 8. The method according to claim 1, wherein said web server presents parameters for defining user preferences to said client that said web server supports. 9. A network environment comprising:
at least one client and at least one web server, wherein said at least one client and said at least one web server both comprise a description language infrastructure that provides classifying categories for web content; a browser on said at least one client, wherein said browser locally defines user preferences for web content as description language classifying categories; wherein said at least one web server stores defined markups with description language information reflecting all alternatives of classifying categories for web content fragments used in said at least one web server; wherein said at least one client requests web content from said at least one web server and receives a response from said at least one web server, wherein said response comprises said requested web content and markup with description language information specifying all alternatives of classifying categories for web content fragments of said requested web content; wherein said browser processes said markup and locally filters said classifying categories for web content fragments of said web content based on said locally defined user preferences; and a display, wherein the display displays a personalized subset of said web content based on said locally defined user preferences. 10. The network environment according to claim 9, wherein said description language infrastructure is configured as extended media query infrastructure providing attributes and values to classify categories for web content. 11. The network environment according to claim 9, wherein said at least one client comprises a user interface configured to edit parameters reflecting said user preferences and usable by said description language infrastructure, and wherein said user interface displays an input mask to a user interface to specify parameters for personalization preferences at said at least one client device. 12. The network environment according to claim 10, wherein said browser comprises a media query plugin performing a local website analysis to detect habits and interests of a user. 13. The network environment according to claim 12, wherein said media query plugin analyzes said habits and interest of said user to automatically define said user preferences. 14. A computer program product for client-side personalization of websites, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising:
providing both a client and a web server with a description language infrastructure that provides classifying categories for web content; locally defining, via a browser, user preferences as description language classifying categories for web content; requesting, by one or more processors, web content from said web server; receiving a response from said web server, wherein said response comprises said requested web content and a markup with description language information specifying all alternatives of classifying categories for web content fragments of said web content; locally filtering, by one or more processors, said classifying categories for web content fragments of said web content based on said locally defined user preferences; and displaying a personalized subset of said web content based on said locally defined user preferences. 15. The computer program product of claim 14, wherein said locally defined user preferences are stored in a local storage of said client. 16. The computer program product of claim 14, wherein said locally defined user preferences are compared with said classifying categories for web content fragments of said web content during filtering; and only web content fragments of said web content with a correlating classifying category is part of said personalized subset of said displayed web content. 17. The computer program product of claim 14, wherein said description language infrastructure is configured as extended media query infrastructure providing attributes and/or values to classify categories for web content. 18. The computer program product of claim 14, wherein said markup comprises categorized content information, wherein said categorized content information flags each web content fragment, and wherein said categorized content information identifies which user preference said web content fragment addresses. 19. The computer program product of claim 18, wherein said content information flags alternative web content fragments for different user preferences. 20. The computer program product of claim 14, wherein said web server presents parameters for defining user preferences to said client that said web server supports. | 2,100 |
6,540 | 6,540 | 15,190,936 | 2,165 | The current document is directed to methods and subsystems within computing systems, including distributed computing systems that efficiently store metric data by approximating a sequence of time-associated data values with one or more linear functions. In a described implementation, a running variability metric is used to control variation within the metric data with respect to the approximating linear functions, with a variation threshold employed to maximize the number of data points represented by a given linear function while ensuring that the variation of the data with respect to the given linear function does not exceed a threshold value. In one implementation, the metric data occurs within a graph-like configuration-management-database representation of the current state of a computer system. | 1. A state-information-storage subsystem within a computer system that includes one or more processors, one or more memories, and one or more data-storage devices, the state-information-storage subsystem comprising:
current state information, including object entities associated with properties and metrics, that is maintained within a combination of one or more memories and one or more data-storage devices; state-information snapshots, stored in one or more physical data-storage devices, that encode the state information for the computer system at various previous times in compressed form, including compressed encodings of sequences of data points, each associated with a property or metric, as a set of one or more linear functions; and a state-information-storage subsystem control component that maintains the current state information, generates linear-function approximations of data-point sequences, generates state-information snapshots, and stores the state-information snapshots in the one or more physical data-storage devices. 2. The state-information-storage subsystem of claim 1 wherein each metric and property are associated with a sequence data points, each data point comprising a time-associated numeric data value. 3. The state-infoiination-storage subsystem of claim 2 wherein one or more property metric entities are initially associated with one or more data points having a non-numeric time-associated data value; and wherein the state-information-storage subsystem converts the non-numeric data values of the data points to numeric values. 4. The state-information-storage subsystem of claim 3 wherein the state-information-storage subsystem converts the non-numeric data values of the data points to numeric values by:
for each entity initially associated with one or more data points having non-numeric data values,
associating a hash function and a hash table with the entity;
for each data point containing a non-numeric data value,
applying the hash function to the non-numeric data value to generate a hash-table index,
identifying a hash-table entry indexed by the generated index;
when the non-numeric data value is not already stored in the hash-table entry or a collision list associated with the hash-table entry,
storing the non-numeric data value in the hash-table entry or a collision list associated with the hash-table entry;
generating a numeric value from the generated hash-table index and from a numeric representation of a location of the non-numeric data value within the hash-table entry or collision list, and
replacing the non-numeric data value in the data point with the generated numeric value. 5. The state-information-storage subsystem of claim 2 wherein the state-information-storage subsystem control component generates a set of linear-function approximations of a data-point sequence by:
considering the data-point sequence as a time-ordered set of remaining data points;
creating an empty set of linear-function approximations;
while the time-ordered set of remaining data points is not empty,
when the time-ordered set of remaining data points contains a single data point, adding the single data point as the final entry in the set of linear-function approximations;
when the time-ordered set of remaining data points contains two data points,
approximating the remaining data points with a line segment with endpoints corresponding to the two remaining data points, and
adding a representation of the line segment as the final entry in the set of linear-function approximations; and
when the data-point sequence contains more than two data points,
generating a next line-segment approximation for at least the next two of the remaining data points,
adding a representation of the next line-segment approximation to the set of linear-function approximations, and
removing the data points approximated by the next approximation from the time-ordered set of remaining data points. 6. The state-information-storage subsystem of claim 5 wherein generating a next line-segment approximation for at least the next two of the remaining data points further comprises:
constructing, as a current line segment, a line segment with a first endpoint corresponding to the first remaining data point and a second endpoint corresponding to the third remaining data point to approximate the first three remaining data points;
while a variation computed for the data points approximated by the current line segment is less than a threshold variation and there is a next data point in the time-ordered set of remaining data points,
extending the current line segment so that the second endpoint of the current line segment coincides with the next data point. 7. The state-information-storage subsystem of claim 6 wherein intermediate data points are data points approximated by the current line segment but not coincident with the endpoints of the current line segment; wherein a relative difference is the difference between the data value of a data point and the intersection of a vertical line coincident with the data point and the current line segment; wherein the variation computed for the data points approximated by the current line segment is computed as the square root of the sum of the relative differences of the data values of the intermediate data points divided by the number of intermediate data points. 8. The state-information-storage subsystem of claim 6 wherein adding a representation of the next line-segment approximation to the set of linear-function approximations further comprises:
generating an equation of a second line that minimizes the distances between the data values of the data points approximated by the current line segment and the second line; and
adding a representation of the second line to the set of linear-function approximations. 9. The state-information-storage subsystem of claim 1 wherein the state-information snapshots are each associated with a timestamp; and wherein the state-information-storage subsystem maintains stored state information for a time at which a most recent snapshot was generated; and wherein the state-information-storage subsystem generates a next snapshot by computing and storing the differences between the current state information and the stored state information for the time at which the most recent snapshot was generated. 10. A method that generates a linear-function approximation of an ordered sequence of data points corresponding to a metric or property, each data point comprising a time-associated data value, the method carried out within a computer system that includes one or more processors, one or more memories, and one or more data-storage devices, the method comprising:
when one or more data points in the ordered sequence of data points has a non-numeric data value, converting the one or more non-numeric data values to numeric data values; determining a set of lines that approximate the data values of the ordered sequence of data points; and storing the set of lines that approximate the data values of the ordered sequence of data points in one or more memories and/or data-storage devices. 11. The method of claim 10 wherein converting the one or more non-numeric data values to numeric data values further comprises:
associating a hash function and a hash table with the ordered sequence of data points;
for each data point that includes a non-numeric time-associated data value,
associating a hash function and a hash table with the property;
for each data point of the ordered sequence of data points containing a non-numeric data value,
applying the hash function to the non-numeric data value to generate a hash-table index,
identifying a hash-table entry indexed by the generated index;
when the non-numeric data value is not already stored in the hash-table entry or a collision list associated with the hash-table entry,
storing the non-numeric data value in the hash-table entry or an entry of the collision list associated with the hash-table entry;
generating a numeric value from the generated hash-table index and from a numeric representation of a location of the non-numeric data value within the hash-table entry or collision list, and
replacing the non-numeric data value in the data point with the generated numeric value. 12. The method of claim 10 wherein determining a set of lines that approximate the data values of the ordered sequence of data points further comprises:
considering the sequence of data points as a time-ordered set of remaining data points;
creating an empty set of linear-function approximations;
while the time-ordered set of remaining data points is not empty,
when the time-ordered set of remaining data points contains a single data point, adding the single data point as the final entry in the set of linear-function approximations;
when the time-ordered set of remaining data points contains two data points,
approximating the remaining data points with a line segment with endpoints corresponding to the two remaining data points, and
adding a representation of the line segment as the final entry in the set of linear-function approximations; and
when the data-point sequence contains more than two data points,
generating a next line-segment approximation for at least the next two of the remaining data points,
adding a representation of the next line-segment approximation to the set of linear-function approximations, and
removing the data points approximated by the next approximation from the time-ordered set of remaining data points. 13. The method of claim 12 wherein generating a next line-segment approximation for at least the next two of the remaining data points further comprises:
constructing, as a current line segment, a line segment with a first endpoint corresponding to the first remaining data point and a second endpoint corresponding to the third remaining data point to approximate the first three remaining data points;
while a variation computed for the data points approximated by the current line segment is less than a threshold variation and there is a next data point in the time-ordered set of remaining data points,
extending the current line segment so that the second endpoint of the current line segment coincides with the next data point. 14. The method of claim 13 wherein intermediate data points are data points approximated by the current line segment but not coincident with the endpoints of the current line segment; wherein a relative difference is the difference between the data value of a data point and the intersection of a vertical line coincident with the data point and the current line segment; wherein the variation computed for the data points approximated by the current line segment is computed as the square root of the sum of the relative differences of the data values of the intermediate data points divided by the number of intermediate data points. 15. The method of claim 12 wherein adding a representation of the next line-segment approximation to the set of linear-function approximations further comprises:
generating an equation of a second line that minimizes the distances between the data values of the data points approximated by the current line segment and the second line; and
adding a representation of the second line to the set of linear-function approximations. 16. The method of claim 12 wherein the representation of the next line-segment comprises one of:
two sets of coordinates for the endpoints of the next line-segment; and
a value for a slope of the next line-segment and a value for a time-axis intercept of the next line-segment. 17. Computer instructions, stored within a physical data-storage device, that, when executed by one or more processors of a computer system that includes the one or more processors, one or more memories, and one or more data-storage devices, control the computer system to generate a linear-function approximation of an ordered sequence of data points corresponding to a metric or property, each data point comprising a time-associated data value, by:
when one or more data points in the ordered sequence of data points has a non-numeric data value, converting the one or more non-numeric data values to numeric data values; determining a set of lines that approximate the data values of the ordered sequence of data points; and storing the set of lines that approximate the data values of the ordered sequence of data points in one or more memories and/or data-storage devices. 18. The computer instructions of claim 17 wherein converting the one or more non-numeric data values to numeric data values further comprises:
associating a hash function and a hash table with the ordered sequence of data points;
for each data point that includes a non-numeric time-associated data value,
associating a hash function and a hash table with the property;
for each data point of the ordered sequence of data points containing a non-numeric data value,
applying the hash function to the non-numeric data value to generate a hash-table index,
identifying a hash-table entry indexed by the generated index;
when the non-numeric data value is not already stored in the hash-table entry or a collision list associated with the hash-table entry,
storing the non-numeric data value in the hash-table entry or an entry of the collision list associated with the hash-table entry;
generating a numeric value from the generated hash-table index and from a numeric representation of a location of the non-numeric data value within the hash-table entry or collision list, and
replacing the non-numeric data value in the data point with the generated numeric value. 19. The computer instructions of claim 17 wherein determining a set of lines that approximate the data values of the ordered sequence of data points further comprises:
considering the sequence of data points as a time-ordered set of remaining data points;
creating an empty set of linear-function approximations;
while the time-ordered set of remaining data points is not empty,
when the time-ordered set of remaining data points contains a single data point, adding the single data point as the final entry in the set of linear-function approximations;
when the time-ordered set of remaining data points contains two data points,
approximating the remaining data points with a line segment with endpoints corresponding to the two remaining data points, and
adding a representation of the line segment as the final entry in the set of linear-function approximations; and
when the data-point sequence contains more than two data points,
generating a next line-segment approximation for at least the next two of the remaining data points,
adding a representation of the next line-segment approximation to the set of linear-function approximations, and
removing the data points approximated by the next approximation from the time-ordered set of remaining data points. 20. The computer instructions of claim 19 wherein generating a next line-segment approximation for at least the next two of the remaining data points further comprises:
constructing, as a current line segment, a line segment with a first endpoint corresponding to the first remaining data point and a second endpoint corresponding to the third remaining data point to approximate the first three remaining data points;
while a variation computed for the data points approximated by the current line segment is less than a threshold variation and there is a next data point in the time-ordered set of remaining data points,
extending the current line segment so that the second endpoint of the current line segment coincides with the next data point. | The current document is directed to methods and subsystems within computing systems, including distributed computing systems that efficiently store metric data by approximating a sequence of time-associated data values with one or more linear functions. In a described implementation, a running variability metric is used to control variation within the metric data with respect to the approximating linear functions, with a variation threshold employed to maximize the number of data points represented by a given linear function while ensuring that the variation of the data with respect to the given linear function does not exceed a threshold value. In one implementation, the metric data occurs within a graph-like configuration-management-database representation of the current state of a computer system.1. A state-information-storage subsystem within a computer system that includes one or more processors, one or more memories, and one or more data-storage devices, the state-information-storage subsystem comprising:
current state information, including object entities associated with properties and metrics, that is maintained within a combination of one or more memories and one or more data-storage devices; state-information snapshots, stored in one or more physical data-storage devices, that encode the state information for the computer system at various previous times in compressed form, including compressed encodings of sequences of data points, each associated with a property or metric, as a set of one or more linear functions; and a state-information-storage subsystem control component that maintains the current state information, generates linear-function approximations of data-point sequences, generates state-information snapshots, and stores the state-information snapshots in the one or more physical data-storage devices. 2. The state-information-storage subsystem of claim 1 wherein each metric and property are associated with a sequence data points, each data point comprising a time-associated numeric data value. 3. The state-infoiination-storage subsystem of claim 2 wherein one or more property metric entities are initially associated with one or more data points having a non-numeric time-associated data value; and wherein the state-information-storage subsystem converts the non-numeric data values of the data points to numeric values. 4. The state-information-storage subsystem of claim 3 wherein the state-information-storage subsystem converts the non-numeric data values of the data points to numeric values by:
for each entity initially associated with one or more data points having non-numeric data values,
associating a hash function and a hash table with the entity;
for each data point containing a non-numeric data value,
applying the hash function to the non-numeric data value to generate a hash-table index,
identifying a hash-table entry indexed by the generated index;
when the non-numeric data value is not already stored in the hash-table entry or a collision list associated with the hash-table entry,
storing the non-numeric data value in the hash-table entry or a collision list associated with the hash-table entry;
generating a numeric value from the generated hash-table index and from a numeric representation of a location of the non-numeric data value within the hash-table entry or collision list, and
replacing the non-numeric data value in the data point with the generated numeric value. 5. The state-information-storage subsystem of claim 2 wherein the state-information-storage subsystem control component generates a set of linear-function approximations of a data-point sequence by:
considering the data-point sequence as a time-ordered set of remaining data points;
creating an empty set of linear-function approximations;
while the time-ordered set of remaining data points is not empty,
when the time-ordered set of remaining data points contains a single data point, adding the single data point as the final entry in the set of linear-function approximations;
when the time-ordered set of remaining data points contains two data points,
approximating the remaining data points with a line segment with endpoints corresponding to the two remaining data points, and
adding a representation of the line segment as the final entry in the set of linear-function approximations; and
when the data-point sequence contains more than two data points,
generating a next line-segment approximation for at least the next two of the remaining data points,
adding a representation of the next line-segment approximation to the set of linear-function approximations, and
removing the data points approximated by the next approximation from the time-ordered set of remaining data points. 6. The state-information-storage subsystem of claim 5 wherein generating a next line-segment approximation for at least the next two of the remaining data points further comprises:
constructing, as a current line segment, a line segment with a first endpoint corresponding to the first remaining data point and a second endpoint corresponding to the third remaining data point to approximate the first three remaining data points;
while a variation computed for the data points approximated by the current line segment is less than a threshold variation and there is a next data point in the time-ordered set of remaining data points,
extending the current line segment so that the second endpoint of the current line segment coincides with the next data point. 7. The state-information-storage subsystem of claim 6 wherein intermediate data points are data points approximated by the current line segment but not coincident with the endpoints of the current line segment; wherein a relative difference is the difference between the data value of a data point and the intersection of a vertical line coincident with the data point and the current line segment; wherein the variation computed for the data points approximated by the current line segment is computed as the square root of the sum of the relative differences of the data values of the intermediate data points divided by the number of intermediate data points. 8. The state-information-storage subsystem of claim 6 wherein adding a representation of the next line-segment approximation to the set of linear-function approximations further comprises:
generating an equation of a second line that minimizes the distances between the data values of the data points approximated by the current line segment and the second line; and
adding a representation of the second line to the set of linear-function approximations. 9. The state-information-storage subsystem of claim 1 wherein the state-information snapshots are each associated with a timestamp; and wherein the state-information-storage subsystem maintains stored state information for a time at which a most recent snapshot was generated; and wherein the state-information-storage subsystem generates a next snapshot by computing and storing the differences between the current state information and the stored state information for the time at which the most recent snapshot was generated. 10. A method that generates a linear-function approximation of an ordered sequence of data points corresponding to a metric or property, each data point comprising a time-associated data value, the method carried out within a computer system that includes one or more processors, one or more memories, and one or more data-storage devices, the method comprising:
when one or more data points in the ordered sequence of data points has a non-numeric data value, converting the one or more non-numeric data values to numeric data values; determining a set of lines that approximate the data values of the ordered sequence of data points; and storing the set of lines that approximate the data values of the ordered sequence of data points in one or more memories and/or data-storage devices. 11. The method of claim 10 wherein converting the one or more non-numeric data values to numeric data values further comprises:
associating a hash function and a hash table with the ordered sequence of data points;
for each data point that includes a non-numeric time-associated data value,
associating a hash function and a hash table with the property;
for each data point of the ordered sequence of data points containing a non-numeric data value,
applying the hash function to the non-numeric data value to generate a hash-table index,
identifying a hash-table entry indexed by the generated index;
when the non-numeric data value is not already stored in the hash-table entry or a collision list associated with the hash-table entry,
storing the non-numeric data value in the hash-table entry or an entry of the collision list associated with the hash-table entry;
generating a numeric value from the generated hash-table index and from a numeric representation of a location of the non-numeric data value within the hash-table entry or collision list, and
replacing the non-numeric data value in the data point with the generated numeric value. 12. The method of claim 10 wherein determining a set of lines that approximate the data values of the ordered sequence of data points further comprises:
considering the sequence of data points as a time-ordered set of remaining data points;
creating an empty set of linear-function approximations;
while the time-ordered set of remaining data points is not empty,
when the time-ordered set of remaining data points contains a single data point, adding the single data point as the final entry in the set of linear-function approximations;
when the time-ordered set of remaining data points contains two data points,
approximating the remaining data points with a line segment with endpoints corresponding to the two remaining data points, and
adding a representation of the line segment as the final entry in the set of linear-function approximations; and
when the data-point sequence contains more than two data points,
generating a next line-segment approximation for at least the next two of the remaining data points,
adding a representation of the next line-segment approximation to the set of linear-function approximations, and
removing the data points approximated by the next approximation from the time-ordered set of remaining data points. 13. The method of claim 12 wherein generating a next line-segment approximation for at least the next two of the remaining data points further comprises:
constructing, as a current line segment, a line segment with a first endpoint corresponding to the first remaining data point and a second endpoint corresponding to the third remaining data point to approximate the first three remaining data points;
while a variation computed for the data points approximated by the current line segment is less than a threshold variation and there is a next data point in the time-ordered set of remaining data points,
extending the current line segment so that the second endpoint of the current line segment coincides with the next data point. 14. The method of claim 13 wherein intermediate data points are data points approximated by the current line segment but not coincident with the endpoints of the current line segment; wherein a relative difference is the difference between the data value of a data point and the intersection of a vertical line coincident with the data point and the current line segment; wherein the variation computed for the data points approximated by the current line segment is computed as the square root of the sum of the relative differences of the data values of the intermediate data points divided by the number of intermediate data points. 15. The method of claim 12 wherein adding a representation of the next line-segment approximation to the set of linear-function approximations further comprises:
generating an equation of a second line that minimizes the distances between the data values of the data points approximated by the current line segment and the second line; and
adding a representation of the second line to the set of linear-function approximations. 16. The method of claim 12 wherein the representation of the next line-segment comprises one of:
two sets of coordinates for the endpoints of the next line-segment; and
a value for a slope of the next line-segment and a value for a time-axis intercept of the next line-segment. 17. Computer instructions, stored within a physical data-storage device, that, when executed by one or more processors of a computer system that includes the one or more processors, one or more memories, and one or more data-storage devices, control the computer system to generate a linear-function approximation of an ordered sequence of data points corresponding to a metric or property, each data point comprising a time-associated data value, by:
when one or more data points in the ordered sequence of data points has a non-numeric data value, converting the one or more non-numeric data values to numeric data values; determining a set of lines that approximate the data values of the ordered sequence of data points; and storing the set of lines that approximate the data values of the ordered sequence of data points in one or more memories and/or data-storage devices. 18. The computer instructions of claim 17 wherein converting the one or more non-numeric data values to numeric data values further comprises:
associating a hash function and a hash table with the ordered sequence of data points;
for each data point that includes a non-numeric time-associated data value,
associating a hash function and a hash table with the property;
for each data point of the ordered sequence of data points containing a non-numeric data value,
applying the hash function to the non-numeric data value to generate a hash-table index,
identifying a hash-table entry indexed by the generated index;
when the non-numeric data value is not already stored in the hash-table entry or a collision list associated with the hash-table entry,
storing the non-numeric data value in the hash-table entry or an entry of the collision list associated with the hash-table entry;
generating a numeric value from the generated hash-table index and from a numeric representation of a location of the non-numeric data value within the hash-table entry or collision list, and
replacing the non-numeric data value in the data point with the generated numeric value. 19. The computer instructions of claim 17 wherein determining a set of lines that approximate the data values of the ordered sequence of data points further comprises:
considering the sequence of data points as a time-ordered set of remaining data points;
creating an empty set of linear-function approximations;
while the time-ordered set of remaining data points is not empty,
when the time-ordered set of remaining data points contains a single data point, adding the single data point as the final entry in the set of linear-function approximations;
when the time-ordered set of remaining data points contains two data points,
approximating the remaining data points with a line segment with endpoints corresponding to the two remaining data points, and
adding a representation of the line segment as the final entry in the set of linear-function approximations; and
when the data-point sequence contains more than two data points,
generating a next line-segment approximation for at least the next two of the remaining data points,
adding a representation of the next line-segment approximation to the set of linear-function approximations, and
removing the data points approximated by the next approximation from the time-ordered set of remaining data points. 20. The computer instructions of claim 19 wherein generating a next line-segment approximation for at least the next two of the remaining data points further comprises:
constructing, as a current line segment, a line segment with a first endpoint corresponding to the first remaining data point and a second endpoint corresponding to the third remaining data point to approximate the first three remaining data points;
while a variation computed for the data points approximated by the current line segment is less than a threshold variation and there is a next data point in the time-ordered set of remaining data points,
extending the current line segment so that the second endpoint of the current line segment coincides with the next data point. | 2,100 |
6,541 | 6,541 | 16,360,403 | 2,187 | An amplifier includes a dynamic bias circuit and an amplification circuit coupled to the dynamic bias circuit. The dynamic bias circuit includes a plurality of transistors coupled to a plurality of resistors. The dynamic bias circuit is configured to generate a bias current with a magnitude that increases in response to the dynamic bias circuit receiving a falling edge of an input signal and decreases in response to the dynamic bias circuit receiving a rising edge of the input signal. The amplification circuit is configured to receive the bias current and amplify the input signal based on the bias current to generate an output signal that has a higher slew rate for a falling signal than for a rising signal. | 1. An amplifier, comprising:
a dynamic bias circuit including a plurality of transistors coupled to a plurality of resistors, the dynamic bias circuit configured to generate a bias current with a magnitude that increases in response to the dynamic bias circuit receiving a falling edge of an input signal and decreases in response to the dynamic bias circuit receiving a rising edge of the input signal; and an amplification circuit coupled to the dynamic bias circuit, the amplification circuit configured to receive the bias current and amplify the input signal based on the bias current to generate an output signal that has a higher slew rate for a falling signal than for a rising signal. 2. The amplifier of claim 1, wherein the plurality of transistors includes:
a first transistor that comprises a first gate, a first source, and a first drain, the first gate connected to a first differential input of the input signal, the first drain connected to ground, and the first source connected to a first resistor; a second transistor that comprises a second gate, a second source, and a second drain, the second gate coupled to a second differential input of the input signal, the second drain connected to ground, and the second source connected to a second resistor; a third transistor that comprises a third gate, a third source, and a third drain, the third source connected to the first resistor; and a fourth transistor that comprises a fourth gate, a fourth source, and a fourth drain, the fourth source connected to the second resistor and the fourth gate connected to the third gate. 3. The amplifier of claim 2, wherein the plurality of transistors further includes:
a fifth transistor that comprises a fifth gate, a fifth source, and a fifth drain, the fifth gate connected to the first differential input and the fifth drain connected to ground; a sixth transistor that comprises a sixth gate, a sixth source, and a sixth drain, the sixth gate coupled to the second differential input and the sixth drain connected to ground; a seventh transistor that comprises a seventh gate, a seventh source, and a seventh drain, the seventh source connected to the fifth source; and an eighth transistor that comprises an eighth gate, an eighth source, and an eighth drain, the eighth source connected to the sixth source and the eighth gate connected to the seventh gate. 4. The amplifier of claim 3, wherein the first, second, fifth, and sixth transistors are p-channel metal oxide semiconductor (PMOS) transistors and the third, fourth, seventh, and eighth transistors are n-channel metal oxide semiconductor (NMOS) transistors. 5. The amplifier of claim 1, wherein the output signal is in a single edge nibble transmission (SENT) protocol. 6. The amplifier of claim 1, wherein the input signal is an analog signal received from a pressure sensor and the output signal is a digital signal. 7. A circuit, comprising:
a plurality of resistors; and a plurality of transistors coupled to the plurality of resistors, the plurality of transistors configured to generate a bias current with a magnitude that increases in response to a first transistor of the plurality of transistors receiving a falling edge of an input signal and decreases in response to the first transistor receiving a rising edge of the input signal. 8. The circuit of claim 7, wherein:
the plurality of transistors further includes a second transistor, a third transistor, and a fourth transistor; the first transistor comprises a first gate, a first source, and a first drain, the first gate connected to a first differential input of the input signal, the first drain connected to ground, and the first source connected to a first resistor of the plurality of resistors; the second transistor comprises a second gate, a second source, and a second drain, the second gate coupled to a second differential input of the input signal, the second drain connected to ground, and the second source connected to a second resistor of the plurality of resistors; the third transistor that comprises a third gate, a third source, and a third drain, the third source connected to the first resistor; and the fourth transistor that comprises a fourth gate, a fourth source, and a fourth drain, the fourth source connected to the second resistor and the fourth gate connected to the third gate. 9. The circuit of claim 8, wherein the plurality of transistors further includes:
a fifth transistor that comprises a fifth gate, a fifth source, and a fifth drain, the fifth gate connected to the first differential input and the fifth drain connected to ground; a sixth transistor that comprises a sixth gate, a sixth source, and a sixth drain, the sixth gate coupled to the second differential input and the sixth drain connected to ground; a seventh transistor that comprises a seventh gate, a seventh source, and a seventh drain, the seventh source connected to the fifth source; and an eighth transistor that comprises an eighth gate, an eighth source, and an eighth drain, the eighth source connected to the sixth source and the eighth gate connected to the seventh gate. 10. The circuit of claim 7, wherein the input signal is an analog signal received from a pressure sensor. 11. A method for generating a digital output signal, comprising:
receiving, by a dynamic bias circuit, an input signal from a sensor; generating, by the dynamic bias circuit, a bias current with a magnitude that increases in response to the dynamic bias circuit receiving a falling edge of the input signal and decreases in response to the dynamic bias circuit receiving a rising edge of the input signal; and amplifying, by an amplification circuit, the input signal based on the bias current to generate the digital output signal that has a higher slew rate for a falling signal than for a rising signal. | An amplifier includes a dynamic bias circuit and an amplification circuit coupled to the dynamic bias circuit. The dynamic bias circuit includes a plurality of transistors coupled to a plurality of resistors. The dynamic bias circuit is configured to generate a bias current with a magnitude that increases in response to the dynamic bias circuit receiving a falling edge of an input signal and decreases in response to the dynamic bias circuit receiving a rising edge of the input signal. The amplification circuit is configured to receive the bias current and amplify the input signal based on the bias current to generate an output signal that has a higher slew rate for a falling signal than for a rising signal.1. An amplifier, comprising:
a dynamic bias circuit including a plurality of transistors coupled to a plurality of resistors, the dynamic bias circuit configured to generate a bias current with a magnitude that increases in response to the dynamic bias circuit receiving a falling edge of an input signal and decreases in response to the dynamic bias circuit receiving a rising edge of the input signal; and an amplification circuit coupled to the dynamic bias circuit, the amplification circuit configured to receive the bias current and amplify the input signal based on the bias current to generate an output signal that has a higher slew rate for a falling signal than for a rising signal. 2. The amplifier of claim 1, wherein the plurality of transistors includes:
a first transistor that comprises a first gate, a first source, and a first drain, the first gate connected to a first differential input of the input signal, the first drain connected to ground, and the first source connected to a first resistor; a second transistor that comprises a second gate, a second source, and a second drain, the second gate coupled to a second differential input of the input signal, the second drain connected to ground, and the second source connected to a second resistor; a third transistor that comprises a third gate, a third source, and a third drain, the third source connected to the first resistor; and a fourth transistor that comprises a fourth gate, a fourth source, and a fourth drain, the fourth source connected to the second resistor and the fourth gate connected to the third gate. 3. The amplifier of claim 2, wherein the plurality of transistors further includes:
a fifth transistor that comprises a fifth gate, a fifth source, and a fifth drain, the fifth gate connected to the first differential input and the fifth drain connected to ground; a sixth transistor that comprises a sixth gate, a sixth source, and a sixth drain, the sixth gate coupled to the second differential input and the sixth drain connected to ground; a seventh transistor that comprises a seventh gate, a seventh source, and a seventh drain, the seventh source connected to the fifth source; and an eighth transistor that comprises an eighth gate, an eighth source, and an eighth drain, the eighth source connected to the sixth source and the eighth gate connected to the seventh gate. 4. The amplifier of claim 3, wherein the first, second, fifth, and sixth transistors are p-channel metal oxide semiconductor (PMOS) transistors and the third, fourth, seventh, and eighth transistors are n-channel metal oxide semiconductor (NMOS) transistors. 5. The amplifier of claim 1, wherein the output signal is in a single edge nibble transmission (SENT) protocol. 6. The amplifier of claim 1, wherein the input signal is an analog signal received from a pressure sensor and the output signal is a digital signal. 7. A circuit, comprising:
a plurality of resistors; and a plurality of transistors coupled to the plurality of resistors, the plurality of transistors configured to generate a bias current with a magnitude that increases in response to a first transistor of the plurality of transistors receiving a falling edge of an input signal and decreases in response to the first transistor receiving a rising edge of the input signal. 8. The circuit of claim 7, wherein:
the plurality of transistors further includes a second transistor, a third transistor, and a fourth transistor; the first transistor comprises a first gate, a first source, and a first drain, the first gate connected to a first differential input of the input signal, the first drain connected to ground, and the first source connected to a first resistor of the plurality of resistors; the second transistor comprises a second gate, a second source, and a second drain, the second gate coupled to a second differential input of the input signal, the second drain connected to ground, and the second source connected to a second resistor of the plurality of resistors; the third transistor that comprises a third gate, a third source, and a third drain, the third source connected to the first resistor; and the fourth transistor that comprises a fourth gate, a fourth source, and a fourth drain, the fourth source connected to the second resistor and the fourth gate connected to the third gate. 9. The circuit of claim 8, wherein the plurality of transistors further includes:
a fifth transistor that comprises a fifth gate, a fifth source, and a fifth drain, the fifth gate connected to the first differential input and the fifth drain connected to ground; a sixth transistor that comprises a sixth gate, a sixth source, and a sixth drain, the sixth gate coupled to the second differential input and the sixth drain connected to ground; a seventh transistor that comprises a seventh gate, a seventh source, and a seventh drain, the seventh source connected to the fifth source; and an eighth transistor that comprises an eighth gate, an eighth source, and an eighth drain, the eighth source connected to the sixth source and the eighth gate connected to the seventh gate. 10. The circuit of claim 7, wherein the input signal is an analog signal received from a pressure sensor. 11. A method for generating a digital output signal, comprising:
receiving, by a dynamic bias circuit, an input signal from a sensor; generating, by the dynamic bias circuit, a bias current with a magnitude that increases in response to the dynamic bias circuit receiving a falling edge of the input signal and decreases in response to the dynamic bias circuit receiving a rising edge of the input signal; and amplifying, by an amplification circuit, the input signal based on the bias current to generate the digital output signal that has a higher slew rate for a falling signal than for a rising signal. | 2,100 |
6,542 | 6,542 | 15,150,296 | 2,161 | A data analysis platform provides recommendations for datasets for analysis. Given a user selected dataset, for example resulting from a search,
automatically identifies other datasets based a variety of different types of relationships, including lineage, structural, content, usage, classification, and organizational/social. Datasets for each type of relationship are identified and scored for relevance, and ranked. Selected ones of the ranked data sets are presented in a recommendation interface. As the user selects from recommended dataset, additional datasets are automatically recommended based in inferences made according to the selected dataset and relationship. | 1. A computer executed method of recommending datasets for data analysis, comprising:
receiving a user selection of a first dataset; determining a context corresponding to the user selection of the first dataset; determining, based on the first dataset and determined context, one or more dataset recommenders, each of the one or more recommenders corresponding to a relationship type between datasets; determining a plurality of second datasets related to the first dataset based on the relationship types; scoring each of the plurality of second datasets using a relevance ranking algorithm specific to the corresponding relationship type to score the relevance of the of the second dataset to first dataset; ranking the plurality of second datasets based on the scoring; selecting a subset of the ranked datasets as the recommended datasets; and presenting the recommended datasets in a graphical user interface, wherein the recommended datasets are grouped by relationship type to the first dataset. 2. The computer executed method of claim 1, wherein the relationship types comprise relationship types selected from the group consisting of:
a lineage relationship based on ancestor or descendant relationships between datasets; a content relationship based on semantically similar datasets; a structure relationship based on structurally compatible datasets; a usage based relationships based on datasets previously used by relevant classes of users in association with the previously chosen datasets; a classification-based relationship based on datasets that share one or more classifications with one or more datasets previously chosen by the user; and; an organizational or social relationship based on social or organizational relationships between users of the datasets. 3. The computer executed method of claim 1, further comprising:
in response to receiving a selection of one or more recommended datasets, providing a second level of recommended datasets, comprising:
determining a second context corresponding to the user selection of the one or more recommended datasets;
determining, based on the one or more recommended datasets and determined second context, one or more dataset recommenders;
determining a plurality of third datasets related to the one or more recommended datasets based on the relationship types;
scoring each of the plurality of third datasets using the relevance ranking algorithm;
ranking the plurality of third datasets based on the scoring;
selecting a subset of the ranked third datasets as the second level of recommended datasets; and
presenting the second level of recommended datasets in the graphical user interface, wherein the second level of recommended datasets are grouped by relationship type to the selected dataset. 4. The computer executed method of claim 1, further comprising:
in response to determining the context corresponding to the user selection of the first dataset, inferring a user goal based on the context for the user selection of the first dataset; and presenting the inferred user goal in the a graphical user interface. 5. The computer executed method of claim 4, further comprising:
receiving user input adjusting the inferred user goal presented in the a graphical user interface to a replacement goal;
in response to the adjusting:
determining a revised plurality of datasets related to the first dataset based on the replacement goal;
scoring each of the revised plurality of datasets using a relevance ranking algorithm specific to the corresponding relationship type to score the relevance of the of the second dataset to first dataset;
ranking the revised plurality of datasets based on the scoring;
selecting a revised subset of the ranked datasets as a revised set of recommended datasets; and
replacing the recommended datasets in the graphical user interface with the revised set of recommended datasets. 6. The computer executed method of claim 4, further comprising:
receiving user input adjusting the inferred user goal presented in the graphical user comprising rejection of the presented inferred goal. 7. The computer executed method of claim 4, wherein the inferred user goal is based on a class associated with the determined context and actions associated with the class. 8. The computer executed method of claim 4, wherein the inferred user goal is selected from the group consisting of finding a cleaner dataset, enriching the dataset, and integrating datasets. 9. The computer executed method of claim 1, wherein scoring each of the plurality of second datasets further comprises:
within each relationship type, scoring the second datasets of the relationship type by relevance to the first dataset; and wherein ranking the plurality of second datasets based on the scoring is based on the scoring within each relationship type and a further scoring of the relationship types. 10. The computer executed method of claim 1, further comprising:
generating a preview of contents of a recommended dataset of the presented recommended datasets in the graphical user interface; and in response to user input selecting the recommended dataset, presenting the preview of the recommended dataset to the user in the graphical user interface. 11. A non-transitory computer-readable memory storing a computer program executable by a processor, the computer program producing a user interface displaying dataset recommendations, the user interface comprising:
a dataset selection control for receiving a user selection of a first dataset; a recommendation bar for presenting a set of recommended datasets based on the user selection of the first dataset and a determined context for the selection, wherein the recommended datasets are grouped within the recommendation bar by relationship type to the first dataset; a relationship confirmation control for receiving a selection of one or more of the recommended datasets. 12. The computer program of claim 11, wherein the user interface is further configured by the computer program to:
in response to receiving a selection of one or more of the recommended datasets, presenting a second level of recommended datasets in the graphical user interface, wherein the second level of recommended datasets are grouped by relationship type to the selected dataset. 13. The computer program of claim 11, further comprising:
presenting an inferred user goal in the a graphical user interface, the inferred user goal based on the determined context for the user selection of the first dataset. 14. The computer program of claim 13, further comprising:
in response to receiving user input adjusting the inferred user goal presented in the graphical user interface to a replacement goal, replacing the recommended datasets in the graphical user interface with a revised set of recommended datasets. 15. The computer program of claim 13, further comprising:
in response to receiving user input adjusting the inferred user goal presented in the graphical user interface comprising rejection of the presented inferred goal, replacing the recommended datasets in the graphical user interface with a revised set of recommended datasets. 16. The computer program of claim 11, further comprising:
in response to user input selecting the recommended dataset, presenting a preview of the recommended dataset to the user in the graphical user interface. 17. A computer program product comprising a non-transitory computer readable storage medium having instructions encoded therein that, when executed by a processor, cause the processor to:
receiving a user selection of a first dataset; determining a context corresponding to the user selection of the first dataset; determining, based on the first dataset and determined context, one or more dataset recommenders, each of the one or more recommenders corresponding to a relationship type between datasets; determining a plurality of second datasets related to the first dataset based on the relationship types; scoring each of the plurality of second datasets using a relevance ranking algorithm specific to the corresponding relationship type to score the relevance of the of the second dataset to first dataset; ranking the plurality of second datasets based on the scoring; selecting a subset of the ranked datasets as the recommended datasets; and presenting the recommended datasets in a graphical user interface, wherein the recommended datasets are grouped by relationship type to the first dataset. 18. The computer program product of claim 17, further comprising instructions encoded therein that, when executed by the processor, cause the processor to perform steps comprising:
in response to receiving a selection of one or more recommended datasets, providing a second level of recommended datasets, comprising:
determining a second context corresponding to the user selection of the one or more recommended datasets;
determining, based on the one or more recommended datasets and determined second context, one or more dataset recommenders;
determining a plurality of third datasets related to the one or more recommended datasets based on the relationship types;
scoring each of the plurality of third datasets using the relevance ranking algorithm;
ranking the plurality of third datasets based on the scoring;
selecting a subset of the ranked third datasets as the second level of recommended datasets; and
presenting the second level of recommended datasets in the graphical user interface, wherein the second level of recommended datasets are grouped by relationship type to the selected dataset. 19. The computer program product of claim 17, further comprising instructions encoded therein that, when executed by the processor, cause the processor to perform steps comprising:
in response to determining the context corresponding to the user selection of the first dataset, inferring a user goal based on the context for the user selection of the first dataset; and presenting the inferred user goal in the a graphical user interface. 20. The computer program product of claim 19, further comprising instructions encoded therein that, when executed by the processor, cause the processor to perform steps comprising:
receiving user input adjusting the inferred user goal presented in the a graphical user interface to a replacement goal; in response to the adjusting:
determining a revised plurality of datasets related to the first dataset based on the replacement goal;
scoring each of the revised plurality of datasets using a relevance ranking algorithm specific to the corresponding relationship type to score the relevance of the of the second dataset to first dataset;
ranking the revised plurality of datasets based on the scoring;
selecting a revised subset of the ranked datasets as a revised set of recommended datasets; and
replacing the recommended datasets in the graphical user interface with the revised set of recommended datasets. 21. The computer program product of claim 17, wherein scoring each of the plurality of second datasets further comprises:
within each relationship type, scoring the second datasets of the relationship type by relevance to the first dataset; and wherein ranking the plurality of second datasets based on the scoring is based on the scoring within each relationship type and a further scoring of the relationship types. 22. The computer program product of claim 17, further comprising instructions encoded therein that, when executed by the processor, cause the processor to perform steps comprising:
generating a preview of contents of a recommended dataset of the presented recommended datasets in the graphical user interface; and in response to user input selecting the recommended dataset, presenting the preview of the recommended dataset to the user in the graphical user interface. | A data analysis platform provides recommendations for datasets for analysis. Given a user selected dataset, for example resulting from a search,
automatically identifies other datasets based a variety of different types of relationships, including lineage, structural, content, usage, classification, and organizational/social. Datasets for each type of relationship are identified and scored for relevance, and ranked. Selected ones of the ranked data sets are presented in a recommendation interface. As the user selects from recommended dataset, additional datasets are automatically recommended based in inferences made according to the selected dataset and relationship.1. A computer executed method of recommending datasets for data analysis, comprising:
receiving a user selection of a first dataset; determining a context corresponding to the user selection of the first dataset; determining, based on the first dataset and determined context, one or more dataset recommenders, each of the one or more recommenders corresponding to a relationship type between datasets; determining a plurality of second datasets related to the first dataset based on the relationship types; scoring each of the plurality of second datasets using a relevance ranking algorithm specific to the corresponding relationship type to score the relevance of the of the second dataset to first dataset; ranking the plurality of second datasets based on the scoring; selecting a subset of the ranked datasets as the recommended datasets; and presenting the recommended datasets in a graphical user interface, wherein the recommended datasets are grouped by relationship type to the first dataset. 2. The computer executed method of claim 1, wherein the relationship types comprise relationship types selected from the group consisting of:
a lineage relationship based on ancestor or descendant relationships between datasets; a content relationship based on semantically similar datasets; a structure relationship based on structurally compatible datasets; a usage based relationships based on datasets previously used by relevant classes of users in association with the previously chosen datasets; a classification-based relationship based on datasets that share one or more classifications with one or more datasets previously chosen by the user; and; an organizational or social relationship based on social or organizational relationships between users of the datasets. 3. The computer executed method of claim 1, further comprising:
in response to receiving a selection of one or more recommended datasets, providing a second level of recommended datasets, comprising:
determining a second context corresponding to the user selection of the one or more recommended datasets;
determining, based on the one or more recommended datasets and determined second context, one or more dataset recommenders;
determining a plurality of third datasets related to the one or more recommended datasets based on the relationship types;
scoring each of the plurality of third datasets using the relevance ranking algorithm;
ranking the plurality of third datasets based on the scoring;
selecting a subset of the ranked third datasets as the second level of recommended datasets; and
presenting the second level of recommended datasets in the graphical user interface, wherein the second level of recommended datasets are grouped by relationship type to the selected dataset. 4. The computer executed method of claim 1, further comprising:
in response to determining the context corresponding to the user selection of the first dataset, inferring a user goal based on the context for the user selection of the first dataset; and presenting the inferred user goal in the a graphical user interface. 5. The computer executed method of claim 4, further comprising:
receiving user input adjusting the inferred user goal presented in the a graphical user interface to a replacement goal;
in response to the adjusting:
determining a revised plurality of datasets related to the first dataset based on the replacement goal;
scoring each of the revised plurality of datasets using a relevance ranking algorithm specific to the corresponding relationship type to score the relevance of the of the second dataset to first dataset;
ranking the revised plurality of datasets based on the scoring;
selecting a revised subset of the ranked datasets as a revised set of recommended datasets; and
replacing the recommended datasets in the graphical user interface with the revised set of recommended datasets. 6. The computer executed method of claim 4, further comprising:
receiving user input adjusting the inferred user goal presented in the graphical user comprising rejection of the presented inferred goal. 7. The computer executed method of claim 4, wherein the inferred user goal is based on a class associated with the determined context and actions associated with the class. 8. The computer executed method of claim 4, wherein the inferred user goal is selected from the group consisting of finding a cleaner dataset, enriching the dataset, and integrating datasets. 9. The computer executed method of claim 1, wherein scoring each of the plurality of second datasets further comprises:
within each relationship type, scoring the second datasets of the relationship type by relevance to the first dataset; and wherein ranking the plurality of second datasets based on the scoring is based on the scoring within each relationship type and a further scoring of the relationship types. 10. The computer executed method of claim 1, further comprising:
generating a preview of contents of a recommended dataset of the presented recommended datasets in the graphical user interface; and in response to user input selecting the recommended dataset, presenting the preview of the recommended dataset to the user in the graphical user interface. 11. A non-transitory computer-readable memory storing a computer program executable by a processor, the computer program producing a user interface displaying dataset recommendations, the user interface comprising:
a dataset selection control for receiving a user selection of a first dataset; a recommendation bar for presenting a set of recommended datasets based on the user selection of the first dataset and a determined context for the selection, wherein the recommended datasets are grouped within the recommendation bar by relationship type to the first dataset; a relationship confirmation control for receiving a selection of one or more of the recommended datasets. 12. The computer program of claim 11, wherein the user interface is further configured by the computer program to:
in response to receiving a selection of one or more of the recommended datasets, presenting a second level of recommended datasets in the graphical user interface, wherein the second level of recommended datasets are grouped by relationship type to the selected dataset. 13. The computer program of claim 11, further comprising:
presenting an inferred user goal in the a graphical user interface, the inferred user goal based on the determined context for the user selection of the first dataset. 14. The computer program of claim 13, further comprising:
in response to receiving user input adjusting the inferred user goal presented in the graphical user interface to a replacement goal, replacing the recommended datasets in the graphical user interface with a revised set of recommended datasets. 15. The computer program of claim 13, further comprising:
in response to receiving user input adjusting the inferred user goal presented in the graphical user interface comprising rejection of the presented inferred goal, replacing the recommended datasets in the graphical user interface with a revised set of recommended datasets. 16. The computer program of claim 11, further comprising:
in response to user input selecting the recommended dataset, presenting a preview of the recommended dataset to the user in the graphical user interface. 17. A computer program product comprising a non-transitory computer readable storage medium having instructions encoded therein that, when executed by a processor, cause the processor to:
receiving a user selection of a first dataset; determining a context corresponding to the user selection of the first dataset; determining, based on the first dataset and determined context, one or more dataset recommenders, each of the one or more recommenders corresponding to a relationship type between datasets; determining a plurality of second datasets related to the first dataset based on the relationship types; scoring each of the plurality of second datasets using a relevance ranking algorithm specific to the corresponding relationship type to score the relevance of the of the second dataset to first dataset; ranking the plurality of second datasets based on the scoring; selecting a subset of the ranked datasets as the recommended datasets; and presenting the recommended datasets in a graphical user interface, wherein the recommended datasets are grouped by relationship type to the first dataset. 18. The computer program product of claim 17, further comprising instructions encoded therein that, when executed by the processor, cause the processor to perform steps comprising:
in response to receiving a selection of one or more recommended datasets, providing a second level of recommended datasets, comprising:
determining a second context corresponding to the user selection of the one or more recommended datasets;
determining, based on the one or more recommended datasets and determined second context, one or more dataset recommenders;
determining a plurality of third datasets related to the one or more recommended datasets based on the relationship types;
scoring each of the plurality of third datasets using the relevance ranking algorithm;
ranking the plurality of third datasets based on the scoring;
selecting a subset of the ranked third datasets as the second level of recommended datasets; and
presenting the second level of recommended datasets in the graphical user interface, wherein the second level of recommended datasets are grouped by relationship type to the selected dataset. 19. The computer program product of claim 17, further comprising instructions encoded therein that, when executed by the processor, cause the processor to perform steps comprising:
in response to determining the context corresponding to the user selection of the first dataset, inferring a user goal based on the context for the user selection of the first dataset; and presenting the inferred user goal in the a graphical user interface. 20. The computer program product of claim 19, further comprising instructions encoded therein that, when executed by the processor, cause the processor to perform steps comprising:
receiving user input adjusting the inferred user goal presented in the a graphical user interface to a replacement goal; in response to the adjusting:
determining a revised plurality of datasets related to the first dataset based on the replacement goal;
scoring each of the revised plurality of datasets using a relevance ranking algorithm specific to the corresponding relationship type to score the relevance of the of the second dataset to first dataset;
ranking the revised plurality of datasets based on the scoring;
selecting a revised subset of the ranked datasets as a revised set of recommended datasets; and
replacing the recommended datasets in the graphical user interface with the revised set of recommended datasets. 21. The computer program product of claim 17, wherein scoring each of the plurality of second datasets further comprises:
within each relationship type, scoring the second datasets of the relationship type by relevance to the first dataset; and wherein ranking the plurality of second datasets based on the scoring is based on the scoring within each relationship type and a further scoring of the relationship types. 22. The computer program product of claim 17, further comprising instructions encoded therein that, when executed by the processor, cause the processor to perform steps comprising:
generating a preview of contents of a recommended dataset of the presented recommended datasets in the graphical user interface; and in response to user input selecting the recommended dataset, presenting the preview of the recommended dataset to the user in the graphical user interface. | 2,100 |
6,543 | 6,543 | 15,265,074 | 2,177 | A vehicular human-machine interface, a dashboard and a method of providing information to a driver of a vehicle. The interface includes a multi-information display that provides a driver icons that are representative of a vehicle systems such that the driver can view, and if necessary, control through the interface. Input is simplified through a reduced set of directional buttons on a steering wheel-mounted four-way switch. By eliminating a separate BACK button from the steering wheel, driver input operations to achieve navigational control between various vehicle system menus that correspond to the icons, as well as sub-menus within a particular vehicle system, is simplified. The simplified navigation that is either between various icons on the display or various menu-based levels that can be sequentially shown also permits, in addition to viewing various vehicle system operational parameters, the ability to change such parameters through adjustment through the human-machine interface. | 1. A vehicular human-machine interface comprising:
a multi-information display situated in a position to be viewed by a driver of a vehicle, the display configured to provide visual indicia in the form of icons presented thereon each of which are representative of a corresponding vehicle system that is selectively accessible for at least one of viewing and control by the driver; a steering wheel-mounted switch that comprises a plurality of directional buttons that may be initiated by a tactile input from the driver, the switch not comprising a separate BACK button; and a control unit cooperative with the switch to selectively highlight one of the icons on the display in response to a tactile input from the switch. 2. The interface of claim 1, wherein the switch comprises a four-way switch such that each of the directional buttons corresponds to a respective up, down, left or right instruction movement. 3. The interface of claim 2, wherein a hierarchical change within a particular menu that corresponds to the selectively highlighted one of the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 4. The interface of claim 3, wherein hierarchical ascendancy between particular sub-menus that are grouped within the menu is achieved exclusively through the left directional button. 5. The interface of claim 2, wherein a lateral change between the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 6. The interface of claim 1, wherein a hierarchical change within a particular menu that corresponds to the selectively highlighted one of the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 7. The interface of claim 1, wherein a lateral change between the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 8. A vehicular dashboard comprising:
a steering wheel projecting therefrom, the steering wheel comprising a wheel-mounted switch disposed thereon, the switch comprising a plurality of directional buttons that may be initiated by a tactile input from the driver, the switch not comprising a separate BACK button; at least one instrument cluster disposed adjacent the steering wheel such that the instrument cluster is situated in a position to be viewed by a driver that is situated in front of the steering wheel, the instrument cluster comprising:
at least one gauge configured to provide visual indicia of an operational status of the vehicle; and
a multi-information display situated in a position to be viewed by the driver, the display configured to provide visual indicia in the form of icons presented thereon each of which are representative of a corresponding vehicle system that is selectively accessible for at least one of viewing and control by the driver; and
a control unit cooperative with the switch to selectively highlight one of the icons on the display in response to a tactile input from the switch. 9. The dashboard of claim 8, wherein the display is situated within the instrument cluster that is mounted along the axis of the steering wheel. 10. The dashboard of claim 8, wherein the switch comprises a four-way switch such that each of the directional buttons corresponds to a respective up, down, left or right instruction movement. 11. The dashboard of claim 10, wherein a hierarchical change within a particular menu that corresponds to the selectively highlighted one of the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 12. The dashboard of claim 11, wherein hierarchical ascendancy between particular sub-menus that are grouped within the menu is achieved exclusively through the left directional button. 13. The dashboard of claim 10, wherein a lateral change between the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 14. The dashboard of claim 8, wherein a hierarchical change within a particular menu that corresponds to the selectively highlighted one of the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 15. The dashboard of claim 8, wherein a lateral change between the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 16. A method of providing vehicle system information on a multi-information display, the method comprising:
conveying, on the display, visual indicia in the form of icons each of which are representative of a corresponding vehicle system; disposing a switch on a steering wheel that is used to provide directional control of the vehicle, the switch comprising a plurality of directional buttons, the switch not comprising a separate BACK button; and configuring a control unit to cooperative with the switch and the display such that upon tactile input to the switch, the control unit instructs the display to selectively highlight one of the icons thereon. 17. The method of claim 16, wherein the switch is a four-way switch such that a hierarchical change within a particular menu that corresponds to the selectively highlighted one of the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 18. The method of claim 17, wherein hierarchical ascendancy between particular sub-menus that are grouped within the menu is achieved exclusively through the left directional button. 19. The method of claim 17, wherein a lateral change between the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 20. The method of claim 16, further comprising adjusting at least one operational parameter within the corresponding vehicle system. | A vehicular human-machine interface, a dashboard and a method of providing information to a driver of a vehicle. The interface includes a multi-information display that provides a driver icons that are representative of a vehicle systems such that the driver can view, and if necessary, control through the interface. Input is simplified through a reduced set of directional buttons on a steering wheel-mounted four-way switch. By eliminating a separate BACK button from the steering wheel, driver input operations to achieve navigational control between various vehicle system menus that correspond to the icons, as well as sub-menus within a particular vehicle system, is simplified. The simplified navigation that is either between various icons on the display or various menu-based levels that can be sequentially shown also permits, in addition to viewing various vehicle system operational parameters, the ability to change such parameters through adjustment through the human-machine interface.1. A vehicular human-machine interface comprising:
a multi-information display situated in a position to be viewed by a driver of a vehicle, the display configured to provide visual indicia in the form of icons presented thereon each of which are representative of a corresponding vehicle system that is selectively accessible for at least one of viewing and control by the driver; a steering wheel-mounted switch that comprises a plurality of directional buttons that may be initiated by a tactile input from the driver, the switch not comprising a separate BACK button; and a control unit cooperative with the switch to selectively highlight one of the icons on the display in response to a tactile input from the switch. 2. The interface of claim 1, wherein the switch comprises a four-way switch such that each of the directional buttons corresponds to a respective up, down, left or right instruction movement. 3. The interface of claim 2, wherein a hierarchical change within a particular menu that corresponds to the selectively highlighted one of the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 4. The interface of claim 3, wherein hierarchical ascendancy between particular sub-menus that are grouped within the menu is achieved exclusively through the left directional button. 5. The interface of claim 2, wherein a lateral change between the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 6. The interface of claim 1, wherein a hierarchical change within a particular menu that corresponds to the selectively highlighted one of the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 7. The interface of claim 1, wherein a lateral change between the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 8. A vehicular dashboard comprising:
a steering wheel projecting therefrom, the steering wheel comprising a wheel-mounted switch disposed thereon, the switch comprising a plurality of directional buttons that may be initiated by a tactile input from the driver, the switch not comprising a separate BACK button; at least one instrument cluster disposed adjacent the steering wheel such that the instrument cluster is situated in a position to be viewed by a driver that is situated in front of the steering wheel, the instrument cluster comprising:
at least one gauge configured to provide visual indicia of an operational status of the vehicle; and
a multi-information display situated in a position to be viewed by the driver, the display configured to provide visual indicia in the form of icons presented thereon each of which are representative of a corresponding vehicle system that is selectively accessible for at least one of viewing and control by the driver; and
a control unit cooperative with the switch to selectively highlight one of the icons on the display in response to a tactile input from the switch. 9. The dashboard of claim 8, wherein the display is situated within the instrument cluster that is mounted along the axis of the steering wheel. 10. The dashboard of claim 8, wherein the switch comprises a four-way switch such that each of the directional buttons corresponds to a respective up, down, left or right instruction movement. 11. The dashboard of claim 10, wherein a hierarchical change within a particular menu that corresponds to the selectively highlighted one of the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 12. The dashboard of claim 11, wherein hierarchical ascendancy between particular sub-menus that are grouped within the menu is achieved exclusively through the left directional button. 13. The dashboard of claim 10, wherein a lateral change between the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 14. The dashboard of claim 8, wherein a hierarchical change within a particular menu that corresponds to the selectively highlighted one of the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 15. The dashboard of claim 8, wherein a lateral change between the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 16. A method of providing vehicle system information on a multi-information display, the method comprising:
conveying, on the display, visual indicia in the form of icons each of which are representative of a corresponding vehicle system; disposing a switch on a steering wheel that is used to provide directional control of the vehicle, the switch comprising a plurality of directional buttons, the switch not comprising a separate BACK button; and configuring a control unit to cooperative with the switch and the display such that upon tactile input to the switch, the control unit instructs the display to selectively highlight one of the icons thereon. 17. The method of claim 16, wherein the switch is a four-way switch such that a hierarchical change within a particular menu that corresponds to the selectively highlighted one of the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 18. The method of claim 17, wherein hierarchical ascendancy between particular sub-menus that are grouped within the menu is achieved exclusively through the left directional button. 19. The method of claim 17, wherein a lateral change between the icons is achieved exclusively through the tactile input from one of the plurality of directional buttons. 20. The method of claim 16, further comprising adjusting at least one operational parameter within the corresponding vehicle system. | 2,100 |
6,544 | 6,544 | 14,460,222 | 2,156 | The present invention relates to a system, method and medium for associating portions of advocational documents with portions of tribunal decisions in view of common or similar characteristics that are identified between the associated entities. In addition, the associated advocational document portions are imparted with certain characteristics resulting from such an association, such as inheriting the topic of the associated tribunal decision portion or inheriting general characteristics of the decision such as judge or jurisdiction. This allows for the subsequent retrieval of advocational documents in view of various criteria associated with a decision or portion thereof. | 1. A computer-implemented method for establishing linkages between an advocational document and a decision, wherein the advocational document and decision each include a plurality of portions, and wherein each decision portion is capable of having a pre-determined affiliation with a topic, comprising:
for a selected portion of the advocational document, comparing one or more portions of the decision to generate a plurality of match scores, wherein each match score is affiliated with one of the portions of the decision for which a comparison transpired; determining which of said match scores is a best match score based upon pre-determined criteria; associating the selected portion with the portion of the decision affiliated with the best match score, and assigning to the selected portion the topic affiliated with the portion of the decision connected with generating the best match score, if the best match score is above a pre-determined threshold; and associating a least one attribute to the advocational document,
wherein said at least one attribute is capable of being used to identify the associated advocational document based on attributes of a second decision, where the second decision is not part of a tribunal record of the advocational document. 2. The computer-implemented method of claim 1, wherein the at least one attribute is inherited from the decision affiliated with the best match score to the advocational document. 3. The computer-implemented method of claim 2, wherein the at least one attribute that is inherited is one of judge, jurisdiction, or attorney. 4. The computer-implemented method of claim 1, wherein the at least one attribute is associated with the selected portion of the advocational document. 5. A computer-implemented method for processing a request for retrieving at least one portion of an advocational document based on a selected portion of a decision, wherein the advocational document has one or more portions affiliated with a topic, wherein the advocational document and/or portions thereof is affiliated with an attribute, and wherein the advocational document is one of a plurality of advocational documents, comprising;
receiving (a) a request for at least one portion of the advocational document that is part of the tribunal record of the decision and that is associated, based on best match criteria, with the portion of a decision selected by a requestor, and/or (b) a request for at least one portion of the advocational document based on the at least one attribute, where the at least one advocational document is not part of the tribunal record of the decision and has an assigned topic common with the selected portion of the decision; upon receiving request (a), determining whether the requested at least one portion of the advocational document as associated with the selected portion of the decision exists, and upon verifying the existence of the requested at least one portion, forwarding the at least one portion of the advocational document to the requestor; upon receiving request (b), determining whether the at least one portion of the advocational document based on the at least one attribute and topic exists, and upon verifying the existence of the requested at least one portion, forwarding the advocational document portion to the requestor,
wherein the method is capable of forwarding each of the results of request (a) and (b) to a requestor. 6. The computer-implemented method of claim 5, wherein the at least one attribute comprises at least one of jurisdiction, judge, date range and attorney. 7. The computer-implemented method of claim 5, wherein an indication is received that the requested at least one portion of the advocational document contains at least one of the same attributes as the selected portion of the decision. 8. A system for establishing linkages between an advocational document and a decision, wherein the advocational document and decision each include a plurality of portions, and wherein each decision portion is capable of having a pre-determined affiliation with a topic, comprising:
a linkage server having a hardware processor and a memory; a database containing the advocational document and decision; a best match determiner operating, at least in part, with the linkage server, wherein the best match determiner comprises; a comparer, wherein the comparer compares one or more portions of the decision to generate a plurality of match scores for a selected portion of the advocational document,
wherein each match score is affiliated with one of the portions of the decision for which a comparison transpired;
a score assessor, wherein the score assessor determines which of said match scores is a best match score based upon pre-determined criteria;
a linker, wherein the linker associates the selected portion with the portion of the decision affiliated with the best match score, and assigns to the selected portion the topic affiliated with the portion of the decision connected with generating the best match score, if the best match score is above a pre-determined threshold; and
an attribute associator, wherein the attribute associator associates a least one attribute to the advocational document, wherein said at least one attribute is capable of being used to identify the associated advocational document based on attributes of a second decision, where the second decision is not part of a tribunal record of the advocational document. 9. The system of claim 8, wherein the best match determiner and the attribute associator are part of the same functional entity. 10. The system of claim 8, wherein the at least one attribute is inherited from the decision affiliated with the best match score to the advocational document. 11. The system of claim 10, wherein the at least one attribute that is inherited is one of judge, jurisdiction, or attorney. 12. The system of claim 8, wherein the at least one attribute is associated with the selected portion of the advocational document. 13. The system of claim 8, wherein the linker further comprises linking a headnote in the decision tied to the portion of the decision affiliated with the best match score with the selected portion of the advocational document. 14. The system of claim 13, wherein the linker creates a corresponding headnote in the advocational document, wherein the link to the advocational document is to the headnote of the advocational document, and wherein the headnote of the advocational document is tied to the selected portion of the advocational document. 15. A system for processing a request for retrieving at least one portion of an advocational document based on a selected portion of a decision, wherein the advocational document has one or more portions affiliated with a topic, wherein the advocational document and/or portions thereof is affiliated with an attribute, and wherein the advocational document is one of a plurality of advocational documents, comprising;
an inquiry server having a hardware processor and a memory; a database containing the plurality of advocational documents and decision; a request receiver operating, at least in part, with the inquiry server, wherein the request receiver receives (a) a request for at least one portion of the advocational document that is part of the tribunal record of the decision and that is associated, based on best match criteria, with the portion of a decision selected by a requestor, and/or (b) a request for at least one portion of the advocational document based on the at least one attribute, where the at least one advocational document is not part of the tribunal record of the decision and has an assigned topic common with the selected portion of the decision; a query processor operating, at least in part, with the inquiry server, wherein the query processor: upon receiving request (a), determines, whether the requested at least one portion of the advocational document as associated with the selected portion of the decision exists in the database, and upon verifying the existence of the requested at least one portion, forwarding the at least one portion of the advocational document to the requestor; upon receiving request (b), determines whether the at least one portion of the advocational document based on the at least one attribute and topic exists in the database, and upon verifying the existence of the requested at least one portion, forwarding the advocational document portion to the requestor, wherein the system is capable of forwarding each of the results of request (a) and (b) to a requestor. 16. The system of claim 15, wherein the at least one attribute comprises at least one of jurisdiction, judge, date range and attorney. 17. The system of claim 15, wherein an indication is received that the requested at least one portion of the advocational document contains an least one of the same attributes as the selected portion of the decision. 18. The system of claim 15, wherein the query processor and the request receiver are part of the same functional entity. | The present invention relates to a system, method and medium for associating portions of advocational documents with portions of tribunal decisions in view of common or similar characteristics that are identified between the associated entities. In addition, the associated advocational document portions are imparted with certain characteristics resulting from such an association, such as inheriting the topic of the associated tribunal decision portion or inheriting general characteristics of the decision such as judge or jurisdiction. This allows for the subsequent retrieval of advocational documents in view of various criteria associated with a decision or portion thereof.1. A computer-implemented method for establishing linkages between an advocational document and a decision, wherein the advocational document and decision each include a plurality of portions, and wherein each decision portion is capable of having a pre-determined affiliation with a topic, comprising:
for a selected portion of the advocational document, comparing one or more portions of the decision to generate a plurality of match scores, wherein each match score is affiliated with one of the portions of the decision for which a comparison transpired; determining which of said match scores is a best match score based upon pre-determined criteria; associating the selected portion with the portion of the decision affiliated with the best match score, and assigning to the selected portion the topic affiliated with the portion of the decision connected with generating the best match score, if the best match score is above a pre-determined threshold; and associating a least one attribute to the advocational document,
wherein said at least one attribute is capable of being used to identify the associated advocational document based on attributes of a second decision, where the second decision is not part of a tribunal record of the advocational document. 2. The computer-implemented method of claim 1, wherein the at least one attribute is inherited from the decision affiliated with the best match score to the advocational document. 3. The computer-implemented method of claim 2, wherein the at least one attribute that is inherited is one of judge, jurisdiction, or attorney. 4. The computer-implemented method of claim 1, wherein the at least one attribute is associated with the selected portion of the advocational document. 5. A computer-implemented method for processing a request for retrieving at least one portion of an advocational document based on a selected portion of a decision, wherein the advocational document has one or more portions affiliated with a topic, wherein the advocational document and/or portions thereof is affiliated with an attribute, and wherein the advocational document is one of a plurality of advocational documents, comprising;
receiving (a) a request for at least one portion of the advocational document that is part of the tribunal record of the decision and that is associated, based on best match criteria, with the portion of a decision selected by a requestor, and/or (b) a request for at least one portion of the advocational document based on the at least one attribute, where the at least one advocational document is not part of the tribunal record of the decision and has an assigned topic common with the selected portion of the decision; upon receiving request (a), determining whether the requested at least one portion of the advocational document as associated with the selected portion of the decision exists, and upon verifying the existence of the requested at least one portion, forwarding the at least one portion of the advocational document to the requestor; upon receiving request (b), determining whether the at least one portion of the advocational document based on the at least one attribute and topic exists, and upon verifying the existence of the requested at least one portion, forwarding the advocational document portion to the requestor,
wherein the method is capable of forwarding each of the results of request (a) and (b) to a requestor. 6. The computer-implemented method of claim 5, wherein the at least one attribute comprises at least one of jurisdiction, judge, date range and attorney. 7. The computer-implemented method of claim 5, wherein an indication is received that the requested at least one portion of the advocational document contains at least one of the same attributes as the selected portion of the decision. 8. A system for establishing linkages between an advocational document and a decision, wherein the advocational document and decision each include a plurality of portions, and wherein each decision portion is capable of having a pre-determined affiliation with a topic, comprising:
a linkage server having a hardware processor and a memory; a database containing the advocational document and decision; a best match determiner operating, at least in part, with the linkage server, wherein the best match determiner comprises; a comparer, wherein the comparer compares one or more portions of the decision to generate a plurality of match scores for a selected portion of the advocational document,
wherein each match score is affiliated with one of the portions of the decision for which a comparison transpired;
a score assessor, wherein the score assessor determines which of said match scores is a best match score based upon pre-determined criteria;
a linker, wherein the linker associates the selected portion with the portion of the decision affiliated with the best match score, and assigns to the selected portion the topic affiliated with the portion of the decision connected with generating the best match score, if the best match score is above a pre-determined threshold; and
an attribute associator, wherein the attribute associator associates a least one attribute to the advocational document, wherein said at least one attribute is capable of being used to identify the associated advocational document based on attributes of a second decision, where the second decision is not part of a tribunal record of the advocational document. 9. The system of claim 8, wherein the best match determiner and the attribute associator are part of the same functional entity. 10. The system of claim 8, wherein the at least one attribute is inherited from the decision affiliated with the best match score to the advocational document. 11. The system of claim 10, wherein the at least one attribute that is inherited is one of judge, jurisdiction, or attorney. 12. The system of claim 8, wherein the at least one attribute is associated with the selected portion of the advocational document. 13. The system of claim 8, wherein the linker further comprises linking a headnote in the decision tied to the portion of the decision affiliated with the best match score with the selected portion of the advocational document. 14. The system of claim 13, wherein the linker creates a corresponding headnote in the advocational document, wherein the link to the advocational document is to the headnote of the advocational document, and wherein the headnote of the advocational document is tied to the selected portion of the advocational document. 15. A system for processing a request for retrieving at least one portion of an advocational document based on a selected portion of a decision, wherein the advocational document has one or more portions affiliated with a topic, wherein the advocational document and/or portions thereof is affiliated with an attribute, and wherein the advocational document is one of a plurality of advocational documents, comprising;
an inquiry server having a hardware processor and a memory; a database containing the plurality of advocational documents and decision; a request receiver operating, at least in part, with the inquiry server, wherein the request receiver receives (a) a request for at least one portion of the advocational document that is part of the tribunal record of the decision and that is associated, based on best match criteria, with the portion of a decision selected by a requestor, and/or (b) a request for at least one portion of the advocational document based on the at least one attribute, where the at least one advocational document is not part of the tribunal record of the decision and has an assigned topic common with the selected portion of the decision; a query processor operating, at least in part, with the inquiry server, wherein the query processor: upon receiving request (a), determines, whether the requested at least one portion of the advocational document as associated with the selected portion of the decision exists in the database, and upon verifying the existence of the requested at least one portion, forwarding the at least one portion of the advocational document to the requestor; upon receiving request (b), determines whether the at least one portion of the advocational document based on the at least one attribute and topic exists in the database, and upon verifying the existence of the requested at least one portion, forwarding the advocational document portion to the requestor, wherein the system is capable of forwarding each of the results of request (a) and (b) to a requestor. 16. The system of claim 15, wherein the at least one attribute comprises at least one of jurisdiction, judge, date range and attorney. 17. The system of claim 15, wherein an indication is received that the requested at least one portion of the advocational document contains an least one of the same attributes as the selected portion of the decision. 18. The system of claim 15, wherein the query processor and the request receiver are part of the same functional entity. | 2,100 |
6,545 | 6,545 | 14,205,397 | 2,116 | A virtualizing and obfuscating communications firmware module may be incorporated into common, mass-market portable computing devices, such as smartphones and tablets, to provide this service. The disclosure encompasses authentication and obfuscation software components that may comprise trusted firmware whose operation is protected from the main portable device operating system that is assumed to be hostile (e.g. infiltrated with malware or under the control of a remote attacker). In certain embodiments, a single-chip design is disclosed, without any specialized hardware: only the primary portable device applications microprocessor may be used by both the main operating system and the virtualizing and obfuscating communications firmware module. The operating system may operates as if it has access to a real communications peripheral, but in reality the virtualizing and obfuscating communications firmware module virtualizes this peripheral. The firmware module may perform authentication of the user and obfuscation of the data without the operating system's knowledge. | 1. A portable computing device, comprising:
at least one operating system; at least one virtualized communications device configured to be accessed by the operating system; at least one physical communications device configured not to be directly accessible by the operating system; and at least one virtualizing and obfuscating firmware module configured for executing concurrently with the operating system on a processor. 2. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to manifest the virtualized communications device on behalf of the operating system. 3. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to intercept communications transactions between the at least one virtualized communications device and the at least one physical communications device. 4. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to perform obfuscation services of data as it is transferred between the at least one virtualized communications device and that at least one physical communications device. 5. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to be launched by a secure boot sequence requiring a hardware root of trust. 6. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to be measured by hardware of the portable computing device. 7. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to be measured by immutable firmware. 8. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to be verified to be valid by using one or more measurement parameters. 9. The portable computing device of claim 8, wherein the one or more measurement parameters comprise at least one of a cryptographic key and a certificate within the portable device hardware. 10. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to be verified to be valid prior to executing the virtualizing and obfuscating communications firmware module. 11. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module comprises one or more additional logical threads of execution that can be mapped to one or physical threads or cores. 12. The portable computing device of claim 11, wherein the additional logical threads of execution enable the virtualizing and obfuscating communications firmware module to execute concurrently with other portions of the at least one operating system to improve overall communications latency and system performance. 13. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to control and manage one or more sensors to enforce a policy in which the virtualized communications system is only made available when one or more sensor readings are within an acceptable range of values. 14. The portable computing device of claim 13, wherein one or more sensors comprise at least one Global Positioning Satellite peripheral. 15. The portable computing device of claim 13, wherein the one or more sensor readings obtained by the virtualizing and obfuscating communications firmware module are resistant to corruption by the main operating system. 16. The portable computing device of claim 13, wherein the one or more sensor readings are provided by at least one of a Global Positioning Service, a cellular signal, and another location-based services. 17. A method of information-in-transit protection, comprising:
configuring at least one virtualized communications device to be accessed by an operating system; configuring at least one physical communications device not to be directly accessible by the operating system; and configuring at least one virtualizing and obfuscating firmware module for executing concurrently with the operating system on a processor. 18. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to manifest the virtualized communications device on behalf of the operating system. 19. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to intercept communications transactions between the at least one virtualized communications device and the at least one physical communications device. 20. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to perform obfuscation services of data as it is transferred between the at least one virtualized communications device and the at least one physical communications device. 21. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to be launched by a secure boot sequence requiring a hardware root of trust. 22. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to be measured by hardware of the portable computing device. 23. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to be measured by immutable firmware. 24. The method of claim 17, further comprising verifying the virtualizing and obfuscating communications firmware module to be valid by using one or more measurement parameters. 25. The method of claim 24, wherein the one or more measurement parameters comprise at least one of a cryptographic key and a certificate within the portable device hardware. 26. The method of claim 17, wherein the virtualizing and obfuscating communications firmware module is configured to be verified to be valid prior to executing the virtualizing and obfuscating communications firmware module. 27. The method of claim 17, wherein the virtualizing and obfuscating communications firmware module comprises one or more additional logical threads of execution that can be mapped to one or physical threads or cores. 28. The method of claim 27, further comprising executing the virtualizing and obfuscating communications firmware module concurrently with other portions of the at least one operating system to improve overall communications latency and system performance. 29. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to control and manage one or more sensors to enforce a policy in which the virtualized communications system is only made available when one or more sensor readings are within an acceptable range of values. 30. The method of claim 29, wherein one or more sensors comprise at least one Global Positioning Satellite peripheral. 31. The method of claim 29, wherein the one or more sensor readings obtained by the virtualizing and obfuscating communications firmware module are resistant to corruption by the main operating system. 32. The method of claim 29, wherein the one or more sensor readings are provided by at least one of a Global Positioning Service, a cellular signal, and another location-based services. | A virtualizing and obfuscating communications firmware module may be incorporated into common, mass-market portable computing devices, such as smartphones and tablets, to provide this service. The disclosure encompasses authentication and obfuscation software components that may comprise trusted firmware whose operation is protected from the main portable device operating system that is assumed to be hostile (e.g. infiltrated with malware or under the control of a remote attacker). In certain embodiments, a single-chip design is disclosed, without any specialized hardware: only the primary portable device applications microprocessor may be used by both the main operating system and the virtualizing and obfuscating communications firmware module. The operating system may operates as if it has access to a real communications peripheral, but in reality the virtualizing and obfuscating communications firmware module virtualizes this peripheral. The firmware module may perform authentication of the user and obfuscation of the data without the operating system's knowledge.1. A portable computing device, comprising:
at least one operating system; at least one virtualized communications device configured to be accessed by the operating system; at least one physical communications device configured not to be directly accessible by the operating system; and at least one virtualizing and obfuscating firmware module configured for executing concurrently with the operating system on a processor. 2. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to manifest the virtualized communications device on behalf of the operating system. 3. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to intercept communications transactions between the at least one virtualized communications device and the at least one physical communications device. 4. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to perform obfuscation services of data as it is transferred between the at least one virtualized communications device and that at least one physical communications device. 5. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to be launched by a secure boot sequence requiring a hardware root of trust. 6. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to be measured by hardware of the portable computing device. 7. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to be measured by immutable firmware. 8. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to be verified to be valid by using one or more measurement parameters. 9. The portable computing device of claim 8, wherein the one or more measurement parameters comprise at least one of a cryptographic key and a certificate within the portable device hardware. 10. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to be verified to be valid prior to executing the virtualizing and obfuscating communications firmware module. 11. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module comprises one or more additional logical threads of execution that can be mapped to one or physical threads or cores. 12. The portable computing device of claim 11, wherein the additional logical threads of execution enable the virtualizing and obfuscating communications firmware module to execute concurrently with other portions of the at least one operating system to improve overall communications latency and system performance. 13. The portable computing device of claim 1, wherein the virtualizing and obfuscating communications firmware module is configured to control and manage one or more sensors to enforce a policy in which the virtualized communications system is only made available when one or more sensor readings are within an acceptable range of values. 14. The portable computing device of claim 13, wherein one or more sensors comprise at least one Global Positioning Satellite peripheral. 15. The portable computing device of claim 13, wherein the one or more sensor readings obtained by the virtualizing and obfuscating communications firmware module are resistant to corruption by the main operating system. 16. The portable computing device of claim 13, wherein the one or more sensor readings are provided by at least one of a Global Positioning Service, a cellular signal, and another location-based services. 17. A method of information-in-transit protection, comprising:
configuring at least one virtualized communications device to be accessed by an operating system; configuring at least one physical communications device not to be directly accessible by the operating system; and configuring at least one virtualizing and obfuscating firmware module for executing concurrently with the operating system on a processor. 18. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to manifest the virtualized communications device on behalf of the operating system. 19. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to intercept communications transactions between the at least one virtualized communications device and the at least one physical communications device. 20. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to perform obfuscation services of data as it is transferred between the at least one virtualized communications device and the at least one physical communications device. 21. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to be launched by a secure boot sequence requiring a hardware root of trust. 22. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to be measured by hardware of the portable computing device. 23. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to be measured by immutable firmware. 24. The method of claim 17, further comprising verifying the virtualizing and obfuscating communications firmware module to be valid by using one or more measurement parameters. 25. The method of claim 24, wherein the one or more measurement parameters comprise at least one of a cryptographic key and a certificate within the portable device hardware. 26. The method of claim 17, wherein the virtualizing and obfuscating communications firmware module is configured to be verified to be valid prior to executing the virtualizing and obfuscating communications firmware module. 27. The method of claim 17, wherein the virtualizing and obfuscating communications firmware module comprises one or more additional logical threads of execution that can be mapped to one or physical threads or cores. 28. The method of claim 27, further comprising executing the virtualizing and obfuscating communications firmware module concurrently with other portions of the at least one operating system to improve overall communications latency and system performance. 29. The method of claim 17, further comprising configuring the virtualizing and obfuscating communications firmware module to control and manage one or more sensors to enforce a policy in which the virtualized communications system is only made available when one or more sensor readings are within an acceptable range of values. 30. The method of claim 29, wherein one or more sensors comprise at least one Global Positioning Satellite peripheral. 31. The method of claim 29, wherein the one or more sensor readings obtained by the virtualizing and obfuscating communications firmware module are resistant to corruption by the main operating system. 32. The method of claim 29, wherein the one or more sensor readings are provided by at least one of a Global Positioning Service, a cellular signal, and another location-based services. | 2,100 |
