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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6,000 | 6,000 | 15,741,830 | 2,133 | An apparatus ( 2 ) comprises one or more bounded pointer storage element ( 60 s ) each to store a pointer ( 62 ) having associated range information ( 64 ) indicating an allowable range of addresses for the pointer ( 62 ). Processing circuitry ( 4 ) performs, in response to a first type of instruction ( 70 ) identifying a given bounded pointer storage element, a predetermined operation for a target range of addresses determined at least in part on the basis of the range information ( 64 ) associated with the pointer stored in the given bounded pointer storage element ( 60 ). | 1. An apparatus comprising:
one or more bounded pointer storage elements, each to store a pointer having associated range information indicative of an allowable range of addresses for said pointer; and processing circuitry to perform, in response to a first type of instruction identifying a given bounded pointer storage element, a predetermined operation for a target range of addresses determined at least in part on the basis of the range information associated with the pointer stored in the given bounded pointer storage element. 2. The apparatus according to claim 1, wherein the allowable range of addresses comprises the target range of addresses. 3. The apparatus according to claim 1, wherein the target range of addresses comprises all of the addresses within the allowable range of addresses. 4. The apparatus according to claim 1, wherein the target range of addresses comprises the addresses between an address indicated by the pointer and an upper address or lower address of the allowable range of addresses. 5. The apparatus according to claim 1, wherein the one or more bounded pointer storage elements comprise one or more registers. 6. The apparatus according to claim 1, wherein in response to a second type of instruction identifying a specified bounded pointer storage element, the processing circuitry is configured to perform an operation on the pointer stored in said specified bounded pointer storage element. 7. The apparatus according to claim 6, wherein in response to the second type of instruction, the processing circuitry is configured to trigger an error condition when an address determined using the pointer stored in said specified bounded pointer storage element is outside the allowable range of addresses indicated by the range information for the specified bounded pointer storage element. 8. The apparatus according to claim 6, wherein said second type of instruction comprises an instruction for setting the pointer stored in said specified bounded pointer storage element. 9. The apparatus according to claim 6, wherein said second type of instruction comprises an instruction for accessing a data value from the address determined using the pointer stored in said specified bounded pointer storage element. 10. The apparatus according to claim 1, comprising a cache comprising a plurality of entries each to store data associated with a corresponding address; and
said first type of instruction comprises a cache maintenance instruction for which the predetermined operation comprises performing a cache maintenance operation on selected entries for which the corresponding address is within the target range of addresses. 11. The apparatus according to claim 10, wherein the cache comprises at least one of:
a data cache; an instruction cache; a translation lookaside buffer; and a branch target address cache. 12. The apparatus according to claim 10, wherein the cache maintenance operation comprises one of:
invalidating the data in the selected entries; cleaning data in the selected entries; and cleaning and invalidating data in the selected entries. 13. The apparatus according to claim 1, wherein the first type of instruction comprises a setting instruction for which the predetermined operation comprises setting data values to a predetermined value for each address in the target range of addresses. 14. The apparatus according to claim 1, wherein the first type of instruction comprises a copy instruction for which the predetermined operation comprises copying respective data values to each address in the target range of addresses. 15. The apparatus according to claim 14, wherein the copy instruction specifies a second bounded pointer storage element for which the allowable range of addresses indicated by the range information identifies a range of addresses of storage locations storing the respective data values to be copied. 16. The apparatus according to claim 1, wherein the first type of instruction comprises a search instruction for which the predetermined operation comprises searching for a specified value at each address in the target range of addresses. 17. The apparatus according to claim 1, wherein said predetermined operation is independent of the value of said pointer stored in the given bounded pointer storage element. 18. The apparatus according to claim 1, wherein in response to an interrupt occurring after performing the predetermined operation for some of the target range of addresses, the processing circuitry is configured to update the pointer in the given bounded pointer storage element to indicate an address at which the predetermined operation was interrupted; and
after returning from processing of the interrupt, the processing circuitry is configured to restart performing the predetermined operation at the address indicated by the pointer in the given bounded pointer storage element. 19. The apparatus according to claim 1, wherein each bounded pointer storage element is configured to store the pointer and the associated range information. 20. The apparatus according to claim 1, comprising a further storage element to store the associated range information for the pointer stored in a corresponding bounded pointer storage element. 21. The apparatus according to claim 1, wherein the range information identifies a lower bound and an upper bound for the allowable range of addresses. 22. The apparatus according to claim 1, wherein the range information identifies one of a lower bound and an upper bound for the allowable range of addresses, and a size of the allowable range of addresses. 23. An apparatus comprising:
at least one means for storing a pointer having associated range information indicative of an allowable range of addresses for said pointer; and means for performing, in response to a first type of instruction identifying a given means for storing, a predetermined operation for a target range of addresses determined at least in part on the basis of the range information associated with the pointer stored in the given means for storing. 24. A method for an apparatus comprising one or more bounded pointer storage element, each to store a pointer having associated range information indicative of an allowable range of addresses for said pointer; the method comprising:
receiving a first type of instruction identifying a given bounded pointer storage element; and in response to the first type of instruction, performing a predetermined operation for a target range of addresses determined at least in part on the basis of the range information associated with the pointer stored in the given bounded pointer storage element. | An apparatus ( 2 ) comprises one or more bounded pointer storage element ( 60 s ) each to store a pointer ( 62 ) having associated range information ( 64 ) indicating an allowable range of addresses for the pointer ( 62 ). Processing circuitry ( 4 ) performs, in response to a first type of instruction ( 70 ) identifying a given bounded pointer storage element, a predetermined operation for a target range of addresses determined at least in part on the basis of the range information ( 64 ) associated with the pointer stored in the given bounded pointer storage element ( 60 ).1. An apparatus comprising:
one or more bounded pointer storage elements, each to store a pointer having associated range information indicative of an allowable range of addresses for said pointer; and processing circuitry to perform, in response to a first type of instruction identifying a given bounded pointer storage element, a predetermined operation for a target range of addresses determined at least in part on the basis of the range information associated with the pointer stored in the given bounded pointer storage element. 2. The apparatus according to claim 1, wherein the allowable range of addresses comprises the target range of addresses. 3. The apparatus according to claim 1, wherein the target range of addresses comprises all of the addresses within the allowable range of addresses. 4. The apparatus according to claim 1, wherein the target range of addresses comprises the addresses between an address indicated by the pointer and an upper address or lower address of the allowable range of addresses. 5. The apparatus according to claim 1, wherein the one or more bounded pointer storage elements comprise one or more registers. 6. The apparatus according to claim 1, wherein in response to a second type of instruction identifying a specified bounded pointer storage element, the processing circuitry is configured to perform an operation on the pointer stored in said specified bounded pointer storage element. 7. The apparatus according to claim 6, wherein in response to the second type of instruction, the processing circuitry is configured to trigger an error condition when an address determined using the pointer stored in said specified bounded pointer storage element is outside the allowable range of addresses indicated by the range information for the specified bounded pointer storage element. 8. The apparatus according to claim 6, wherein said second type of instruction comprises an instruction for setting the pointer stored in said specified bounded pointer storage element. 9. The apparatus according to claim 6, wherein said second type of instruction comprises an instruction for accessing a data value from the address determined using the pointer stored in said specified bounded pointer storage element. 10. The apparatus according to claim 1, comprising a cache comprising a plurality of entries each to store data associated with a corresponding address; and
said first type of instruction comprises a cache maintenance instruction for which the predetermined operation comprises performing a cache maintenance operation on selected entries for which the corresponding address is within the target range of addresses. 11. The apparatus according to claim 10, wherein the cache comprises at least one of:
a data cache; an instruction cache; a translation lookaside buffer; and a branch target address cache. 12. The apparatus according to claim 10, wherein the cache maintenance operation comprises one of:
invalidating the data in the selected entries; cleaning data in the selected entries; and cleaning and invalidating data in the selected entries. 13. The apparatus according to claim 1, wherein the first type of instruction comprises a setting instruction for which the predetermined operation comprises setting data values to a predetermined value for each address in the target range of addresses. 14. The apparatus according to claim 1, wherein the first type of instruction comprises a copy instruction for which the predetermined operation comprises copying respective data values to each address in the target range of addresses. 15. The apparatus according to claim 14, wherein the copy instruction specifies a second bounded pointer storage element for which the allowable range of addresses indicated by the range information identifies a range of addresses of storage locations storing the respective data values to be copied. 16. The apparatus according to claim 1, wherein the first type of instruction comprises a search instruction for which the predetermined operation comprises searching for a specified value at each address in the target range of addresses. 17. The apparatus according to claim 1, wherein said predetermined operation is independent of the value of said pointer stored in the given bounded pointer storage element. 18. The apparatus according to claim 1, wherein in response to an interrupt occurring after performing the predetermined operation for some of the target range of addresses, the processing circuitry is configured to update the pointer in the given bounded pointer storage element to indicate an address at which the predetermined operation was interrupted; and
after returning from processing of the interrupt, the processing circuitry is configured to restart performing the predetermined operation at the address indicated by the pointer in the given bounded pointer storage element. 19. The apparatus according to claim 1, wherein each bounded pointer storage element is configured to store the pointer and the associated range information. 20. The apparatus according to claim 1, comprising a further storage element to store the associated range information for the pointer stored in a corresponding bounded pointer storage element. 21. The apparatus according to claim 1, wherein the range information identifies a lower bound and an upper bound for the allowable range of addresses. 22. The apparatus according to claim 1, wherein the range information identifies one of a lower bound and an upper bound for the allowable range of addresses, and a size of the allowable range of addresses. 23. An apparatus comprising:
at least one means for storing a pointer having associated range information indicative of an allowable range of addresses for said pointer; and means for performing, in response to a first type of instruction identifying a given means for storing, a predetermined operation for a target range of addresses determined at least in part on the basis of the range information associated with the pointer stored in the given means for storing. 24. A method for an apparatus comprising one or more bounded pointer storage element, each to store a pointer having associated range information indicative of an allowable range of addresses for said pointer; the method comprising:
receiving a first type of instruction identifying a given bounded pointer storage element; and in response to the first type of instruction, performing a predetermined operation for a target range of addresses determined at least in part on the basis of the range information associated with the pointer stored in the given bounded pointer storage element. | 2,100 |
6,001 | 6,001 | 15,006,723 | 2,176 | One embodiment provides a method, including: accepting, at an input surface, ink input; determining, using a processor, typeset for the ink input; providing, on a display, a combined display of the ink input and the typeset; where the combined display visually associates the ink input and the typeset. Other aspects are described and claimed. | 1. A method, comprising:
accepting, at an input surface, ink input; determining, using a processor, typeset for the ink input; providing, on a display, a combined display of the ink input and the typeset; wherein said combined display visually associates the ink input and the typeset. 2. The method of claim 1, wherein the combined display comprises a side-by-side display of the ink input and the typeset. 3. The method of claim 2, wherein the providing a combined display comprises scaling the typeset. 4. The method of claim 3, wherein the scaling proceeds dynamically in response to added ink input. 5. The method of claim 1, wherein the combined display comprises a first view and a second view; each of the first view and the second view comprising one of the ink input and the typeset. 6. The method of claim 5, wherein the second view comprises a window. 7. The method of claim 6, wherein the window is displayed responsive to user input. 8. The method of claim 7, wherein the window is displayed in association with a cursor location. 9. The method of claim 1, wherein the combined display visually associates the ink input and the typeset dynamically. 10. The method of claim 9, wherein the combined display visually associates the ink input and the typeset dynamically by highlighting one or more of an ink input portion and a typeset word associated with a cursor location. 11. A device, comprising:
a display; an input surface; a processor operatively coupled to the display and the input surface; a memory device that stores instructions executable by the processor to: accept, at the input surface, ink input; determine typeset for the ink input; provide, on the display, a combined display of the ink input and the typeset; wherein said combined display visually associates the ink input and the typeset. 12. The device of claim 11, wherein the combined display comprises a side-by-side display of the ink input and the typeset. 13. The device of claim 12, wherein the instructions executed by the processor to provide a combined display comprise instructions to scale the typeset. 14. The device of claim 13, wherein the instructions executable by the processor to scale proceed dynamically in response to added ink input. 15. The device of claim 11, wherein the combined display comprises a first view and a second view; each of the first view and the second view comprising one of the ink input and the typeset. 16. The device of claim 15, wherein the second view comprises a window. 17. The device of claim 16, wherein the window is displayed responsive to user input. 18. The device of claim 17, wherein the window is displayed in association with a cursor location. 19. The device of claim 11, wherein:
the combined display visually associates the ink input and the typeset dynamically; and wherein the combined display visually associates the ink input and the typeset dynamically by highlighting one or more of an ink input portion and a typeset word associated with a cursor location. 20. A product, comprising:
a storage device having code stored therewith, the code being executable by a processor and comprising: code that accepts, at an input surface, ink input; code that determines, using a processor, typeset for the ink input; code that provides, on a display, a combined display of the ink input and the typeset; wherein said combined display visually associates the ink input and the typeset. | One embodiment provides a method, including: accepting, at an input surface, ink input; determining, using a processor, typeset for the ink input; providing, on a display, a combined display of the ink input and the typeset; where the combined display visually associates the ink input and the typeset. Other aspects are described and claimed.1. A method, comprising:
accepting, at an input surface, ink input; determining, using a processor, typeset for the ink input; providing, on a display, a combined display of the ink input and the typeset; wherein said combined display visually associates the ink input and the typeset. 2. The method of claim 1, wherein the combined display comprises a side-by-side display of the ink input and the typeset. 3. The method of claim 2, wherein the providing a combined display comprises scaling the typeset. 4. The method of claim 3, wherein the scaling proceeds dynamically in response to added ink input. 5. The method of claim 1, wherein the combined display comprises a first view and a second view; each of the first view and the second view comprising one of the ink input and the typeset. 6. The method of claim 5, wherein the second view comprises a window. 7. The method of claim 6, wherein the window is displayed responsive to user input. 8. The method of claim 7, wherein the window is displayed in association with a cursor location. 9. The method of claim 1, wherein the combined display visually associates the ink input and the typeset dynamically. 10. The method of claim 9, wherein the combined display visually associates the ink input and the typeset dynamically by highlighting one or more of an ink input portion and a typeset word associated with a cursor location. 11. A device, comprising:
a display; an input surface; a processor operatively coupled to the display and the input surface; a memory device that stores instructions executable by the processor to: accept, at the input surface, ink input; determine typeset for the ink input; provide, on the display, a combined display of the ink input and the typeset; wherein said combined display visually associates the ink input and the typeset. 12. The device of claim 11, wherein the combined display comprises a side-by-side display of the ink input and the typeset. 13. The device of claim 12, wherein the instructions executed by the processor to provide a combined display comprise instructions to scale the typeset. 14. The device of claim 13, wherein the instructions executable by the processor to scale proceed dynamically in response to added ink input. 15. The device of claim 11, wherein the combined display comprises a first view and a second view; each of the first view and the second view comprising one of the ink input and the typeset. 16. The device of claim 15, wherein the second view comprises a window. 17. The device of claim 16, wherein the window is displayed responsive to user input. 18. The device of claim 17, wherein the window is displayed in association with a cursor location. 19. The device of claim 11, wherein:
the combined display visually associates the ink input and the typeset dynamically; and wherein the combined display visually associates the ink input and the typeset dynamically by highlighting one or more of an ink input portion and a typeset word associated with a cursor location. 20. A product, comprising:
a storage device having code stored therewith, the code being executable by a processor and comprising: code that accepts, at an input surface, ink input; code that determines, using a processor, typeset for the ink input; code that provides, on a display, a combined display of the ink input and the typeset; wherein said combined display visually associates the ink input and the typeset. | 2,100 |
6,002 | 6,002 | 14,754,675 | 2,198 | In filtering requests to be forwarded to a runtime environment, a filtering apparatus intercepts a new runtime request for the runtime environment and determines execution paths that may be traversed by the runtime request when executed in the runtime environment. The filtering apparatus assigns a probability of traversal by the runtime request to each of the execution paths and identifies at least one given execution path that reference a stressed resource of the runtime environment. Based on the probabilities assigned to the at least one given execution path, the filtering apparatus determines whether or not to block the runtime request from being sent to the runtime environment. If the probability assigned to the at least one given execution path exceeds a configured threshold, the runtime request is blocked from being sent to the runtime environment. Otherwise, the runtime request is sent to the runtime environment. | 1. A method for filtering requests to be forwarded to a runtime environment, comprising:
intercepting a new runtime request for the runtime environment; determining one or more execution paths that may be traversed by the runtime request when executed in the runtime environment; assigning a probability of traversal by the runtime request to each of the one or more execution paths; identifying at least one given execution path of the one or more execution paths that reference a stressed resource of the runtime environment; and based on the probabilities assigned to the at least one given execution path, determining whether or not to block the runtime request from being sent to the runtime environment. 2. The method of claim 1, wherein the determining whether or not to block the runtime request from being sent to the runtime environment comprises:
in response to determining that the probability assigned to the at least one given execution path exceeds a configured threshold, blocking the runtime request from being sent to the runtime environment; and in response to determining that the probability assigned to the at least one given execution path does not exceed the configured threshold, sending the runtime request to the runtime environment. 3. The method of claim 1, wherein the determining of the one or more execution paths that may be traversed by the runtime request when executed in the runtime environment comprises:
determining a request class to which the runtime request belongs; mapping the request class to a resource tree comprising one or more sub-trees, wherein the resource tree represents one or more resources in the runtime environment, wherein the one or more sub-trees represent the one or more execution paths; and identifying one or more of the sub-trees that may be traversed by the runtime request when executed in the runtime environment. 4. The method of claim 3, wherein the identifying of the one or more of the sub-trees that may be traversed by the runtime request when executed in the runtime environment comprises:
when no execution history exists for the runtime request, deducing the one or more sub-trees from an application deployment descriptor. 5. The method of claim 1, wherein the assigning of the probability of traversal by the runtime request to each of the one or more execution paths comprises:
when no execution history exists for the runtime request, assigning each execution path the same probability. 6. The method of claim 1, wherein the assigning of the probability of traversal by the runtime request to each of the one or more execution paths comprises:
when an execution history exists for the runtime request, assigning each execution path a probability based on a percentage of runtime requests that historically used the execution path. 7. The method of claim 1, wherein the identifying of the at least one given execution path of the one or more execution paths that reference the stressed resource of the runtime environment comprises:
receiving an alert from a monitoring tool coupled to the runtime environment that a given resource is stressed; and determining that the at least one given execution path references the given resource. 8. A computer program product for filtering requests to be forwarded to a runtime environment, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising:
intercepting a new runtime request for the runtime environment; determining one or more execution paths that may be traversed by the runtime request when executed in the runtime environment; assigning a probability of traversal by the runtime request to each of the one or more execution paths; identifying at least one given execution path of the one or more execution paths that reference a stressed resource of the runtime environment; and based on the probabilities assigned to the at least one given execution path, determining whether or not to block the runtime request from being sent to the runtime environment. 9. The computer program product of claim 8, wherein the determining whether or not to block the runtime request from being sent to the runtime environment comprises:
in response to determining that the probability assigned to the at least one given execution path exceeds a configured threshold, blocking the runtime request from being sent to the runtime environment; and in response to determining that the probability assigned to the at least one given execution path does not exceed the configured threshold, sending the runtime request to the runtime environment. 10. The computer program product of claim 8, wherein the determining of the one or more execution paths that may be traversed by the runtime request when executed in the runtime environment comprises:
determining a request class to which the runtime request belongs; mapping the request class to a resource tree comprising one or more sub-trees, wherein the resource tree represents one or more resources in the runtime environment, wherein the one or more sub-trees represent the one or more execution paths; and identifying one or more of the sub-trees that may be traversed by the runtime request when executed in the runtime environment. 11. The computer program product of claim 10, wherein the identifying of the one or more of the sub-trees that may be traversed by the runtime request when executed in the runtime environment comprises:
when no execution history exists for the runtime request, deducing the one or more sub-trees from an application deployment descriptor. 12. The computer program product of claim 8, wherein the assigning of the probability of traversal by the runtime request to each of the one or more execution paths comprises:
when no execution history exists for the runtime request, assigning each execution path a same probability. 13. The computer program product of claim 8, wherein the assigning of the probability of traversal by the runtime request to each of the one or more execution paths comprises:
when an execution history exists for the runtime request, assigning each execution path a probability based on a percentage of runtime requests that historically used the execution path. 14. The computer program product of claim 8, wherein the identifying of the at least one given execution path of the one or more execution paths that reference the stressed resource of the runtime environment comprises:
receiving an alert from a monitoring tool coupled to the runtime environment that a given resource is stressed; and determining that the at least one given execution path references the given resource. 15. A system, comprising:
a processor; and a computer readable storage medium having program instructions embodied therewith, the program instructions executable by the processor to cause the processor to perform a method comprising: intercepting a new runtime request for the runtime environment; determining one or more execution paths that may be traversed by the runtime request when executed in the runtime environment; assigning a probability of traversal by the runtime request to each of the one or more execution paths; identifying at least one given execution path of the one or more execution paths that reference a stressed resource of the runtime environment; and based on the probabilities assigned to the at least one given execution path, determining whether or not to block the runtime request from being sent to the runtime environment. 16. The system of claim 15, wherein the determining whether or not to block the runtime request from being sent to the runtime environment comprises:
in response to determining that the probability assigned to the at least one given execution path exceeds a configured threshold, blocking the runtime request from being sent to the runtime environment; and in response to determining that the probability assigned to the at least one given execution path does not exceed the configured threshold, sending the runtime request to the runtime environment. 17. The system of claim 15, wherein the determining of the one or more execution paths that may be traversed by the runtime request when executed in the runtime environment comprises:
determining a request class to which the runtime request belongs; mapping the request class to a resource tree comprising one or more sub-trees, wherein the resource tree represents one or more resources in the runtime environment, wherein the one or more sub-tress represent the one or more execution paths; and identifying one or more of the sub-trees that may be traversed by the runtime request when executed in the runtime environment. 18. The system of claim 15, wherein the assigning of the probability of traversal by the runtime request to each of the one or more execution paths comprises:
when no execution history exists for the runtime request, assigning each execution path a same probability. 19. The system of claim 15, wherein the assigning of the probability of traversal by the runtime request to each of the one or more execution paths comprises:
when an execution history exists for the runtime request, assigning each execution path a probability based on a percentage of runtime requests that historically used the execution path. 20. The system of claim 15, wherein the identifying of the at least one given execution path of the one or more execution paths that reference the stressed resource of the runtime environment comprises:
receiving an alert from a monitoring tool coupled to the runtime environment that a given resource is stressed; and determining that the at least one given execution path references the given resource. | In filtering requests to be forwarded to a runtime environment, a filtering apparatus intercepts a new runtime request for the runtime environment and determines execution paths that may be traversed by the runtime request when executed in the runtime environment. The filtering apparatus assigns a probability of traversal by the runtime request to each of the execution paths and identifies at least one given execution path that reference a stressed resource of the runtime environment. Based on the probabilities assigned to the at least one given execution path, the filtering apparatus determines whether or not to block the runtime request from being sent to the runtime environment. If the probability assigned to the at least one given execution path exceeds a configured threshold, the runtime request is blocked from being sent to the runtime environment. Otherwise, the runtime request is sent to the runtime environment.1. A method for filtering requests to be forwarded to a runtime environment, comprising:
intercepting a new runtime request for the runtime environment; determining one or more execution paths that may be traversed by the runtime request when executed in the runtime environment; assigning a probability of traversal by the runtime request to each of the one or more execution paths; identifying at least one given execution path of the one or more execution paths that reference a stressed resource of the runtime environment; and based on the probabilities assigned to the at least one given execution path, determining whether or not to block the runtime request from being sent to the runtime environment. 2. The method of claim 1, wherein the determining whether or not to block the runtime request from being sent to the runtime environment comprises:
in response to determining that the probability assigned to the at least one given execution path exceeds a configured threshold, blocking the runtime request from being sent to the runtime environment; and in response to determining that the probability assigned to the at least one given execution path does not exceed the configured threshold, sending the runtime request to the runtime environment. 3. The method of claim 1, wherein the determining of the one or more execution paths that may be traversed by the runtime request when executed in the runtime environment comprises:
determining a request class to which the runtime request belongs; mapping the request class to a resource tree comprising one or more sub-trees, wherein the resource tree represents one or more resources in the runtime environment, wherein the one or more sub-trees represent the one or more execution paths; and identifying one or more of the sub-trees that may be traversed by the runtime request when executed in the runtime environment. 4. The method of claim 3, wherein the identifying of the one or more of the sub-trees that may be traversed by the runtime request when executed in the runtime environment comprises:
when no execution history exists for the runtime request, deducing the one or more sub-trees from an application deployment descriptor. 5. The method of claim 1, wherein the assigning of the probability of traversal by the runtime request to each of the one or more execution paths comprises:
when no execution history exists for the runtime request, assigning each execution path the same probability. 6. The method of claim 1, wherein the assigning of the probability of traversal by the runtime request to each of the one or more execution paths comprises:
when an execution history exists for the runtime request, assigning each execution path a probability based on a percentage of runtime requests that historically used the execution path. 7. The method of claim 1, wherein the identifying of the at least one given execution path of the one or more execution paths that reference the stressed resource of the runtime environment comprises:
receiving an alert from a monitoring tool coupled to the runtime environment that a given resource is stressed; and determining that the at least one given execution path references the given resource. 8. A computer program product for filtering requests to be forwarded to a runtime environment, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising:
intercepting a new runtime request for the runtime environment; determining one or more execution paths that may be traversed by the runtime request when executed in the runtime environment; assigning a probability of traversal by the runtime request to each of the one or more execution paths; identifying at least one given execution path of the one or more execution paths that reference a stressed resource of the runtime environment; and based on the probabilities assigned to the at least one given execution path, determining whether or not to block the runtime request from being sent to the runtime environment. 9. The computer program product of claim 8, wherein the determining whether or not to block the runtime request from being sent to the runtime environment comprises:
in response to determining that the probability assigned to the at least one given execution path exceeds a configured threshold, blocking the runtime request from being sent to the runtime environment; and in response to determining that the probability assigned to the at least one given execution path does not exceed the configured threshold, sending the runtime request to the runtime environment. 10. The computer program product of claim 8, wherein the determining of the one or more execution paths that may be traversed by the runtime request when executed in the runtime environment comprises:
determining a request class to which the runtime request belongs; mapping the request class to a resource tree comprising one or more sub-trees, wherein the resource tree represents one or more resources in the runtime environment, wherein the one or more sub-trees represent the one or more execution paths; and identifying one or more of the sub-trees that may be traversed by the runtime request when executed in the runtime environment. 11. The computer program product of claim 10, wherein the identifying of the one or more of the sub-trees that may be traversed by the runtime request when executed in the runtime environment comprises:
when no execution history exists for the runtime request, deducing the one or more sub-trees from an application deployment descriptor. 12. The computer program product of claim 8, wherein the assigning of the probability of traversal by the runtime request to each of the one or more execution paths comprises:
when no execution history exists for the runtime request, assigning each execution path a same probability. 13. The computer program product of claim 8, wherein the assigning of the probability of traversal by the runtime request to each of the one or more execution paths comprises:
when an execution history exists for the runtime request, assigning each execution path a probability based on a percentage of runtime requests that historically used the execution path. 14. The computer program product of claim 8, wherein the identifying of the at least one given execution path of the one or more execution paths that reference the stressed resource of the runtime environment comprises:
receiving an alert from a monitoring tool coupled to the runtime environment that a given resource is stressed; and determining that the at least one given execution path references the given resource. 15. A system, comprising:
a processor; and a computer readable storage medium having program instructions embodied therewith, the program instructions executable by the processor to cause the processor to perform a method comprising: intercepting a new runtime request for the runtime environment; determining one or more execution paths that may be traversed by the runtime request when executed in the runtime environment; assigning a probability of traversal by the runtime request to each of the one or more execution paths; identifying at least one given execution path of the one or more execution paths that reference a stressed resource of the runtime environment; and based on the probabilities assigned to the at least one given execution path, determining whether or not to block the runtime request from being sent to the runtime environment. 16. The system of claim 15, wherein the determining whether or not to block the runtime request from being sent to the runtime environment comprises:
in response to determining that the probability assigned to the at least one given execution path exceeds a configured threshold, blocking the runtime request from being sent to the runtime environment; and in response to determining that the probability assigned to the at least one given execution path does not exceed the configured threshold, sending the runtime request to the runtime environment. 17. The system of claim 15, wherein the determining of the one or more execution paths that may be traversed by the runtime request when executed in the runtime environment comprises:
determining a request class to which the runtime request belongs; mapping the request class to a resource tree comprising one or more sub-trees, wherein the resource tree represents one or more resources in the runtime environment, wherein the one or more sub-tress represent the one or more execution paths; and identifying one or more of the sub-trees that may be traversed by the runtime request when executed in the runtime environment. 18. The system of claim 15, wherein the assigning of the probability of traversal by the runtime request to each of the one or more execution paths comprises:
when no execution history exists for the runtime request, assigning each execution path a same probability. 19. The system of claim 15, wherein the assigning of the probability of traversal by the runtime request to each of the one or more execution paths comprises:
when an execution history exists for the runtime request, assigning each execution path a probability based on a percentage of runtime requests that historically used the execution path. 20. The system of claim 15, wherein the identifying of the at least one given execution path of the one or more execution paths that reference the stressed resource of the runtime environment comprises:
receiving an alert from a monitoring tool coupled to the runtime environment that a given resource is stressed; and determining that the at least one given execution path references the given resource. | 2,100 |
6,003 | 6,003 | 15,707,140 | 2,116 | An illustrative example system for monitoring a plurality of events in a manufacturing facility includes a plurality of monitoring devices. Each of the monitoring devices obtains data regarding a selected one of the events. A reporting device receives the data obtained by the monitoring devices and provides a report regarding the monitored events. The report includes information regarding at least one characteristic of each of the monitored events. The information in the report is dynamically updated to provide a real time indication of the characteristics of the monitored events. The real time indications are presented in respective cells of the report. | 1. A system for monitoring a plurality of events in a manufacturing facility, the system comprising:
a plurality of monitoring devices, each of the monitoring devices obtains data regarding a selected one of the events; and a reporting device that receives the data obtained by the monitoring devices and provides a report regarding the monitored events, the report including information regarding at least one characteristic of each of the monitored events, the information in the report being dynamically updated to provide a real time indication of the characteristics of the monitored events, the real time indications being presented in respective cells of the report, wherein: a first set of the cells provides at least one indication of a machine or equipment involved in at least one of the monitored events, a second set of the cells provides an indication of a status of a machine or equipment having an indication in the first set of the cells, a third set of the cells provides an indication of a total run time for a machine or equipment having an indication in the first set of cells, a fourth set of the cells provides an indication of a number of cycles performed by a machine or equipment having an indication in the first set of cells, at least one of the monitoring devices includes a housing mounted in a selected location relative to a selected machine, the at least one of the monitoring devices includes a memory and a processor in the housing, the at least one of the monitoring devices includes a plurality of user-defined inputs embedded in the memory or the processor, the user-defined inputs configure the at least one of the monitoring devices to obtain selected information regarding operation of the selected machine, the at least one of the monitoring devices providing a real-time, dynamically updated output to an individual machine operator of the selected machine regarding current operation of the selected machine. 2. The system of claim 1, wherein
the reporting device includes a display; and the report is visually perceivable on the display. 3. The system of claim 1, wherein the reporting device provides the report in a spreadsheet format. 4. The system of claim 1, wherein the reporting device includes a memory portion that contains a record of the indications of the report over time. 5. The system of claim 1, wherein
at least one of the monitoring devices is configured to obtain the data from a sensor that is configured to provide information regarding the corresponding selected one of the events. 6. The system of claim 1, wherein
at least one of the monitoring devices comprises a sensor configured to obtain the data regarding the corresponding selected one of the events. 7. The system of claim 1, wherein at least one of the monitoring devices comprises
a processor for interpreting the data and providing the information to be included in the report; and a memory portion for at least temporarily retaining the data obtained by the at least one of the monitoring devices. 8. The system of claim 1, wherein the monitoring devices communicate with the reporting device. 9. The system of claim 1, comprising
a communication hub that receives data from the monitoring devices and communicates the received data to the reporting device. 10. A method of monitoring a plurality of events in a manufacturing facility, the method comprising the steps of:
obtaining data regarding the events from monitoring devices; communicating the obtained data to a reporting device; providing a report regarding the monitored events, the report including information regarding at least one characteristic of each of the monitored events; dynamically updating the information of the report to provide a real time indication of the characteristics of the monitored events; presenting the real time indications in respective cells of the report; and using at least one of the reporting device or one of the monitoring devices to provide a real-time, dynamically updated output to an individual machine operator of a selected machine regarding current operation of the selected machine, wherein: the real-time, dynamically updated output comprises a plurality of cells, a first set of the cells provides at least one indication of a machine or equipment involved in at least one of the monitored events, a second set of the cells provides an indication of a status of a machine or equipment having an indication in the first set of the cells, a third set of the cells provides an indication of a total run time for a machine or equipment having an indication in the first set of cells, a fourth set of the cells provides an indication of a number of cycles performed by a machine or equipment having an indication in the first set of cells, the at least one of the monitoring devices includes a housing mounted in a selected location relative to the selected machine, the at least one of the monitoring devices includes a memory and a processor in the housing, the at least one of the monitoring devices includes a plurality of user-defined inputs embedded in the memory or the processor, and the user-defined inputs configure the at least one of the monitoring devices to obtain selected information regarding operation of the selected machine. 11. The method of claim 10, comprising