6,546 | 6,546 | 16,791,323 | 2,182 | Methods of memory allocation in which registers referenced by different groups of instances of the same task are mapped to individual logical memories. Other example methods describe the mapping of registers referenced by a task to different banks within a single logical memory and in various examples this mapping may take into consideration which bank is likely to be the dominant bank for the particular task and the allocation for one or more other tasks. | 1. A method of memory allocation in a processing system, the processing system comprising a plurality of logical memories and the method comprising:
creating tasks, each of the tasks comprising a plurality of separate instances, each instance operating on a different data item; grouping instances of one of the tasks into one or more groups; for each of the groups, mapping registers referenced by the group to one of the plurality of logical memories based on a pre-defined allocation scheme adjusted by a current value of a group counter; and adjusting the group counter for each of the tasks. 2. The method according to claim 1, wherein the group counter is adjusted for a task by incrementing the group counter for a previous task by one. 3. The method according to claim 1, wherein the instances of the task are grouped into G groups, where G is an integer, and wherein the group counter is adjusted for a task by incrementing the group counter for a previous task by G. 4. The method according to claim 1, wherein mapping registers referenced by the group to one of the plurality of logical memories based on a pre-defined allocation scheme adjusted by a current value of a group counter comprises:
mapping registers referenced by the group to one of the plurality of logical memories based on a pre-defined sequence of the plurality of logical memories in the processing system, starting at a position in the sequence specified by the current value of the group counter. 5. The method according to claim 1, wherein each of the logical memories comprises a plurality of memory banks, and wherein the method further comprises:
allocating a bank counter value to the task;
and wherein mapping registers referenced by the group to one of the plurality of logical memories based on a pre-defined allocation scheme adjusted by a current value of a group counter further comprises:
mapping registers referenced by the task to memory banks in one of the plurality of logical memories, wherein said one of the plurality of logical memories comprises b banks, wherein b is an integer, and wherein the mapping is based on b and the allocated bank counter value. 6. The method according to claim 5, wherein allocating a bank counter value to the task comprises allocating a current value of the bank counter to the task, wherein the value of the bank counter is adjusted for each of the tasks. 7. The method according to claim 6, wherein the value of the bank counter is adjusted by incrementing the bank counter for a previous task. 8. The method according to claim 6, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
mapping registers referenced by the task to memory banks in said one of the plurality of logical memories according to:
(bank number)=((register number)+(allocated bank counter value)) mod b,
where bank number is an identifier for a memory bank and register number is an identifier for a register. 9. The method according to claim 6, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
calculating a memory address for a register based on a base pointer for the task, a register offset determined from the register number and a bank offset determined from the allocated bank counter value. 10. The method according to claim 6, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
updating a base pointer for the task based on the allocated bank counter value; and calculating a memory address for a register based on the updated base pointer for the task and a register offset determined from the register number. 11. The method according to claim 5, wherein allocating a bank counter value to the task comprises allocating a current value of the bank counter to the task and the method further comprises:
identifying a dominant bank associated with the task and adjusting the bank counter value for allocation to a next task,
and wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
mapping registers in the task to memory banks in said one of the plurality of logical memories based on b, the allocated bank counter value and the dominant bank for the task. 12. The method according to claim 11, wherein adjusting the bank counter value comprises incrementing the bank counter value. 13. The method according to claim 11, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories based on b, the allocated bank counter value and the dominant bank for the task comprises:
mapping registers referenced by the task to memory banks in said one of the plurality of logical memories based on b, the allocated bank counter value and the dominant bank for the task according to:
(bank number)=((register number)+(bank difference)) mod b, and
(bank difference)=(allocated bank counter value)−(dominant bank number)
where bank number is an identifier for a memory bank, dominant bank number is an identifier for the dominant bank of the task and register number is an identifier for a register. 14. The method according to claim 11, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories based on b, the allocated bank counter value and the dominant bank for the task comprises:
calculating a memory address for a register based on a base pointer for the task, a register offset determined from the register number and a bank difference offset determined from the allocated bank counter value and the dominant bank of the task. 15. The method according to claim 11, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories based on b, the allocated bank counter value and the dominant bank for the task comprises:
updating a base pointer for the task based on the allocated bank counter value and the dominant bank for the task; and calculating a memory address for a register based on the updated base pointer for the task and a register offset determined from the register number. 16. The method according to claim 5, wherein the method further comprises:
identifying a dominant bank associated with the task,
and wherein allocating a bank counter value to the task comprises:
allocating a bank counter value to the task based on the dominant bank for the task and a stored dominant bank mask; and
updating the dominant bank mask based on the allocation. 17. The method according to claim 16, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
mapping registers referenced by the task to memory banks in said one of the plurality of logical memories according to:
(bank number)=((register number)+(allocated bank counter value)) mod b,
where bank number is an identifier for a memory bank and register number is an identifier for a register. 18. The method according to claim 16, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
calculating a memory address for a register based on a base pointer for the task, a register offset determined from the register and a bank offset determined from the allocated bank counter value. 19. The method according to claim 16, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
updating a base pointer for the task based on the allocated bank counter value; and calculating a memory address for a register based on the updated base pointer for the task and a register offset determined from the register number. 20. A processing system comprising:
a plurality of logical memories; a group counter; a task creation module configured to create tasks, each of the tasks comprising a plurality of separate instances, each instance operating on a different data item; a scheduler configured to group instances of one of the tasks into one or more groups; and an address generation unit configured, for each of the groups, to map registers referenced by the group to one of the plurality of logical memories based on a pre-defined allocation scheme adjusted by a current value of the group counter;
and wherein either the task creation module or the scheduler is further configured to adjust the group counter for each of the tasks. | Methods of memory allocation in which registers referenced by different groups of instances of the same task are mapped to individual logical memories. Other example methods describe the mapping of registers referenced by a task to different banks within a single logical memory and in various examples this mapping may take into consideration which bank is likely to be the dominant bank for the particular task and the allocation for one or more other tasks.1. A method of memory allocation in a processing system, the processing system comprising a plurality of logical memories and the method comprising:
creating tasks, each of the tasks comprising a plurality of separate instances, each instance operating on a different data item; grouping instances of one of the tasks into one or more groups; for each of the groups, mapping registers referenced by the group to one of the plurality of logical memories based on a pre-defined allocation scheme adjusted by a current value of a group counter; and adjusting the group counter for each of the tasks. 2. The method according to claim 1, wherein the group counter is adjusted for a task by incrementing the group counter for a previous task by one. 3. The method according to claim 1, wherein the instances of the task are grouped into G groups, where G is an integer, and wherein the group counter is adjusted for a task by incrementing the group counter for a previous task by G. 4. The method according to claim 1, wherein mapping registers referenced by the group to one of the plurality of logical memories based on a pre-defined allocation scheme adjusted by a current value of a group counter comprises:
mapping registers referenced by the group to one of the plurality of logical memories based on a pre-defined sequence of the plurality of logical memories in the processing system, starting at a position in the sequence specified by the current value of the group counter. 5. The method according to claim 1, wherein each of the logical memories comprises a plurality of memory banks, and wherein the method further comprises:
allocating a bank counter value to the task;
and wherein mapping registers referenced by the group to one of the plurality of logical memories based on a pre-defined allocation scheme adjusted by a current value of a group counter further comprises:
mapping registers referenced by the task to memory banks in one of the plurality of logical memories, wherein said one of the plurality of logical memories comprises b banks, wherein b is an integer, and wherein the mapping is based on b and the allocated bank counter value. 6. The method according to claim 5, wherein allocating a bank counter value to the task comprises allocating a current value of the bank counter to the task, wherein the value of the bank counter is adjusted for each of the tasks. 7. The method according to claim 6, wherein the value of the bank counter is adjusted by incrementing the bank counter for a previous task. 8. The method according to claim 6, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
mapping registers referenced by the task to memory banks in said one of the plurality of logical memories according to:
(bank number)=((register number)+(allocated bank counter value)) mod b,
where bank number is an identifier for a memory bank and register number is an identifier for a register. 9. The method according to claim 6, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
calculating a memory address for a register based on a base pointer for the task, a register offset determined from the register number and a bank offset determined from the allocated bank counter value. 10. The method according to claim 6, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
updating a base pointer for the task based on the allocated bank counter value; and calculating a memory address for a register based on the updated base pointer for the task and a register offset determined from the register number. 11. The method according to claim 5, wherein allocating a bank counter value to the task comprises allocating a current value of the bank counter to the task and the method further comprises:
identifying a dominant bank associated with the task and adjusting the bank counter value for allocation to a next task,
and wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
mapping registers in the task to memory banks in said one of the plurality of logical memories based on b, the allocated bank counter value and the dominant bank for the task. 12. The method according to claim 11, wherein adjusting the bank counter value comprises incrementing the bank counter value. 13. The method according to claim 11, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories based on b, the allocated bank counter value and the dominant bank for the task comprises:
mapping registers referenced by the task to memory banks in said one of the plurality of logical memories based on b, the allocated bank counter value and the dominant bank for the task according to:
(bank number)=((register number)+(bank difference)) mod b, and
(bank difference)=(allocated bank counter value)−(dominant bank number)
where bank number is an identifier for a memory bank, dominant bank number is an identifier for the dominant bank of the task and register number is an identifier for a register. 14. The method according to claim 11, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories based on b, the allocated bank counter value and the dominant bank for the task comprises:
calculating a memory address for a register based on a base pointer for the task, a register offset determined from the register number and a bank difference offset determined from the allocated bank counter value and the dominant bank of the task. 15. The method according to claim 11, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories based on b, the allocated bank counter value and the dominant bank for the task comprises:
updating a base pointer for the task based on the allocated bank counter value and the dominant bank for the task; and calculating a memory address for a register based on the updated base pointer for the task and a register offset determined from the register number. 16. The method according to claim 5, wherein the method further comprises:
identifying a dominant bank associated with the task,
and wherein allocating a bank counter value to the task comprises:
allocating a bank counter value to the task based on the dominant bank for the task and a stored dominant bank mask; and
updating the dominant bank mask based on the allocation. 17. The method according to claim 16, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
mapping registers referenced by the task to memory banks in said one of the plurality of logical memories according to:
(bank number)=((register number)+(allocated bank counter value)) mod b,
where bank number is an identifier for a memory bank and register number is an identifier for a register. 18. The method according to claim 16, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
calculating a memory address for a register based on a base pointer for the task, a register offset determined from the register and a bank offset determined from the allocated bank counter value. 19. The method according to claim 16, wherein mapping registers referenced by the task to memory banks in one of the plurality of logical memories comprises:
updating a base pointer for the task based on the allocated bank counter value; and calculating a memory address for a register based on the updated base pointer for the task and a register offset determined from the register number. 20. A processing system comprising:
a plurality of logical memories; a group counter; a task creation module configured to create tasks, each of the tasks comprising a plurality of separate instances, each instance operating on a different data item; a scheduler configured to group instances of one of the tasks into one or more groups; and an address generation unit configured, for each of the groups, to map registers referenced by the group to one of the plurality of logical memories based on a pre-defined allocation scheme adjusted by a current value of the group counter;
and wherein either the task creation module or the scheduler is further configured to adjust the group counter for each of the tasks. | 2,100 |
6,547 | 6,547 | 16,192,181 | 2,171 | A method for controlling a display system of a motor vehicle via a controller is provided. An image is generated on a surface of the motor vehicle, and an object placed on the surface is detected. The image is adjusted such that at least a portion of the image is moved from a first area of the surface in which the object has been detected to a second area of the surface. A display system for a motor vehicle configured to perform the method is also provided. | 1. A method for controlling a display system of a motor vehicle, the method comprising:
generating an image on a surface of the motor vehicle via a controller; detecting, via the controller, an object placed on the surface; and adjusting the image, via the controller, such that a portion of the image is moved from a first area of the surface in which the object has been detected to a second area of the surface. 2. The method of claim 1, wherein the portion comprises a first content item of the image intended to be displayed at least partially within the first area; and
wherein the method further comprises: determining via the controller that a further portion of the image has a second content item of the image, and that the second content item is associated with the first content item; and moving, via the controller, the further portion together with the portion of the image. 3. The method of claim 2 further comprising adjusting, via the controller, a size and/or a shape of the further portion according to the second area of the surface. 4. The method of claim 3, wherein a size and/or a shape of the portion and the size and/or the shape of the further portion are adjusted together according to the second area. 5. The method of claim 1, wherein the image is generated via the controller by projecting the image onto the surface of an interior trim portion of the motor vehicle. 6. The method of claim 1, wherein the image is generated onto the surface of an interior trim portion of the motor vehicle via the controller by one or more display elements provided at or below the surface. 7. The method of claim 1, wherein detecting an object placed on the surface further comprises capturing an image of the surface, and identifying a location of the object on the surface within the captured image via the controller. 8. The method of claim 1, wherein detecting an object placed on the surface further comprises receiving measurements via the controller from one or more touch sensors provided at or below the surface. 9. The method of claim 1 further comprising adjusting a shape and/or a size of at least the portion of the image to be moved according to the second area of the surface via the controller. 10. The method of claim 1 further comprising determining via the controller the portion of the image to be moved based on a size and/or a position of the object and a content item within the image. 11. The method of claim 1 further comprising:
determining via the controller a position and/or an orientation of one or more seats for occupants of the motor vehicle, wherein the position and/or the orientation of the seats within an interior of the motor vehicle are variable; and
displaying the image via the controller such that at least a part of the image is in a determined orientation based on the position and/or the orientation of the seats. 12. The method of claim 11 further comprising:
determining via the controller a change in the position and/or the orientation of the seats;
adjusting via the controller the orientation of the image or the part thereof according to the change in the position and/or the orientation of the seats; and
adjusting via the controller the portion of the image moved into the second area according to the position of the object relative to the image following the change in orientation; and
adjusting via the controller the position of the second area and/or the orientation of the portion of the image according to a change in the position and/or the orientation of the seats. 13. The method of claim 1 further comprising determining an orientation of the motor vehicle via the controller; and
displaying via the controller the image such that at least a part of the image is in a determined orientation, wherein the determined orientation is based on a position and/or an orientation of at least part of the image relative to the orientation of the motor vehicle. 14. The method of claim 13 further comprising:
determining via the controller a change in the orientation of the motor vehicle;
adjusting via the controller the orientation of the image or part thereof according to the change in orientation of the motor vehicle;
adjusting via the controller the portion of the image moved into the second area according to the position of the object relative to the image following the change in orientation; and
adjusting via the controller the position of the second area and/or the orientation of the portion of the image according to a change in orientation of the motor vehicle. 15. A display system for a motor vehicle, comprising:
a display device to display an image on a surface of the motor vehicle; an object detector to detect objects placed on the surface; and a controller to control the display device to generate the image on the surface, receive a signal from the object detector indicative of an object placed on the surface, and control the display device to adjust the image such that a portion of the image is moved from a first area of the surface in which the object has been detected to a second area of the surface. 16. The display system of claim 15 wherein the surface is provided on an interior trim portion of the motor vehicle;
wherein the portion the image has a first content item of the image intended to be displayed at least partially within the first area; and
wherein the controller is further configured to control the display device to adjust the image such that a further portion of the image is moved, wherein the further portion of the image has a second content item of the image, and the second content item is associated with the first content item. 17. The display system of claim 15, wherein the display device comprises a projector configured to project the image onto the surface. 18. The display system of claim 15, wherein the display device comprises a plurality of display elements provided at or beneath the surface. 19. The display system of claim 15, wherein the object detector comprises a camera arranged to capture an image of the surface. 20. The display system of claim 15, wherein the object detector comprises one or more touch sensors provided at or below the surface. | A method for controlling a display system of a motor vehicle via a controller is provided. An image is generated on a surface of the motor vehicle, and an object placed on the surface is detected. The image is adjusted such that at least a portion of the image is moved from a first area of the surface in which the object has been detected to a second area of the surface. A display system for a motor vehicle configured to perform the method is also provided.1. A method for controlling a display system of a motor vehicle, the method comprising:
generating an image on a surface of the motor vehicle via a controller; detecting, via the controller, an object placed on the surface; and adjusting the image, via the controller, such that a portion of the image is moved from a first area of the surface in which the object has been detected to a second area of the surface. 2. The method of claim 1, wherein the portion comprises a first content item of the image intended to be displayed at least partially within the first area; and
wherein the method further comprises: determining via the controller that a further portion of the image has a second content item of the image, and that the second content item is associated with the first content item; and moving, via the controller, the further portion together with the portion of the image. 3. The method of claim 2 further comprising adjusting, via the controller, a size and/or a shape of the further portion according to the second area of the surface. 4. The method of claim 3, wherein a size and/or a shape of the portion and the size and/or the shape of the further portion are adjusted together according to the second area. 5. The method of claim 1, wherein the image is generated via the controller by projecting the image onto the surface of an interior trim portion of the motor vehicle. 6. The method of claim 1, wherein the image is generated onto the surface of an interior trim portion of the motor vehicle via the controller by one or more display elements provided at or below the surface. 7. The method of claim 1, wherein detecting an object placed on the surface further comprises capturing an image of the surface, and identifying a location of the object on the surface within the captured image via the controller. 8. The method of claim 1, wherein detecting an object placed on the surface further comprises receiving measurements via the controller from one or more touch sensors provided at or below the surface. 9. The method of claim 1 further comprising adjusting a shape and/or a size of at least the portion of the image to be moved according to the second area of the surface via the controller. 10. The method of claim 1 further comprising determining via the controller the portion of the image to be moved based on a size and/or a position of the object and a content item within the image. 11. The method of claim 1 further comprising:
determining via the controller a position and/or an orientation of one or more seats for occupants of the motor vehicle, wherein the position and/or the orientation of the seats within an interior of the motor vehicle are variable; and
displaying the image via the controller such that at least a part of the image is in a determined orientation based on the position and/or the orientation of the seats. 12. The method of claim 11 further comprising:
determining via the controller a change in the position and/or the orientation of the seats;
adjusting via the controller the orientation of the image or the part thereof according to the change in the position and/or the orientation of the seats; and
adjusting via the controller the portion of the image moved into the second area according to the position of the object relative to the image following the change in orientation; and
adjusting via the controller the position of the second area and/or the orientation of the portion of the image according to a change in the position and/or the orientation of the seats. 13. The method of claim 1 further comprising determining an orientation of the motor vehicle via the controller; and
displaying via the controller the image such that at least a part of the image is in a determined orientation, wherein the determined orientation is based on a position and/or an orientation of at least part of the image relative to the orientation of the motor vehicle. 14. The method of claim 13 further comprising:
determining via the controller a change in the orientation of the motor vehicle;
adjusting via the controller the orientation of the image or part thereof according to the change in orientation of the motor vehicle;
adjusting via the controller the portion of the image moved into the second area according to the position of the object relative to the image following the change in orientation; and
adjusting via the controller the position of the second area and/or the orientation of the portion of the image according to a change in orientation of the motor vehicle. 15. A display system for a motor vehicle, comprising:
a display device to display an image on a surface of the motor vehicle; an object detector to detect objects placed on the surface; and a controller to control the display device to generate the image on the surface, receive a signal from the object detector indicative of an object placed on the surface, and control the display device to adjust the image such that a portion of the image is moved from a first area of the surface in which the object has been detected to a second area of the surface. 16. The display system of claim 15 wherein the surface is provided on an interior trim portion of the motor vehicle;
wherein the portion the image has a first content item of the image intended to be displayed at least partially within the first area; and
wherein the controller is further configured to control the display device to adjust the image such that a further portion of the image is moved, wherein the further portion of the image has a second content item of the image, and the second content item is associated with the first content item. 17. The display system of claim 15, wherein the display device comprises a projector configured to project the image onto the surface. 18. The display system of claim 15, wherein the display device comprises a plurality of display elements provided at or beneath the surface. 19. The display system of claim 15, wherein the object detector comprises a camera arranged to capture an image of the surface. 20. The display system of claim 15, wherein the object detector comprises one or more touch sensors provided at or below the surface. | 2,100 |
6,548 | 6,548 | 14,722,264 | 2,175 | A content management system and method work as a companion to other applications that control the system. The system and method draw information from the operations or structure of the controlling application to display and manage the content objects relevant to a record displayed by a user of the controlling application and stored in the content management system. The system and method operate in conjunction with the controlling application so that this management and display of content objects is dynamic, real-time, and context-sensitive for the user. | 1. A method for displaying a content object to a user of a controlling application comprising:
in response to the user accessing a record in the controlling application, receiving, by a dynamic content engine comprising at least one processor, a notification of the user's access of the record, the notification comprising a primary key and a record type for the record; retrieving one or more display commands for the record based on the record type, each display command specifying one or more data required from the controlling application to display the content object; retrieving, in real-time, the specified one or more data that is associated with the primary key from the controlling application; retrieving one or more related data from the controlling application that is related to the specified one or more data; and populating a user interface with the specified one or more data and the one or more related data for display to the user and for subsequent access by the user of the content object associated with the record in the controlling application, wherein the user interface visually reflects relationships among the records, or the data in the records, in the controlling application and provides access to the content object. 2. The method of claim 1, wherein the content object comprises a document file, an image file, or a video file. 3. The method of claim 1, wherein the content object comprises a folder, wherein the folder comprises a document file, an image file, or a video file. 4. The method of claim 1, further comprising:
in response to the user locating content that does not otherwise exist in the controlling application, instructing the controlling application to create a new record, wherein the instructing further comprises providing a record type to the controlling application, wherein the record type specifies a type of the content; and upon receiving a second primary key for the new record, associating the content with the primary key. 5. The method of claim 1, wherein the user interface visually reflects hierarchical relationships among the records, or the data in the records, in the controlling application. 6. The method of claim 1, wherein the user interface visually reflects direct relationships among the records, or the data in the records, in the controlling application. 7. The method of claim 1, wherein the user interface visually reflects indirect relationships among the records, or the data in the records, in the controlling application. 8. The method of claim 1, further comprising:
in response to the user navigating between a first record reflected in the user interface to a second record in the user interface: receiving, by the dynamic content engine, a notification of the user's access of the second record, the notification comprising a second primary key about the second record; retrieving one or more display commands for the second record based on the second primary key, each display command specifying one or more second data required from the controlling application; retrieving the specified one or more second data from the controlling application; populating a user interface with the specified one or more second data for display to the user. 9. The method of claim 1, further comprising:
in response to a request by the user, instructing the controlling application to export one or more second data for the record; and inducting the one or more second data; and associating the one or more second data with the primary key. 10. A system for displaying a content object to a user of a controlling application comprising:
at least one processor configured to:
in response to the user accessing a record in the controlling application, receive, by a dynamic content engine comprising at least one processor, a notification of the user's access of the record, the notification comprising a primary key and a record type for the record;
retrieve one or more display commands for the record based on the record type, each display command specifying one or more data required from the controlling application to display the content object;
retrieve, in real-time, the specified one or more data that is associated with the primary key from the controlling application;
retrieve one or more related data from the controlling application that is related to the specified one or more data; and
populate a user interface with the specified one or more data and the one or more related data for display to the user and for subsequent access by the user of the content object associated with the record in the controlling application, wherein the user interface visually reflects relationships among the records, or the data in the records, in the controlling application and provides access to the content object. 11. The system of claim 10, wherein the content object comprises a document file, an image file, or a video file. 12. The system of claim 10, wherein the content object comprises a folder, wherein the folder comprises a document file, an image file, or a video file. 13. The system of claim 10, further comprising:
in response to the user locating content that does not otherwise exist in the controlling application, instruct the controlling application to create a new record, wherein the instruct further comprises provide a record type to the controlling application, wherein the record type specifies a type of the content; and upon receiving a second primary key for the new record, associate the content with the primary key. 14. The system of claim 10, wherein the user interface visually reflects hierarchical relationships among the records, or the data in the records, in the controlling application. 15. The system of claim 10, wherein the user interface visually reflects direct relationships among the records, or the data in the records, in the controlling application. 16. The system of claim 10, wherein the user interface visually reflects indirect relationships among the records, or the data in the records, in the controlling application. 17. The system of claim 10, further comprising:
in response to the user navigating between a first record reflected in the user interface to a second record in the user interface: receive, by the dynamic content engine, a notification of the user's access of the second record, the notification comprising a second primary key about the second record; retrieve one or more display commands for the second record based on the second primary key, each display command specifying one or more second data required from the controlling application; retrieve the specified one or more second data from the controlling application; populate a user interface with the specified one or more second data for display to the user. 18. The system of claim 10, further comprising:
in response to a request by the user, instruct the controlling application to export one or more second data for the record; and induct the one or more second data; and associate the one or more second data with the primary key. | A content management system and method work as a companion to other applications that control the system. The system and method draw information from the operations or structure of the controlling application to display and manage the content objects relevant to a record displayed by a user of the controlling application and stored in the content management system. The system and method operate in conjunction with the controlling application so that this management and display of content objects is dynamic, real-time, and context-sensitive for the user.1. A method for displaying a content object to a user of a controlling application comprising:
in response to the user accessing a record in the controlling application, receiving, by a dynamic content engine comprising at least one processor, a notification of the user's access of the record, the notification comprising a primary key and a record type for the record; retrieving one or more display commands for the record based on the record type, each display command specifying one or more data required from the controlling application to display the content object; retrieving, in real-time, the specified one or more data that is associated with the primary key from the controlling application; retrieving one or more related data from the controlling application that is related to the specified one or more data; and populating a user interface with the specified one or more data and the one or more related data for display to the user and for subsequent access by the user of the content object associated with the record in the controlling application, wherein the user interface visually reflects relationships among the records, or the data in the records, in the controlling application and provides access to the content object. 2. The method of claim 1, wherein the content object comprises a document file, an image file, or a video file. 3. The method of claim 1, wherein the content object comprises a folder, wherein the folder comprises a document file, an image file, or a video file. 4. The method of claim 1, further comprising:
in response to the user locating content that does not otherwise exist in the controlling application, instructing the controlling application to create a new record, wherein the instructing further comprises providing a record type to the controlling application, wherein the record type specifies a type of the content; and upon receiving a second primary key for the new record, associating the content with the primary key. 5. The method of claim 1, wherein the user interface visually reflects hierarchical relationships among the records, or the data in the records, in the controlling application. 6. The method of claim 1, wherein the user interface visually reflects direct relationships among the records, or the data in the records, in the controlling application. 7. The method of claim 1, wherein the user interface visually reflects indirect relationships among the records, or the data in the records, in the controlling application. 8. The method of claim 1, further comprising:
in response to the user navigating between a first record reflected in the user interface to a second record in the user interface: receiving, by the dynamic content engine, a notification of the user's access of the second record, the notification comprising a second primary key about the second record; retrieving one or more display commands for the second record based on the second primary key, each display command specifying one or more second data required from the controlling application; retrieving the specified one or more second data from the controlling application; populating a user interface with the specified one or more second data for display to the user. 9. The method of claim 1, further comprising:
in response to a request by the user, instructing the controlling application to export one or more second data for the record; and inducting the one or more second data; and associating the one or more second data with the primary key. 10. A system for displaying a content object to a user of a controlling application comprising:
at least one processor configured to:
in response to the user accessing a record in the controlling application, receive, by a dynamic content engine comprising at least one processor, a notification of the user's access of the record, the notification comprising a primary key and a record type for the record;
retrieve one or more display commands for the record based on the record type, each display command specifying one or more data required from the controlling application to display the content object;
retrieve, in real-time, the specified one or more data that is associated with the primary key from the controlling application;
retrieve one or more related data from the controlling application that is related to the specified one or more data; and
populate a user interface with the specified one or more data and the one or more related data for display to the user and for subsequent access by the user of the content object associated with the record in the controlling application, wherein the user interface visually reflects relationships among the records, or the data in the records, in the controlling application and provides access to the content object. 11. The system of claim 10, wherein the content object comprises a document file, an image file, or a video file. 12. The system of claim 10, wherein the content object comprises a folder, wherein the folder comprises a document file, an image file, or a video file. 13. The system of claim 10, further comprising:
in response to the user locating content that does not otherwise exist in the controlling application, instruct the controlling application to create a new record, wherein the instruct further comprises provide a record type to the controlling application, wherein the record type specifies a type of the content; and upon receiving a second primary key for the new record, associate the content with the primary key. 14. The system of claim 10, wherein the user interface visually reflects hierarchical relationships among the records, or the data in the records, in the controlling application. 15. The system of claim 10, wherein the user interface visually reflects direct relationships among the records, or the data in the records, in the controlling application. 16. The system of claim 10, wherein the user interface visually reflects indirect relationships among the records, or the data in the records, in the controlling application. 17. The system of claim 10, further comprising:
in response to the user navigating between a first record reflected in the user interface to a second record in the user interface: receive, by the dynamic content engine, a notification of the user's access of the second record, the notification comprising a second primary key about the second record; retrieve one or more display commands for the second record based on the second primary key, each display command specifying one or more second data required from the controlling application; retrieve the specified one or more second data from the controlling application; populate a user interface with the specified one or more second data for display to the user. 18. The system of claim 10, further comprising:
in response to a request by the user, instruct the controlling application to export one or more second data for the record; and induct the one or more second data; and associate the one or more second data with the primary key. | 2,100 |
6,549 | 6,549 | 15,334,009 | 2,152 | Examples herein involve detection of entities in unstructured data. Terms are extracted from unstructured data. Entities scores for the terms are calculated using information from a name probability source, a known entity database, and historical context information. The entity scores indicate a probability that the respective terms refer to entities. The presence of detected entities are indicated based on the entity scores. | 1. A method comprising:
extracting terms from a corpus of unstructured data; calculating respective entity scores for the terms using information from a name probability source, a known entity database, and historical context information, the entity scores indicating a probability that the respective terms refer to entities of interest; and indicating the presence of entities of interest detected in the corpus of unstructured data based on the entity score for each of the terms. 2. The method as defined in claim 1, wherein the name probability source indicates a frequency that the terms refer to a name or a frequency that the terms refer to a non-name. 3. The method as defined in claim 1, wherein the known entity database comprises a directory of known entities or an organization structure of known entities. 4. The method as defined in claim 1, wherein the historical context information includes information associated with the unstructured data or information associated with known entities of the known entity database. 5. The method as defined in claim 1, further comprising: for each term extracted from the corpus of unstructured data, assigning the entity score to each term based on a probability that the term is a name using the name probability source, the name probability source indicating a frequency that each term refers to a name or a frequency that each term refers to a non-name. 6. The method as defined in claim 5, further comprising: adjusting the entity score of each term based on the term referring to an entity of a known entity database. 7. The method as defined in claim 6, wherein the term refers to an entity of a known entity database if a portion of the term matches an identifier of the entity in the known entity database. 8. The method as defined in claim 6, further comprising:
determining a term is associated with an entity in the known entity database based on content of the historical context information. 9. The method as defined in claim 8, wherein the term does not match a term for an entity in the known entity database. 10. A non-transitory machine readable storage medium comprising instructions that, when executed, cause a machine to at least:
extract a term from a corpus of unstructured data; calculate an entity score for the term based on a probability calculated from information of a name probability source indicating a probability that a term is a name or non-name, a known entity database of known entities associated with a matter, and historical context information associated with the matter; and indicate the presence of an entity in the corpus of unstructured data based on the entity score for the term. 11. The non-transitory machine readable medium of claim 10, wherein the instructions when executed, further cause the machine to:
indicate the entity is an entity of interest based on the entity score for the term, the entity of interest comprising an entity associated with the matter. 12. The non-transitory machine readable medium of claim 10, wherein the instructions when executed, further cause the machine to:
assign the entity score to the term based on the probability that the term is a name or non-name; adjust the entity score to indicate a probability that the term refers to an entity of interest based on the term being associated with an entity of the known entity database. 13. The non-transitory machine readable medium of claim 12, wherein the instructions when executed, further cause the machine to:
adjust the entity score to indicate a probability that the term refers to an entity of interest when the term is included in the historical context information and is associated with an entity of the known entity database. 14. The non-transitory machine readable medium of claim 10, wherein the entity is not referred to in the known entity database. 15. An apparatus comprising:
a corpus receiver to extract terms from unstructured data; a probability calculator to calculate respective entity scores for the terms based on information from a name probability source, a known entity database, and historical context information; an entity identifier to identify entities in the unstructured data based on the entity scores; and an entity indicator to indicate the presence of the identified entities in the unstructured data. 16. The apparatus of claim 15, wherein the entity identifier is to use a threshold entity score to determine whether a particular term refers to an entity, wherein the entity is not in the known entity database. 17. The apparatus of claim 15, wherein the entity identifier is to use a threshold entity score to determine whether a particular term refers to an entity of interest, the entity of interest comprising an entity associated with a particular matter. 18. The apparatus of claim 17, wherein the entity of interest does is not in the known entity database. 19. The apparatus of claim 15, wherein the entity indicator is to indicate relationship information between entities detected in the unstructured data. 20. The apparatus of claim 15, wherein the name probability source comprises a probability that the terms are a name or non-name, the known entity database comprises known entities associated with a matter, and the historical context information comprises information associated with the matter. | Examples herein involve detection of entities in unstructured data. Terms are extracted from unstructured data. Entities scores for the terms are calculated using information from a name probability source, a known entity database, and historical context information. The entity scores indicate a probability that the respective terms refer to entities. The presence of detected entities are indicated based on the entity scores.1. A method comprising:
extracting terms from a corpus of unstructured data; calculating respective entity scores for the terms using information from a name probability source, a known entity database, and historical context information, the entity scores indicating a probability that the respective terms refer to entities of interest; and indicating the presence of entities of interest detected in the corpus of unstructured data based on the entity score for each of the terms. 2. The method as defined in claim 1, wherein the name probability source indicates a frequency that the terms refer to a name or a frequency that the terms refer to a non-name. 3. The method as defined in claim 1, wherein the known entity database comprises a directory of known entities or an organization structure of known entities. 4. The method as defined in claim 1, wherein the historical context information includes information associated with the unstructured data or information associated with known entities of the known entity database. 5. The method as defined in claim 1, further comprising: for each term extracted from the corpus of unstructured data, assigning the entity score to each term based on a probability that the term is a name using the name probability source, the name probability source indicating a frequency that each term refers to a name or a frequency that each term refers to a non-name. 6. The method as defined in claim 5, further comprising: adjusting the entity score of each term based on the term referring to an entity of a known entity database. 7. The method as defined in claim 6, wherein the term refers to an entity of a known entity database if a portion of the term matches an identifier of the entity in the known entity database. 8. The method as defined in claim 6, further comprising:
determining a term is associated with an entity in the known entity database based on content of the historical context information. 9. The method as defined in claim 8, wherein the term does not match a term for an entity in the known entity database. 10. A non-transitory machine readable storage medium comprising instructions that, when executed, cause a machine to at least:
extract a term from a corpus of unstructured data; calculate an entity score for the term based on a probability calculated from information of a name probability source indicating a probability that a term is a name or non-name, a known entity database of known entities associated with a matter, and historical context information associated with the matter; and indicate the presence of an entity in the corpus of unstructured data based on the entity score for the term. 11. The non-transitory machine readable medium of claim 10, wherein the instructions when executed, further cause the machine to:
indicate the entity is an entity of interest based on the entity score for the term, the entity of interest comprising an entity associated with the matter. 12. The non-transitory machine readable medium of claim 10, wherein the instructions when executed, further cause the machine to:
assign the entity score to the term based on the probability that the term is a name or non-name; adjust the entity score to indicate a probability that the term refers to an entity of interest based on the term being associated with an entity of the known entity database. 13. The non-transitory machine readable medium of claim 12, wherein the instructions when executed, further cause the machine to:
adjust the entity score to indicate a probability that the term refers to an entity of interest when the term is included in the historical context information and is associated with an entity of the known entity database. 14. The non-transitory machine readable medium of claim 10, wherein the entity is not referred to in the known entity database. 15. An apparatus comprising:
a corpus receiver to extract terms from unstructured data; a probability calculator to calculate respective entity scores for the terms based on information from a name probability source, a known entity database, and historical context information; an entity identifier to identify entities in the unstructured data based on the entity scores; and an entity indicator to indicate the presence of the identified entities in the unstructured data. 16. The apparatus of claim 15, wherein the entity identifier is to use a threshold entity score to determine whether a particular term refers to an entity, wherein the entity is not in the known entity database. 17. The apparatus of claim 15, wherein the entity identifier is to use a threshold entity score to determine whether a particular term refers to an entity of interest, the entity of interest comprising an entity associated with a particular matter. 18. The apparatus of claim 17, wherein the entity of interest does is not in the known entity database. 19. The apparatus of claim 15, wherein the entity indicator is to indicate relationship information between entities detected in the unstructured data. 20. The apparatus of claim 15, wherein the name probability source comprises a probability that the terms are a name or non-name, the known entity database comprises known entities associated with a matter, and the historical context information comprises information associated with the matter. | 2,100 |
6,550 | 6,550 | 16,234,666 | 2,166 | A machine-learning driven Database Management System (DBMS) is provided. One or more machine-learning algorithms are trained on the database constructs and execution plans produced by a database optimizer for queries. The trained machine-learning algorithms provide predictors when supplied the constructs and plans for a given query. The predictors are processed by the DBMS to make resource, scheduling, and Service Level Agreement (SLA) compliance decisions with respect to the given query. | 1. A method, comprising:
inputting database constructs generated by a database optimizer as an input to a trained machine-learning algorithm; obtaining a database operation predictor from the machine-learning algorithm as an output; modifying at least one of the database constructs based on the database operation predictor producing a modified database construct; and processing a database operation with the database constructs and the modified database construct. 2. The method of claim 1, wherein inputting further includes inputting the database constructs as query execution plans for a query. 3. The method of claim 2, wherein inputting further includes identifying at least one database construct as a least cost query execution plan identified from the query execution plans by the database optimizer. 4. The method of claim 3, wherein identifying further includes identifying individual pieces of the least cost query execution plan as: a total number of spools used, cardinality for tables with any intermediate results used, a total number of merge joins, a total number of hash joins, nested loop joins, references for the spools, and costs per database resource assigned by the database optimizer. 5. The method of claim 1, wherein obtaining further includes acquiring the database operation predictor as an estimated Central Process Unit (CPU) execution time for one or more Access Module Processors to execute when processing the database operation. 6. The method of claim 1, wherein obtaining further includes acquiring the database operation predictor as an estimated number of Input/Output (I/O) operations performed by one or more Access Module Processors during execution when processing the database operation. 7. The method of claim 1, modifying further includes changing a scheduled execution time for the database operation as the modified database construct. 8. The method of claim 1, wherein modifying further includes changing a scheduled execution time for execution of a query as the modified database construct. 9. The method of claim 1, wherein modifying further includes changing a workgroup assigned to the database operation as the modified database construct. 10. The method of claim 1 further comprising, storing the database operation predictor in database statistics associated with the database operation and the database constructs. 11. The method of claim 10 further comprising, rendering an interface from the database statistics depicting relationships between the database operation, the database operation predictor, the database constructs, and the modified database construct with respect to other instances of the database operation, other database operation predictors, other database constructs, and other modified database constructs. 12. A method comprising:
training a machine-learning algorithm with database constructs produced by a database optimizer; receiving query execution plans for a query from the database optimizer with a least cost query execution plan identified by the database optimizer for the query; providing the query execution plans as input to the machine-learning algorithm; obtaining as an output a predicted execution time for the query based on the least cost query execution plan; and modifying one of: the least cost query execution plan for the query, a scheduled execution time for the query, and resources that are used to execute the query based on the predicted execution time. 13. The method of claim 12 further comprising, notifying a database administrator when based on the predicted execution time a Service Level Goal (SLG) or Service Level Agreement (SLA) associated with the query will be unable to be satisfied using the least cost query execution plan or using a modified version of the least cost query execution plan that was modified based on the predicted execution time. 14. The method of claim 12 further comprising:
providing an interface rendered through a database tool that models the database constructs, the query execution plans, an actual query execution time for the query, and the predicted execution time for the query against other queries having other database constructs, other query execution plans, other actual query execution times for the other queries, and other predicted execution times provided by the machine-learning algorithm for the other queries. 15. The method of claim 15, wherein providing further includes providing the database tool within a workload scheduler and management component of a database system. 16. The method of claim 12, wherein training further includes training the machine-learning algorithm as a linear regression-based machine-learning algorithm. 17. The method of claim 12, wherein modifying further includes selecting a different one of the query execution plans to execute the query instead of the least cost query execution plan based on the predicted execution time and a historical actual execution time known for the different query execution plan. 18. The method of claim 12, wherein modifying further includes changing an execution resource of the least cost query execution plan based on the predicted query execution time and a current performance associated with the execution resource. 19. A system, comprising:
a database management system; at least one hardware processor; a non-transitory computer-readable storage medium having executable instructions representing a trained machine-learning algorithm; the machine learning algorithm configured to execute on the at least one hardware processor from the non-transitory computer-readable storage medium and to perform processing to:
i) receive as input database constructs produced by a database optimizer for a database operation of the database management system; and
ii) provide as output a predicted value relevant to one of: one or more of the database constructs and the database operation;
wherein the database management system is configured to process the predict value to determine whether to modify one of: the one or more database constructs and the database operation before processing the database operation within the database management system. 20. The system of claim 19, wherein the predicted value is an estimated query execution time for a query and the database operation is execution of a query execution plan for the query within the database management system. | A machine-learning driven Database Management System (DBMS) is provided. One or more machine-learning algorithms are trained on the database constructs and execution plans produced by a database optimizer for queries. The trained machine-learning algorithms provide predictors when supplied the constructs and plans for a given query. The predictors are processed by the DBMS to make resource, scheduling, and Service Level Agreement (SLA) compliance decisions with respect to the given query.1. A method, comprising:
inputting database constructs generated by a database optimizer as an input to a trained machine-learning algorithm; obtaining a database operation predictor from the machine-learning algorithm as an output; modifying at least one of the database constructs based on the database operation predictor producing a modified database construct; and processing a database operation with the database constructs and the modified database construct. 2. The method of claim 1, wherein inputting further includes inputting the database constructs as query execution plans for a query. 3. The method of claim 2, wherein inputting further includes identifying at least one database construct as a least cost query execution plan identified from the query execution plans by the database optimizer. 4. The method of claim 3, wherein identifying further includes identifying individual pieces of the least cost query execution plan as: a total number of spools used, cardinality for tables with any intermediate results used, a total number of merge joins, a total number of hash joins, nested loop joins, references for the spools, and costs per database resource assigned by the database optimizer. 5. The method of claim 1, wherein obtaining further includes acquiring the database operation predictor as an estimated Central Process Unit (CPU) execution time for one or more Access Module Processors to execute when processing the database operation. 6. The method of claim 1, wherein obtaining further includes acquiring the database operation predictor as an estimated number of Input/Output (I/O) operations performed by one or more Access Module Processors during execution when processing the database operation. 7. The method of claim 1, modifying further includes changing a scheduled execution time for the database operation as the modified database construct. 8. The method of claim 1, wherein modifying further includes changing a scheduled execution time for execution of a query as the modified database construct. 9. The method of claim 1, wherein modifying further includes changing a workgroup assigned to the database operation as the modified database construct. 10. The method of claim 1 further comprising, storing the database operation predictor in database statistics associated with the database operation and the database constructs. 11. The method of claim 10 further comprising, rendering an interface from the database statistics depicting relationships between the database operation, the database operation predictor, the database constructs, and the modified database construct with respect to other instances of the database operation, other database operation predictors, other database constructs, and other modified database constructs. 12. A method comprising:
training a machine-learning algorithm with database constructs produced by a database optimizer; receiving query execution plans for a query from the database optimizer with a least cost query execution plan identified by the database optimizer for the query; providing the query execution plans as input to the machine-learning algorithm; obtaining as an output a predicted execution time for the query based on the least cost query execution plan; and modifying one of: the least cost query execution plan for the query, a scheduled execution time for the query, and resources that are used to execute the query based on the predicted execution time. 13. The method of claim 12 further comprising, notifying a database administrator when based on the predicted execution time a Service Level Goal (SLG) or Service Level Agreement (SLA) associated with the query will be unable to be satisfied using the least cost query execution plan or using a modified version of the least cost query execution plan that was modified based on the predicted execution time. 14. The method of claim 12 further comprising:
providing an interface rendered through a database tool that models the database constructs, the query execution plans, an actual query execution time for the query, and the predicted execution time for the query against other queries having other database constructs, other query execution plans, other actual query execution times for the other queries, and other predicted execution times provided by the machine-learning algorithm for the other queries. 15. The method of claim 15, wherein providing further includes providing the database tool within a workload scheduler and management component of a database system. 16. The method of claim 12, wherein training further includes training the machine-learning algorithm as a linear regression-based machine-learning algorithm. 17. The method of claim 12, wherein modifying further includes selecting a different one of the query execution plans to execute the query instead of the least cost query execution plan based on the predicted execution time and a historical actual execution time known for the different query execution plan. 18. The method of claim 12, wherein modifying further includes changing an execution resource of the least cost query execution plan based on the predicted query execution time and a current performance associated with the execution resource. 19. A system, comprising:
a database management system; at least one hardware processor; a non-transitory computer-readable storage medium having executable instructions representing a trained machine-learning algorithm; the machine learning algorithm configured to execute on the at least one hardware processor from the non-transitory computer-readable storage medium and to perform processing to:
i) receive as input database constructs produced by a database optimizer for a database operation of the database management system; and
ii) provide as output a predicted value relevant to one of: one or more of the database constructs and the database operation;
wherein the database management system is configured to process the predict value to determine whether to modify one of: the one or more database constructs and the database operation before processing the database operation within the database management system. 20. The system of claim 19, wherein the predicted value is an estimated query execution time for a query and the database operation is execution of a query execution plan for the query within the database management system. | 2,100 |
6,551 | 6,551 | 16,786,218 | 2,121 | A heating system includes a plurality of heater elements, a plurality of switches connected to the plurality of heater elements, a set of predetermined performance information including heater information specific for each heater element, at least one temperature sensor measuring temperature of at least one heater element from among the plurality of heater elements, and a heater control unit in communication with the temperature sensor(s). The heater control unit controls the heater elements differently, via the switches, based on the heater information and the measured temperature from the temperature sensor(s). | 1. A heating system comprising:
a plurality of heater elements; a plurality of switches connected to the plurality of heater elements; a set of predetermined performance information including heater information specific for each heater element; at least one temperature sensor measuring temperature of at least one heater element from among the plurality of heater elements; and a heater control unit in communication with the at least one temperature sensor, wherein the heater control unit controls the plurality of heater elements differently, via the plurality of switches, based on the heater information and the measured temperature from the at least one temperature sensor. 2. The heating system according to claim 1 further comprising at least one support bracket in contact with at least one heater element among the plurality of heater elements. 3. The heating system according to claim 1, wherein the set of predetermined performance information includes sensor information that includes a measurement of temperature conditions at a location adjacent to the at least one heater element. 4. The heating system according to claim 1, wherein the set of predetermined performance information includes switch information, wherein the switch information includes a measurement of current and voltage, rate of heating associated with solid state components of the plurality of switches as a function of an amount of electrical current that is being switched, or a combination thereof. 5. The heating system according to claim 1, wherein the set of predetermined performance information is stored as at least one of written text, a bar code, a data matrix, and a radio frequency identification (RFID) tag. 6. The heating system according to claim 1, wherein the heater information, for each of the plurality of heater elements, includes at least one of a rate of heating at a desired voltage, a rate of heating under a specified flow condition, heater resistance, heater stability, temperature profile, flow uniformity, and temperature conditions in a location adjacent to the plurality of heater elements. 7. The heating system according to claim 1 further comprising a plurality of temperature sensors to measure temperatures of the plurality of heater elements. 8. The heating system according to claim 1, wherein the at least one temperature sensor is a thermocouple, a thermistor, or a resistive temperature device. 9. The heating system according to claim 1 further comprising a signal conditioning module in communication with the at least one temperature sensor and configured to process, at least one of, sensor time response and sensor contact resistance to a sheath of the at least one heater element. 10. The heating system according to claim 9, wherein the signal conditioning module is configured to store the heater information for the plurality of heating elements. 11. The heating system according to claim 1, wherein the plurality of switches are controlled by a switch control unit that is in communication with the heater control unit. 12. The heating system according to claim 1, wherein a resistance of each of the plurality of heating elements varies with temperature. 13. A method of providing thermal control in a system including a plurality of heater elements, the method comprising:
providing a set of predetermined performance information including heater information specific for each of the plurality of heater elements; acquiring temperature from at least one temperature sensor regarding at least one heater element from among the plurality of heater elements; and controlling the plurality of heater elements differently via a plurality of switches based on the heater information and the acquired temperature from the at least one temperature sensor, wherein the plurality of switches are coupled to the plurality of heater elements to control power to the plurality of heater elements. 14. The method according to claim 13 further comprising supporting a heater element from among the plurality of heater elements with a support bracket in contact with the heater element. 15. The method according to claim 13, wherein the set of predetermined performance information includes sensor information that includes a measurement of temperature conditions at a location adjacent to the at least one heater element. 16. The method according to claim 13, wherein the set of predetermined performance information includes switch information, wherein the switch information includes a measurement of current and voltage, rate of heating associated with solid state components of the plurality of switches as a function of an amount of electrical current that is being switched, or a combination thereof. 17. The method according to claim 13, wherein the set of predetermined performance information is stored as at least one of written text, a bar code, a data matrix, and a radio frequency identification (RFID) tag. 18. The method according to claim 13, wherein the heater information, for each of the plurality of heater elements, includes at least one of a rate of heating at a desired voltage, a rate of heating under a specified flow condition, heater resistance, heater stability, temperature profile, flow uniformity, and temperature conditions in a location adjacent to the plurality of heater elements. 19. The method according to claim 13, wherein a resistance of each of the plurality of heating elements varies with temperature. 20. The method according to claim 13 further comprising reducing power to the at least heater element from among the plurality of heater element when the temperature of the at least one heater element is greater than or equal to a predetermined temperature limit, wherein the heater information includes predetermined temperature limit for each of the plurality of heater elements. | A heating system includes a plurality of heater elements, a plurality of switches connected to the plurality of heater elements, a set of predetermined performance information including heater information specific for each heater element, at least one temperature sensor measuring temperature of at least one heater element from among the plurality of heater elements, and a heater control unit in communication with the temperature sensor(s). The heater control unit controls the heater elements differently, via the switches, based on the heater information and the measured temperature from the temperature sensor(s).1. A heating system comprising:
a plurality of heater elements; a plurality of switches connected to the plurality of heater elements; a set of predetermined performance information including heater information specific for each heater element; at least one temperature sensor measuring temperature of at least one heater element from among the plurality of heater elements; and a heater control unit in communication with the at least one temperature sensor, wherein the heater control unit controls the plurality of heater elements differently, via the plurality of switches, based on the heater information and the measured temperature from the at least one temperature sensor. 2. The heating system according to claim 1 further comprising at least one support bracket in contact with at least one heater element among the plurality of heater elements. 3. The heating system according to claim 1, wherein the set of predetermined performance information includes sensor information that includes a measurement of temperature conditions at a location adjacent to the at least one heater element. 4. The heating system according to claim 1, wherein the set of predetermined performance information includes switch information, wherein the switch information includes a measurement of current and voltage, rate of heating associated with solid state components of the plurality of switches as a function of an amount of electrical current that is being switched, or a combination thereof. 5. The heating system according to claim 1, wherein the set of predetermined performance information is stored as at least one of written text, a bar code, a data matrix, and a radio frequency identification (RFID) tag. 6. The heating system according to claim 1, wherein the heater information, for each of the plurality of heater elements, includes at least one of a rate of heating at a desired voltage, a rate of heating under a specified flow condition, heater resistance, heater stability, temperature profile, flow uniformity, and temperature conditions in a location adjacent to the plurality of heater elements. 7. The heating system according to claim 1 further comprising a plurality of temperature sensors to measure temperatures of the plurality of heater elements. 8. The heating system according to claim 1, wherein the at least one temperature sensor is a thermocouple, a thermistor, or a resistive temperature device. 9. The heating system according to claim 1 further comprising a signal conditioning module in communication with the at least one temperature sensor and configured to process, at least one of, sensor time response and sensor contact resistance to a sheath of the at least one heater element. 10. The heating system according to claim 9, wherein the signal conditioning module is configured to store the heater information for the plurality of heating elements. 11. The heating system according to claim 1, wherein the plurality of switches are controlled by a switch control unit that is in communication with the heater control unit. 12. The heating system according to claim 1, wherein a resistance of each of the plurality of heating elements varies with temperature. 13. A method of providing thermal control in a system including a plurality of heater elements, the method comprising:
providing a set of predetermined performance information including heater information specific for each of the plurality of heater elements; acquiring temperature from at least one temperature sensor regarding at least one heater element from among the plurality of heater elements; and controlling the plurality of heater elements differently via a plurality of switches based on the heater information and the acquired temperature from the at least one temperature sensor, wherein the plurality of switches are coupled to the plurality of heater elements to control power to the plurality of heater elements. 14. The method according to claim 13 further comprising supporting a heater element from among the plurality of heater elements with a support bracket in contact with the heater element. 15. The method according to claim 13, wherein the set of predetermined performance information includes sensor information that includes a measurement of temperature conditions at a location adjacent to the at least one heater element. 16. The method according to claim 13, wherein the set of predetermined performance information includes switch information, wherein the switch information includes a measurement of current and voltage, rate of heating associated with solid state components of the plurality of switches as a function of an amount of electrical current that is being switched, or a combination thereof. 17. The method according to claim 13, wherein the set of predetermined performance information is stored as at least one of written text, a bar code, a data matrix, and a radio frequency identification (RFID) tag. 18. The method according to claim 13, wherein the heater information, for each of the plurality of heater elements, includes at least one of a rate of heating at a desired voltage, a rate of heating under a specified flow condition, heater resistance, heater stability, temperature profile, flow uniformity, and temperature conditions in a location adjacent to the plurality of heater elements. 19. The method according to claim 13, wherein a resistance of each of the plurality of heating elements varies with temperature. 20. The method according to claim 13 further comprising reducing power to the at least heater element from among the plurality of heater element when the temperature of the at least one heater element is greater than or equal to a predetermined temperature limit, wherein the heater information includes predetermined temperature limit for each of the plurality of heater elements. | 2,100 |
6,552 | 6,552 | 15,894,980 | 2,196 | Embodiments of the present invention include a method for running a virtual manager scheduler for scheduling activities for virtual machines. The method may include: defining a schedule for one or more activities to be executed for a virtual machine; applying an adjustment to the schedule in accordance with feedback information received via a virtual machine client aggregating the feedback information from a plurality of virtual machine clients, each being related to a virtual machine, per scheduled activity type; and determining of a group adjustment for a determined group of the virtual machine clients based on a function of the feedback information of the plurality of virtual machine clients. | 1. A method for running a virtual manager scheduler for scheduling activities, for virtual machines, the method comprising:
defining an activity schedule for a virtual machine, the activity schedule comprising a timetable defining points in time for scheduled activities to be executed for the virtual machine; applying an adjustment to the activity schedule for at least one of the scheduled activities based on feedback information received from one or more users via one or more virtual machine clients; aggregating the feedback information received from the one or more virtual machine clients based on activity type, wherein each virtual machine client is related to a different virtual machine; and determining a group adjustment for the one or more virtual machine clients based on the feedback information received from the one or more virtual machine clients, wherein determining the group adjustment comprises determining a feedback rank for one of the scheduled activities and an associated period of time for the one scheduled activity. 2. The method of claim 1, wherein the one or more virtual machine clients renders the activity schedule to a user interface, receives the feedback information regarding details of the activity schedule, and sends the feedback information to a virtual machine manager. 3. The method of claim 1, further comprising:
validating active hours of the virtual machine and active days of the virtual machine by the one or more virtual machine clients based on a session status of a virtual machine. 4. The method of claim 1, wherein the feedback information comprises information about declining or postponing a next upcoming activity, a user identifier, an activity identifier, a user identifier specific adjustment to the activity schedule, a textual explanation, or a timestamp. 5. The method of claim 1, wherein the function of the feedback information is based on a threshold value of feedback information or an average of individual adjustments being used for generating the group adjustment. 6. The method of claim 1, wherein the one or more virtual machine clients receive an updated schedule for the scheduled activities. 7. A method comprising:
defining an activity schedule for a virtual machine, the activity schedule comprises a timetable defining points in time for scheduled activities to be executed for the virtual machine; presenting the activity schedule to a user via a virtual machine client associated with the virtual machine; receiving feedback information about the activity schedule from the user via the virtual machine client; adjusting the activity schedule by changing a scheduled time for at least one of the scheduled activities based on the feedback information from the virtual machine client; aggregating the feedback information received from the virtual machine client based on an activity type; and applying a group adjustment to the activity schedule based on the aggregated feedback information, the group adjustment is only applied to scheduled activities of the same activity type. 8. The method of claim 7, further comprising:
validating the scheduled activities; and performing the scheduled activities. 9. The method of claim 7, further comprising:
automatically detecting status information for the virtual machine; and adjusting the activity schedule for the virtual machine based on the status information. 10. The method of claim 7, wherein the feedback information comprises a user identifier, an activity identifier, a user identifier specific adjustment to the schedule, a textual explanation, and a timestamp. 11. The method of claim 7, wherein applying the group adjustment to the activity schedule comprises:
ranking the scheduled activities and an associated period of time based on the aggregated feedback. 12. A method comprising:
defining an activity schedule for each of a plurality of virtual machines, each activity schedule comprising a timetable defining points in time for one or more scheduled activities to be executed for the plurality of virtual machines, the timetable comprises active hours during a day of the virtual machine, active days during a week of the virtual machine, a point in time for a maintenance activity, a point in time for a deletion activity, a point in time for a shut-down activity, a point in time for a snapshot of the virtual machine, a point in time for a backup activity, a point in time for putting the virtual machine in a sleep mode, and a point in time for resuming the virtual machine from the sleep mode; presenting the activity schedules to one or more users via one or more virtual machine clients associated with the plurality of virtual machines; receiving first feedback information about the activity schedules from the one or more users via the one or more virtual machine clients; adjusting each of the activity schedules by changing a scheduled time for at least one of the scheduled activities based on the first feedback information from the virtual machine client; aggregating the first feedback information received from the one or more virtual machine clients based on an activity type; and applying a group adjustment to all of the activity schedules of the plurality of virtual machines based on the aggregated first feedback information, the group adjustment is only applied to scheduled activities of the same activity type. 13. The method of claim 12, further comprising:
presenting the adjusted activity schedules to the one or more users via the one or more virtual machine clients associated with the plurality of virtual machines; and receiving second feedback information about the activity schedules from the one or more users via the one or more virtual machine clients. 14. The method of claim 12, further comprising:
automatically detecting status information for the plurality of virtual machines; and adjusting the activity schedules for the plurality of virtual machines based on the status information. 15. The method of claim 12, wherein both the first feedback information and the second feedback information comprises a user identifier, an activity identifier, a user identifier specific adjustment to the schedule, a textual explanation, and a timestamp. 16. The method of claim 12, wherein applying the group adjustment to all of the activity schedules comprises:
ranking the one or more scheduled activities and an associated period of time based on the aggregated first feedback information. | Embodiments of the present invention include a method for running a virtual manager scheduler for scheduling activities for virtual machines. The method may include: defining a schedule for one or more activities to be executed for a virtual machine; applying an adjustment to the schedule in accordance with feedback information received via a virtual machine client aggregating the feedback information from a plurality of virtual machine clients, each being related to a virtual machine, per scheduled activity type; and determining of a group adjustment for a determined group of the virtual machine clients based on a function of the feedback information of the plurality of virtual machine clients.1. A method for running a virtual manager scheduler for scheduling activities, for virtual machines, the method comprising:
defining an activity schedule for a virtual machine, the activity schedule comprising a timetable defining points in time for scheduled activities to be executed for the virtual machine; applying an adjustment to the activity schedule for at least one of the scheduled activities based on feedback information received from one or more users via one or more virtual machine clients; aggregating the feedback information received from the one or more virtual machine clients based on activity type, wherein each virtual machine client is related to a different virtual machine; and determining a group adjustment for the one or more virtual machine clients based on the feedback information received from the one or more virtual machine clients, wherein determining the group adjustment comprises determining a feedback rank for one of the scheduled activities and an associated period of time for the one scheduled activity. 2. The method of claim 1, wherein the one or more virtual machine clients renders the activity schedule to a user interface, receives the feedback information regarding details of the activity schedule, and sends the feedback information to a virtual machine manager. 3. The method of claim 1, further comprising:
validating active hours of the virtual machine and active days of the virtual machine by the one or more virtual machine clients based on a session status of a virtual machine. 4. The method of claim 1, wherein the feedback information comprises information about declining or postponing a next upcoming activity, a user identifier, an activity identifier, a user identifier specific adjustment to the activity schedule, a textual explanation, or a timestamp. 5. The method of claim 1, wherein the function of the feedback information is based on a threshold value of feedback information or an average of individual adjustments being used for generating the group adjustment. 6. The method of claim 1, wherein the one or more virtual machine clients receive an updated schedule for the scheduled activities. 7. A method comprising:
defining an activity schedule for a virtual machine, the activity schedule comprises a timetable defining points in time for scheduled activities to be executed for the virtual machine; presenting the activity schedule to a user via a virtual machine client associated with the virtual machine; receiving feedback information about the activity schedule from the user via the virtual machine client; adjusting the activity schedule by changing a scheduled time for at least one of the scheduled activities based on the feedback information from the virtual machine client; aggregating the feedback information received from the virtual machine client based on an activity type; and applying a group adjustment to the activity schedule based on the aggregated feedback information, the group adjustment is only applied to scheduled activities of the same activity type. 8. The method of claim 7, further comprising:
validating the scheduled activities; and performing the scheduled activities. 9. The method of claim 7, further comprising:
automatically detecting status information for the virtual machine; and adjusting the activity schedule for the virtual machine based on the status information. 10. The method of claim 7, wherein the feedback information comprises a user identifier, an activity identifier, a user identifier specific adjustment to the schedule, a textual explanation, and a timestamp. 11. The method of claim 7, wherein applying the group adjustment to the activity schedule comprises:
ranking the scheduled activities and an associated period of time based on the aggregated feedback. 12. A method comprising:
defining an activity schedule for each of a plurality of virtual machines, each activity schedule comprising a timetable defining points in time for one or more scheduled activities to be executed for the plurality of virtual machines, the timetable comprises active hours during a day of the virtual machine, active days during a week of the virtual machine, a point in time for a maintenance activity, a point in time for a deletion activity, a point in time for a shut-down activity, a point in time for a snapshot of the virtual machine, a point in time for a backup activity, a point in time for putting the virtual machine in a sleep mode, and a point in time for resuming the virtual machine from the sleep mode; presenting the activity schedules to one or more users via one or more virtual machine clients associated with the plurality of virtual machines; receiving first feedback information about the activity schedules from the one or more users via the one or more virtual machine clients; adjusting each of the activity schedules by changing a scheduled time for at least one of the scheduled activities based on the first feedback information from the virtual machine client; aggregating the first feedback information received from the one or more virtual machine clients based on an activity type; and applying a group adjustment to all of the activity schedules of the plurality of virtual machines based on the aggregated first feedback information, the group adjustment is only applied to scheduled activities of the same activity type. 13. The method of claim 12, further comprising:
presenting the adjusted activity schedules to the one or more users via the one or more virtual machine clients associated with the plurality of virtual machines; and receiving second feedback information about the activity schedules from the one or more users via the one or more virtual machine clients. 14. The method of claim 12, further comprising:
automatically detecting status information for the plurality of virtual machines; and adjusting the activity schedules for the plurality of virtual machines based on the status information. 15. The method of claim 12, wherein both the first feedback information and the second feedback information comprises a user identifier, an activity identifier, a user identifier specific adjustment to the schedule, a textual explanation, and a timestamp. 16. The method of claim 12, wherein applying the group adjustment to all of the activity schedules comprises:
ranking the one or more scheduled activities and an associated period of time based on the aggregated first feedback information. | 2,100 |
6,553 | 6,553 | 15,252,635 | 2,132 | A method for isolating access to shared software resources is disclosed. As part of deployment of an application, an aspect of an execution context for isolating access to a shared variable may be specified. During execution of the application, a current value of the aspect of the execution context may be determined. An access to the shared variable may be detected during execution of the application, and access to the shared variable may be redirected to an isolated copy of the shared variable dependent upon the current value of the aspect of the execution context and the shared variable. | 1. A method, comprising:
specifying, during deployment of an application, an aspect of an execution context for isolating access to a shared variable included in a library referenced by the application; during execution of the application, determining a current value of the aspect of the execution context; detecting an access to the shared variable during execution of the application; and in response to detecting the access, redirecting the access to the shared variable to an isolated copy of the shared variable dependent upon the current value of the aspect of the execution context and the shared variable. 2. The method of claim 1, wherein redirecting the access to the shared variable to the isolated copy includes retrieving a particular entry of a plurality of entries stored in a table. 3. The method of claim 2, wherein the particular entry includes a location in memory for the isolated copy for the shared variable. 4. The method of claim 1, wherein determining the current value of the aspect of the execution context for isolating access to the shared variable includes determining a particular execution thread of a plurality of execution threads. 5. The method of claim 1, wherein determining the current value for the aspect of the execution context for isolating access to the shared variable includes determining an application context from a plurality of application contexts provision on a virtual machine. 6. The method of claim 1, wherein the shared variable includes at least one static variable. 7. A non-transitory computer-accessible storage medium having program instructions stored therein that, in response to execution by a computer system, causes the computer system to perform operations including:
specifying, during deployment of an application, an aspect of an execution context for isolating access to a shared variable included in a library referenced by the application; during execution of the application, determining a current value for the aspect of the execution context; detecting an access to the shared variable during execution of the application; and in response to detecting the access, redirecting the access to the shared variable to an isolated copy of the shared variable dependent upon the current value for the aspect of the execution context and the shared variable. 8. The non-transitory computer-accessible storage medium of claim 7, wherein redirecting the access to the shared variable to the isolated copy includes retrieving a particular entry of a plurality of entries stored in a table. 9. The non-transitory computer-accessible storage medium of claim 8, wherein the particular entry includes a location in memory for the isolated copy for the shared variable. 10. The non-transitory computer-accessible storage medium of claim 7, wherein determining the current value for the aspect of the execution context for isolating access to the shared variable includes determining a particular execution thread of a plurality of execution threads. 11. The non-transitory computer-accessible storage medium of claim 7, wherein determining the current value for the aspect of the execution context for isolating access to the shared variable includes determining an application context from a plurality of application contexts provision on a virtual machine. 12. The non-transitory computer-accessible storage medium of claim 7, wherein determining the current value for the aspect of the execution context for isolating access to the shared variable includes determining a particular processor of a plurality of processors. 13. The non-transitory computer-accessible storage medium of claim 7, wherein the shared variable includes at least one static variable. 14. A system comprising:
one or more memories configured to store instructions, and one or more processors configured to receive instructions from the one or more memories and execute the instructions to cause the system to perform operations comprising:
specifying, during deployment of an application, an aspect of an execution context for isolating access to a shared variable included in a library referenced by the application;
during execution of the application, determining a current value for the aspect of the execution context for the shared variable;
detecting an access to the shared variable during execution of the application; and
in response to detecting the access, redirecting the access to the shared variable to an isolated copy of the shared variable dependent upon the current value for the aspect of the execution context and the shared variable. 15. The system of claim 14, wherein redirecting the access to the shared variable to the isolated copy includes retrieving a particular entry of a plurality of entries stored in a table. 16. The system of claim 15, wherein the particular entry includes a location in memory for the isolated copy for the shared variable. 17. The system of claim 15, wherein the particular entry includes the isolated copy of the shared variable. 18. The system of claim 14, wherein determining the current value for the aspect of the execution context for isolating access to the shared variable includes determining a particular execution thread of a plurality of execution threads. 19. The system of claim 14, wherein determining the current value for the aspect of the execution context for isolating access to the shared variable includes determining an application context from a plurality of application contexts provision on a virtual machine. 20. The system of claim 14, wherein the shared variable includes at least one static variable. | A method for isolating access to shared software resources is disclosed. As part of deployment of an application, an aspect of an execution context for isolating access to a shared variable may be specified. During execution of the application, a current value of the aspect of the execution context may be determined. An access to the shared variable may be detected during execution of the application, and access to the shared variable may be redirected to an isolated copy of the shared variable dependent upon the current value of the aspect of the execution context and the shared variable.1. A method, comprising:
specifying, during deployment of an application, an aspect of an execution context for isolating access to a shared variable included in a library referenced by the application; during execution of the application, determining a current value of the aspect of the execution context; detecting an access to the shared variable during execution of the application; and in response to detecting the access, redirecting the access to the shared variable to an isolated copy of the shared variable dependent upon the current value of the aspect of the execution context and the shared variable. 2. The method of claim 1, wherein redirecting the access to the shared variable to the isolated copy includes retrieving a particular entry of a plurality of entries stored in a table. 3. The method of claim 2, wherein the particular entry includes a location in memory for the isolated copy for the shared variable. 4. The method of claim 1, wherein determining the current value of the aspect of the execution context for isolating access to the shared variable includes determining a particular execution thread of a plurality of execution threads. 5. The method of claim 1, wherein determining the current value for the aspect of the execution context for isolating access to the shared variable includes determining an application context from a plurality of application contexts provision on a virtual machine. 6. The method of claim 1, wherein the shared variable includes at least one static variable. 7. A non-transitory computer-accessible storage medium having program instructions stored therein that, in response to execution by a computer system, causes the computer system to perform operations including:
specifying, during deployment of an application, an aspect of an execution context for isolating access to a shared variable included in a library referenced by the application; during execution of the application, determining a current value for the aspect of the execution context; detecting an access to the shared variable during execution of the application; and in response to detecting the access, redirecting the access to the shared variable to an isolated copy of the shared variable dependent upon the current value for the aspect of the execution context and the shared variable. 8. The non-transitory computer-accessible storage medium of claim 7, wherein redirecting the access to the shared variable to the isolated copy includes retrieving a particular entry of a plurality of entries stored in a table. 9. The non-transitory computer-accessible storage medium of claim 8, wherein the particular entry includes a location in memory for the isolated copy for the shared variable. 10. The non-transitory computer-accessible storage medium of claim 7, wherein determining the current value for the aspect of the execution context for isolating access to the shared variable includes determining a particular execution thread of a plurality of execution threads. 11. The non-transitory computer-accessible storage medium of claim 7, wherein determining the current value for the aspect of the execution context for isolating access to the shared variable includes determining an application context from a plurality of application contexts provision on a virtual machine. 12. The non-transitory computer-accessible storage medium of claim 7, wherein determining the current value for the aspect of the execution context for isolating access to the shared variable includes determining a particular processor of a plurality of processors. 13. The non-transitory computer-accessible storage medium of claim 7, wherein the shared variable includes at least one static variable. 14. A system comprising:
one or more memories configured to store instructions, and one or more processors configured to receive instructions from the one or more memories and execute the instructions to cause the system to perform operations comprising:
specifying, during deployment of an application, an aspect of an execution context for isolating access to a shared variable included in a library referenced by the application;
during execution of the application, determining a current value for the aspect of the execution context for the shared variable;
detecting an access to the shared variable during execution of the application; and
in response to detecting the access, redirecting the access to the shared variable to an isolated copy of the shared variable dependent upon the current value for the aspect of the execution context and the shared variable. 15. The system of claim 14, wherein redirecting the access to the shared variable to the isolated copy includes retrieving a particular entry of a plurality of entries stored in a table. 16. The system of claim 15, wherein the particular entry includes a location in memory for the isolated copy for the shared variable. 17. The system of claim 15, wherein the particular entry includes the isolated copy of the shared variable. 18. The system of claim 14, wherein determining the current value for the aspect of the execution context for isolating access to the shared variable includes determining a particular execution thread of a plurality of execution threads. 19. The system of claim 14, wherein determining the current value for the aspect of the execution context for isolating access to the shared variable includes determining an application context from a plurality of application contexts provision on a virtual machine. 20. The system of claim 14, wherein the shared variable includes at least one static variable. | 2,100 |
6,554 | 6,554 | 15,118,178 | 2,148 | In one embodiment, a kinetic shape is designed by determining an applied force to be applied to an object that is to incorporate the kinetic shape, determining a reactive force that is desired to be produced in response to the applied force, inputting the applied force and the reactive force into a kinetic shape equation, and solving the equation to obtain the kinetic shape. | 1. A method for designing a kinetic shape, the method comprising:
identifying an applied force to be applied to an object that is to incorporate the kinetic shape; identifying a reactive force that is desired to be produced in response to the applied force; inputting the applied force and the reactive force into a kinetic shape equation; and solving the equation to obtain the kinetic shape. 2. The method of claim 1, wherein identifying an applied force comprises identifying a constant force. 3. The method of claim 1, wherein identifying an applied force comprises identifying a variable force that varies as a function of an angle through which the kinetic shape rotates. 4. The method of claim 1, wherein identifying a reactive force comprises identifying a constant force. 5. The method of claim 1, wherein identifying a reactive force comprises identifying a variable force that varies as a function of an angle through which the kinetic shape rotates. 6. The method of claim 1, wherein identifying an applied force comprises determining a force to be applied to the object by a particular system or individual and wherein identifying a reactive force comprises determining a reaction force desirable for the particular system or individual such that the kinetic shape is custom designed for the system or individual. 7. The method of claim 1, wherein the kinetic shape equation defines two-dimensional kinetic shapes and is mathematically defined as:
R
(
θ
)
=
R
(
θ
i
)
exp
[
∫
F
r
(
θ
)
F
v
(
θ
)
d
θ
]
where θ is an angular position around the kinetic shape, R is a radius of the kinetic shape, Fv is the applied force, Fr is the reactive force, and θi is an initial angle of the kinetic shape. 8. The method of claim 1, wherein the kinetic shape equation defines three-dimensional kinetic shapes and is mathematically defined as:
R
r
(
θ
,
φ
)
=
R
r
(
θ
i
,
φ
i
)
exp
[
∫
F
r
(
θ
,
φ
)
F
v
(
θ
,
φ
)
d
θ
]
R
r
(
θ
,
φ
)
=
R
t
(
θ
i
,
φ
i
)
exp
[
∫
F
t
(
θ
,
φ
)
F
r
(
θ
,
φ
)
d
φ
]
where θ is an elevation angle around the kinetic shape, φ is an azimuth angle around the kinetic shape, Rr is a shape radius in the radial direction, Rt is a shape radius in the tangential direction, Fv is the applied force, Fr is a radial ground reaction force, Ft is a tangential ground reaction force, and θi and φi are the initial elevation and azimuth angles, respectively. 9. A non-transitory computer-readable medium that stores a kinetic shape derivation module, the module comprising:
logic configured to identify an applied force to be applied to an object that is to incorporate the kinetic shape; logic configured to identify a reactive force that is desired to be produced in response to the applied force; logic configured to input the applied force and the reactive force into a kinetic shape equation; and logic configured to solve the equation to obtain the kinetic shape. 10. The computer-readable medium of claim 9, wherein the kinetic shape equation defines two-dimensional kinetic shapes and is mathematically defined as:
R
(
θ
)
=
R
(
θ
i
)
exp
[
∫
F
r
(
θ
)
F
v
(
θ
)
d
θ
]
where θ is an angular position around the kinetic shape, R is a radius of the kinetic shape, Fv is the applied force, Fr is the reactive force, and θi is an initial angle of the kinetic shape. 11. The computer-readable medium of claim 9, wherein the kinetic shape equation defines three-dimensional kinetic shapes and is mathematically defined as:
R
r
(
θ
,
φ
)
=
R
r
(
θ
i
,
φ
i
)
exp
[
∫
F
r
(
θ
,
φ
)
F
v
(
θ
,
φ
)
d
θ
]
R
r
(
θ
,
φ
)
=
R
t
(
θ
i
,
φ
i
)
exp
[
∫
F
t
(
θ
,
φ
)
F
r
(
θ
,
φ
)
d
φ
]
where θ is an elevation angle around the kinetic shape, φ is an azimuth angle around the kinetic shape, Rr is a shape radius in the radial direction, Rt is a shape radius in the tangential direction, Fv is the applied force, Fr is a radial ground reaction force, Ft is a tangential ground reaction force, and θi and φi are the initial elevation and azimuth angles, respectively. 12. A physical object that incorporates a kinetic shape, the object designed using a process comprising:
identifying an applied force to be applied to the object; identifying a reactive force that is desired to be produced in response to the applied force; inputting the applied force and the reactive force into a kinetic shape equation; and solving the equation to obtain the kinetic shape. 13. The object of claim 12, wherein identifying an applied force comprises determining a force to be applied to the object by a particular system or individual and wherein identifying a reactive force comprises determining a reaction force desirable for the particular system or individual such that the kinetic shape is custom designed for the system or individual. 14. The object of claim 12, wherein the kinetic shape equation defines two-dimensional kinetic shapes and is mathematically defined as:
R
(
θ
)
=
R
(
θ
i
)
exp
[
∫
F
r
(
θ
)
F
v
(
θ
)
d
θ
]
where θ is an angular position around the kinetic shape, R is a radius of the kinetic shape, Fv is the applied force, Fr is the reactive force, and θi is an initial angle of the kinetic shape. 15. The object of claim 12, wherein the kinetic shape equation defines three-dimensional kinetic shapes and is mathematically defined as:
R
r
(
θ
,
φ
)
=
R
r
(
θ
i
,
φ
i
)
exp
[
∫
F
r
(
θ
,
φ
)
F
v
(
θ
,
φ
)
d
θ
]
R
r
(
θ
,
φ
)
=
R
t
(
θ
i
,
φ
i
)
exp
[
∫
F
t
(
θ
,
φ
)
F
r
(
θ
,
φ
)
d
φ
]
where θ is an elevation angle around the kinetic shape, φ is an azimuth angle around the kinetic shape, Rr is a shape radius in the radial direction, Rt is a shape radius in the tangential direction, Fv is the applied force, Fr is a radial ground reaction force, Ft is a tangential ground reaction force, and θi and φi are the initial elevation and azimuth angles, respectively. 16. The object of claim 12, wherein the object is a gait enhancing mobile shoe that includes wheels incorporating the kinetic shape. 17. The object of claim 12, wherein the object is a walking crutch or cane that includes a tip that incorporates the kinetic shape. 18. The object of claim 12, wherein the object is a prosthetic device that includes a sole that incorporates the kinetic shape. 19. The object of claim 12, wherein the object is a rocking board that includes an elongated platform having a kinetic shape element at each end that incorporates the kinetic shape. 20. The object of claim 12, wherein the kinetic shape is a curve having a non-constant radius. 21. The method of claim 1, further comprising constructing a physical object that incorporates the kinetic shape. | In one embodiment, a kinetic shape is designed by determining an applied force to be applied to an object that is to incorporate the kinetic shape, determining a reactive force that is desired to be produced in response to the applied force, inputting the applied force and the reactive force into a kinetic shape equation, and solving the equation to obtain the kinetic shape.1. A method for designing a kinetic shape, the method comprising:
identifying an applied force to be applied to an object that is to incorporate the kinetic shape; identifying a reactive force that is desired to be produced in response to the applied force; inputting the applied force and the reactive force into a kinetic shape equation; and solving the equation to obtain the kinetic shape. 2. The method of claim 1, wherein identifying an applied force comprises identifying a constant force. 3. The method of claim 1, wherein identifying an applied force comprises identifying a variable force that varies as a function of an angle through which the kinetic shape rotates. 4. The method of claim 1, wherein identifying a reactive force comprises identifying a constant force. 5. The method of claim 1, wherein identifying a reactive force comprises identifying a variable force that varies as a function of an angle through which the kinetic shape rotates. 6. The method of claim 1, wherein identifying an applied force comprises determining a force to be applied to the object by a particular system or individual and wherein identifying a reactive force comprises determining a reaction force desirable for the particular system or individual such that the kinetic shape is custom designed for the system or individual. 7. The method of claim 1, wherein the kinetic shape equation defines two-dimensional kinetic shapes and is mathematically defined as:
R
(
θ
)
=
R
(
θ
i
)
exp
[
∫
F
r
(
θ
)
F
v
(
θ
)
d
θ
]
where θ is an angular position around the kinetic shape, R is a radius of the kinetic shape, Fv is the applied force, Fr is the reactive force, and θi is an initial angle of the kinetic shape. 8. The method of claim 1, wherein the kinetic shape equation defines three-dimensional kinetic shapes and is mathematically defined as:
R
r
(
θ
,
φ
)
=
R
r
(
θ
i
,
φ
i
)
exp
[
∫
F
r
(
θ
,
φ
)
F
v
(
θ
,
φ
)
d
θ
]
R
r
(
θ
,
φ
)
=
R
t
(
θ
i
,
φ
i
)
exp
[
∫
F
t
(
θ
,
φ
)
F
r
(
θ
,
φ
)
d
φ
]
where θ is an elevation angle around the kinetic shape, φ is an azimuth angle around the kinetic shape, Rr is a shape radius in the radial direction, Rt is a shape radius in the tangential direction, Fv is the applied force, Fr is a radial ground reaction force, Ft is a tangential ground reaction force, and θi and φi are the initial elevation and azimuth angles, respectively. 9. A non-transitory computer-readable medium that stores a kinetic shape derivation module, the module comprising:
logic configured to identify an applied force to be applied to an object that is to incorporate the kinetic shape; logic configured to identify a reactive force that is desired to be produced in response to the applied force; logic configured to input the applied force and the reactive force into a kinetic shape equation; and logic configured to solve the equation to obtain the kinetic shape. 10. The computer-readable medium of claim 9, wherein the kinetic shape equation defines two-dimensional kinetic shapes and is mathematically defined as:
R
(
θ
)
=
R
(
θ
i
)
exp
[
∫
F
r
(
θ
)
F
v
(
θ
)
d
θ
]
where θ is an angular position around the kinetic shape, R is a radius of the kinetic shape, Fv is the applied force, Fr is the reactive force, and θi is an initial angle of the kinetic shape. 11. The computer-readable medium of claim 9, wherein the kinetic shape equation defines three-dimensional kinetic shapes and is mathematically defined as:
R
r
(
θ
,
φ
)
=
R
r
(
θ
i
,
φ
i
)
exp
[
∫
F
r
(
θ
,
φ
)
F
v
(
θ
,
φ
)
d
θ
]
R
r
(
θ
,
φ
)
=
R
t
(
θ
i
,
φ
i
)
exp
[
∫
F
t
(
θ
,
φ
)
F
r
(
θ
,
φ
)
d
φ
]
where θ is an elevation angle around the kinetic shape, φ is an azimuth angle around the kinetic shape, Rr is a shape radius in the radial direction, Rt is a shape radius in the tangential direction, Fv is the applied force, Fr is a radial ground reaction force, Ft is a tangential ground reaction force, and θi and φi are the initial elevation and azimuth angles, respectively. 12. A physical object that incorporates a kinetic shape, the object designed using a process comprising:
identifying an applied force to be applied to the object; identifying a reactive force that is desired to be produced in response to the applied force; inputting the applied force and the reactive force into a kinetic shape equation; and solving the equation to obtain the kinetic shape. 13. The object of claim 12, wherein identifying an applied force comprises determining a force to be applied to the object by a particular system or individual and wherein identifying a reactive force comprises determining a reaction force desirable for the particular system or individual such that the kinetic shape is custom designed for the system or individual. 14. The object of claim 12, wherein the kinetic shape equation defines two-dimensional kinetic shapes and is mathematically defined as:
R
(
θ
)
=
R
(
θ
i
)
exp
[
∫
F
r
(
θ
)
F
v
(
θ
)
d
θ
]
where θ is an angular position around the kinetic shape, R is a radius of the kinetic shape, Fv is the applied force, Fr is the reactive force, and θi is an initial angle of the kinetic shape. 15. The object of claim 12, wherein the kinetic shape equation defines three-dimensional kinetic shapes and is mathematically defined as:
R
r
(
θ
,
φ
)
=
R
r
(
θ
i
,
φ
i
)
exp
[
∫
F
r
(
θ
,
φ
)
F
v
(
θ
,
φ
)
d
θ
]
R
r
(
θ
,
φ
)
=
R
t
(
θ
i
,
φ
i
)
exp
[
∫
F
t
(
θ
,
φ
)
F
r
(
θ
,
φ
)
d
φ
]
where θ is an elevation angle around the kinetic shape, φ is an azimuth angle around the kinetic shape, Rr is a shape radius in the radial direction, Rt is a shape radius in the tangential direction, Fv is the applied force, Fr is a radial ground reaction force, Ft is a tangential ground reaction force, and θi and φi are the initial elevation and azimuth angles, respectively. 16. The object of claim 12, wherein the object is a gait enhancing mobile shoe that includes wheels incorporating the kinetic shape. 17. The object of claim 12, wherein the object is a walking crutch or cane that includes a tip that incorporates the kinetic shape. 18. The object of claim 12, wherein the object is a prosthetic device that includes a sole that incorporates the kinetic shape. 19. The object of claim 12, wherein the object is a rocking board that includes an elongated platform having a kinetic shape element at each end that incorporates the kinetic shape. 20. The object of claim 12, wherein the kinetic shape is a curve having a non-constant radius. 21. The method of claim 1, further comprising constructing a physical object that incorporates the kinetic shape. | 2,100 |
6,555 | 6,555 | 15,978,110 | 2,173 | A device displays a first selectable user interface (UI) element associated with a first touch activation region. The device detects a change of movement of the display. In response to the change of movement, the device adjusts the first touch activation region to encompass a new area. The new area is at least partially different from the first touch activation region prior to the change of movement and is based on the change of the movement. After detecting the change of movement, the device detects a touch input. In accordance with a determination that the touch input is detected within the adjusted first touch activation region, the device performs a user interface operation associated with the first selectable UI element. In accordance with a determination that the touch input is detected outside the adjusted first touch activation region, the device forgoes performance of the user interface operation. | 1. A method comprising:
at a device with a non-transitory memory, and one or more processors in communication with a touch-sensitive display:
displaying one or more selectable user interface elements on the touch-sensitive display that are associated with corresponding touch activation regions, wherein the one or more selectable user interface elements include a first selectable user interface element that is associated with a first touch activation region;
detecting a change of movement of the touch-sensitive display that has an associated respective direction;
in response to detecting the change of movement of the touch-sensitive display:
adjusting the first touch activation region to encompass a new area of the touch-sensitive display that is at least partially different from the first touch activation region prior to detecting the change of movement, and the new area is based on the change of movement of the touch-sensitive display;
after detecting the change of movement of the touch-sensitive display, detecting a touch input on the touch-sensitive display; and
in response to detecting the touch input on the touch-sensitive display:
in accordance with a determination that the touch input is detected within the adjusted first touch activation region, performing a user interface operation that is associated with the first selectable user interface element; and
in accordance with a determination that the touch input is detected outside of the adjusted first touch activation region, forgoing performance of the user interface operation that is associated with the first selectable user interface element. 2. The method of claim 1, wherein adjusting the first touch activation region includes changing a size of the first touch activation region. 3. The method of claim 1, wherein adjusting the first touch activation region includes changing a shape of the first touch activation region. 4. The method of claim 1, wherein adjusting the first touch activation region includes: determining a degree of adjustment for the first touch activation region based on a size of the first selectable user interface element. 5. The method of claim 1, wherein adjusting the first touch activation region includes maintaining a visual representation of the first selectable user interface element. 6. The method of claim 1, wherein detecting the change in movement includes receiving sensor measurements from one or more sensors. 7. The method of claim 1, wherein adjusting the first touch activation region includes determining an adjustment to the first touch activation region based on a length of an arm. 8. The method of claim 7, wherein adjusting the first touch activation region includes determining an estimated value that corresponds to the length of the arm based on one or more of information stored in the non-transitory memory, and information received from one or more sensors. 9. The method of claim 1, wherein detecting the touch input comprises:
detecting a plurality of touch inputs on the touch-sensitive display; determining a primary touch input of the plurality of touch inputs based on the change of movement of the touch-sensitive display; and discarding the remainder of the touch inputs after determining the primary touch input. 10. The method of claim 1, wherein:
detecting the change of movement of the touch-sensitive display includes detecting a change in a direction of movement of the touch-sensitive display; and adjusting the first touch activation region includes:
in accordance with a determination that the change in the direction of movement of the touch-sensitive display is in a first movement-direction, adjusting the first touch activation region to encompass a first area of the touch-sensitive display that is in a first display-direction from an area of the touch-sensitive display that contained the first touch activation region prior to detecting the change in direction of movement of the touch-sensitive display, wherein the first area was not included in the first touch activation region prior to detecting the change in the direction of movement; and
in accordance with a determination that the change in the direction of movement of the touch-sensitive display is in a second movement-direction, adjusting the first touch activation region to encompass a second area of the touch-sensitive display that is in a second display-direction from the area of the touch-sensitive display that contained the first touch activation region prior to detecting the change in direction of movement of the touch-sensitive display, wherein the second area was not included in the first touch activation region prior to detecting the change in the direction of movement and the second area is different from the first area. 11. The method of claim 10, wherein the first movement-direction includes one or more movement-direction components and the first display-direction includes one or more display-direction components; and wherein at least one of the display-direction components is opposite from the one or more movement-direction components. 12. The method of claim 10, wherein adjusting the first touch activation region includes determining a degree of adjustment for the first touch activation region based on an amount of change in the direction of movement of the touch-sensitive display. 13. The method of claim 10, further comprising:
detecting that the change in direction of movement of the touch-sensitive display has ceased; and re-adjusting the first touch activation region in response to detecting that the change has ceased. 14. The method of claim 13, wherein re-adjusting the first touch activation region includes reversing the adjustment that was made to the first touch activation region. 15. The method of claim 13, wherein re-adjusting the first touch activation region includes:
adjusting the first touch activation region to temporarily encompass a third area that is in a third display-direction opposite from the first display-direction, the third area is situated beyond the area of the touch-sensitive display that contained the first touch activation region prior to detecting the change in direction of movement of the touch-sensitive display; determining that the first touch activation region has encompassed the third area for a threshold amount of time; and in response to determining that the threshold amount of time has elapsed, adjusting the first touch activation region to encompass the area of the touch-sensitive display that contained the first touch activation region prior to detecting the change in direction of movement of the touch-sensitive display. 16. The method of claim 13, further comprising:
after re-adjusting the first touch activation region, detecting a second touch input on the touch-sensitive display; and in response to detecting the second touch input on the touch-sensitive display:
in accordance with a determination that the second touch input is detected within the first touch activation region, performing a user interface operation that is associated with the first selectable user interface element; and
in accordance with a determination that the second touch input is detected outside of the first touch activation region, forgoing performance of the user interface operation that is associated with the first selectable user interface element. 17. The method of claim 15, wherein a first amount of change between the first area and the area that contained the first touch activation region prior to detecting the change is greater than a second amount of change between the third area and the area that contained the first touch activation region prior to detecting the change. 18. The method of claim 10, wherein the one or more selectable user interface elements include a second selectable user interface element that is associated with a second touch activation region; and
wherein the method further comprises:
adjusting the second touch activation region in the same display-direction as the first touch activation region in response to detecting the change in direction of movement of the touch-sensitive display. 19. An electronic device, comprising:
a display; an input device; one or more processors; non-transitory memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for:
displaying one or more selectable user interface elements on the touch-sensitive display that are associated with corresponding touch activation regions, wherein the one or more selectable user interface elements include a first selectable user interface element that is associated with a first touch activation region;
detecting a change of movement of the touch-sensitive display that has an associated respective direction;
in response to detecting the change of movement of the touch-sensitive display:
adjusting the first touch activation region to encompass a new area of the touch-sensitive display that is at least partially different from the first touch activation region prior to detecting the change of movement, and the new area is based on the change of movement of the touch-sensitive display;
after detecting the change of movement of the touch-sensitive display, detecting a touch input on the touch-sensitive display; and
in response to detecting the touch input on the touch-sensitive display:
in accordance with a determination that the touch input is detected within the adjusted first touch activation region, performing a user interface operation that is associated with the first selectable user interface element; and
in accordance with a determination that the touch input is detected outside of the adjusted first touch activation region, forgoing performance of the user interface operation that is associated with the first selectable user interface element. 20. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which, when executed by an electronic device with a display, and an input device, cause the electronic device to:
display one or more selectable user interface elements on the touch-sensitive display that are associated with corresponding touch activation regions, wherein the one or more selectable user interface elements include a first selectable user interface element that is associated with a first touch activation region; detect a change of movement of the touch-sensitive display that has an associated respective direction; in response to detecting the change of movement of the touch-sensitive display:
adjust the first touch activation region to encompass a new area of the touch-sensitive display that is at least partially different from the first touch activation region prior to detecting the change of movement, and the new area is based on the change of movement of the touch-sensitive display;
after detecting the change of movement of the touch-sensitive display, detect a touch input on the touch-sensitive display; and in response to detecting the touch input on the touch-sensitive display:
in accordance with a determination that the touch input is detected within the adjusted first touch activation region, perform a user interface operation that is associated with the first selectable user interface element; and
in accordance with a determination that the touch input is detected outside of the adjusted first touch activation region, forgo performance of the user interface operation that is associated with the first selectable user interface element. | A device displays a first selectable user interface (UI) element associated with a first touch activation region. The device detects a change of movement of the display. In response to the change of movement, the device adjusts the first touch activation region to encompass a new area. The new area is at least partially different from the first touch activation region prior to the change of movement and is based on the change of the movement. After detecting the change of movement, the device detects a touch input. In accordance with a determination that the touch input is detected within the adjusted first touch activation region, the device performs a user interface operation associated with the first selectable UI element. In accordance with a determination that the touch input is detected outside the adjusted first touch activation region, the device forgoes performance of the user interface operation.1. A method comprising:
at a device with a non-transitory memory, and one or more processors in communication with a touch-sensitive display:
displaying one or more selectable user interface elements on the touch-sensitive display that are associated with corresponding touch activation regions, wherein the one or more selectable user interface elements include a first selectable user interface element that is associated with a first touch activation region;
detecting a change of movement of the touch-sensitive display that has an associated respective direction;
in response to detecting the change of movement of the touch-sensitive display:
adjusting the first touch activation region to encompass a new area of the touch-sensitive display that is at least partially different from the first touch activation region prior to detecting the change of movement, and the new area is based on the change of movement of the touch-sensitive display;
after detecting the change of movement of the touch-sensitive display, detecting a touch input on the touch-sensitive display; and
in response to detecting the touch input on the touch-sensitive display:
in accordance with a determination that the touch input is detected within the adjusted first touch activation region, performing a user interface operation that is associated with the first selectable user interface element; and
in accordance with a determination that the touch input is detected outside of the adjusted first touch activation region, forgoing performance of the user interface operation that is associated with the first selectable user interface element. 2. The method of claim 1, wherein adjusting the first touch activation region includes changing a size of the first touch activation region. 3. The method of claim 1, wherein adjusting the first touch activation region includes changing a shape of the first touch activation region. 4. The method of claim 1, wherein adjusting the first touch activation region includes: determining a degree of adjustment for the first touch activation region based on a size of the first selectable user interface element. 5. The method of claim 1, wherein adjusting the first touch activation region includes maintaining a visual representation of the first selectable user interface element. 6. The method of claim 1, wherein detecting the change in movement includes receiving sensor measurements from one or more sensors. 7. The method of claim 1, wherein adjusting the first touch activation region includes determining an adjustment to the first touch activation region based on a length of an arm. 8. The method of claim 7, wherein adjusting the first touch activation region includes determining an estimated value that corresponds to the length of the arm based on one or more of information stored in the non-transitory memory, and information received from one or more sensors. 9. The method of claim 1, wherein detecting the touch input comprises:
detecting a plurality of touch inputs on the touch-sensitive display; determining a primary touch input of the plurality of touch inputs based on the change of movement of the touch-sensitive display; and discarding the remainder of the touch inputs after determining the primary touch input. 10. The method of claim 1, wherein:
detecting the change of movement of the touch-sensitive display includes detecting a change in a direction of movement of the touch-sensitive display; and adjusting the first touch activation region includes:
in accordance with a determination that the change in the direction of movement of the touch-sensitive display is in a first movement-direction, adjusting the first touch activation region to encompass a first area of the touch-sensitive display that is in a first display-direction from an area of the touch-sensitive display that contained the first touch activation region prior to detecting the change in direction of movement of the touch-sensitive display, wherein the first area was not included in the first touch activation region prior to detecting the change in the direction of movement; and
in accordance with a determination that the change in the direction of movement of the touch-sensitive display is in a second movement-direction, adjusting the first touch activation region to encompass a second area of the touch-sensitive display that is in a second display-direction from the area of the touch-sensitive display that contained the first touch activation region prior to detecting the change in direction of movement of the touch-sensitive display, wherein the second area was not included in the first touch activation region prior to detecting the change in the direction of movement and the second area is different from the first area. 11. The method of claim 10, wherein the first movement-direction includes one or more movement-direction components and the first display-direction includes one or more display-direction components; and wherein at least one of the display-direction components is opposite from the one or more movement-direction components. 12. The method of claim 10, wherein adjusting the first touch activation region includes determining a degree of adjustment for the first touch activation region based on an amount of change in the direction of movement of the touch-sensitive display. 13. The method of claim 10, further comprising:
detecting that the change in direction of movement of the touch-sensitive display has ceased; and re-adjusting the first touch activation region in response to detecting that the change has ceased. 14. The method of claim 13, wherein re-adjusting the first touch activation region includes reversing the adjustment that was made to the first touch activation region. 15. The method of claim 13, wherein re-adjusting the first touch activation region includes:
adjusting the first touch activation region to temporarily encompass a third area that is in a third display-direction opposite from the first display-direction, the third area is situated beyond the area of the touch-sensitive display that contained the first touch activation region prior to detecting the change in direction of movement of the touch-sensitive display; determining that the first touch activation region has encompassed the third area for a threshold amount of time; and in response to determining that the threshold amount of time has elapsed, adjusting the first touch activation region to encompass the area of the touch-sensitive display that contained the first touch activation region prior to detecting the change in direction of movement of the touch-sensitive display. 16. The method of claim 13, further comprising:
after re-adjusting the first touch activation region, detecting a second touch input on the touch-sensitive display; and in response to detecting the second touch input on the touch-sensitive display:
in accordance with a determination that the second touch input is detected within the first touch activation region, performing a user interface operation that is associated with the first selectable user interface element; and
in accordance with a determination that the second touch input is detected outside of the first touch activation region, forgoing performance of the user interface operation that is associated with the first selectable user interface element. 17. The method of claim 15, wherein a first amount of change between the first area and the area that contained the first touch activation region prior to detecting the change is greater than a second amount of change between the third area and the area that contained the first touch activation region prior to detecting the change. 18. The method of claim 10, wherein the one or more selectable user interface elements include a second selectable user interface element that is associated with a second touch activation region; and
wherein the method further comprises:
adjusting the second touch activation region in the same display-direction as the first touch activation region in response to detecting the change in direction of movement of the touch-sensitive display. 19. An electronic device, comprising:
a display; an input device; one or more processors; non-transitory memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for:
displaying one or more selectable user interface elements on the touch-sensitive display that are associated with corresponding touch activation regions, wherein the one or more selectable user interface elements include a first selectable user interface element that is associated with a first touch activation region;
detecting a change of movement of the touch-sensitive display that has an associated respective direction;
in response to detecting the change of movement of the touch-sensitive display:
adjusting the first touch activation region to encompass a new area of the touch-sensitive display that is at least partially different from the first touch activation region prior to detecting the change of movement, and the new area is based on the change of movement of the touch-sensitive display;
after detecting the change of movement of the touch-sensitive display, detecting a touch input on the touch-sensitive display; and
in response to detecting the touch input on the touch-sensitive display:
in accordance with a determination that the touch input is detected within the adjusted first touch activation region, performing a user interface operation that is associated with the first selectable user interface element; and
in accordance with a determination that the touch input is detected outside of the adjusted first touch activation region, forgoing performance of the user interface operation that is associated with the first selectable user interface element. 20. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which, when executed by an electronic device with a display, and an input device, cause the electronic device to:
display one or more selectable user interface elements on the touch-sensitive display that are associated with corresponding touch activation regions, wherein the one or more selectable user interface elements include a first selectable user interface element that is associated with a first touch activation region; detect a change of movement of the touch-sensitive display that has an associated respective direction; in response to detecting the change of movement of the touch-sensitive display:
adjust the first touch activation region to encompass a new area of the touch-sensitive display that is at least partially different from the first touch activation region prior to detecting the change of movement, and the new area is based on the change of movement of the touch-sensitive display;
after detecting the change of movement of the touch-sensitive display, detect a touch input on the touch-sensitive display; and in response to detecting the touch input on the touch-sensitive display:
in accordance with a determination that the touch input is detected within the adjusted first touch activation region, perform a user interface operation that is associated with the first selectable user interface element; and
in accordance with a determination that the touch input is detected outside of the adjusted first touch activation region, forgo performance of the user interface operation that is associated with the first selectable user interface element. | 2,100 |
6,556 | 6,556 | 15,182,537 | 2,154 | For securing a physical environment, an intersection determination is performed using a first record of a first person and a second record of a second person, to determine whether a travel plan of the first person and a travel plan of the second person intersect at a location and a time. When the intersection determination is affirmative, an analysis is performed whether a first object associated with the first person and a second object associated with the second person are combinable to form a combined object having a combined property. When the combined property is designated as harmful in the physical environment, a suspicion indication is outputted. The suspicion indication includes an identity of the first person, an identity of the second person, and a level of suspicion. | 1. A method for securing a physical environment, the method comprising:
performing an intersection determination using a first record of a first person and a second record of a second person, to determine whether a travel plan of the first person and a travel plan of the second person intersect at a location and a time; analyzing, responsive to the intersection determination being affirmative, whether a first object associated with the first person and a second object associated with the second person are combinable to form a combined object having a combined property; and outputting, responsive to the combined property being designated as harmful in the physical environment, a suspicion indication wherein the suspicion indication includes an identity of the first person, an identity of the second person, and a level of suspicion. 2. The method of claim 1, further comprising:
analyzing, responsive to the combined property being designated as harmful in the physical environment, a relationship data to determine whether a relationship exists between the first person and the second person; and increasing, responsive to the relationship existing between the first person and the second person, the level of suspicion. 3. The method of claim 2, further comprising:
accessing a social media repository to obtain social media relationship data, wherein the social media relationship data forms the relationship data. 4. The method of claim 1, further comprising:
analyzing, responsive to the combined property being designated as harmful in the physical environment, a communication data to determine whether a communication links the first person and the second person; and increasing, responsive to the communication linking the first person and the second person, the level of suspicion. 5. The method of claim 4, further comprising:
accessing a telecommunications service repository to obtain telecommunications data, wherein the telecommunications data forms the communication data, and wherein the first person is linked to the second person by reasons of their communications with another entity. 6. The method of claim 1, wherein the suspicion indication further includes a description of the first object and a description of the second object. 7. The method of claim 1, wherein the level of suspicion corresponds to a level of harmfulness of the combined object. 8. The method of claim 1, further comprising:
determining, using a repository of combined objects, whether the combined property is designated as harmful in the physical environment, wherein the repository of combined objects comprises a set of combined objects, each combined object in the set of combined objects having a set of combined properties, and wherein the combined object is a member of the set of combined objects. 9. The method of claim 1, further comprising:
concluding that the first object and the second object are combinable in different combinations, each combination forming a different combined object in a set of combined objects, each different combined object having a different combined property, wherein a first combined property of a first combined object is not designated as harmful, and wherein a second combined property of a second combined object is designated as harmful; selecting the second combined object as the combined object; and selecting the second combined property as the combined property. 10. The method of claim 1, further comprising:
detecting a presence of the first person at a first location in the physical environment, the first person being associated with the first object; forming the first record corresponding to the first person, the first record including an identifier of the first person and the travel plan of the first person; forming a first object record corresponding to the first object, the first object record comprising a property of the first object, wherein the first object satisfies a requirement for legal presence in the physical environment; detecting a presence of the second person at a second location in the physical environment, the second person being associated with the second object; forming a second record corresponding to the second person, the second record including an identifier of the second person and the travel plan of the second person; forming a second object record corresponding to the second object, the second object record comprising a property of the second object, wherein the second object satisfies the requirement for legal presence in the physical environment. 11. The method of claim 10, wherein the property of the first object comprises a composition of the first object. 12. The method of claim 10, wherein the property of the first object comprises a possible use of the first object. 13. The method of claim 1, wherein the method is embodied in a computer program product comprising one or more computer-readable storage devices and computer-readable program instructions which are stored on the one or more computer-readable tangible storage devices and executed by one or more processors. 14. The method of claim 1, wherein the method is embodied in a computer system comprising one or more processors, one or more computer-readable memories, one or more computer-readable storage devices and program instructions which are stored on the one or more computer-readable storage devices for execution by the one or more processors via the one or more memories and executed by the one or more processors. 15. A computer program product for securing a physical environment, the computer program product comprising one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices, the stored program instructions comprising:
program instructions to perform an intersection determination using a first record of a first person and a second record of a second person, to determine whether a travel plan of the first person and a travel plan of the second person intersect at a location and a time; program instructions to analyze, responsive to the intersection determination being affirmative, whether a first object associated with the first person and a second object associated with the second person are combinable to form a combined object having a combined property; and program instructions to output, responsive to the combined property being designated as harmful in the physical environment, a suspicion indication wherein the suspicion indication includes an identity of the first person, an identity of the second person, and a level of suspicion. 16. The computer program product of claim 15, further comprising:
program instructions to analyze, responsive to the combined property being designated as harmful in the physical environment, a relationship data to determine whether a relationship exists between the first person and the second person; and program instructions to increase, responsive to the relationship existing between the first person and the second person, the level of suspicion. 17. The computer program product of claim 16, further comprising:
program instructions to access a social media repository to obtain social media relationship data, wherein the social media relationship data forms the relationship data. 18. The computer program product of claim 15, further comprising:
program instructions to analyze, responsive to the combined property being designated as harmful in the physical environment, a communication data to determine whether a communication links the first person and the second person; and program instructions to increase, responsive to the communication linking the first person and the second person, the level of suspicion. 19. The computer program product of claim 18, further comprising:
program instructions to access a telecommunications service repository to obtain telecommunications data, wherein the telecommunications data forms the communication data, and wherein the first person is linked to the second person by reasons of their communications with another entity. 20. A computer system for securing a physical environment, the computer system comprising one or more processors, one or more computer-readable memories, and one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, the stored program instructions comprising:
program instructions to perform an intersection determination using a first record of a first person and a second record of a second person, to determine whether a travel plan of the first person and a travel plan of the second person intersect at a location and a time; program instructions to analyze, responsive to the intersection determination being affirmative, whether a first object associated with the first person and a second object associated with the second person are combinable to form a combined object having a combined property; and program instructions to output, responsive to the combined property being designated as harmful in the physical environment, a suspicion indication wherein the suspicion indication includes an identity of the first person, an identity of the second person, and a level of suspicion. | For securing a physical environment, an intersection determination is performed using a first record of a first person and a second record of a second person, to determine whether a travel plan of the first person and a travel plan of the second person intersect at a location and a time. When the intersection determination is affirmative, an analysis is performed whether a first object associated with the first person and a second object associated with the second person are combinable to form a combined object having a combined property. When the combined property is designated as harmful in the physical environment, a suspicion indication is outputted. The suspicion indication includes an identity of the first person, an identity of the second person, and a level of suspicion.1. A method for securing a physical environment, the method comprising:
performing an intersection determination using a first record of a first person and a second record of a second person, to determine whether a travel plan of the first person and a travel plan of the second person intersect at a location and a time; analyzing, responsive to the intersection determination being affirmative, whether a first object associated with the first person and a second object associated with the second person are combinable to form a combined object having a combined property; and outputting, responsive to the combined property being designated as harmful in the physical environment, a suspicion indication wherein the suspicion indication includes an identity of the first person, an identity of the second person, and a level of suspicion. 2. The method of claim 1, further comprising:
analyzing, responsive to the combined property being designated as harmful in the physical environment, a relationship data to determine whether a relationship exists between the first person and the second person; and increasing, responsive to the relationship existing between the first person and the second person, the level of suspicion. 3. The method of claim 2, further comprising:
accessing a social media repository to obtain social media relationship data, wherein the social media relationship data forms the relationship data. 4. The method of claim 1, further comprising:
analyzing, responsive to the combined property being designated as harmful in the physical environment, a communication data to determine whether a communication links the first person and the second person; and increasing, responsive to the communication linking the first person and the second person, the level of suspicion. 5. The method of claim 4, further comprising:
accessing a telecommunications service repository to obtain telecommunications data, wherein the telecommunications data forms the communication data, and wherein the first person is linked to the second person by reasons of their communications with another entity. 6. The method of claim 1, wherein the suspicion indication further includes a description of the first object and a description of the second object. 7. The method of claim 1, wherein the level of suspicion corresponds to a level of harmfulness of the combined object. 8. The method of claim 1, further comprising:
determining, using a repository of combined objects, whether the combined property is designated as harmful in the physical environment, wherein the repository of combined objects comprises a set of combined objects, each combined object in the set of combined objects having a set of combined properties, and wherein the combined object is a member of the set of combined objects. 9. The method of claim 1, further comprising:
concluding that the first object and the second object are combinable in different combinations, each combination forming a different combined object in a set of combined objects, each different combined object having a different combined property, wherein a first combined property of a first combined object is not designated as harmful, and wherein a second combined property of a second combined object is designated as harmful; selecting the second combined object as the combined object; and selecting the second combined property as the combined property. 10. The method of claim 1, further comprising:
detecting a presence of the first person at a first location in the physical environment, the first person being associated with the first object; forming the first record corresponding to the first person, the first record including an identifier of the first person and the travel plan of the first person; forming a first object record corresponding to the first object, the first object record comprising a property of the first object, wherein the first object satisfies a requirement for legal presence in the physical environment; detecting a presence of the second person at a second location in the physical environment, the second person being associated with the second object; forming a second record corresponding to the second person, the second record including an identifier of the second person and the travel plan of the second person; forming a second object record corresponding to the second object, the second object record comprising a property of the second object, wherein the second object satisfies the requirement for legal presence in the physical environment. 11. The method of claim 10, wherein the property of the first object comprises a composition of the first object. 12. The method of claim 10, wherein the property of the first object comprises a possible use of the first object. 13. The method of claim 1, wherein the method is embodied in a computer program product comprising one or more computer-readable storage devices and computer-readable program instructions which are stored on the one or more computer-readable tangible storage devices and executed by one or more processors. 14. The method of claim 1, wherein the method is embodied in a computer system comprising one or more processors, one or more computer-readable memories, one or more computer-readable storage devices and program instructions which are stored on the one or more computer-readable storage devices for execution by the one or more processors via the one or more memories and executed by the one or more processors. 15. A computer program product for securing a physical environment, the computer program product comprising one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices, the stored program instructions comprising:
program instructions to perform an intersection determination using a first record of a first person and a second record of a second person, to determine whether a travel plan of the first person and a travel plan of the second person intersect at a location and a time; program instructions to analyze, responsive to the intersection determination being affirmative, whether a first object associated with the first person and a second object associated with the second person are combinable to form a combined object having a combined property; and program instructions to output, responsive to the combined property being designated as harmful in the physical environment, a suspicion indication wherein the suspicion indication includes an identity of the first person, an identity of the second person, and a level of suspicion. 16. The computer program product of claim 15, further comprising:
program instructions to analyze, responsive to the combined property being designated as harmful in the physical environment, a relationship data to determine whether a relationship exists between the first person and the second person; and program instructions to increase, responsive to the relationship existing between the first person and the second person, the level of suspicion. 17. The computer program product of claim 16, further comprising:
program instructions to access a social media repository to obtain social media relationship data, wherein the social media relationship data forms the relationship data. 18. The computer program product of claim 15, further comprising:
program instructions to analyze, responsive to the combined property being designated as harmful in the physical environment, a communication data to determine whether a communication links the first person and the second person; and program instructions to increase, responsive to the communication linking the first person and the second person, the level of suspicion. 19. The computer program product of claim 18, further comprising:
program instructions to access a telecommunications service repository to obtain telecommunications data, wherein the telecommunications data forms the communication data, and wherein the first person is linked to the second person by reasons of their communications with another entity. 20. A computer system for securing a physical environment, the computer system comprising one or more processors, one or more computer-readable memories, and one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, the stored program instructions comprising:
program instructions to perform an intersection determination using a first record of a first person and a second record of a second person, to determine whether a travel plan of the first person and a travel plan of the second person intersect at a location and a time; program instructions to analyze, responsive to the intersection determination being affirmative, whether a first object associated with the first person and a second object associated with the second person are combinable to form a combined object having a combined property; and program instructions to output, responsive to the combined property being designated as harmful in the physical environment, a suspicion indication wherein the suspicion indication includes an identity of the first person, an identity of the second person, and a level of suspicion. | 2,100 |
6,557 | 6,557 | 14,811,301 | 2,169 | Disclosed are various examples of integrating multiple domains within a directory service. A computing device retrieves a first list of members in a first group of users for the domain from a first directory service for a first domain. The computing device then determines that a second group of users is a member of the first group of users, wherein the second group of users corresponds to a second domain. The computing device then retrieves a second list of members in the second group of users from a second directory service for a second domain. The computing device subsequently compares the first list of members in the first group of users and the second list of members in the second group of users with a third list of members in a third group of users, wherein the third list of members in the third group of users corresponds to a user list maintained by the application. The computing device then adds to the third list of members in the third group of users each user that is both present in the first list of members in the first group of users or in the second list of members in the second group of users and missing from the third list of members in the third group of users. | 1. A system, comprising:
a computing device comprising a processor and a memory; and an application stored in the memory of the computing device that, when executed by the processor of the computing device, causes the computing device to at least:
retrieve a first list of members in a first group of users for the domain from a first directory service for a first domain;
determine that a second group of users is a member of the first group of users, wherein the second group of users corresponds to a second domain;
retrieve a second list of members in the second group of users from a second directory service for a second domain;
compare the first list of members in the first group of users and the second list of members in the second group of users with a third list of members in a third group of users, wherein the third list of members in the third group of users corresponds to a user list maintained by the application; and
add to the third list of members in the third group of users each user that is both:
present in the first list of members in the first group of users or in the second list of members in the second group of users, and
missing from the third list of members in the third group of users. 2. The system of claim 1, wherein the application, when executed by the processor of the computing device, further causes the computing device to at least remove from the third list of members in the third group of users any user that is present in the third list of members in the third group of users and omitted from both the first list of members in the first group of users and the second list of members in the second group of users. 3. The system of claim 1, wherein the application, when executed by the processor of the computing device, further causes the computing device to at least:
query a table to identify the first directory service based at least in part on a first domain name corresponding to the first domain; and query the table to identify the second directory service based at least in part on a second domain name corresponding to the second domain. 4. The system of claim 1, wherein the application, when executed by the processor of the computing device, further causes the computing device to at least:
count a number of users to be added to the third list of members in the third group of users; determine that the number of users to be added exceeds a threshold value; and delay an addition of users to the third list of members in the third group of users based at least in part on the number of users to be added exceeding the threshold value until confirmation is received from an administrator. 5. The system of claim 1, wherein the second domain is a subdomain of the first domain. 6. The system of claim 1, wherein the second domain is a trusted domain of the first domain. 7. The system of claim 1, wherein the application, when executed by the processor of the computing device, further causes the computing device to at least:
identify a client computing device associated with a user included in the third group of users; determine that the client computing device is not associated with at least one policy linked to the third group of users; and send the at least one policy to a management component executing on the client computing device. 8. A method, comprising:
retrieving a first list of members in a first group of users for a first domain from a first directory service; determining that a second group of users is a member of the first group of users, wherein the second group of users corresponds to a second domain; retrieving a second list of members in the second group of users for a second domain from a second directory service; comparing the first list of members in the first group of users and the second list of members in the second group of users with a third list of members in a third group of users, wherein the third list of members in the third group of users corresponds to a user list; and adding to the third list of members in the third group of users each user that is both:
present in the first list of members in the first group of users or in the second list of members in the second group of users, and
missing from the third list of members in the third group of users. 9. The method of claim 8, further comprising removing from the third list of members in the third group of users any user that is present in the third list of members in the third group of users and omitted from both the first list of members in the first group of users and the second list of members in the second group of users. 10. The method of claim 8, further comprising:
querying a table to identify the first directory service based at least in part on a first domain name corresponding to the first domain; and querying the table to identify the second directory service based at least in part on a second domain name corresponding to the second domain. 11. The method of claim 8, further comprising:
counting a number of users to be added to the third list of members in the third group of users; determining that the number of users to be added exceeds a threshold value; and delaying an addition of users to the third list of members in the third group of users based at least in part on determining that the number of users to be added exceeds the threshold value until confirmation is received from an administrator. 12. The method of claim 8, wherein the second domain is a subdomain of the first domain. 13. The method of claim 8, wherein the second domain is a trusted domain of the first domain. 14. The method of claim 8, further comprising:
identifying a client computing device associated with a user included in the third group of users; determining that the client computing device is not associated with at least one policy linked to the third group of users; and sending the at least one policy to a management component executing on the client computing device. 15. A non-transitory computer-readable medium storing a plurality of computer instructions executable by a computing device, the plurality of computer instructions being configured to cause the computing device to at least:
retrieve a first list of members in a first group of users for a first domain from a first directory service; determine that a second group of users is a member of the first group of users, wherein the second group of users corresponds to a second domain; retrieve a second list of members in the second group of users for a second domain from a second directory service; compare the first list of members in the first group of users and the second list of members in the second group of users with a third list of members in a third group of users, wherein the third list of members in the third group of users corresponds to a user list; and add to the third list of members in the third group of users each user that is both:
present in the first list of members in the first group of users or in the second list of members in the second group of users, and
missing from the third list of members in the third group of users. 16. The non-transitory computer-readable medium of claim 15, wherein the plurality of computer instructions are further configured to cause the computing device to at least remove from the third list of members in the third group of users any user that is present in the third list of members in the third group of users and omitted from both the first list of members in the first group of users and the second list of members in the second group of users. 17. The non-transitory computer-readable medium of claim 15, wherein the plurality of computer instructions are further configured to cause the computing device to at least:
query a table to identify the first directory service based at least in part on a first domain name corresponding to the first domain; and query the table to identify the second directory service based at least in part on a second domain name corresponding to the second domain. 18. The non-transitory computer-readable medium of claim 15, wherein the plurality of computer instructions are further configured to cause the computing device to at least:
count a number of users to be added to the third list of members in the third group of users; determine that the number of users to be added exceeds a threshold value; and delay an addition of users to the third list of members in the third group of users based at least in part on the number of users to be added exceeding the threshold value until confirmation is received from an administrator. 19. The non-transitory computer-readable medium of claim 15, wherein the second domain is a subdomain of the first domain. 20. The non-transitory computer-readable medium of claim 15, wherein the second domain is a trusted domain of the first domain. | Disclosed are various examples of integrating multiple domains within a directory service. A computing device retrieves a first list of members in a first group of users for the domain from a first directory service for a first domain. The computing device then determines that a second group of users is a member of the first group of users, wherein the second group of users corresponds to a second domain. The computing device then retrieves a second list of members in the second group of users from a second directory service for a second domain. The computing device subsequently compares the first list of members in the first group of users and the second list of members in the second group of users with a third list of members in a third group of users, wherein the third list of members in the third group of users corresponds to a user list maintained by the application. The computing device then adds to the third list of members in the third group of users each user that is both present in the first list of members in the first group of users or in the second list of members in the second group of users and missing from the third list of members in the third group of users.1. A system, comprising:
a computing device comprising a processor and a memory; and an application stored in the memory of the computing device that, when executed by the processor of the computing device, causes the computing device to at least:
retrieve a first list of members in a first group of users for the domain from a first directory service for a first domain;
determine that a second group of users is a member of the first group of users, wherein the second group of users corresponds to a second domain;
retrieve a second list of members in the second group of users from a second directory service for a second domain;
compare the first list of members in the first group of users and the second list of members in the second group of users with a third list of members in a third group of users, wherein the third list of members in the third group of users corresponds to a user list maintained by the application; and
add to the third list of members in the third group of users each user that is both:
present in the first list of members in the first group of users or in the second list of members in the second group of users, and
missing from the third list of members in the third group of users. 2. The system of claim 1, wherein the application, when executed by the processor of the computing device, further causes the computing device to at least remove from the third list of members in the third group of users any user that is present in the third list of members in the third group of users and omitted from both the first list of members in the first group of users and the second list of members in the second group of users. 3. The system of claim 1, wherein the application, when executed by the processor of the computing device, further causes the computing device to at least:
query a table to identify the first directory service based at least in part on a first domain name corresponding to the first domain; and query the table to identify the second directory service based at least in part on a second domain name corresponding to the second domain. 4. The system of claim 1, wherein the application, when executed by the processor of the computing device, further causes the computing device to at least:
count a number of users to be added to the third list of members in the third group of users; determine that the number of users to be added exceeds a threshold value; and delay an addition of users to the third list of members in the third group of users based at least in part on the number of users to be added exceeding the threshold value until confirmation is received from an administrator. 5. The system of claim 1, wherein the second domain is a subdomain of the first domain. 6. The system of claim 1, wherein the second domain is a trusted domain of the first domain. 7. The system of claim 1, wherein the application, when executed by the processor of the computing device, further causes the computing device to at least:
identify a client computing device associated with a user included in the third group of users; determine that the client computing device is not associated with at least one policy linked to the third group of users; and send the at least one policy to a management component executing on the client computing device. 8. A method, comprising:
retrieving a first list of members in a first group of users for a first domain from a first directory service; determining that a second group of users is a member of the first group of users, wherein the second group of users corresponds to a second domain; retrieving a second list of members in the second group of users for a second domain from a second directory service; comparing the first list of members in the first group of users and the second list of members in the second group of users with a third list of members in a third group of users, wherein the third list of members in the third group of users corresponds to a user list; and adding to the third list of members in the third group of users each user that is both:
present in the first list of members in the first group of users or in the second list of members in the second group of users, and
missing from the third list of members in the third group of users. 9. The method of claim 8, further comprising removing from the third list of members in the third group of users any user that is present in the third list of members in the third group of users and omitted from both the first list of members in the first group of users and the second list of members in the second group of users. 10. The method of claim 8, further comprising:
querying a table to identify the first directory service based at least in part on a first domain name corresponding to the first domain; and querying the table to identify the second directory service based at least in part on a second domain name corresponding to the second domain. 11. The method of claim 8, further comprising:
counting a number of users to be added to the third list of members in the third group of users; determining that the number of users to be added exceeds a threshold value; and delaying an addition of users to the third list of members in the third group of users based at least in part on determining that the number of users to be added exceeds the threshold value until confirmation is received from an administrator. 12. The method of claim 8, wherein the second domain is a subdomain of the first domain. 13. The method of claim 8, wherein the second domain is a trusted domain of the first domain. 14. The method of claim 8, further comprising:
identifying a client computing device associated with a user included in the third group of users; determining that the client computing device is not associated with at least one policy linked to the third group of users; and sending the at least one policy to a management component executing on the client computing device. 15. A non-transitory computer-readable medium storing a plurality of computer instructions executable by a computing device, the plurality of computer instructions being configured to cause the computing device to at least:
retrieve a first list of members in a first group of users for a first domain from a first directory service; determine that a second group of users is a member of the first group of users, wherein the second group of users corresponds to a second domain; retrieve a second list of members in the second group of users for a second domain from a second directory service; compare the first list of members in the first group of users and the second list of members in the second group of users with a third list of members in a third group of users, wherein the third list of members in the third group of users corresponds to a user list; and add to the third list of members in the third group of users each user that is both:
present in the first list of members in the first group of users or in the second list of members in the second group of users, and
missing from the third list of members in the third group of users. 16. The non-transitory computer-readable medium of claim 15, wherein the plurality of computer instructions are further configured to cause the computing device to at least remove from the third list of members in the third group of users any user that is present in the third list of members in the third group of users and omitted from both the first list of members in the first group of users and the second list of members in the second group of users. 17. The non-transitory computer-readable medium of claim 15, wherein the plurality of computer instructions are further configured to cause the computing device to at least:
query a table to identify the first directory service based at least in part on a first domain name corresponding to the first domain; and query the table to identify the second directory service based at least in part on a second domain name corresponding to the second domain. 18. The non-transitory computer-readable medium of claim 15, wherein the plurality of computer instructions are further configured to cause the computing device to at least:
count a number of users to be added to the third list of members in the third group of users; determine that the number of users to be added exceeds a threshold value; and delay an addition of users to the third list of members in the third group of users based at least in part on the number of users to be added exceeding the threshold value until confirmation is received from an administrator. 19. The non-transitory computer-readable medium of claim 15, wherein the second domain is a subdomain of the first domain. 20. The non-transitory computer-readable medium of claim 15, wherein the second domain is a trusted domain of the first domain. | 2,100 |
6,558 | 6,558 | 15,815,788 | 2,174 | A processing device comprising a graphical user interface in an industrial vehicle is provided. The processing device comprises a touch screen display that receives touch gesture commands from a vehicle operator, memory storing executable instructions, and a processor in communication with the memory. The processor when executing the executable instructions: defines a plurality of widgets, wherein each widget comprises a visual representation of a current state of an associated function of the vehicle, displays a subset of the plurality of widgets on a portion of the touch screen display defining a plurality of widget spaces, and displays an icon tray on the touch screen display comprising one or more icons, in which at least one of the one or more icons corresponds to a respective one of the plurality of widgets. | 1. A processing device comprising a graphical user interface in an industrial vehicle, the processing device comprising:
a screen display; memory storing executable instructions; and a processor in communication with the memory, wherein the processor when executing the executable instructions:
defines one or more widgets, each widget comprising a visual representation of a current state of an associated function of the industrial vehicle;
controls display of at least one of the one or more widgets on a portion of the screen display defining one or more widget spaces;
controls display of an icon tray on the screen display comprising one or more icons, wherein at least one of the one or more icons corresponds to a respective one of the one or more widgets;
detects activation of one of the one or more icons corresponding to the respective one widget;
in response to detecting the activation of the one icon, allows a first menu portion of the respective one widget to be displayed; and
controls display of a first menu associated with the respective one widget. 2. The processing device of claim 1, wherein the processor when executing the executable instructions:
in response to detecting the activation of the one icon,
allows a first menu portion of the respective one widget to be activated;
detects activation of the first menu portion; and
in response to detecting the activation of the first menu portion, controls display of the first menu associated with the respective one widget. 3. The processing device of claim 1, wherein the processor when executing the executable instructions:
further in response to detecting the activation of the one icon, locks the respective one widget in position in a first widget space on the screen display. 4. The processing device of claim 3, wherein the processor when executing the executable instructions:
defines a plurality of widgets and a plurality of widget spaces; and further in response to detecting the activation of the one icon:
shifts the remaining one or more widgets to the one or more remaining widget spaces. 5. The processing device of claim 1, wherein the processor when executing the executable instructions:
defines the icon tray as a separate portion of the screen display from the one or more widget spaces, the icon tray being spaced apart from the one or more widget spaces. 6. The processing device of claim 1, wherein:
the screen display comprises a touch screen display that receives touch gesture commands from a vehicle operator; and the processor when executing the executable instructions:
shifts a position of one or more of the widgets on the touch screen display following detection of a touch gesture on the touch screen display. 7. The processing device of claim 1, wherein:
the screen display comprises a touch screen display that receives touch gesture commands from a vehicle operator; and the first menu portion of the respective one widget is activated by a vehicle operator touching or selecting the first menu portion. 8. The processing device of claim 7, wherein:
the first menu comprises a list, a sidebar, or a scroll wheel; and a display of options in the first menu is altered by one of a tap gesture, a swipe gesture, or a slide gesture on the touch screen display, the options within the first menu being color-coded with a different color. 9. The processing device of claim 1, wherein the processor when executing the executable instructions:
defines a plurality of sub-menus, each sub-menu corresponding to a particular option within the first menu, wherein one sub-menu is displayed on the screen display after the corresponding option within the first menu has been selected. 10. The processing device of claim 9, wherein the processor when executing the executable instructions:
color codes at least a portion of the one sub-menu using a same color associated with the corresponding option within the first menu. 11. The processing device of claim 9, wherein one or more of the first menu or the sub-menus are displayed within the respective one widget. 12. The processing device of claim 9, wherein one or more of the first menu or the sub-menus are displayed in a separate window that is temporarily superimposed over one or more of the widget spaces. 13. The processing device of claim 1, wherein the processor when executing the executable instructions:
defines the respective one widget as a rack height select (RHS) widget, the RHS widget comprising:
a workspace zone menu defining the first menu, the workspace zone menu comprising a plurality of workspace zones, each workspace zone having a corresponding sub-menu comprising a plurality of stored rack heights associated with the workspace zone; and
a load presence indicator. 14. The processing device of claim 1, further comprising:
a vehicle network system connecting the processor to at least one vehicle network bus, wherein the processor extracts a current position of a carriage assembly and a current sensed load weight, wherein the processor when executing the executable instructions:
defines one of the one or more widgets as a capacity data monitoring (CDM) widget, the CDM widget comprising a visual representation of the current position of the carriage assembly and the current sensed load weight. 15. The processing device of claim 1, further comprising a vehicle operator control section comprising one or more physical input control elements, wherein the one or more physical input control elements are used to make selections on the screen display. 16. The processing device of claim 15, wherein the one or more physical input control elements comprise at least one of a five-button control, a trigger switch, or a rotary control knob. 17. The processing device of claim 1, wherein:
the screen display comprises a touch screen display that receives touch gesture commands from a vehicle operator; and the processor when executing the executable instructions:
determines if a speed of the industrial vehicle is below a threshold speed; and
changes one or more of the one or more widgets on the touch screen display following detection of a touch gesture on the touch screen display and if the speed of the industrial vehicle is below the threshold speed. 18. The processing device of claim 1, wherein the processor when executing the executable instructions:
further in response to detecting the activation of the one icon, moves the respective one widget to a predefined widget space. | A processing device comprising a graphical user interface in an industrial vehicle is provided. The processing device comprises a touch screen display that receives touch gesture commands from a vehicle operator, memory storing executable instructions, and a processor in communication with the memory. The processor when executing the executable instructions: defines a plurality of widgets, wherein each widget comprises a visual representation of a current state of an associated function of the vehicle, displays a subset of the plurality of widgets on a portion of the touch screen display defining a plurality of widget spaces, and displays an icon tray on the touch screen display comprising one or more icons, in which at least one of the one or more icons corresponds to a respective one of the plurality of widgets.1. A processing device comprising a graphical user interface in an industrial vehicle, the processing device comprising:
a screen display; memory storing executable instructions; and a processor in communication with the memory, wherein the processor when executing the executable instructions:
defines one or more widgets, each widget comprising a visual representation of a current state of an associated function of the industrial vehicle;
controls display of at least one of the one or more widgets on a portion of the screen display defining one or more widget spaces;
controls display of an icon tray on the screen display comprising one or more icons, wherein at least one of the one or more icons corresponds to a respective one of the one or more widgets;
detects activation of one of the one or more icons corresponding to the respective one widget;
in response to detecting the activation of the one icon, allows a first menu portion of the respective one widget to be displayed; and
controls display of a first menu associated with the respective one widget. 2. The processing device of claim 1, wherein the processor when executing the executable instructions:
in response to detecting the activation of the one icon,
allows a first menu portion of the respective one widget to be activated;
detects activation of the first menu portion; and
in response to detecting the activation of the first menu portion, controls display of the first menu associated with the respective one widget. 3. The processing device of claim 1, wherein the processor when executing the executable instructions:
further in response to detecting the activation of the one icon, locks the respective one widget in position in a first widget space on the screen display. 4. The processing device of claim 3, wherein the processor when executing the executable instructions:
defines a plurality of widgets and a plurality of widget spaces; and further in response to detecting the activation of the one icon:
shifts the remaining one or more widgets to the one or more remaining widget spaces. 5. The processing device of claim 1, wherein the processor when executing the executable instructions:
defines the icon tray as a separate portion of the screen display from the one or more widget spaces, the icon tray being spaced apart from the one or more widget spaces. 6. The processing device of claim 1, wherein:
the screen display comprises a touch screen display that receives touch gesture commands from a vehicle operator; and the processor when executing the executable instructions:
shifts a position of one or more of the widgets on the touch screen display following detection of a touch gesture on the touch screen display. 7. The processing device of claim 1, wherein:
the screen display comprises a touch screen display that receives touch gesture commands from a vehicle operator; and the first menu portion of the respective one widget is activated by a vehicle operator touching or selecting the first menu portion. 8. The processing device of claim 7, wherein:
the first menu comprises a list, a sidebar, or a scroll wheel; and a display of options in the first menu is altered by one of a tap gesture, a swipe gesture, or a slide gesture on the touch screen display, the options within the first menu being color-coded with a different color. 9. The processing device of claim 1, wherein the processor when executing the executable instructions:
defines a plurality of sub-menus, each sub-menu corresponding to a particular option within the first menu, wherein one sub-menu is displayed on the screen display after the corresponding option within the first menu has been selected. 10. The processing device of claim 9, wherein the processor when executing the executable instructions:
color codes at least a portion of the one sub-menu using a same color associated with the corresponding option within the first menu. 11. The processing device of claim 9, wherein one or more of the first menu or the sub-menus are displayed within the respective one widget. 12. The processing device of claim 9, wherein one or more of the first menu or the sub-menus are displayed in a separate window that is temporarily superimposed over one or more of the widget spaces. 13. The processing device of claim 1, wherein the processor when executing the executable instructions:
defines the respective one widget as a rack height select (RHS) widget, the RHS widget comprising:
a workspace zone menu defining the first menu, the workspace zone menu comprising a plurality of workspace zones, each workspace zone having a corresponding sub-menu comprising a plurality of stored rack heights associated with the workspace zone; and
a load presence indicator. 14. The processing device of claim 1, further comprising:
a vehicle network system connecting the processor to at least one vehicle network bus, wherein the processor extracts a current position of a carriage assembly and a current sensed load weight, wherein the processor when executing the executable instructions:
defines one of the one or more widgets as a capacity data monitoring (CDM) widget, the CDM widget comprising a visual representation of the current position of the carriage assembly and the current sensed load weight. 15. The processing device of claim 1, further comprising a vehicle operator control section comprising one or more physical input control elements, wherein the one or more physical input control elements are used to make selections on the screen display. 16. The processing device of claim 15, wherein the one or more physical input control elements comprise at least one of a five-button control, a trigger switch, or a rotary control knob. 17. The processing device of claim 1, wherein:
the screen display comprises a touch screen display that receives touch gesture commands from a vehicle operator; and the processor when executing the executable instructions:
determines if a speed of the industrial vehicle is below a threshold speed; and
changes one or more of the one or more widgets on the touch screen display following detection of a touch gesture on the touch screen display and if the speed of the industrial vehicle is below the threshold speed. 18. The processing device of claim 1, wherein the processor when executing the executable instructions:
further in response to detecting the activation of the one icon, moves the respective one widget to a predefined widget space. | 2,100 |
6,559 | 6,559 | 15,359,419 | 2,161 | A network-based service may be provided for facilitating queries for a number of items, such as travel services. A user may submit a query including criteria for determining one or more relevant items. Based on the submitted query, the network-based service may present the user with information regarding the actions of other similar users of the network-based service, such as searches performed by the other users. Based on this information, the user may elect to supplement the current query to conform to the actions for other users. In some embodiments, actions by other users may be based at least in part on a category of the querying user. By presenting actions of similar users, a current user may be enabled to select the most relevant query terms for identifying a desired item. | 1. A computer-implemented method comprising:
as implemented by one or more computing devices configured with specific executable instructions,
identifying, from usage data reflective of user activity on a travel service, a first search criterion, wherein the first search criterion is associated with a user;
identifying, from the usage data, a second search criterion, wherein the second search criterion is associated with the user;
determining that the second search criterion was received in response to a presentation of search results corresponding to the first search criterion;
generating a first user interface element corresponding to the first search criterion and the second search criterion, wherein selection of the first user interface element, when presented to an additional user, enables generation of a new travel item query that includes at least the second search criterion;
receiving, from a user computing device, a first travel item query;
determining that the first travel item query includes the first search criterion;
transmitting, to the user computing device, search results corresponding to the first travel item query, for presentation to the additional user in a user interface that includes the first user interface element;
receiving, from the user computing device, selection of the first user interface element;
in response to receiving the selection of the first user interface element:
generating the new travel item query that includes the second search criterion; and
transmitting, to the user computing device, search results corresponding to the new travel item query. 2. The computer-implemented method of claim 1, wherein the first search criterion comprises a first arrival location, and wherein the second search criterion comprises a second arrival location. 3. The computer-implemented method of claim 1 further comprising:
identifying, from the usage data, a third search criterion associated with a second user;
identifying, from the usage data, a fourth search criterion associated with the second user;
determining that the fourth search criterion was received in response to a presentation of search results corresponding to the third search criterion;
generating a second user interface element corresponding to the third search criterion and the fourth search criterion, wherein selection of the second user interface element, when presented to an additional user, enables generation of a second new travel item query that includes at least the fourth criterion;
determining that the first travel item query includes the third search criterion; and
transmitting the second user interface element to the user computing device. 4. The computer-implemented method of claim 1, wherein generating the first user interface element is based at least in part on identifying a threshold number of queries within the usage data, wherein each of the threshold number of queries includes the second search criterion and corresponds to a presentation of search results based on the first search criterion. 5. The computer-implemented method of claim 1, wherein generating the first user interface element is based at least in part on determining a likelihood that transmitting a search result based on the first search criterion corresponds to receiving a query that includes the second search criterion. 6. A system comprising:
a data store configured to store one or more assertions, wherein each of the one or more assertions identifies at least an initial search criterion and a modified search criterion; and a processor in communication with the data store, the processor configured by specific executable instructions to:
receive, from a user computing device, a first query including a first search criterion;
identify, based at least in part on the first search criterion, a first assertion of the one or more assertions, wherein the first assertion identifies the first search criterion and a modified first search criterion;
transmit, to the user computing device, search results corresponding to the first query, and the first assertion;
receive, from the user computing device, selection of a user interface element associated with the first assertion, wherein the selection corresponds to a user request to generate a second query including the modified first search criterion;
generate the second query including the modified first search criterion; and
transmit, to the user computing device, search results corresponding to the second query. 7. The system of claim 6, wherein the processor is further configured to:
generate instructions for displaying a user interface that includes the user interface element; and transmit the instructions for displaying the user interface to the user computing device. 8. The system of claim 6, wherein the first assertion is associated with a first category. 9. The system of claim 8, wherein the processor is further configured to determine, based at least in part on the first search criterion, a category of the first query, and wherein the first assertion is identified based at least in part on the category of the first query. 10. The system of claim 9, wherein the category is determined based at least in part on a user profile associated with the user computing device, a past activity of the user computing device, or a previously acquired travel item associated with the user computing device. 11. The system of claim 6, wherein the processor is further configured to:
receive, from the user computing device, a new query including a new search criterion; generate a new assertion, wherein the new assertion identifies at least the first modified criterion and the new search criterion; and store the new assertion in the data store. 12. The system of claim 6, wherein the first search criterion comprises a travel destination and the modified first search criterion comprises an alternate travel destination. 13. The system of claim 6, wherein the first search criterion comprises a departure date and the modified first search criterion comprises a range of departure dates. 14. The system of claim 6, wherein the processor is further configured to:
determine that a second assertion of the one or more assertions identifies at least the first search criterion; and transmit, to the user computing device, the second assertion. 15. A non-transitory computer readable storage medium having computer executable instructions, wherein the computer executable instructions, when executed by a computing system, cause the computing system to:
maintain one or more assertions, wherein each of the one or more assertions identifies an initial search criterion and a modified search criterion, and wherein each of the one or more assertions enables generation of a new query based at least in part on the modified search criterion; determine, based at least in part on information received from a user computing device, a first query including a first search criterion; determine that a first assertion of the one or more assertions is relevant to the first query, the first assertion identifying the first search criterion and a modified first search criterion; transmit, to the user computing device, the first assertion; receive, from the user computing device, selection of a user interface element associated with the first assertion; generate a second query based at least in part on the modified first search criterion; and transmit, to the user computing device, search results associated with the second query. 16. The non-transitory computer readable storage medium of claim 15, wherein the computer executable instructions further cause the computing system to:
determine that a second assertion of the one or more assertions is relevant to the first query, the second assertion identifying at least the first search criterion; and determine a prioritization of the first assertion and the second assertion. 17. The non-transitory computer readable storage medium of claim 16, wherein the prioritization is based at least in part on usage data reflective of a first number of users associated with the first assertion and usage data reflective of a second number of users associated with the second assertion. 18. The non-transitory computer readable storage medium of claim 15, wherein each of the one or more assertions is associated with a category, and wherein the first assertion is determined to be relevant to the first query based at least in part on a category associated with the first query. 19. The non-transitory computer readable storage medium of claim 18, wherein the computer executable instructions further cause the computing system to determine the category associated with the first query. 20. The non-transitory computer readable storage medium of claim 15, wherein the first query is at least one of an explicit query or an inferred query. | A network-based service may be provided for facilitating queries for a number of items, such as travel services. A user may submit a query including criteria for determining one or more relevant items. Based on the submitted query, the network-based service may present the user with information regarding the actions of other similar users of the network-based service, such as searches performed by the other users. Based on this information, the user may elect to supplement the current query to conform to the actions for other users. In some embodiments, actions by other users may be based at least in part on a category of the querying user. By presenting actions of similar users, a current user may be enabled to select the most relevant query terms for identifying a desired item.1. A computer-implemented method comprising:
as implemented by one or more computing devices configured with specific executable instructions,
identifying, from usage data reflective of user activity on a travel service, a first search criterion, wherein the first search criterion is associated with a user;
identifying, from the usage data, a second search criterion, wherein the second search criterion is associated with the user;
determining that the second search criterion was received in response to a presentation of search results corresponding to the first search criterion;
generating a first user interface element corresponding to the first search criterion and the second search criterion, wherein selection of the first user interface element, when presented to an additional user, enables generation of a new travel item query that includes at least the second search criterion;
receiving, from a user computing device, a first travel item query;
determining that the first travel item query includes the first search criterion;
transmitting, to the user computing device, search results corresponding to the first travel item query, for presentation to the additional user in a user interface that includes the first user interface element;
receiving, from the user computing device, selection of the first user interface element;
in response to receiving the selection of the first user interface element:
generating the new travel item query that includes the second search criterion; and
transmitting, to the user computing device, search results corresponding to the new travel item query. 2. The computer-implemented method of claim 1, wherein the first search criterion comprises a first arrival location, and wherein the second search criterion comprises a second arrival location. 3. The computer-implemented method of claim 1 further comprising:
identifying, from the usage data, a third search criterion associated with a second user;
identifying, from the usage data, a fourth search criterion associated with the second user;
determining that the fourth search criterion was received in response to a presentation of search results corresponding to the third search criterion;
generating a second user interface element corresponding to the third search criterion and the fourth search criterion, wherein selection of the second user interface element, when presented to an additional user, enables generation of a second new travel item query that includes at least the fourth criterion;
determining that the first travel item query includes the third search criterion; and
transmitting the second user interface element to the user computing device. 4. The computer-implemented method of claim 1, wherein generating the first user interface element is based at least in part on identifying a threshold number of queries within the usage data, wherein each of the threshold number of queries includes the second search criterion and corresponds to a presentation of search results based on the first search criterion. 5. The computer-implemented method of claim 1, wherein generating the first user interface element is based at least in part on determining a likelihood that transmitting a search result based on the first search criterion corresponds to receiving a query that includes the second search criterion. 6. A system comprising:
a data store configured to store one or more assertions, wherein each of the one or more assertions identifies at least an initial search criterion and a modified search criterion; and a processor in communication with the data store, the processor configured by specific executable instructions to:
receive, from a user computing device, a first query including a first search criterion;
identify, based at least in part on the first search criterion, a first assertion of the one or more assertions, wherein the first assertion identifies the first search criterion and a modified first search criterion;
transmit, to the user computing device, search results corresponding to the first query, and the first assertion;
receive, from the user computing device, selection of a user interface element associated with the first assertion, wherein the selection corresponds to a user request to generate a second query including the modified first search criterion;
generate the second query including the modified first search criterion; and
transmit, to the user computing device, search results corresponding to the second query. 7. The system of claim 6, wherein the processor is further configured to:
generate instructions for displaying a user interface that includes the user interface element; and transmit the instructions for displaying the user interface to the user computing device. 8. The system of claim 6, wherein the first assertion is associated with a first category. 9. The system of claim 8, wherein the processor is further configured to determine, based at least in part on the first search criterion, a category of the first query, and wherein the first assertion is identified based at least in part on the category of the first query. 10. The system of claim 9, wherein the category is determined based at least in part on a user profile associated with the user computing device, a past activity of the user computing device, or a previously acquired travel item associated with the user computing device. 11. The system of claim 6, wherein the processor is further configured to:
receive, from the user computing device, a new query including a new search criterion; generate a new assertion, wherein the new assertion identifies at least the first modified criterion and the new search criterion; and store the new assertion in the data store. 12. The system of claim 6, wherein the first search criterion comprises a travel destination and the modified first search criterion comprises an alternate travel destination. 13. The system of claim 6, wherein the first search criterion comprises a departure date and the modified first search criterion comprises a range of departure dates. 14. The system of claim 6, wherein the processor is further configured to:
determine that a second assertion of the one or more assertions identifies at least the first search criterion; and transmit, to the user computing device, the second assertion. 15. A non-transitory computer readable storage medium having computer executable instructions, wherein the computer executable instructions, when executed by a computing system, cause the computing system to:
maintain one or more assertions, wherein each of the one or more assertions identifies an initial search criterion and a modified search criterion, and wherein each of the one or more assertions enables generation of a new query based at least in part on the modified search criterion; determine, based at least in part on information received from a user computing device, a first query including a first search criterion; determine that a first assertion of the one or more assertions is relevant to the first query, the first assertion identifying the first search criterion and a modified first search criterion; transmit, to the user computing device, the first assertion; receive, from the user computing device, selection of a user interface element associated with the first assertion; generate a second query based at least in part on the modified first search criterion; and transmit, to the user computing device, search results associated with the second query. 16. The non-transitory computer readable storage medium of claim 15, wherein the computer executable instructions further cause the computing system to:
determine that a second assertion of the one or more assertions is relevant to the first query, the second assertion identifying at least the first search criterion; and determine a prioritization of the first assertion and the second assertion. 17. The non-transitory computer readable storage medium of claim 16, wherein the prioritization is based at least in part on usage data reflective of a first number of users associated with the first assertion and usage data reflective of a second number of users associated with the second assertion. 18. The non-transitory computer readable storage medium of claim 15, wherein each of the one or more assertions is associated with a category, and wherein the first assertion is determined to be relevant to the first query based at least in part on a category associated with the first query. 19. The non-transitory computer readable storage medium of claim 18, wherein the computer executable instructions further cause the computing system to determine the category associated with the first query. 20. The non-transitory computer readable storage medium of claim 15, wherein the first query is at least one of an explicit query or an inferred query. | 2,100 |
6,560 | 6,560 | 14,147,399 | 2,176 | A reward program is a type of “loyalty marketing” that typically utilizes a formal scheme to promote or encourage specific actions or behavior by a target audience. For instance, credit card companies have been known to offer “cash back” rewards to cardholders for using a particular credit card over some other form of payment. As another example, airlines are known to offer “frequent flier” mile rewards for electing to fly on a particular airline. The frequent flier miles can be traded in for travel discounts. Loyalty marketing concepts can also be applied to website applications. For instance, a website reward program can allow visitors an opportunity to earn virtual awards, e.g.: badges, titles, points, etc. Visitors can also earn awards that translate into real-world benefits, such as discounts, vouchers, etc. | 1. A method of creating an awards profile comprising:
creating an empty image, wherein creating an empty image further comprises assigning pixels to the empty image; receiving data from a user; rendering the data received from the user and creating a user profile from the received data; creating a user avatar; assigning the user avatar to the empty image; executing a first subset of logical encodings; executing a second subset of logical encodings; executing a first subset of graphical encodings corresponding to the first subset of logical encodings; executing a second subset of graphical encodings corresponding to the second subset of logical encodings; overlaying the first subset of graphical encodings and the second subset of graphical encodings onto the empty image to create the awards profile; and transmitting the awards profile. 2. The method of claim 1, further comprising:
defining the empty image as a fixed two dimensional space; overlaying a trophy case onto a first portion of the fixed two dimensional space; assigning the first subset of logical encodings to the trophy case; and allocating a first subset of Cartesian coordinates to the first subset of logical encodings in the trophy case, wherein the first subset of Cartesian coordinates are predetermined and exist for each badge. 3. The method of claim 2, further comprising:
ordering badges into a trophy case entry queue; selecting a first badge from the trophy case entry queue based on a time stamp; and assigning the first badge from the trophy case entry queue to a first location in the trophy case. 4. The method of claim 3, further comprising:
determining whether there is an additional time-stamped badge; selecting, in response to determining that there is an additional time-stamped badge, the additional time-stamped badge; assigning the additional time-stamped badge to a first location in the trophy case; and assigning the first badge to a second location in the trophy case. 5. The method of claim 4, further comprising:
concluding, in response to determining that there are no additional time-stamped badges, that there are no additional time-stamped badges. 6. The method of claim 5, further comprising:
overlaying a map onto a second portion of the fixed two dimensional space; assigning the second subset of logical encodings to the map; allocating a second subset of Cartesian coordinates corresponding to the second subset of logical encodings to the map, wherein the second subset of Cartesian coordinates are pre-determined and exist for each badge. 7. The method of claim 6, further comprising:
ordering badges into a map entry queue; selecting a first badge from the map entry queue based on the time stamp; determining whether the first badge is an earned badge; assigning, in response to determining that the badge is earned, the earned badge to the map; and stacking more than one earned badge assigned to a same location on the map in reverse chronological order. 8. The method of claim 7, further comprising:
determining, in response to determining that the badge is not an earned badge, whether the badge is a progress badge; assigning, in response to determining that the badge is a progress badge, the progress badge to the map; stacking more than one progress badge assigned to the same location on the map in reverse chronological order; and assigning, in response to determining that the badge is not a progress badge, an unearned badge to the map. 9. The method of claim 8, further comprising:
determining whether there is an additional badge; and accessing, in response to determining that there is an additional badge, the additional badge. 10. A method of assigning a badge to an image comprising:
receiving input; accessing data associated with a badge; predefining unique features associated with the badge and assigning the features to the badge; determining whether the received input is associated with the badge; determining, in response to determining that the received input is associated with the badge, whether the badge is unlocked; determining, in response to determining that the badge is unlocked, whether the badge is a progress badge; determining, in response to determining that the badge is a progress badge, whether the progress badge has been completed; and in response to determining that the progress badge has been completed:
activating the badge; and
time stamping the badge. 11. The method of claim 10, further comprising:
determining, in response to determining that the received input is not associated with the badge, whether additional data is associated with an additional badge. 12. The method of claim 11, further comprising:
accessing, in response to determining that there is additional data associated with the additional badge, the additional data. 13. The method of claim 11, further comprising:
determining, in response to determining that the badge is not unlocked, whether additional data is associated with an additional badge. 14. The method of claim 13, further comprising:
accessing, in response to determining that there is additional data associated with the additional badge, the additional data. 15. The method of claim 10, further comprising, in response to determining that the badge is not a progress badge, activating the badge and time stamping the badge. 16. The method of claim 10, further comprising, in response to determining that the progress badge is not completed, storing the badge. 17. The method of claim 16, further comprising:
determining, in response to storing the badge, whether additional data is associated with an additional badge. 18. The method of claim 18, further comprising:
accessing, in response to determining that there is additional data associated with the additional badge, the additional data. 19. The method of claim 10, further comprising:
ordering the badges chronologically. 20. Computer readable storage hardware with a program stored thereon, wherein the program instructs a processor to perform:
receiving input; accessing data associated with a badge; predefining unique features associated with the badge and assigning the features to the badge; determining whether the received input is associated with the badge; determining, in response to determining that the received input is associated with the badge, whether the badge is unlocked; determining, in response to determining that the badge is unlocked, whether the badge is a progress badge; determining, in response to determining that the badge is a progress badge, whether the progress badge has been completed; and in response to determining that the progress badge has been completed:
activating the badge; and
and time stamping the badge. | A reward program is a type of “loyalty marketing” that typically utilizes a formal scheme to promote or encourage specific actions or behavior by a target audience. For instance, credit card companies have been known to offer “cash back” rewards to cardholders for using a particular credit card over some other form of payment. As another example, airlines are known to offer “frequent flier” mile rewards for electing to fly on a particular airline. The frequent flier miles can be traded in for travel discounts. Loyalty marketing concepts can also be applied to website applications. For instance, a website reward program can allow visitors an opportunity to earn virtual awards, e.g.: badges, titles, points, etc. Visitors can also earn awards that translate into real-world benefits, such as discounts, vouchers, etc.1. A method of creating an awards profile comprising:
creating an empty image, wherein creating an empty image further comprises assigning pixels to the empty image; receiving data from a user; rendering the data received from the user and creating a user profile from the received data; creating a user avatar; assigning the user avatar to the empty image; executing a first subset of logical encodings; executing a second subset of logical encodings; executing a first subset of graphical encodings corresponding to the first subset of logical encodings; executing a second subset of graphical encodings corresponding to the second subset of logical encodings; overlaying the first subset of graphical encodings and the second subset of graphical encodings onto the empty image to create the awards profile; and transmitting the awards profile. 2. The method of claim 1, further comprising:
defining the empty image as a fixed two dimensional space; overlaying a trophy case onto a first portion of the fixed two dimensional space; assigning the first subset of logical encodings to the trophy case; and allocating a first subset of Cartesian coordinates to the first subset of logical encodings in the trophy case, wherein the first subset of Cartesian coordinates are predetermined and exist for each badge. 3. The method of claim 2, further comprising:
ordering badges into a trophy case entry queue; selecting a first badge from the trophy case entry queue based on a time stamp; and assigning the first badge from the trophy case entry queue to a first location in the trophy case. 4. The method of claim 3, further comprising:
determining whether there is an additional time-stamped badge; selecting, in response to determining that there is an additional time-stamped badge, the additional time-stamped badge; assigning the additional time-stamped badge to a first location in the trophy case; and assigning the first badge to a second location in the trophy case. 5. The method of claim 4, further comprising:
concluding, in response to determining that there are no additional time-stamped badges, that there are no additional time-stamped badges. 6. The method of claim 5, further comprising:
overlaying a map onto a second portion of the fixed two dimensional space; assigning the second subset of logical encodings to the map; allocating a second subset of Cartesian coordinates corresponding to the second subset of logical encodings to the map, wherein the second subset of Cartesian coordinates are pre-determined and exist for each badge. 7. The method of claim 6, further comprising:
ordering badges into a map entry queue; selecting a first badge from the map entry queue based on the time stamp; determining whether the first badge is an earned badge; assigning, in response to determining that the badge is earned, the earned badge to the map; and stacking more than one earned badge assigned to a same location on the map in reverse chronological order. 8. The method of claim 7, further comprising:
determining, in response to determining that the badge is not an earned badge, whether the badge is a progress badge; assigning, in response to determining that the badge is a progress badge, the progress badge to the map; stacking more than one progress badge assigned to the same location on the map in reverse chronological order; and assigning, in response to determining that the badge is not a progress badge, an unearned badge to the map. 9. The method of claim 8, further comprising:
determining whether there is an additional badge; and accessing, in response to determining that there is an additional badge, the additional badge. 10. A method of assigning a badge to an image comprising:
receiving input; accessing data associated with a badge; predefining unique features associated with the badge and assigning the features to the badge; determining whether the received input is associated with the badge; determining, in response to determining that the received input is associated with the badge, whether the badge is unlocked; determining, in response to determining that the badge is unlocked, whether the badge is a progress badge; determining, in response to determining that the badge is a progress badge, whether the progress badge has been completed; and in response to determining that the progress badge has been completed:
activating the badge; and
time stamping the badge. 11. The method of claim 10, further comprising:
determining, in response to determining that the received input is not associated with the badge, whether additional data is associated with an additional badge. 12. The method of claim 11, further comprising:
accessing, in response to determining that there is additional data associated with the additional badge, the additional data. 13. The method of claim 11, further comprising:
determining, in response to determining that the badge is not unlocked, whether additional data is associated with an additional badge. 14. The method of claim 13, further comprising:
accessing, in response to determining that there is additional data associated with the additional badge, the additional data. 15. The method of claim 10, further comprising, in response to determining that the badge is not a progress badge, activating the badge and time stamping the badge. 16. The method of claim 10, further comprising, in response to determining that the progress badge is not completed, storing the badge. 17. The method of claim 16, further comprising:
determining, in response to storing the badge, whether additional data is associated with an additional badge. 18. The method of claim 18, further comprising:
accessing, in response to determining that there is additional data associated with the additional badge, the additional data. 19. The method of claim 10, further comprising:
ordering the badges chronologically. 20. Computer readable storage hardware with a program stored thereon, wherein the program instructs a processor to perform:
receiving input; accessing data associated with a badge; predefining unique features associated with the badge and assigning the features to the badge; determining whether the received input is associated with the badge; determining, in response to determining that the received input is associated with the badge, whether the badge is unlocked; determining, in response to determining that the badge is unlocked, whether the badge is a progress badge; determining, in response to determining that the badge is a progress badge, whether the progress badge has been completed; and in response to determining that the progress badge has been completed:
activating the badge; and
and time stamping the badge. | 2,100 |
6,561 | 6,561 | 16,070,570 | 2,119 | In one aspect of the invention a system and method is claimed for providing model parameters for three dimensional fabrication of anatomical structures by obtaining and reconstructing three dimensional image data with a medical imager wherein imaging acquisition parameters of the imaging system and/or reconstruction input parameters of the reconstructor are optimized for maximum geometry precision. Advantageously, the imaging system is further configured to obtain material and/or functional information of the anatomical structure model and that material information is used to incorporate the material information in the anatomical model. | 1. A system for providing 3D model parameters for fabricating a physical 3D anatomical model, comprising:
an imaging system configured to acquire three dimensional image data of an anatomical structure; a reconstructor for reconstructing the acquired three dimensional image data into 3D model parameters; a 3D model providing unit for directly or indirectly providing the 3D model parameters to a device for fabricating the physical 3D anatomical model, a parameter provider for providing imaging acquisition parameters of the imaging system and/or reconstruction input parameters of the reconstructor that are optimized for maximum geometry precision. 2. The system according to claim 1, wherein the parameter provider is implemented as at least one selectable preset parameter setting. 3. The system according to claim 1, wherein the imaging system is further configured to obtain material information of the anatomical structure. 4. The system according to claim 3, wherein the material information comprises one or more of material composition; structural distribution of material, such as material density or porosity; material energy information, such as radiation absorption or reflection properties; perfusion of other materials within the material, such as blood or contrast agent perfusion properties; tissue contrast information, such as contrast of or between hard and soft tissue materials; or temperature information. 5. The system according to claim 1 wherein the imaging system is a 3D x-ray imaging system, such as a computed tomography imaging system, preferably a spectral 3D x-ray imaging system or a phase-contrast x-ray imaging system; a magnetic resonance imaging system; an ultrasound imaging system; a positron emission tomography imaging system; a single photon emission computed tomography system; or combinations thereof. 6. A device for fabricating the physical 3D anatomical structure model that is configured to fabricate the physical anatomical structure model based on 3D model parameters received from a system according to claim 1. 7. The device according to claim 6, that is further configured to adapt fabrication output based on material and/or functional properties within the 3D model parameters. 8. The device according to claim 7, wherein the fabrication output includes different colors; color grades; transparency levels for different material parameters; variations in mechanical properties, such as stiffness or hardness; and/or imaging properties, such ultrasound reflectivity, transmissivity or x-ray absorption. 9. The device according to claim 6 comprising a 3D printer. 10. A method for providing model parameters for three dimensional fabrication of anatomical structures, comprising the step of:
obtaining three dimensional image data of an anatomical structure, wherein the image data was obtained with a medical imager 20 that is configured to acquire the three dimensional image data; reconstructing the acquired three dimensional image data into 3D model parameters. directly or indirectly providing the 3D model parameters to a device for fabricating the physical 3D anatomical structure model,
characterized in that imaging acquisition parameters of the imaging system and/or reconstruction input parameters of the reconstructor are optimized for maximum geometry precision. 11. The method according to claim 10, wherein the medical imager 20 is further configured to obtain material and/or functional information of the anatomical structure model 13. 12. The method according to claim 11, wherein the material information comprises one or more of material composition; structural distribution of material, such as material density; material energy information, such as radiation absorption or reflection properties; perfusion of other materials within the material, such as blood or contrast agent perfusion properties; tissue contrast information, such as contrast of or between hard and soft tissue materials; or temperature information. 13. The method according to claim 11, wherein the anatomical structure model 13 comprises material and/or information of the anatomical model. 14. The method for fabricating a physical 3D anatomical structure model comprising the steps of method of claim 10 followed by fabricating the physical anatomical structure model based on the 3D model parameters, preferably by 3D printing. 15. A computer program product that, when running on a computer, performs the step of claim 14. | In one aspect of the invention a system and method is claimed for providing model parameters for three dimensional fabrication of anatomical structures by obtaining and reconstructing three dimensional image data with a medical imager wherein imaging acquisition parameters of the imaging system and/or reconstruction input parameters of the reconstructor are optimized for maximum geometry precision. Advantageously, the imaging system is further configured to obtain material and/or functional information of the anatomical structure model and that material information is used to incorporate the material information in the anatomical model.1. A system for providing 3D model parameters for fabricating a physical 3D anatomical model, comprising:
an imaging system configured to acquire three dimensional image data of an anatomical structure; a reconstructor for reconstructing the acquired three dimensional image data into 3D model parameters; a 3D model providing unit for directly or indirectly providing the 3D model parameters to a device for fabricating the physical 3D anatomical model, a parameter provider for providing imaging acquisition parameters of the imaging system and/or reconstruction input parameters of the reconstructor that are optimized for maximum geometry precision. 2. The system according to claim 1, wherein the parameter provider is implemented as at least one selectable preset parameter setting. 3. The system according to claim 1, wherein the imaging system is further configured to obtain material information of the anatomical structure. 4. The system according to claim 3, wherein the material information comprises one or more of material composition; structural distribution of material, such as material density or porosity; material energy information, such as radiation absorption or reflection properties; perfusion of other materials within the material, such as blood or contrast agent perfusion properties; tissue contrast information, such as contrast of or between hard and soft tissue materials; or temperature information. 5. The system according to claim 1 wherein the imaging system is a 3D x-ray imaging system, such as a computed tomography imaging system, preferably a spectral 3D x-ray imaging system or a phase-contrast x-ray imaging system; a magnetic resonance imaging system; an ultrasound imaging system; a positron emission tomography imaging system; a single photon emission computed tomography system; or combinations thereof. 6. A device for fabricating the physical 3D anatomical structure model that is configured to fabricate the physical anatomical structure model based on 3D model parameters received from a system according to claim 1. 7. The device according to claim 6, that is further configured to adapt fabrication output based on material and/or functional properties within the 3D model parameters. 8. The device according to claim 7, wherein the fabrication output includes different colors; color grades; transparency levels for different material parameters; variations in mechanical properties, such as stiffness or hardness; and/or imaging properties, such ultrasound reflectivity, transmissivity or x-ray absorption. 9. The device according to claim 6 comprising a 3D printer. 10. A method for providing model parameters for three dimensional fabrication of anatomical structures, comprising the step of:
obtaining three dimensional image data of an anatomical structure, wherein the image data was obtained with a medical imager 20 that is configured to acquire the three dimensional image data; reconstructing the acquired three dimensional image data into 3D model parameters. directly or indirectly providing the 3D model parameters to a device for fabricating the physical 3D anatomical structure model,
characterized in that imaging acquisition parameters of the imaging system and/or reconstruction input parameters of the reconstructor are optimized for maximum geometry precision. 11. The method according to claim 10, wherein the medical imager 20 is further configured to obtain material and/or functional information of the anatomical structure model 13. 12. The method according to claim 11, wherein the material information comprises one or more of material composition; structural distribution of material, such as material density; material energy information, such as radiation absorption or reflection properties; perfusion of other materials within the material, such as blood or contrast agent perfusion properties; tissue contrast information, such as contrast of or between hard and soft tissue materials; or temperature information. 13. The method according to claim 11, wherein the anatomical structure model 13 comprises material and/or information of the anatomical model. 14. The method for fabricating a physical 3D anatomical structure model comprising the steps of method of claim 10 followed by fabricating the physical anatomical structure model based on the 3D model parameters, preferably by 3D printing. 15. A computer program product that, when running on a computer, performs the step of claim 14. | 2,100 |
6,562 | 6,562 | 14,616,667 | 2,152 | A method for presenting output returned by a command-line interface is disclosed. In one embodiment, such a method submits, by way of a command-line interface (CLI), a command to retrieve a list of resources. The method further submits, in association with the command, an indicator to compress the list. In response to receiving the command and indicator, the method retrieves the list of resources and compresses the list such that resources with identical attributes are presented as a single tuple in the list. Such a tuple may, in certain embodiments, identify the resources with identical attributes as a range of resources and/or as a comma delimited list of resources. The tuple may also, in certain embodiments, identify how many resources with identical attributes are represented by the tuple. A corresponding system and computer program product are also disclosed. | 1. A method for presenting output returned by a command-line interface, the method comprising:
submitting, by way of a command-line interface (CLI), a command to retrieve a list of resources; submitting, in association with the command, an indicator to compress the list; retrieving the list of resources; and compressing the list such that resources with identical attributes are presented as a single tuple in the list. 2. The method of claim 1, wherein the tuple identifies the resources with identical attributes in a column of the tuple. 3. The method of claim 1, wherein the tuple identifies the resources with identical attributes as a range of resources. 4. The method of claim 1, wherein the tuple identifies the resources with identical attributes in a comma delimited list of resources. 5. The method of claim 1, wherein the tuple identifies how many resources with identical attributes are represented by the tuple. 6. The method of claim 1, wherein the resources with identical attributes include contiguous resources. 7. The method of claim 1, wherein the resources with identical attributes include non-contiguous resources. 8. The method of claim 1, wherein the identical attributes are a user-selected set of identical attributes. 9. A computer program product for presenting output returned by a command-line interface, the computer program product comprising a computer-readable storage medium having computer-usable program code embodied therein, the computer-usable program code comprising:
computer-usable program code to submit, by way of a command-line interface (CLI), a command to retrieve a list of resources; computer-usable program code to submit, in association with the command, an indicator to compress the list; computer-usable program code to retrieve the list of resources; and computer-usable program code to compress the list such that resources with identical attributes are presented as a single tuple in the list. 10. The computer program product of claim 9, wherein the tuple identifies the resources with identical attributes in a column of the tuple. 11. The computer program product of claim 9, wherein the tuple identifies the resources with identical attributes as a range of resources. 12. The computer program product of claim 9, wherein the tuple identifies the resources with identical attributes in a comma delimited list of resources. 13. The computer program product of claim 9, wherein the tuple identifies how many resources with identical attributes are represented by the tuple. 14. The computer program product of claim 9, wherein the resources with identical attributes include contiguous resources. 15. The computer program product of claim 9, wherein the resources with identical attributes include non-contiguous resources. 16. The computer program product of claim 9, wherein the identical attributes are a user-selected set of identical attributes. 17. A system for presenting output returned by a command-line interface, the system comprising:
at least one processor; at least one memory device coupled to the at least one processor and storing instructions for execution on the at least one processor, the instructions causing the at least one processor to:
submit, by way of a command-line interface (CLI), a command to retrieve a list of resources;
submit, in association with the command, an indicator to compress the list;
retrieve the list of resources; and
compress the list such that resources with identical attributes are presented as a single tuple in the list. 18. The system of claim 17, wherein the tuple identifies the resources with identical attributes as at least one of: a range of resources and a comma delimited list of resources. 19. The system of claim 17, wherein the tuple identifies how many resources with identical attributes are represented by the tuple. 20. The system of claim 17, wherein the identical attributes are a user-selected set of identical attributes. | A method for presenting output returned by a command-line interface is disclosed. In one embodiment, such a method submits, by way of a command-line interface (CLI), a command to retrieve a list of resources. The method further submits, in association with the command, an indicator to compress the list. In response to receiving the command and indicator, the method retrieves the list of resources and compresses the list such that resources with identical attributes are presented as a single tuple in the list. Such a tuple may, in certain embodiments, identify the resources with identical attributes as a range of resources and/or as a comma delimited list of resources. The tuple may also, in certain embodiments, identify how many resources with identical attributes are represented by the tuple. A corresponding system and computer program product are also disclosed.1. A method for presenting output returned by a command-line interface, the method comprising:
submitting, by way of a command-line interface (CLI), a command to retrieve a list of resources; submitting, in association with the command, an indicator to compress the list; retrieving the list of resources; and compressing the list such that resources with identical attributes are presented as a single tuple in the list. 2. The method of claim 1, wherein the tuple identifies the resources with identical attributes in a column of the tuple. 3. The method of claim 1, wherein the tuple identifies the resources with identical attributes as a range of resources. 4. The method of claim 1, wherein the tuple identifies the resources with identical attributes in a comma delimited list of resources. 5. The method of claim 1, wherein the tuple identifies how many resources with identical attributes are represented by the tuple. 6. The method of claim 1, wherein the resources with identical attributes include contiguous resources. 7. The method of claim 1, wherein the resources with identical attributes include non-contiguous resources. 8. The method of claim 1, wherein the identical attributes are a user-selected set of identical attributes. 9. A computer program product for presenting output returned by a command-line interface, the computer program product comprising a computer-readable storage medium having computer-usable program code embodied therein, the computer-usable program code comprising:
computer-usable program code to submit, by way of a command-line interface (CLI), a command to retrieve a list of resources; computer-usable program code to submit, in association with the command, an indicator to compress the list; computer-usable program code to retrieve the list of resources; and computer-usable program code to compress the list such that resources with identical attributes are presented as a single tuple in the list. 10. The computer program product of claim 9, wherein the tuple identifies the resources with identical attributes in a column of the tuple. 11. The computer program product of claim 9, wherein the tuple identifies the resources with identical attributes as a range of resources. 12. The computer program product of claim 9, wherein the tuple identifies the resources with identical attributes in a comma delimited list of resources. 13. The computer program product of claim 9, wherein the tuple identifies how many resources with identical attributes are represented by the tuple. 14. The computer program product of claim 9, wherein the resources with identical attributes include contiguous resources. 15. The computer program product of claim 9, wherein the resources with identical attributes include non-contiguous resources. 16. The computer program product of claim 9, wherein the identical attributes are a user-selected set of identical attributes. 17. A system for presenting output returned by a command-line interface, the system comprising:
at least one processor; at least one memory device coupled to the at least one processor and storing instructions for execution on the at least one processor, the instructions causing the at least one processor to:
submit, by way of a command-line interface (CLI), a command to retrieve a list of resources;
submit, in association with the command, an indicator to compress the list;
retrieve the list of resources; and
compress the list such that resources with identical attributes are presented as a single tuple in the list. 18. The system of claim 17, wherein the tuple identifies the resources with identical attributes as at least one of: a range of resources and a comma delimited list of resources. 19. The system of claim 17, wherein the tuple identifies how many resources with identical attributes are represented by the tuple. 20. The system of claim 17, wherein the identical attributes are a user-selected set of identical attributes. | 2,100 |
6,563 | 6,563 | 16,041,232 | 2,153 | The present invention relates to summarizing cross-network user behavioral data. The summarizing cross-network user behavioral data may particularly include publishing the data to one or more data structures that become accessible to a server hosting an authorized domain when a user accesses the authorized domain. | 1. (canceled) 2. A computer-implemented method, implemented, at least in part, by a client computer, the method comprising:
collecting, by the client computer, cross-network user behavior data related to a user's interactions on the client computer with a plurality of web sites; summarizing, by the client computer, the collected cross-network user behavior data on the client computer; publishing, by the client computer, the summarized cross-network user behavior data on the client computer to one or more memory structures on the client computer; and in response to the user accessing an authorized domain via the client computer via a network, providing, by the client computer, at least some of the summarized cross-network user behavior data in the one or more memory structures on the client computer to a server at the authorized domain. 3. The method of claim 2, wherein the summarizing includes, for a plurality of subject categories, one or more of:
categorizing recency of the user visiting a web site on the client computer in at least some of the plurality of subject categories, categorizing user category involvement from the user visiting the website on the client computer in at least some of the subject categories by rolling up indicators of visits into categorical time segments, categorizing recency of selections of at least one banner advertisement on the client computer, or categorizing user category involvement from user selections of the at least one banner advertisement on the client computer. 4. The method of claim 3, wherein the categorizing the user category involvement includes rolling up the indicators of visits into non-overlapping categorical time segments of differing lengths. 5. The method of claim 3, wherein the categorizing the user category involvement includes representing granular time segments with flags to indicate user category involvement during the granular time segment and summarizing a portion of the granular time segments by aggregation into categorical time segments. 6. The method of claim 2, further comprising:
prioritizing a plurality of subject categories, selecting at least one subject category of the plurality of subject categories, and publishing the summarized cross-network user behavior data for the plurality of subject categories to a single memory structure. 7. The method of claim 2, wherein the cross-network user behavior data includes data relating to visits to the plurality of web sites or selections of banner advertisements that are not all associated with a behavioral data collection network. 8. The method of claim 2, wherein the cross-network user behavior data is further related to selections of banner advertisements that are not all associated with the portal. 9. The method of claim 2, wherein the cross-network user behavior data includes data relating to visits to the plurality of web sites or selections of banner advertisements that are not all associated with a virtual storefront. 10. The method of claim 2, wherein the cross-network user behavior data is further related to selections of banner advertisements that are not all associated with the content provider. 11. The method of claim 2, wherein the cross-network user behavior data includes data relating to behavioral data corresponding to a plurality of visits to the plurality of web sites or selections of banner advertisements that are not all associated with a behavioral data collection network. 12. The method of claim 2, wherein the publishing takes place on a periodic basis. 13. The method of claim 2, wherein the publishing takes place in response to one or more web site visit or one or more banner advertisement selection. 14. The method of claim 2, further comprising, receiving at the client computer a message or an advertisement targeted using the summarized cross-network user behavior data published to the one or more memory structures on the client computer. 15. The method of claim 2, wherein the cross-network user behavior data includes data relating to entries of a URL in a browser address window of the client computer, or selections of a URL hyperlink. 16. The method of claim 2, wherein the one or more memory structures include one or more cookies. 17. The method of claim 2, further comprising, compressing and encrypting the summarized cross-network user behavior data in the one or more memory structures on the client computer. 18. A client computer to publish cross-network user behavior data, the client computer comprising:
at least one or more processor coupled to one or more memory structures, the at least one or more processor configured to:
collect cross-network user behavior data related to a user's interactions on the client computer with a plurality of web sites;
summarize the collected cross-network user behavior data on the client computer;
publish the summarized cross-network user behavior data on the client computer to the one or more memory structures on the client computer; and
in response to the user accessing an authorized domain via the client computer via a network, provide at least some of the summarized cross-network user behavior data in the one or more memory structures on the client computer to a server at the authorized domain. 19. The client computer of claim 18, wherein the at least one or more processor is further configured to:
prioritize a plurality of subject categories, select at least one subject category of the plurality of subject categories, and publish the summarized cross-network user behavior data for the plurality of subject categories to a single memory structure. 20. The client computer of claim 18, wherein the cross-network user behavior data includes data relating to visits to the plurality of web sites or selections of banner advertisements that are not all associated with a behavioral data collection network. 21. A non-transitory computer-readable medium storing executable instructions that, in response to execution, cause a client computer to perform operations comprising:
collecting cross-network user behavior data related to a user's interactions on the client computer with a plurality of web sites; summarizing the collected cross-network user behavior data on the client computer; publishing the summarized cross-network user behavior data on the client computer to one or more memory structures on the client computer; and in response to the user accessing an authorized domain via the client computer via a network, providing at least some of the summarized cross-network user behavior data in the one or more memory structures on the client computer to a server at the authorized domain. | The present invention relates to summarizing cross-network user behavioral data. The summarizing cross-network user behavioral data may particularly include publishing the data to one or more data structures that become accessible to a server hosting an authorized domain when a user accesses the authorized domain.1. (canceled) 2. A computer-implemented method, implemented, at least in part, by a client computer, the method comprising:
collecting, by the client computer, cross-network user behavior data related to a user's interactions on the client computer with a plurality of web sites; summarizing, by the client computer, the collected cross-network user behavior data on the client computer; publishing, by the client computer, the summarized cross-network user behavior data on the client computer to one or more memory structures on the client computer; and in response to the user accessing an authorized domain via the client computer via a network, providing, by the client computer, at least some of the summarized cross-network user behavior data in the one or more memory structures on the client computer to a server at the authorized domain. 3. The method of claim 2, wherein the summarizing includes, for a plurality of subject categories, one or more of:
categorizing recency of the user visiting a web site on the client computer in at least some of the plurality of subject categories, categorizing user category involvement from the user visiting the website on the client computer in at least some of the subject categories by rolling up indicators of visits into categorical time segments, categorizing recency of selections of at least one banner advertisement on the client computer, or categorizing user category involvement from user selections of the at least one banner advertisement on the client computer. 4. The method of claim 3, wherein the categorizing the user category involvement includes rolling up the indicators of visits into non-overlapping categorical time segments of differing lengths. 5. The method of claim 3, wherein the categorizing the user category involvement includes representing granular time segments with flags to indicate user category involvement during the granular time segment and summarizing a portion of the granular time segments by aggregation into categorical time segments. 6. The method of claim 2, further comprising:
prioritizing a plurality of subject categories, selecting at least one subject category of the plurality of subject categories, and publishing the summarized cross-network user behavior data for the plurality of subject categories to a single memory structure. 7. The method of claim 2, wherein the cross-network user behavior data includes data relating to visits to the plurality of web sites or selections of banner advertisements that are not all associated with a behavioral data collection network. 8. The method of claim 2, wherein the cross-network user behavior data is further related to selections of banner advertisements that are not all associated with the portal. 9. The method of claim 2, wherein the cross-network user behavior data includes data relating to visits to the plurality of web sites or selections of banner advertisements that are not all associated with a virtual storefront. 10. The method of claim 2, wherein the cross-network user behavior data is further related to selections of banner advertisements that are not all associated with the content provider. 11. The method of claim 2, wherein the cross-network user behavior data includes data relating to behavioral data corresponding to a plurality of visits to the plurality of web sites or selections of banner advertisements that are not all associated with a behavioral data collection network. 12. The method of claim 2, wherein the publishing takes place on a periodic basis. 13. The method of claim 2, wherein the publishing takes place in response to one or more web site visit or one or more banner advertisement selection. 14. The method of claim 2, further comprising, receiving at the client computer a message or an advertisement targeted using the summarized cross-network user behavior data published to the one or more memory structures on the client computer. 15. The method of claim 2, wherein the cross-network user behavior data includes data relating to entries of a URL in a browser address window of the client computer, or selections of a URL hyperlink. 16. The method of claim 2, wherein the one or more memory structures include one or more cookies. 17. The method of claim 2, further comprising, compressing and encrypting the summarized cross-network user behavior data in the one or more memory structures on the client computer. 18. A client computer to publish cross-network user behavior data, the client computer comprising:
at least one or more processor coupled to one or more memory structures, the at least one or more processor configured to:
collect cross-network user behavior data related to a user's interactions on the client computer with a plurality of web sites;
summarize the collected cross-network user behavior data on the client computer;
publish the summarized cross-network user behavior data on the client computer to the one or more memory structures on the client computer; and
in response to the user accessing an authorized domain via the client computer via a network, provide at least some of the summarized cross-network user behavior data in the one or more memory structures on the client computer to a server at the authorized domain. 19. The client computer of claim 18, wherein the at least one or more processor is further configured to:
prioritize a plurality of subject categories, select at least one subject category of the plurality of subject categories, and publish the summarized cross-network user behavior data for the plurality of subject categories to a single memory structure. 20. The client computer of claim 18, wherein the cross-network user behavior data includes data relating to visits to the plurality of web sites or selections of banner advertisements that are not all associated with a behavioral data collection network. 21. A non-transitory computer-readable medium storing executable instructions that, in response to execution, cause a client computer to perform operations comprising:
collecting cross-network user behavior data related to a user's interactions on the client computer with a plurality of web sites; summarizing the collected cross-network user behavior data on the client computer; publishing the summarized cross-network user behavior data on the client computer to one or more memory structures on the client computer; and in response to the user accessing an authorized domain via the client computer via a network, providing at least some of the summarized cross-network user behavior data in the one or more memory structures on the client computer to a server at the authorized domain. | 2,100 |
6,564 | 6,564 | 14,028,913 | 2,119 | User interface sessions in a user interface device are initiated or resumed according to stored state data. A session request is received from a first client device. A user profile associated with the session request is identified and a determination made as to whether a previous session exists. If no previous session exists, a new session is instantiated using a default session configuration. If a previous session exists, a new session is instantiated according to the previous session. | 1. A method of initiating a user interface session on a first client device for controlling a process plant, the method comprising:
receiving from the first client device a session request; identifying a user profile associated with the session request; determining whether a previous session exists; and if no previous session exists, instantiating a new session using a default session configuration; or if a previous session exists, instantiating a new session according to the previous session. 2. A method according to claim 1, wherein identifying a user profile associated with the session request comprises receiving from the first client device a user identifier associated with the user profile, the user identifier currently logged into the first client device. 3. A method according to claim 1, wherein identifying a user profile associated with the session request comprises receiving from the first client device a user identifier associated with the user profile, the user identifier currently logged into a second client device. 4. A method according to claim 1, further comprising:
transmitting to the second client device a request to instantiate on the first client device a session according to the session operating on the second client device; and receiving from the second client device a confirmation. 5. A method according to claim 1, wherein determining whether a previous session exists comprises requesting from the first client device a session identifier associated with the previous session. 6. A method according to claim 1, wherein determining whether a previous session exists comprises receiving from the first client device, in response to the session identifier request, a session identifier. 7. A method according to claim 1, wherein determining whether a previous session exists comprises receiving with the session request a session identifier. 8. A method according to claim 1, wherein instantiating a new session according to the previous session comprises:
determining whether a session identifier was received with the session request; if a session identifier was received with the session request, instantiating a session associated with the session identifier; or if no session identifier was received with the session request, instantiating a session associated with a most recent session. 9. A method according to claim 1, wherein instantiating a session associated with a most recent session comprises instantiating a session associated with a most recent session of a user identifier associated with the first client device. | User interface sessions in a user interface device are initiated or resumed according to stored state data. A session request is received from a first client device. A user profile associated with the session request is identified and a determination made as to whether a previous session exists. If no previous session exists, a new session is instantiated using a default session configuration. If a previous session exists, a new session is instantiated according to the previous session.1. A method of initiating a user interface session on a first client device for controlling a process plant, the method comprising:
receiving from the first client device a session request; identifying a user profile associated with the session request; determining whether a previous session exists; and if no previous session exists, instantiating a new session using a default session configuration; or if a previous session exists, instantiating a new session according to the previous session. 2. A method according to claim 1, wherein identifying a user profile associated with the session request comprises receiving from the first client device a user identifier associated with the user profile, the user identifier currently logged into the first client device. 3. A method according to claim 1, wherein identifying a user profile associated with the session request comprises receiving from the first client device a user identifier associated with the user profile, the user identifier currently logged into a second client device. 4. A method according to claim 1, further comprising:
transmitting to the second client device a request to instantiate on the first client device a session according to the session operating on the second client device; and receiving from the second client device a confirmation. 5. A method according to claim 1, wherein determining whether a previous session exists comprises requesting from the first client device a session identifier associated with the previous session. 6. A method according to claim 1, wherein determining whether a previous session exists comprises receiving from the first client device, in response to the session identifier request, a session identifier. 7. A method according to claim 1, wherein determining whether a previous session exists comprises receiving with the session request a session identifier. 8. A method according to claim 1, wherein instantiating a new session according to the previous session comprises:
determining whether a session identifier was received with the session request; if a session identifier was received with the session request, instantiating a session associated with the session identifier; or if no session identifier was received with the session request, instantiating a session associated with a most recent session. 9. A method according to claim 1, wherein instantiating a session associated with a most recent session comprises instantiating a session associated with a most recent session of a user identifier associated with the first client device. | 2,100 |
6,565 | 6,565 | 16,098,121 | 2,174 | A monitor includes: a display device; a first Universal Serial Bus (USB) upstream port; and a second USB upstream port. In response to a new host being connected to one of the USB upstream ports when the other of the USB upstream ports has active status by already supporting an active host, the monitor is to display on the display device a prompt to a user to switch active status to the USB upstream port connected to the new host. | 1. A monitor comprising:
a display device; a first Universal Serial Bus (USB) upstream port; and a second USB upstream port; wherein, in response to a new host being connected to one of the USB upstream ports when the other of the USB upstream ports has active status by already supporting an active host, the monitor displaying on the display device a prompt to a user to switch active status to the USB upstream port connected to the new host. 2. The monitor of claim 1, wherein the first USB upstream port is a USB 3.0 upstream port and the second USB upstream port is a USB-C upstream port. 3. The monitor of claim 1, wherein the prompt comprises an On-Screen Display (OSD) indicating a new host has been detected. 4. The monitor of claim 1, wherein the prompt comprises an On-Screen Display (OSD) indicating functionality of a number of hot-keys, one of the hot-keys having a function to switch active status from a currently active one of the USB ports to the other of the USB ports. 5. The monitor of claim 4, wherein, if the hot-keys do not normally include a key for switching active status among the USB ports, the monitor over-rides an establish function of a first of the hot-keys, making a function of the first hot-key to switch active status among the USB ports. 6. The monitor of claim 5, wherein the established function of the first hot-key is over-ridden for a set amount of time after which, if the first hot-key has not been actuated, the first hot-key is returned to its established function. 7. The monitor of claim 5, wherein the monitor changes an icon in the OSD for the first hot-key when over-riding the established function of the first hot-key. 8. The monitor of claim 1, wherein the display device is a touch-sensitive display, and the prompt comprises a button displayed on the touch-sensitive display to switch active status to the USB port connected to the new host. 9. The monitor of claim 1, wherein the prompt comprises a menu in an On-Screen Display (OSD), the menu including an option to select either of the USB ports as having active status. 10. The monitor of claim 9, wherein the menu comprises an automated option under which active status is given to a first of the USB ports to receive a connection to an active host. 11. A monitor comprising:
a display device; a first Universal Serial Bus (USB) upstream port; a second USB upstream port; and a processor for outputting an on-screen display (OSD) on the display device; wherein, the OSD comprises controls for selecting which of the USB upstream ports is given active status; and, in response to a new host being connected to one of the USB upstream ports when the other of the USB upstream ports has active status by already supporting an active host, the OSD to prompt a user for input whether to switch active status to the USB upstream port connected to the new host. 12. A method comprising:
with a monitor comprising a display device, a first Universal Serial Bus (USB) upstream port and a second USB upstream port, detecting a new host being connected to one of the USB upstream ports when the other of the USB upstream ports has active status by already supporting an active host; and, in response to the new host being connected to one of the USB upstream ports, displaying on the display device a prompt to a user to switch active status to the USB upstream port connected to the new host. 13. The method of claim 12, wherein the prompt comprises an On-Screen Display (OSD) indicating a new host has been detected. 14. The method of claim 12, wherein the prompt comprises an On-Screen Display (OSD) indicating functionality of a number of hot-keys, one of the hot-keys having a function to switch active status from a currently active one of the USB ports to the other of the USB ports. 15. The method of claim 12, wherein the prompt comprises a menu in an On-Screen Display (OSD), the menu comprising options to select either of the USB ports as having active status and an option to select an automatic functionality under which active status is given to a first of the USB ports to receive a connection to an active host and is retained by that USB port as long as that host is active. | A monitor includes: a display device; a first Universal Serial Bus (USB) upstream port; and a second USB upstream port. In response to a new host being connected to one of the USB upstream ports when the other of the USB upstream ports has active status by already supporting an active host, the monitor is to display on the display device a prompt to a user to switch active status to the USB upstream port connected to the new host.1. A monitor comprising:
a display device; a first Universal Serial Bus (USB) upstream port; and a second USB upstream port; wherein, in response to a new host being connected to one of the USB upstream ports when the other of the USB upstream ports has active status by already supporting an active host, the monitor displaying on the display device a prompt to a user to switch active status to the USB upstream port connected to the new host. 2. The monitor of claim 1, wherein the first USB upstream port is a USB 3.0 upstream port and the second USB upstream port is a USB-C upstream port. 3. The monitor of claim 1, wherein the prompt comprises an On-Screen Display (OSD) indicating a new host has been detected. 4. The monitor of claim 1, wherein the prompt comprises an On-Screen Display (OSD) indicating functionality of a number of hot-keys, one of the hot-keys having a function to switch active status from a currently active one of the USB ports to the other of the USB ports. 5. The monitor of claim 4, wherein, if the hot-keys do not normally include a key for switching active status among the USB ports, the monitor over-rides an establish function of a first of the hot-keys, making a function of the first hot-key to switch active status among the USB ports. 6. The monitor of claim 5, wherein the established function of the first hot-key is over-ridden for a set amount of time after which, if the first hot-key has not been actuated, the first hot-key is returned to its established function. 7. The monitor of claim 5, wherein the monitor changes an icon in the OSD for the first hot-key when over-riding the established function of the first hot-key. 8. The monitor of claim 1, wherein the display device is a touch-sensitive display, and the prompt comprises a button displayed on the touch-sensitive display to switch active status to the USB port connected to the new host. 9. The monitor of claim 1, wherein the prompt comprises a menu in an On-Screen Display (OSD), the menu including an option to select either of the USB ports as having active status. 10. The monitor of claim 9, wherein the menu comprises an automated option under which active status is given to a first of the USB ports to receive a connection to an active host. 11. A monitor comprising:
a display device; a first Universal Serial Bus (USB) upstream port; a second USB upstream port; and a processor for outputting an on-screen display (OSD) on the display device; wherein, the OSD comprises controls for selecting which of the USB upstream ports is given active status; and, in response to a new host being connected to one of the USB upstream ports when the other of the USB upstream ports has active status by already supporting an active host, the OSD to prompt a user for input whether to switch active status to the USB upstream port connected to the new host. 12. A method comprising:
with a monitor comprising a display device, a first Universal Serial Bus (USB) upstream port and a second USB upstream port, detecting a new host being connected to one of the USB upstream ports when the other of the USB upstream ports has active status by already supporting an active host; and, in response to the new host being connected to one of the USB upstream ports, displaying on the display device a prompt to a user to switch active status to the USB upstream port connected to the new host. 13. The method of claim 12, wherein the prompt comprises an On-Screen Display (OSD) indicating a new host has been detected. 14. The method of claim 12, wherein the prompt comprises an On-Screen Display (OSD) indicating functionality of a number of hot-keys, one of the hot-keys having a function to switch active status from a currently active one of the USB ports to the other of the USB ports. 15. The method of claim 12, wherein the prompt comprises a menu in an On-Screen Display (OSD), the menu comprising options to select either of the USB ports as having active status and an option to select an automatic functionality under which active status is given to a first of the USB ports to receive a connection to an active host and is retained by that USB port as long as that host is active. | 2,100 |
6,566 | 6,566 | 16,222,400 | 2,119 | The invention relates to an apparatus and a method for controlling a ventilator by means of a detection unit for control commands, wherein the detection unit detects control commands of a user in a detection region of the detection unit, the detection unit comprising at least one sensor for control commands, a memory, an apparatus for producing digital control commands and an interface for coupling to the ventilator and for transmitting the control commands to the ventilator. | 1. An apparatus for controlling a ventilator by means of a detection unit for control commands, wherein the detection unit detects control commands of a user in a detection region of the detection unit, the detection unit comprising at least one sensor for control commands, a memory, an device for producing digital control commands, and an interface for coupling to the ventilator and for transmitting the control commands to the ventilator. 2. The apparatus of claim 1, wherein the ventilator comprises an interface to the detection unit. 3. The apparatus of claim 1, wherein the detection unit is embodied as a camera. 4. The apparatus of claim 1, wherein the detection unit is embodied as a 3D camera or a TOF camera with a detection region. 5. The apparatus of claim 1, wherein the detection unit is configured to process and evaluate image data or gestures detected in the detection region. 6. The apparatus of claim 1, wherein the detection unit compares current image data with predetermined image data for purposes of evaluating movement or gesture of a user, the predetermined image data being stored in the memory. 7. The apparatus of claim 1, wherein at least one application, an interaction and/or a control of different functions of the ventilator is/are activatable or deactivatable on the basis of a gesture detected in the detection region. 8. The apparatus of claim 1, wherein the detection unit is coupled to an illumination unit for illuminating the detection region. 9. The apparatus of claim 8, wherein the illumination unit emits light in a visible range and/or in an infrared spectral range. 10. The apparatus of claim 8, wherein the illumination unit projects a virtual operating element into the detection region. 11. The apparatus of claim 8, wherein the illumination unit projects a virtual image of display and/or operating elements of the ventilator into the detection region. 12. The apparatus of claim 8, wherein the illumination unit projects a virtual image of the ventilator into the detection region. 13. The apparatus of claim 8, wherein the illumination unit projects measurement values or evaluations of the ventilator into the detection region. 14. The apparatus of claim 1, wherein the detection unit is arranged in or on the ventilator. 15. The apparatus of claim 1, wherein the detection unit is embodied as a remote control. 16. The apparatus of claim 8, wherein the illumination unit is arranged in or on the detection unit or the ventilator. 17. The apparatus of claim 1, wherein the detection unit comprises a speech sensor and identifies voice commands and converts the voice commands into digital control commands and transmits the voice commands to the ventilator via the interface, the detection unit being configured to authenticate voice commands (23) and generating an optical and/or auditory and/or graphical response for a user before the control command is implemented. 18. A method for controlling a ventilator by means of a detection unit for control commands, wherein the detection unit detects control commands of a user in a detection region of the detection unit, the detection unit comprising at least one sensor for control commands, a memory, an apparatus for producing digital control commands and an interface for coupling to the ventilator and for transmitting the control commands to the ventilator. 19. The apparatus of claim 1, wherein the detection unit is configured for processing and evaluating image data or gestures detected in the detection region and is embodied as a camera. 20. The apparatus of claim 16, wherein the illumination unit projects a virtual image and measurement values or evaluations of the ventilator into the detection region. | The invention relates to an apparatus and a method for controlling a ventilator by means of a detection unit for control commands, wherein the detection unit detects control commands of a user in a detection region of the detection unit, the detection unit comprising at least one sensor for control commands, a memory, an apparatus for producing digital control commands and an interface for coupling to the ventilator and for transmitting the control commands to the ventilator.1. An apparatus for controlling a ventilator by means of a detection unit for control commands, wherein the detection unit detects control commands of a user in a detection region of the detection unit, the detection unit comprising at least one sensor for control commands, a memory, an device for producing digital control commands, and an interface for coupling to the ventilator and for transmitting the control commands to the ventilator. 2. The apparatus of claim 1, wherein the ventilator comprises an interface to the detection unit. 3. The apparatus of claim 1, wherein the detection unit is embodied as a camera. 4. The apparatus of claim 1, wherein the detection unit is embodied as a 3D camera or a TOF camera with a detection region. 5. The apparatus of claim 1, wherein the detection unit is configured to process and evaluate image data or gestures detected in the detection region. 6. The apparatus of claim 1, wherein the detection unit compares current image data with predetermined image data for purposes of evaluating movement or gesture of a user, the predetermined image data being stored in the memory. 7. The apparatus of claim 1, wherein at least one application, an interaction and/or a control of different functions of the ventilator is/are activatable or deactivatable on the basis of a gesture detected in the detection region. 8. The apparatus of claim 1, wherein the detection unit is coupled to an illumination unit for illuminating the detection region. 9. The apparatus of claim 8, wherein the illumination unit emits light in a visible range and/or in an infrared spectral range. 10. The apparatus of claim 8, wherein the illumination unit projects a virtual operating element into the detection region. 11. The apparatus of claim 8, wherein the illumination unit projects a virtual image of display and/or operating elements of the ventilator into the detection region. 12. The apparatus of claim 8, wherein the illumination unit projects a virtual image of the ventilator into the detection region. 13. The apparatus of claim 8, wherein the illumination unit projects measurement values or evaluations of the ventilator into the detection region. 14. The apparatus of claim 1, wherein the detection unit is arranged in or on the ventilator. 15. The apparatus of claim 1, wherein the detection unit is embodied as a remote control. 16. The apparatus of claim 8, wherein the illumination unit is arranged in or on the detection unit or the ventilator. 17. The apparatus of claim 1, wherein the detection unit comprises a speech sensor and identifies voice commands and converts the voice commands into digital control commands and transmits the voice commands to the ventilator via the interface, the detection unit being configured to authenticate voice commands (23) and generating an optical and/or auditory and/or graphical response for a user before the control command is implemented. 18. A method for controlling a ventilator by means of a detection unit for control commands, wherein the detection unit detects control commands of a user in a detection region of the detection unit, the detection unit comprising at least one sensor for control commands, a memory, an apparatus for producing digital control commands and an interface for coupling to the ventilator and for transmitting the control commands to the ventilator. 19. The apparatus of claim 1, wherein the detection unit is configured for processing and evaluating image data or gestures detected in the detection region and is embodied as a camera. 20. The apparatus of claim 16, wherein the illumination unit projects a virtual image and measurement values or evaluations of the ventilator into the detection region. | 2,100 |
6,567 | 6,567 | 16,329,159 | 2,175 | A method for preselecting and/or selecting a menu, a submenu, a function, or a function value of an electronic device. The menu, the submenu, the function, or the function value is preselectable and/or selectable using a touchpad with a first body part and an audible feedback is output table. The audible feedback is activated by an additional touch of the touchpad at any point with a second body part. | 1.-17. (canceled) 18. A method for preselecting and/or selecting at least one of a menu, a submenu, a function, and a function value of an electronic device, comprising:
touching a touchpad of the electronic device with a first body part to at least one of preselect and select the menu, the submenu, the function, or the function value; and activating an audible feedback by an additional touch of the touchpad at any point with a second body part; and outputting the audible feedback for the at least one of preselected and selected menu, submenu, function value, or function of the electronic device. 19. The method as claimed in claim 18, further comprising:
applying and dragging of a third body part to alter a preselected or selected function value. 20. The method as claimed in claim 18, wherein each of the menu, the submenu, the function, and the function value is associated with a position on the touchpad. 21. The method as claimed in claim 20, wherein each of the menu, the submenu, the function, and the function value is preselectable and/or selectable by a touch of the associated position. 22. The method as claimed in claim 18, wherein the first body part is a first finger. 23. The method as claimed in claim 22, wherein the second body part is a second finger. 24. The method as claimed in claim 23, wherein the first and second fingers touch the touchpad adjacently. 25. A user apparatus configured for preselecting and/or selecting at least one of a menu, a submenu, a function or a function value of an electronic device, comprising:
a touchpad configured to be touched of with a first body part to preselect and/or select the menu, the submenu, the function or the function value; and an output for an audible feedback for the preselected and/or selected menu, submenu, function value or the preselected and/or selected function of the electronic device, wherein the audible feedback is activable by an additional touch of the touchpad at any point with a second body part. 26. The user apparatus as claimed in claim 25, wherein the applying and dragging of a third body part is usable to alter a function value. 27. The user apparatus as claimed in claim 25, wherein the menu, the submenu, the function or the function value is associated with a position on the touchpad. 28. The user apparatus as claimed in claim 27, wherein the preselectable and/or selectable menu, the preselectable and/or selectable submenu, the preselectable and/or selectable function or the preselectable and/or selectable function value is preselectable and/or selectable by a touch of the associated position. 29. The user apparatus as claimed in claim 25, wherein the first body part is a first finger. 30. The user apparatus as claimed in claim 29, wherein the second body part is a second finger. 31. The user apparatus as claimed in claim 30, wherein the audible feedback is activatable by a touch of the touchpad when the first and second fingers touch the touchpad adjacently. 32. The user apparatus as claimed in claim 25, wherein the touchpad has a capacitive, inductive, resistive, or optical touch detection. 33. The user apparatus as claimed in claim 25, wherein the touchpad is a touchscreen. 34. The user apparatus as claimed in claim 33, wherein the touchscreen has an electro-optical display. | A method for preselecting and/or selecting a menu, a submenu, a function, or a function value of an electronic device. The menu, the submenu, the function, or the function value is preselectable and/or selectable using a touchpad with a first body part and an audible feedback is output table. The audible feedback is activated by an additional touch of the touchpad at any point with a second body part.1.-17. (canceled) 18. A method for preselecting and/or selecting at least one of a menu, a submenu, a function, and a function value of an electronic device, comprising:
touching a touchpad of the electronic device with a first body part to at least one of preselect and select the menu, the submenu, the function, or the function value; and activating an audible feedback by an additional touch of the touchpad at any point with a second body part; and outputting the audible feedback for the at least one of preselected and selected menu, submenu, function value, or function of the electronic device. 19. The method as claimed in claim 18, further comprising:
applying and dragging of a third body part to alter a preselected or selected function value. 20. The method as claimed in claim 18, wherein each of the menu, the submenu, the function, and the function value is associated with a position on the touchpad. 21. The method as claimed in claim 20, wherein each of the menu, the submenu, the function, and the function value is preselectable and/or selectable by a touch of the associated position. 22. The method as claimed in claim 18, wherein the first body part is a first finger. 23. The method as claimed in claim 22, wherein the second body part is a second finger. 24. The method as claimed in claim 23, wherein the first and second fingers touch the touchpad adjacently. 25. A user apparatus configured for preselecting and/or selecting at least one of a menu, a submenu, a function or a function value of an electronic device, comprising:
a touchpad configured to be touched of with a first body part to preselect and/or select the menu, the submenu, the function or the function value; and an output for an audible feedback for the preselected and/or selected menu, submenu, function value or the preselected and/or selected function of the electronic device, wherein the audible feedback is activable by an additional touch of the touchpad at any point with a second body part. 26. The user apparatus as claimed in claim 25, wherein the applying and dragging of a third body part is usable to alter a function value. 27. The user apparatus as claimed in claim 25, wherein the menu, the submenu, the function or the function value is associated with a position on the touchpad. 28. The user apparatus as claimed in claim 27, wherein the preselectable and/or selectable menu, the preselectable and/or selectable submenu, the preselectable and/or selectable function or the preselectable and/or selectable function value is preselectable and/or selectable by a touch of the associated position. 29. The user apparatus as claimed in claim 25, wherein the first body part is a first finger. 30. The user apparatus as claimed in claim 29, wherein the second body part is a second finger. 31. The user apparatus as claimed in claim 30, wherein the audible feedback is activatable by a touch of the touchpad when the first and second fingers touch the touchpad adjacently. 32. The user apparatus as claimed in claim 25, wherein the touchpad has a capacitive, inductive, resistive, or optical touch detection. 33. The user apparatus as claimed in claim 25, wherein the touchpad is a touchscreen. 34. The user apparatus as claimed in claim 33, wherein the touchscreen has an electro-optical display. | 2,100 |
6,568 | 6,568 | 15,889,239 | 2,191 | Disclosed are examples of deploying application to devices that are enrolled as managed devices with a management service. An application package is deployed to a management component on a client device. The management component causes the application package to be installed by an application installation client that is installed on the client device and that is a separate application from the management component. | 1. A system for deploying an application to a managed device enrolled with a management service, comprising:
a client device comprising a processor and a memory; and a management component stored in the memos that, when executed by the processor, causes the client device to at least:
obtain an application package identified by the management service, the application package comprising an application for installation on the client device, wherein the management service sends the application package to the client device based upon an assignment of the application package to a grouping of client device that includes the client device;
generate a command to cause installation of the application on the client device;
provide the command to cause installation of the application to an application installation client;
query the application installation client for a status of the installation of the application; and
transmit the status of the installation of the application the management service. 2. The system of claim 1, wherein the application installation client is a separate application from the management component. 3. The system of claim 1, wherein the management component obtains the application package by receiving a command to retrieve the application package from a command queue, wherein the management service writes the command to retrieve the application package to the command queue. 4. The system of claim 1, wherein the status of the installation of the implication further comprises a status of post-installation scripts associated with the installation of the application. 5. The system of claim 1, wherein the management component provides the application installation client by writing to a manifest and a catalog associated with the application installation client. 6. The system of claim 1, wherein the management component executes a server process that acts as proxy server on behalf of the application installation client to obtain the application package identified by the management service. 7. The system of claim 1, wherein the application package is formatted in an Apple package format or a disk image format. 8. A method for deploying an application to a managed device enrolled with a management service, comprising:
obtaining, in a management component installed on a client device, an application package identified by the management service, the application package comprising an application for installation on the client device, wherein the management service sends the application package to the client device based upon an assignment of the application package to a grouping of client device that includes the client device; generating, in the management component, a command to cause installation of the application on the client device; providing, by management component, the command to cause installation of the application to an application installation client; querying, by the management component, the application installation client for a status of the installation of the application; and transmitting, from the management component, the status of the installation of the application the management service. 9. The method of claim 8, wherein the application installation client is a separate application from the management component. 10. The method of claim 8, wherein obtaining the application package further comprises receiving a command to retrieve the application package from a command queue, wherein the management service writes the command to retrieve the application package to the command queue. 11. The method of claim 8, wherein the status of the installation of the application further comprises a status of post-installation scripts associated with the installation of the application. 12. The method of claim 8, further comprising providing, by the management component, the command to cause installation of the application to the application installation client by writing to a manifest and a catalog associated with the application installation client. 13. The method of claim 8, further comprising executing a server process that acts as proxy server on behalf of the application installation client to obtain the application package identified by the management service. 14. The method of claim 8, wherein the application package is formatted in an Apple package format or a disk image format. 15. A non-transitory computer-readable medium embodying a program executable on a client device, the program facilitating deployment of an application to the client, device enrolled with a management service, the program causing the client device to at least:
obtain an application package identified by the management service, the application package comprising an application for installation on the client device, wherein the management service sends the application package to the client device based upon an assignment of the application package to a grouping of client device that includes the client device; generate a command to cause installation of the application on the client device; provide the command to cause installation of the application to an application installation client; query the application installation client for a status of the installation of the application; and transmit the status of the installation of the application the management service. 16. The non-transitory computer-readable medium of claim 15, wherein the program causes the client device to obtain the application package by receiving a command to retrieve the application package from a command queue, wherein the management service writes the command to retrieve the application package to the command queue. 17. The non-transitory computer-readable medium of claim 15, wherein the status of the installation of the application further comprises a status of post-installation scripts associated with the installation of the application. 18. The non-transitory computer-readable medium of claim 15, wherein the program causes the client device to provide the command to cause installation of the application to an application installation client by writing to a manifest and a catalog associated with the application installation client. 19. The non-transitory computer-readable medium of claim 15, wherein the program causes the client device to execute a server process that acts as proxy server on behalf of the application installation client to obtain the application package identified by the management service. 20. The non-transitory computer-readable medium of claim 15, wherein the application package is formatted in an Apple package format or a disk image format. | Disclosed are examples of deploying application to devices that are enrolled as managed devices with a management service. An application package is deployed to a management component on a client device. The management component causes the application package to be installed by an application installation client that is installed on the client device and that is a separate application from the management component.1. A system for deploying an application to a managed device enrolled with a management service, comprising:
a client device comprising a processor and a memory; and a management component stored in the memos that, when executed by the processor, causes the client device to at least:
obtain an application package identified by the management service, the application package comprising an application for installation on the client device, wherein the management service sends the application package to the client device based upon an assignment of the application package to a grouping of client device that includes the client device;
generate a command to cause installation of the application on the client device;
provide the command to cause installation of the application to an application installation client;
query the application installation client for a status of the installation of the application; and
transmit the status of the installation of the application the management service. 2. The system of claim 1, wherein the application installation client is a separate application from the management component. 3. The system of claim 1, wherein the management component obtains the application package by receiving a command to retrieve the application package from a command queue, wherein the management service writes the command to retrieve the application package to the command queue. 4. The system of claim 1, wherein the status of the installation of the implication further comprises a status of post-installation scripts associated with the installation of the application. 5. The system of claim 1, wherein the management component provides the application installation client by writing to a manifest and a catalog associated with the application installation client. 6. The system of claim 1, wherein the management component executes a server process that acts as proxy server on behalf of the application installation client to obtain the application package identified by the management service. 7. The system of claim 1, wherein the application package is formatted in an Apple package format or a disk image format. 8. A method for deploying an application to a managed device enrolled with a management service, comprising:
obtaining, in a management component installed on a client device, an application package identified by the management service, the application package comprising an application for installation on the client device, wherein the management service sends the application package to the client device based upon an assignment of the application package to a grouping of client device that includes the client device; generating, in the management component, a command to cause installation of the application on the client device; providing, by management component, the command to cause installation of the application to an application installation client; querying, by the management component, the application installation client for a status of the installation of the application; and transmitting, from the management component, the status of the installation of the application the management service. 9. The method of claim 8, wherein the application installation client is a separate application from the management component. 10. The method of claim 8, wherein obtaining the application package further comprises receiving a command to retrieve the application package from a command queue, wherein the management service writes the command to retrieve the application package to the command queue. 11. The method of claim 8, wherein the status of the installation of the application further comprises a status of post-installation scripts associated with the installation of the application. 12. The method of claim 8, further comprising providing, by the management component, the command to cause installation of the application to the application installation client by writing to a manifest and a catalog associated with the application installation client. 13. The method of claim 8, further comprising executing a server process that acts as proxy server on behalf of the application installation client to obtain the application package identified by the management service. 14. The method of claim 8, wherein the application package is formatted in an Apple package format or a disk image format. 15. A non-transitory computer-readable medium embodying a program executable on a client device, the program facilitating deployment of an application to the client, device enrolled with a management service, the program causing the client device to at least:
obtain an application package identified by the management service, the application package comprising an application for installation on the client device, wherein the management service sends the application package to the client device based upon an assignment of the application package to a grouping of client device that includes the client device; generate a command to cause installation of the application on the client device; provide the command to cause installation of the application to an application installation client; query the application installation client for a status of the installation of the application; and transmit the status of the installation of the application the management service. 16. The non-transitory computer-readable medium of claim 15, wherein the program causes the client device to obtain the application package by receiving a command to retrieve the application package from a command queue, wherein the management service writes the command to retrieve the application package to the command queue. 17. The non-transitory computer-readable medium of claim 15, wherein the status of the installation of the application further comprises a status of post-installation scripts associated with the installation of the application. 18. The non-transitory computer-readable medium of claim 15, wherein the program causes the client device to provide the command to cause installation of the application to an application installation client by writing to a manifest and a catalog associated with the application installation client. 19. The non-transitory computer-readable medium of claim 15, wherein the program causes the client device to execute a server process that acts as proxy server on behalf of the application installation client to obtain the application package identified by the management service. 20. The non-transitory computer-readable medium of claim 15, wherein the application package is formatted in an Apple package format or a disk image format. | 2,100 |
6,569 | 6,569 | 15,348,175 | 2,195 | A time stamp value associated with a virtual function of a guest virtual machine (VM) is periodically updated. One of a plurality of idle worker threads in a thread pool is assigned to periodically increment the time stamp value after initialization of an instance of the guest VM. An inactive status of the guest VM is detected based at least in part on the time stamp value not changing over a specified time period. The provision of resources to the virtual function of the inactive guest VM can be terminated based on its inactive status. In one embodiment, the virtual function is associated with a graphics processing unit (GPU) and terminating the provision of resources includes terminating the scheduling of cycles of GPU time. | 1. A method, comprising:
periodically updating, in a shared memory on a host system, a time stamp value associated with a virtual function of a guest virtual machine (VM); detecting an inactive status of the guest VM based at least in part on the time stamp value remaining fixed over a specified time period; and terminating, in response to detecting the inactive status of the guest VM, a provision of a first resource on the host system to the virtual function. 2. The method of claim 1, further comprising:
assigning, in response to detecting the inactive status of the guest VM, the virtual function to an inactive list; and preventing the virtual function in the inactive list from communicating with the guest VM having the inactive status. 3. The method of claim 1, wherein the virtual function is associated with a graphics processing unit (GPU) and the first resource on the host system comprises cycles of GPU time. 4. The method of claim 1, wherein the virtual function is associated with a central processing unit (CPU) and the first resource on the host system comprises cycles of CPU processing time. 5. The method of claim 1, wherein periodically updating the time stamp value comprises assigning a thread instantiated in a guest VM device driver of the VM to periodically increment the time stamp value. 6. The method of claim 5, wherein assigning the thread comprises assigning one of a plurality of idle worker threads in a thread pool to periodically increment the time stamp value. 7. The method of claim 1, wherein detecting an inactive state of the guest VM includes assigning a thread instantiated in a device scheduler to periodically query the time stamp value and determining whether the time stamp value has changed over the specified time period. 8. The method of claim 1, wherein periodically updating the time stamp value begins after initialization of an instance of the guest VM. 9. A system, comprising:
a server to host a plurality of guest virtual machines (VMs), wherein the server comprises a physical device with resources allocated to the plurality of guest VMs, and further wherein a virtual function associated with the physical device is configured for each of the plurality of guest VMs; and a shared memory, wherein the shared memory stores a time stamp value for each virtual function of the plurality of the guest VMs, wherein an inactive status of one of the plurality of guest VMs is detected based at least in part on the time stamp value for that one of the plurality of guest VMs remaining fixed over a specified time period. 10. The system of claim 9, wherein the physical device comprises a graphics processing unit (GPU) with cycles of GPU time allocated to the plurality of guest VMs. 11. The system of claim 10, wherein cycles of GPU time are terminated to the virtual function for that one of the plurality of guest VMs having the inactive status. 12. The system of claim 9, wherein the virtual function for that one of the plurality of guest VMs is assigned, in response to detecting the inactive status, an inactive list, and further wherein provisioning of resources is terminated for virtual functions in the inactive list. 13. The system of claim 9, wherein the physical device comprises a central processing unit (CPU) with cycles of CPU processing time allocated to the plurality of guest VMs. 14. The system of claim 9, wherein a thread is instantiated in a guest VM device driver of each of the plurality of guest VMs to periodically increment the time stamp value. 15. The system of claim 9, wherein a thread is instantiated in a device scheduler to periodically query the time stamp value for each virtual function and determine whether the time stamp value has changed over the specified time period. 16. The system of claim 9, wherein the time stamp value begins periodically updating after initialization of each instance of the plurality of the guest VMs 17. A non-transitory computer readable medium embodying a set of executable instructions, the set of executable instructions to manipulate a processor to:
periodically update, in a shared memory on a host system, a time stamp value associated with a virtual function of a guest virtual machine (VM); detect an inactive status of the guest VM based at least in part on the time stamp value remaining fixed over a specified time period; and terminate the provision of resources on the host system to the virtual function having the inactive status. 18. The non-transitory computer readable medium of claim 17, wherein the processor is to:
assign, in response to detecting the inactive status of the guest VM, the virtual function to an inactive list; and prevent the virtual function in the inactive list from communicating with the guest VM having the inactive status. 19. The non-transitory computer readable medium of claim 17, wherein the virtual function is associated with a graphics processing unit (GPU), and further wherein the provision of resources is terminated by terminating the scheduling of cycles of GPU time to the virtual function. 20. The non-transitory computer readable medium of claim 17, wherein the time stamp value is periodically updated by assigning a thread instantiated in a guest VM device driver of the guest VM to periodically increment the time stamp value. | A time stamp value associated with a virtual function of a guest virtual machine (VM) is periodically updated. One of a plurality of idle worker threads in a thread pool is assigned to periodically increment the time stamp value after initialization of an instance of the guest VM. An inactive status of the guest VM is detected based at least in part on the time stamp value not changing over a specified time period. The provision of resources to the virtual function of the inactive guest VM can be terminated based on its inactive status. In one embodiment, the virtual function is associated with a graphics processing unit (GPU) and terminating the provision of resources includes terminating the scheduling of cycles of GPU time.1. A method, comprising:
periodically updating, in a shared memory on a host system, a time stamp value associated with a virtual function of a guest virtual machine (VM); detecting an inactive status of the guest VM based at least in part on the time stamp value remaining fixed over a specified time period; and terminating, in response to detecting the inactive status of the guest VM, a provision of a first resource on the host system to the virtual function. 2. The method of claim 1, further comprising:
assigning, in response to detecting the inactive status of the guest VM, the virtual function to an inactive list; and preventing the virtual function in the inactive list from communicating with the guest VM having the inactive status. 3. The method of claim 1, wherein the virtual function is associated with a graphics processing unit (GPU) and the first resource on the host system comprises cycles of GPU time. 4. The method of claim 1, wherein the virtual function is associated with a central processing unit (CPU) and the first resource on the host system comprises cycles of CPU processing time. 5. The method of claim 1, wherein periodically updating the time stamp value comprises assigning a thread instantiated in a guest VM device driver of the VM to periodically increment the time stamp value. 6. The method of claim 5, wherein assigning the thread comprises assigning one of a plurality of idle worker threads in a thread pool to periodically increment the time stamp value. 7. The method of claim 1, wherein detecting an inactive state of the guest VM includes assigning a thread instantiated in a device scheduler to periodically query the time stamp value and determining whether the time stamp value has changed over the specified time period. 8. The method of claim 1, wherein periodically updating the time stamp value begins after initialization of an instance of the guest VM. 9. A system, comprising:
a server to host a plurality of guest virtual machines (VMs), wherein the server comprises a physical device with resources allocated to the plurality of guest VMs, and further wherein a virtual function associated with the physical device is configured for each of the plurality of guest VMs; and a shared memory, wherein the shared memory stores a time stamp value for each virtual function of the plurality of the guest VMs, wherein an inactive status of one of the plurality of guest VMs is detected based at least in part on the time stamp value for that one of the plurality of guest VMs remaining fixed over a specified time period. 10. The system of claim 9, wherein the physical device comprises a graphics processing unit (GPU) with cycles of GPU time allocated to the plurality of guest VMs. 11. The system of claim 10, wherein cycles of GPU time are terminated to the virtual function for that one of the plurality of guest VMs having the inactive status. 12. The system of claim 9, wherein the virtual function for that one of the plurality of guest VMs is assigned, in response to detecting the inactive status, an inactive list, and further wherein provisioning of resources is terminated for virtual functions in the inactive list. 13. The system of claim 9, wherein the physical device comprises a central processing unit (CPU) with cycles of CPU processing time allocated to the plurality of guest VMs. 14. The system of claim 9, wherein a thread is instantiated in a guest VM device driver of each of the plurality of guest VMs to periodically increment the time stamp value. 15. The system of claim 9, wherein a thread is instantiated in a device scheduler to periodically query the time stamp value for each virtual function and determine whether the time stamp value has changed over the specified time period. 16. The system of claim 9, wherein the time stamp value begins periodically updating after initialization of each instance of the plurality of the guest VMs 17. A non-transitory computer readable medium embodying a set of executable instructions, the set of executable instructions to manipulate a processor to:
periodically update, in a shared memory on a host system, a time stamp value associated with a virtual function of a guest virtual machine (VM); detect an inactive status of the guest VM based at least in part on the time stamp value remaining fixed over a specified time period; and terminate the provision of resources on the host system to the virtual function having the inactive status. 18. The non-transitory computer readable medium of claim 17, wherein the processor is to:
assign, in response to detecting the inactive status of the guest VM, the virtual function to an inactive list; and prevent the virtual function in the inactive list from communicating with the guest VM having the inactive status. 19. The non-transitory computer readable medium of claim 17, wherein the virtual function is associated with a graphics processing unit (GPU), and further wherein the provision of resources is terminated by terminating the scheduling of cycles of GPU time to the virtual function. 20. The non-transitory computer readable medium of claim 17, wherein the time stamp value is periodically updated by assigning a thread instantiated in a guest VM device driver of the guest VM to periodically increment the time stamp value. | 2,100 |
6,570 | 6,570 | 15,700,443 | 2,195 | Embodiments of a software defined automation system that provides a reference architecture for designing, managing and maintaining a highly available, scalable and flexible automation system. In some embodiments, an SDA system can include a localized subsystem including a system controller node and multiple compute nodes. The multiple compute nodes can be communicatively coupled to the system controller node via a first communication network. The system controller node can manage the multiple compute nodes and virtualization of a control system on a compute node via the first communication network. The virtualized control system includes virtualized control system elements connected to a virtual network that is connected to a second communication network to enable the virtualized control system elements to control a physical control system element via the second communication network connected to the virtual network. | 1. A software-defined automation (SDA) system comprising:
a localized subsystem including a system controller node and one or more compute nodes, wherein the one or more compute nodes are communicatively coupled to the system controller node via a first communication network; and wherein the system controller node manages the one or more compute nodes and virtualization of a control system or a portion thereof on at least one compute node from the one or more compute nodes via the first communication network and connects the virtualized control system including at least one virtualized control system element to a virtual network mapped to a second communication network to enable the at least one virtualized control system element to control at least one physical control system element via the second communication network connected to the virtual network. 2. The SDA system of claim 1, wherein the one or more compute nodes includes an edge device that is selected in part based on its proximity to the at least one physical control system element and a server machine. 3. The SDA system of claim 1, wherein the at least one virtualized control system element runs on at least one host on the at least one compute node, and wherein the at least one host includes a virtual machine, container or bare metal. 4. The SDA system of claim 1, further comprising:
a cyber security subsystem including a cyber security controller node, wherein the cyber security controller node provides at least one security policy to the localized subsystem for configuring security of the at least one virtualized control system element, and at least one host executing the at least one virtualized control system element on the at least one compute node. 5. The SDA system of claim 4, wherein the at least one security policy requires a firewall for the virtualized control system, and wherein the localized subsystem, in accordance with the at least one security policy, instantiates a virtual firewall for the virtualized control system on the at least one compute node. 6. The SDA system of claim 4, further comprising:
a configurable network subsystem including a network controller node, wherein the network controller node, in response to the virtualization of the control system or the portion thereof in the localized subsystem, configures at least one physical or virtual network element to manage network traffic flow associated with the control of the at least one physical control system element. 7. The SDA system of claim 1, wherein the network controller node controls the at least one physical or virtual network element by deploying one or more network policies. 8. The SDA system of claim 7, wherein the one or more network policies include policies for controlling at least one of: connectivity, bandwidth, latency and traffic flow. 9. The SDA system of claim 6, wherein the cyber security subsystem provides at least one security policy to the configurable network subsystem to configure security of at the least one physical or virtual network element. 10. The SDA system of claim 9, wherein the at least one security policy specifies types of commands allowed to propagate through the second communication network to the at least one physical control system element via the at least one physical or virtual network element. 11. The SDA system of claim 1, further comprising:
a configurable network subsystem including a network controller node, wherein the network controller node, in response to a change in the localized subsystem, configures at least one physical or virtual network element to manage network traffic flow associated with the control of the at least one physical control system element. 12. The SDA system of claim 1, wherein the configurable network subsystem includes a time sensitive network component for handling time-sensitive deterministic network traffic. 13. The SDA system of claim 1, wherein the at least one virtualized control element is a software implementation of an embedded system or a component in the embedded system. 14. The SDA system of claim 1, wherein managing the one or more compute nodes includes instantiating, configuring, starting, stopping and destroying hosts on the one or more compute nodes. 15. The SDA system of claim 1, further comprising a system software running on a host on a compute node from the one or more compute nodes, the system software communicating, via an application programming interface, control system virtualization description for the virtualization of the control system or the portion thereof in the localized subsystem. 16. The SDA system of claim 1, further comprising a system software through which least two of: topology, inventory, configuration or diagnostics information corresponding to components of the localized subsystem are accessible to an entity, the system software running on a host on a compute node from the one or more compute nodes and communicating with the localized subsystem via an application programming interface. 17. The SDA system of claim 1, wherein the localized subsystem including the system controller node and the one or more compute nodes are localized in a single highly available server. 18. A method of defining an automation system via software comprising:
virtualizing, by a localized subsystem, a control system or a portion thereof on at least one compute node from one or more compute nodes, wherein the localized subsystem includes a system controller node communicatively coupled to the one or more compute nodes via a first communication network; and connecting by the localized subsystem, at least one virtualized control system element of the virtualized control system to a virtual network connected to a second communication network, wherein the at least one virtualized control system element controls at least one physical control system element via the second communication network connected to the virtual network. 19.-42. (canceled) 43. A software-defined automation (SDA) system comprising:
a localized subsystem including a system controller node communicatively coupled to one or more compute nodes via a first communication network, wherein the system controller node virtualizes a control system or a portion thereof on at least one compute node from the one or more compute nodes, and connects the virtualized control system including at least one virtualized control system element to a virtual network mapped to a second communication network to enable the at least one virtualized control system element to control at least one physical control system element via the second communication network; a cyber security subsystem including a cyber security controller node, wherein the cyber security controller node provides at least one security policy to the localized subsystem for configuring security of the at least one virtualized control system element, and at least one host executing the at least one virtualized control system element on the at least one compute node; and a network subsystem including a network controller node, wherein the network controller node, in response to the virtualization of the control system or the portion thereof in the localized subsystem, configures at least one physical or virtual network element to manage network traffic flow associated with the control of the at least one physical control system element. 44. A method of defining an automation system via software comprising:
virtualizing, by a localized subsystem, a control system or a portion thereof on at least one compute node from one or more compute nodes, wherein the localized subsystem includes a system controller node communicatively coupled to the one or more compute nodes via a first communication network; connecting, by the localized subsystem, at least one virtualized control system element of the virtualized control system to a virtual network connected to a second communication network, wherein the at least one virtualized control system element controls at least one physical control system element via the second communication network connected to the virtual network; configuring, by the localized subsystem, security of the at least one virtualized control system element, and at least one host executing the at least one virtualized control system element on the at least one compute node by applying at least one security policy from a cyber security subsystem; and in response to the virtualizing of the control system or the portion thereof in the localized subsystem, configuring at least one physical or virtual network element to manage network traffic flow associated with the control of the at least one physical control system element by deploying one or more network policies associated with control of at least one of: connectivity, bandwidth, latency and traffic flow. | Embodiments of a software defined automation system that provides a reference architecture for designing, managing and maintaining a highly available, scalable and flexible automation system. In some embodiments, an SDA system can include a localized subsystem including a system controller node and multiple compute nodes. The multiple compute nodes can be communicatively coupled to the system controller node via a first communication network. The system controller node can manage the multiple compute nodes and virtualization of a control system on a compute node via the first communication network. The virtualized control system includes virtualized control system elements connected to a virtual network that is connected to a second communication network to enable the virtualized control system elements to control a physical control system element via the second communication network connected to the virtual network.1. A software-defined automation (SDA) system comprising:
a localized subsystem including a system controller node and one or more compute nodes, wherein the one or more compute nodes are communicatively coupled to the system controller node via a first communication network; and wherein the system controller node manages the one or more compute nodes and virtualization of a control system or a portion thereof on at least one compute node from the one or more compute nodes via the first communication network and connects the virtualized control system including at least one virtualized control system element to a virtual network mapped to a second communication network to enable the at least one virtualized control system element to control at least one physical control system element via the second communication network connected to the virtual network. 2. The SDA system of claim 1, wherein the one or more compute nodes includes an edge device that is selected in part based on its proximity to the at least one physical control system element and a server machine. 3. The SDA system of claim 1, wherein the at least one virtualized control system element runs on at least one host on the at least one compute node, and wherein the at least one host includes a virtual machine, container or bare metal. 4. The SDA system of claim 1, further comprising:
a cyber security subsystem including a cyber security controller node, wherein the cyber security controller node provides at least one security policy to the localized subsystem for configuring security of the at least one virtualized control system element, and at least one host executing the at least one virtualized control system element on the at least one compute node. 5. The SDA system of claim 4, wherein the at least one security policy requires a firewall for the virtualized control system, and wherein the localized subsystem, in accordance with the at least one security policy, instantiates a virtual firewall for the virtualized control system on the at least one compute node. 6. The SDA system of claim 4, further comprising:
a configurable network subsystem including a network controller node, wherein the network controller node, in response to the virtualization of the control system or the portion thereof in the localized subsystem, configures at least one physical or virtual network element to manage network traffic flow associated with the control of the at least one physical control system element. 7. The SDA system of claim 1, wherein the network controller node controls the at least one physical or virtual network element by deploying one or more network policies. 8. The SDA system of claim 7, wherein the one or more network policies include policies for controlling at least one of: connectivity, bandwidth, latency and traffic flow. 9. The SDA system of claim 6, wherein the cyber security subsystem provides at least one security policy to the configurable network subsystem to configure security of at the least one physical or virtual network element. 10. The SDA system of claim 9, wherein the at least one security policy specifies types of commands allowed to propagate through the second communication network to the at least one physical control system element via the at least one physical or virtual network element. 11. The SDA system of claim 1, further comprising:
a configurable network subsystem including a network controller node, wherein the network controller node, in response to a change in the localized subsystem, configures at least one physical or virtual network element to manage network traffic flow associated with the control of the at least one physical control system element. 12. The SDA system of claim 1, wherein the configurable network subsystem includes a time sensitive network component for handling time-sensitive deterministic network traffic. 13. The SDA system of claim 1, wherein the at least one virtualized control element is a software implementation of an embedded system or a component in the embedded system. 14. The SDA system of claim 1, wherein managing the one or more compute nodes includes instantiating, configuring, starting, stopping and destroying hosts on the one or more compute nodes. 15. The SDA system of claim 1, further comprising a system software running on a host on a compute node from the one or more compute nodes, the system software communicating, via an application programming interface, control system virtualization description for the virtualization of the control system or the portion thereof in the localized subsystem. 16. The SDA system of claim 1, further comprising a system software through which least two of: topology, inventory, configuration or diagnostics information corresponding to components of the localized subsystem are accessible to an entity, the system software running on a host on a compute node from the one or more compute nodes and communicating with the localized subsystem via an application programming interface. 17. The SDA system of claim 1, wherein the localized subsystem including the system controller node and the one or more compute nodes are localized in a single highly available server. 18. A method of defining an automation system via software comprising:
virtualizing, by a localized subsystem, a control system or a portion thereof on at least one compute node from one or more compute nodes, wherein the localized subsystem includes a system controller node communicatively coupled to the one or more compute nodes via a first communication network; and connecting by the localized subsystem, at least one virtualized control system element of the virtualized control system to a virtual network connected to a second communication network, wherein the at least one virtualized control system element controls at least one physical control system element via the second communication network connected to the virtual network. 19.-42. (canceled) 43. A software-defined automation (SDA) system comprising:
a localized subsystem including a system controller node communicatively coupled to one or more compute nodes via a first communication network, wherein the system controller node virtualizes a control system or a portion thereof on at least one compute node from the one or more compute nodes, and connects the virtualized control system including at least one virtualized control system element to a virtual network mapped to a second communication network to enable the at least one virtualized control system element to control at least one physical control system element via the second communication network; a cyber security subsystem including a cyber security controller node, wherein the cyber security controller node provides at least one security policy to the localized subsystem for configuring security of the at least one virtualized control system element, and at least one host executing the at least one virtualized control system element on the at least one compute node; and a network subsystem including a network controller node, wherein the network controller node, in response to the virtualization of the control system or the portion thereof in the localized subsystem, configures at least one physical or virtual network element to manage network traffic flow associated with the control of the at least one physical control system element. 44. A method of defining an automation system via software comprising:
virtualizing, by a localized subsystem, a control system or a portion thereof on at least one compute node from one or more compute nodes, wherein the localized subsystem includes a system controller node communicatively coupled to the one or more compute nodes via a first communication network; connecting, by the localized subsystem, at least one virtualized control system element of the virtualized control system to a virtual network connected to a second communication network, wherein the at least one virtualized control system element controls at least one physical control system element via the second communication network connected to the virtual network; configuring, by the localized subsystem, security of the at least one virtualized control system element, and at least one host executing the at least one virtualized control system element on the at least one compute node by applying at least one security policy from a cyber security subsystem; and in response to the virtualizing of the control system or the portion thereof in the localized subsystem, configuring at least one physical or virtual network element to manage network traffic flow associated with the control of the at least one physical control system element by deploying one or more network policies associated with control of at least one of: connectivity, bandwidth, latency and traffic flow. | 2,100 |
6,571 | 6,571 | 16,720,481 | 2,159 | A method for execution by a query processing module includes determining a query expression indicating a query for execution. An operator tree is generated based on a nested ordering of a plurality of operators indicated by the query expression. Conjunctive normal form (CNF) conversion cost data is generated based on the operator tree, and disjunctive normal form (DNF) conversion cost data is also generated based on the operator tree. Conversion selection data is generated based on the CNF conversion cost data and the DNF conversion cost data. The conversion selection data indicates a selection to perform either a CNF conversion or a DNF conversion. A normalized query expression is generated by performing either the CNF conversion or the DNF conversion upon the query expression based on the conversion selection data. Execution of the query is facilitated in accordance with the normalized query expression. | 1. A method for execution by at least one processing module of a database system, comprising:
determining a query expression indicating a query for execution; generating an operator tree based on a nested ordering of a plurality of operators indicated by the query expression; generating conjunctive normal form (CNF) conversion cost data based on the operator tree; generating disjunctive normal form (DNF) conversion cost data based on the operator tree; generating conversion selection data, based on the CNF conversion cost data and the DNF conversion cost data, that indicates a selection to perform, upon the query expression, one of: a CNF conversion or a DNF conversion; generating a normalized query expression by performing the one of: the CNF conversion or the DNF conversion upon the query expression based on the conversion selection data; and facilitating execution of the query in accordance with the normalized query expression. 2. The method of claim 1, wherein the operator tree indicates the plurality of operators as a plurality of operator nodes of the operator tree;
wherein generating the CNF conversion cost data includes calculating a CNF cost for each of the plurality of operator nodes of the operator tree; wherein generating the DNF conversion cost data includes calculating a DNF cost for each of the plurality of operator nodes of the operator tree. 3. The method of claim 2, wherein calculating the CNF cost for each of the plurality of operator nodes of the operator tree includes applying a depth-first CNF calculation via a recursive process applied to the operator tree, and wherein calculating the DNF cost for each of the plurality of operator nodes of the operator tree includes applying a depth-first DNF calculation via the recursive process applied to the operator tree. 4. The method of claim 2, wherein calculating the CNF cost for each of the plurality of operator nodes of the operator tree includes, for each OR node in the operator tree, multiplying a CNF cost of each child node of the each OR node;
wherein calculating the CNF cost for each of the plurality of operator nodes of the operator tree includes, for each AND node in the operator tree, summing a CNF cost of each child node of the each AND node; wherein calculating the DNF cost for each of the plurality of operator nodes of the operator tree includes, for each OR node in the operator tree, summing a DNF cost of each child node of the each OR node; and wherein calculating the DNF cost for each of the plurality of operator nodes of the operator tree includes, for each AND node in the operator tree, multiplying a DNF cost of each child node of the each AND node. 5. The method of claim 4, wherein every leaf node of the operator tree is assigned a same DNF cost and is further assigned a same CNF cost, wherein the same DNF cost is equal to the same CNF cost. 6. The method of claim 1, wherein the nested ordering of the plurality of operators indicated by the query expression is presented in a non-normalized form. 7. The method of claim 1, wherein generating the conversion selection data includes selecting the CNF conversion when the CNF conversion cost data is more favorable than the DNF conversion cost data, and wherein generating the conversion selection data includes selecting the DNF conversion when the DNF conversion cost data is more favorable than the CNF conversion cost data. 8. The method of claim 1, wherein generating the conversion selection data includes automatically selecting the CNF conversion when the CNF conversion cost data compares favorably to a predetermined threshold CNF conversion cost. 9. The method of claim 8, wherein the DNF conversion cost data indicates a more favorable conversion cost than the CNF conversion cost data, and wherein the conversion selection data is generated to indicate selection of the CNF conversion based on the CNF conversion cost data comparing favorably to the predetermined threshold CNF conversion cost. 10. The method of claim 1, wherein generating the conversion selection data includes automatically selecting the CNF conversion when the DNF conversion cost data compares unfavorably to a predetermined threshold DNF conversion cost. 11. The method of claim 10, wherein the DNF conversion cost data indicates a more favorable conversion cost than the CNF conversion cost data, and wherein the conversion selection data is generated to indicate selection of the CNF conversion based on the DNF conversion cost data comparing unfavorably to the predetermined threshold DNF conversion cost. 12. The method of claim 1, wherein the DNF conversion cost data and the CNF conversion cost data are generated concurrently by generating a CNF cost and DNF cost for each of a plurality of operator nodes of the operator tree by performing a single depth-first traversal of the operator tree. 13. The method of claim 1, wherein the normalized query expression is automatically set to the query expression in response to determining the query expression is in one of: CNF form or DNF form. 14. The method of claim 13, further comprising:
determining whether the query expression is in one of: CNF form or DNF form; and foregoing the generating of the CNF conversion cost data and the generating of the DNF conversion cost data in response to determining the query expression is in one of: CNF form or DNF form; wherein the CNF conversion cost data and the DNF conversion cost data are generated in response to determining the query expression is not in one of: CNF form or DNF form. 15. The method of claim 14, wherein determining whether the query expression is in one of: CNF form or DNF form, is based on the operator tree. 16. The method of claim 1, wherein facilitating execution of the query in accordance with the normalized query expression includes generating a query operator execution flow based on the normal query expression and further includes performing a plurality of operator executions of a plurality of operators of the query operator execution flow. 17. The method of claim 1, wherein the CNF conversion is selected in the conversion selection data, wherein the normalized query expression is generated by performing the CNF conversion upon the query expression based on the CNF conversion being selected in the conversion selection data, further comprising:
determining a second query expression indicating a second query for execution; generating a second operator tree based on a nested ordering of a second plurality of operators indicated by the second query expression; generating second CNF conversion cost data based on the second operator tree; generating second DNF conversion cost data based on the second operator tree; generating second conversion selection data, based on the second CNF conversion cost data and the second DNF conversion cost data, that indicates a selection to perform upon a DNF conversion upon the second query expression; generating a second normalized query expression by performing the DNF conversion upon the second query expression based on the second conversion selection data; and facilitating execution of the second query in accordance with the second normalized query expression. 18. The method of claim 17, wherein facilitating execution of the query includes performing a first plurality of operator executions of a first plurality of operators in accordance with a CNF query operator execution flow generated for the query, wherein performance of the first plurality of operator executions spans a first temporal period, wherein facilitating execution of the second query includes performing a second plurality of operator executions of a second plurality of operators in accordance with a DNF query operator execution flow generated for the second query, wherein performance of the second plurality of operator executions spans a second temporal period, and wherein the first temporal period has a non-null overlap with the second temporal period. 19. A query expression processing module comprising:
at least one processor; and memory that stores executable instructions that, when executed by the at least one processor, cause the query expression processing module to:
determine a query expression indicating a query for execution;
generate an operator tree based on a nested ordering of a plurality of operators indicated by the query expression;
generate conjunctive normal form (CNF) conversion cost data based on the operator tree;
generate disjunctive normal form (DNF) conversion cost data based on the operator tree;
generate conversion selection data, based on the CNF conversion cost data and the DNF conversion cost data, that indicates a selection to perform, upon the query expression, one of: a CNF conversion or a DNF conversion;
generate a normalized query expression by performing the one of: the CNF conversion or the DNF conversion upon the query expression based on the conversion selection data; and
facilitate execution of the query in accordance with the normalized query expression. 20. A non-transitory computer readable storage medium comprises:
at least one memory section that stores operational instructions that, when executed by a processing module that includes a processor and a memory, causes the processing module to:
determine a query expression indicating a query for execution;
generate an operator tree based on a nested ordering of a plurality of operators indicated by the query expression;
generate conjunctive normal form (CNF) conversion cost data based on the operator tree;
generate disjunctive normal form (DNF) conversion cost data based on the operator tree;
generate conversion selection data, based on the CNF conversion cost data and the DNF conversion cost data, that indicates a selection to perform, upon the query expression, one of: a CNF conversion or a DNF conversion;
generate a normalized query expression by performing the one of: the CNF conversion or the DNF conversion upon the query expression based on the conversion selection data; and
facilitate execution of the query in accordance with the normalized query expression. | A method for execution by a query processing module includes determining a query expression indicating a query for execution. An operator tree is generated based on a nested ordering of a plurality of operators indicated by the query expression. Conjunctive normal form (CNF) conversion cost data is generated based on the operator tree, and disjunctive normal form (DNF) conversion cost data is also generated based on the operator tree. Conversion selection data is generated based on the CNF conversion cost data and the DNF conversion cost data. The conversion selection data indicates a selection to perform either a CNF conversion or a DNF conversion. A normalized query expression is generated by performing either the CNF conversion or the DNF conversion upon the query expression based on the conversion selection data. Execution of the query is facilitated in accordance with the normalized query expression.1. A method for execution by at least one processing module of a database system, comprising:
determining a query expression indicating a query for execution; generating an operator tree based on a nested ordering of a plurality of operators indicated by the query expression; generating conjunctive normal form (CNF) conversion cost data based on the operator tree; generating disjunctive normal form (DNF) conversion cost data based on the operator tree; generating conversion selection data, based on the CNF conversion cost data and the DNF conversion cost data, that indicates a selection to perform, upon the query expression, one of: a CNF conversion or a DNF conversion; generating a normalized query expression by performing the one of: the CNF conversion or the DNF conversion upon the query expression based on the conversion selection data; and facilitating execution of the query in accordance with the normalized query expression. 2. The method of claim 1, wherein the operator tree indicates the plurality of operators as a plurality of operator nodes of the operator tree;
wherein generating the CNF conversion cost data includes calculating a CNF cost for each of the plurality of operator nodes of the operator tree; wherein generating the DNF conversion cost data includes calculating a DNF cost for each of the plurality of operator nodes of the operator tree. 3. The method of claim 2, wherein calculating the CNF cost for each of the plurality of operator nodes of the operator tree includes applying a depth-first CNF calculation via a recursive process applied to the operator tree, and wherein calculating the DNF cost for each of the plurality of operator nodes of the operator tree includes applying a depth-first DNF calculation via the recursive process applied to the operator tree. 4. The method of claim 2, wherein calculating the CNF cost for each of the plurality of operator nodes of the operator tree includes, for each OR node in the operator tree, multiplying a CNF cost of each child node of the each OR node;
wherein calculating the CNF cost for each of the plurality of operator nodes of the operator tree includes, for each AND node in the operator tree, summing a CNF cost of each child node of the each AND node; wherein calculating the DNF cost for each of the plurality of operator nodes of the operator tree includes, for each OR node in the operator tree, summing a DNF cost of each child node of the each OR node; and wherein calculating the DNF cost for each of the plurality of operator nodes of the operator tree includes, for each AND node in the operator tree, multiplying a DNF cost of each child node of the each AND node. 5. The method of claim 4, wherein every leaf node of the operator tree is assigned a same DNF cost and is further assigned a same CNF cost, wherein the same DNF cost is equal to the same CNF cost. 6. The method of claim 1, wherein the nested ordering of the plurality of operators indicated by the query expression is presented in a non-normalized form. 7. The method of claim 1, wherein generating the conversion selection data includes selecting the CNF conversion when the CNF conversion cost data is more favorable than the DNF conversion cost data, and wherein generating the conversion selection data includes selecting the DNF conversion when the DNF conversion cost data is more favorable than the CNF conversion cost data. 8. The method of claim 1, wherein generating the conversion selection data includes automatically selecting the CNF conversion when the CNF conversion cost data compares favorably to a predetermined threshold CNF conversion cost. 9. The method of claim 8, wherein the DNF conversion cost data indicates a more favorable conversion cost than the CNF conversion cost data, and wherein the conversion selection data is generated to indicate selection of the CNF conversion based on the CNF conversion cost data comparing favorably to the predetermined threshold CNF conversion cost. 10. The method of claim 1, wherein generating the conversion selection data includes automatically selecting the CNF conversion when the DNF conversion cost data compares unfavorably to a predetermined threshold DNF conversion cost. 11. The method of claim 10, wherein the DNF conversion cost data indicates a more favorable conversion cost than the CNF conversion cost data, and wherein the conversion selection data is generated to indicate selection of the CNF conversion based on the DNF conversion cost data comparing unfavorably to the predetermined threshold DNF conversion cost. 12. The method of claim 1, wherein the DNF conversion cost data and the CNF conversion cost data are generated concurrently by generating a CNF cost and DNF cost for each of a plurality of operator nodes of the operator tree by performing a single depth-first traversal of the operator tree. 13. The method of claim 1, wherein the normalized query expression is automatically set to the query expression in response to determining the query expression is in one of: CNF form or DNF form. 14. The method of claim 13, further comprising:
determining whether the query expression is in one of: CNF form or DNF form; and foregoing the generating of the CNF conversion cost data and the generating of the DNF conversion cost data in response to determining the query expression is in one of: CNF form or DNF form; wherein the CNF conversion cost data and the DNF conversion cost data are generated in response to determining the query expression is not in one of: CNF form or DNF form. 15. The method of claim 14, wherein determining whether the query expression is in one of: CNF form or DNF form, is based on the operator tree. 16. The method of claim 1, wherein facilitating execution of the query in accordance with the normalized query expression includes generating a query operator execution flow based on the normal query expression and further includes performing a plurality of operator executions of a plurality of operators of the query operator execution flow. 17. The method of claim 1, wherein the CNF conversion is selected in the conversion selection data, wherein the normalized query expression is generated by performing the CNF conversion upon the query expression based on the CNF conversion being selected in the conversion selection data, further comprising:
determining a second query expression indicating a second query for execution; generating a second operator tree based on a nested ordering of a second plurality of operators indicated by the second query expression; generating second CNF conversion cost data based on the second operator tree; generating second DNF conversion cost data based on the second operator tree; generating second conversion selection data, based on the second CNF conversion cost data and the second DNF conversion cost data, that indicates a selection to perform upon a DNF conversion upon the second query expression; generating a second normalized query expression by performing the DNF conversion upon the second query expression based on the second conversion selection data; and facilitating execution of the second query in accordance with the second normalized query expression. 18. The method of claim 17, wherein facilitating execution of the query includes performing a first plurality of operator executions of a first plurality of operators in accordance with a CNF query operator execution flow generated for the query, wherein performance of the first plurality of operator executions spans a first temporal period, wherein facilitating execution of the second query includes performing a second plurality of operator executions of a second plurality of operators in accordance with a DNF query operator execution flow generated for the second query, wherein performance of the second plurality of operator executions spans a second temporal period, and wherein the first temporal period has a non-null overlap with the second temporal period. 19. A query expression processing module comprising:
at least one processor; and memory that stores executable instructions that, when executed by the at least one processor, cause the query expression processing module to:
determine a query expression indicating a query for execution;
generate an operator tree based on a nested ordering of a plurality of operators indicated by the query expression;
generate conjunctive normal form (CNF) conversion cost data based on the operator tree;
generate disjunctive normal form (DNF) conversion cost data based on the operator tree;
generate conversion selection data, based on the CNF conversion cost data and the DNF conversion cost data, that indicates a selection to perform, upon the query expression, one of: a CNF conversion or a DNF conversion;
generate a normalized query expression by performing the one of: the CNF conversion or the DNF conversion upon the query expression based on the conversion selection data; and
facilitate execution of the query in accordance with the normalized query expression. 20. A non-transitory computer readable storage medium comprises:
at least one memory section that stores operational instructions that, when executed by a processing module that includes a processor and a memory, causes the processing module to:
determine a query expression indicating a query for execution;
generate an operator tree based on a nested ordering of a plurality of operators indicated by the query expression;
generate conjunctive normal form (CNF) conversion cost data based on the operator tree;
generate disjunctive normal form (DNF) conversion cost data based on the operator tree;
generate conversion selection data, based on the CNF conversion cost data and the DNF conversion cost data, that indicates a selection to perform, upon the query expression, one of: a CNF conversion or a DNF conversion;
generate a normalized query expression by performing the one of: the CNF conversion or the DNF conversion upon the query expression based on the conversion selection data; and
facilitate execution of the query in accordance with the normalized query expression. | 2,100 |
6,572 | 6,572 | 16,138,708 | 2,138 | A processing unit includes one or more processor cores and a set of registers to store configuration information for the processing unit. The processing unit also includes a coprocessor configured to receive a request to modify a memory allocation for a kernel concurrently with the kernel executing on the at least one processor core. The coprocessor is configured to modify the memory allocation by modifying the configuration information stored in the set of registers. In some cases, initial configuration information is provided to the set of registers by a different processing unit. The initial configuration information is stored in the set of registers prior to the coprocessor modifying the configuration information. | 1. A processing unit comprising:
at least one processor core; a first set of registers to store configuration information for the processing unit; and a coprocessor configured to receive a request to modify a memory allocation for a kernel concurrently with the kernel executing on the at least one processor core and to modify the memory allocation by modifying the configuration information stored in the first set of registers. 2. The processing unit of claim 1, wherein initial configuration information is provided to the first set of registers by another processing unit external to the processing unit, and wherein the initial configuration information is stored in the first set of registers prior to the coprocessor modifying the configuration information. 3. The processing unit of claim 1, wherein the coprocessor is configured to increase the memory allocation in response to the kernel requesting additional memory resources and decrease the memory allocation in response to the kernel requesting that a portion of a previously allocated memory resources be deallocated. 4. The processing unit of claim 1, wherein the kernel requests the modification of the memory allocation by at least one of: initiating an interrupt, writing the request to a memory location that is used as a doorbell signal, or polling a memory location. 5. The processing unit of claim 1, further comprising:
a second set of registers to store arguments that define the memory allocation, and wherein the coprocessor writes modified values of the arguments to the second set of registers to indicate the modifications of the configuration information stored in the first set of registers. 6. The processing unit of claim 1, further comprising:
a pre-allocated argument buffer to store arguments that define the memory allocation, wherein the coprocessor writes modified values of the arguments to the pre-allocated argument buffer to indicate the modifications of the configuration information stored in the first set of registers, and wherein a dereference is used to load an address of the argument buffer. 7. The processing unit of claim 6, wherein the arguments include at least one of an address of a first byte of a dynamically allocated region of memory and a descriptor associated with the dynamically allocated region of memory. 8. The processing unit of claim 1, wherein the coprocessor is configured to launch a task, and wherein the task generates the request to modify the memory allocation during a lifetime of the task. 9. The processing unit of claim 1, wherein the coprocessor is configured to allocate and manage a data structure, and wherein the kernel populates or removes items from the data structure. 10. A method comprising:
storing configuration information for a first processing unit in a first set of registers; and receiving, at a coprocessor implemented in the first processing unit, a request to modify a memory allocation for a kernel concurrently with the kernel executing on at least one processor core in the first processing unit; and modifying, at the coprocessor, the memory allocation by modifying the configuration information stored in the first set of registers. 11. The method of claim 10, further comprising:
receiving, at the first processing unit from a second processing unit, initial configuration information; and storing the initial configuration information in the first set of registers prior to the coprocessor modifying the configuration information. 12. The method of claim 10, further comprising at least one of:
increasing the memory allocation in response to the kernel requesting additional memory resources; and decreasing the memory allocation in response to the kernel requesting that a portion of a previously allocated memory resources be deallocated. 13. The method of claim 10, wherein requesting the modification of the memory allocation comprises at least one of: initiating an interrupt, writing the request to a memory location that is used as a doorbell signal, or polling a memory address. 14. The method of claim 10, further comprising:
writing modified values of arguments that define the memory allocation to a second set of registers to indicate the modifications of the configuration information stored in the first set of registers. 15. The method of claim 10, further comprising:
writing modified values of arguments that define the memory allocation to a pre-allocated argument buffer to indicate the modifications of the configuration information stored in the first set of registers, and using a dereference to load an address of the argument buffer. 16. The method of claim 15, wherein the arguments include at least one of an address of a first byte of a dynamically allocated region of memory and a descriptor associated with the dynamically allocated region of memory. 17. The method of claim 10, launching, from the coprocessor, a task that generates the request to modify the memory allocation during a lifetime of the task. 18. The method of claim 10, further comprising:
allocating and managing a data structure at the coprocessor, and wherein the kernel populates or removes items from the data structure. 19. A processing unit comprising:
a memory pool including a plurality of regions; and a coprocessor configured to receive a request to modify an allocation of the plurality of regions for a kernel concurrently with the kernel executing on a shader in the processing unit. 20. The processing unit of claim 19, wherein the memory pool stores metadata for the plurality of regions and free lists indicating whether the plurality of regions are free or in use. | A processing unit includes one or more processor cores and a set of registers to store configuration information for the processing unit. The processing unit also includes a coprocessor configured to receive a request to modify a memory allocation for a kernel concurrently with the kernel executing on the at least one processor core. The coprocessor is configured to modify the memory allocation by modifying the configuration information stored in the set of registers. In some cases, initial configuration information is provided to the set of registers by a different processing unit. The initial configuration information is stored in the set of registers prior to the coprocessor modifying the configuration information.1. A processing unit comprising:
at least one processor core; a first set of registers to store configuration information for the processing unit; and a coprocessor configured to receive a request to modify a memory allocation for a kernel concurrently with the kernel executing on the at least one processor core and to modify the memory allocation by modifying the configuration information stored in the first set of registers. 2. The processing unit of claim 1, wherein initial configuration information is provided to the first set of registers by another processing unit external to the processing unit, and wherein the initial configuration information is stored in the first set of registers prior to the coprocessor modifying the configuration information. 3. The processing unit of claim 1, wherein the coprocessor is configured to increase the memory allocation in response to the kernel requesting additional memory resources and decrease the memory allocation in response to the kernel requesting that a portion of a previously allocated memory resources be deallocated. 4. The processing unit of claim 1, wherein the kernel requests the modification of the memory allocation by at least one of: initiating an interrupt, writing the request to a memory location that is used as a doorbell signal, or polling a memory location. 5. The processing unit of claim 1, further comprising:
a second set of registers to store arguments that define the memory allocation, and wherein the coprocessor writes modified values of the arguments to the second set of registers to indicate the modifications of the configuration information stored in the first set of registers. 6. The processing unit of claim 1, further comprising:
a pre-allocated argument buffer to store arguments that define the memory allocation, wherein the coprocessor writes modified values of the arguments to the pre-allocated argument buffer to indicate the modifications of the configuration information stored in the first set of registers, and wherein a dereference is used to load an address of the argument buffer. 7. The processing unit of claim 6, wherein the arguments include at least one of an address of a first byte of a dynamically allocated region of memory and a descriptor associated with the dynamically allocated region of memory. 8. The processing unit of claim 1, wherein the coprocessor is configured to launch a task, and wherein the task generates the request to modify the memory allocation during a lifetime of the task. 9. The processing unit of claim 1, wherein the coprocessor is configured to allocate and manage a data structure, and wherein the kernel populates or removes items from the data structure. 10. A method comprising:
storing configuration information for a first processing unit in a first set of registers; and receiving, at a coprocessor implemented in the first processing unit, a request to modify a memory allocation for a kernel concurrently with the kernel executing on at least one processor core in the first processing unit; and modifying, at the coprocessor, the memory allocation by modifying the configuration information stored in the first set of registers. 11. The method of claim 10, further comprising:
receiving, at the first processing unit from a second processing unit, initial configuration information; and storing the initial configuration information in the first set of registers prior to the coprocessor modifying the configuration information. 12. The method of claim 10, further comprising at least one of:
increasing the memory allocation in response to the kernel requesting additional memory resources; and decreasing the memory allocation in response to the kernel requesting that a portion of a previously allocated memory resources be deallocated. 13. The method of claim 10, wherein requesting the modification of the memory allocation comprises at least one of: initiating an interrupt, writing the request to a memory location that is used as a doorbell signal, or polling a memory address. 14. The method of claim 10, further comprising:
writing modified values of arguments that define the memory allocation to a second set of registers to indicate the modifications of the configuration information stored in the first set of registers. 15. The method of claim 10, further comprising:
writing modified values of arguments that define the memory allocation to a pre-allocated argument buffer to indicate the modifications of the configuration information stored in the first set of registers, and using a dereference to load an address of the argument buffer. 16. The method of claim 15, wherein the arguments include at least one of an address of a first byte of a dynamically allocated region of memory and a descriptor associated with the dynamically allocated region of memory. 17. The method of claim 10, launching, from the coprocessor, a task that generates the request to modify the memory allocation during a lifetime of the task. 18. The method of claim 10, further comprising:
allocating and managing a data structure at the coprocessor, and wherein the kernel populates or removes items from the data structure. 19. A processing unit comprising:
a memory pool including a plurality of regions; and a coprocessor configured to receive a request to modify an allocation of the plurality of regions for a kernel concurrently with the kernel executing on a shader in the processing unit. 20. The processing unit of claim 19, wherein the memory pool stores metadata for the plurality of regions and free lists indicating whether the plurality of regions are free or in use. | 2,100 |
6,573 | 6,573 | 15,299,124 | 2,125 | This document discloses effective augmented telepathic communication as a gadget-free extension of human senses. The conveyance of mental information and cognitive processes to perceive or communicate being made possible by data structures for generating and maintaining representations of biological systems activity with auditory, visual, kinesthetic, tactile, emotion, movement, smell, taste, and concept data in a computing environment. In preferable embodiments of the present invention, one or more methods include steps for representing brain, nervous system, and sensory systems activity with mental information and cognitive processes as data for incorporating values with applications, systems, or instance relevant computing environments. In a preferable embodiment of the present invention, methods also include the association of data representing the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with mixes of machine learning tasks for human-computer interfacing and communicating using optional devices or acting as a biological computing environment. | 1. A non-transitory computer readable medium containing data representing either of or both data structures and program instructions for generating, analyzing, extending, communicating, integrating, storing, converting, editing, encoding, or maintaining said data structures representing one or more unit of category Nervous System depicting referring expressions relating to nervous system cells, nerves, tissue, electrical or chemical impulses, and trace occurrences related to signaling the communication of information and its processing in a biological body optionally with zero, one, or more unit of category Sensory System depicting referring expressions relating to sensory systems cells, nerves, tissue, electrical or chemical impulses, and trace occurrences related to signaling the communication of sensory information for its interpretation or processing in a biological body and zero, one, or more unit of category Brain and Nerve Activity optionally depicting referring expressions associating Nervous System category units with Sensory System category units wherein zero, one, or more Brain and Nerve Activity, zero, one, or more Sensory System, and one or more Nervous System units with Sensory System and Nervous System units optionally relating as Brain and Nerve Activity units being associated with one or more unit in at least one of the following categories:
Communication depicting referring expressions relating to the conveyance of ideas as sound, visual imagery, text, concept, or feelings; Cognition depicting referring expressions relating to considering, knowing, understanding, or believing; Perception depicting referring expressions relating to sensing, perceiving, observing, or becoming aware; Experience depicting referring expressions relating to feeling or reflecting on abstractions; Imagery depicting referring expressions relating to the visually perceived, remembered, or imagined; Sound depicting referring expressions relating to the auditorily perceived, remembered, or imagined; Symbol depicting referring expressions relating to meanings; Stimulus depicting referring expressions relating to evoking actions and conditions; Behavior depicting referring expressions relating to acting as or reacting to a stimulus; and People depicting referring expressions relating to community groups and individuals wherein each Brain and Nerve Activity, Sensory System, Nervous System, Communication, Cognition, Perception, Experience, Imagery, Sound, Symbol, Stimulus, Behavior, and People category unit consisting of zero, one, or more members with each member describing one or more object, element, asset, act, condition, process, or product representing zero, one, or more event, status, location, or hierarchical coordinate system and having zero, one, or more relationship, reference, property, description, or dimension of interest wherein data structures representing one or more unit in one or more category being generated using one or more referring expression and zero, one, or more hierarchical coordinate system by an optional method comprising the steps of: analyzing one or more body; obtaining information about one or more body; and generating one or more representation. 2. The non-transitory computer readable medium of claim 1, wherein the analyzing step of the optional method comprising the examination of any object, element, asset, act, condition, process, or product of the biological systems, communication, or behavior of one or more body using zero, one, or a plurality of wearable or surgically implanted device, sensor, probe, or electrode with zero, one, or more proximity to one or more body using zero, one, or more wearable or surgically implanted device, sensor, probe, or electrode. 3. The non-transitory computer readable medium of claim 2, wherein data structures being generated or maintained comprising at least one of the following:
data representing information obtained from one or more body with zero, one, or more representation of a vantage optionally being associated with referring expressions relating the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representation of a vantage; data representing one or more referring expression relating one or more representation of: (visual, auditory, or kinesthetic data obtained from one or more body with zero, one, or more representation of a vantage; non-verbal, verbal, perceived, remembered, or imagined communication with zero, one, or more representation of a vantage; measurement, activity, or condition associated with zero, one, or more location of one or more of the following obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body: biological systems, sensory systems, nervous system, brain cells, nerves, tissue, electrical impulse events, molecular signaling, chemical changes, magnetic properties, and trace occurrences; or text, sound, visual imagery, thought, idea, meaning, relationship, feeling, and communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body with zero, one, or more representation of a vantage); data representing one or more parameter in stimulation transmission signal formatting instructions, wherein stimulation transmission signal comprising one or more referring expression relating: (one or more representation of text, sound, visual imagery, thought, idea, meaning, relationship, feeling, vantage, or communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body; perception or cognition directly to biological systems of one or more body; visual, auditory, or kinesthetic perception or cognition directly to biological systems of one or more body; non-verbal, verbal, perceived, remembered, or imagined communication directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, remembering, imagining, or cognizing using sound, visual imagery, text, and feelings directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representations of a vantage; or subliminal information optionally being combined with auditory, visual, kinesthetic, tactile, emotion, concept, movement, smell, taste, or communications data directly to biological systems of one or more consuming or interacting body); data representing one or more referring expression relating: (active and passive user information; one or more representation comprising information obtained about one or more body using satellite-based technologies, ambient fields, microscopy techniques, interferometry methods, remote sensing, radar, radio, optics, directed energy, or tracking technologies; one or more interacting or interfacing body with the objects, elements, assets, acts, conditions, processes, or products of one or more computing environment using zero, one, or more hardware component or device item; communication without optional subvocalization, voicing, writing, or gesturing; one or more body with data structures or program instructions performing one or more financial transaction using one or more program, application, interface, or marketplace; one or more body with data structures or program instructions performing one or more of the following tasks: analyzing, extending, communicating, integrating, storing, converting, editing, or encoding; one or more body with data structures or program instructions interfacing one or more human user participating as one or more biological computing environment in networking arrangement with zero, one, or more computing environment; one or more body with data structures or program instructions interfacing one or more user interacting with one or more computing environment using zero localized input devices, zero, one, or more thought, zero, one, or more voiced command, and zero, one, or more gesture; one or more representation of one or more object, element, asset, act, condition, process, or product of data being associated by zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; or representations of communication, sensory or nervous system information, perception, cognition, experiences, stimulus, behavior, or relevant conditions with one or more referring expression from first-person, second-person, or third-person perspectives in the manner of zero, one, or more of each of the following: graphically, programmatically, computationally, textually, numerically, symbolically, audibly, sequentially, or conceptually); and data representing one or more referring expression relating at least one body with data structures or program instructions interfacing at least one body with one or more computing environment returning output from, associating one or more representation with output from, or executing at least one of the following process activity types: (performing tasks supporting communication, search, education, entertainment, research, navigation, measurement, calculation, business, productivity, language tools and translation, song recognition, augmented reality, situational awareness, decision support, medical or psychological treatment, social information interpretation, law enforcement, military, security, surveillance, authorization, access control, building automation, financial transaction, instant knowledge, memory extension, intelligence amplification, graphic design, three dimensional modeling, three dimensional printing, dreams, public speaking, performance, self improvement, or personal development; biometric measurement of the face, ear, eye, iris, retina, fingerprint, finger or hand geometry, gait, odor, or voice; locating, identifying, verifying, classifying, profiling, or recognizing of objects, structures, groups, or individuals with zero, one, or more of the following: facial expression, body language, posture, gesture, tone, proximity, signature or handwriting, typing, writing style, word or phrase choice, registration information, or license plate; or computer vision, pattern recognition, shape recognition, object recognition, biometric measurement, speech or voice recognition, geography, proximity, character recognition, or eye tracking). 4. The non-transitory computer readable medium of claim 3, wherein data structures representing one or more unit in at least one category being associated by either the means of one or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement or an optional method comprising the steps of:
analyzing at least one category unit member using one or more referring expression and the optional means of zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; obtaining zero, one, or more referring expression; and generating one or more representation. 5. A machine having a memory containing data representing either of or both data structures and program instructions for generating, analyzing, extending, communicating, integrating, storing, converting, editing, encoding, or maintaining said data structures representing one or more unit in at least one of the following categories:
Mental Information depicting referring expressions relating to the known, believed, and understood; Cognitive Processes depicting referring expressions relating to sensing, observing, considering, imagining, feeling, experiencing, remembering, and committing to memory; Communications Information depicting referring expressions relating to conveying ideas, acting as a stimulus, and responding to stimulus; Biological Systems depicting referring expressions relating to application relevant organs, divisions, tissue, cells, nerves, processes, or activities in a biological body; Biological Systems Activity depicting referring expressions relating to the application relevant processes or activity pertaining to organs, divisions, tissue, cells, nerves, electrical or chemical impulses, and trace occurrences related to signaling the communication of information and its processing in a biological body; People depicting referring expressions relating to community groups and individuals; and Stimulus depicting referring expressions relating to evoking actions and conditions; wherein each Mental Information, Cognitive Processes, Communications Information, Biological Systems, Biological Systems Activity, People, and Stimulus category unit consisting of zero, one, or more members with each member describing one or more object, element, asset, act, condition, process, or product and representing zero, one, or more event, status, location, or hierarchical coordinate system and having zero, one, or more relationship, reference, property, description, or dimension of interest. 6. The machine of claim 5, wherein data structures representing at least one unit in one or more category being generated using one or more referring expression and zero, one, or more hierarchical coordinate system by an optional method comprising the steps of:
analyzing one or more body; obtaining information about one or more body; and generating one or more representation. 7. The machine of claim 6, wherein data structures being generated or maintained comprising at least one of the following:
data representing information obtained from one or more body with zero, one, or more representation of a vantage optionally being associated with referring expressions relating the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representation of a vantage; data representing one or more referring expression relating one or more representation of: (visual, auditory, or kinesthetic data obtained from one or more body with zero, one, or more representation of a vantage; non-verbal, verbal, perceived, remembered, or imagined communication with zero, one, or more representation of a vantage; measurement, activity, or condition associated with zero, one, or more location of one or more of the following obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body: biological systems, sensory systems, nervous system, brain cells, nerves, tissue, electrical impulse events, molecular signaling, chemical changes, magnetic properties, and trace occurrences; or text, sound, visual imagery, thought, idea, meaning, relationship, feeling, and communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body with zero, one, or more representation of a vantage); data representing one or more parameter in stimulation transmission signal formatting instructions, wherein stimulation transmission signal comprising one or more referring expression relating: (one or more representation of text, sound, visual imagery, thought, idea, meaning, relationship, feeling, vantage, or communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body; perception or cognition directly to biological systems of one or more body; visual, auditory, or kinesthetic perception or cognition directly to biological systems of one or more body; non-verbal, verbal, perceived, remembered, or imagined communication directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, remembering, imagining, or cognizing using sound, visual imagery, text, and feelings directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representations of a vantage; or subliminal information optionally being combined with auditory, visual, kinesthetic, tactile, emotion, concept, movement, smell, taste, or communications data directly to biological systems of one or more consuming or interacting body); data representing one or more referring expression relating: (active and passive user information; one or more representation comprising information obtained about one or more body using satellite-based technologies, ambient fields, microscopy techniques, interferometry methods, remote sensing, radar, radio, optics, directed energy, or tracking technologies; one or more interacting or interfacing body with the objects, elements, assets, acts, conditions, processes, or products of one or more computing environment using zero, one, or more hardware component or device item; communication without optional subvocalization, voicing, writing, or gesturing; one or more body with data structures or program instructions performing one or more financial transaction using one or more program, application, interface, or marketplace; one or more body with data structures or program instructions performing one or more of the following tasks: analyzing, extending, communicating, integrating, storing, converting, editing, or encoding; one or more body with data structures or program instructions interfacing one or more human user participating as one or more biological computing environment in networking arrangement with zero, one, or more computing environment; one or more body with data structures or program instructions interfacing one or more user interacting with one or more computing environment using zero localized input devices, zero, one, or more thought, zero, one, or more voiced command, and zero, one, or more gesture; one or more representation of one or more object, element, asset, act, condition, process, or product of data being associated by zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; or representations of communication, sensory or nervous system information, perception, cognition, experiences, stimulus, behavior, or relevant conditions with one or more referring expression from first-person, second-person, or third-person perspectives in the manner of zero, one, or more of each of the following: graphically, programmatically, computationally, textually, numerically, symbolically, audibly, sequentially, or conceptually); and data representing one or more referring expression relating at least one body with data structures or program instructions interfacing at least one body with one or more computing environment returning output from, associating one or more representation with output from, or executing at least one of the following process activity types: (performing tasks supporting communication, search, education, entertainment, research, navigation, measurement, calculation, business, productivity, language tools and translation, song recognition, augmented reality, situational awareness, decision support, medical or psychological treatment, social information interpretation, law enforcement, military, security, surveillance, authorization, access control, building automation, financial transaction, instant knowledge, memory extension, intelligence amplification, graphic design, three dimensional modeling, three dimensional printing, dreams, public speaking, performance, self improvement, or personal development; biometric measurement of the face, ear, eye, iris, retina, fingerprint, finger or hand geometry, gait, odor, or voice; locating, identifying, verifying, classifying, profiling, or recognizing of objects, structures, groups, or individuals with zero, one, or more of the following: facial expression, body language, posture, gesture, tone, proximity, signature or handwriting, typing, writing style, word or phrase choice, registration information, or license plate; or computer vision, pattern recognition, shape recognition, object recognition, biometric measurement, speech or voice recognition, geography, proximity, character recognition, or eye tracking). 8. The machine of claim 7, wherein the analyzing step of the optional method comprising the examination of any object, element, asset, act, condition, process, or product of biological systems, communication, stimulus, or behavior of one or more bodies using zero, one, or a plurality of wearable or surgically implanted device, sensor, probe, or electrode with zero, one, or more proximity to one or more body using zero, one, or more wearable or surgically implanted device, sensor, probe, or electrode. 9. The machine of claim 8, wherein data structures representing one or more unit in at least one category being associated by either the means of one or more machine learning task classified under zero, one, or more of the following category types:
supervised, semi-supervised, unsupervised, and reinforcement or an optional method comprising the steps of: analyzing one or more category unit members using one or more referring expression and the optional means of zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; obtaining zero, one, or more referring expression; and generating one or more representation. 10. A system having a memory containing data representing either of or both data structures and program instructions for generating, analyzing, extending, communicating, integrating, storing, converting, editing, encoding, or maintaining said data structures representing one or more unit in at least one of the following categories:
Brain Activity depicting referring expressions relating brain cells, nerves, tissue, electrical or chemical impulses, and trace occurrences related to signaling the communication of sensory, bodily, mental, and cognitive information and its processing in the brain of a biological body; Nerve Activity depicting referring expressions relating cells, nerves, tissue, electrical or chemical impulses, and trace occurrences related to signaling the communication of sensory and bodily information and its processing outside of the brain of a biological body; Physical Structure depicting referring expressions relating to proximity or application relevant organs, divisions, tissue, cells, nerves and the imparting references of each constituent; Communication depicting referring expressions relating to the conveyance of ideas, acting as a stimulus, or reacting to a stimulus; Thought depicting referring expressions relating to perceiving, experiencing, considering, and cognizing sensory information, knowledge, abstractions, or stimulus relevant mental actions; Imagery depicting referring expressions relating to the visually perceived, remembered, or imagined; Sound depicting referring expressions relating to the auditorily perceived, remembered, or imagined; Symbol depicting referring expressions relating to perceiving, imagining, experiencing, and cognizing meanings; People depicting referring expressions relating to community groups and individuals; and Stimulus depicting referring expressions relating to evoking actions and conditions; wherein each Brain Activity, Nerve Activity, Physical Structures, Communication, Thought, Imagery, Sound, Symbol, People, and Stimulus category unit consisting of zero, one, or more member with each member describing one or more object, element, asset, act, condition, process, or product and representing zero, one, or more event, status, location, or hierarchical coordinate system and having zero, one, or more relationship, reference, property, description, or dimension of interest. 11. The system of claim 10, wherein data structures representing at least one unit in one or more category being generated using one or more referring expression and zero, one, or more hierarchical coordinate system by an optional method comprising the steps of:
analyzing one or more body; obtaining information about one or more body; and generating one or more representation. 12. The system of claim 11, wherein data structures being generated or maintained comprising at least one of the following:
data representing information obtained from one or more body with zero, one, or more representation of a vantage optionally being associated with referring expressions relating the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representation of a vantage; data representing one or more referring expression relating one or more representation of: (visual, auditory, or kinesthetic data obtained from one or more body with zero, one, or more representation of a vantage; non-verbal, verbal, perceived, remembered, or imagined communication with zero, one, or more representation of a vantage; measurement, activity, or condition associated with zero, one, or more location of one or more of the following obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body: biological systems, sensory systems, nervous system, brain cells, nerves, tissue, electrical impulse events, molecular signaling, chemical changes, magnetic properties, and trace occurrences; or text, sound, visual imagery, thought, idea, meaning, relationship, feeling, and communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body with zero, one, or more representation of a vantage); data representing one or more parameter in stimulation transmission signal formatting instructions, wherein stimulation transmission signal comprising one or more referring expression relating: (one or more representation of text, sound, visual imagery, thought, idea, meaning, relationship, feeling, vantage, or communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body; perception or cognition directly to biological systems of one or more body; visual, auditory, or kinesthetic perception or cognition directly to biological systems of one or more body; non-verbal, verbal, perceived, remembered, or imagined communication directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, remembering, imagining, or cognizing using sound, visual imagery, text, and feelings directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representations of a vantage; or subliminal information optionally being combined with auditory, visual, kinesthetic, tactile, emotion, concept, movement, smell, taste, or communications data directly to biological systems of one or more consuming or interacting body); data representing one or more referring expression relating: (active and passive user information; one or more representation comprising information obtained about one or more body using satellite-based technologies, ambient fields, microscopy techniques, interferometry methods, remote sensing, radar, radio, optics, directed energy, or tracking technologies; one or more interacting or interfacing body with the objects, elements, assets, acts, conditions, processes, or products of one or more computing environment using zero, one, or more hardware component or device item; communication without optional subvocalization, voicing, writing, or gesturing; one or more body with data structures or program instructions performing one or more financial transaction using one or more program, application, interface, or marketplace; one or more body with data structures or program instructions performing one or more of the following tasks: analyzing, extending, communicating, integrating, storing, converting, editing, or encoding; one or more body with data structures or program instructions interfacing one or more human user participating as one or more biological computing environment in networking arrangement with zero, one, or more computing environment; one or more body with data structures or program instructions interfacing one or more user interacting with one or more computing environment using zero localized input devices, zero, one, or more thought, zero, one, or more voiced command, and zero, one, or more gesture; one or more representation of one or more object, element, asset, act, condition, process, or product of data being associated by zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; or representations of communication, sensory or nervous system information, perception, cognition, experiences, stimulus, behavior, or relevant conditions with one or more referring expression from first-person, second-person, or third-person perspectives in the manner of zero, one, or more of each of the following: graphically, programmatically, computationally, textually, numerically, symbolically, audibly, sequentially, or conceptually); and data representing one or more referring expression relating at least one body with data structures or program instructions interfacing at least one body with one or more computing environment returning output from, associating one or more representation with output from, or executing at least one of the following process activity types: (performing tasks supporting communication, search, education, entertainment, research, navigation, measurement, calculation, business, productivity, language tools and translation, song recognition, augmented reality, situational awareness, decision support, medical or psychological treatment, social information interpretation, law enforcement, military, security, surveillance, authorization, access control, building automation, financial transaction, instant knowledge, memory extension, intelligence amplification, graphic design, three dimensional modeling, three dimensional printing, dreams, public speaking, performance, self improvement, or personal development; biometric measurement of the face, ear, eye, iris, retina, fingerprint, finger or hand geometry, gait, odor, or voice; locating, identifying, verifying, classifying, profiling, or recognizing of objects, structures, groups, or individuals with zero, one, or more of the following: facial expression, body language, posture, gesture, tone, proximity, signature or handwriting, typing, writing style, word or phrase choice, registration information, or license plate; or computer vision, pattern recognition, shape recognition, object recognition, biometric measurement, speech or voice recognition, geography, proximity, character recognition, or eye tracking). 13. The system of claim 12, wherein the analyzing step of the optional method comprising the examination of any object, element, asset, act, condition, process, or product of biological systems, communication, stimulus, or behavior of one or more body using zero, one, or a plurality of wearable or surgically implanted device, sensor, probe, or electrode with zero, one, or more proximity to one or more body using zero, one, or more wearable or surgically implanted device, sensor, probe, or electrode. 14. The system of claim 13, wherein data structures representing one or more unit in at least one category being associated by either the means of one or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement or an optional method comprising the steps of:
analyzing one or more category unit members using one or more referring expression and the optional means of zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; obtaining zero, one, or more referring expression; and generating one or more representation. 15. A method of obtaining and distributing communication data from an artificial satellite comprising:
receiving one or more source signal from one or more transmitter, transmission station, or artificial satellite and relaying one or more source signal toward one or more body with at least one source signal comprising one or more of the following: data representing one or more parameter in signal formatting instructions, wherein signal relating one or more modulating representation directly stimulating biological systems in one or more body with one or more visual, auditory, or kinesthetic element being mentally perceived and zero, one, or more instance being adapted to the subliminal; data representing one or more parameter in signal formatting instructions, wherein signal relating mental information or cognitive processes obtained from measuring and optionally associating biological systems data of one or more body; modulating representations directly stimulating biological systems in one or more body with one or more image, sound, or feeling being mentally perceived and zero, one, or more instance being adapted to the subliminal; one or more transcranial stimulation field stimulating the brain, nervous system, skin, or other biological systems in one or more body; at least one transcranial stimulation field stimulating the brain, nervous system, skin, or other biological systems in one or more body being paired with modulating representations directly stimulating biological systems in one or more body with one or more image, sound, or feeling being mentally perceived and zero, one, or more instance being adapted to the subliminal; one or more sample, measurement, image, or any data representing at least one measurement or referring expression relating biological systems, brain cell, nerve, or tissue activity and conditions in one or more body with one or more measurement or referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing one or more referring expression relating sound, visual imagery, ideas, meanings, relationships, or feelings obtained from biological systems data of at least one body with one or more referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing communication without optional subvocalization, voicing, writing, or gesturing; and one or more sample, measurement, image, or any data relating activity, conditions, positions, or location of biological systems, brain cells, nerves, or tissue of one or more biological body in the act of perceiving, experiencing, imagining, remembering, cognizing, or communicating one or more of the following: non-verbal, verbal, perceived, remembered, or imagined communication; sound, visual imagery, ideas, meanings, relationships, or feelings; and objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, imagining, remembering, cognizing, or communicating. 16. The method of claim 15, further comprising:
obtaining one or more measurement or one or more referring expression relating biological systems, brain cell, nerve, or tissue activity, conditions, positions, or locations with one or more optional vantage describing communication of one or more biological body and receiving, relaying, or distributing one or more sample, measurement, image, or referring expression, data relaying or distributing representations of measurement relating biological systems, brain cell, nerve, or tissue activity and conditions of one or more body, or one or more response signal regarding one or more body, a response signal comprising at least one of the following: data representing one or more parameter in signal formatting instructions, wherein signal relating mental information or cognitive processes obtained from measuring and optionally associating biological systems data of one or more body; one or more sample, measurement, image, or any data representing at least one measurement or referring expression relating biological systems, brain cell, nerve, or tissue activity and conditions in one or more body with one or more measurement or referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing one or more referring expression relating sound, visual imagery, ideas, meanings, relationships, or feelings obtained from biological systems data of at least one body with one or more referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing communication without optional subvocalization, voicing, writing, or gesturing; and one or more sample, measurement, image, or any data relating activity, conditions, positions, or location of biological systems, brain cells, nerves, or tissue of one or more biological body in the act of perceiving, experiencing, imagining, remembering, cognizing, or communicating one or more of the following: non-verbal, verbal, perceived, remembered, or imagined communication; sound, visual imagery, ideas, meanings, relationships, or feelings; and objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, imagining, remembering, cognizing, or communicating. 17. The method of claim 16, further comprising:
relaying one or more response signal toward one or more receiver or receiving station; evaluating one or more response signal; and generating one or more representation. 18. The method of claim 17, wherein one or more representation or referring expression being associated by either the means of one or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement or an optional method comprising the steps of:
analyzing one or more representation or referring expression using one or more referring expression and the optional means of zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; obtaining zero, one, or more referring expression; and generating one or more representation. 19. A communications system comprising one or more computing environment having configuration to at least generate and maintain representations, at least one transmitter or transmission station having configuration to at least transmit, relay, or distribute one or more signal, one or more receiver or receiving station having configuration to at least receive one or more signal, one or more artificial satellite having configuration to receive, relay, transmit, or distribute one or more signal, at least one artificial satellite having configuration to sense or image accordingly, and zero, one, or more device having configuration to format or support one or more signal or signal product accordingly wherein one or more signal being sensed, sampled, imaged, transmitted, relayed, received, or distributed comprising one or more of the following:
data representing one or more parameter in signal formatting instructions, wherein signal relating one or more modulating representation directly stimulating biological systems in one or more body with one or more visual, auditory, or kinesthetic element being mentally perceived and zero, one, or more instance being adapted to the subliminal; data representing one or more parameter in signal formatting instructions, wherein signal relating mental information or cognitive processes obtained from measuring and optionally associating biological systems data of one or more body; modulating representations directly stimulating biological systems in one or more body with one or more image, sound, or feeling being mentally perceived and zero, one, or more instance being adapted to the subliminal; one or more transcranial stimulation field stimulating the brain, nervous system, skin, or other biological systems in one or more body; at least one transcranial stimulation field stimulating the brain, nervous system, skin, or other biological systems in one or more body being paired with modulating representations directly stimulating biological systems in one or more body with one or more image, sound, or feeling being mentally perceived and zero, one, or more instance being adapted to the subliminal; one or more sample, measurement, image, or any data representing at least one measurement or referring expression relating biological systems, brain cell, nerve, or tissue activity and conditions in one or more body with one or more measurement or referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing one or more referring expression relating sound, visual imagery, ideas, meanings, relationships, or feelings obtained from biological systems data of at least one body with one or more referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing communication without optional subvocalization, voicing, writing, or gesturing; and one or more sample, measurement, image, or any data relating activity, conditions, positions, or location of biological systems, brain cells, nerves, or tissue of one or more biological body in the act of perceiving, experiencing, imagining, remembering, cognizing, or communicating one or more of the following: non-verbal, verbal, perceived, remembered, or imagined communication; sound, visual imagery, ideas, meanings, relationships, or feelings; and objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, imagining, remembering, cognizing, or communicating. 20. The communications system of claim 19, wherein data structures being generated or maintained comprising at least one of the following:
data representing information obtained from one or more body with zero, one, or more representation of a vantage optionally being associated with referring expressions relating the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representation of a vantage; data representing one or more referring expression relating one or more representation of: (visual, auditory, or kinesthetic data obtained from one or more body with zero, one, or more representation of a vantage; non-verbal, verbal, perceived, remembered, or imagined communication with zero, one, or more representation of a vantage; measurement, activity, or condition associated with zero, one, or more location of one or more of the following obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body: biological systems, sensory systems, nervous system, brain cells, nerves, tissue, electrical impulse events, molecular signaling, chemical changes, magnetic properties, and trace occurrences; or text, sound, visual imagery, thought, idea, meaning, relationship, feeling, and communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body with zero, one, or more representation of a vantage); data representing one or more parameter in stimulation transmission signal formatting instructions, wherein stimulation transmission signal comprising one or more referring expression relating: (one or more representation of text, sound, visual imagery, thought, idea, meaning, relationship, feeling, vantage, or communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body; perception or cognition directly to biological systems of one or more body; visual, auditory, or kinesthetic perception or cognition directly to biological systems of one or more body; non-verbal, verbal, perceived, remembered, or imagined communication directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, remembering, imagining, or cognizing using sound, visual imagery, text, and feelings directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representations of a vantage; or subliminal information optionally being combined with auditory, visual, kinesthetic, tactile, emotion, concept, movement, smell, taste, or communications data directly to biological systems of one or more consuming or interacting body); data representing one or more referring expression relating: (active and passive user information; one or more representation comprising information obtained about one or more body using satellite-based technologies, ambient fields, microscopy techniques, interferometry methods, remote sensing, radar, radio, optics, directed energy, or tracking technologies; one or more interacting or interfacing body with the objects, elements, assets, acts, conditions, processes, or products of one or more computing environment using zero, one, or more hardware component or device item; communication without optional subvocalization, voicing, writing, or gesturing; one or more body with data structures or program instructions performing one or more financial transaction using one or more program, application, interface, or marketplace; one or more body with data structures or program instructions performing one or more of the following tasks: analyzing, extending, communicating, integrating, storing, converting, editing, or encoding; one or more body with data structures or program instructions interfacing one or more human user participating as one or more biological computing environment in networking arrangement with zero, one, or more computing environment; one or more body with data structures or program instructions interfacing one or more user interacting with one or more computing environment using zero localized input devices, zero, one, or more thought, zero, one, or more voiced command, and zero, one, or more gesture; one or more representation of one or more object, element, asset, act, condition, process, or product of data being associated by zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; or representations of communication, sensory or nervous system information, perception, cognition, experiences, stimulus, behavior, or relevant conditions with one or more referring expression from first-person, second-person, or third-person perspectives in the manner of zero, one, or more of each of the following: graphically, programmatically, computationally, textually, numerically, symbolically, audibly, sequentially, or conceptually); and data representing one or more referring expression relating at least one body with data structures or program instructions interfacing at least one body with one or more computing environment returning output from, associating one or more representation with output from, or executing at least one of the following process activity types: (performing tasks supporting communication, search, education, entertainment, research, navigation, measurement, calculation, business, productivity, language tools and translation, song recognition, augmented reality, situational awareness, decision support, medical or psychological treatment, social information interpretation, law enforcement, military, security, surveillance, authorization, access control, building automation, financial transaction, instant knowledge, memory extension, intelligence amplification, graphic design, three dimensional modeling, three dimensional printing, dreams, public speaking, performance, self improvement, or personal development; biometric measurement of the face, ear, eye, iris, retina, fingerprint, finger or hand geometry, gait, odor, or voice; locating, identifying, verifying, classifying, profiling, or recognizing of objects, structures, groups, or individuals with zero, one, or more of the following: facial expression, body language, posture, gesture, tone, proximity, signature or handwriting, typing, writing style, word or phrase choice, registration information, or license plate; or computer vision, pattern recognition, shape recognition, object recognition, biometric measurement, speech or voice recognition, geography, proximity, character recognition, or eye tracking). 21. The communications system of claim 20, wherein data structures representing one or more signal, parameter, instance, element, or referring expression being associated by either the means of one or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement or an optional method comprising the steps of:
analyzing one or more signal, parameter, instance, element, or referring expression using one or more representation or referring expression and the optional means of zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; obtaining zero, one, or more referring expression; and generating one or more representation. 22. A communications satellite having configuration to receive, relay, transmit, or distribute one or more signal, zero, one, or more component to sense or image, and zero, one, or more component having configuration to format or support one or more signal, product, or signal product accordingly wherein one or more signal being sensed, sampled, imaged, transmitted, relayed, received, or distributed comprising one or more of the following: data representing one or more parameter in signal formatting instructions, wherein signal relating one or more modulating representation directly stimulating biological systems in one or more body with one or more visual, auditory, or kinesthetic element being mentally perceived and zero, one, or more instance being adapted to the subliminal;
data representing one or more parameter in signal formatting instructions, wherein signal relating mental information or cognitive processes obtained from measuring and optionally associating biological systems data of one or more body; modulating representations directly stimulating biological systems in one or more body with one or more image, sound, or feeling being mentally perceived and zero, one, or more instance being adapted to the subliminal; one or more transcranial stimulation field stimulating the brain, nervous system, skin, or other biological systems in one or more body; at least one transcranial stimulation field stimulating the brain, nervous system, skin, or other biological systems in one or more body being paired with modulating representations directly stimulating biological systems in one or more body with one or more image, sound, or feeling being mentally perceived and zero, one, or more instance being adapted to the subliminal; one or more sample, measurement, image, or any data representing at least one measurement or referring expression relating biological systems, brain cell, nerve, or tissue activity and conditions in one or more body with one or more measurement or referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing one or more referring expression relating sound, visual imagery, ideas, meanings, relationships, or feelings obtained from biological systems data of at least one body with one or more referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing communication without optional subvocalization, voicing, writing, or gesturing; and one or more sample, measurement, image, or any data relating activity, conditions, positions, or location of biological systems, brain cells, nerves, or tissue of one or more biological body in the act of perceiving, experiencing, imagining, remembering, cognizing, or communicating one or more of the following: non-verbal, verbal, perceived, remembered, or imagined communication; sound, visual imagery, ideas, meanings, relationships, or feelings; and objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, imagining, remembering, cognizing, or communicating. | This document discloses effective augmented telepathic communication as a gadget-free extension of human senses. The conveyance of mental information and cognitive processes to perceive or communicate being made possible by data structures for generating and maintaining representations of biological systems activity with auditory, visual, kinesthetic, tactile, emotion, movement, smell, taste, and concept data in a computing environment. In preferable embodiments of the present invention, one or more methods include steps for representing brain, nervous system, and sensory systems activity with mental information and cognitive processes as data for incorporating values with applications, systems, or instance relevant computing environments. In a preferable embodiment of the present invention, methods also include the association of data representing the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with mixes of machine learning tasks for human-computer interfacing and communicating using optional devices or acting as a biological computing environment.1. A non-transitory computer readable medium containing data representing either of or both data structures and program instructions for generating, analyzing, extending, communicating, integrating, storing, converting, editing, encoding, or maintaining said data structures representing one or more unit of category Nervous System depicting referring expressions relating to nervous system cells, nerves, tissue, electrical or chemical impulses, and trace occurrences related to signaling the communication of information and its processing in a biological body optionally with zero, one, or more unit of category Sensory System depicting referring expressions relating to sensory systems cells, nerves, tissue, electrical or chemical impulses, and trace occurrences related to signaling the communication of sensory information for its interpretation or processing in a biological body and zero, one, or more unit of category Brain and Nerve Activity optionally depicting referring expressions associating Nervous System category units with Sensory System category units wherein zero, one, or more Brain and Nerve Activity, zero, one, or more Sensory System, and one or more Nervous System units with Sensory System and Nervous System units optionally relating as Brain and Nerve Activity units being associated with one or more unit in at least one of the following categories:
Communication depicting referring expressions relating to the conveyance of ideas as sound, visual imagery, text, concept, or feelings; Cognition depicting referring expressions relating to considering, knowing, understanding, or believing; Perception depicting referring expressions relating to sensing, perceiving, observing, or becoming aware; Experience depicting referring expressions relating to feeling or reflecting on abstractions; Imagery depicting referring expressions relating to the visually perceived, remembered, or imagined; Sound depicting referring expressions relating to the auditorily perceived, remembered, or imagined; Symbol depicting referring expressions relating to meanings; Stimulus depicting referring expressions relating to evoking actions and conditions; Behavior depicting referring expressions relating to acting as or reacting to a stimulus; and People depicting referring expressions relating to community groups and individuals wherein each Brain and Nerve Activity, Sensory System, Nervous System, Communication, Cognition, Perception, Experience, Imagery, Sound, Symbol, Stimulus, Behavior, and People category unit consisting of zero, one, or more members with each member describing one or more object, element, asset, act, condition, process, or product representing zero, one, or more event, status, location, or hierarchical coordinate system and having zero, one, or more relationship, reference, property, description, or dimension of interest wherein data structures representing one or more unit in one or more category being generated using one or more referring expression and zero, one, or more hierarchical coordinate system by an optional method comprising the steps of: analyzing one or more body; obtaining information about one or more body; and generating one or more representation. 2. The non-transitory computer readable medium of claim 1, wherein the analyzing step of the optional method comprising the examination of any object, element, asset, act, condition, process, or product of the biological systems, communication, or behavior of one or more body using zero, one, or a plurality of wearable or surgically implanted device, sensor, probe, or electrode with zero, one, or more proximity to one or more body using zero, one, or more wearable or surgically implanted device, sensor, probe, or electrode. 3. The non-transitory computer readable medium of claim 2, wherein data structures being generated or maintained comprising at least one of the following:
data representing information obtained from one or more body with zero, one, or more representation of a vantage optionally being associated with referring expressions relating the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representation of a vantage; data representing one or more referring expression relating one or more representation of: (visual, auditory, or kinesthetic data obtained from one or more body with zero, one, or more representation of a vantage; non-verbal, verbal, perceived, remembered, or imagined communication with zero, one, or more representation of a vantage; measurement, activity, or condition associated with zero, one, or more location of one or more of the following obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body: biological systems, sensory systems, nervous system, brain cells, nerves, tissue, electrical impulse events, molecular signaling, chemical changes, magnetic properties, and trace occurrences; or text, sound, visual imagery, thought, idea, meaning, relationship, feeling, and communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body with zero, one, or more representation of a vantage); data representing one or more parameter in stimulation transmission signal formatting instructions, wherein stimulation transmission signal comprising one or more referring expression relating: (one or more representation of text, sound, visual imagery, thought, idea, meaning, relationship, feeling, vantage, or communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body; perception or cognition directly to biological systems of one or more body; visual, auditory, or kinesthetic perception or cognition directly to biological systems of one or more body; non-verbal, verbal, perceived, remembered, or imagined communication directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, remembering, imagining, or cognizing using sound, visual imagery, text, and feelings directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representations of a vantage; or subliminal information optionally being combined with auditory, visual, kinesthetic, tactile, emotion, concept, movement, smell, taste, or communications data directly to biological systems of one or more consuming or interacting body); data representing one or more referring expression relating: (active and passive user information; one or more representation comprising information obtained about one or more body using satellite-based technologies, ambient fields, microscopy techniques, interferometry methods, remote sensing, radar, radio, optics, directed energy, or tracking technologies; one or more interacting or interfacing body with the objects, elements, assets, acts, conditions, processes, or products of one or more computing environment using zero, one, or more hardware component or device item; communication without optional subvocalization, voicing, writing, or gesturing; one or more body with data structures or program instructions performing one or more financial transaction using one or more program, application, interface, or marketplace; one or more body with data structures or program instructions performing one or more of the following tasks: analyzing, extending, communicating, integrating, storing, converting, editing, or encoding; one or more body with data structures or program instructions interfacing one or more human user participating as one or more biological computing environment in networking arrangement with zero, one, or more computing environment; one or more body with data structures or program instructions interfacing one or more user interacting with one or more computing environment using zero localized input devices, zero, one, or more thought, zero, one, or more voiced command, and zero, one, or more gesture; one or more representation of one or more object, element, asset, act, condition, process, or product of data being associated by zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; or representations of communication, sensory or nervous system information, perception, cognition, experiences, stimulus, behavior, or relevant conditions with one or more referring expression from first-person, second-person, or third-person perspectives in the manner of zero, one, or more of each of the following: graphically, programmatically, computationally, textually, numerically, symbolically, audibly, sequentially, or conceptually); and data representing one or more referring expression relating at least one body with data structures or program instructions interfacing at least one body with one or more computing environment returning output from, associating one or more representation with output from, or executing at least one of the following process activity types: (performing tasks supporting communication, search, education, entertainment, research, navigation, measurement, calculation, business, productivity, language tools and translation, song recognition, augmented reality, situational awareness, decision support, medical or psychological treatment, social information interpretation, law enforcement, military, security, surveillance, authorization, access control, building automation, financial transaction, instant knowledge, memory extension, intelligence amplification, graphic design, three dimensional modeling, three dimensional printing, dreams, public speaking, performance, self improvement, or personal development; biometric measurement of the face, ear, eye, iris, retina, fingerprint, finger or hand geometry, gait, odor, or voice; locating, identifying, verifying, classifying, profiling, or recognizing of objects, structures, groups, or individuals with zero, one, or more of the following: facial expression, body language, posture, gesture, tone, proximity, signature or handwriting, typing, writing style, word or phrase choice, registration information, or license plate; or computer vision, pattern recognition, shape recognition, object recognition, biometric measurement, speech or voice recognition, geography, proximity, character recognition, or eye tracking). 4. The non-transitory computer readable medium of claim 3, wherein data structures representing one or more unit in at least one category being associated by either the means of one or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement or an optional method comprising the steps of:
analyzing at least one category unit member using one or more referring expression and the optional means of zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; obtaining zero, one, or more referring expression; and generating one or more representation. 5. A machine having a memory containing data representing either of or both data structures and program instructions for generating, analyzing, extending, communicating, integrating, storing, converting, editing, encoding, or maintaining said data structures representing one or more unit in at least one of the following categories:
Mental Information depicting referring expressions relating to the known, believed, and understood; Cognitive Processes depicting referring expressions relating to sensing, observing, considering, imagining, feeling, experiencing, remembering, and committing to memory; Communications Information depicting referring expressions relating to conveying ideas, acting as a stimulus, and responding to stimulus; Biological Systems depicting referring expressions relating to application relevant organs, divisions, tissue, cells, nerves, processes, or activities in a biological body; Biological Systems Activity depicting referring expressions relating to the application relevant processes or activity pertaining to organs, divisions, tissue, cells, nerves, electrical or chemical impulses, and trace occurrences related to signaling the communication of information and its processing in a biological body; People depicting referring expressions relating to community groups and individuals; and Stimulus depicting referring expressions relating to evoking actions and conditions; wherein each Mental Information, Cognitive Processes, Communications Information, Biological Systems, Biological Systems Activity, People, and Stimulus category unit consisting of zero, one, or more members with each member describing one or more object, element, asset, act, condition, process, or product and representing zero, one, or more event, status, location, or hierarchical coordinate system and having zero, one, or more relationship, reference, property, description, or dimension of interest. 6. The machine of claim 5, wherein data structures representing at least one unit in one or more category being generated using one or more referring expression and zero, one, or more hierarchical coordinate system by an optional method comprising the steps of:
analyzing one or more body; obtaining information about one or more body; and generating one or more representation. 7. The machine of claim 6, wherein data structures being generated or maintained comprising at least one of the following:
data representing information obtained from one or more body with zero, one, or more representation of a vantage optionally being associated with referring expressions relating the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representation of a vantage; data representing one or more referring expression relating one or more representation of: (visual, auditory, or kinesthetic data obtained from one or more body with zero, one, or more representation of a vantage; non-verbal, verbal, perceived, remembered, or imagined communication with zero, one, or more representation of a vantage; measurement, activity, or condition associated with zero, one, or more location of one or more of the following obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body: biological systems, sensory systems, nervous system, brain cells, nerves, tissue, electrical impulse events, molecular signaling, chemical changes, magnetic properties, and trace occurrences; or text, sound, visual imagery, thought, idea, meaning, relationship, feeling, and communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body with zero, one, or more representation of a vantage); data representing one or more parameter in stimulation transmission signal formatting instructions, wherein stimulation transmission signal comprising one or more referring expression relating: (one or more representation of text, sound, visual imagery, thought, idea, meaning, relationship, feeling, vantage, or communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body; perception or cognition directly to biological systems of one or more body; visual, auditory, or kinesthetic perception or cognition directly to biological systems of one or more body; non-verbal, verbal, perceived, remembered, or imagined communication directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, remembering, imagining, or cognizing using sound, visual imagery, text, and feelings directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representations of a vantage; or subliminal information optionally being combined with auditory, visual, kinesthetic, tactile, emotion, concept, movement, smell, taste, or communications data directly to biological systems of one or more consuming or interacting body); data representing one or more referring expression relating: (active and passive user information; one or more representation comprising information obtained about one or more body using satellite-based technologies, ambient fields, microscopy techniques, interferometry methods, remote sensing, radar, radio, optics, directed energy, or tracking technologies; one or more interacting or interfacing body with the objects, elements, assets, acts, conditions, processes, or products of one or more computing environment using zero, one, or more hardware component or device item; communication without optional subvocalization, voicing, writing, or gesturing; one or more body with data structures or program instructions performing one or more financial transaction using one or more program, application, interface, or marketplace; one or more body with data structures or program instructions performing one or more of the following tasks: analyzing, extending, communicating, integrating, storing, converting, editing, or encoding; one or more body with data structures or program instructions interfacing one or more human user participating as one or more biological computing environment in networking arrangement with zero, one, or more computing environment; one or more body with data structures or program instructions interfacing one or more user interacting with one or more computing environment using zero localized input devices, zero, one, or more thought, zero, one, or more voiced command, and zero, one, or more gesture; one or more representation of one or more object, element, asset, act, condition, process, or product of data being associated by zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; or representations of communication, sensory or nervous system information, perception, cognition, experiences, stimulus, behavior, or relevant conditions with one or more referring expression from first-person, second-person, or third-person perspectives in the manner of zero, one, or more of each of the following: graphically, programmatically, computationally, textually, numerically, symbolically, audibly, sequentially, or conceptually); and data representing one or more referring expression relating at least one body with data structures or program instructions interfacing at least one body with one or more computing environment returning output from, associating one or more representation with output from, or executing at least one of the following process activity types: (performing tasks supporting communication, search, education, entertainment, research, navigation, measurement, calculation, business, productivity, language tools and translation, song recognition, augmented reality, situational awareness, decision support, medical or psychological treatment, social information interpretation, law enforcement, military, security, surveillance, authorization, access control, building automation, financial transaction, instant knowledge, memory extension, intelligence amplification, graphic design, three dimensional modeling, three dimensional printing, dreams, public speaking, performance, self improvement, or personal development; biometric measurement of the face, ear, eye, iris, retina, fingerprint, finger or hand geometry, gait, odor, or voice; locating, identifying, verifying, classifying, profiling, or recognizing of objects, structures, groups, or individuals with zero, one, or more of the following: facial expression, body language, posture, gesture, tone, proximity, signature or handwriting, typing, writing style, word or phrase choice, registration information, or license plate; or computer vision, pattern recognition, shape recognition, object recognition, biometric measurement, speech or voice recognition, geography, proximity, character recognition, or eye tracking). 8. The machine of claim 7, wherein the analyzing step of the optional method comprising the examination of any object, element, asset, act, condition, process, or product of biological systems, communication, stimulus, or behavior of one or more bodies using zero, one, or a plurality of wearable or surgically implanted device, sensor, probe, or electrode with zero, one, or more proximity to one or more body using zero, one, or more wearable or surgically implanted device, sensor, probe, or electrode. 9. The machine of claim 8, wherein data structures representing one or more unit in at least one category being associated by either the means of one or more machine learning task classified under zero, one, or more of the following category types:
supervised, semi-supervised, unsupervised, and reinforcement or an optional method comprising the steps of: analyzing one or more category unit members using one or more referring expression and the optional means of zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; obtaining zero, one, or more referring expression; and generating one or more representation. 10. A system having a memory containing data representing either of or both data structures and program instructions for generating, analyzing, extending, communicating, integrating, storing, converting, editing, encoding, or maintaining said data structures representing one or more unit in at least one of the following categories:
Brain Activity depicting referring expressions relating brain cells, nerves, tissue, electrical or chemical impulses, and trace occurrences related to signaling the communication of sensory, bodily, mental, and cognitive information and its processing in the brain of a biological body; Nerve Activity depicting referring expressions relating cells, nerves, tissue, electrical or chemical impulses, and trace occurrences related to signaling the communication of sensory and bodily information and its processing outside of the brain of a biological body; Physical Structure depicting referring expressions relating to proximity or application relevant organs, divisions, tissue, cells, nerves and the imparting references of each constituent; Communication depicting referring expressions relating to the conveyance of ideas, acting as a stimulus, or reacting to a stimulus; Thought depicting referring expressions relating to perceiving, experiencing, considering, and cognizing sensory information, knowledge, abstractions, or stimulus relevant mental actions; Imagery depicting referring expressions relating to the visually perceived, remembered, or imagined; Sound depicting referring expressions relating to the auditorily perceived, remembered, or imagined; Symbol depicting referring expressions relating to perceiving, imagining, experiencing, and cognizing meanings; People depicting referring expressions relating to community groups and individuals; and Stimulus depicting referring expressions relating to evoking actions and conditions; wherein each Brain Activity, Nerve Activity, Physical Structures, Communication, Thought, Imagery, Sound, Symbol, People, and Stimulus category unit consisting of zero, one, or more member with each member describing one or more object, element, asset, act, condition, process, or product and representing zero, one, or more event, status, location, or hierarchical coordinate system and having zero, one, or more relationship, reference, property, description, or dimension of interest. 11. The system of claim 10, wherein data structures representing at least one unit in one or more category being generated using one or more referring expression and zero, one, or more hierarchical coordinate system by an optional method comprising the steps of:
analyzing one or more body; obtaining information about one or more body; and generating one or more representation. 12. The system of claim 11, wherein data structures being generated or maintained comprising at least one of the following:
data representing information obtained from one or more body with zero, one, or more representation of a vantage optionally being associated with referring expressions relating the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representation of a vantage; data representing one or more referring expression relating one or more representation of: (visual, auditory, or kinesthetic data obtained from one or more body with zero, one, or more representation of a vantage; non-verbal, verbal, perceived, remembered, or imagined communication with zero, one, or more representation of a vantage; measurement, activity, or condition associated with zero, one, or more location of one or more of the following obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body: biological systems, sensory systems, nervous system, brain cells, nerves, tissue, electrical impulse events, molecular signaling, chemical changes, magnetic properties, and trace occurrences; or text, sound, visual imagery, thought, idea, meaning, relationship, feeling, and communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body with zero, one, or more representation of a vantage); data representing one or more parameter in stimulation transmission signal formatting instructions, wherein stimulation transmission signal comprising one or more referring expression relating: (one or more representation of text, sound, visual imagery, thought, idea, meaning, relationship, feeling, vantage, or communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body; perception or cognition directly to biological systems of one or more body; visual, auditory, or kinesthetic perception or cognition directly to biological systems of one or more body; non-verbal, verbal, perceived, remembered, or imagined communication directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, remembering, imagining, or cognizing using sound, visual imagery, text, and feelings directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representations of a vantage; or subliminal information optionally being combined with auditory, visual, kinesthetic, tactile, emotion, concept, movement, smell, taste, or communications data directly to biological systems of one or more consuming or interacting body); data representing one or more referring expression relating: (active and passive user information; one or more representation comprising information obtained about one or more body using satellite-based technologies, ambient fields, microscopy techniques, interferometry methods, remote sensing, radar, radio, optics, directed energy, or tracking technologies; one or more interacting or interfacing body with the objects, elements, assets, acts, conditions, processes, or products of one or more computing environment using zero, one, or more hardware component or device item; communication without optional subvocalization, voicing, writing, or gesturing; one or more body with data structures or program instructions performing one or more financial transaction using one or more program, application, interface, or marketplace; one or more body with data structures or program instructions performing one or more of the following tasks: analyzing, extending, communicating, integrating, storing, converting, editing, or encoding; one or more body with data structures or program instructions interfacing one or more human user participating as one or more biological computing environment in networking arrangement with zero, one, or more computing environment; one or more body with data structures or program instructions interfacing one or more user interacting with one or more computing environment using zero localized input devices, zero, one, or more thought, zero, one, or more voiced command, and zero, one, or more gesture; one or more representation of one or more object, element, asset, act, condition, process, or product of data being associated by zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; or representations of communication, sensory or nervous system information, perception, cognition, experiences, stimulus, behavior, or relevant conditions with one or more referring expression from first-person, second-person, or third-person perspectives in the manner of zero, one, or more of each of the following: graphically, programmatically, computationally, textually, numerically, symbolically, audibly, sequentially, or conceptually); and data representing one or more referring expression relating at least one body with data structures or program instructions interfacing at least one body with one or more computing environment returning output from, associating one or more representation with output from, or executing at least one of the following process activity types: (performing tasks supporting communication, search, education, entertainment, research, navigation, measurement, calculation, business, productivity, language tools and translation, song recognition, augmented reality, situational awareness, decision support, medical or psychological treatment, social information interpretation, law enforcement, military, security, surveillance, authorization, access control, building automation, financial transaction, instant knowledge, memory extension, intelligence amplification, graphic design, three dimensional modeling, three dimensional printing, dreams, public speaking, performance, self improvement, or personal development; biometric measurement of the face, ear, eye, iris, retina, fingerprint, finger or hand geometry, gait, odor, or voice; locating, identifying, verifying, classifying, profiling, or recognizing of objects, structures, groups, or individuals with zero, one, or more of the following: facial expression, body language, posture, gesture, tone, proximity, signature or handwriting, typing, writing style, word or phrase choice, registration information, or license plate; or computer vision, pattern recognition, shape recognition, object recognition, biometric measurement, speech or voice recognition, geography, proximity, character recognition, or eye tracking). 13. The system of claim 12, wherein the analyzing step of the optional method comprising the examination of any object, element, asset, act, condition, process, or product of biological systems, communication, stimulus, or behavior of one or more body using zero, one, or a plurality of wearable or surgically implanted device, sensor, probe, or electrode with zero, one, or more proximity to one or more body using zero, one, or more wearable or surgically implanted device, sensor, probe, or electrode. 14. The system of claim 13, wherein data structures representing one or more unit in at least one category being associated by either the means of one or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement or an optional method comprising the steps of:
analyzing one or more category unit members using one or more referring expression and the optional means of zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; obtaining zero, one, or more referring expression; and generating one or more representation. 15. A method of obtaining and distributing communication data from an artificial satellite comprising:
receiving one or more source signal from one or more transmitter, transmission station, or artificial satellite and relaying one or more source signal toward one or more body with at least one source signal comprising one or more of the following: data representing one or more parameter in signal formatting instructions, wherein signal relating one or more modulating representation directly stimulating biological systems in one or more body with one or more visual, auditory, or kinesthetic element being mentally perceived and zero, one, or more instance being adapted to the subliminal; data representing one or more parameter in signal formatting instructions, wherein signal relating mental information or cognitive processes obtained from measuring and optionally associating biological systems data of one or more body; modulating representations directly stimulating biological systems in one or more body with one or more image, sound, or feeling being mentally perceived and zero, one, or more instance being adapted to the subliminal; one or more transcranial stimulation field stimulating the brain, nervous system, skin, or other biological systems in one or more body; at least one transcranial stimulation field stimulating the brain, nervous system, skin, or other biological systems in one or more body being paired with modulating representations directly stimulating biological systems in one or more body with one or more image, sound, or feeling being mentally perceived and zero, one, or more instance being adapted to the subliminal; one or more sample, measurement, image, or any data representing at least one measurement or referring expression relating biological systems, brain cell, nerve, or tissue activity and conditions in one or more body with one or more measurement or referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing one or more referring expression relating sound, visual imagery, ideas, meanings, relationships, or feelings obtained from biological systems data of at least one body with one or more referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing communication without optional subvocalization, voicing, writing, or gesturing; and one or more sample, measurement, image, or any data relating activity, conditions, positions, or location of biological systems, brain cells, nerves, or tissue of one or more biological body in the act of perceiving, experiencing, imagining, remembering, cognizing, or communicating one or more of the following: non-verbal, verbal, perceived, remembered, or imagined communication; sound, visual imagery, ideas, meanings, relationships, or feelings; and objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, imagining, remembering, cognizing, or communicating. 16. The method of claim 15, further comprising:
obtaining one or more measurement or one or more referring expression relating biological systems, brain cell, nerve, or tissue activity, conditions, positions, or locations with one or more optional vantage describing communication of one or more biological body and receiving, relaying, or distributing one or more sample, measurement, image, or referring expression, data relaying or distributing representations of measurement relating biological systems, brain cell, nerve, or tissue activity and conditions of one or more body, or one or more response signal regarding one or more body, a response signal comprising at least one of the following: data representing one or more parameter in signal formatting instructions, wherein signal relating mental information or cognitive processes obtained from measuring and optionally associating biological systems data of one or more body; one or more sample, measurement, image, or any data representing at least one measurement or referring expression relating biological systems, brain cell, nerve, or tissue activity and conditions in one or more body with one or more measurement or referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing one or more referring expression relating sound, visual imagery, ideas, meanings, relationships, or feelings obtained from biological systems data of at least one body with one or more referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing communication without optional subvocalization, voicing, writing, or gesturing; and one or more sample, measurement, image, or any data relating activity, conditions, positions, or location of biological systems, brain cells, nerves, or tissue of one or more biological body in the act of perceiving, experiencing, imagining, remembering, cognizing, or communicating one or more of the following: non-verbal, verbal, perceived, remembered, or imagined communication; sound, visual imagery, ideas, meanings, relationships, or feelings; and objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, imagining, remembering, cognizing, or communicating. 17. The method of claim 16, further comprising:
relaying one or more response signal toward one or more receiver or receiving station; evaluating one or more response signal; and generating one or more representation. 18. The method of claim 17, wherein one or more representation or referring expression being associated by either the means of one or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement or an optional method comprising the steps of:
analyzing one or more representation or referring expression using one or more referring expression and the optional means of zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; obtaining zero, one, or more referring expression; and generating one or more representation. 19. A communications system comprising one or more computing environment having configuration to at least generate and maintain representations, at least one transmitter or transmission station having configuration to at least transmit, relay, or distribute one or more signal, one or more receiver or receiving station having configuration to at least receive one or more signal, one or more artificial satellite having configuration to receive, relay, transmit, or distribute one or more signal, at least one artificial satellite having configuration to sense or image accordingly, and zero, one, or more device having configuration to format or support one or more signal or signal product accordingly wherein one or more signal being sensed, sampled, imaged, transmitted, relayed, received, or distributed comprising one or more of the following:
data representing one or more parameter in signal formatting instructions, wherein signal relating one or more modulating representation directly stimulating biological systems in one or more body with one or more visual, auditory, or kinesthetic element being mentally perceived and zero, one, or more instance being adapted to the subliminal; data representing one or more parameter in signal formatting instructions, wherein signal relating mental information or cognitive processes obtained from measuring and optionally associating biological systems data of one or more body; modulating representations directly stimulating biological systems in one or more body with one or more image, sound, or feeling being mentally perceived and zero, one, or more instance being adapted to the subliminal; one or more transcranial stimulation field stimulating the brain, nervous system, skin, or other biological systems in one or more body; at least one transcranial stimulation field stimulating the brain, nervous system, skin, or other biological systems in one or more body being paired with modulating representations directly stimulating biological systems in one or more body with one or more image, sound, or feeling being mentally perceived and zero, one, or more instance being adapted to the subliminal; one or more sample, measurement, image, or any data representing at least one measurement or referring expression relating biological systems, brain cell, nerve, or tissue activity and conditions in one or more body with one or more measurement or referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing one or more referring expression relating sound, visual imagery, ideas, meanings, relationships, or feelings obtained from biological systems data of at least one body with one or more referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing communication without optional subvocalization, voicing, writing, or gesturing; and one or more sample, measurement, image, or any data relating activity, conditions, positions, or location of biological systems, brain cells, nerves, or tissue of one or more biological body in the act of perceiving, experiencing, imagining, remembering, cognizing, or communicating one or more of the following: non-verbal, verbal, perceived, remembered, or imagined communication; sound, visual imagery, ideas, meanings, relationships, or feelings; and objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, imagining, remembering, cognizing, or communicating. 20. The communications system of claim 19, wherein data structures being generated or maintained comprising at least one of the following:
data representing information obtained from one or more body with zero, one, or more representation of a vantage optionally being associated with referring expressions relating the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representation of a vantage; data representing one or more referring expression relating one or more representation of: (visual, auditory, or kinesthetic data obtained from one or more body with zero, one, or more representation of a vantage; non-verbal, verbal, perceived, remembered, or imagined communication with zero, one, or more representation of a vantage; measurement, activity, or condition associated with zero, one, or more location of one or more of the following obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body: biological systems, sensory systems, nervous system, brain cells, nerves, tissue, electrical impulse events, molecular signaling, chemical changes, magnetic properties, and trace occurrences; or text, sound, visual imagery, thought, idea, meaning, relationship, feeling, and communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body with zero, one, or more representation of a vantage); data representing one or more parameter in stimulation transmission signal formatting instructions, wherein stimulation transmission signal comprising one or more referring expression relating: (one or more representation of text, sound, visual imagery, thought, idea, meaning, relationship, feeling, vantage, or communication obtained from one or more perceiving, cognizing, experiencing, remembering, or imagining body; perception or cognition directly to biological systems of one or more body; visual, auditory, or kinesthetic perception or cognition directly to biological systems of one or more body; non-verbal, verbal, perceived, remembered, or imagined communication directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, remembering, imagining, or cognizing using sound, visual imagery, text, and feelings directly to biological systems of one or more body; the objects, elements, assets, acts, conditions, processes, or products of perceiving, cognizing, communicating, experiencing, imagining, remembering, recognizing, thinking, judging, reasoning, problem solving, conceptualizing, or planning with zero, one, or more representations of a vantage; or subliminal information optionally being combined with auditory, visual, kinesthetic, tactile, emotion, concept, movement, smell, taste, or communications data directly to biological systems of one or more consuming or interacting body); data representing one or more referring expression relating: (active and passive user information; one or more representation comprising information obtained about one or more body using satellite-based technologies, ambient fields, microscopy techniques, interferometry methods, remote sensing, radar, radio, optics, directed energy, or tracking technologies; one or more interacting or interfacing body with the objects, elements, assets, acts, conditions, processes, or products of one or more computing environment using zero, one, or more hardware component or device item; communication without optional subvocalization, voicing, writing, or gesturing; one or more body with data structures or program instructions performing one or more financial transaction using one or more program, application, interface, or marketplace; one or more body with data structures or program instructions performing one or more of the following tasks: analyzing, extending, communicating, integrating, storing, converting, editing, or encoding; one or more body with data structures or program instructions interfacing one or more human user participating as one or more biological computing environment in networking arrangement with zero, one, or more computing environment; one or more body with data structures or program instructions interfacing one or more user interacting with one or more computing environment using zero localized input devices, zero, one, or more thought, zero, one, or more voiced command, and zero, one, or more gesture; one or more representation of one or more object, element, asset, act, condition, process, or product of data being associated by zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; or representations of communication, sensory or nervous system information, perception, cognition, experiences, stimulus, behavior, or relevant conditions with one or more referring expression from first-person, second-person, or third-person perspectives in the manner of zero, one, or more of each of the following: graphically, programmatically, computationally, textually, numerically, symbolically, audibly, sequentially, or conceptually); and data representing one or more referring expression relating at least one body with data structures or program instructions interfacing at least one body with one or more computing environment returning output from, associating one or more representation with output from, or executing at least one of the following process activity types: (performing tasks supporting communication, search, education, entertainment, research, navigation, measurement, calculation, business, productivity, language tools and translation, song recognition, augmented reality, situational awareness, decision support, medical or psychological treatment, social information interpretation, law enforcement, military, security, surveillance, authorization, access control, building automation, financial transaction, instant knowledge, memory extension, intelligence amplification, graphic design, three dimensional modeling, three dimensional printing, dreams, public speaking, performance, self improvement, or personal development; biometric measurement of the face, ear, eye, iris, retina, fingerprint, finger or hand geometry, gait, odor, or voice; locating, identifying, verifying, classifying, profiling, or recognizing of objects, structures, groups, or individuals with zero, one, or more of the following: facial expression, body language, posture, gesture, tone, proximity, signature or handwriting, typing, writing style, word or phrase choice, registration information, or license plate; or computer vision, pattern recognition, shape recognition, object recognition, biometric measurement, speech or voice recognition, geography, proximity, character recognition, or eye tracking). 21. The communications system of claim 20, wherein data structures representing one or more signal, parameter, instance, element, or referring expression being associated by either the means of one or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement or an optional method comprising the steps of:
analyzing one or more signal, parameter, instance, element, or referring expression using one or more representation or referring expression and the optional means of zero, one, or more machine learning task classified under zero, one, or more of the following category types: supervised, semi-supervised, unsupervised, and reinforcement; obtaining zero, one, or more referring expression; and generating one or more representation. 22. A communications satellite having configuration to receive, relay, transmit, or distribute one or more signal, zero, one, or more component to sense or image, and zero, one, or more component having configuration to format or support one or more signal, product, or signal product accordingly wherein one or more signal being sensed, sampled, imaged, transmitted, relayed, received, or distributed comprising one or more of the following: data representing one or more parameter in signal formatting instructions, wherein signal relating one or more modulating representation directly stimulating biological systems in one or more body with one or more visual, auditory, or kinesthetic element being mentally perceived and zero, one, or more instance being adapted to the subliminal;
data representing one or more parameter in signal formatting instructions, wherein signal relating mental information or cognitive processes obtained from measuring and optionally associating biological systems data of one or more body; modulating representations directly stimulating biological systems in one or more body with one or more image, sound, or feeling being mentally perceived and zero, one, or more instance being adapted to the subliminal; one or more transcranial stimulation field stimulating the brain, nervous system, skin, or other biological systems in one or more body; at least one transcranial stimulation field stimulating the brain, nervous system, skin, or other biological systems in one or more body being paired with modulating representations directly stimulating biological systems in one or more body with one or more image, sound, or feeling being mentally perceived and zero, one, or more instance being adapted to the subliminal; one or more sample, measurement, image, or any data representing at least one measurement or referring expression relating biological systems, brain cell, nerve, or tissue activity and conditions in one or more body with one or more measurement or referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing one or more referring expression relating sound, visual imagery, ideas, meanings, relationships, or feelings obtained from biological systems data of at least one body with one or more referring expression relating communication, thought, activity, conditions, or locations of one or more body; data representing communication without optional subvocalization, voicing, writing, or gesturing; and one or more sample, measurement, image, or any data relating activity, conditions, positions, or location of biological systems, brain cells, nerves, or tissue of one or more biological body in the act of perceiving, experiencing, imagining, remembering, cognizing, or communicating one or more of the following: non-verbal, verbal, perceived, remembered, or imagined communication; sound, visual imagery, ideas, meanings, relationships, or feelings; and objects, elements, assets, acts, conditions, processes, or products of perceiving, experiencing, imagining, remembering, cognizing, or communicating. | 2,100 |
6,574 | 6,574 | 15,384,164 | 2,181 | A non-volatile storage system includes: a host and a storage device. The host includes a submission queue memory, a completion queue memory, and a read/write data memory, and the storage device includes: a controller configured to concurrently communicate with the read/write data memory and with at least one of the submission queue memory and the completion queue memory; and a memory device configured to communicate with the controller. | 1. A non-volatile storage system comprising:
a host comprising a submission queue memory, a completion queue memory, and a read/write data memory; and a storage device comprising:
a controller configured to concurrently communicate with the read/write data memory and with at least one of the submission queue memory and the completion queue memory; and
a memory device configured to communicate with the controller. 2. The non-volatile storage system of claim 1, wherein the controller is configured to concurrently receive data from the read/write data memory and from the submission queue memory,
wherein a physical interface connecting the controller and the host to each other is configured for the host to concurrently send data from both the read/write data memory and the submission queue memory by utilizing either dedicated lanes or dynamically configurable lanes of the physical interface, and wherein the physical interface operates according to a protocol, the protocol being configured to prioritize data from the submission queue memory over the data from the read/write data memory via the physical interface. 3. The non-volatile storage system of claim 2, wherein the controller is configured to concurrently receive data from the read/write data memory and transmit data to the completion queue memory,
wherein the physical interface is configured for the host to concurrently send data from the read/write data memory and transmit data to the completion queue memory by utilizing either the dedicated lanes or the dynamically configurable lanes, and wherein the protocol is configured to prioritize data to the completion queue memory over the data from the read/write data memory via the physical interface. 4. The non-volatile storage system of claim 1, wherein the controller is configured to concurrently communicate with the read/write data memory via a data interface and with the at least one of the submission queue memory and the completion queue memory via a command interface. 5. The non-volatile storage system of claim 4, wherein the storage device is configured to communicate with the host via a peripheral component interconnect express (PCIe) bus having a plurality of lanes. 6. The non-volatile storage system of claim 5, wherein the command interface comprises some of the lanes of the PCIe bus, and the data interface comprises the remaining lanes of the PCIe bus. 7. The non-volatile storage system of claim 4, wherein the command interface is configured to selectively transmit data between the controller and the read/write data memory and between the controller and the at least one of the submission queue memory and the completion queue memory. 8. A method of data storage access between a remote initiator and a non-volatile storage device via a host, the method comprising:
transmitting a write command from the remote initiator to the storage device via the host; transmitting write data corresponding to the write command from the remote initiator to the storage device via the host; transmitting a command from the remote initiator to the storage device via the host concurrently with the transmitting the write data to the storage device from the host; and when the command is a read command, transmitting read data from storage device to the host in response to the read command. 9. The method of claim 8, further comprising transmitting an in-capsule command and data from the remote initiator to the storage device via the host concurrently with the transmitting the write data to the storage device via the host. 10. The method of claim 8, wherein the write command and the read command are transmitted between the host and the storage device via a command interface, and
wherein the write data and the read data are transmitted between the host and the storage device via a data interface different from the command interface. 11. The method of claim 10, further comprising:
transmitting a second completion entry from the storage device to the host when the transmitting of the read data is completed; and transmitting a first completion entry from the storage device to the host when the transmitting of the write data is completed, wherein the transmitting the second completion entry occurs before the transmitting the first completion entry. 12. The method of claim 8, wherein the write command and the read command are transmitted from the host to the storage device via a command interface,
wherein the write data is transmitted from the host to the storage device via a first data interface, and wherein the read data is transmitted from the storage device to the host via a second data interface, each of the command interface, the first data interface, and the second data interface being different from each other. 13. The method of claim 12, wherein the command interface, the first data interface, and the second data interface are separate AXI interfaces. 14. A method of data storage access between a host and a non-volatile storage device, the host comprising a processor and a host memory, and the non-volatile storage device comprising a controller and a memory device, the method comprising:
transmitting a write command from the host to the controller via a command interface; transmitting write data from the host memory to the controller via a data interface; and concurrently transmitting another command from the host to the controller via the command interface as the write data is transmitted from the host to the controller via the data interface. 15. The method of claim 14, further comprising concurrently transmitting data from the memory device to the host via the data interface as the transmitting the write data from the host to the controller via the data interface. 16. The method of claim 15, further comprising concurrently transmitting the write data from the host to the controller via the command interface and the data interface. 17. The method of claim 16, further comprising transmitting a completion entry corresponding to the write command to the host via the command interface. 18. The method of claim 16, wherein the host and the controller communicate via a peripheral component interconnect express (PCIe) bus having a plurality of lanes,
wherein some of the lanes are dedicated as the command interface, and wherein the remaining lanes are dedicated as the data interface. 19. The method of claim 18, wherein the host memory comprises a submission queue configured to store commands, and
wherein the lanes dedicated as the command interface are configured to transmit the write data when there are no pending commands in the submission queue. 20. The method of claim 16. wherein the host and the controller communicate via a plurality of AXI interfaces,
wherein at least one of the AXI interfaces is dedicated as the command interface, and wherein at least two of the AXI interfaces are dedicated as the data interface. | A non-volatile storage system includes: a host and a storage device. The host includes a submission queue memory, a completion queue memory, and a read/write data memory, and the storage device includes: a controller configured to concurrently communicate with the read/write data memory and with at least one of the submission queue memory and the completion queue memory; and a memory device configured to communicate with the controller.1. A non-volatile storage system comprising:
a host comprising a submission queue memory, a completion queue memory, and a read/write data memory; and a storage device comprising:
a controller configured to concurrently communicate with the read/write data memory and with at least one of the submission queue memory and the completion queue memory; and
a memory device configured to communicate with the controller. 2. The non-volatile storage system of claim 1, wherein the controller is configured to concurrently receive data from the read/write data memory and from the submission queue memory,
wherein a physical interface connecting the controller and the host to each other is configured for the host to concurrently send data from both the read/write data memory and the submission queue memory by utilizing either dedicated lanes or dynamically configurable lanes of the physical interface, and wherein the physical interface operates according to a protocol, the protocol being configured to prioritize data from the submission queue memory over the data from the read/write data memory via the physical interface. 3. The non-volatile storage system of claim 2, wherein the controller is configured to concurrently receive data from the read/write data memory and transmit data to the completion queue memory,
wherein the physical interface is configured for the host to concurrently send data from the read/write data memory and transmit data to the completion queue memory by utilizing either the dedicated lanes or the dynamically configurable lanes, and wherein the protocol is configured to prioritize data to the completion queue memory over the data from the read/write data memory via the physical interface. 4. The non-volatile storage system of claim 1, wherein the controller is configured to concurrently communicate with the read/write data memory via a data interface and with the at least one of the submission queue memory and the completion queue memory via a command interface. 5. The non-volatile storage system of claim 4, wherein the storage device is configured to communicate with the host via a peripheral component interconnect express (PCIe) bus having a plurality of lanes. 6. The non-volatile storage system of claim 5, wherein the command interface comprises some of the lanes of the PCIe bus, and the data interface comprises the remaining lanes of the PCIe bus. 7. The non-volatile storage system of claim 4, wherein the command interface is configured to selectively transmit data between the controller and the read/write data memory and between the controller and the at least one of the submission queue memory and the completion queue memory. 8. A method of data storage access between a remote initiator and a non-volatile storage device via a host, the method comprising:
transmitting a write command from the remote initiator to the storage device via the host; transmitting write data corresponding to the write command from the remote initiator to the storage device via the host; transmitting a command from the remote initiator to the storage device via the host concurrently with the transmitting the write data to the storage device from the host; and when the command is a read command, transmitting read data from storage device to the host in response to the read command. 9. The method of claim 8, further comprising transmitting an in-capsule command and data from the remote initiator to the storage device via the host concurrently with the transmitting the write data to the storage device via the host. 10. The method of claim 8, wherein the write command and the read command are transmitted between the host and the storage device via a command interface, and
wherein the write data and the read data are transmitted between the host and the storage device via a data interface different from the command interface. 11. The method of claim 10, further comprising:
transmitting a second completion entry from the storage device to the host when the transmitting of the read data is completed; and transmitting a first completion entry from the storage device to the host when the transmitting of the write data is completed, wherein the transmitting the second completion entry occurs before the transmitting the first completion entry. 12. The method of claim 8, wherein the write command and the read command are transmitted from the host to the storage device via a command interface,
wherein the write data is transmitted from the host to the storage device via a first data interface, and wherein the read data is transmitted from the storage device to the host via a second data interface, each of the command interface, the first data interface, and the second data interface being different from each other. 13. The method of claim 12, wherein the command interface, the first data interface, and the second data interface are separate AXI interfaces. 14. A method of data storage access between a host and a non-volatile storage device, the host comprising a processor and a host memory, and the non-volatile storage device comprising a controller and a memory device, the method comprising:
transmitting a write command from the host to the controller via a command interface; transmitting write data from the host memory to the controller via a data interface; and concurrently transmitting another command from the host to the controller via the command interface as the write data is transmitted from the host to the controller via the data interface. 15. The method of claim 14, further comprising concurrently transmitting data from the memory device to the host via the data interface as the transmitting the write data from the host to the controller via the data interface. 16. The method of claim 15, further comprising concurrently transmitting the write data from the host to the controller via the command interface and the data interface. 17. The method of claim 16, further comprising transmitting a completion entry corresponding to the write command to the host via the command interface. 18. The method of claim 16, wherein the host and the controller communicate via a peripheral component interconnect express (PCIe) bus having a plurality of lanes,
wherein some of the lanes are dedicated as the command interface, and wherein the remaining lanes are dedicated as the data interface. 19. The method of claim 18, wherein the host memory comprises a submission queue configured to store commands, and
wherein the lanes dedicated as the command interface are configured to transmit the write data when there are no pending commands in the submission queue. 20. The method of claim 16. wherein the host and the controller communicate via a plurality of AXI interfaces,
wherein at least one of the AXI interfaces is dedicated as the command interface, and wherein at least two of the AXI interfaces are dedicated as the data interface. | 2,100 |
6,575 | 6,575 | 16,294,566 | 2,191 | A multiple storage node system including a first and second node is provided. The first node includes a first baseboard management controller (BMC), a first flash ROM configured to store a first flash image, and a first switch device configured to connect the first BMC to the first flash ROM. The second node includes an exact configuration of the first node. The first BMC is connected to the second switch device, and the second flash image is the same as the first flash. | 1. A multi-node storage system comprising:
a first node comprising:
a first baseboard management controller (BMC);
a first flash ROM configured to store a first flash image; and
a first switch device configured to connect the first BMC to the first flash ROM; and
a second node comprising:
a second BMC connected to the first switch device;
a second flash ROM configured to store a second flash image; and
a second switch device configured to connect the second BMC to the second flash ROM,
wherein the first BMC is connected to the second switch device, wherein the second flash image is the same as the first flash. 2. The multi-node storage system of claim 1,
wherein the first node further comprises a first storage controller, a third flash ROM configured to store a third flash image, and a third switch device configured to connect either the first BMC or the second BMC to the third flash ROM, and wherein the second node further comprises a second storage controller, a fourth flash ROM configured to store a fourth flash image, fourth flash image identical to the third flash image, and a fourth switch configured to connect either the first BMC or the second BMC to the fourth flash ROM. 3. The multi-node storage system of claim 1, wherein the first node further comprises a first plurality of storage devices connected to the first storage expander switch controller and the second storage expander switch controller. 4. The multi-node storage system of claim 3, wherein the first plurality of storage devices comprises at least one of a hard disk drive (HDD), a solid state drive (SSD), or a non-volatile memory express (NVMe). 5. The multi-node storage system of claim 4, wherein the NVMe is configured to serve as a host controller interface and storage protocol to facilitate transfer of data between the first storage switch expander controller and the SSD drive. 6. The multi-node storage system of claim 1, wherein the second node further comprises a second plurality of storage devices connected to the first storage expander switch controller and the second storage expander switch controller. 7. The multi-node storage system of claim 6, wherein the second plurality of storage devices comprises at least one of a hard disk drive (HDD), a solid state drive (SSD), or a non-volatile memory express (NVMe). 8. The multi-node storage system of claim 7, wherein the NVMe is configured to serve as a host controller interface and storage protocol to facilitate transfer of data between the second storage switch expander controller and the SSD drive. 9. The multi-node storage system of claim 1, wherein the first flash image comprises a first BMC firmware flash image and the second flash image comprises a first storage switch expander controller firmware flash image. 10. The multi-node storage system of claim 2, wherein the third flash image comprises a second BMC firmware flash image and the fourth flash image comprises a second storage switch expander controller firmware flash image. 11. The multi-node storage system of claim 2, wherein each of the first switch device, the second switch device, the third switch device, and the fourth switch device comprises a multiplexor (MUX). 12. The multi-node storage system of claim 10, wherein each of the first switch device, the second switch device, the third switch device, and the fourth switch device is configured to multiplex the first BMC and the second BMC. 13. The multi-node storage system of claim 11, wherein the first BMC is configured to retrieve the third flash image stored in the third flash ROM, or the fourth flash image in the fourth flash ROM. 14. The multi-node storage system of claim 11, wherein the second BMC is configured to retrieve the first flash image stored in the first flash ROM, or the second flash image stored in the second flash ROM. 15. A method of updating a firmware in a multi storage node system, the method comprising:
power cycling a first node, the first node comprising: a first baseboard management controller (BMC), a first flash ROM configured to store a first flash image, and a first switch device configured to connect the first BMC to the first flash ROM; activating the first flash image in the first flash ROM; determining at least one of the following: at least one hardware component within the first node is not online or ready for a firmware update, the second flash image is corrupted, and/or the first node is unable to boot to OS; and retrieving, by the first BMC, a second flash image stored in a second flash ROM stored on a second node, wherein the first BMC is connected to a second switch device in the second node, wherein the second flash image is the same as the first flash. 16. The method of claim 15, wherein the first node further comprises a first storage controller, a third flash ROM configured to store a third flash image, and a third switch device configured to connect either the first BMC or the second BMC to the third flash ROM, and
wherein the second node further comprises a second storage controller, a fourth flash ROM configured to store a fourth flash image, fourth flash image identical to the third flash image, and a fourth switch configured to connect either the first BMC or the second BMC to the fourth flash ROM. 17. The method of claim 16, wherein the first flash image comprises a first BMC firmware flash image and the second flash image comprises a first storage switch expander controller firmware flash image. 18. The method of claim 16, wherein the third flash image comprises a second BMC firmware flash image and the fourth flash image comprises a second storage switch expander controller firmware flash image. 19. The method of claim 16, wherein each of the first switch device, the second switch device, the third switch device, and the fourth switch device comprises a multiplexor (MUX). 20. The method of claim 19, wherein each of the first switch device, the second switch device, the third switch device, and the fourth switch device is configured to multiplex the first BMC and the second BMC. | A multiple storage node system including a first and second node is provided. The first node includes a first baseboard management controller (BMC), a first flash ROM configured to store a first flash image, and a first switch device configured to connect the first BMC to the first flash ROM. The second node includes an exact configuration of the first node. The first BMC is connected to the second switch device, and the second flash image is the same as the first flash.1. A multi-node storage system comprising:
a first node comprising:
a first baseboard management controller (BMC);
a first flash ROM configured to store a first flash image; and
a first switch device configured to connect the first BMC to the first flash ROM; and
a second node comprising:
a second BMC connected to the first switch device;
a second flash ROM configured to store a second flash image; and
a second switch device configured to connect the second BMC to the second flash ROM,
wherein the first BMC is connected to the second switch device, wherein the second flash image is the same as the first flash. 2. The multi-node storage system of claim 1,
wherein the first node further comprises a first storage controller, a third flash ROM configured to store a third flash image, and a third switch device configured to connect either the first BMC or the second BMC to the third flash ROM, and wherein the second node further comprises a second storage controller, a fourth flash ROM configured to store a fourth flash image, fourth flash image identical to the third flash image, and a fourth switch configured to connect either the first BMC or the second BMC to the fourth flash ROM. 3. The multi-node storage system of claim 1, wherein the first node further comprises a first plurality of storage devices connected to the first storage expander switch controller and the second storage expander switch controller. 4. The multi-node storage system of claim 3, wherein the first plurality of storage devices comprises at least one of a hard disk drive (HDD), a solid state drive (SSD), or a non-volatile memory express (NVMe). 5. The multi-node storage system of claim 4, wherein the NVMe is configured to serve as a host controller interface and storage protocol to facilitate transfer of data between the first storage switch expander controller and the SSD drive. 6. The multi-node storage system of claim 1, wherein the second node further comprises a second plurality of storage devices connected to the first storage expander switch controller and the second storage expander switch controller. 7. The multi-node storage system of claim 6, wherein the second plurality of storage devices comprises at least one of a hard disk drive (HDD), a solid state drive (SSD), or a non-volatile memory express (NVMe). 8. The multi-node storage system of claim 7, wherein the NVMe is configured to serve as a host controller interface and storage protocol to facilitate transfer of data between the second storage switch expander controller and the SSD drive. 9. The multi-node storage system of claim 1, wherein the first flash image comprises a first BMC firmware flash image and the second flash image comprises a first storage switch expander controller firmware flash image. 10. The multi-node storage system of claim 2, wherein the third flash image comprises a second BMC firmware flash image and the fourth flash image comprises a second storage switch expander controller firmware flash image. 11. The multi-node storage system of claim 2, wherein each of the first switch device, the second switch device, the third switch device, and the fourth switch device comprises a multiplexor (MUX). 12. The multi-node storage system of claim 10, wherein each of the first switch device, the second switch device, the third switch device, and the fourth switch device is configured to multiplex the first BMC and the second BMC. 13. The multi-node storage system of claim 11, wherein the first BMC is configured to retrieve the third flash image stored in the third flash ROM, or the fourth flash image in the fourth flash ROM. 14. The multi-node storage system of claim 11, wherein the second BMC is configured to retrieve the first flash image stored in the first flash ROM, or the second flash image stored in the second flash ROM. 15. A method of updating a firmware in a multi storage node system, the method comprising:
power cycling a first node, the first node comprising: a first baseboard management controller (BMC), a first flash ROM configured to store a first flash image, and a first switch device configured to connect the first BMC to the first flash ROM; activating the first flash image in the first flash ROM; determining at least one of the following: at least one hardware component within the first node is not online or ready for a firmware update, the second flash image is corrupted, and/or the first node is unable to boot to OS; and retrieving, by the first BMC, a second flash image stored in a second flash ROM stored on a second node, wherein the first BMC is connected to a second switch device in the second node, wherein the second flash image is the same as the first flash. 16. The method of claim 15, wherein the first node further comprises a first storage controller, a third flash ROM configured to store a third flash image, and a third switch device configured to connect either the first BMC or the second BMC to the third flash ROM, and
wherein the second node further comprises a second storage controller, a fourth flash ROM configured to store a fourth flash image, fourth flash image identical to the third flash image, and a fourth switch configured to connect either the first BMC or the second BMC to the fourth flash ROM. 17. The method of claim 16, wherein the first flash image comprises a first BMC firmware flash image and the second flash image comprises a first storage switch expander controller firmware flash image. 18. The method of claim 16, wherein the third flash image comprises a second BMC firmware flash image and the fourth flash image comprises a second storage switch expander controller firmware flash image. 19. The method of claim 16, wherein each of the first switch device, the second switch device, the third switch device, and the fourth switch device comprises a multiplexor (MUX). 20. The method of claim 19, wherein each of the first switch device, the second switch device, the third switch device, and the fourth switch device is configured to multiplex the first BMC and the second BMC. | 2,100 |
6,576 | 6,576 | 14,672,772 | 2,145 | A vehicle includes an interface and a processor programmed to prompt a user to configure a series of configurable features. The processor may be further programmed to sequentially output via the interface the series of configurable features based on a configuration request. The series of configurable features each prompting the user to select one of a plurality of options associated with the configurable feature to capture a preference of the user for the configurable feature. The processor may be further programmed to alter settings associated with the configurable features based on the selection of the options via the user interface. | 1. A vehicle comprising:
an interface; and a processor programmed to,
in response to a configuration request, sequentially output via the interface a series of configurable features each prompting a user to select one of a plurality of options associated with the configurable feature to capture a preference of the user for the configurable feature, and
in response to selection via the interface of the options, alter settings associated with the configurable features. 2. The vehicle of claim 1, wherein the processor is further programmed to establish communication, via a wireless transceiver, with a handheld device configured to execute at least one feature from the configurable features, and transmit a signal to alter settings associated with the at least one feature executed at the handheld device. 3. The vehicle of claim 1, wherein the processor is further programmed to establish communication, via a wireless transceiver, with a network having a database, and transmit the altered settings associated with the configurable features to the database for storage. 4. The vehicle of claim 1, wherein the interface is a voice command receiver, a soft key, a hard key or a touch display screen. 5. The vehicle of claim 1, wherein the series of configurable features are vehicle features available for the vehicle. 6. The vehicle of claim 1, wherein the processor is further programmed to output each of the series of configurable features for no more than a predefined period of time. 7. The vehicle of claim 1, wherein the series of configurable features are associated with a mobile device connection, a navigation system, a drive-away locking feature, a motion sensor sensitivity feature, or a light time feature. 8. The vehicle of claim 7, wherein the plurality of options for the navigation system include a toll road preference, a home address entry, or a point of interest entry. 9. A device comprising:
a processor programmed to,
in response to a vehicle configuration request, sequentially output a series of configurable features each prompting a user to select one of a plurality of options associated with the configurable feature to capture a preference of the user for the configurable feature, and
in response to selection of the options, transmit a signal, via a communication connection with a vehicle processor, to alter settings for the configurable features. 10. The device of claim 9, wherein the processor is further programmed to establish communication with a network having a database and to transmit the altered settings to the database for storage. 11. The device of claim 9, wherein the processor is further programmed to output each of the series of configurable features for no more than a predefined period of time. 12. The device of claim 9, wherein the series of configurable features are associated with a mobile device connection, a navigation system, a drive-away locking feature, a motion sensor sensitivity feature, or a light time feature. 13. The device of claim 12, wherein the plurality of options for the drive-away locking feature include an activate automatic door lock option or a deactivate automatic door lock option. 14. A configuration method comprising:
executing, via a vehicle processor, a configuration request for sequentially outputting, via an interface in communication with the vehicle processor, a series of configurable features each prompting a user to select one of a plurality of options associated with the configurable feature to capture a preference of the user for the configurable feature; and in response to selection via the interface of the options, altering settings associated with the configurable features. 15. The method of claim 14, further comprising establishing communication with a handheld device, via a wireless transceiver in communication with the vehicle processor, configured to execute at least one feature from the configurable features, and transmitting a signal to alter settings associated with the at least one feature executed at the handheld device. 16. The method of claim 14, further comprising establishing communication with a network having a database via a wireless transceiver in communication with the vehicle processor, and transmitting the altered settings to the database for storage. 17. The method of claim 14, wherein the series of configurable features are associated with a mobile device connection, a navigation system, a drive-away locking feature, a motion sensor sensitivity feature, or a light time feature 18. The method of claim 14, wherein the interface is a soft key, a hard key or an in-vehicle touch display screen. | A vehicle includes an interface and a processor programmed to prompt a user to configure a series of configurable features. The processor may be further programmed to sequentially output via the interface the series of configurable features based on a configuration request. The series of configurable features each prompting the user to select one of a plurality of options associated with the configurable feature to capture a preference of the user for the configurable feature. The processor may be further programmed to alter settings associated with the configurable features based on the selection of the options via the user interface.1. A vehicle comprising:
an interface; and a processor programmed to,
in response to a configuration request, sequentially output via the interface a series of configurable features each prompting a user to select one of a plurality of options associated with the configurable feature to capture a preference of the user for the configurable feature, and
in response to selection via the interface of the options, alter settings associated with the configurable features. 2. The vehicle of claim 1, wherein the processor is further programmed to establish communication, via a wireless transceiver, with a handheld device configured to execute at least one feature from the configurable features, and transmit a signal to alter settings associated with the at least one feature executed at the handheld device. 3. The vehicle of claim 1, wherein the processor is further programmed to establish communication, via a wireless transceiver, with a network having a database, and transmit the altered settings associated with the configurable features to the database for storage. 4. The vehicle of claim 1, wherein the interface is a voice command receiver, a soft key, a hard key or a touch display screen. 5. The vehicle of claim 1, wherein the series of configurable features are vehicle features available for the vehicle. 6. The vehicle of claim 1, wherein the processor is further programmed to output each of the series of configurable features for no more than a predefined period of time. 7. The vehicle of claim 1, wherein the series of configurable features are associated with a mobile device connection, a navigation system, a drive-away locking feature, a motion sensor sensitivity feature, or a light time feature. 8. The vehicle of claim 7, wherein the plurality of options for the navigation system include a toll road preference, a home address entry, or a point of interest entry. 9. A device comprising:
a processor programmed to,
in response to a vehicle configuration request, sequentially output a series of configurable features each prompting a user to select one of a plurality of options associated with the configurable feature to capture a preference of the user for the configurable feature, and
in response to selection of the options, transmit a signal, via a communication connection with a vehicle processor, to alter settings for the configurable features. 10. The device of claim 9, wherein the processor is further programmed to establish communication with a network having a database and to transmit the altered settings to the database for storage. 11. The device of claim 9, wherein the processor is further programmed to output each of the series of configurable features for no more than a predefined period of time. 12. The device of claim 9, wherein the series of configurable features are associated with a mobile device connection, a navigation system, a drive-away locking feature, a motion sensor sensitivity feature, or a light time feature. 13. The device of claim 12, wherein the plurality of options for the drive-away locking feature include an activate automatic door lock option or a deactivate automatic door lock option. 14. A configuration method comprising:
executing, via a vehicle processor, a configuration request for sequentially outputting, via an interface in communication with the vehicle processor, a series of configurable features each prompting a user to select one of a plurality of options associated with the configurable feature to capture a preference of the user for the configurable feature; and in response to selection via the interface of the options, altering settings associated with the configurable features. 15. The method of claim 14, further comprising establishing communication with a handheld device, via a wireless transceiver in communication with the vehicle processor, configured to execute at least one feature from the configurable features, and transmitting a signal to alter settings associated with the at least one feature executed at the handheld device. 16. The method of claim 14, further comprising establishing communication with a network having a database via a wireless transceiver in communication with the vehicle processor, and transmitting the altered settings to the database for storage. 17. The method of claim 14, wherein the series of configurable features are associated with a mobile device connection, a navigation system, a drive-away locking feature, a motion sensor sensitivity feature, or a light time feature 18. The method of claim 14, wherein the interface is a soft key, a hard key or an in-vehicle touch display screen. | 2,100 |
6,577 | 6,577 | 15,995,535 | 2,173 | An example method is provided for a computing device to perform user interface control based on a pinch gesture. The computing device includes a touch-sensitive display. The method may comprise: displaying, on the touch-sensitive display, a user interface that includes a user interface element, which occupies part of the user interface and is selectable for resizing, and detecting, on the touch-sensitive display, a pinch gesture for resizing the user interface element within the user interface. The method may further comprise: determining a direction of the pinch gesture; and based on the direction of the pinch gesture, resizing the user interface element horizontally, vertically or diagonally within the user interface. | 1-22. (canceled) 23. A method for performing user interface control based on a pinch gesture provided to a touch-sensitive display of a computing device comprising:
displaying, on the touch-sensitive display, a user interface element; determining a direction of the pinch gesture detected on the touch-sensitive display; automatically selecting an edge or a corner of the user interface element based on a position of the user interface element in comparison to a reference point and the direction of the pinch gesture; and resizing the user interface element by adjusting the selected edge or the selected corner based on the direction of the pinch gesture. 24. The method of claim 23, wherein the direction of the pinch gesture is determined based on an angle between multiple touch points of the pinch gesture with respect to an axis. 25. The method of claim 24, further comprising determining the angle between the multiple touch points of the pinch gesture based on at least two positions of the multiple touch points of the pinch gesture. 26. The method of claim 25, wherein the angle can be determined based on an absolute distance between the at least two positions of the multiple touch points. 27. The method of claim 25, wherein the direction is determined by comparing the angle with an angle threshold. 28. The method of claim 1, wherein a resizing scale for adjusting the selected edge or the selected corner is based on a speed of the pinch gesture. 29. The method of claim 23, wherein the position of the user interface element within a user interface is based on a center point of the user interface element. 30. The method of claim 23, wherein the pinch gesture comprises a first pinch gesture, and the further comprises:
detecting a tap gesture on a user interface for selecting the user interface for resizing, wherein the user interface element occupies part of the user interface; and resizing the user interface based on a second pinch gesture detected on the user interface. 31. A non-transitory computer-readable storage medium that includes program instructions that, when executed by a processor of a computing device, cause the processor to perform a method of user interface control based on a pinch gesture provided to a touch-sensitive display of the computing device, the method comprising:
displaying, on the touch-sensitive display, a user interface element; determining a direction of a pinch gesture detected on the touch-sensitive display; automatically selecting an edge or a corner of the user interface element based on a position of the user interface element in comparison to a reference point and the direction of the pinch gesture; and resizing the user interface element by adjusting the selected edge or the selected corner based on the direction of the pinch gesture. 32. The non-transitory computer-readable storage medium of claim 31, wherein the direction of the pinch gesture is determined based on an angle between multiple touch points of the pinch gesture with respect to an axis. 33. The non-transitory computer-readable storage medium of claim 32, wherein the method further comprises determining the angle between the multiple touch points of the pinch gesture based on at least two positions of the multiple touch points of the pinch gesture. 34. The non-transitory computer-readable storage medium of claim 33, wherein the angle can be determined based on an absolute distance between the at least two positions of the multiple touch point. 35. The non-transitory computer-readable storage medium of claim 33, wherein the direction is determined by comparing the angle with a direction threshold. 36. The non-transitory computer-readable storage medium of claim 31, wherein a resizing scale for adjusting the selected edge or the selected corner is based on a speed of the pinch gesture. 37. A system, comprising:
a computing device; an application executable in the computing device, wherein, when executed, the application causes the computing device to at least: display, on a touch-sensitive display of the computing device, a user interface element; determine a direction of a pinch gesture detected on the touch-sensitive display; automatically selecting an edge or a corner of the user interface element based on a position of the user interface element in comparison to a reference point and the direction of the pinch gesture; and resize the user interface element by adjusting the selected edge or the selected corner based on the direction of the pinch gesture. 38. The system of claim 37, wherein the direction of the pinch gesture is determined based on an angle between multiple touch points of the pinch gesture with respect to an axis. 39. The system of claim 38, wherein, when executed, the application further causes the computing device to at least to determine the angle between the multiple touch points of the pinch gesture based on at least two positions of the multiple touch points of the pinch gesture. 40. The system of claim 39, wherein the angle can be determined based on an absolute distance between the at least two positions of the multiple touch point. 41. The system of claim 38, wherein the direction is determined by comparing the angle with an angle threshold. 42. The system of claim 37, wherein the pinch gesture comprises a first pinch gestures, and wherein, when executed, the application further causes the computing device to at least to:
detect a tap gesture on a user interface for selecting the user interface for resizing, wherein the user interface element occupies part of the user interface; and resize the user interface based on a second pinch gesture detected on the user interface. | An example method is provided for a computing device to perform user interface control based on a pinch gesture. The computing device includes a touch-sensitive display. The method may comprise: displaying, on the touch-sensitive display, a user interface that includes a user interface element, which occupies part of the user interface and is selectable for resizing, and detecting, on the touch-sensitive display, a pinch gesture for resizing the user interface element within the user interface. The method may further comprise: determining a direction of the pinch gesture; and based on the direction of the pinch gesture, resizing the user interface element horizontally, vertically or diagonally within the user interface.1-22. (canceled) 23. A method for performing user interface control based on a pinch gesture provided to a touch-sensitive display of a computing device comprising:
displaying, on the touch-sensitive display, a user interface element; determining a direction of the pinch gesture detected on the touch-sensitive display; automatically selecting an edge or a corner of the user interface element based on a position of the user interface element in comparison to a reference point and the direction of the pinch gesture; and resizing the user interface element by adjusting the selected edge or the selected corner based on the direction of the pinch gesture. 24. The method of claim 23, wherein the direction of the pinch gesture is determined based on an angle between multiple touch points of the pinch gesture with respect to an axis. 25. The method of claim 24, further comprising determining the angle between the multiple touch points of the pinch gesture based on at least two positions of the multiple touch points of the pinch gesture. 26. The method of claim 25, wherein the angle can be determined based on an absolute distance between the at least two positions of the multiple touch points. 27. The method of claim 25, wherein the direction is determined by comparing the angle with an angle threshold. 28. The method of claim 1, wherein a resizing scale for adjusting the selected edge or the selected corner is based on a speed of the pinch gesture. 29. The method of claim 23, wherein the position of the user interface element within a user interface is based on a center point of the user interface element. 30. The method of claim 23, wherein the pinch gesture comprises a first pinch gesture, and the further comprises:
detecting a tap gesture on a user interface for selecting the user interface for resizing, wherein the user interface element occupies part of the user interface; and resizing the user interface based on a second pinch gesture detected on the user interface. 31. A non-transitory computer-readable storage medium that includes program instructions that, when executed by a processor of a computing device, cause the processor to perform a method of user interface control based on a pinch gesture provided to a touch-sensitive display of the computing device, the method comprising:
displaying, on the touch-sensitive display, a user interface element; determining a direction of a pinch gesture detected on the touch-sensitive display; automatically selecting an edge or a corner of the user interface element based on a position of the user interface element in comparison to a reference point and the direction of the pinch gesture; and resizing the user interface element by adjusting the selected edge or the selected corner based on the direction of the pinch gesture. 32. The non-transitory computer-readable storage medium of claim 31, wherein the direction of the pinch gesture is determined based on an angle between multiple touch points of the pinch gesture with respect to an axis. 33. The non-transitory computer-readable storage medium of claim 32, wherein the method further comprises determining the angle between the multiple touch points of the pinch gesture based on at least two positions of the multiple touch points of the pinch gesture. 34. The non-transitory computer-readable storage medium of claim 33, wherein the angle can be determined based on an absolute distance between the at least two positions of the multiple touch point. 35. The non-transitory computer-readable storage medium of claim 33, wherein the direction is determined by comparing the angle with a direction threshold. 36. The non-transitory computer-readable storage medium of claim 31, wherein a resizing scale for adjusting the selected edge or the selected corner is based on a speed of the pinch gesture. 37. A system, comprising:
a computing device; an application executable in the computing device, wherein, when executed, the application causes the computing device to at least: display, on a touch-sensitive display of the computing device, a user interface element; determine a direction of a pinch gesture detected on the touch-sensitive display; automatically selecting an edge or a corner of the user interface element based on a position of the user interface element in comparison to a reference point and the direction of the pinch gesture; and resize the user interface element by adjusting the selected edge or the selected corner based on the direction of the pinch gesture. 38. The system of claim 37, wherein the direction of the pinch gesture is determined based on an angle between multiple touch points of the pinch gesture with respect to an axis. 39. The system of claim 38, wherein, when executed, the application further causes the computing device to at least to determine the angle between the multiple touch points of the pinch gesture based on at least two positions of the multiple touch points of the pinch gesture. 40. The system of claim 39, wherein the angle can be determined based on an absolute distance between the at least two positions of the multiple touch point. 41. The system of claim 38, wherein the direction is determined by comparing the angle with an angle threshold. 42. The system of claim 37, wherein the pinch gesture comprises a first pinch gestures, and wherein, when executed, the application further causes the computing device to at least to:
detect a tap gesture on a user interface for selecting the user interface for resizing, wherein the user interface element occupies part of the user interface; and resize the user interface based on a second pinch gesture detected on the user interface. | 2,100 |
6,578 | 6,578 | 12,503,472 | 2,147 | A project systems integrator integrates a financial planning system and an operational planning system for a project. The integrator loads a work breakdown structure (“WBS”) from the financial planning system and another WBS from the operational planning system. The integrator then records links between corresponding nodes of the financial WBS and operational WBS. When data is entered, updated, or otherwise changed, the data is propagated between the nodes in accordance with the links. | 1. A computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to integrate a financial planning system and an operational planning system for a project by:
loading a first work breakdown structure (WBS) from the financial planning system; loading a second WBS from the operational planning system; recording at least one link between a first node in the first WBS and a second node in the second WBS; and propagating data between the first node and the second node via the link. 2. The computer-readable medium of claim 1, wherein data entered into the financial planning system at the first node is propagated to the second node. 3. The computer-readable medium of claim 1, wherein data entered into the operational planning system at the second node is propagated to the first node. 4. The computer-readable medium of claim 1, further comprising recording a plurality of links linking a plurality of nodes in the first WBS and a plurality of nodes in the second WBS. 5. The computer-readable medium of claim 4, wherein the plurality of links are many-to-one. 6. The computer-readable medium of claim 4, wherein the plurality of links are one-to-one. 7. The computer-readable medium of claim 1, wherein the data flows in a one-way direction from the first node to the second node, and the data comprises at least one of: resource definition data, resource availability data, and budget data. 8. The computer-readable medium of claim 1, wherein the data flows in a one-way direction from the second node to the first node, and the data comprises at least one of: resource assignment data, resource demand data, estimated hours at completion data, estimated cost at completion data, cost of work done data, and percent completed data. 9. The computer-readable medium of claim 1, wherein the data flows in a two-way direction between the first node and the second node. 10. The computer-readable medium of claim 1, wherein the at least one link is changed to link the first node to a third node in the second WBS. 11. A computer-implemented method for integrating a financial planning system and an operational planning system for a project, comprising:
loading a first work breakdown structure (WBS) from the financial planning system; loading a second WBS from the operational planning system; recording at least one link between a first node in the first WBS and a second node in the second WBS; and propagating data between the first node and the second node in accordance with the link. 12. The method of claim 11, wherein data entered into the financial planning system at the first node is propagated to the second node. 13. The method of claim 11, wherein data entered into the operational planning system at the second node is propagated to the first node. 14. The method of claim 11, wherein the data flows in a one-way direction from the first node to the second node, and the data comprises at least one of: resource definition data, resource availability data, and budget data. 15. The method of claim 11, wherein the data flows in a one-way direction from the second node to the first node, and the data comprises at least one of: resource assignment data, resource demand data, estimated hours at completion data, estimated cost at completion data, cost of work done data, and percent completed data. 16. A system for integrating a financial planning system and an operational planning system for a project, comprising:
a financial planning system having a first work breakdown structure (WBS); an operational planning system having a second WBS; and a project systems integrator that records at least one link between a first node in the first WBS and a second node in the second WBS and propagates data between the first node and the second node in accordance with the link. 17. The system of claim 16, wherein the link comprises a web service. 18. The system of claim 16, wherein the link comprises extract, load and transport integration. 19. The computer-readable medium of claim 1, wherein the first node and second node are tasks. 20. The computer-readable medium of claim 1, wherein the data comprises changed data from the first WBS or the second WBS. | A project systems integrator integrates a financial planning system and an operational planning system for a project. The integrator loads a work breakdown structure (“WBS”) from the financial planning system and another WBS from the operational planning system. The integrator then records links between corresponding nodes of the financial WBS and operational WBS. When data is entered, updated, or otherwise changed, the data is propagated between the nodes in accordance with the links.1. A computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to integrate a financial planning system and an operational planning system for a project by:
loading a first work breakdown structure (WBS) from the financial planning system; loading a second WBS from the operational planning system; recording at least one link between a first node in the first WBS and a second node in the second WBS; and propagating data between the first node and the second node via the link. 2. The computer-readable medium of claim 1, wherein data entered into the financial planning system at the first node is propagated to the second node. 3. The computer-readable medium of claim 1, wherein data entered into the operational planning system at the second node is propagated to the first node. 4. The computer-readable medium of claim 1, further comprising recording a plurality of links linking a plurality of nodes in the first WBS and a plurality of nodes in the second WBS. 5. The computer-readable medium of claim 4, wherein the plurality of links are many-to-one. 6. The computer-readable medium of claim 4, wherein the plurality of links are one-to-one. 7. The computer-readable medium of claim 1, wherein the data flows in a one-way direction from the first node to the second node, and the data comprises at least one of: resource definition data, resource availability data, and budget data. 8. The computer-readable medium of claim 1, wherein the data flows in a one-way direction from the second node to the first node, and the data comprises at least one of: resource assignment data, resource demand data, estimated hours at completion data, estimated cost at completion data, cost of work done data, and percent completed data. 9. The computer-readable medium of claim 1, wherein the data flows in a two-way direction between the first node and the second node. 10. The computer-readable medium of claim 1, wherein the at least one link is changed to link the first node to a third node in the second WBS. 11. A computer-implemented method for integrating a financial planning system and an operational planning system for a project, comprising:
loading a first work breakdown structure (WBS) from the financial planning system; loading a second WBS from the operational planning system; recording at least one link between a first node in the first WBS and a second node in the second WBS; and propagating data between the first node and the second node in accordance with the link. 12. The method of claim 11, wherein data entered into the financial planning system at the first node is propagated to the second node. 13. The method of claim 11, wherein data entered into the operational planning system at the second node is propagated to the first node. 14. The method of claim 11, wherein the data flows in a one-way direction from the first node to the second node, and the data comprises at least one of: resource definition data, resource availability data, and budget data. 15. The method of claim 11, wherein the data flows in a one-way direction from the second node to the first node, and the data comprises at least one of: resource assignment data, resource demand data, estimated hours at completion data, estimated cost at completion data, cost of work done data, and percent completed data. 16. A system for integrating a financial planning system and an operational planning system for a project, comprising:
a financial planning system having a first work breakdown structure (WBS); an operational planning system having a second WBS; and a project systems integrator that records at least one link between a first node in the first WBS and a second node in the second WBS and propagates data between the first node and the second node in accordance with the link. 17. The system of claim 16, wherein the link comprises a web service. 18. The system of claim 16, wherein the link comprises extract, load and transport integration. 19. The computer-readable medium of claim 1, wherein the first node and second node are tasks. 20. The computer-readable medium of claim 1, wherein the data comprises changed data from the first WBS or the second WBS. | 2,100 |
6,579 | 6,579 | 15,755,540 | 2,119 | The present invention provides an improved system, device and method for reliably commissioning application devices within an application control network that scales well even with large installations of the respective application control systems. Instead of relying on a direct physical identification of the application devices installed at a specific position, e.g. in a building, the commissioning is based on feedback on trigger events and relative positions of the application devices. In a system comprising a commissioning device and a commissioning base station having access to an application plan the commissioning device is communicatively connected with the commissioning base station and is adapted to determine a relative position of a first application device that is communicatively coupled with an application control network. The commissioning device is further adapted to interact with the commissioning base station to trigger a reaction of the first application device and to verify that the reaction occurred. The system is adapted to create a corresponding application plan entry for the first application devices upon verification of the reaction. | 1-14. (canceled) 15. A system comprising
a commissioning base station adapted to access an application plan, wherein the application plan may be empty or comprise one or more application plan entries and scenes; commissioning device communicatively connected with the commissioning base station, and adapted to determine a position within a bounded area detected by the commissioning device of a first application device that is coupled with the commissioning base station via an application network, characterized in that the commissioning device is adapted to interact with the commissioning base station to trigger a reaction of the first application device; and the commissioning base station is adapted to create a corresponding application plan entry for the first application device upon verification of the reaction, to locate the first application device in a network graph representing the network topology upon occurrence of the reaction of the first application device, to determine at least a second application device in the vicinity of the first application device in the network graph; and to trigger the second application device; wherein the commissioning device is adapted to determine a position of the at least second application device within a bounded area upon detecting a reaction of the triggered second application device, and wherein the system is further adapted to create an application plan entry for the second application device and an application scene entry associating the first application device with the second application device. 16. The system according to claim 15, wherein the commissioning device is an autonomous vehicle, in particular a ground based vehicle, a marine vessel or an aerial vehicle. 17. The system according to claim 15, wherein creating an application plan entry or application scene comprises updating an existing application plan entry or application scene. 18. A commissioning device comprising
an imaging module and a situational awareness module; a communication interface enabling communication with a commissioning base station; wherein the situational awareness module processes data provided by the imaging module to construct a relative coordinate system and geo-fence of a bounded area, to detect a sensor device communicatively coupled with the commissioning base station within the bounded area and to determine the position of the sensor device within the bounded area; and wherein the commissioning device is configured to trigger a reaction of the sensor device receivable by the commissioning base station via an application network; to assist in creating a corresponding application plan entry for the application devices upon verification of the reaction by the commissioning base station, to detect a reaction of a lighting device triggered by the commissioning base station that is communicatively coupled with lighting device, and assist in creating an application plan entry for the lighting device and an application scene entry associating the sensor device with the lighting device. 19. The commissioning device according to claim 15 wherein the imaging module comprises an imaging sensor, a laser range finder, a laser scanner or combinations thereof. 20. The commissioning device according to claim 15 further comprising a motion control system connected to the situational awareness module and/or receiving input from a navigational module wherein the control system is adapted to control autonomous movements of the commissioning device. 21. The commissioning device according to claim 15 further comprising a micro processor, a memory module and a storage module, wherein the microprocessor is adapted to run the motion control system, the situational awareness module, the navigational module or combinations thereof. 22. The commissioning device according to claim 15 further comprising a directional antenna for communication with the commissioning base station. 23. The commissioning device according to claim 15, wherein the first application device is a network forwarding device. 24. A method for commissioning an application device within an application control network comprising at least a first application device coupled with a commissioning base station via the application control network; wherein the method comprises:
determining by a commissioning device a bounded area and create a relative coordinate system and geo-fence of the bounded area; triggering an event resulting in a reaction of the first application device; determining by a commissioning device a position of the first application device within the relative coordinate system, creating an application plan entry for the first application device to be stored in the application plan upon detection of the reaction, and locating the first application device in a network graph representative of the network topology, and determining at least a second application device in the vicinity of the first application device in the network graph; triggering a reaction of the second application device; determining by a commissioning device a position of the second application device within the relative coordinate system, and creating an application plan entry for second application device to be stored in the application plan and an application scene entry associating the first application device with the second application device. 25. The method according to claim 15, wherein the application plan entry comprises the relative coordinates of the application device. 26. The method according to claim 15, wherein triggering an event comprises submitting a request to change a mode of operation of the first application device, and
wherein determining a position of the application device comprises identifying the first application device by observing the changed mode of operation. 27. The method according to claim 15, wherein triggering an event comprises creating a signal to be detected by the first application device, and
wherein creating an application plan entry comprises creating the application plan entry upon detection of a signal transmitted by the first application device to the application control network in reaction to the detected signal. | The present invention provides an improved system, device and method for reliably commissioning application devices within an application control network that scales well even with large installations of the respective application control systems. Instead of relying on a direct physical identification of the application devices installed at a specific position, e.g. in a building, the commissioning is based on feedback on trigger events and relative positions of the application devices. In a system comprising a commissioning device and a commissioning base station having access to an application plan the commissioning device is communicatively connected with the commissioning base station and is adapted to determine a relative position of a first application device that is communicatively coupled with an application control network. The commissioning device is further adapted to interact with the commissioning base station to trigger a reaction of the first application device and to verify that the reaction occurred. The system is adapted to create a corresponding application plan entry for the first application devices upon verification of the reaction.1-14. (canceled) 15. A system comprising
a commissioning base station adapted to access an application plan, wherein the application plan may be empty or comprise one or more application plan entries and scenes; commissioning device communicatively connected with the commissioning base station, and adapted to determine a position within a bounded area detected by the commissioning device of a first application device that is coupled with the commissioning base station via an application network, characterized in that the commissioning device is adapted to interact with the commissioning base station to trigger a reaction of the first application device; and the commissioning base station is adapted to create a corresponding application plan entry for the first application device upon verification of the reaction, to locate the first application device in a network graph representing the network topology upon occurrence of the reaction of the first application device, to determine at least a second application device in the vicinity of the first application device in the network graph; and to trigger the second application device; wherein the commissioning device is adapted to determine a position of the at least second application device within a bounded area upon detecting a reaction of the triggered second application device, and wherein the system is further adapted to create an application plan entry for the second application device and an application scene entry associating the first application device with the second application device. 16. The system according to claim 15, wherein the commissioning device is an autonomous vehicle, in particular a ground based vehicle, a marine vessel or an aerial vehicle. 17. The system according to claim 15, wherein creating an application plan entry or application scene comprises updating an existing application plan entry or application scene. 18. A commissioning device comprising
an imaging module and a situational awareness module; a communication interface enabling communication with a commissioning base station; wherein the situational awareness module processes data provided by the imaging module to construct a relative coordinate system and geo-fence of a bounded area, to detect a sensor device communicatively coupled with the commissioning base station within the bounded area and to determine the position of the sensor device within the bounded area; and wherein the commissioning device is configured to trigger a reaction of the sensor device receivable by the commissioning base station via an application network; to assist in creating a corresponding application plan entry for the application devices upon verification of the reaction by the commissioning base station, to detect a reaction of a lighting device triggered by the commissioning base station that is communicatively coupled with lighting device, and assist in creating an application plan entry for the lighting device and an application scene entry associating the sensor device with the lighting device. 19. The commissioning device according to claim 15 wherein the imaging module comprises an imaging sensor, a laser range finder, a laser scanner or combinations thereof. 20. The commissioning device according to claim 15 further comprising a motion control system connected to the situational awareness module and/or receiving input from a navigational module wherein the control system is adapted to control autonomous movements of the commissioning device. 21. The commissioning device according to claim 15 further comprising a micro processor, a memory module and a storage module, wherein the microprocessor is adapted to run the motion control system, the situational awareness module, the navigational module or combinations thereof. 22. The commissioning device according to claim 15 further comprising a directional antenna for communication with the commissioning base station. 23. The commissioning device according to claim 15, wherein the first application device is a network forwarding device. 24. A method for commissioning an application device within an application control network comprising at least a first application device coupled with a commissioning base station via the application control network; wherein the method comprises:
determining by a commissioning device a bounded area and create a relative coordinate system and geo-fence of the bounded area; triggering an event resulting in a reaction of the first application device; determining by a commissioning device a position of the first application device within the relative coordinate system, creating an application plan entry for the first application device to be stored in the application plan upon detection of the reaction, and locating the first application device in a network graph representative of the network topology, and determining at least a second application device in the vicinity of the first application device in the network graph; triggering a reaction of the second application device; determining by a commissioning device a position of the second application device within the relative coordinate system, and creating an application plan entry for second application device to be stored in the application plan and an application scene entry associating the first application device with the second application device. 25. The method according to claim 15, wherein the application plan entry comprises the relative coordinates of the application device. 26. The method according to claim 15, wherein triggering an event comprises submitting a request to change a mode of operation of the first application device, and
wherein determining a position of the application device comprises identifying the first application device by observing the changed mode of operation. 27. The method according to claim 15, wherein triggering an event comprises creating a signal to be detected by the first application device, and
wherein creating an application plan entry comprises creating the application plan entry upon detection of a signal transmitted by the first application device to the application control network in reaction to the detected signal. | 2,100 |
6,580 | 6,580 | 15,349,041 | 2,128 | Mechanisms for bootstrapping knowledge acquisition from a limited knowledge domain are presented. Natural language content is received and a primary and secondary portion of natural language content are identified within the natural language content. The secondary portion of natural language content is analyzed to identify indications of meaning directed to elements of the primary portion of natural language content. Features related to the secondary portion of the natural language content indicate meaning directed to the primary portion of the natural language content. A collection of domain knowledge is generated from an analysis of the primary and secondary portions of the natural language content and stored to provide meaningful responses to requests. | 1. A method, in a data processing system comprising a processor and a memory accessible by the processor, for acquiring knowledge from natural language content, the method comprising:
receiving, by the data processing system, natural language content from a corpus of information; identifying, by the data processing system, a primary portion of natural language content that references an object of the natural language content; identifying, by the data processing system, a secondary portion of natural language content that references an action for the object; analyzing, by the data processing system, the secondary portion of natural language content to identify at least one feature of the action for the object, wherein the at least one feature indicates meaning directed to the primary portion of natural language content; generating, by the data processing system, a collection of domain knowledge from the analysis of the primary portion and the secondary portion of the natural language content; and storing the collection of domain knowledge in a storage facility accessible by the processor of the data processing system for use in processing other natural language content. 2. The method of claim 1, wherein analyzing the secondary portion of natural language content further comprises correlating a temporal characteristic applied to the primary portion of natural language content. 3. The method of claim 1, further comprising:
analyzing, by the data processing system, a second portion of natural language content in which a reference to a second object is present; determining, by the data processing system, whether or not the second object has a same or similar type to a type of the object referenced by the primary portion of natural language content; and in response to the second object having a same or similar type to a type of the object referenced by the primary portion of natural language content, associating the meaning indicated by the at least one feature of the action with the second object in the collection of domain knowledge. 4. The method of claim 1, wherein the collection of domain knowledge is seeded with a plurality of features relevant to an action based on an initial analysis of natural language content. 5. The method of claim 1, further comprising performing a cognitive operation to build the collection of domain knowledge. 6. The method of claim 5, wherein the cognitive operation is a question answering operation performed by a question and answer pipeline implemented in the data processing system. 7. The method of claim 1, further comprising generating a meaningful response to a request for an instruction by analyzing the request and accessing the collection of domain knowledge. 8. The method of claim 7, wherein generating the meaningful response comprises:
applying an appropriate feature and action stored in the collection of domain knowledge to an object identified from the request. 9. The method of claim 8, wherein the request is for cooking instructions. 10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed in a data processing system, causes the data processing system to:
receive natural language content from a corpus of information; identify a primary portion of natural language content that references an object of the natural language content; identify a secondary portion of natural language content that references an action for the object; analyze the secondary portion of natural language content to identify at least one feature of the action for the object, wherein the at least one feature indicates meaning directed to the primary portion of natural language content; generate a collection of domain knowledge from the analysis of the primary portion and the secondary portion of the natural language content; and store the collection of domain knowledge in a storage facility accessible by the data processing system for use in processing other natural language content. 11. The computer program product of claim 10, wherein analyzing the secondary portion of natural language content further comprises correlating a temporal characteristic applied to the primary portion of natural language content. 12. The computer program product of claim 10, wherein generating the collection of domain knowledge further comprises storing the collection of domain knowledge in a storage facility accessible by the processor of the data processing system. 13. The computer program product of claim 10, wherein the computer readable program further causes the data processing system to:
analyze a second portion of natural language content in which a reference to a second object is present; determine whether or not the second object has a same or similar type to a type of the object referenced by the primary portion of natural language content; and in response to the second object having a same or similar type to a type of the object referenced by the primary portion of natural language content, associate the meaning indicated by the at least one feature of the action with the second object in the collection of domain knowledge. 14. The computer program product of claim 10, further comprising performing a cognitive operation to build the collection of domain knowledge. 15. The computer program product of claim 14, wherein the cognitive operation is a question answering operation performed by a question and answer pipeline implemented in the data processing system. 16. The computer program product of claim 10, further comprising generating a meaningful response to a request for an instruction by analyzing the request and accessing the collection of domain knowledge. 17. The computer program product of claim 16, wherein generating the meaningful response comprises:
applying an appropriate feature and action stored in the collection of domain knowledge to an object identified from the request. 18. The computer program product of claim 17, wherein the request is for cooking instructions. 19. The computer program product of claim 10, wherein the corpus of information includes a recipe. 20. An apparatus comprising:
a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive natural language content from a corpus of information; identify a primary portion of natural language content that references an object of the natural language content; identify a secondary portion of natural language content that references an action for the object; analyze the secondary portion of natural language content to identify at least one feature of the action for the object, wherein the at least one feature indicates meaning directed to the primary portion of natural language content; generate a collection of domain knowledge from the analysis of the primary portion and the secondary portion of the natural language content; and store the collection of domain knowledge in a storage facility accessible by the processor of the apparatus for use in processing other natural language content. | Mechanisms for bootstrapping knowledge acquisition from a limited knowledge domain are presented. Natural language content is received and a primary and secondary portion of natural language content are identified within the natural language content. The secondary portion of natural language content is analyzed to identify indications of meaning directed to elements of the primary portion of natural language content. Features related to the secondary portion of the natural language content indicate meaning directed to the primary portion of the natural language content. A collection of domain knowledge is generated from an analysis of the primary and secondary portions of the natural language content and stored to provide meaningful responses to requests.1. A method, in a data processing system comprising a processor and a memory accessible by the processor, for acquiring knowledge from natural language content, the method comprising:
receiving, by the data processing system, natural language content from a corpus of information; identifying, by the data processing system, a primary portion of natural language content that references an object of the natural language content; identifying, by the data processing system, a secondary portion of natural language content that references an action for the object; analyzing, by the data processing system, the secondary portion of natural language content to identify at least one feature of the action for the object, wherein the at least one feature indicates meaning directed to the primary portion of natural language content; generating, by the data processing system, a collection of domain knowledge from the analysis of the primary portion and the secondary portion of the natural language content; and storing the collection of domain knowledge in a storage facility accessible by the processor of the data processing system for use in processing other natural language content. 2. The method of claim 1, wherein analyzing the secondary portion of natural language content further comprises correlating a temporal characteristic applied to the primary portion of natural language content. 3. The method of claim 1, further comprising:
analyzing, by the data processing system, a second portion of natural language content in which a reference to a second object is present; determining, by the data processing system, whether or not the second object has a same or similar type to a type of the object referenced by the primary portion of natural language content; and in response to the second object having a same or similar type to a type of the object referenced by the primary portion of natural language content, associating the meaning indicated by the at least one feature of the action with the second object in the collection of domain knowledge. 4. The method of claim 1, wherein the collection of domain knowledge is seeded with a plurality of features relevant to an action based on an initial analysis of natural language content. 5. The method of claim 1, further comprising performing a cognitive operation to build the collection of domain knowledge. 6. The method of claim 5, wherein the cognitive operation is a question answering operation performed by a question and answer pipeline implemented in the data processing system. 7. The method of claim 1, further comprising generating a meaningful response to a request for an instruction by analyzing the request and accessing the collection of domain knowledge. 8. The method of claim 7, wherein generating the meaningful response comprises:
applying an appropriate feature and action stored in the collection of domain knowledge to an object identified from the request. 9. The method of claim 8, wherein the request is for cooking instructions. 10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed in a data processing system, causes the data processing system to:
receive natural language content from a corpus of information; identify a primary portion of natural language content that references an object of the natural language content; identify a secondary portion of natural language content that references an action for the object; analyze the secondary portion of natural language content to identify at least one feature of the action for the object, wherein the at least one feature indicates meaning directed to the primary portion of natural language content; generate a collection of domain knowledge from the analysis of the primary portion and the secondary portion of the natural language content; and store the collection of domain knowledge in a storage facility accessible by the data processing system for use in processing other natural language content. 11. The computer program product of claim 10, wherein analyzing the secondary portion of natural language content further comprises correlating a temporal characteristic applied to the primary portion of natural language content. 12. The computer program product of claim 10, wherein generating the collection of domain knowledge further comprises storing the collection of domain knowledge in a storage facility accessible by the processor of the data processing system. 13. The computer program product of claim 10, wherein the computer readable program further causes the data processing system to:
analyze a second portion of natural language content in which a reference to a second object is present; determine whether or not the second object has a same or similar type to a type of the object referenced by the primary portion of natural language content; and in response to the second object having a same or similar type to a type of the object referenced by the primary portion of natural language content, associate the meaning indicated by the at least one feature of the action with the second object in the collection of domain knowledge. 14. The computer program product of claim 10, further comprising performing a cognitive operation to build the collection of domain knowledge. 15. The computer program product of claim 14, wherein the cognitive operation is a question answering operation performed by a question and answer pipeline implemented in the data processing system. 16. The computer program product of claim 10, further comprising generating a meaningful response to a request for an instruction by analyzing the request and accessing the collection of domain knowledge. 17. The computer program product of claim 16, wherein generating the meaningful response comprises:
applying an appropriate feature and action stored in the collection of domain knowledge to an object identified from the request. 18. The computer program product of claim 17, wherein the request is for cooking instructions. 19. The computer program product of claim 10, wherein the corpus of information includes a recipe. 20. An apparatus comprising:
a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive natural language content from a corpus of information; identify a primary portion of natural language content that references an object of the natural language content; identify a secondary portion of natural language content that references an action for the object; analyze the secondary portion of natural language content to identify at least one feature of the action for the object, wherein the at least one feature indicates meaning directed to the primary portion of natural language content; generate a collection of domain knowledge from the analysis of the primary portion and the secondary portion of the natural language content; and store the collection of domain knowledge in a storage facility accessible by the processor of the apparatus for use in processing other natural language content. | 2,100 |
6,581 | 6,581 | 16,117,478 | 2,154 | Disclosed herein are system, method, and computer program product embodiments for providing a smart search and help system. An embodiment operates by receiving a search term from a user account. A role associated with the user account is determined. One or more documents of the repository that are associated with the search term are identified. The identified one or more documents are ranked based on both their association with the search term and their association with the role. The ranked one or more documents are returned. | 1. A computer-implemented method, comprising:
receiving a search term from a user account, wherein the search term comprises a plurality of words; determining a role associated with the user account, wherein the role is associated with one or more documents of a repository; identifying one or more documents of the repository that are associated with the search term; ranking the identified one or more documents based on both their association with the search term and their association with the role; and returning the ranked one or more documents. 2. The method of claim 1, wherein the ranking comprises:
determining that a first one of the ranked documents includes a verified association to the search term, wherein a second one of the ranked documents does not include the verified association, and wherein the first ranked document is ranked higher than the second ranked document based on the verified association. 3. The method of claim 2, wherein the search term is associated with a product, and
wherein the first ranked document comprises a user manual of the product. 4. The method of claim 1, wherein the ranking comprises:
determining that the plurality of words include at least a first word and a second word; calculating, for each of the identified documents, a distance between the first word and the second word within a context of each respective one of the identified documents; and ranking the identified documents based on the distance, wherein a greater distance corresponds to a lower ranking. 5. The method of claim 1, wherein the ranking comprises:
determining a structure of the one or more identified documents; identifying a location of the one or more words of the search term within the structure for a respective one of the identified documents; and ranking the identified documents based on the identified location. 6. The method of claim 1, further comprising:
receiving the search term from a second user account associated with a second role; and ranking the identified one or more documents based on both their association with the search term and their association with the second role, wherein the ranking based on the role differs from the ranking based on the second role. 7. The method of claim 1, wherein the identifying comprises:
computing a vector for the search term; computing a vector for each of a plurality of the documents from the repository; and comparing the vector for the search term to the vector for each of the documents to determine a similarity score. 8. The method of claim 7, further comprising:
ranking the plurality of documents based on the similarity score. 9. A system, comprising:
a memory; and at least one processor coupled to the memory and configured to: receive a search term from a user account, wherein the search term comprises a plurality of words; determine a role associated with the user account, wherein the role is associated with one or more documents of a repository; identify one or more documents of the repository that are associated with the search term; rank the identified one or more documents based on both their association with the search term and their association with the role; and return the ranked one or more documents. 10. The system of claim 9, wherein the at least one processor configured to rank is configured to:
determine that a first one of the ranked documents includes a verified association to the search term, wherein a second one of the ranked documents does not include the verified association, and wherein the first ranked document is ranked higher than the second ranked document based on the verified association. 11. The system of claim 10, wherein the search term is associated with a product, and
wherein the first ranked document comprises a user manual of the product. 12. The system of claim 9, wherein the at least one processor configured to rank is configured to:
determine that the plurality of words include at least a first word and a second word; calculate, for each of the identified documents, a distance between the first word and the second word within a context of each respective one of the identified documents; and rank the identified documents based on the distance, wherein a greater distance corresponds to a lower ranking. 13. The system of claim 9, wherein the at least one processor configured to rank is configured to:
determine a structure of the one or more identified documents: identify a location of the one or more words of the search term within the structure for a respective one of the identified documents; and rank the identified documents based on the identified location. 14. The system of claim 9, wherein the at least one processor is further configured to:
receive the search term from a second user account associated with a second role; and rank the identified one or more documents based on both their association with the search term and their association with the second role, wherein the ranking based on the role differs from the ranking based on the second role. 15. The system of claim 9, wherein the at least one processor configured to identify is configured to:
compute a vector for the search term; compute a vector for each of a plurality of the documents from the repository; and compare the vector for the search term to the vector for each of the documents to determine a similarity score. 16. The system of claim 15, wherein the at least one processor is further configured to:
rank the plurality of documents based on the similarity score. 17. A non-transitory computer-readable device having instructions stored thereon that,
when executed by at least one computing device, cause the at least one computing device to perform operations comprising: receiving a search term from a user account, wherein the search term comprises a plurality of words; determining a role associated with the user account, wherein the role is associated with one or more documents of a repository; identifying one or more documents of the repository that are associated with the search term; ranking the identified one or more documents based on both their association with the search term and their association with the role; and returning the ranked one or more documents. 18. The non-transitory computer-readable device of claim 17, wherein the ranking comprises:
determining that a first one of the ranked documents includes a verified association to the search term, wherein a second one of the ranked documents does not include the verified association, and wherein the first ranked document is ranked higher than the second ranked document based on the verified association. 19. The non-transitory computer-readable device of claim 18, wherein the search term is associated with a product, and wherein the first ranked document comprises a user manual of the product. 20. The non-transitory computer-readable device of claim 17, wherein the ranking comprises:
determining that the plurality of words include at least a first word and a second word; calculating, for each of the identified documents, a distance between the first word and the second word within a context of each respective one of the identified documents; and ranking the identified documents based on the distance, wherein a greater distance corresponds to a lower ranking. | Disclosed herein are system, method, and computer program product embodiments for providing a smart search and help system. An embodiment operates by receiving a search term from a user account. A role associated with the user account is determined. One or more documents of the repository that are associated with the search term are identified. The identified one or more documents are ranked based on both their association with the search term and their association with the role. The ranked one or more documents are returned.1. A computer-implemented method, comprising:
receiving a search term from a user account, wherein the search term comprises a plurality of words; determining a role associated with the user account, wherein the role is associated with one or more documents of a repository; identifying one or more documents of the repository that are associated with the search term; ranking the identified one or more documents based on both their association with the search term and their association with the role; and returning the ranked one or more documents. 2. The method of claim 1, wherein the ranking comprises:
determining that a first one of the ranked documents includes a verified association to the search term, wherein a second one of the ranked documents does not include the verified association, and wherein the first ranked document is ranked higher than the second ranked document based on the verified association. 3. The method of claim 2, wherein the search term is associated with a product, and
wherein the first ranked document comprises a user manual of the product. 4. The method of claim 1, wherein the ranking comprises:
determining that the plurality of words include at least a first word and a second word; calculating, for each of the identified documents, a distance between the first word and the second word within a context of each respective one of the identified documents; and ranking the identified documents based on the distance, wherein a greater distance corresponds to a lower ranking. 5. The method of claim 1, wherein the ranking comprises:
determining a structure of the one or more identified documents; identifying a location of the one or more words of the search term within the structure for a respective one of the identified documents; and ranking the identified documents based on the identified location. 6. The method of claim 1, further comprising:
receiving the search term from a second user account associated with a second role; and ranking the identified one or more documents based on both their association with the search term and their association with the second role, wherein the ranking based on the role differs from the ranking based on the second role. 7. The method of claim 1, wherein the identifying comprises:
computing a vector for the search term; computing a vector for each of a plurality of the documents from the repository; and comparing the vector for the search term to the vector for each of the documents to determine a similarity score. 8. The method of claim 7, further comprising:
ranking the plurality of documents based on the similarity score. 9. A system, comprising:
a memory; and at least one processor coupled to the memory and configured to: receive a search term from a user account, wherein the search term comprises a plurality of words; determine a role associated with the user account, wherein the role is associated with one or more documents of a repository; identify one or more documents of the repository that are associated with the search term; rank the identified one or more documents based on both their association with the search term and their association with the role; and return the ranked one or more documents. 10. The system of claim 9, wherein the at least one processor configured to rank is configured to:
determine that a first one of the ranked documents includes a verified association to the search term, wherein a second one of the ranked documents does not include the verified association, and wherein the first ranked document is ranked higher than the second ranked document based on the verified association. 11. The system of claim 10, wherein the search term is associated with a product, and
wherein the first ranked document comprises a user manual of the product. 12. The system of claim 9, wherein the at least one processor configured to rank is configured to:
determine that the plurality of words include at least a first word and a second word; calculate, for each of the identified documents, a distance between the first word and the second word within a context of each respective one of the identified documents; and rank the identified documents based on the distance, wherein a greater distance corresponds to a lower ranking. 13. The system of claim 9, wherein the at least one processor configured to rank is configured to:
determine a structure of the one or more identified documents: identify a location of the one or more words of the search term within the structure for a respective one of the identified documents; and rank the identified documents based on the identified location. 14. The system of claim 9, wherein the at least one processor is further configured to:
receive the search term from a second user account associated with a second role; and rank the identified one or more documents based on both their association with the search term and their association with the second role, wherein the ranking based on the role differs from the ranking based on the second role. 15. The system of claim 9, wherein the at least one processor configured to identify is configured to:
compute a vector for the search term; compute a vector for each of a plurality of the documents from the repository; and compare the vector for the search term to the vector for each of the documents to determine a similarity score. 16. The system of claim 15, wherein the at least one processor is further configured to:
rank the plurality of documents based on the similarity score. 17. A non-transitory computer-readable device having instructions stored thereon that,
when executed by at least one computing device, cause the at least one computing device to perform operations comprising: receiving a search term from a user account, wherein the search term comprises a plurality of words; determining a role associated with the user account, wherein the role is associated with one or more documents of a repository; identifying one or more documents of the repository that are associated with the search term; ranking the identified one or more documents based on both their association with the search term and their association with the role; and returning the ranked one or more documents. 18. The non-transitory computer-readable device of claim 17, wherein the ranking comprises:
determining that a first one of the ranked documents includes a verified association to the search term, wherein a second one of the ranked documents does not include the verified association, and wherein the first ranked document is ranked higher than the second ranked document based on the verified association. 19. The non-transitory computer-readable device of claim 18, wherein the search term is associated with a product, and wherein the first ranked document comprises a user manual of the product. 20. The non-transitory computer-readable device of claim 17, wherein the ranking comprises:
determining that the plurality of words include at least a first word and a second word; calculating, for each of the identified documents, a distance between the first word and the second word within a context of each respective one of the identified documents; and ranking the identified documents based on the distance, wherein a greater distance corresponds to a lower ranking. | 2,100 |
6,582 | 6,582 | 14,519,680 | 2,119 | Systems and methods include/use, among other components, a three-dimensional (3-D) printer creating 3-D items based on 3-D printing information, and a finishing device. The finishing device performs finishing operations on the 3-D item based on finishing information. Also, such systems and methods include a communications device, and the communications device automatically provides the 3-D printing information to the 3-D printer, provides the finishing information to the finishing device, and provides two-way status information updates between the 3-D printer and the finishing device. | 1. A system comprising:
a three-dimensional (3-D) printer creating a 3-D item based on 3-D printing information; a finishing device operatively connected to said 3-D printer performing finishing operations on said 3-D item based on finishing information; and a communications device operatively connected to said 3-D printer and said finishing device, said communications device automatically providing said 3-D printing information to said 3-D printer and said finishing information to said finishing device. 2. The system according to claim 1, said finishing information comprising command signals and status signals. 3. The system according to claim 2, said status signals comprising status information of a progress of said creating said 3-D item. 4. The system according to claim 2, said command signals comprising instructions of finishing operations to be performed on said 3-D item. 5. The system according to claim 1, said communications device transmitting said finishing information from said 3-D printer to said finishing device during a time period between when said 3-D printer begins creating said 3-D item and when said 3-D printer completes creating said 3-D item. 6. The system according to claim 1, said communications device comprising one or more devices, said one or more devices being integral with at least one of: said 3-D printer; and said finisher device. 7. The system according to claim 1, said finishing information comprising at least one of:
dimensions of said 3-D item; instructions to begin cycle-up of one or more finishing devices; requests for progress status of finishing operations; and requests for ready state, consumable supply levels, and failure status states of said one or more finishing devices. 8. A system comprising:
a three-dimensional (3-D) printer creating a 3-D item based on 3-D printing information; a finishing device operatively connected to said 3-D printer performing finishing operations on said 3-D item based on finishing information; and a communications device operatively connected to said 3-D printer and said finishing device, said communications device automatically providing:
said 3-D printing information to said 3-D printer and said finishing information to said finishing device; and
two-way status information updates between said 3-D printer and said finishing device. 9. The system according to claim 8, said finishing information comprising command signals and status signals. 10. The system according to claim 9, said status signals comprising status information of a progress of said creating said 3-D item. 11. The system according to claim 8, said command signals comprising instructions of finishing operations to be performed on said 3-D item. 12. The system according to claim 8, said communications device transmitting said finishing information from said 3-D printer to said finishing device during a time period between when said 3-D printer begins creating said 3-D item and when said 3-D printer completes creating said 3-D item. 13. The system according to claim 8, said communications device comprising one or more devices, said one or more devices being integral with at least one of: said 3-D printer; and said finisher device. 14. The system according to claim 8, said finishing information comprising at least one of:
dimensions of said 3-D item; instructions to begin cycle-up of one or more finishing devices; requests for progress status of finishing operations; and requests for ready state, consumable supply levels, and failure status states of said one or more finishing devices. 15. A method comprising:
providing 3-D printing information to a three-dimensional (3-D) printer, said 3-D printer automatically creating 3-D item based on said 3-D printing information; automatically providing finishing information to a finishing device using a special-purpose communications device, said finishing device automatically performing finishing operations on said 3-D item based on said finishing information, and said communications device being operatively connected to said 3-D printer and said finishing device; and automatically providing two-way status information updates between said 3-D printer and said finishing device using said special-purpose communications device. 16. The method according to claim 15, said finishing information comprising command signals and status signals. 17. The method according to claim 16, said status signals comprising status information of a progress of said creating said 3-D item. 18. The method according to claim 16, said command signals comprising instructions of finishing operations to be performed on said 3-D item. 19. The method according to claim 15, said transmitting said finishing information comprising transmitting said finishing information from said 3-D printer to said finishing device during a time period between when said 3-D printer begins creating said 3-D item and when said 3-D printer completes creating said 3-D item. 20. The method according to claim 15, said communications device comprising one or more devices, said one or more devices being integral with at least one of: said 3-D printer; and said finisher device. | Systems and methods include/use, among other components, a three-dimensional (3-D) printer creating 3-D items based on 3-D printing information, and a finishing device. The finishing device performs finishing operations on the 3-D item based on finishing information. Also, such systems and methods include a communications device, and the communications device automatically provides the 3-D printing information to the 3-D printer, provides the finishing information to the finishing device, and provides two-way status information updates between the 3-D printer and the finishing device.1. A system comprising:
a three-dimensional (3-D) printer creating a 3-D item based on 3-D printing information; a finishing device operatively connected to said 3-D printer performing finishing operations on said 3-D item based on finishing information; and a communications device operatively connected to said 3-D printer and said finishing device, said communications device automatically providing said 3-D printing information to said 3-D printer and said finishing information to said finishing device. 2. The system according to claim 1, said finishing information comprising command signals and status signals. 3. The system according to claim 2, said status signals comprising status information of a progress of said creating said 3-D item. 4. The system according to claim 2, said command signals comprising instructions of finishing operations to be performed on said 3-D item. 5. The system according to claim 1, said communications device transmitting said finishing information from said 3-D printer to said finishing device during a time period between when said 3-D printer begins creating said 3-D item and when said 3-D printer completes creating said 3-D item. 6. The system according to claim 1, said communications device comprising one or more devices, said one or more devices being integral with at least one of: said 3-D printer; and said finisher device. 7. The system according to claim 1, said finishing information comprising at least one of:
dimensions of said 3-D item; instructions to begin cycle-up of one or more finishing devices; requests for progress status of finishing operations; and requests for ready state, consumable supply levels, and failure status states of said one or more finishing devices. 8. A system comprising:
a three-dimensional (3-D) printer creating a 3-D item based on 3-D printing information; a finishing device operatively connected to said 3-D printer performing finishing operations on said 3-D item based on finishing information; and a communications device operatively connected to said 3-D printer and said finishing device, said communications device automatically providing:
said 3-D printing information to said 3-D printer and said finishing information to said finishing device; and
two-way status information updates between said 3-D printer and said finishing device. 9. The system according to claim 8, said finishing information comprising command signals and status signals. 10. The system according to claim 9, said status signals comprising status information of a progress of said creating said 3-D item. 11. The system according to claim 8, said command signals comprising instructions of finishing operations to be performed on said 3-D item. 12. The system according to claim 8, said communications device transmitting said finishing information from said 3-D printer to said finishing device during a time period between when said 3-D printer begins creating said 3-D item and when said 3-D printer completes creating said 3-D item. 13. The system according to claim 8, said communications device comprising one or more devices, said one or more devices being integral with at least one of: said 3-D printer; and said finisher device. 14. The system according to claim 8, said finishing information comprising at least one of:
dimensions of said 3-D item; instructions to begin cycle-up of one or more finishing devices; requests for progress status of finishing operations; and requests for ready state, consumable supply levels, and failure status states of said one or more finishing devices. 15. A method comprising:
providing 3-D printing information to a three-dimensional (3-D) printer, said 3-D printer automatically creating 3-D item based on said 3-D printing information; automatically providing finishing information to a finishing device using a special-purpose communications device, said finishing device automatically performing finishing operations on said 3-D item based on said finishing information, and said communications device being operatively connected to said 3-D printer and said finishing device; and automatically providing two-way status information updates between said 3-D printer and said finishing device using said special-purpose communications device. 16. The method according to claim 15, said finishing information comprising command signals and status signals. 17. The method according to claim 16, said status signals comprising status information of a progress of said creating said 3-D item. 18. The method according to claim 16, said command signals comprising instructions of finishing operations to be performed on said 3-D item. 19. The method according to claim 15, said transmitting said finishing information comprising transmitting said finishing information from said 3-D printer to said finishing device during a time period between when said 3-D printer begins creating said 3-D item and when said 3-D printer completes creating said 3-D item. 20. The method according to claim 15, said communications device comprising one or more devices, said one or more devices being integral with at least one of: said 3-D printer; and said finisher device. | 2,100 |
6,583 | 6,583 | 12,494,045 | 2,179 | The present disclosure teaches a solution for a user customizable abstraction layer for tailoring all operating system, application, and web based interfaces. The interface differs from conventional user interfaces by presenting a dynamic interface which can enable user access across all domains and applications with which the user can interact. The interface can be dynamically built as a user interacts with clients (e.g., devices/applications). Clients can utilize common usage patterns, installed application, installed themes, personal information, and the like, to create a highly customized adaptive user designed and modifiable interface. | 1. A dioramic system comprising:
an application interaction manager for receiving output events from a plurality of applications and for sending input event to said applications; a diorama rendering engine for dynamically generating output for a dioramic user interface from received ones of the output events in accordance with at user customizations established within the dioramic system; a user interaction manager for dynamically receiving user input from a dioramic user interface and converting in real-time said user input into said sent input events in accordance with user customizations established with in the dioramic system; and a diorama bus configured to communicatively link said application interaction manager, said diorama rendering engine, and said user interaction manager to each other, wherein said dioramic user interface is a three dimensional interface independent of said applications comprising environment characteristics and avatars having characteristics derived from application specific events, wherein each of said application interaction manager, said diorama rendering engine, and said user interaction manager comprise computer program products stored in a physical medium executable by a hardware processor. 2. The system of claim 1, wherein the dioramic system is hosted on a computing device providing the dioramic user experience for all user interaction functions and services of an operating system of the computing device, said dioramic system interfacing with the operating system by one of the following:
A) interfacing with the operating system by being embedded within the operating system software; and B) interfacing with the operating system being implemented in an independent layer co-located with the operating system. 3. The system of claim 1, wherein each of said application interaction manager, said diorama rendering engine, and said user interaction manager comprise software applications implemented within a J2EE server, said dioramic system comprising middleware executing between a remotely located application and a remotely located diorama client. 4. The system of claim 1, wherein said dioramic user interface establishes a user to machine interaction transparent to and independent of the applications exchanging data with the application interaction manager. 5. The system of claim 1, further comprising:
a user application interaction analysis engine for receiving an application output event and automatically conveying said event to the dioramic user interface. 6. The system of claim 1, further comprising:
an avatar engine configured to generate an avatar within a dioramic user interface, wherein the avatar has at least one of a physical characteristic and a personality characteristic, wherein the physical characteristic and personality characteristic is derived from a data set of an executing application and preferences of the user. 7. The system of claim 6, wherein avatar specifics for avatars utilized by said avatar engines are associated with a set of constraints, said constraints limiting behavior in manner consistent with an established persona. 8. The system of claim 6, avatars representing a famous individual having a public persona, wherein the avatars have constraints designed to keep interactions of the avatar consistent with the public personas of the represented individual. 9. The system of claim 1, further comprising:
a theme engine able to establish a plurality of settings for a dioramic user interface, wherein the settings alter the presentation and the behavior of the dioramic user interface during the application session in a manner transparent to the application without interrupting the application session. 10. The system of claim 1, further comprising:
a personality engine of the dioramic system able to receive user specific settings, wherein the user specific settings modify an avatar personality characteristic, wherein the personality characteristic is linked to an output of an executing application. 11. A method for interfacing between a human and a machine comprising:
identifying an application executing on computing equipment comprising hardware; while executing the application, generating output events and responding to input events, said output events being directed to a dioramic system, said input events coming from said dioramic system, said dioramic system comprising an application independent layer of abstraction between a user and the executing application; said dioramic system generating a dioramic user interface, which is presented to a user, wherein the dioramic user interface is tailored in accordance with user specific customizations specific to the dioramic system; said dioramic system detecting each output event, processing the output event in accordance with the user specific customizations to generate output presented within the dioramic user interface; and said dioramic system detecting user provided input, converting the user provided input in accordance with the user specific customizations to generate said input events, which are handled by said executing application, wherein specifics of said dioramic user interface resulting from the user customizations are application transparent. 12. The method of claim 11, wherein said dioramic user interface is a three dimensional interface not natively supported by the executing application. 13. The method of claim 11, further comprising:
the dioramic system establishing at least one object of said application as an avatar within the dioramic user interface, wherein said executing application lacks programmatic code for representing said at least one object as an avatar. 14. The method of claim 11, applying a personality characteristic to the avatar, wherein the personality characteristic and at least one physical characteristic is dependent upon a user specific data set of the executing application, which is represented as a different personality trait inherently comprehensible based upon at least one of a personality characteristics mapped from a data state of the executing application. 15. The method of claim 1 1, wherein a user of the dioramic system is represented as an avatar within the dioramic system interface, said dioramic system interface persisting characteristics of said avatar across boundaries of discrete computing environments. 16. The method of claim 11, wherein at least one environmental characteristic, said environmental characteristic consistent with a theme established for a diorama, which is absent in the application, said environmental characteristic varying based upon application specific data set information specific to the user or the dioramic interface. 17. The method of claim 1 1, representing a user of the dioramic user interface within the dioramic user interface as an avatar, said avatar being able to navigate a three dimensional virtual environment established by the dioramic system, said user environment comprising a plurality of other avatars and environments with which said avatar is able to interact, wherein at least at one of the other avatars or environments are specific to a different executing application, said different executing application and said application lacking programmatic linkages other than those established by said dioramic system. 18. The method of claim 11, establishing a semantic theme within the dioramic system, wherein said semantic theme represents at least one object of said application as an avatar within the dioramic user interface, wherein said executing application lacks programmatic code for representing said theme. 19. A method for interacting between a set of humans and a set of application comprising:
identifying at least one collaboration application executing in a computing space; and said application concurrently interacting with a plurality of different users in real time, each of said users utilizing a different user interface for said interactions, wherein at least one of said user interfaces comprises a dioramic user interface, wherein at least another of said user interfaces comprising an application specific interface, wherein said dioramic user interface is an application transparent interface comprising three dimensional interface independent of said application, said dioramic user interface comprising environment characteristics and avatars having characteristics derived from application specific events, which change based upon application specific events, wherein said application lacks programmatic code for the environment characteristics and said avatars. 20. The method of claim 19, further comprising:
receiving a user customization directed to the dioramic user interface, changing an environment of the dioramic user interface and a plurality of avatars during the application session in a manner transparent to the application without interrupting the application session. | The present disclosure teaches a solution for a user customizable abstraction layer for tailoring all operating system, application, and web based interfaces. The interface differs from conventional user interfaces by presenting a dynamic interface which can enable user access across all domains and applications with which the user can interact. The interface can be dynamically built as a user interacts with clients (e.g., devices/applications). Clients can utilize common usage patterns, installed application, installed themes, personal information, and the like, to create a highly customized adaptive user designed and modifiable interface.1. A dioramic system comprising:
an application interaction manager for receiving output events from a plurality of applications and for sending input event to said applications; a diorama rendering engine for dynamically generating output for a dioramic user interface from received ones of the output events in accordance with at user customizations established within the dioramic system; a user interaction manager for dynamically receiving user input from a dioramic user interface and converting in real-time said user input into said sent input events in accordance with user customizations established with in the dioramic system; and a diorama bus configured to communicatively link said application interaction manager, said diorama rendering engine, and said user interaction manager to each other, wherein said dioramic user interface is a three dimensional interface independent of said applications comprising environment characteristics and avatars having characteristics derived from application specific events, wherein each of said application interaction manager, said diorama rendering engine, and said user interaction manager comprise computer program products stored in a physical medium executable by a hardware processor. 2. The system of claim 1, wherein the dioramic system is hosted on a computing device providing the dioramic user experience for all user interaction functions and services of an operating system of the computing device, said dioramic system interfacing with the operating system by one of the following:
A) interfacing with the operating system by being embedded within the operating system software; and B) interfacing with the operating system being implemented in an independent layer co-located with the operating system. 3. The system of claim 1, wherein each of said application interaction manager, said diorama rendering engine, and said user interaction manager comprise software applications implemented within a J2EE server, said dioramic system comprising middleware executing between a remotely located application and a remotely located diorama client. 4. The system of claim 1, wherein said dioramic user interface establishes a user to machine interaction transparent to and independent of the applications exchanging data with the application interaction manager. 5. The system of claim 1, further comprising:
a user application interaction analysis engine for receiving an application output event and automatically conveying said event to the dioramic user interface. 6. The system of claim 1, further comprising:
an avatar engine configured to generate an avatar within a dioramic user interface, wherein the avatar has at least one of a physical characteristic and a personality characteristic, wherein the physical characteristic and personality characteristic is derived from a data set of an executing application and preferences of the user. 7. The system of claim 6, wherein avatar specifics for avatars utilized by said avatar engines are associated with a set of constraints, said constraints limiting behavior in manner consistent with an established persona. 8. The system of claim 6, avatars representing a famous individual having a public persona, wherein the avatars have constraints designed to keep interactions of the avatar consistent with the public personas of the represented individual. 9. The system of claim 1, further comprising:
a theme engine able to establish a plurality of settings for a dioramic user interface, wherein the settings alter the presentation and the behavior of the dioramic user interface during the application session in a manner transparent to the application without interrupting the application session. 10. The system of claim 1, further comprising:
a personality engine of the dioramic system able to receive user specific settings, wherein the user specific settings modify an avatar personality characteristic, wherein the personality characteristic is linked to an output of an executing application. 11. A method for interfacing between a human and a machine comprising:
identifying an application executing on computing equipment comprising hardware; while executing the application, generating output events and responding to input events, said output events being directed to a dioramic system, said input events coming from said dioramic system, said dioramic system comprising an application independent layer of abstraction between a user and the executing application; said dioramic system generating a dioramic user interface, which is presented to a user, wherein the dioramic user interface is tailored in accordance with user specific customizations specific to the dioramic system; said dioramic system detecting each output event, processing the output event in accordance with the user specific customizations to generate output presented within the dioramic user interface; and said dioramic system detecting user provided input, converting the user provided input in accordance with the user specific customizations to generate said input events, which are handled by said executing application, wherein specifics of said dioramic user interface resulting from the user customizations are application transparent. 12. The method of claim 11, wherein said dioramic user interface is a three dimensional interface not natively supported by the executing application. 13. The method of claim 11, further comprising:
the dioramic system establishing at least one object of said application as an avatar within the dioramic user interface, wherein said executing application lacks programmatic code for representing said at least one object as an avatar. 14. The method of claim 11, applying a personality characteristic to the avatar, wherein the personality characteristic and at least one physical characteristic is dependent upon a user specific data set of the executing application, which is represented as a different personality trait inherently comprehensible based upon at least one of a personality characteristics mapped from a data state of the executing application. 15. The method of claim 1 1, wherein a user of the dioramic system is represented as an avatar within the dioramic system interface, said dioramic system interface persisting characteristics of said avatar across boundaries of discrete computing environments. 16. The method of claim 11, wherein at least one environmental characteristic, said environmental characteristic consistent with a theme established for a diorama, which is absent in the application, said environmental characteristic varying based upon application specific data set information specific to the user or the dioramic interface. 17. The method of claim 1 1, representing a user of the dioramic user interface within the dioramic user interface as an avatar, said avatar being able to navigate a three dimensional virtual environment established by the dioramic system, said user environment comprising a plurality of other avatars and environments with which said avatar is able to interact, wherein at least at one of the other avatars or environments are specific to a different executing application, said different executing application and said application lacking programmatic linkages other than those established by said dioramic system. 18. The method of claim 11, establishing a semantic theme within the dioramic system, wherein said semantic theme represents at least one object of said application as an avatar within the dioramic user interface, wherein said executing application lacks programmatic code for representing said theme. 19. A method for interacting between a set of humans and a set of application comprising:
identifying at least one collaboration application executing in a computing space; and said application concurrently interacting with a plurality of different users in real time, each of said users utilizing a different user interface for said interactions, wherein at least one of said user interfaces comprises a dioramic user interface, wherein at least another of said user interfaces comprising an application specific interface, wherein said dioramic user interface is an application transparent interface comprising three dimensional interface independent of said application, said dioramic user interface comprising environment characteristics and avatars having characteristics derived from application specific events, which change based upon application specific events, wherein said application lacks programmatic code for the environment characteristics and said avatars. 20. The method of claim 19, further comprising:
receiving a user customization directed to the dioramic user interface, changing an environment of the dioramic user interface and a plurality of avatars during the application session in a manner transparent to the application without interrupting the application session. | 2,100 |
6,584 | 6,584 | 15,716,050 | 2,195 | Constraining memory use for overlapping virtual memory operations is described. The memory use is constrained to prevent memory from exceeding an operational threshold, e.g., in relation to operations for modifying content. These operations are implemented according to algorithms having a plurality of instructions. Before the instructions are performed in relation to the content, virtual memory is allocated to the content data, which is then loaded into the virtual memory and is also partitioned into data portions. In the context of the described techniques, at least one of the instructions affects multiple portions of the content data loaded in virtual memory. When this occurs, the instruction is carried out, in part, by transferring the multiple portions of content data between the virtual memory and a memory such that a number of portions of the content data in the memory is constrained to the memory that is reserved for the operation. | 1. In a digital medium environment to prevent memory use from exceeding an operational threshold, a method implemented by at least one computing device, the method comprising:
allocating, by the at least one computing device, virtual memory for content that is to be modified according to a content operation algorithm; loading, by the at least one computing device, data of the content into the virtual memory, the loaded data partitioned into portions; reserving, by the at least one computing device, at least some of a memory for carrying out the content operation algorithm; receiving, by the at least one computing device, an instruction in connection with carrying out the content operation algorithm, the instruction affecting a plurality of the portions; and performing, by the at least one computing device, the instruction, in part, by transferring the plurality of portions between the virtual memory and the memory such that portions in the memory are constrained to the reserved memory. 2. A method as described in claim 1, wherein a size of the reserved memory corresponds to a multiple of a portion size of the portions. 3. A method as described in claim 1, wherein a size of the reserved memory is smaller than a size of the data loaded into the virtual memory. 4. A method as described in claim 1, further comprising:
determining that transfer of a portion of the plurality of portions to the memory will not exceed the reserved memory; and responsive to the determining:
reading the portion from the virtual memory; and
writing the portion to the reserved memory. 5. A method as described in claim 1, further comprising:
determining that transfer of a first portion of the plurality of portions to the memory will exceed the reserved memory; and responsive to the determining:
reading, from the reserved memory, a second portion of the plurality of portions;
writing the second portion to the virtual memory;
reading the first portion from the virtual memory; and
writing the first portion to the reserved memory. 6. A method as described in claim 5, wherein writing the second portion to the virtual memory is effective to save modifications made to the second portion while in the reserved memory and according to the content operation algorithm. 7. A method as described in claim 1, further comprising aggregating a plurality of physical devices of the at least one computing device to form the virtual memory. 8. A method as described in claim 1, wherein the memory comprises physical memory. 9. A method as described in claim 8, wherein the physical memory comprises random-access memory (RAM). 10. A method as described in claim 1, wherein the memory comprises a second virtual memory. 11. A method as described in claim 1, further comprising partitioning the data of the content into the portions. 12. A system comprising:
a plurality of physical devices having storage for aggregation as virtual memory; at least one processor; and computer readable media having stored thereon instructions that are executable by the at least one processor to implement a virtual memory manager to perform operations comprising:
loading, into an allocated portion of the virtual memory, data of content that is to be modified according to a content operation algorithm; and
carrying out the content operation algorithm, in part, by transferring portions of the loaded data between the allocated virtual memory and a portion of memory reserved for the content operation algorithm such that the portions transferred are constrained to the reserved portion of the memory. 13. A system as described in claim 12, wherein:
the content operation algorithm includes an instruction affecting a plurality of the portions of the loaded data; and carrying out the content operation algorithm includes transferring the plurality of affected portions between the allocated virtual memory and the reserved portion of memory such that the plurality of affected portions are constrained to the reserved portion of the memory. 14. A system as described in claim 12, further comprising a housing having a form factor of a mobile phone. 15. A system as described in claim 12, further comprising a housing having a form factor of a tablet device. 16. A system as described in claim 12, wherein the operations further comprise:
allocating the portion of the virtual memory to the content that is to be modified; partitioning the data of the content into the portions; and reserving the portion of memory for the content operation algorithm. 17. A system as described in claim 12, wherein the operations further comprise determining whether transfer of a portion of the loaded data to the reserved portion of memory will exceed the reserved portion of memory, the transfer of the portion of loaded data between the allocated virtual memory and the reserved portion of memory being based on the determining. 18. A system as described in claim 17, wherein the transfer comprises writing the portion of loaded data to the reserved portion of memory based on the determining. 19. A system as described in claim 17, wherein the transfer comprises swapping the portion of loaded data with a different portion of the data in the reserved portion of memory based on the determining. 20. In a digital medium environment to prevent memory use from exceeding an operational threshold, a method implemented by at least one computing device, the method comprising:
receiving, by the at least one computing device, a request to perform a modification operation on content, the modification operation implemented according to an algorithm having a plurality of instructions; loading, by the at least one computing device, data of the content into virtual memory allocated to the content; and modifying, by the at least one computing device, the content according to the modification operation by carrying out the instructions of the algorithm, including carrying out at least one instruction of the plurality of instructions that affects multiple portions of the data in the virtual memory, the at least one instruction carried out, in part, by transferring the multiple portions between the virtual memory and a memory of the at least one computing device such that a number of the portions of the data in the memory is constrained to a portion of the memory reserved for the modification operation. | Constraining memory use for overlapping virtual memory operations is described. The memory use is constrained to prevent memory from exceeding an operational threshold, e.g., in relation to operations for modifying content. These operations are implemented according to algorithms having a plurality of instructions. Before the instructions are performed in relation to the content, virtual memory is allocated to the content data, which is then loaded into the virtual memory and is also partitioned into data portions. In the context of the described techniques, at least one of the instructions affects multiple portions of the content data loaded in virtual memory. When this occurs, the instruction is carried out, in part, by transferring the multiple portions of content data between the virtual memory and a memory such that a number of portions of the content data in the memory is constrained to the memory that is reserved for the operation.1. In a digital medium environment to prevent memory use from exceeding an operational threshold, a method implemented by at least one computing device, the method comprising:
allocating, by the at least one computing device, virtual memory for content that is to be modified according to a content operation algorithm; loading, by the at least one computing device, data of the content into the virtual memory, the loaded data partitioned into portions; reserving, by the at least one computing device, at least some of a memory for carrying out the content operation algorithm; receiving, by the at least one computing device, an instruction in connection with carrying out the content operation algorithm, the instruction affecting a plurality of the portions; and performing, by the at least one computing device, the instruction, in part, by transferring the plurality of portions between the virtual memory and the memory such that portions in the memory are constrained to the reserved memory. 2. A method as described in claim 1, wherein a size of the reserved memory corresponds to a multiple of a portion size of the portions. 3. A method as described in claim 1, wherein a size of the reserved memory is smaller than a size of the data loaded into the virtual memory. 4. A method as described in claim 1, further comprising:
determining that transfer of a portion of the plurality of portions to the memory will not exceed the reserved memory; and responsive to the determining:
reading the portion from the virtual memory; and
writing the portion to the reserved memory. 5. A method as described in claim 1, further comprising:
determining that transfer of a first portion of the plurality of portions to the memory will exceed the reserved memory; and responsive to the determining:
reading, from the reserved memory, a second portion of the plurality of portions;
writing the second portion to the virtual memory;
reading the first portion from the virtual memory; and
writing the first portion to the reserved memory. 6. A method as described in claim 5, wherein writing the second portion to the virtual memory is effective to save modifications made to the second portion while in the reserved memory and according to the content operation algorithm. 7. A method as described in claim 1, further comprising aggregating a plurality of physical devices of the at least one computing device to form the virtual memory. 8. A method as described in claim 1, wherein the memory comprises physical memory. 9. A method as described in claim 8, wherein the physical memory comprises random-access memory (RAM). 10. A method as described in claim 1, wherein the memory comprises a second virtual memory. 11. A method as described in claim 1, further comprising partitioning the data of the content into the portions. 12. A system comprising:
a plurality of physical devices having storage for aggregation as virtual memory; at least one processor; and computer readable media having stored thereon instructions that are executable by the at least one processor to implement a virtual memory manager to perform operations comprising:
loading, into an allocated portion of the virtual memory, data of content that is to be modified according to a content operation algorithm; and
carrying out the content operation algorithm, in part, by transferring portions of the loaded data between the allocated virtual memory and a portion of memory reserved for the content operation algorithm such that the portions transferred are constrained to the reserved portion of the memory. 13. A system as described in claim 12, wherein:
the content operation algorithm includes an instruction affecting a plurality of the portions of the loaded data; and carrying out the content operation algorithm includes transferring the plurality of affected portions between the allocated virtual memory and the reserved portion of memory such that the plurality of affected portions are constrained to the reserved portion of the memory. 14. A system as described in claim 12, further comprising a housing having a form factor of a mobile phone. 15. A system as described in claim 12, further comprising a housing having a form factor of a tablet device. 16. A system as described in claim 12, wherein the operations further comprise:
allocating the portion of the virtual memory to the content that is to be modified; partitioning the data of the content into the portions; and reserving the portion of memory for the content operation algorithm. 17. A system as described in claim 12, wherein the operations further comprise determining whether transfer of a portion of the loaded data to the reserved portion of memory will exceed the reserved portion of memory, the transfer of the portion of loaded data between the allocated virtual memory and the reserved portion of memory being based on the determining. 18. A system as described in claim 17, wherein the transfer comprises writing the portion of loaded data to the reserved portion of memory based on the determining. 19. A system as described in claim 17, wherein the transfer comprises swapping the portion of loaded data with a different portion of the data in the reserved portion of memory based on the determining. 20. In a digital medium environment to prevent memory use from exceeding an operational threshold, a method implemented by at least one computing device, the method comprising:
receiving, by the at least one computing device, a request to perform a modification operation on content, the modification operation implemented according to an algorithm having a plurality of instructions; loading, by the at least one computing device, data of the content into virtual memory allocated to the content; and modifying, by the at least one computing device, the content according to the modification operation by carrying out the instructions of the algorithm, including carrying out at least one instruction of the plurality of instructions that affects multiple portions of the data in the virtual memory, the at least one instruction carried out, in part, by transferring the multiple portions between the virtual memory and a memory of the at least one computing device such that a number of the portions of the data in the memory is constrained to a portion of the memory reserved for the modification operation. | 2,100 |
6,585 | 6,585 | 15,885,386 | 2,132 | Techniques are disclosed relating to provisioning fault domain sets (FDS). In some embodiments, a computer server system implements an FDS for disseminating a storage service across a plurality of fault domains. To implement the FDS, in some embodiments, the computer server system access FDS data specifying a desired state of the FDS in which the storage service is disseminated across at least a particular number of fault domains. The computer server system may determine available resources of the plurality of fault domains and determine a current state of the FDS based on fault domains that have already been provisioned to the FDS. Based on at least the desired state of the FDS, the current state of the FDS, and the available resources, the computer server system provisions one or more additional fault domains to the FDS to reconcile the FDS's current state with the FDS's desired state. | 1. A method, comprising:
implementing, by a computer server system, a fault domain set (FDS) for disseminating a storage service across a plurality of fault domains within the computer server system, wherein each of the plurality of fault domains corresponds to a set of hardware server components, wherein the implementing includes:
accessing FDS data that specifies a desired state of the FDS in which the storage service is disseminated across at least a particular number of fault domains;
determining available resources corresponding to the plurality of fault domains, wherein the available resources are usable for attaining the desired state;
determining a current state of the FDS based on ones of the plurality of fault domains that have already been provisioned to the FDS; and
based on at least the desired state of the FDS, the current state of the FDS, and the available resources, provisioning one or more additional fault domains to the FDS to reconcile the current state of the FDS with the desired state of the FDS, wherein the one or more additional fault domains facilitate implementation of the storage service. 2. The method of claim 1, wherein provisioning a fault domain by the computer server system, includes:
accessing fault domain data associated with the fault domain that specifies a desired state of the fault domain in which at least a particular amount of storage is served from the fault domain for the storage service; determining available resources corresponding to the fault domain; determining resources corresponding to the fault domain that have already been provisioned for the storage service; and based on at least the desired state of the fault domain, the already provisioned resources, and the available resources corresponding to the fault domain, provisioning one or more of the available resources for the storage service. 3. The method of claim 1, wherein the available resources include computer nodes and storage that are available for implementing the storage service, and wherein a first one of the plurality of fault domains includes a first amount of storage capacity and a second one of the plurality of fault domains includes a second, different amount of storage capacity. 4. The method of claim 1, wherein ones of the available resources are associated with an indication that specifies a fault domain to which that available resource belongs. 5. The method of claim 4, wherein determining available resources corresponding to the plurality of fault domains includes:
determining, for a given fault domain, particular ones of the available resources that belong to that fault domain based on indications corresponding to the particular available resources specifying that fault domain. 6. The method of claim 1, wherein the FDS data specifies, for the desired state of the FDS, a minimum aggregate storage capacity for the FDS. 7. The method of claim 1, wherein the FDS data specifies a status of the FDS, wherein the status is usable to determine the current state of the FDS and indicates a number of fault domains that have already been provisioned to the FDS. 8. The method of claim 7, wherein the implementing further includes:
modifying the number indicated in the status of the FDS to indicate that the one or more additional fault domains have been provisioned to the FDS. 9. A non-transitory, computer-readable medium having program instructions stored thereon that are capable of causing a computer system within a data processing center to perform operations comprising:
implementing a fault domain set (FDS) for distributing instances of an application across a plurality of fault domains within the data processing center, wherein ones of the plurality of fault domains correspond to distinct sets of one or more computer systems within the data processing center, wherein the implementing includes:
retrieving FDS data that specifies characteristics of the FDS, wherein one of the characteristics indicates that the instances of the application should be distributed across at least a particular number of fault domains;
determining available resources of the plurality of fault domains;
determining a state of the FDS based on ones of the plurality of fault domains that have already been provisioned to the FDS; and
based on at least the characteristics, the available resources, the state of the FDS, provisioning one or more of the plurality of fault domains to the FDS such that at least the particular number of fault domains is provisioned to the FDS. 10. The non-transitory, computer-readable medium of claim 9, wherein the provisioning of a fault domain includes:
retrieving fault domain data that specifies characteristics of the fault domain that include that at least a particular amount of resources of the fault domain should be provisioned to the FDS; determining available resources of the fault domain; and based on at least the characteristics of the fault domain and the available resources of the fault domain, provisioning at least the particular amount of resources from the available resources to the FDS. 11. The non-transitory, computer-readable medium of claim 9, wherein the FDS data specifies a minimum and a maximum amount of resources to be served from a single fault domain, wherein the resources include storage capacity. 12. The non-transitory, computer-readable medium of claim 9, wherein the provisioning of the at least a particular number of fault domains to the FDS includes:
associating, a given provisioned fault domain, with an identifier that indicates that the given provisioned fault domain belongs to the FDS. 13. The non-transitory, computer-readable medium of claim 9, wherein a particular one of the plurality of fault domains is associated with an identifier indicating that the particular fault domain belongs to a different FDS, wherein the determining of the available resources includes:
determining whether the different FDS referenced by the identifier has been deleted; and in response to determining that the different FDS has been deleted, determining that resources of the particular fault domain are available for provisioning to the FDS. 14. The non-transitory, computer-readable medium of claim 9, wherein the operations further comprise:
causing information describing a topology of the FDS to be displayed to a user of the data processing center, wherein the information indicates fault domains that have been provisioned to the FDS. 15. A method, comprising:
receiving, by a computer system of a data processing center, an indication that a fault domain set (FDS) has been created, wherein the indication is associated with FDS data that specifies that a storage service is to be disseminated across at least a number of a plurality of fault domains within the data processing center, and wherein each of the plurality of fault domains corresponds to a set of computer systems in the data processing center; accessing, by the computer system, the FDS data associated with the indication; determining, by the computer system, resources corresponding to the plurality of fault domains that are available for distributing the storage service; and based on at least the resources that are available and the accessed FDS data, the computer system provisioning one or more of the plurality of fault domains to the FDS such that the at least a number of fault domains is provisioned to the FDS. 16. The method of claim 15, further comprising:
determining, by the computer system, a set of fault domains that have already been provisioned to the FDS, wherein the provisioning of the one or more fault domains is based on the set of already provisioned fault domains. 17. The method of claim 15, wherein provisioning a fault domain includes assigning one or more update domains to the fault domain, wherein a given one of the assigned update domains specifies instances of the storage service that are to be updated as a group, and wherein the assigned update domains for the fault domain allow an update to the storage service to be applied without compromising availability of the storage service. 18. The method of claim 17, wherein provisioning the fault domain includes:
accessing, by the computer system, fault domain data associated with the fault domain, wherein the fault domain data specifies a maximum number of allowable instances of the storage service within an update domain; determining available resources corresponding to the fault domain; determining a number of instances of the storage service to be instantiated within the fault domain; and based on at least the available resources corresponding to the fault domain, the number of instances of the storage service to be instantiated, and the maximum number of allowable instances, assigning the one or more update domains to the fault domain. 19. The method of claim 18, wherein provisioning the fault domain further includes:
after an instance of the storage service that is instantiated on a computer system of the fault domain can access available resources of the fault domain, the computer system updating a status indication defined in the fault domain data to indicate that the storage service is accessible from the instance. 20. The method of claim 15, wherein the FDS data specifies storage volumes in the available resources, wherein the storage volumes are accessible by the storage service for storing data. | Techniques are disclosed relating to provisioning fault domain sets (FDS). In some embodiments, a computer server system implements an FDS for disseminating a storage service across a plurality of fault domains. To implement the FDS, in some embodiments, the computer server system access FDS data specifying a desired state of the FDS in which the storage service is disseminated across at least a particular number of fault domains. The computer server system may determine available resources of the plurality of fault domains and determine a current state of the FDS based on fault domains that have already been provisioned to the FDS. Based on at least the desired state of the FDS, the current state of the FDS, and the available resources, the computer server system provisions one or more additional fault domains to the FDS to reconcile the FDS's current state with the FDS's desired state.1. A method, comprising:
implementing, by a computer server system, a fault domain set (FDS) for disseminating a storage service across a plurality of fault domains within the computer server system, wherein each of the plurality of fault domains corresponds to a set of hardware server components, wherein the implementing includes:
accessing FDS data that specifies a desired state of the FDS in which the storage service is disseminated across at least a particular number of fault domains;
determining available resources corresponding to the plurality of fault domains, wherein the available resources are usable for attaining the desired state;
determining a current state of the FDS based on ones of the plurality of fault domains that have already been provisioned to the FDS; and
based on at least the desired state of the FDS, the current state of the FDS, and the available resources, provisioning one or more additional fault domains to the FDS to reconcile the current state of the FDS with the desired state of the FDS, wherein the one or more additional fault domains facilitate implementation of the storage service. 2. The method of claim 1, wherein provisioning a fault domain by the computer server system, includes:
accessing fault domain data associated with the fault domain that specifies a desired state of the fault domain in which at least a particular amount of storage is served from the fault domain for the storage service; determining available resources corresponding to the fault domain; determining resources corresponding to the fault domain that have already been provisioned for the storage service; and based on at least the desired state of the fault domain, the already provisioned resources, and the available resources corresponding to the fault domain, provisioning one or more of the available resources for the storage service. 3. The method of claim 1, wherein the available resources include computer nodes and storage that are available for implementing the storage service, and wherein a first one of the plurality of fault domains includes a first amount of storage capacity and a second one of the plurality of fault domains includes a second, different amount of storage capacity. 4. The method of claim 1, wherein ones of the available resources are associated with an indication that specifies a fault domain to which that available resource belongs. 5. The method of claim 4, wherein determining available resources corresponding to the plurality of fault domains includes:
determining, for a given fault domain, particular ones of the available resources that belong to that fault domain based on indications corresponding to the particular available resources specifying that fault domain. 6. The method of claim 1, wherein the FDS data specifies, for the desired state of the FDS, a minimum aggregate storage capacity for the FDS. 7. The method of claim 1, wherein the FDS data specifies a status of the FDS, wherein the status is usable to determine the current state of the FDS and indicates a number of fault domains that have already been provisioned to the FDS. 8. The method of claim 7, wherein the implementing further includes:
modifying the number indicated in the status of the FDS to indicate that the one or more additional fault domains have been provisioned to the FDS. 9. A non-transitory, computer-readable medium having program instructions stored thereon that are capable of causing a computer system within a data processing center to perform operations comprising:
implementing a fault domain set (FDS) for distributing instances of an application across a plurality of fault domains within the data processing center, wherein ones of the plurality of fault domains correspond to distinct sets of one or more computer systems within the data processing center, wherein the implementing includes:
retrieving FDS data that specifies characteristics of the FDS, wherein one of the characteristics indicates that the instances of the application should be distributed across at least a particular number of fault domains;
determining available resources of the plurality of fault domains;
determining a state of the FDS based on ones of the plurality of fault domains that have already been provisioned to the FDS; and
based on at least the characteristics, the available resources, the state of the FDS, provisioning one or more of the plurality of fault domains to the FDS such that at least the particular number of fault domains is provisioned to the FDS. 10. The non-transitory, computer-readable medium of claim 9, wherein the provisioning of a fault domain includes:
retrieving fault domain data that specifies characteristics of the fault domain that include that at least a particular amount of resources of the fault domain should be provisioned to the FDS; determining available resources of the fault domain; and based on at least the characteristics of the fault domain and the available resources of the fault domain, provisioning at least the particular amount of resources from the available resources to the FDS. 11. The non-transitory, computer-readable medium of claim 9, wherein the FDS data specifies a minimum and a maximum amount of resources to be served from a single fault domain, wherein the resources include storage capacity. 12. The non-transitory, computer-readable medium of claim 9, wherein the provisioning of the at least a particular number of fault domains to the FDS includes:
associating, a given provisioned fault domain, with an identifier that indicates that the given provisioned fault domain belongs to the FDS. 13. The non-transitory, computer-readable medium of claim 9, wherein a particular one of the plurality of fault domains is associated with an identifier indicating that the particular fault domain belongs to a different FDS, wherein the determining of the available resources includes:
determining whether the different FDS referenced by the identifier has been deleted; and in response to determining that the different FDS has been deleted, determining that resources of the particular fault domain are available for provisioning to the FDS. 14. The non-transitory, computer-readable medium of claim 9, wherein the operations further comprise:
causing information describing a topology of the FDS to be displayed to a user of the data processing center, wherein the information indicates fault domains that have been provisioned to the FDS. 15. A method, comprising:
receiving, by a computer system of a data processing center, an indication that a fault domain set (FDS) has been created, wherein the indication is associated with FDS data that specifies that a storage service is to be disseminated across at least a number of a plurality of fault domains within the data processing center, and wherein each of the plurality of fault domains corresponds to a set of computer systems in the data processing center; accessing, by the computer system, the FDS data associated with the indication; determining, by the computer system, resources corresponding to the plurality of fault domains that are available for distributing the storage service; and based on at least the resources that are available and the accessed FDS data, the computer system provisioning one or more of the plurality of fault domains to the FDS such that the at least a number of fault domains is provisioned to the FDS. 16. The method of claim 15, further comprising:
determining, by the computer system, a set of fault domains that have already been provisioned to the FDS, wherein the provisioning of the one or more fault domains is based on the set of already provisioned fault domains. 17. The method of claim 15, wherein provisioning a fault domain includes assigning one or more update domains to the fault domain, wherein a given one of the assigned update domains specifies instances of the storage service that are to be updated as a group, and wherein the assigned update domains for the fault domain allow an update to the storage service to be applied without compromising availability of the storage service. 18. The method of claim 17, wherein provisioning the fault domain includes:
accessing, by the computer system, fault domain data associated with the fault domain, wherein the fault domain data specifies a maximum number of allowable instances of the storage service within an update domain; determining available resources corresponding to the fault domain; determining a number of instances of the storage service to be instantiated within the fault domain; and based on at least the available resources corresponding to the fault domain, the number of instances of the storage service to be instantiated, and the maximum number of allowable instances, assigning the one or more update domains to the fault domain. 19. The method of claim 18, wherein provisioning the fault domain further includes:
after an instance of the storage service that is instantiated on a computer system of the fault domain can access available resources of the fault domain, the computer system updating a status indication defined in the fault domain data to indicate that the storage service is accessible from the instance. 20. The method of claim 15, wherein the FDS data specifies storage volumes in the available resources, wherein the storage volumes are accessible by the storage service for storing data. | 2,100 |
6,586 | 6,586 | 16,186,348 | 2,143 | A system for determining relevant information based on user interactions may include a processor configured to receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more application including applications local to the device that are stored in the memory and applications external to the device. The processor may be further configured to provide, using a machine learning (ML) model, a relevance score for each of one or more user interface (UI) elements based on each of the features. The processor may be further configured to sort one or more UI elements based on a ranking of the relevance scores. The processor may be further configured to provide, as output, the one or more UI elements based at least in part on the ranking. | 1. A device, comprising:
a memory; and at least one processor configured to:
receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more applications including applications local to the device that are stored in the memory and applications external to the device;
provide, using a machine learning (ML) model, a relevance score for each of one or more user interface (UI) elements based on each of the features, wherein the relevance score is based at least in part on weights assigned to features based on the user activity and respective variance values of the features;
sort one or more UI elements based on a ranking of the relevance scores; and
provide, as output, the one or more UI elements based at least in part on the ranking. 2. The device of claim 1, wherein the relevance score is based at least in part on a sum of respective Gaussian curves. 3. The device of claim 1, wherein the relevance score is further based on a value indicating a likelihood that a user will click on or tap a particular UI element. 4. The device of claim 1, wherein a high variance value of a first feature indicates a low confidence associated with the first feature, and a low variance value of a second feature indicates a high confidence associated with the second feature, wherein the first feature is assigned a greater weight than the second feature for providing the relevance score. 5. The device of claim 1, wherein the features include a signal based on a location or time. 6. The device of claim 1, wherein the application data is provided by the application using one or more application programming interfaces. 7. The device of claim 1, wherein the weights assigned to features are adjusted over time as new application data related to user activity is received. 8. The device of claim 1, wherein the features are included in different groups. 9. The device of claim 8, wherein the different groups include a group of features that are shared across the applications and a second group of features that are specific to a particular application. 10. The device of claim 8, wherein the device comprises a wearable electronic device and each UI element is provided for display by the wearable electronic device in accordance with the ranking, and wherein the each UI element corresponds to a watch face graphical element. 11. A method comprising:
receiving application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more applications including applications local to a device and applications external to the device; providing, using a machine learning (ML) model, a relevance score for each of one or more user interface (UI) elements based on each of the features, wherein the relevance score is based at least in part on weights assigned to features based on the user activity and respective variance values of the features; sorting one or more UI elements based on a ranking of the relevance scores; and providing, as output, the one or more UI elements based at least in part on the ranking. 12. A computer program product comprising code stored in a non-transitory computer-readable storage medium, the code comprising:
code to receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more applications including applications local to a device and applications external to the device; code to provide, using a machine learning (ML) model, a relevance score for each of one or more user interface (UI) elements based on each of the features, wherein the relevance score is based at least in part on weights assigned to features based on the user activity and respective variance values of the features; code to sort one or more UI elements based on a ranking of the relevance scores; and code to provide, as output, the one or more UI elements based at least in part on the ranking. | A system for determining relevant information based on user interactions may include a processor configured to receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more application including applications local to the device that are stored in the memory and applications external to the device. The processor may be further configured to provide, using a machine learning (ML) model, a relevance score for each of one or more user interface (UI) elements based on each of the features. The processor may be further configured to sort one or more UI elements based on a ranking of the relevance scores. The processor may be further configured to provide, as output, the one or more UI elements based at least in part on the ranking.1. A device, comprising:
a memory; and at least one processor configured to:
receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more applications including applications local to the device that are stored in the memory and applications external to the device;
provide, using a machine learning (ML) model, a relevance score for each of one or more user interface (UI) elements based on each of the features, wherein the relevance score is based at least in part on weights assigned to features based on the user activity and respective variance values of the features;
sort one or more UI elements based on a ranking of the relevance scores; and
provide, as output, the one or more UI elements based at least in part on the ranking. 2. The device of claim 1, wherein the relevance score is based at least in part on a sum of respective Gaussian curves. 3. The device of claim 1, wherein the relevance score is further based on a value indicating a likelihood that a user will click on or tap a particular UI element. 4. The device of claim 1, wherein a high variance value of a first feature indicates a low confidence associated with the first feature, and a low variance value of a second feature indicates a high confidence associated with the second feature, wherein the first feature is assigned a greater weight than the second feature for providing the relevance score. 5. The device of claim 1, wherein the features include a signal based on a location or time. 6. The device of claim 1, wherein the application data is provided by the application using one or more application programming interfaces. 7. The device of claim 1, wherein the weights assigned to features are adjusted over time as new application data related to user activity is received. 8. The device of claim 1, wherein the features are included in different groups. 9. The device of claim 8, wherein the different groups include a group of features that are shared across the applications and a second group of features that are specific to a particular application. 10. The device of claim 8, wherein the device comprises a wearable electronic device and each UI element is provided for display by the wearable electronic device in accordance with the ranking, and wherein the each UI element corresponds to a watch face graphical element. 11. A method comprising:
receiving application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more applications including applications local to a device and applications external to the device; providing, using a machine learning (ML) model, a relevance score for each of one or more user interface (UI) elements based on each of the features, wherein the relevance score is based at least in part on weights assigned to features based on the user activity and respective variance values of the features; sorting one or more UI elements based on a ranking of the relevance scores; and providing, as output, the one or more UI elements based at least in part on the ranking. 12. A computer program product comprising code stored in a non-transitory computer-readable storage medium, the code comprising:
code to receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more applications including applications local to a device and applications external to the device; code to provide, using a machine learning (ML) model, a relevance score for each of one or more user interface (UI) elements based on each of the features, wherein the relevance score is based at least in part on weights assigned to features based on the user activity and respective variance values of the features; code to sort one or more UI elements based on a ranking of the relevance scores; and code to provide, as output, the one or more UI elements based at least in part on the ranking. | 2,100 |
6,587 | 6,587 | 15,032,583 | 2,192 | A predefined hierarchical service tree can be stored that includes a top at a service category definition level and a bottom at a level of a number of devices, each of the number of devices selected to perform a specific service function. A sequential progression can be enforced through the predefined hierarchical service tree to perform a service. | 1. A non-transitory machine-readable medium storing instructions executable by a processing resource to:
store a predefined hierarchical service tree that comprises a top at a service category definition level and a bottom at a level of a number of devices, each of the number of devices selected to perform a specific service function; and enforce a sequential progression through the predefined hierarchical service tree to perform a service. 2. The medium of claim 1, wherein the predefined hierarchical service tree comprises an actual service level that defines a specific service, the actual service level one level below the service category definition level. 3. The medium of claim 2, wherein the predefined hierarchical service tree comprises a service component level that defines a number of components usable to perform the specific service, the service component level one level below the actual service level. 4. The medium of claim 3, wherein the predefined hierarchical service tree comprises a system element level that defines a functionality of each of the number of devices usable by at least one of the number of components, the system element level one level below the service component level. 5. The medium of claim 4, wherein each of the number of devices connect to the predefined hierarchical service tree through the system element level. 6. A system to provide hierarchical service trees, comprising a processing resource in communication with a non-transitory machine readable medium having instructions executed by the processing resource to implement:
storage of a number of predefined hierarchical service trees that each comprises a top at a service category definition level and a bottom at a level of a number of devices; storage of a number of actual services at an actual services level one level below the service category definition level, wherein each actual service defines a specific service; storage of a number of service components at a service component level one level below the actual services level, wherein each service component defines a number of components usable to perform a specific service; and a containment engine to restrict at least one actual service to containment in a service category definition and to enable at least one service component to containment in a first actual service in a first predefined hierarchical service tree and a second actual service in a second predefined hierarchical service tree. 7. The system of claim 6, comprising a usage engine to allow at least one usage link between the first actual service and the second actual service. 8. The system of claim 6, comprising a usage engine to allow a usage link from a service component to at least one actual service. 9. The system of claim 6, comprising a dependency engine to track containment and usage link dependencies in the first predefined hierarchical service tree. 10. The system of claim 6, comprising a dependency engine to track containment and usage link dependencies between the first predefined hierarchical service tree and the second predefined hierarchical service tree. 11. A method for implementing hierarchical service trees, comprising:
accessing a number of predefined hierarchical service trees that each comprises a number of levels with a service category definition at a top level of a hierarchy and a number of devices at a bottom level of the hierarchy; enabling a first containment link from a first instance to a second instance in a next lower level of the hierarchy and preventing a second containment link from the first instance to a third instance in a same, level of the hierarchy, wherein a containment link defines a dependency between instances in the hierarchy; and enabling a usage link from the first instance to the third instance in the same level of the hierarchy, wherein the usage link defines a functional relationship between instances in a first predefined hierarchical service tree and a second predefined hierarchical service tree. 12. The method of claim 11, comprising storing an actual service level one level below the service category definition level, the actual service level defining specific services, wherein the same level of the hierarchy is the actual service level. 13. The method of claim 12, comprising enabling a service component level stored one level below the actual service level to have a number of containment links to instances in a system element level and to have a number of usage links to instances in the actual service level, the service component level defining a number of components usable to perform the specific service. 14. The method of claim 13, comprising enabling the system element level stored one level below the service component level to have a number of containment links to the number of devices at the bottom level of the hierarchy, the system element level defining a functionality of each of the number of devices. 15. The method of claim 11, comprising designing a service to use the enabled containment links and the enabled usage links to enforce a progression through each level of at least one predefined hierarchical service tree. | A predefined hierarchical service tree can be stored that includes a top at a service category definition level and a bottom at a level of a number of devices, each of the number of devices selected to perform a specific service function. A sequential progression can be enforced through the predefined hierarchical service tree to perform a service.1. A non-transitory machine-readable medium storing instructions executable by a processing resource to:
store a predefined hierarchical service tree that comprises a top at a service category definition level and a bottom at a level of a number of devices, each of the number of devices selected to perform a specific service function; and enforce a sequential progression through the predefined hierarchical service tree to perform a service. 2. The medium of claim 1, wherein the predefined hierarchical service tree comprises an actual service level that defines a specific service, the actual service level one level below the service category definition level. 3. The medium of claim 2, wherein the predefined hierarchical service tree comprises a service component level that defines a number of components usable to perform the specific service, the service component level one level below the actual service level. 4. The medium of claim 3, wherein the predefined hierarchical service tree comprises a system element level that defines a functionality of each of the number of devices usable by at least one of the number of components, the system element level one level below the service component level. 5. The medium of claim 4, wherein each of the number of devices connect to the predefined hierarchical service tree through the system element level. 6. A system to provide hierarchical service trees, comprising a processing resource in communication with a non-transitory machine readable medium having instructions executed by the processing resource to implement:
storage of a number of predefined hierarchical service trees that each comprises a top at a service category definition level and a bottom at a level of a number of devices; storage of a number of actual services at an actual services level one level below the service category definition level, wherein each actual service defines a specific service; storage of a number of service components at a service component level one level below the actual services level, wherein each service component defines a number of components usable to perform a specific service; and a containment engine to restrict at least one actual service to containment in a service category definition and to enable at least one service component to containment in a first actual service in a first predefined hierarchical service tree and a second actual service in a second predefined hierarchical service tree. 7. The system of claim 6, comprising a usage engine to allow at least one usage link between the first actual service and the second actual service. 8. The system of claim 6, comprising a usage engine to allow a usage link from a service component to at least one actual service. 9. The system of claim 6, comprising a dependency engine to track containment and usage link dependencies in the first predefined hierarchical service tree. 10. The system of claim 6, comprising a dependency engine to track containment and usage link dependencies between the first predefined hierarchical service tree and the second predefined hierarchical service tree. 11. A method for implementing hierarchical service trees, comprising:
accessing a number of predefined hierarchical service trees that each comprises a number of levels with a service category definition at a top level of a hierarchy and a number of devices at a bottom level of the hierarchy; enabling a first containment link from a first instance to a second instance in a next lower level of the hierarchy and preventing a second containment link from the first instance to a third instance in a same, level of the hierarchy, wherein a containment link defines a dependency between instances in the hierarchy; and enabling a usage link from the first instance to the third instance in the same level of the hierarchy, wherein the usage link defines a functional relationship between instances in a first predefined hierarchical service tree and a second predefined hierarchical service tree. 12. The method of claim 11, comprising storing an actual service level one level below the service category definition level, the actual service level defining specific services, wherein the same level of the hierarchy is the actual service level. 13. The method of claim 12, comprising enabling a service component level stored one level below the actual service level to have a number of containment links to instances in a system element level and to have a number of usage links to instances in the actual service level, the service component level defining a number of components usable to perform the specific service. 14. The method of claim 13, comprising enabling the system element level stored one level below the service component level to have a number of containment links to the number of devices at the bottom level of the hierarchy, the system element level defining a functionality of each of the number of devices. 15. The method of claim 11, comprising designing a service to use the enabled containment links and the enabled usage links to enforce a progression through each level of at least one predefined hierarchical service tree. | 2,100 |
6,588 | 6,588 | 15,822,246 | 2,175 | A computer implemented method of editing attributes of data records presented through GUI elements by a webpage, comprising using one or more processors of a client terminal hosting a web browser for executing a code for parsing a webpage rendered by the web browser to extract identifier information of one or more GUI elements presented in the webpage, the GUI elements presenting a value of one or more attributes of a data record extracted from a database according to the identifier information. The GUI elements are presented in a non-editable area, identifying a user selection indicative of the GUI elements, rendering an editing GUI element for editing the value, extracting a user input received from a user using the editing GUI element and forwarding to a server hosting the webpage instructions to update the value in the data record according to the user input. | 1. A computer implemented method of editing attributes of data records presented through GUI elements by a webpage, comprising:
using at least one processor of a client terminal hosting a web browser for executing a code for:
parsing a webpage rendered by said web browser to extract identifier information of at least one GUI element presented in said webpage, said at least one GUI element presenting a value of at least one attribute of a data record extracted from a database according to said identifier information, said at least one GUI element is presented in a non-editable area;
identifying a user selection indicative of said at least one GUI element;
rendering an editing GUI element for editing said value;
extracting a user input received from a user using said editing GUI element; and
forwarding to a server hosting said webpage instructions to update said value in said data record according to said user input. 2. The computer implemented method of claim 1, wherein said identifier information is extracted using an Application Programming Interface (API) of said application. 3. The computer implemented method of claim 1, wherein said identifier information is extracted by rendering at least one other webpage loaded invisibly to said user on said GUI. 4. The computer implemented method of claim 1, wherein said identifier information is extracted according to pre-defined identifier information. 5. The computer implemented method of claim 1, wherein said editing GUI element is rendered according to a permission attribute value indicating an access privilege value for said at least one attribute. 6. The computer implemented method of claim 1, wherein said instructions are forwarded to said server using an Application Programming Interface (API) of said application. 7. The computer implemented method of claim 1, wherein said instructions are forwarded to said server by updating said value in at least one other webpage loaded invisibly to said user on said GUI. 8. The computer implemented method of claim 1, wherein said at least one GUI element is marked to indicate to said user that said at least one attribute is editable. 9. The computer implemented method of claim 1, further comprising auto-completing of a text inserted by said user using said editing GUI element. 10. The computer implemented method of claim 1, further comprising presenting a completion indication to said user after said instructions are forward to said server. 11. The computer implemented method of claim 1, further comprising marking said at least one GUI element in case said value of said at least one attribute complies with at least one conditional rule. 12. The computer implemented method of claim 1, further comprises rendering said editing GUI element to receive said user input for editing said value of said at least one attribute for multiple data records such as said data record presented by respective GUI elements in said webpage. 13. The computer implemented method of claim 1, wherein said editing GUI element further comprising a restore field for restoring said updated value to said value as set prior to said edit, said value as set prior to said edit is stored in an event log. 14. The computer implemented method of claim 1, wherein said editing GUI element further comprising a delete field for deleting said data record in case said identifier information identifies said data record as allowed for deletion. 15. The computer implemented method of claim 1, wherein said editing GUI element further comprising a duplicate field for duplicating said data record in case said identifier information identifies said data record as allowed for duplication. 16. The computer implemented method of claim 1, wherein said editing GUI element further comprising an add field for adding a new data record such as said data record in case said identifier information identifies that said new data record is allowed to be added. 17. The computer implemented method of claim 1, wherein said editing GUI element further comprising presenting additional information for said data record in response to at least one additional action of said user interaction. 18. A system for editing attributes of data records presented through GUI elements by a webpage, comprising:
at least one processor of a client terminal, which is configured for hosting a web browser; and a program store configured to store program code for execution by said at least one processor, said code comprising: code instructions to parse a webpage rendered by said web browser to extract identifier information of at least one GUI element presented in said webpage, said at least one GUI element presenting a value of at least one attribute of a data record extracted from a database according to said identifier information, said at least one GUI element is presented in a non-editable area; code instructions to identify a user selection indicative of said at least one GUI element; code instructions to render an editing GUI element for editing said value; code instructions to extract a user input received from a user using said editing GUI element; and code instructions to forward to a server hosting said webpage instructions to update said value in said data record according to said user input. 19. A computer program product, comprising a non-transitory computer-readable medium in which program code is stored for execution by a computer, said program code comprising:
code instructions to parse a webpage rendered by said web browser to extract identifier information of at least one GUI element presented in said webpage, said at least one GUI element presenting a value of at least one attribute of a data record extracted from a database according to said identifier information, said at least one GUI element is presented in a non-editable area; code instructions to identify a user selection indicative of said at least one GUI element; code instructions to render an editing GUI element for editing said value; code instructions to extract a user input received from a user using said editing GUI element; and code instructions to forward to a server hosting said webpage instructions to update said value in said data record according to said user input. 20. A computer implemented method of editing attributes of data records presented through GUI elements displayed by an application, comprising:
using at least one processor of a client terminal for executing a code for: parsing an application page displaying user context to extract identifier information of at least one GUI element presented in said application page, said at least one GUI element presenting a value of at least one attribute of a data record extracted from a database according to said identifier information, said at least one GUI element is presented in a non-editable area; identifying a user selection indicative of said at least one GUI element; rendering an editing GUI element for editing said value; extracting a user input received from a user using said editing GUI element; and instructing said application to update said value in said data record according to said user input. 21. The computer implemented method of claim 20, wherein said application is a member of a group consisting of: a local application executed by said client terminal and a web application executed by a remote server accessible from said client terminal over at least one network. | A computer implemented method of editing attributes of data records presented through GUI elements by a webpage, comprising using one or more processors of a client terminal hosting a web browser for executing a code for parsing a webpage rendered by the web browser to extract identifier information of one or more GUI elements presented in the webpage, the GUI elements presenting a value of one or more attributes of a data record extracted from a database according to the identifier information. The GUI elements are presented in a non-editable area, identifying a user selection indicative of the GUI elements, rendering an editing GUI element for editing the value, extracting a user input received from a user using the editing GUI element and forwarding to a server hosting the webpage instructions to update the value in the data record according to the user input.1. A computer implemented method of editing attributes of data records presented through GUI elements by a webpage, comprising:
using at least one processor of a client terminal hosting a web browser for executing a code for:
parsing a webpage rendered by said web browser to extract identifier information of at least one GUI element presented in said webpage, said at least one GUI element presenting a value of at least one attribute of a data record extracted from a database according to said identifier information, said at least one GUI element is presented in a non-editable area;
identifying a user selection indicative of said at least one GUI element;
rendering an editing GUI element for editing said value;
extracting a user input received from a user using said editing GUI element; and
forwarding to a server hosting said webpage instructions to update said value in said data record according to said user input. 2. The computer implemented method of claim 1, wherein said identifier information is extracted using an Application Programming Interface (API) of said application. 3. The computer implemented method of claim 1, wherein said identifier information is extracted by rendering at least one other webpage loaded invisibly to said user on said GUI. 4. The computer implemented method of claim 1, wherein said identifier information is extracted according to pre-defined identifier information. 5. The computer implemented method of claim 1, wherein said editing GUI element is rendered according to a permission attribute value indicating an access privilege value for said at least one attribute. 6. The computer implemented method of claim 1, wherein said instructions are forwarded to said server using an Application Programming Interface (API) of said application. 7. The computer implemented method of claim 1, wherein said instructions are forwarded to said server by updating said value in at least one other webpage loaded invisibly to said user on said GUI. 8. The computer implemented method of claim 1, wherein said at least one GUI element is marked to indicate to said user that said at least one attribute is editable. 9. The computer implemented method of claim 1, further comprising auto-completing of a text inserted by said user using said editing GUI element. 10. The computer implemented method of claim 1, further comprising presenting a completion indication to said user after said instructions are forward to said server. 11. The computer implemented method of claim 1, further comprising marking said at least one GUI element in case said value of said at least one attribute complies with at least one conditional rule. 12. The computer implemented method of claim 1, further comprises rendering said editing GUI element to receive said user input for editing said value of said at least one attribute for multiple data records such as said data record presented by respective GUI elements in said webpage. 13. The computer implemented method of claim 1, wherein said editing GUI element further comprising a restore field for restoring said updated value to said value as set prior to said edit, said value as set prior to said edit is stored in an event log. 14. The computer implemented method of claim 1, wherein said editing GUI element further comprising a delete field for deleting said data record in case said identifier information identifies said data record as allowed for deletion. 15. The computer implemented method of claim 1, wherein said editing GUI element further comprising a duplicate field for duplicating said data record in case said identifier information identifies said data record as allowed for duplication. 16. The computer implemented method of claim 1, wherein said editing GUI element further comprising an add field for adding a new data record such as said data record in case said identifier information identifies that said new data record is allowed to be added. 17. The computer implemented method of claim 1, wherein said editing GUI element further comprising presenting additional information for said data record in response to at least one additional action of said user interaction. 18. A system for editing attributes of data records presented through GUI elements by a webpage, comprising:
at least one processor of a client terminal, which is configured for hosting a web browser; and a program store configured to store program code for execution by said at least one processor, said code comprising: code instructions to parse a webpage rendered by said web browser to extract identifier information of at least one GUI element presented in said webpage, said at least one GUI element presenting a value of at least one attribute of a data record extracted from a database according to said identifier information, said at least one GUI element is presented in a non-editable area; code instructions to identify a user selection indicative of said at least one GUI element; code instructions to render an editing GUI element for editing said value; code instructions to extract a user input received from a user using said editing GUI element; and code instructions to forward to a server hosting said webpage instructions to update said value in said data record according to said user input. 19. A computer program product, comprising a non-transitory computer-readable medium in which program code is stored for execution by a computer, said program code comprising:
code instructions to parse a webpage rendered by said web browser to extract identifier information of at least one GUI element presented in said webpage, said at least one GUI element presenting a value of at least one attribute of a data record extracted from a database according to said identifier information, said at least one GUI element is presented in a non-editable area; code instructions to identify a user selection indicative of said at least one GUI element; code instructions to render an editing GUI element for editing said value; code instructions to extract a user input received from a user using said editing GUI element; and code instructions to forward to a server hosting said webpage instructions to update said value in said data record according to said user input. 20. A computer implemented method of editing attributes of data records presented through GUI elements displayed by an application, comprising:
using at least one processor of a client terminal for executing a code for: parsing an application page displaying user context to extract identifier information of at least one GUI element presented in said application page, said at least one GUI element presenting a value of at least one attribute of a data record extracted from a database according to said identifier information, said at least one GUI element is presented in a non-editable area; identifying a user selection indicative of said at least one GUI element; rendering an editing GUI element for editing said value; extracting a user input received from a user using said editing GUI element; and instructing said application to update said value in said data record according to said user input. 21. The computer implemented method of claim 20, wherein said application is a member of a group consisting of: a local application executed by said client terminal and a web application executed by a remote server accessible from said client terminal over at least one network. | 2,100 |
6,589 | 6,589 | 15,685,801 | 2,167 | The current document is directed a resource-exchange system that facilitates resource exchange and sharing among computing facilities. The currently disclosed methods and systems employ efficient, distributed-search methods and subsystems within distributed computer systems that include large numbers of geographically distributed data centers to locate resource-provider computing facilities that match the resource needs of resource-consumer computing-facilities based on attribute values associated with the needed resources, the resource providers, and the resource consumers. The resource-exchange system monitors and controls resource exchanges on behalf of participants in the resource-exchange system in order to optimize resource usage within participant data centers and computing facilities. Virtual machines that provide the execution environment for multi-tiered applications described by hierarchically organized multi-tiered-application specifications are automatically distributed across one or more resource-provider-computing-facility hosts by the resource-exchange system. | 1. An automated resource-exchange system comprising:
multiple resource-exchange-system participants, each comprising a computing facility that includes multiple computers, each having one or more processors and one or more memories, and a local cloud-exchange instance; and a cloud-exchange system that is implemented on one or more physical computers, each including one or more processors and one or more memories, and that includes a cloud-exchange engine, the cloud-exchange system automatically placing virtual machines of a multi-tiered application for which remote hosting is requested by a resource-consumer resource-exchange-system participant into one or more resource-provider resource-exchange-system participants. 2. The automated resource-exchange system of claim 1 wherein the cloud-exchange system automatically places virtual machines of a multi-tiered application for which remote hosting is requested into one or more resource-provider resource-exchange-system participants by:
receiving a hosting request from the resource-consumer resource-exchange-system participant;
extracting one of a multi-tiered-application specification and a reference to a multi-tiered-application specification from the hosting request;
parsing the multi-tiered-application specification to identify groups of one or more multi-tiered-application virtual machines with equivalent hosting constraints;
generating a search expression for each identified virtual-machine group;
submitting each search expression to a distributed-search-engine component of the cloud-exchange system to obtain scored candidate host assignments for the virtual-machine group for which the search expression was generated;
selecting a set of candidate host assignments for the multi-tiered-application virtual machines with a lowest cumulative score; and
launching execution of the multi-tiered-application according to the selected set of candidate host assignments. 3. The automated resource-exchange system of claim 2 wherein the multi-tiered-application specification is encoded in a hierarchical data-encoding language according to a multi-tiered-application-specification standard. 4. The automated resource-exchange system of claim 2 wherein the hosting request may additionally contain one of a buy policy and a reference to a buy policy. 5. The automated resource-exchange system of claim 3 wherein generating a search expression for an identified virtual-machine group further comprises:
parsing the multi-tiered-application specification and, if included in the hosting request, a buy policy to identify
a general set of hosting constraints without dependencies on other virtual machines of other identified virtual-machine groups, and
a dependent set of hosting constraints that additionally include dependencies on other virtual machines of other identified virtual-machine groups; and
combining the general set of hosting constraints, requirements, and parameters and the dependent set of hosting constraints, requirements, and parameters into a search expression for the virtual-machine group; 6. The automated resource-exchange system of claim 2 wherein submitting a search expression to a distributed-search-engine component of the cloud-exchange system to obtain scored candidate host assignments for a virtual-machine group for which the search expression was generated further comprises:
submitting a general set of hosting constraints included in the search expression to the distributed-search-engine component of the cloud-exchange system to obtain a set of scored candidate host assignments; and
iteratively selecting, for each virtual machine in the virtual-machine group, members of a final set of candidate host assignments, one for each virtual machine in the virtual-machine group, according to a dependent set of hosting constraints included in the search expression. 7. The automated resource-exchange system of claim 2 wherein hosting constraints include:
affinity requirements;
network latency requirements;
operational parameters;
cost-center assignments;
service-level-agreement requirements;
compliance and regulatory requirements;
price filters;
connectivity requirements;
infrastructure-support requirements;
security requirements;
reputational requirements; resource-exchange certification requirements;
network-bandwidth requirements;
uptime requirements;
white-list/black-list filters;
logical-switch constraints,
routing-constraints;
firewall constraints;
load-balancer constraints; and
hosting-location constraints. 8. The automated resource-exchange system of claim 2 wherein the virtual-machine groups are sorted in descending order according to the degree to which they are constrained with respect to placement for hosting. 9. The automated resource-exchange system of claim 8 wherein search expressions for the virtual-machine groups are submitted to a distributed-search-engine component according to the sorted order. 10. The automated resource-exchange system of claim 8 wherein search expressions for the virtual-machine groups are submitted in a depth-first, recursive search of a subset of the possible virtual-machine-to-host assignments. 11. The automated resource-exchange system of claim 2 wherein launching execution of the multi-tiered-application according to the selected set of candidate host assignments further comprises:
invoking a multi-tiered-application orchestrator to configure and launch the multi-tiered application according to the multi-tiered-application specification and the selected set of candidate host assignments for the multi-tiered-application virtual machines. 12. A method that increases an operational efficiency of multiple computing facilities, the method comprising:
aggregating the multiple computing facilities into a resource-exchange system, each computing facility including multiple computers, each computer having one or more processors and one or more memories, by
transforming each computing facility into a resource-exchange-system participant by including a local cloud-exchange instance in the computing facility, and
including, in the resource-exchange system, a cloud-exchange system, implemented on one or more physical computers, each including one or more processors and one or more memories, the cloud-exchange system including a cloud-exchange engine; and
increasing the operational efficiency of the resource-exchange system by automatically placing virtual machines of a multi-tiered application for which remote hosting is requested by a resource-consumer resource-exchange-system participant into one or more resource-provider resource-exchange-system participants. 13. The method of claim 12 wherein the cloud-exchange system automatically places virtual machines of a multi-tiered application for which remote hosting is requested into one or more resource-provider resource-exchange-system participants by:
receiving a hosting request from the resource-consumer resource-exchange-system participant;
extracting one of a multi-tiered-application specification and a reference to a multi-tiered-application specification from the hosting request;
parsing the multi-tiered-application specification to identify groups of one or more multi-tiered-application virtual machines with equivalent hosting constraints;
generating a search expression for each identified virtual-machine group;
submitting each search expression to a distributed-search-engine component of the cloud-exchange system to obtain scored candidate host assignments for the virtual-machine group for which the search expression was generated;
selecting a set of candidate host assignments for the multi-tiered-application virtual machines with a lowest cumulative score; and
launching execution of the multi-tiered-application according to the selected set of candidate host assignments. 14. The method of claim 13 wherein the multi-tiered-application specification is encoded in a hierarchical data-encoding language according to a multi-tiered-application-specification standard. 15. The method of claim 13 wherein generating a search expression for an identified virtual-machine group further comprises:
parsing the multi-tiered-application specification and, if included in the hosting request, a buy policy to identify
a general set of hosting constraints without dependencies on other virtual machines of other identified virtual-machine groups, and
a dependent set of hosting constraints that additionally include dependencies on other virtual machines of other identified virtual-machine groups; and
combining the general set of hosting constraints, requirements, and parameters and the dependent set of hosting constraints, requirements, and parameters into a search expression for the virtual-machine group; 16. The method of claim 13 wherein submitting a search expression to a distributed-search-engine component of the cloud-exchange system to obtain scored candidate host assignments for a virtual-machine group for which the search expression was generated further comprises:
submitting a general set of hosting constraints included in the search expression to the distributed-search-engine component of the cloud-exchange system to obtain a set of scored candidate host assignments; and
iteratively selecting, for each virtual machine in the virtual-machine group, members of a final set of candidate host assignments, one for each virtual machine in the virtual-machine group, according to a dependent set of hosting constraints included in the search expression. 17. The method of claim 13 wherein hosting constraints include:
affinity requirements;
network latency requirements;
operational parameters;
cost-center assignments;
service-level-agreement requirements;
compliance and regulatory requirements;
price filters;
connectivity requirements;
infrastructure-support requirements;
security requirements;
reputational requirements; resource-exchange certification requirements;
network-bandwidth requirements;
uptime requirements;
white-list/black-list filters;
logical-switch constraints,
routing-constraints;
firewall constraints;
load-balancer constraints; and
hosting-location constraints. 18. The method of claim 13 wherein the virtual-machine groups are sorted in descending order according to the degree to which they are constrained with respect to placement for hosting. 19. The method of claim 18 wherein search expressions for the virtual-machine groups are submitted to a distributed-search-engine component according to the sorted order. 20. The method of claim 19 wherein search expressions for the virtual-machine groups are submitted in a depth-first, recursive search of a subset of the possible virtual-machine-to-host assignments. 21. The method of claim 13 wherein launching execution of the multi-tiered-application according to the selected set of candidate host assignments further comprises:
invoking a multi-tiered-application orchestrator to configure and launch the multi-tiered application according to the multi-tiered-application specification and the selected set of candidate host assignments for the multi-tiered-application virtual machines. 22. A physical data-storage device encoded with computer instructions that, when executed by processors within an automated resource-exchange system comprising resource-exchange-system-participant computing facilities and a cloud-exchange system, control the automated resource-exchange system to automatically increase the operational efficiency of the resource-exchange system by:
aggregating the multiple computing facilities into a resource-exchange system, each computing facility including multiple computers, each computer having one or more processors and one or more memories, by
transforming each computing facility into a resource-exchange-system participant by including a local cloud-exchange instance in the computing facility, and
including, in the resource-exchange system, a cloud-exchange system, implemented on one or more physical computers, each including one or more processors and one or more memories, the cloud-exchange system including a cloud-exchange engine; and
increasing the operational efficiency of the resource-exchange system by automatically placing virtual machines of a multi-tiered application for which remote hosting is requested by a resource-consumer resource-exchange-system participant into one or more resource-provider resource-exchange-system participants. | The current document is directed a resource-exchange system that facilitates resource exchange and sharing among computing facilities. The currently disclosed methods and systems employ efficient, distributed-search methods and subsystems within distributed computer systems that include large numbers of geographically distributed data centers to locate resource-provider computing facilities that match the resource needs of resource-consumer computing-facilities based on attribute values associated with the needed resources, the resource providers, and the resource consumers. The resource-exchange system monitors and controls resource exchanges on behalf of participants in the resource-exchange system in order to optimize resource usage within participant data centers and computing facilities. Virtual machines that provide the execution environment for multi-tiered applications described by hierarchically organized multi-tiered-application specifications are automatically distributed across one or more resource-provider-computing-facility hosts by the resource-exchange system.1. An automated resource-exchange system comprising:
multiple resource-exchange-system participants, each comprising a computing facility that includes multiple computers, each having one or more processors and one or more memories, and a local cloud-exchange instance; and a cloud-exchange system that is implemented on one or more physical computers, each including one or more processors and one or more memories, and that includes a cloud-exchange engine, the cloud-exchange system automatically placing virtual machines of a multi-tiered application for which remote hosting is requested by a resource-consumer resource-exchange-system participant into one or more resource-provider resource-exchange-system participants. 2. The automated resource-exchange system of claim 1 wherein the cloud-exchange system automatically places virtual machines of a multi-tiered application for which remote hosting is requested into one or more resource-provider resource-exchange-system participants by:
receiving a hosting request from the resource-consumer resource-exchange-system participant;
extracting one of a multi-tiered-application specification and a reference to a multi-tiered-application specification from the hosting request;
parsing the multi-tiered-application specification to identify groups of one or more multi-tiered-application virtual machines with equivalent hosting constraints;
generating a search expression for each identified virtual-machine group;
submitting each search expression to a distributed-search-engine component of the cloud-exchange system to obtain scored candidate host assignments for the virtual-machine group for which the search expression was generated;
selecting a set of candidate host assignments for the multi-tiered-application virtual machines with a lowest cumulative score; and
launching execution of the multi-tiered-application according to the selected set of candidate host assignments. 3. The automated resource-exchange system of claim 2 wherein the multi-tiered-application specification is encoded in a hierarchical data-encoding language according to a multi-tiered-application-specification standard. 4. The automated resource-exchange system of claim 2 wherein the hosting request may additionally contain one of a buy policy and a reference to a buy policy. 5. The automated resource-exchange system of claim 3 wherein generating a search expression for an identified virtual-machine group further comprises:
parsing the multi-tiered-application specification and, if included in the hosting request, a buy policy to identify
a general set of hosting constraints without dependencies on other virtual machines of other identified virtual-machine groups, and
a dependent set of hosting constraints that additionally include dependencies on other virtual machines of other identified virtual-machine groups; and
combining the general set of hosting constraints, requirements, and parameters and the dependent set of hosting constraints, requirements, and parameters into a search expression for the virtual-machine group; 6. The automated resource-exchange system of claim 2 wherein submitting a search expression to a distributed-search-engine component of the cloud-exchange system to obtain scored candidate host assignments for a virtual-machine group for which the search expression was generated further comprises:
submitting a general set of hosting constraints included in the search expression to the distributed-search-engine component of the cloud-exchange system to obtain a set of scored candidate host assignments; and
iteratively selecting, for each virtual machine in the virtual-machine group, members of a final set of candidate host assignments, one for each virtual machine in the virtual-machine group, according to a dependent set of hosting constraints included in the search expression. 7. The automated resource-exchange system of claim 2 wherein hosting constraints include:
affinity requirements;
network latency requirements;
operational parameters;
cost-center assignments;
service-level-agreement requirements;
compliance and regulatory requirements;
price filters;
connectivity requirements;
infrastructure-support requirements;
security requirements;
reputational requirements; resource-exchange certification requirements;
network-bandwidth requirements;
uptime requirements;
white-list/black-list filters;
logical-switch constraints,
routing-constraints;
firewall constraints;
load-balancer constraints; and
hosting-location constraints. 8. The automated resource-exchange system of claim 2 wherein the virtual-machine groups are sorted in descending order according to the degree to which they are constrained with respect to placement for hosting. 9. The automated resource-exchange system of claim 8 wherein search expressions for the virtual-machine groups are submitted to a distributed-search-engine component according to the sorted order. 10. The automated resource-exchange system of claim 8 wherein search expressions for the virtual-machine groups are submitted in a depth-first, recursive search of a subset of the possible virtual-machine-to-host assignments. 11. The automated resource-exchange system of claim 2 wherein launching execution of the multi-tiered-application according to the selected set of candidate host assignments further comprises:
invoking a multi-tiered-application orchestrator to configure and launch the multi-tiered application according to the multi-tiered-application specification and the selected set of candidate host assignments for the multi-tiered-application virtual machines. 12. A method that increases an operational efficiency of multiple computing facilities, the method comprising:
aggregating the multiple computing facilities into a resource-exchange system, each computing facility including multiple computers, each computer having one or more processors and one or more memories, by
transforming each computing facility into a resource-exchange-system participant by including a local cloud-exchange instance in the computing facility, and
including, in the resource-exchange system, a cloud-exchange system, implemented on one or more physical computers, each including one or more processors and one or more memories, the cloud-exchange system including a cloud-exchange engine; and
increasing the operational efficiency of the resource-exchange system by automatically placing virtual machines of a multi-tiered application for which remote hosting is requested by a resource-consumer resource-exchange-system participant into one or more resource-provider resource-exchange-system participants. 13. The method of claim 12 wherein the cloud-exchange system automatically places virtual machines of a multi-tiered application for which remote hosting is requested into one or more resource-provider resource-exchange-system participants by:
receiving a hosting request from the resource-consumer resource-exchange-system participant;
extracting one of a multi-tiered-application specification and a reference to a multi-tiered-application specification from the hosting request;
parsing the multi-tiered-application specification to identify groups of one or more multi-tiered-application virtual machines with equivalent hosting constraints;
generating a search expression for each identified virtual-machine group;
submitting each search expression to a distributed-search-engine component of the cloud-exchange system to obtain scored candidate host assignments for the virtual-machine group for which the search expression was generated;
selecting a set of candidate host assignments for the multi-tiered-application virtual machines with a lowest cumulative score; and
launching execution of the multi-tiered-application according to the selected set of candidate host assignments. 14. The method of claim 13 wherein the multi-tiered-application specification is encoded in a hierarchical data-encoding language according to a multi-tiered-application-specification standard. 15. The method of claim 13 wherein generating a search expression for an identified virtual-machine group further comprises:
parsing the multi-tiered-application specification and, if included in the hosting request, a buy policy to identify
a general set of hosting constraints without dependencies on other virtual machines of other identified virtual-machine groups, and
a dependent set of hosting constraints that additionally include dependencies on other virtual machines of other identified virtual-machine groups; and
combining the general set of hosting constraints, requirements, and parameters and the dependent set of hosting constraints, requirements, and parameters into a search expression for the virtual-machine group; 16. The method of claim 13 wherein submitting a search expression to a distributed-search-engine component of the cloud-exchange system to obtain scored candidate host assignments for a virtual-machine group for which the search expression was generated further comprises:
submitting a general set of hosting constraints included in the search expression to the distributed-search-engine component of the cloud-exchange system to obtain a set of scored candidate host assignments; and
iteratively selecting, for each virtual machine in the virtual-machine group, members of a final set of candidate host assignments, one for each virtual machine in the virtual-machine group, according to a dependent set of hosting constraints included in the search expression. 17. The method of claim 13 wherein hosting constraints include:
affinity requirements;
network latency requirements;
operational parameters;
cost-center assignments;
service-level-agreement requirements;
compliance and regulatory requirements;
price filters;
connectivity requirements;
infrastructure-support requirements;
security requirements;
reputational requirements; resource-exchange certification requirements;
network-bandwidth requirements;
uptime requirements;
white-list/black-list filters;
logical-switch constraints,
routing-constraints;
firewall constraints;
load-balancer constraints; and
hosting-location constraints. 18. The method of claim 13 wherein the virtual-machine groups are sorted in descending order according to the degree to which they are constrained with respect to placement for hosting. 19. The method of claim 18 wherein search expressions for the virtual-machine groups are submitted to a distributed-search-engine component according to the sorted order. 20. The method of claim 19 wherein search expressions for the virtual-machine groups are submitted in a depth-first, recursive search of a subset of the possible virtual-machine-to-host assignments. 21. The method of claim 13 wherein launching execution of the multi-tiered-application according to the selected set of candidate host assignments further comprises:
invoking a multi-tiered-application orchestrator to configure and launch the multi-tiered application according to the multi-tiered-application specification and the selected set of candidate host assignments for the multi-tiered-application virtual machines. 22. A physical data-storage device encoded with computer instructions that, when executed by processors within an automated resource-exchange system comprising resource-exchange-system-participant computing facilities and a cloud-exchange system, control the automated resource-exchange system to automatically increase the operational efficiency of the resource-exchange system by:
aggregating the multiple computing facilities into a resource-exchange system, each computing facility including multiple computers, each computer having one or more processors and one or more memories, by
transforming each computing facility into a resource-exchange-system participant by including a local cloud-exchange instance in the computing facility, and
including, in the resource-exchange system, a cloud-exchange system, implemented on one or more physical computers, each including one or more processors and one or more memories, the cloud-exchange system including a cloud-exchange engine; and
increasing the operational efficiency of the resource-exchange system by automatically placing virtual machines of a multi-tiered application for which remote hosting is requested by a resource-consumer resource-exchange-system participant into one or more resource-provider resource-exchange-system participants. | 2,100 |
6,590 | 6,590 | 15,197,552 | 2,195 | A managed object of a virtualized computing environment, which contains the runtime state of a parent virtual machine (VM) and can be placed in any host of the virtualized computing environment, is used for instantly cloning child VMs off that managed object. The managed object is not an executable object (i.e., the state of the managed object is static) and thus it does not require most of the overhead memory associated with a VM. As a result, this managed object can support instant cloning of VMs with a reduction in memory, storage, and CPU overhead relative to when a parent template VM is used. | 1. In a virtualized computing environment having a host computer in which managed objects of the virtualized computing environment are provisioned, the managed objects including a first executable object loaded into memory of the host computer and executing on a processor of the host computer and a non-executable object, a method of provisioning a second executable object from the non-executable object, said method comprising the steps of:
suspending execution of the first executable object, and while suspended, capturing a snapshot of a runtime state of the first executable object; creating the non-executable object from the captured snapshot, wherein the non-executable object contains the runtime state of the first executable object and is an object of the virtualized computing environment that is separately managed from the first executable object; and provisioning the second executable object from the non-executable object to restore the runtime state of the first executable object in the second executable object. 2. The method of claim 1, wherein the non-executable object is maintained in the memory of the host computer and persisted in a storage device of the host computer. 3. The method of claim 2, further comprising:
copying the non-executable object in memory of another host computer or in another storage device. 4. The method of claim 2, wherein the non-executable object is maintained in the memory of the host computer and memory space allocated to the non-executable object is reclaimable. 5. The method of claim 1, wherein the first executable object is a virtual machine and the runtime state of the first executable object includes memory pages of the virtual computing instance, a mapping between guest physical memory page numbers of the virtual machine and machine memory pages numbers of the host computer, and state of devices of the virtual machine. 6. The method of claim 1, wherein the second executable object is provisioned in the same host computer as the first executable object. 7. The method of claim 1, further comprising:
loading the non-executable object into a memory of another host computer of the virtualized computing environment, wherein the second executable object is provisioned in said another host computer. 8. A non-transitory computer readable medium comprising instructions carried out by a host computer of a virtualized computing environment, in which managed objects of the virtualized computing environment are provisioned, the managed objects including a first executable object loaded into memory of the host computer and executing on a processor of the host computer and a non-executable object, wherein the instructions when executed in the processor of the host computer carries out a method of provisioning a second executable object from the non-executable object, said method comprising the steps of:
suspending execution of the first executable object, and while suspended, capturing a snapshot of a runtime state of the first executable object; creating the non-executable object from the captured snapshot, wherein the non-executable object contains the runtime state of the first executable object and is an object of the virtualized computing environment that is separately managed from the first executable object; and provisioning the second executable object from the non-executable object to restore the runtime state of the first executable object in the second executable object. 9. The non-transitory computer readable medium of claim 8, wherein the non-executable object is maintained in the memory of the host computer and persisted in a storage device of the host computer. 10. The non-transitory computer readable medium of claim 9, wherein the method further comprises:
copying the non-executable object in memory of another host computer or in another storage device. 11. The non-transitory computer readable medium of claim 8, wherein the non-executable object is maintained in the memory of the host computer and memory space allocated to the non-executable object is reclaimable. 12. The non-transitory computer readable medium of claim 8, wherein the first executable object is a virtual machine and the runtime state of the first executable object includes memory pages of the virtual computing instance, a mapping between guest physical memory page numbers of the virtual machine and machine memory pages numbers of the host computer, and state of devices of the virtual machine. 13. The non-transitory computer readable medium of claim 8, wherein the second executable object is provisioned in the same host computer as the first executable object. 14. The non-transitory computer readable medium of claim 8, wherein the method further comprises:
loading the non-executable object into a memory of another host computer of the virtualized computing environment, wherein a third executable object is provisioned from the non-executable object in said another host computer. 15. A virtualized computing environment comprising a cluster of host computers, including a first host computer and a second host computer, in which managed objects of the virtualized computing environment are provisioned, the managed objects including a first executable object loaded into memory of the first host computer and executing on a processor of the first host computer and a non-executable object, wherein the processor of the first host computer is programmed to carry out a method of provisioning a second executable object from the non-executable object, said method comprising the steps of:
suspending execution of the first executable object, and while suspended, capturing a snapshot of a runtime state of the first executable object; creating the non-executable object from the captured snapshot, wherein the non-executable object contains the runtime state of the first executable object and is an object of the virtualized computing environment that is separately managed from the first executable object; and provisioning the second executable object from the non-executable object to restore the runtime state of the first executable object in the second executable object. 16. The virtualized computing environment of claim 15, wherein the non-executable object is maintained in the memory of the host computer and persisted in a storage device of the host computer. 17. The virtualized computing environment of claim 16, wherein the method further comprises:
copying the non-executable object in memory of another host computer or in another storage device. 18. The virtualized computing environment of claim 15, wherein the first executable object is a virtual machine and the runtime state of the first executable object includes memory pages of the virtual computing instance, a mapping between guest physical memory page numbers of the virtual machine and machine memory pages numbers of the host computer, and state of devices of the virtual machine. 19. The virtualized computing environment of claim 15, wherein the method further comprises:
loading the non-executable object into a memory of another host computer of the virtualized computing environment, wherein the second executable object is provisioned in said another host computer. 20. The virtualized computing environment of claim 15, wherein the non-executable object is a cluster-level entity and is managed by a distributed resource scheduler (DRS) component running in a virtual machine management server, the DRS component placing the non-executable object in a particular host computer in the cluster based on: (i) whether an image of the non-executable object is accessible to the particular host computer; (ii) memory required to be reserved for the non-executable object; (iii) computational cost for instantiating the non-executable object; and (iv) computational cost for migrating the non-executable object. | A managed object of a virtualized computing environment, which contains the runtime state of a parent virtual machine (VM) and can be placed in any host of the virtualized computing environment, is used for instantly cloning child VMs off that managed object. The managed object is not an executable object (i.e., the state of the managed object is static) and thus it does not require most of the overhead memory associated with a VM. As a result, this managed object can support instant cloning of VMs with a reduction in memory, storage, and CPU overhead relative to when a parent template VM is used.1. In a virtualized computing environment having a host computer in which managed objects of the virtualized computing environment are provisioned, the managed objects including a first executable object loaded into memory of the host computer and executing on a processor of the host computer and a non-executable object, a method of provisioning a second executable object from the non-executable object, said method comprising the steps of:
suspending execution of the first executable object, and while suspended, capturing a snapshot of a runtime state of the first executable object; creating the non-executable object from the captured snapshot, wherein the non-executable object contains the runtime state of the first executable object and is an object of the virtualized computing environment that is separately managed from the first executable object; and provisioning the second executable object from the non-executable object to restore the runtime state of the first executable object in the second executable object. 2. The method of claim 1, wherein the non-executable object is maintained in the memory of the host computer and persisted in a storage device of the host computer. 3. The method of claim 2, further comprising:
copying the non-executable object in memory of another host computer or in another storage device. 4. The method of claim 2, wherein the non-executable object is maintained in the memory of the host computer and memory space allocated to the non-executable object is reclaimable. 5. The method of claim 1, wherein the first executable object is a virtual machine and the runtime state of the first executable object includes memory pages of the virtual computing instance, a mapping between guest physical memory page numbers of the virtual machine and machine memory pages numbers of the host computer, and state of devices of the virtual machine. 6. The method of claim 1, wherein the second executable object is provisioned in the same host computer as the first executable object. 7. The method of claim 1, further comprising:
loading the non-executable object into a memory of another host computer of the virtualized computing environment, wherein the second executable object is provisioned in said another host computer. 8. A non-transitory computer readable medium comprising instructions carried out by a host computer of a virtualized computing environment, in which managed objects of the virtualized computing environment are provisioned, the managed objects including a first executable object loaded into memory of the host computer and executing on a processor of the host computer and a non-executable object, wherein the instructions when executed in the processor of the host computer carries out a method of provisioning a second executable object from the non-executable object, said method comprising the steps of:
suspending execution of the first executable object, and while suspended, capturing a snapshot of a runtime state of the first executable object; creating the non-executable object from the captured snapshot, wherein the non-executable object contains the runtime state of the first executable object and is an object of the virtualized computing environment that is separately managed from the first executable object; and provisioning the second executable object from the non-executable object to restore the runtime state of the first executable object in the second executable object. 9. The non-transitory computer readable medium of claim 8, wherein the non-executable object is maintained in the memory of the host computer and persisted in a storage device of the host computer. 10. The non-transitory computer readable medium of claim 9, wherein the method further comprises:
copying the non-executable object in memory of another host computer or in another storage device. 11. The non-transitory computer readable medium of claim 8, wherein the non-executable object is maintained in the memory of the host computer and memory space allocated to the non-executable object is reclaimable. 12. The non-transitory computer readable medium of claim 8, wherein the first executable object is a virtual machine and the runtime state of the first executable object includes memory pages of the virtual computing instance, a mapping between guest physical memory page numbers of the virtual machine and machine memory pages numbers of the host computer, and state of devices of the virtual machine. 13. The non-transitory computer readable medium of claim 8, wherein the second executable object is provisioned in the same host computer as the first executable object. 14. The non-transitory computer readable medium of claim 8, wherein the method further comprises:
loading the non-executable object into a memory of another host computer of the virtualized computing environment, wherein a third executable object is provisioned from the non-executable object in said another host computer. 15. A virtualized computing environment comprising a cluster of host computers, including a first host computer and a second host computer, in which managed objects of the virtualized computing environment are provisioned, the managed objects including a first executable object loaded into memory of the first host computer and executing on a processor of the first host computer and a non-executable object, wherein the processor of the first host computer is programmed to carry out a method of provisioning a second executable object from the non-executable object, said method comprising the steps of:
suspending execution of the first executable object, and while suspended, capturing a snapshot of a runtime state of the first executable object; creating the non-executable object from the captured snapshot, wherein the non-executable object contains the runtime state of the first executable object and is an object of the virtualized computing environment that is separately managed from the first executable object; and provisioning the second executable object from the non-executable object to restore the runtime state of the first executable object in the second executable object. 16. The virtualized computing environment of claim 15, wherein the non-executable object is maintained in the memory of the host computer and persisted in a storage device of the host computer. 17. The virtualized computing environment of claim 16, wherein the method further comprises:
copying the non-executable object in memory of another host computer or in another storage device. 18. The virtualized computing environment of claim 15, wherein the first executable object is a virtual machine and the runtime state of the first executable object includes memory pages of the virtual computing instance, a mapping between guest physical memory page numbers of the virtual machine and machine memory pages numbers of the host computer, and state of devices of the virtual machine. 19. The virtualized computing environment of claim 15, wherein the method further comprises:
loading the non-executable object into a memory of another host computer of the virtualized computing environment, wherein the second executable object is provisioned in said another host computer. 20. The virtualized computing environment of claim 15, wherein the non-executable object is a cluster-level entity and is managed by a distributed resource scheduler (DRS) component running in a virtual machine management server, the DRS component placing the non-executable object in a particular host computer in the cluster based on: (i) whether an image of the non-executable object is accessible to the particular host computer; (ii) memory required to be reserved for the non-executable object; (iii) computational cost for instantiating the non-executable object; and (iv) computational cost for migrating the non-executable object. | 2,100 |
6,591 | 6,591 | 15,677,496 | 2,163 | A method and system for caching concept structures in a cache memory of a vehicle control system of an autonomous vehicle. The method includes collecting driving data generated by at least one sensor of the autonomous vehicle, wherein the driving data includes at least a location pointer of the autonomous vehicle; retrieving at least one concept structure that matches the collected at least one location pointer, wherein each retrieved concept structure includes metadata describing a concept of a driving decision; and storing the retrieved at least one concept structure in the cache memory. | 1. A method for caching concept structures in a cache memory of a vehicle control system of an autonomous vehicle, comprising:
collecting driving data generated by at least one sensor of the autonomous vehicle, wherein the driving data includes at least a location pointer of the autonomous vehicle; retrieving at least one concept structure that matches the collected at least one location pointer, wherein each retrieved concept structure includes metadata describing a concept of a driving decision; and storing the retrieved at least one concept structure in the cache memory. 2. The method of claim 1, wherein vehicle control system is configured to determine automated driving decisions for the autonomous vehicle based on the cached at least one concept structure. 3. The method of claim 2, wherein the vehicle control system is configured to determine the automated driving decisions based further on the metadata of the cached at least one concept structure and metadata of at least one multimedia content element captured by sensors of the autonomous vehicle. 4. The method of claim 1, wherein the matching at least one concept structure is retrieved from a deep content classification (DCC) system, the DCC system storing a plurality of concept structures, each concept structure further including a collection of signatures generated based on multimedia data elements. 5. The method of claim 4, wherein the matching at least one concept structure is retrieved from the DCC system based on at least one signature generated for the driving data and the collections of signatures of the plurality of concept structures stored in the DCC system. 6. The method of claim 5, further comprising:
sending, to a signature generator system, at least a portion of the driving data, wherein the signature generator system is configured to generate the at least one signature for the driving data based on the sent at least a portion of the driving data. 7. The method of claim 6, wherein the signature generator system includes a plurality of at least statistically independent computational cores, wherein the properties of each core are set independently of the properties of each other core. 8. The method of claim 5, wherein the DCC system is configured to compare the at least one signature generated for the driving data to the collection of signatures of each concept structure, wherein the collection of signatures of each matching concept structure matches the at least one signature generated for the driving data above a predetermined threshold. 9. A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process for caching concept structures in a cache memory of a vehicle control system of an autonomous vehicle, the process comprising:
collecting driving data generated by at least one sensor of the autonomous vehicle, wherein the driving data includes at least a location pointer of the autonomous vehicle; retrieving at least one concept structure that matches the collected at least one location pointer, wherein each retrieved concept structure includes metadata describing a concept of a driving decision; and storing the retrieved at least one concept structure in the cache memory. 10. A system for caching concept structures in a cache memory of a vehicle control system of an autonomous vehicle, comprising:
a processing circuitry; and a memory connected to the processing circuitry, the memory containing instructions that, when executed by the processing circuitry, configure the system to: collect driving data generated by at least one sensor of the autonomous vehicle, wherein the driving data includes at least a location pointer of the autonomous vehicle; retrieve at least one concept structure that matches the collected at least one location pointer, wherein each retrieved concept structure includes metadata describing a concept of a driving decision; and store the retrieved at least one concept structure in the cache memory. 11. The system of claim 10, wherein vehicle control system is configured to determine automated driving decisions for the autonomous vehicle based on the cached at least one concept structure. 12. The system of claim 11, wherein the vehicle control system is configured to determine the automated driving decisions based further on the metadata of the cached at least one concept structure and metadata of at least one multimedia content element captured by sensors of the autonomous vehicle. 13. The system of claim 10, wherein the matching at least one concept structure is retrieved from a deep content classification (DCC) system, the DCC system storing a plurality of concept structures, each concept structure further including a collection of signatures generated based on multimedia data elements. 14. The system of claim 13, wherein the matching at least one concept structure is retrieved from the DCC system based on at least one signature generated for the driving data and the collections of signatures of the plurality of concept structures stored in the DCC system. 15. The system of claim 14, wherein the system is further configured to:
send, to a signature generator system, at least a portion of the driving data, wherein the signature generator system is configured to generate the at least one signature for the driving data based on the sent at least a portion of the driving data. 16. The system of claim 14, wherein the signature generator system includes a plurality of at least statistically independent computational cores, wherein the properties of each core are set independently of the properties of each other core. 17. The system of claim 13, wherein the DCC system is configured to compare the at least one signature generated for the driving data to the collection of signatures of each concept structure, wherein the collection of signatures of each matching concept structure matches the at least one signature generated for the driving data above a predetermined threshold. 18. The system of claim 10, wherein the system is the vehicle control system. | A method and system for caching concept structures in a cache memory of a vehicle control system of an autonomous vehicle. The method includes collecting driving data generated by at least one sensor of the autonomous vehicle, wherein the driving data includes at least a location pointer of the autonomous vehicle; retrieving at least one concept structure that matches the collected at least one location pointer, wherein each retrieved concept structure includes metadata describing a concept of a driving decision; and storing the retrieved at least one concept structure in the cache memory.1. A method for caching concept structures in a cache memory of a vehicle control system of an autonomous vehicle, comprising:
collecting driving data generated by at least one sensor of the autonomous vehicle, wherein the driving data includes at least a location pointer of the autonomous vehicle; retrieving at least one concept structure that matches the collected at least one location pointer, wherein each retrieved concept structure includes metadata describing a concept of a driving decision; and storing the retrieved at least one concept structure in the cache memory. 2. The method of claim 1, wherein vehicle control system is configured to determine automated driving decisions for the autonomous vehicle based on the cached at least one concept structure. 3. The method of claim 2, wherein the vehicle control system is configured to determine the automated driving decisions based further on the metadata of the cached at least one concept structure and metadata of at least one multimedia content element captured by sensors of the autonomous vehicle. 4. The method of claim 1, wherein the matching at least one concept structure is retrieved from a deep content classification (DCC) system, the DCC system storing a plurality of concept structures, each concept structure further including a collection of signatures generated based on multimedia data elements. 5. The method of claim 4, wherein the matching at least one concept structure is retrieved from the DCC system based on at least one signature generated for the driving data and the collections of signatures of the plurality of concept structures stored in the DCC system. 6. The method of claim 5, further comprising:
sending, to a signature generator system, at least a portion of the driving data, wherein the signature generator system is configured to generate the at least one signature for the driving data based on the sent at least a portion of the driving data. 7. The method of claim 6, wherein the signature generator system includes a plurality of at least statistically independent computational cores, wherein the properties of each core are set independently of the properties of each other core. 8. The method of claim 5, wherein the DCC system is configured to compare the at least one signature generated for the driving data to the collection of signatures of each concept structure, wherein the collection of signatures of each matching concept structure matches the at least one signature generated for the driving data above a predetermined threshold. 9. A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process for caching concept structures in a cache memory of a vehicle control system of an autonomous vehicle, the process comprising:
collecting driving data generated by at least one sensor of the autonomous vehicle, wherein the driving data includes at least a location pointer of the autonomous vehicle; retrieving at least one concept structure that matches the collected at least one location pointer, wherein each retrieved concept structure includes metadata describing a concept of a driving decision; and storing the retrieved at least one concept structure in the cache memory. 10. A system for caching concept structures in a cache memory of a vehicle control system of an autonomous vehicle, comprising:
a processing circuitry; and a memory connected to the processing circuitry, the memory containing instructions that, when executed by the processing circuitry, configure the system to: collect driving data generated by at least one sensor of the autonomous vehicle, wherein the driving data includes at least a location pointer of the autonomous vehicle; retrieve at least one concept structure that matches the collected at least one location pointer, wherein each retrieved concept structure includes metadata describing a concept of a driving decision; and store the retrieved at least one concept structure in the cache memory. 11. The system of claim 10, wherein vehicle control system is configured to determine automated driving decisions for the autonomous vehicle based on the cached at least one concept structure. 12. The system of claim 11, wherein the vehicle control system is configured to determine the automated driving decisions based further on the metadata of the cached at least one concept structure and metadata of at least one multimedia content element captured by sensors of the autonomous vehicle. 13. The system of claim 10, wherein the matching at least one concept structure is retrieved from a deep content classification (DCC) system, the DCC system storing a plurality of concept structures, each concept structure further including a collection of signatures generated based on multimedia data elements. 14. The system of claim 13, wherein the matching at least one concept structure is retrieved from the DCC system based on at least one signature generated for the driving data and the collections of signatures of the plurality of concept structures stored in the DCC system. 15. The system of claim 14, wherein the system is further configured to:
send, to a signature generator system, at least a portion of the driving data, wherein the signature generator system is configured to generate the at least one signature for the driving data based on the sent at least a portion of the driving data. 16. The system of claim 14, wherein the signature generator system includes a plurality of at least statistically independent computational cores, wherein the properties of each core are set independently of the properties of each other core. 17. The system of claim 13, wherein the DCC system is configured to compare the at least one signature generated for the driving data to the collection of signatures of each concept structure, wherein the collection of signatures of each matching concept structure matches the at least one signature generated for the driving data above a predetermined threshold. 18. The system of claim 10, wherein the system is the vehicle control system. | 2,100 |
6,592 | 6,592 | 13,230,831 | 2,152 | Making an information retrieval process public, so that it can be followed by others, allows capturing of an interest graph that allows people to learn more about shared interests with other people. This also allows items of interest to a trusted resource (such as an expert) to be identified. These items can then be brought to the attention of other users that share the same interest as the expert. In addition, by keeping track of what particular content a user has already seen, the system can bring items of interest to the user's attention, where the user has not yet seen those items. | 1. A computer-implemented method of presenting content to a user in a search system that has a computer with a processor, the method comprising:
identifying, with the processor, a trusted resource for a given subject matter area; identifying, with the processor, that the user has a subject matter area of interest that matches the given subject matter area of the trusted resource; identifying, with the processor, seen content that the user has already interacted with in the search system; identifying, with the processor, unseen content of interest in the given subject matter area, that the trusted resource has interacted with, and that the user has not already interacted with; and generating a user interface display presenting the unseen content of interest to the user, indicating that the user has not yet interacted with the unseen content of interest, and indicating that the trusted resource has interacted with the unseen content of interest. 2. The computer-implemented method of claim 1 wherein identifying the trusted resource, comprises:
receiving, from a given user, inputs indicative of interactions with content;
identifying a subject matter area of the content interacted with by the given user;
determining a level of knowledge of the given user in the subject matter area of the content, based on a linguistic content of the inputs from the given user; and
if the level of knowledge of the given user in the subject matter area of the content meets a threshold level, then identifying the given user as a trusted resource in the subject matter area of the content. 3. The computer-implemented method of claim 2 wherein receiving inputs indicative of interactions with content comprises:
receiving queries in a public search system. 4. The computer-implemented method of claim 1 wherein identifying seen content, comprises:
receiving user interaction inputs indicative of a user interacting with different items of content; and
storing the user interaction inputs to generate a store of seen content for the user. 5. The computer-implemented method of claim 4 wherein receiving user interaction inputs, comprises:
displaying posts in a public stream of the search system, for the user, as the different items of content;
receiving user click inputs indicative of a user clicking on, liking, or commenting on, the posts; and
generating a click index of the click inputs for the user, wherein storing the user interaction inputs comprises storing the click index. 6. The computer-implemented method of claim 5 wherein identifying unseen content of interest, comprises:
comparing an identification of content of interest that the trusted resource has interacted with to the click inputs in the click index for the user to identify whether the user has interacted with the content of interest that the trusted resource has interacted with. 7. The computer-implemented method of claim 1 and further comprising:
identifying content in the given subject matter area that the trusted resource has interacted with by identifying content authored by the trusted resource within the search system. 8. The computer-implemented method of claim 1 and further comprising:
identifying content in the given subject matter area that the trusted resource has interacted with by identifying content the trusted resource has interacted with on a third party site. 9. The computer-implemented method of claim 1 wherein the search system comprises a public search system in which public streams are generated for the user and the trusted resource, each public stream having posts therein, and further comprising:
receiving an input by the trusted resource indicative of the trusted resource interacting with a post in the public stream of the trusted resource; and
identifying content in the post as content that the trusted resource interacted with. 10. The computer-implemented method of claim 9 wherein receiving an input by the trusted resource indicative of the trusted resource interacting with a post in the public stream comprises:
receiving the input by the trusted resource as an indication that the trusted resource has authored, liked or commented on the post. 11. The computer-implemented method of claim 1 wherein generating a user interface display comprises:
receiving a query, requesting information in the given subject matter area, from the user;
generating search results responsive to the query; and
generating the user interface display visually identifying certain ones of the search results as unseen content of interest. 12. The computer-implemented method of claim 1 wherein the search system displays selectable elements representing subject matter areas of interest to the user, including the given subject matter area, and wherein generating a user interface display comprises:
receiving a user selection of the selectable element representing the given subject matter area; and
generating the user interface display showing the unseen content of interest for the given subject matter area represented by the selectable element selected by the user. 13. The computer-implemented method of claim 1 wherein the search system comprises a public search system that displays a public search stream to the user having posts therein, and wherein generating the user interface display comprises:
generating the user interface as a post to the public stream of the user. 14. A public search system, comprising:
a user interface component receiving user inputs indicative of user queries and user interactions with content generated by the public search system; a search component that receives queries input by a user, searches a data store and returns results responsive to the queries; an interest tracking component identifying topics of interest to the user an unseen content of interest tracking component that tracks, comprising:
a trusted resource identifier identifying respective trusted resources in each of the identified topics of interest;
a new content identifier identifying new content that the trusted resources interacted with in their respective topic of interest; and
a seen results data store storing information indicative of search results that the user has interacted with, the unseen content of interest tracking component comparing the new content to the information in the seen results data store to determine whether the user has already interacted with the new content, to obtain a set of unseen content of interest for the user, and generating a user interface display at the user interface component displaying the unseen content of interest and an indication of why the unseen content of interest is being displayed; and
a computer processor being a functional component of the system and activated by the interest tracking component and the unseen content of interest tracking component to facilitate identifying the topics of interest, the trusted resources and the unseen content of interest. 15. The public search system of claim 14 and further comprising:
a topic feed generator that generates a public stream that has posts that include the user queries and results, the new content identifier identifying, as new content, items in the posts of the public stream of a trusted resource that the trusted resource has interacted with. 16. The public search system of claim 15 wherein the new content identifier identifies, as new content, search results returned in response to a trusted resource query submitted by the trusted resource and that the trusted resource selected for viewing. 17. The public search system of claim 14 wherein the unseen content of interest tracking component generates the user interface display, in response to receiving a user query related to the unseen content of interest, the user interface display visually emphasizing the unseen content of interest and textually identifying the trusted resource that interacted with the unseen content of interest. 18. A computer-implemented method of providing information to a user in a public search system, comprising:
identifying a trusted resource for a given subject matter of interest based on interactions of the trusted resource with the search system in the given subject matter; storing query progressions of the trusted resource for queries submitted by the trusted resource relating to the given subject matter; storing result information indicative of search results returned in response to a final query in each stored query progression and indicative of results that the trusted resource interacted with; receiving a query progression from a user, including a user query related to the given subject matter; comparing the query progression from the user to the stored query progressions of the trusted resource to identify a matching, stored query progression; and providing a user interface display to the user based on the matching, stored query progression. 19. The computer-implemented method of claim 18 wherein providing a user interface display comprises:
providing a suggestion that the user modify the user query to be the final query in the matching stored query progression. 20. The computer-implemented method of claim 18 wherein providing a user interface display comprises:
providing the search results returned in response to the final query in the matching stored query progression and that the trusted resource interacted with. | Making an information retrieval process public, so that it can be followed by others, allows capturing of an interest graph that allows people to learn more about shared interests with other people. This also allows items of interest to a trusted resource (such as an expert) to be identified. These items can then be brought to the attention of other users that share the same interest as the expert. In addition, by keeping track of what particular content a user has already seen, the system can bring items of interest to the user's attention, where the user has not yet seen those items.1. A computer-implemented method of presenting content to a user in a search system that has a computer with a processor, the method comprising:
identifying, with the processor, a trusted resource for a given subject matter area; identifying, with the processor, that the user has a subject matter area of interest that matches the given subject matter area of the trusted resource; identifying, with the processor, seen content that the user has already interacted with in the search system; identifying, with the processor, unseen content of interest in the given subject matter area, that the trusted resource has interacted with, and that the user has not already interacted with; and generating a user interface display presenting the unseen content of interest to the user, indicating that the user has not yet interacted with the unseen content of interest, and indicating that the trusted resource has interacted with the unseen content of interest. 2. The computer-implemented method of claim 1 wherein identifying the trusted resource, comprises:
receiving, from a given user, inputs indicative of interactions with content;
identifying a subject matter area of the content interacted with by the given user;
determining a level of knowledge of the given user in the subject matter area of the content, based on a linguistic content of the inputs from the given user; and
if the level of knowledge of the given user in the subject matter area of the content meets a threshold level, then identifying the given user as a trusted resource in the subject matter area of the content. 3. The computer-implemented method of claim 2 wherein receiving inputs indicative of interactions with content comprises:
receiving queries in a public search system. 4. The computer-implemented method of claim 1 wherein identifying seen content, comprises:
receiving user interaction inputs indicative of a user interacting with different items of content; and
storing the user interaction inputs to generate a store of seen content for the user. 5. The computer-implemented method of claim 4 wherein receiving user interaction inputs, comprises:
displaying posts in a public stream of the search system, for the user, as the different items of content;
receiving user click inputs indicative of a user clicking on, liking, or commenting on, the posts; and
generating a click index of the click inputs for the user, wherein storing the user interaction inputs comprises storing the click index. 6. The computer-implemented method of claim 5 wherein identifying unseen content of interest, comprises:
comparing an identification of content of interest that the trusted resource has interacted with to the click inputs in the click index for the user to identify whether the user has interacted with the content of interest that the trusted resource has interacted with. 7. The computer-implemented method of claim 1 and further comprising:
identifying content in the given subject matter area that the trusted resource has interacted with by identifying content authored by the trusted resource within the search system. 8. The computer-implemented method of claim 1 and further comprising:
identifying content in the given subject matter area that the trusted resource has interacted with by identifying content the trusted resource has interacted with on a third party site. 9. The computer-implemented method of claim 1 wherein the search system comprises a public search system in which public streams are generated for the user and the trusted resource, each public stream having posts therein, and further comprising:
receiving an input by the trusted resource indicative of the trusted resource interacting with a post in the public stream of the trusted resource; and
identifying content in the post as content that the trusted resource interacted with. 10. The computer-implemented method of claim 9 wherein receiving an input by the trusted resource indicative of the trusted resource interacting with a post in the public stream comprises:
receiving the input by the trusted resource as an indication that the trusted resource has authored, liked or commented on the post. 11. The computer-implemented method of claim 1 wherein generating a user interface display comprises:
receiving a query, requesting information in the given subject matter area, from the user;
generating search results responsive to the query; and
generating the user interface display visually identifying certain ones of the search results as unseen content of interest. 12. The computer-implemented method of claim 1 wherein the search system displays selectable elements representing subject matter areas of interest to the user, including the given subject matter area, and wherein generating a user interface display comprises:
receiving a user selection of the selectable element representing the given subject matter area; and
generating the user interface display showing the unseen content of interest for the given subject matter area represented by the selectable element selected by the user. 13. The computer-implemented method of claim 1 wherein the search system comprises a public search system that displays a public search stream to the user having posts therein, and wherein generating the user interface display comprises:
generating the user interface as a post to the public stream of the user. 14. A public search system, comprising:
a user interface component receiving user inputs indicative of user queries and user interactions with content generated by the public search system; a search component that receives queries input by a user, searches a data store and returns results responsive to the queries; an interest tracking component identifying topics of interest to the user an unseen content of interest tracking component that tracks, comprising:
a trusted resource identifier identifying respective trusted resources in each of the identified topics of interest;
a new content identifier identifying new content that the trusted resources interacted with in their respective topic of interest; and
a seen results data store storing information indicative of search results that the user has interacted with, the unseen content of interest tracking component comparing the new content to the information in the seen results data store to determine whether the user has already interacted with the new content, to obtain a set of unseen content of interest for the user, and generating a user interface display at the user interface component displaying the unseen content of interest and an indication of why the unseen content of interest is being displayed; and
a computer processor being a functional component of the system and activated by the interest tracking component and the unseen content of interest tracking component to facilitate identifying the topics of interest, the trusted resources and the unseen content of interest. 15. The public search system of claim 14 and further comprising:
a topic feed generator that generates a public stream that has posts that include the user queries and results, the new content identifier identifying, as new content, items in the posts of the public stream of a trusted resource that the trusted resource has interacted with. 16. The public search system of claim 15 wherein the new content identifier identifies, as new content, search results returned in response to a trusted resource query submitted by the trusted resource and that the trusted resource selected for viewing. 17. The public search system of claim 14 wherein the unseen content of interest tracking component generates the user interface display, in response to receiving a user query related to the unseen content of interest, the user interface display visually emphasizing the unseen content of interest and textually identifying the trusted resource that interacted with the unseen content of interest. 18. A computer-implemented method of providing information to a user in a public search system, comprising:
identifying a trusted resource for a given subject matter of interest based on interactions of the trusted resource with the search system in the given subject matter; storing query progressions of the trusted resource for queries submitted by the trusted resource relating to the given subject matter; storing result information indicative of search results returned in response to a final query in each stored query progression and indicative of results that the trusted resource interacted with; receiving a query progression from a user, including a user query related to the given subject matter; comparing the query progression from the user to the stored query progressions of the trusted resource to identify a matching, stored query progression; and providing a user interface display to the user based on the matching, stored query progression. 19. The computer-implemented method of claim 18 wherein providing a user interface display comprises:
providing a suggestion that the user modify the user query to be the final query in the matching stored query progression. 20. The computer-implemented method of claim 18 wherein providing a user interface display comprises:
providing the search results returned in response to the final query in the matching stored query progression and that the trusted resource interacted with. | 2,100 |
6,593 | 6,593 | 14,831,101 | 2,164 | A method for enabling data set changes to be reverted to a prior point in time or state is disclosed. In one embodiment, such a method includes providing a data set comprising one or more data elements and a specified number of generations of the data elements. In certain embodiments, the data set is a partitioned data set extended (PDSE) data set, and the data elements are “members” within the PDSE data set. The method further includes tracking changes made by a job to data elements of the data set. The method further references, in a data structure (also referred to herein as a “cluster”) associated with the job, previous generations of the data elements changed by the job. In certain embodiments, the data structure is stored in the data set. A corresponding system and computer program product are also disclosed. | 1. A method to enable data set changes to be reverted to a prior point in time or state, the method comprising:
providing a data set comprising one or more data elements and a specified number of generations of the data elements; tracking changes made by a job to data elements of the data set; and referencing, in a data structure associated with the job, previous generations of the data elements changed by the job. 2. The method of claim 1, wherein the data set is a partitioned data set extended (PDSE) data set, and the data elements are members within the PDSE data set. 3. The method of claim 1, further comprising using the data structure to revert the data set to a state prior to the changes by the job. 4. The method of claim 1, further comprising storing the data structure in the data set. 5. The method of claim 1, further comprising retiring the data structure when at least one generation referenced by the data structure is permanently deleted from the data set. 6. The method of claim 1, further comprising referencing the data structure in a log structure outside of the data set. 7. The method of claim 6, further comprising removing the data structure from the log structure when the data structure is invalid. 8. A computer program product to enable data set changes to be reverted to a prior point in time or state, the computer program product comprising a computer-readable medium having computer-usable program code embodied therein, the computer-usable program code comprising:
computer-usable program code to provide a data set comprising one or more data elements and a specified number of generations of the data elements; computer-usable program code to track changes made by a job to data elements of the data set; and computer-usable program code to reference, in a data structure associated with the job, previous generations of the data elements changed by the job. 9. The computer program product of claim 8, wherein the data set is a partitioned data set extended (PDSE) data set, and the data elements are members within the PDSE data set. 10. The computer program product of claim 8, further comprising computer-usable program code to use the data structure to revert the data set to a state prior to the changes by the job. 11. The computer program product of claim 8, further comprising computer-usable program code to store the data structure in the data set. 12. The computer program product of claim 8, further comprising computer-usable program code to invalidate the data structure when at least one generation referenced by the data structure is permanently deleted from the data set. 13. The computer program product of claim 8, further comprising computer-usable program code to reference the data structure in a log structure outside of the data set. 14. The computer program product of claim 13, further comprising computer-usable program code to remove the data structure from the log structure when the data structure is invalid. 15. A system to enable data set changes to be reverted to a prior point in time or state, the system comprising:
at least one processor; at least one memory device operably coupled to the at least one processor and storing instructions for execution on the at least one processor, the instructions causing the at least one processor to:
provide a data set comprising one or more data elements and a specified number of generations of the data elements;
track changes made by a job to data elements of the data set; and
reference, in a data structure associated with the job, previous generations of the data elements changed by the job. 16. The system of claim 15, wherein the data set is a partitioned data set extended (PDSE) data set, and the data elements are members within the PDSE data set. 17. The system of claim 15, wherein the instructions further cause the at least one processor to use the data structure to revert the data set to a state prior to the changes by the job. 18. The system of claim 15, wherein the instructions further cause the at least one processor to store the data structure in the data set. 19. The system of claim 15, wherein the instructions further cause the at least one processor to invalidate the data structure when at least one generation referenced by the data structure is permanently deleted from the data set. 20. The system of claim 15, wherein the instructions further cause the at least one processor to reference the data structure in a log structure outside of the data set, and remove the data structure from the log structure when the data structure is invalid. | A method for enabling data set changes to be reverted to a prior point in time or state is disclosed. In one embodiment, such a method includes providing a data set comprising one or more data elements and a specified number of generations of the data elements. In certain embodiments, the data set is a partitioned data set extended (PDSE) data set, and the data elements are “members” within the PDSE data set. The method further includes tracking changes made by a job to data elements of the data set. The method further references, in a data structure (also referred to herein as a “cluster”) associated with the job, previous generations of the data elements changed by the job. In certain embodiments, the data structure is stored in the data set. A corresponding system and computer program product are also disclosed.1. A method to enable data set changes to be reverted to a prior point in time or state, the method comprising:
providing a data set comprising one or more data elements and a specified number of generations of the data elements; tracking changes made by a job to data elements of the data set; and referencing, in a data structure associated with the job, previous generations of the data elements changed by the job. 2. The method of claim 1, wherein the data set is a partitioned data set extended (PDSE) data set, and the data elements are members within the PDSE data set. 3. The method of claim 1, further comprising using the data structure to revert the data set to a state prior to the changes by the job. 4. The method of claim 1, further comprising storing the data structure in the data set. 5. The method of claim 1, further comprising retiring the data structure when at least one generation referenced by the data structure is permanently deleted from the data set. 6. The method of claim 1, further comprising referencing the data structure in a log structure outside of the data set. 7. The method of claim 6, further comprising removing the data structure from the log structure when the data structure is invalid. 8. A computer program product to enable data set changes to be reverted to a prior point in time or state, the computer program product comprising a computer-readable medium having computer-usable program code embodied therein, the computer-usable program code comprising:
computer-usable program code to provide a data set comprising one or more data elements and a specified number of generations of the data elements; computer-usable program code to track changes made by a job to data elements of the data set; and computer-usable program code to reference, in a data structure associated with the job, previous generations of the data elements changed by the job. 9. The computer program product of claim 8, wherein the data set is a partitioned data set extended (PDSE) data set, and the data elements are members within the PDSE data set. 10. The computer program product of claim 8, further comprising computer-usable program code to use the data structure to revert the data set to a state prior to the changes by the job. 11. The computer program product of claim 8, further comprising computer-usable program code to store the data structure in the data set. 12. The computer program product of claim 8, further comprising computer-usable program code to invalidate the data structure when at least one generation referenced by the data structure is permanently deleted from the data set. 13. The computer program product of claim 8, further comprising computer-usable program code to reference the data structure in a log structure outside of the data set. 14. The computer program product of claim 13, further comprising computer-usable program code to remove the data structure from the log structure when the data structure is invalid. 15. A system to enable data set changes to be reverted to a prior point in time or state, the system comprising:
at least one processor; at least one memory device operably coupled to the at least one processor and storing instructions for execution on the at least one processor, the instructions causing the at least one processor to:
provide a data set comprising one or more data elements and a specified number of generations of the data elements;
track changes made by a job to data elements of the data set; and
reference, in a data structure associated with the job, previous generations of the data elements changed by the job. 16. The system of claim 15, wherein the data set is a partitioned data set extended (PDSE) data set, and the data elements are members within the PDSE data set. 17. The system of claim 15, wherein the instructions further cause the at least one processor to use the data structure to revert the data set to a state prior to the changes by the job. 18. The system of claim 15, wherein the instructions further cause the at least one processor to store the data structure in the data set. 19. The system of claim 15, wherein the instructions further cause the at least one processor to invalidate the data structure when at least one generation referenced by the data structure is permanently deleted from the data set. 20. The system of claim 15, wherein the instructions further cause the at least one processor to reference the data structure in a log structure outside of the data set, and remove the data structure from the log structure when the data structure is invalid. | 2,100 |
6,594 | 6,594 | 15,785,795 | 2,174 | A smart device is provided with a main remote control application that may be configured using information obtained from a QR code. The main remote control application may present images of original remote controls corresponding to devices which are controllable by the configured main remote control application. In connection with a presented image of an original remote control, the display may present icons that are representative of a subset of the buttons of the original remote control. The user interface also allows a user to select amongst the images of the original remote controls to change which appliances are to be controlled via the user interface. A pop-up remote control widget may also be provided which may be invoked without switching to the main remote control application provisioned on the smart device. | 1. A non-transitory, computer-readable media having stored thereon instructions which, when executed by a processing device of a smart device, cause the smart device to perform steps comprising:
causing a first graphical user interface to be displayed in a touch sensitive display of the smart device; responding to a first predetermined user input provided to the smart device while the first graphical user interface is caused to be displayed in the touch sensitive display of the smart device to cause a second graphical user interface having a plurality of user selectable user interface elements to be made active within the touch sensitive display of the smart device whereupon the user interface elements of the second user interface are caused to be displayed in the touch sensitive display of the smart device over at least a portion of the first graphical user interface; determining if a user has interacted with at least one of the plurality of user selectable user interface elements of the second graphical user interface caused to be displayed in the touch sensitive display of the smart device over at least a portion of the first graphical user interface; and when it is determined that the user has interacted with at least one of the plurality of user selectable user interface elements of the second graphical user interface caused to be displayed in the touch sensitive display of the smart device over at least a portion of the first graphical user interface causing the smart device to transmit a command to control at least one of a first plurality of functional operations of at least one intended target controllable device correspond to the at least one of the plurality of user selectable user interface elements interacted with by the user; wherein user input received into the smart device is used to select from a library of command code sets a command code set appropriate for use in commanding functional operations of the at least one intended target controllable device and wherein the command caused to be transmitted in response to the user interacting with at least one of the plurality of user selectable user interface elements of the second graphical user interface caused to be displayed over the first graphical user interface in the touch sensitive display of the smart device is selected from the command code set selected from the library of command code sets. 2. The non-transitory, computer-readable media as recited in claim 1, wherein the plurality of user selectable user interface elements of the second graphical user interface are caused to be displayed in the touch sensitive display of the smart device over the first graphical user interface until a second predetermined user input is provided to the smart device. 3. The non-transitory, computer-readable media as recited in claim 2, wherein the first predetermined user input comprises a first predetermined user interaction with the touch screen display of the smart device and the second predetermined user input comprises a second predetermined user interaction with the touch screen display of the smart device. 4. The non-transitory, computer-readable media as recited in claim 3, wherein the second predetermined user interaction with the touch screen display comprises a touching of the touch screen display of the smart device outside of the displayed second graphical user interface. 5. The non-transitory, computer-readable media as recited in claim 1, wherein the instructions determine which user selectable user interface elements to include in the second user interface when the second user interface is caused to be made active within the touch screen display of the smart device. 6. The non-transitory, computer-readable media as recited in claim 2, wherein the second predetermined user input provided to the smart device is the same as the first predetermined user input provided to the smart device excepting that the second predetermined user input is provided to the smart device subsequent to the first predetermined user input being provided to the smart device. 7. The computer-readable media as recited in claim 1, wherein the plurality of user selectable user interface elements of the second graphical user interface comprises one or more user selectable user interface elements for controlling volume operational functions of the at least one intended target controllable device. 8. The computer-readable media as recited in claim 1, wherein the plurality of user selectable user interface elements of the second graphical user interface comprises one or more user selectable user interface elements for controlling channel tuning operational functions of the at least one intended target controllable device. 9. The computer-readable media as recited in claim 1, wherein the plurality of user selectable user interface elements of the second graphical user interface comprises one or more user selectable user interface elements for controlling media transport operational functions of the at least one intended target controllable device. 10. The computer-readable media as recited in claim 1, wherein the instructions provide a main remote control application usable on the smart device to command functional operations of the at least one intended target device and wherein the main remote control application functions to receive the user input into the smart device used to select from the library of command code sets the command code set appropriate for use in commanding functional operations of the at least one intended target controllable device. 11. The computer-readable media as recited in claim 10, wherein the second graphical user interface having a plurality of user selectable user interface elements is capable of being made active independently of the main remote control application being made active. | A smart device is provided with a main remote control application that may be configured using information obtained from a QR code. The main remote control application may present images of original remote controls corresponding to devices which are controllable by the configured main remote control application. In connection with a presented image of an original remote control, the display may present icons that are representative of a subset of the buttons of the original remote control. The user interface also allows a user to select amongst the images of the original remote controls to change which appliances are to be controlled via the user interface. A pop-up remote control widget may also be provided which may be invoked without switching to the main remote control application provisioned on the smart device.1. A non-transitory, computer-readable media having stored thereon instructions which, when executed by a processing device of a smart device, cause the smart device to perform steps comprising:
causing a first graphical user interface to be displayed in a touch sensitive display of the smart device; responding to a first predetermined user input provided to the smart device while the first graphical user interface is caused to be displayed in the touch sensitive display of the smart device to cause a second graphical user interface having a plurality of user selectable user interface elements to be made active within the touch sensitive display of the smart device whereupon the user interface elements of the second user interface are caused to be displayed in the touch sensitive display of the smart device over at least a portion of the first graphical user interface; determining if a user has interacted with at least one of the plurality of user selectable user interface elements of the second graphical user interface caused to be displayed in the touch sensitive display of the smart device over at least a portion of the first graphical user interface; and when it is determined that the user has interacted with at least one of the plurality of user selectable user interface elements of the second graphical user interface caused to be displayed in the touch sensitive display of the smart device over at least a portion of the first graphical user interface causing the smart device to transmit a command to control at least one of a first plurality of functional operations of at least one intended target controllable device correspond to the at least one of the plurality of user selectable user interface elements interacted with by the user; wherein user input received into the smart device is used to select from a library of command code sets a command code set appropriate for use in commanding functional operations of the at least one intended target controllable device and wherein the command caused to be transmitted in response to the user interacting with at least one of the plurality of user selectable user interface elements of the second graphical user interface caused to be displayed over the first graphical user interface in the touch sensitive display of the smart device is selected from the command code set selected from the library of command code sets. 2. The non-transitory, computer-readable media as recited in claim 1, wherein the plurality of user selectable user interface elements of the second graphical user interface are caused to be displayed in the touch sensitive display of the smart device over the first graphical user interface until a second predetermined user input is provided to the smart device. 3. The non-transitory, computer-readable media as recited in claim 2, wherein the first predetermined user input comprises a first predetermined user interaction with the touch screen display of the smart device and the second predetermined user input comprises a second predetermined user interaction with the touch screen display of the smart device. 4. The non-transitory, computer-readable media as recited in claim 3, wherein the second predetermined user interaction with the touch screen display comprises a touching of the touch screen display of the smart device outside of the displayed second graphical user interface. 5. The non-transitory, computer-readable media as recited in claim 1, wherein the instructions determine which user selectable user interface elements to include in the second user interface when the second user interface is caused to be made active within the touch screen display of the smart device. 6. The non-transitory, computer-readable media as recited in claim 2, wherein the second predetermined user input provided to the smart device is the same as the first predetermined user input provided to the smart device excepting that the second predetermined user input is provided to the smart device subsequent to the first predetermined user input being provided to the smart device. 7. The computer-readable media as recited in claim 1, wherein the plurality of user selectable user interface elements of the second graphical user interface comprises one or more user selectable user interface elements for controlling volume operational functions of the at least one intended target controllable device. 8. The computer-readable media as recited in claim 1, wherein the plurality of user selectable user interface elements of the second graphical user interface comprises one or more user selectable user interface elements for controlling channel tuning operational functions of the at least one intended target controllable device. 9. The computer-readable media as recited in claim 1, wherein the plurality of user selectable user interface elements of the second graphical user interface comprises one or more user selectable user interface elements for controlling media transport operational functions of the at least one intended target controllable device. 10. The computer-readable media as recited in claim 1, wherein the instructions provide a main remote control application usable on the smart device to command functional operations of the at least one intended target device and wherein the main remote control application functions to receive the user input into the smart device used to select from the library of command code sets the command code set appropriate for use in commanding functional operations of the at least one intended target controllable device. 11. The computer-readable media as recited in claim 10, wherein the second graphical user interface having a plurality of user selectable user interface elements is capable of being made active independently of the main remote control application being made active. | 2,100 |
6,595 | 6,595 | 15,241,488 | 2,183 | A computer architecture employs multiple special-purpose processors having different affinities for program execution to execute substantial portions of general-purpose programs to provide improved performance with respect to a general-purpose processor executing the general-purpose program alone. | 1. A computer architecture for executing a program comprising:
a memory cache; a set of heterogeneous processors sharing the memory cache and providing relatively different performances with respect to different portions of the program; and a switch unit alternately switching between the heterogeneous processors for different portions of the program based on an assessed comparative advantage of the heterogeneous processors in executing the different portions; wherein the heterogeneous processors include: (a) a general-purpose processor providing speculative execution and capable of executing the program entirely; (b) a first special purpose processor providing higher performance execution than the general-purpose processor for first given program portions; and (c) a second special purpose processor providing higher performance execution than the general-purpose processor for second given program portions. 2. The computer architecture of claim 1 wherein the first special purpose processor provides higher performance execution than the general-purpose processor for a first given program portion having a predetermined level of control criticality and the second purpose processor provides higher performance execution than the general-purpose processor for a second given program portion exhibiting more control criticality than the first given program portion 3. The computer architecture of claim 2 wherein the second purpose processor provides higher performance execution than the general-purpose processor for the second given program providing a predetermined level of consistency of control flow and wherein the first special purpose processor provides higher performance execution than the general-purpose processor for the first given program portions exhibiting less control consistency than the second program portion. 4. The computer architecture of claim 3 wherein the second special purpose processor provides a level of speculation less than a level of speculation provided by the general-purpose processor. 5. The computer architecture of claim 1 wherein the set of heterogeneous processors includes a specialized processor not providing speculative execution. 6. The computer architecture of claim 1 further including a third special purpose processor providing higher performance execution than the general-purpose processor for a third program portion having a predetermined level of data parallelism and wherein the first and second special purpose processors provide higher performance execution than the general-purpose processor for the first and second given programs exhibiting less data parallelism than the third program portion 7. The computer architecture of claim 6 further including a fourth special purpose processor providing higher performance execution than the general-purpose processor for a fourth program portion having lower control complexity than the third program portion wherein the fourth special purpose processor provides higher performance execution than the general-purpose processor for the fourth program portion and the third special purpose processor provides higher performance execution than the general-purpose processor for the third program portion having greater control complexity than the fourth program portion. 8. The computer architecture of claim 7 wherein the fourth special purpose processor is a processor executing a single instruction in parallel on multiple data elements. 9. The computer architecture of claim 8 wherein the third and fourth special purpose processors are processors accepting a single instruction for execution in parallel on multiple data elements and providing comparative relative advantages on different lengths of data vectors. 10. The computer architecture of claim 1 wherein the general-purpose processor provides configuration data to given other heterogeneous processors before switching to the given other heterogeneous processors for execution of a program portion. 11. The computer architecture of claim 1 wherein the switch unit is controlled by one of the heterogeneous processors. 12. The computer architecture of claim 1 wherein only a single one of the heterogeneous processors other than the general-purpose processor executes at a time and remaining processors other than the general-purpose processor are placed in a reduced energy consumption state. 13. The computer architecture of claim 1 wherein the general-purpose processor is an out-of-order processor. 14. The computer architecture of claim 1 further including:
a real-time program profiler monitoring execution of different portions of the program on different of the processors to assess comparative advantages of the different processors in executing the different portions during an earlier execution of the different portions; and
wherein the switch unit alternately switches between the processors for a later execution of the different portions of the program based on the assessed comparative advantage as indicated by the real-time program profiler during the earlier execution of the different portions. 15. The computer architecture of claim 14 wherein the real-time program profiler monitors execution of a given portion of the program to assess a degree of control criticality. 16. The computer architecture of claim 14 wherein the real-time program profiler monitors data dependencies in the execution of a given portion of the program to assess a degree of data parallelism with larger numbers of dependencies associated with lesser data parallelism. 17. The computer architecture of claim 14 wherein the real-time program profiler monitors a number of branches in the execution of a given portion of the program to assess control flow complexity with larger numbers of branches associated with more control flow complexity. 18. The computer architecture of claim 14 wherein the real-time program profiler is executed at least in part on one of the heterogeneous processors. 19. A method of executing a program on a computer architecture having:
a memory cache; a set of heterogeneous processors sharing the memory cache and providing relatively different performances with respect to different portions of the program; and a switch unit alternately switching between the heterogeneous processors for different portions of the program based on an assessed comparative advantage of the heterogeneous processors in executing the different portions; wherein the heterogeneous processors include: (a) a general-purpose processor providing speculative execution and capable of executing the program entirely; (b) a first special purpose processor providing higher performance execution than the general-purpose processor for first given program portions; and (c) a second special purpose processor providing higher performance execution than the general-purpose processor for second given program portions; the method comprising the steps of: (a) allocating program portions to different of the heterogeneous processors according to a first allocation pattern; (b) profiling the allocated program portions during execution on the heterogeneous processors according to the first allocation pattern; and (c) based on the profiling, reallocate the program portions to the different heterogeneous processors according to a second allocation pattern providing improved performance. | A computer architecture employs multiple special-purpose processors having different affinities for program execution to execute substantial portions of general-purpose programs to provide improved performance with respect to a general-purpose processor executing the general-purpose program alone.1. A computer architecture for executing a program comprising:
a memory cache; a set of heterogeneous processors sharing the memory cache and providing relatively different performances with respect to different portions of the program; and a switch unit alternately switching between the heterogeneous processors for different portions of the program based on an assessed comparative advantage of the heterogeneous processors in executing the different portions; wherein the heterogeneous processors include: (a) a general-purpose processor providing speculative execution and capable of executing the program entirely; (b) a first special purpose processor providing higher performance execution than the general-purpose processor for first given program portions; and (c) a second special purpose processor providing higher performance execution than the general-purpose processor for second given program portions. 2. The computer architecture of claim 1 wherein the first special purpose processor provides higher performance execution than the general-purpose processor for a first given program portion having a predetermined level of control criticality and the second purpose processor provides higher performance execution than the general-purpose processor for a second given program portion exhibiting more control criticality than the first given program portion 3. The computer architecture of claim 2 wherein the second purpose processor provides higher performance execution than the general-purpose processor for the second given program providing a predetermined level of consistency of control flow and wherein the first special purpose processor provides higher performance execution than the general-purpose processor for the first given program portions exhibiting less control consistency than the second program portion. 4. The computer architecture of claim 3 wherein the second special purpose processor provides a level of speculation less than a level of speculation provided by the general-purpose processor. 5. The computer architecture of claim 1 wherein the set of heterogeneous processors includes a specialized processor not providing speculative execution. 6. The computer architecture of claim 1 further including a third special purpose processor providing higher performance execution than the general-purpose processor for a third program portion having a predetermined level of data parallelism and wherein the first and second special purpose processors provide higher performance execution than the general-purpose processor for the first and second given programs exhibiting less data parallelism than the third program portion 7. The computer architecture of claim 6 further including a fourth special purpose processor providing higher performance execution than the general-purpose processor for a fourth program portion having lower control complexity than the third program portion wherein the fourth special purpose processor provides higher performance execution than the general-purpose processor for the fourth program portion and the third special purpose processor provides higher performance execution than the general-purpose processor for the third program portion having greater control complexity than the fourth program portion. 8. The computer architecture of claim 7 wherein the fourth special purpose processor is a processor executing a single instruction in parallel on multiple data elements. 9. The computer architecture of claim 8 wherein the third and fourth special purpose processors are processors accepting a single instruction for execution in parallel on multiple data elements and providing comparative relative advantages on different lengths of data vectors. 10. The computer architecture of claim 1 wherein the general-purpose processor provides configuration data to given other heterogeneous processors before switching to the given other heterogeneous processors for execution of a program portion. 11. The computer architecture of claim 1 wherein the switch unit is controlled by one of the heterogeneous processors. 12. The computer architecture of claim 1 wherein only a single one of the heterogeneous processors other than the general-purpose processor executes at a time and remaining processors other than the general-purpose processor are placed in a reduced energy consumption state. 13. The computer architecture of claim 1 wherein the general-purpose processor is an out-of-order processor. 14. The computer architecture of claim 1 further including:
a real-time program profiler monitoring execution of different portions of the program on different of the processors to assess comparative advantages of the different processors in executing the different portions during an earlier execution of the different portions; and
wherein the switch unit alternately switches between the processors for a later execution of the different portions of the program based on the assessed comparative advantage as indicated by the real-time program profiler during the earlier execution of the different portions. 15. The computer architecture of claim 14 wherein the real-time program profiler monitors execution of a given portion of the program to assess a degree of control criticality. 16. The computer architecture of claim 14 wherein the real-time program profiler monitors data dependencies in the execution of a given portion of the program to assess a degree of data parallelism with larger numbers of dependencies associated with lesser data parallelism. 17. The computer architecture of claim 14 wherein the real-time program profiler monitors a number of branches in the execution of a given portion of the program to assess control flow complexity with larger numbers of branches associated with more control flow complexity. 18. The computer architecture of claim 14 wherein the real-time program profiler is executed at least in part on one of the heterogeneous processors. 19. A method of executing a program on a computer architecture having:
a memory cache; a set of heterogeneous processors sharing the memory cache and providing relatively different performances with respect to different portions of the program; and a switch unit alternately switching between the heterogeneous processors for different portions of the program based on an assessed comparative advantage of the heterogeneous processors in executing the different portions; wherein the heterogeneous processors include: (a) a general-purpose processor providing speculative execution and capable of executing the program entirely; (b) a first special purpose processor providing higher performance execution than the general-purpose processor for first given program portions; and (c) a second special purpose processor providing higher performance execution than the general-purpose processor for second given program portions; the method comprising the steps of: (a) allocating program portions to different of the heterogeneous processors according to a first allocation pattern; (b) profiling the allocated program portions during execution on the heterogeneous processors according to the first allocation pattern; and (c) based on the profiling, reallocate the program portions to the different heterogeneous processors according to a second allocation pattern providing improved performance. | 2,100 |
6,596 | 6,596 | 14,573,137 | 2,136 | Systems and methods for building file system images using cached logical volume snapshots. An example method may comprise: producing a buildroot descriptor in view of a list of identifiers of software packages to be included into a new file system image; and responsive to locating, in a storage memory, a logical volume snapshot associated with the buildroot descriptor, creating the new file system image using the logical volume snapshot. | 1. A method, comprising:
producing, by a processing device, a buildroot descriptor in view of a list of identifiers of software packages to be included into a new file system image; and responsive to locating, in a storage memory, a logical volume snapshot associated with the buildroot descriptor, creating the new file system image using the logical volume snapshot. 2. The method of claim 1, wherein the storage memory comprises a logical volume manager (LVM) cache. 3. The method of claim 1, wherein producing the buildroot descriptor comprises:
lexicographically ordering the list of identifiers of the software packages to produce an ordered list comprising one or more elements; concatenating the elements of the ordered list to produce a temporary string; calculating a hash function of the temporary string. 4. The method of claim 1, wherein creating the new file system image comprises cloning the logical volume snapshot. 5. The method of claim 4, wherein cloning the logical volume snapshot produces a new copy-on-write (COW) snapshot associated with the logical volume snapshot. 6. The method of claim 1, further comprising:
moving the buildroot descriptor to a top position of a list of buildroot descriptors associated with the storage memory. 7. The method of claim 1, further comprising:
responsive to failing locate, in the storage memory, a logical volume snapshot identified by the buildroot descriptor, creating the new file system image by installing the software packages identified by the list; and storing, in the storage memory, a snapshot of a logical volume comprising the new file system image. 8. The method of claim 1, further comprising:
removing, from the storage memory, a least recently accessed logical volume snapshot. 9. A system, comprising:
a memory; and a processing device, coupled to the memory, to:
produce a buildroot descriptor in view of a list of identifiers of software packages to be included into a new file system image; and
responsive to locating, in a storage memory, a logical volume snapshot associated with the buildroot descriptor, create the new file system image using the logical volume snapshot. 10. The system of claim 9, wherein the storage memory comprises a logical volume manager (LVM) cache. 11. The system of claim 9, wherein producing the buildroot descriptor comprises:
lexicographically ordering the list of identifiers of the software packages to produce an ordered list comprising one or more elements; concatenating the elements of the ordered list to produce a temporary string; calculating a hash function of the temporary string. 12. The system of claim 9, wherein creating the new file system image comprises cloning the logical volume snapshot. 13. The system of claim 9, further comprising:
moving the buildroot descriptor to a top position of a list of buildroot descriptors associated with the storage memory. 14. The system of claim 9, further comprising:
responsive to failing locate, in the storage memory, a logical volume snapshot identified by the buildroot descriptor, creating the new file system image by installing the software packages identified by the list; and storing, in the storage memory, a snapshot of a logical volume comprising the new file system image. 15. A non-transitory computer-readable storage medium comprising executable instructions that, when executed by a processing device of a file system server, cause the processing device to:
produce, by the processing device, a buildroot descriptor in view of a list of identifiers of software packages to be included into a new file system image; and responsive to locating, in a storage memory, a logical volume snapshot associated with the buildroot descriptor, create the new file system image using the logical volume snapshot. 16. The non-transitory computer-readable storage medium of claim 15, wherein the storage memory comprises a logical volume manager (LVM) cache. 17. The non-transitory computer-readable storage medium of claim 15, wherein producing the buildroot descriptor comprises:
lexicographically ordering the list of identifiers of the software packages to produce an ordered list comprising one or more elements; concatenating the elements of the ordered list to produce a temporary string; calculating a hash function of the temporary string. 18. The non-transitory computer-readable storage medium of claim 15, wherein creating the new file system image comprises cloning the logical volume snapshot. 19. The non-transitory computer-readable storage medium of claim 15, further comprising:
moving the buildroot descriptor to a top position of a list of buildroot descriptors associated with the storage memory. 20. The non-transitory computer-readable storage medium of claim 15, further comprising:
responsive to failing locate, in the storage memory, a logical volume snapshot identified by the buildroot descriptor, creating the new file system image by installing the software packages identified by the list; and storing, in the storage memory, a snapshot of a logical volume comprising the new file system image. | Systems and methods for building file system images using cached logical volume snapshots. An example method may comprise: producing a buildroot descriptor in view of a list of identifiers of software packages to be included into a new file system image; and responsive to locating, in a storage memory, a logical volume snapshot associated with the buildroot descriptor, creating the new file system image using the logical volume snapshot.1. A method, comprising:
producing, by a processing device, a buildroot descriptor in view of a list of identifiers of software packages to be included into a new file system image; and responsive to locating, in a storage memory, a logical volume snapshot associated with the buildroot descriptor, creating the new file system image using the logical volume snapshot. 2. The method of claim 1, wherein the storage memory comprises a logical volume manager (LVM) cache. 3. The method of claim 1, wherein producing the buildroot descriptor comprises:
lexicographically ordering the list of identifiers of the software packages to produce an ordered list comprising one or more elements; concatenating the elements of the ordered list to produce a temporary string; calculating a hash function of the temporary string. 4. The method of claim 1, wherein creating the new file system image comprises cloning the logical volume snapshot. 5. The method of claim 4, wherein cloning the logical volume snapshot produces a new copy-on-write (COW) snapshot associated with the logical volume snapshot. 6. The method of claim 1, further comprising:
moving the buildroot descriptor to a top position of a list of buildroot descriptors associated with the storage memory. 7. The method of claim 1, further comprising:
responsive to failing locate, in the storage memory, a logical volume snapshot identified by the buildroot descriptor, creating the new file system image by installing the software packages identified by the list; and storing, in the storage memory, a snapshot of a logical volume comprising the new file system image. 8. The method of claim 1, further comprising:
removing, from the storage memory, a least recently accessed logical volume snapshot. 9. A system, comprising:
a memory; and a processing device, coupled to the memory, to:
produce a buildroot descriptor in view of a list of identifiers of software packages to be included into a new file system image; and
responsive to locating, in a storage memory, a logical volume snapshot associated with the buildroot descriptor, create the new file system image using the logical volume snapshot. 10. The system of claim 9, wherein the storage memory comprises a logical volume manager (LVM) cache. 11. The system of claim 9, wherein producing the buildroot descriptor comprises:
lexicographically ordering the list of identifiers of the software packages to produce an ordered list comprising one or more elements; concatenating the elements of the ordered list to produce a temporary string; calculating a hash function of the temporary string. 12. The system of claim 9, wherein creating the new file system image comprises cloning the logical volume snapshot. 13. The system of claim 9, further comprising:
moving the buildroot descriptor to a top position of a list of buildroot descriptors associated with the storage memory. 14. The system of claim 9, further comprising:
responsive to failing locate, in the storage memory, a logical volume snapshot identified by the buildroot descriptor, creating the new file system image by installing the software packages identified by the list; and storing, in the storage memory, a snapshot of a logical volume comprising the new file system image. 15. A non-transitory computer-readable storage medium comprising executable instructions that, when executed by a processing device of a file system server, cause the processing device to:
produce, by the processing device, a buildroot descriptor in view of a list of identifiers of software packages to be included into a new file system image; and responsive to locating, in a storage memory, a logical volume snapshot associated with the buildroot descriptor, create the new file system image using the logical volume snapshot. 16. The non-transitory computer-readable storage medium of claim 15, wherein the storage memory comprises a logical volume manager (LVM) cache. 17. The non-transitory computer-readable storage medium of claim 15, wherein producing the buildroot descriptor comprises:
lexicographically ordering the list of identifiers of the software packages to produce an ordered list comprising one or more elements; concatenating the elements of the ordered list to produce a temporary string; calculating a hash function of the temporary string. 18. The non-transitory computer-readable storage medium of claim 15, wherein creating the new file system image comprises cloning the logical volume snapshot. 19. The non-transitory computer-readable storage medium of claim 15, further comprising:
moving the buildroot descriptor to a top position of a list of buildroot descriptors associated with the storage memory. 20. The non-transitory computer-readable storage medium of claim 15, further comprising:
responsive to failing locate, in the storage memory, a logical volume snapshot identified by the buildroot descriptor, creating the new file system image by installing the software packages identified by the list; and storing, in the storage memory, a snapshot of a logical volume comprising the new file system image. | 2,100 |
6,597 | 6,597 | 15,179,923 | 2,187 | A computer program embodied on a tangible computer readable medium includes computer code for identifying a stored configuration of a system, computer code for determining whether the stored configuration of the system includes digital signatures of each of a plurality of parties, and computer code for conditionally implementing a current configuration of the system, based on the determining. | 1. A computer program embodied on a tangible computer readable medium, comprising:
computer code for identifying a stored configuration of a system; computer code for determining whether the stored configuration of the system includes digital signatures of each of a plurality of parties; and computer code for conditionally implementing a current configuration of the system, based on the determining. 2. The computer program of claim 1, wherein the stored configuration of the system includes a firmware image. 3. The computer program of claim 1, wherein the stored configuration of the system includes a configuration of one or more sub-modules of the system. 4. The computer program of claim 1, wherein the plurality of parties include at least one lessor of the system and at least one lessee of the system. 5. The computer program of claim 1, wherein determining whether the stored configuration of the system includes digital signatures of each of the plurality of parties includes retrieving stored certificates for each of the plurality of parties and verifying each of the digital signatures of each of the plurality of parties, utilizing the retrieved certificates. 6. The computer program of claim 1, wherein the digital signatures of the plurality of parties are included within the stored configuration of the system as a result of creating a mutually secured configuration. 7. The computer program of claim 6, wherein creating the mutually secured configuration includes creating and storing a certificate for each of the plurality of parties. 8. The computer program of claim 6, wherein creating the mutually secured configuration includes calculating a hash value for the stored configuration of the system. 9. The computer program of claim 8, wherein creating the mutually secured configuration includes applying a signature of each of the plurality of parties to the hash value. 10. A method, comprising:
identifying a stored configuration of a system; determining whether the stored configuration of the system includes digital signatures of each of a plurality of parties; and conditionally implementing a current configuration of the system, based on the determining. 11. The method of claim 1, wherein the stored configuration of the system includes a firmware image. 12. The method of claim 1, wherein the stored configuration of the system includes a configuration of one or more sub-modules of the system. 13. The method of claim 1, wherein the plurality of parties include at least one lessor of the system and at least one lessee of the system. 14. The method of claim 1, wherein determining whether the stored configuration of the system includes digital signatures of each of the plurality of parties includes retrieving stored certificates for each of the plurality of parties and verifying each of the digital signatures of each of the plurality of parties, utilizing the retrieved certificates. 15. The method of claim 1, wherein the digital signatures of the plurality of parties are included within the stored configuration of the system as a result of creating a mutually secured configuration. 16. The method of claim 15, wherein creating the mutually secured configuration includes creating and storing a certificate for each of the plurality of parties. 17. The method of claim 15, wherein creating the mutually secured configuration includes calculating a hash value for the stored configuration of the system. 18. The method of claim 17, wherein creating the mutually secured configuration includes applying a signature of each of the plurality of parties to the hash value. 19. A system, comprising:
a processor and logic integrated with and/or executable by the processor, the logic being configured to: identify a system configuration; calculate a hash value for the system configuration; create a signed hash value, utilizing the hash value and a plurality of private keys; and store the signed hash value. 20. The system of claim 19, wherein the processor is coupled to memory via a bus. | A computer program embodied on a tangible computer readable medium includes computer code for identifying a stored configuration of a system, computer code for determining whether the stored configuration of the system includes digital signatures of each of a plurality of parties, and computer code for conditionally implementing a current configuration of the system, based on the determining.1. A computer program embodied on a tangible computer readable medium, comprising:
computer code for identifying a stored configuration of a system; computer code for determining whether the stored configuration of the system includes digital signatures of each of a plurality of parties; and computer code for conditionally implementing a current configuration of the system, based on the determining. 2. The computer program of claim 1, wherein the stored configuration of the system includes a firmware image. 3. The computer program of claim 1, wherein the stored configuration of the system includes a configuration of one or more sub-modules of the system. 4. The computer program of claim 1, wherein the plurality of parties include at least one lessor of the system and at least one lessee of the system. 5. The computer program of claim 1, wherein determining whether the stored configuration of the system includes digital signatures of each of the plurality of parties includes retrieving stored certificates for each of the plurality of parties and verifying each of the digital signatures of each of the plurality of parties, utilizing the retrieved certificates. 6. The computer program of claim 1, wherein the digital signatures of the plurality of parties are included within the stored configuration of the system as a result of creating a mutually secured configuration. 7. The computer program of claim 6, wherein creating the mutually secured configuration includes creating and storing a certificate for each of the plurality of parties. 8. The computer program of claim 6, wherein creating the mutually secured configuration includes calculating a hash value for the stored configuration of the system. 9. The computer program of claim 8, wherein creating the mutually secured configuration includes applying a signature of each of the plurality of parties to the hash value. 10. A method, comprising:
identifying a stored configuration of a system; determining whether the stored configuration of the system includes digital signatures of each of a plurality of parties; and conditionally implementing a current configuration of the system, based on the determining. 11. The method of claim 1, wherein the stored configuration of the system includes a firmware image. 12. The method of claim 1, wherein the stored configuration of the system includes a configuration of one or more sub-modules of the system. 13. The method of claim 1, wherein the plurality of parties include at least one lessor of the system and at least one lessee of the system. 14. The method of claim 1, wherein determining whether the stored configuration of the system includes digital signatures of each of the plurality of parties includes retrieving stored certificates for each of the plurality of parties and verifying each of the digital signatures of each of the plurality of parties, utilizing the retrieved certificates. 15. The method of claim 1, wherein the digital signatures of the plurality of parties are included within the stored configuration of the system as a result of creating a mutually secured configuration. 16. The method of claim 15, wherein creating the mutually secured configuration includes creating and storing a certificate for each of the plurality of parties. 17. The method of claim 15, wherein creating the mutually secured configuration includes calculating a hash value for the stored configuration of the system. 18. The method of claim 17, wherein creating the mutually secured configuration includes applying a signature of each of the plurality of parties to the hash value. 19. A system, comprising:
a processor and logic integrated with and/or executable by the processor, the logic being configured to: identify a system configuration; calculate a hash value for the system configuration; create a signed hash value, utilizing the hash value and a plurality of private keys; and store the signed hash value. 20. The system of claim 19, wherein the processor is coupled to memory via a bus. | 2,100 |
6,598 | 6,598 | 15,480,712 | 2,145 | Disclosed are various embodiments for improving user interface rendering performance. A network page is received from one or more servers, where the network page includes code that renders a graphical placeholder for a user interface component. The code that renders the graphical placeholder for the user interface component is executed. Code that renders an updated view of the user interface component is received from the server(s) in response to a scrolling action or a viewport manipulation bringing the graphical placeholder for the user interface component into view. The code that renders the updated view of the user interface component is executed. | 1. A system, comprising:
at least one computing device; and a network page generation application executable in the at least one computing device, wherein when executed the network page generation application causes the at least one computing device to at least:
generates a network page that is configured to defer loading of additional code that renders a user interface component, the network page including code that renders a graphical placeholder for the user interface component, the code that renders the graphical placeholder being configured to:
load the additional code in response to a scrolling action or a viewport manipulation bringing the graphical placeholder for the user interface component into view; and
execute the additional code to render the user interface component. 2. The system of claim 1, wherein the code that renders the graphical placeholder is configured to load the additional code from a client-side cache. 3. The system of claim 1, wherein the code that renders the graphical placeholder is configured to request the additional code from the at least one computing device. 4. The system of claim 1, wherein the additional code is configured to:
determine that a user interaction with the user interface component has occurred; receive control code that controls the user interface component from the at least one computing device; and execute the control code to process the user interaction. 5. The system of claim 4, wherein the control code is executed to process a queue of events associated with the user interaction and to render an updated view of the user interface component in response to processing the queue of events. 6. The system of claim 4, wherein the user interaction comprises a selection of a button of the user interface component, and the control code is configured to process playback of media. 7. The system of claim 1, wherein the additional code is configured to:
determine that the graphical placeholder has been rendered on a display at least a predefined length of time; receive control code that controls the user interface component from the at least one computing device; and execute the control code. 8. The system of claim 1, wherein the user interface component includes a plurality of user interface elements. 9. A method, comprising:
receiving, via at least one of one or more computing devices, a network page from at least one server, the network page including code that renders a graphical placeholder for a user interface component; executing, via at least one of the one or more computing devices, the code that renders the graphical placeholder for the user interface component; receiving, via at least one of the one or more computing devices, code that renders an updated view of the user interface component from the at least one server in response to a scrolling action or a viewport manipulation bringing the graphical placeholder for the user interface component into view; and executing, via at least one of the one or more computing devices, the code that renders the updated view of the user interface component. 10. The method of claim 9, further comprising determining, via at least one of the one or more computing devices, that the graphical placeholder has been rendered on a display for at least a predetermined length of time. 11. The method of claim 9, further comprising caching, via at least one of the one or more computing devices, the code that renders the updated view of the user interface component. 12. The method of claim 9, further comprising asynchronously requesting, via at least one of the one or more computing devices, data from the at least one server based at least in part on a user interaction with the updated view of the user interface component. 13. The method of claim 9, wherein the updated view of the user interface component is configured to appear fully functional but lacks at least a portion of functionality. 14. The method of claim 9, wherein the code that renders the updated view of the user interface component further comprises controller logic for the user interface component. 15. The method of claim 9, further comprising:
determining, via at least one of the one or more computing devices, that the graphical placeholder has been rendered on a display at least a predefined length of time; receiving, via at least one of the one or more computing devices, control code that controls the user interface component from the at least one server; and executing, via at least one of the one or more computing devices, the control code. 16. The method of claim 9, further comprising:
determining, via at least one of the one or more computing devices, that a user interaction with the user interface component has occurred; receiving, via at least one of the one or more computing devices, control code that controls the user interface component from the at least one server; and executing, via at least one of the one or more computing devices, the control code to process the user interaction. 17. A non-transitory computer-readable medium embodying a program executable in at least one computing device, wherein when executed the program causes the at least one computing device to at least:
render a user interface that includes a graphical placeholder for a user interface component; load additional code that renders the user interface component in response to a scrolling action or a viewport manipulation bringing the graphical placeholder for the user interface component into view; and execute the additional code to render the user interface component. 18. The non-transitory computer-readable medium of claim 17, wherein the program is configured to defer loading of media playback code until a user interacts with an initial view of the user interface component. 19. The non-transitory computer-readable medium of claim 17, wherein the additional code is loaded over a data communications network. 20. The non-transitory computer-readable medium of claim 17, wherein the additional code is loaded via inter-process communication. | Disclosed are various embodiments for improving user interface rendering performance. A network page is received from one or more servers, where the network page includes code that renders a graphical placeholder for a user interface component. The code that renders the graphical placeholder for the user interface component is executed. Code that renders an updated view of the user interface component is received from the server(s) in response to a scrolling action or a viewport manipulation bringing the graphical placeholder for the user interface component into view. The code that renders the updated view of the user interface component is executed.1. A system, comprising:
at least one computing device; and a network page generation application executable in the at least one computing device, wherein when executed the network page generation application causes the at least one computing device to at least:
generates a network page that is configured to defer loading of additional code that renders a user interface component, the network page including code that renders a graphical placeholder for the user interface component, the code that renders the graphical placeholder being configured to:
load the additional code in response to a scrolling action or a viewport manipulation bringing the graphical placeholder for the user interface component into view; and
execute the additional code to render the user interface component. 2. The system of claim 1, wherein the code that renders the graphical placeholder is configured to load the additional code from a client-side cache. 3. The system of claim 1, wherein the code that renders the graphical placeholder is configured to request the additional code from the at least one computing device. 4. The system of claim 1, wherein the additional code is configured to:
determine that a user interaction with the user interface component has occurred; receive control code that controls the user interface component from the at least one computing device; and execute the control code to process the user interaction. 5. The system of claim 4, wherein the control code is executed to process a queue of events associated with the user interaction and to render an updated view of the user interface component in response to processing the queue of events. 6. The system of claim 4, wherein the user interaction comprises a selection of a button of the user interface component, and the control code is configured to process playback of media. 7. The system of claim 1, wherein the additional code is configured to:
determine that the graphical placeholder has been rendered on a display at least a predefined length of time; receive control code that controls the user interface component from the at least one computing device; and execute the control code. 8. The system of claim 1, wherein the user interface component includes a plurality of user interface elements. 9. A method, comprising:
receiving, via at least one of one or more computing devices, a network page from at least one server, the network page including code that renders a graphical placeholder for a user interface component; executing, via at least one of the one or more computing devices, the code that renders the graphical placeholder for the user interface component; receiving, via at least one of the one or more computing devices, code that renders an updated view of the user interface component from the at least one server in response to a scrolling action or a viewport manipulation bringing the graphical placeholder for the user interface component into view; and executing, via at least one of the one or more computing devices, the code that renders the updated view of the user interface component. 10. The method of claim 9, further comprising determining, via at least one of the one or more computing devices, that the graphical placeholder has been rendered on a display for at least a predetermined length of time. 11. The method of claim 9, further comprising caching, via at least one of the one or more computing devices, the code that renders the updated view of the user interface component. 12. The method of claim 9, further comprising asynchronously requesting, via at least one of the one or more computing devices, data from the at least one server based at least in part on a user interaction with the updated view of the user interface component. 13. The method of claim 9, wherein the updated view of the user interface component is configured to appear fully functional but lacks at least a portion of functionality. 14. The method of claim 9, wherein the code that renders the updated view of the user interface component further comprises controller logic for the user interface component. 15. The method of claim 9, further comprising:
determining, via at least one of the one or more computing devices, that the graphical placeholder has been rendered on a display at least a predefined length of time; receiving, via at least one of the one or more computing devices, control code that controls the user interface component from the at least one server; and executing, via at least one of the one or more computing devices, the control code. 16. The method of claim 9, further comprising:
determining, via at least one of the one or more computing devices, that a user interaction with the user interface component has occurred; receiving, via at least one of the one or more computing devices, control code that controls the user interface component from the at least one server; and executing, via at least one of the one or more computing devices, the control code to process the user interaction. 17. A non-transitory computer-readable medium embodying a program executable in at least one computing device, wherein when executed the program causes the at least one computing device to at least:
render a user interface that includes a graphical placeholder for a user interface component; load additional code that renders the user interface component in response to a scrolling action or a viewport manipulation bringing the graphical placeholder for the user interface component into view; and execute the additional code to render the user interface component. 18. The non-transitory computer-readable medium of claim 17, wherein the program is configured to defer loading of media playback code until a user interacts with an initial view of the user interface component. 19. The non-transitory computer-readable medium of claim 17, wherein the additional code is loaded over a data communications network. 20. The non-transitory computer-readable medium of claim 17, wherein the additional code is loaded via inter-process communication. | 2,100 |
6,599 | 6,599 | 16,004,869 | 2,159 | During an annotation technique, an electronic device may receive an optical image associated with an object and other sensor information associated with the object, where the optical image and the other sensor information have associated timestamps that are concurrent or in close temporal proximity. Then, the electronic device may identify the object based at least in part on the optical image and/or the other sensor information. Moreover, the electronic device may extract a signature associated with the object from the other sensor information. The signature may include: a range to the object, a first angle to the object along a first axis, Doppler information associated with the object and/or a second angle to the object along a second axis. Next, the electronic device may store annotation information associated with the identified object and the extracted signature in a data structure in memory. | 1. An electronic device, comprising:
an interface circuit configured to communicate with a first sensor and a second sensor; memory; and an integrated circuit, coupled to the interface circuit and the memory, which is configured to:
measure, using the first sensor, an optical image associated with an object and, using the second sensor, other sensor information associated with the object, wherein the optical image and the other sensor information have associated timestamps that are concurrent or temporal proximity less than a predefined amount, wherein the measuring is dynamically adapted based at least in part on environmental conditions, and wherein the other sensor information comprises radar information;
identify the object based at least in part on the optical image;
determine, using a predictive model, predefined or predetermined annotation information for the object;
extract a signature associated with the object from the other sensor information; and
store the predefined or predetermined annotation information associated with the identified object and the extracted signature in a data structure in the memory to generate an annotated dataset of the extracted signature from the radar information using the optical image. 2. The electronic device of claim 1, wherein the integrated circuit is configured to provide one or more signals or instructions to the first sensor to acquire the optical image and to the second sensor to perform another measurement of the other sensor information. 3. The electronic device of claim 1, wherein the electronic device comprises the second sensor that is configured to perform the radar measurements; and
wherein the second sensor comprises multiple antennas, including a first subset of the antennas are configured to transmit radar signals and a second subset of the antennas are configured to receive reflected radar signals. 4. The electronic device of claim 3, wherein the integrated circuit is configured to dynamically adapt at least one of the first subset or the second subset. 5. The electronic device of claim 1, wherein the integrated circuit is configured to train a second predictive model based at least in part on information in the data structure; and
wherein the second predictive model uses the extracted signature and the predefined or predetermined annotation as inputs, and outputs an identification or classification of one or more objects. 6. (canceled) 7. The electronic device of claim 1, wherein the signature comprises one or more of: a range to the object, a first angle to the object along a first axis, Doppler information associated with the object, and a second angle to the object along a second axis. 8. The electronic device of claim 1, wherein the electronic device comprises the first sensor that is configured to perform optical imaging. 9. (canceled) 10. The electronic device of claim 1, wherein the integrated circuit comprises a processor;
wherein the memory stores program instructions, which, when executed by the processor, causes the electronic device to perform the receiving, the identifying, the extracting and the storing. 11. A non-transitory computer-readable storage medium for use in conjunction with an electronic device, the computer-readable storage medium storing program instructions, wherein, when executed by the computer system, the program instructions cause the computer system to perform one or more operations comprising:
measuring, using a first sensor, an optical image associated with an object and, using a second sensor, other sensor information associated with the object, wherein the optical image and the other sensor information have associated timestamps that are concurrent or temporal proximity less than a predefined amount, wherein the measuring is dynamically adapted based at least in part on environmental conditions, and wherein the other sensor information comprises radar information; identifying the object based at least in part on the optical image; determining, using a predictive model, predefined or predetermined annotation information for the object; extracting a signature associated with the object from the other sensor information; and storing the predefined or predetermined annotation information associated with the identified object and the extracted signature in a data structure in memory in or associated with the electronic device to generate an annotated dataset of the extracted signature from the radar information using the optical image. 12. The computer-readable storage medium of claim 11, wherein the one or more operations comprise providing one or more signals or instructions to the first sensor to acquire the optical image and to the second sensor to perform another measurement of the other sensor information. 13. The computer-readable storage medium of claim 11, wherein the second sensor performs the radar measurements using multiple antennas;
wherein a first subset of the antennas transmits radar signals and a second subset of the antennas receive reflected radar signals; and wherein the one or more operations comprises dynamically adapting at least one of the first subset or the second subset. 14. The computer-readable storage medium of claim 11, wherein the one or more operations comprise training a second predictive model based at least in part on information in the data structure; and
wherein the second predictive model uses the extracted signature and the predefined or predetermined annotation as inputs, and outputs an identification or classification of one or more objects. 15. (canceled) 16. The computer-readable storage medium of claim 11, wherein the signature comprises one or more of: a range to the object, a first angle to the object along a first axis, Doppler information associated with the object, and a second angle to the object along a second axis. 17. A method for generating an annotated dataset, comprising:
by an electronic device:
measuring, using a first sensor, an optical image associated with an object and, using a second sensor, other sensor information associated with the object, wherein the optical image and the other sensor information have associated timestamps that are concurrent or temporal proximity less than a predefined amount, wherein the measuring is dynamically adapted based at least in part on environmental conditions, and wherein the other sensor information comprises radar information;
identifying the object based at least in part on the optical image;
determining, using a predictive model, predefined or predetermined annotation information for the object;
extracting a signature associated with the object from the other sensor information; and
generating the annotated dataset of the extracted signature from the radar information using the optical image by storing the predefined or predetermined annotation information associated with the identified object and the extracted signature in memory in or associated with the electronic device. 18. The method of claim 17, wherein the method comprises providing one or more signals or instructions to the first sensor to acquire the optical image and to the second sensor to perform another measurement of the other sensor information. 19. (canceled) 20. The method of claim 17, wherein the signature comprises one or more of: a range to the object, a first angle to the object along a first axis, Doppler information associated with the object, and a second angle to the object along a second axis. 21. The method of claim 17, wherein the method comprises training a second predictive model based at least in part on information in the data structure; and
wherein the second predictive model uses the extracted signature and the predefined or predetermined annotation as inputs, and outputs an identification or classification of one or more objects. 22. The method of claim 17, wherein the second sensor performs the radar measurements; and
wherein the second sensor comprises multiple antennas, including a first subset of the antennas that transmit radar signals and a second subset of the antennas that receive reflected radar signals. 23. The method of claim 22, wherein the method comprises dynamically adapting at least one of the first subset or the second subset. | During an annotation technique, an electronic device may receive an optical image associated with an object and other sensor information associated with the object, where the optical image and the other sensor information have associated timestamps that are concurrent or in close temporal proximity. Then, the electronic device may identify the object based at least in part on the optical image and/or the other sensor information. Moreover, the electronic device may extract a signature associated with the object from the other sensor information. The signature may include: a range to the object, a first angle to the object along a first axis, Doppler information associated with the object and/or a second angle to the object along a second axis. Next, the electronic device may store annotation information associated with the identified object and the extracted signature in a data structure in memory.1. An electronic device, comprising:
an interface circuit configured to communicate with a first sensor and a second sensor; memory; and an integrated circuit, coupled to the interface circuit and the memory, which is configured to:
measure, using the first sensor, an optical image associated with an object and, using the second sensor, other sensor information associated with the object, wherein the optical image and the other sensor information have associated timestamps that are concurrent or temporal proximity less than a predefined amount, wherein the measuring is dynamically adapted based at least in part on environmental conditions, and wherein the other sensor information comprises radar information;
identify the object based at least in part on the optical image;
determine, using a predictive model, predefined or predetermined annotation information for the object;
extract a signature associated with the object from the other sensor information; and
store the predefined or predetermined annotation information associated with the identified object and the extracted signature in a data structure in the memory to generate an annotated dataset of the extracted signature from the radar information using the optical image. 2. The electronic device of claim 1, wherein the integrated circuit is configured to provide one or more signals or instructions to the first sensor to acquire the optical image and to the second sensor to perform another measurement of the other sensor information. 3. The electronic device of claim 1, wherein the electronic device comprises the second sensor that is configured to perform the radar measurements; and
wherein the second sensor comprises multiple antennas, including a first subset of the antennas are configured to transmit radar signals and a second subset of the antennas are configured to receive reflected radar signals. 4. The electronic device of claim 3, wherein the integrated circuit is configured to dynamically adapt at least one of the first subset or the second subset. 5. The electronic device of claim 1, wherein the integrated circuit is configured to train a second predictive model based at least in part on information in the data structure; and
wherein the second predictive model uses the extracted signature and the predefined or predetermined annotation as inputs, and outputs an identification or classification of one or more objects. 6. (canceled) 7. The electronic device of claim 1, wherein the signature comprises one or more of: a range to the object, a first angle to the object along a first axis, Doppler information associated with the object, and a second angle to the object along a second axis. 8. The electronic device of claim 1, wherein the electronic device comprises the first sensor that is configured to perform optical imaging. 9. (canceled) 10. The electronic device of claim 1, wherein the integrated circuit comprises a processor;
wherein the memory stores program instructions, which, when executed by the processor, causes the electronic device to perform the receiving, the identifying, the extracting and the storing. 11. A non-transitory computer-readable storage medium for use in conjunction with an electronic device, the computer-readable storage medium storing program instructions, wherein, when executed by the computer system, the program instructions cause the computer system to perform one or more operations comprising:
measuring, using a first sensor, an optical image associated with an object and, using a second sensor, other sensor information associated with the object, wherein the optical image and the other sensor information have associated timestamps that are concurrent or temporal proximity less than a predefined amount, wherein the measuring is dynamically adapted based at least in part on environmental conditions, and wherein the other sensor information comprises radar information; identifying the object based at least in part on the optical image; determining, using a predictive model, predefined or predetermined annotation information for the object; extracting a signature associated with the object from the other sensor information; and storing the predefined or predetermined annotation information associated with the identified object and the extracted signature in a data structure in memory in or associated with the electronic device to generate an annotated dataset of the extracted signature from the radar information using the optical image. 12. The computer-readable storage medium of claim 11, wherein the one or more operations comprise providing one or more signals or instructions to the first sensor to acquire the optical image and to the second sensor to perform another measurement of the other sensor information. 13. The computer-readable storage medium of claim 11, wherein the second sensor performs the radar measurements using multiple antennas;
wherein a first subset of the antennas transmits radar signals and a second subset of the antennas receive reflected radar signals; and wherein the one or more operations comprises dynamically adapting at least one of the first subset or the second subset. 14. The computer-readable storage medium of claim 11, wherein the one or more operations comprise training a second predictive model based at least in part on information in the data structure; and
wherein the second predictive model uses the extracted signature and the predefined or predetermined annotation as inputs, and outputs an identification or classification of one or more objects. 15. (canceled) 16. The computer-readable storage medium of claim 11, wherein the signature comprises one or more of: a range to the object, a first angle to the object along a first axis, Doppler information associated with the object, and a second angle to the object along a second axis. 17. A method for generating an annotated dataset, comprising:
by an electronic device:
measuring, using a first sensor, an optical image associated with an object and, using a second sensor, other sensor information associated with the object, wherein the optical image and the other sensor information have associated timestamps that are concurrent or temporal proximity less than a predefined amount, wherein the measuring is dynamically adapted based at least in part on environmental conditions, and wherein the other sensor information comprises radar information;
identifying the object based at least in part on the optical image;
determining, using a predictive model, predefined or predetermined annotation information for the object;
extracting a signature associated with the object from the other sensor information; and
generating the annotated dataset of the extracted signature from the radar information using the optical image by storing the predefined or predetermined annotation information associated with the identified object and the extracted signature in memory in or associated with the electronic device. 18. The method of claim 17, wherein the method comprises providing one or more signals or instructions to the first sensor to acquire the optical image and to the second sensor to perform another measurement of the other sensor information. 19. (canceled) 20. The method of claim 17, wherein the signature comprises one or more of: a range to the object, a first angle to the object along a first axis, Doppler information associated with the object, and a second angle to the object along a second axis. 21. The method of claim 17, wherein the method comprises training a second predictive model based at least in part on information in the data structure; and
wherein the second predictive model uses the extracted signature and the predefined or predetermined annotation as inputs, and outputs an identification or classification of one or more objects. 22. The method of claim 17, wherein the second sensor performs the radar measurements; and
wherein the second sensor comprises multiple antennas, including a first subset of the antennas that transmit radar signals and a second subset of the antennas that receive reflected radar signals. 23. The method of claim 22, wherein the method comprises dynamically adapting at least one of the first subset or the second subset. | 2,100 |
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