displaying the report in a visually perceivable format on a display. 12. The method of claim 10, comprising providing the report in a spreadsheet format. 13. The method of claim 10, comprising maintaining a record of the indications of the report over time in a memory associated with the reporting device. 14. The method of claim 10, comprising communicating the data from the monitoring devices to the reporting device. 15. The method of claim 10, comprising
communicating the data from the monitoring devices to a communication hub; and communicating at least one of the data or the report information from the communication hub to the reporting device. 16. The method of claim 10, comprising providing the real-time, dynamically updated output to the machine operator on a display screen. 17. A manufacturing machine, comprising:
a machine portion that is configured to at least partially complete at least one manufacturing process in an automated fashion; and at least one monitoring device including a housing mounted in a selected location relative to the machine portion, the at least one monitoring device including a memory and a processor in the housing, the at least one monitoring device including a plurality of user-defined inputs embedded in the memory or the processor, the user-defined inputs configuring the at least one monitoring device to obtain selected information regarding operation of the machine portion while completing the at least one process; and a reporting device that receives the selected information obtained by the monitoring devices, wherein: at least one of the reporting device and the at least one monitoring device provides a real-time, dynamically updated output to an individual machine operator of the machine regarding current operation of the selected machine, the real-time, dynamically updated output comprises a plurality of cells, a first set of the cells provides at least one indication of a machine or equipment involved in at least one of the monitored events, a second set of the cells provides an indication of a status of a machine or equipment having an indication in the first set of the cells, a third set of the cells provides an indication of a total run time for a machine or equipment having an indication in the first set of cells, and a fourth set of the cells provides an indication of a number of cycles performed by a machine or equipment having an indication in the first set of cells. 18. The machine of claim 17, comprising a display screen associated with the reporting device, the display screen providing the real-time, dynamically updated output to the machine operator. | An illustrative example system for monitoring a plurality of events in a manufacturing facility includes a plurality of monitoring devices. Each of the monitoring devices obtains data regarding a selected one of the events. A reporting device receives the data obtained by the monitoring devices and provides a report regarding the monitored events. The report includes information regarding at least one characteristic of each of the monitored events. The information in the report is dynamically updated to provide a real time indication of the characteristics of the monitored events. The real time indications are presented in respective cells of the report.1. A system for monitoring a plurality of events in a manufacturing facility, the system comprising:
a plurality of monitoring devices, each of the monitoring devices obtains data regarding a selected one of the events; and a reporting device that receives the data obtained by the monitoring devices and provides a report regarding the monitored events, the report including information regarding at least one characteristic of each of the monitored events, the information in the report being dynamically updated to provide a real time indication of the characteristics of the monitored events, the real time indications being presented in respective cells of the report, wherein: a first set of the cells provides at least one indication of a machine or equipment involved in at least one of the monitored events, a second set of the cells provides an indication of a status of a machine or equipment having an indication in the first set of the cells, a third set of the cells provides an indication of a total run time for a machine or equipment having an indication in the first set of cells, a fourth set of the cells provides an indication of a number of cycles performed by a machine or equipment having an indication in the first set of cells, at least one of the monitoring devices includes a housing mounted in a selected location relative to a selected machine, the at least one of the monitoring devices includes a memory and a processor in the housing, the at least one of the monitoring devices includes a plurality of user-defined inputs embedded in the memory or the processor, the user-defined inputs configure the at least one of the monitoring devices to obtain selected information regarding operation of the selected machine, the at least one of the monitoring devices providing a real-time, dynamically updated output to an individual machine operator of the selected machine regarding current operation of the selected machine. 2. The system of claim 1, wherein
the reporting device includes a display; and the report is visually perceivable on the display. 3. The system of claim 1, wherein the reporting device provides the report in a spreadsheet format. 4. The system of claim 1, wherein the reporting device includes a memory portion that contains a record of the indications of the report over time. 5. The system of claim 1, wherein
at least one of the monitoring devices is configured to obtain the data from a sensor that is configured to provide information regarding the corresponding selected one of the events. 6. The system of claim 1, wherein
at least one of the monitoring devices comprises a sensor configured to obtain the data regarding the corresponding selected one of the events. 7. The system of claim 1, wherein at least one of the monitoring devices comprises
a processor for interpreting the data and providing the information to be included in the report; and a memory portion for at least temporarily retaining the data obtained by the at least one of the monitoring devices. 8. The system of claim 1, wherein the monitoring devices communicate with the reporting device. 9. The system of claim 1, comprising
a communication hub that receives data from the monitoring devices and communicates the received data to the reporting device. 10. A method of monitoring a plurality of events in a manufacturing facility, the method comprising the steps of:
obtaining data regarding the events from monitoring devices; communicating the obtained data to a reporting device; providing a report regarding the monitored events, the report including information regarding at least one characteristic of each of the monitored events; dynamically updating the information of the report to provide a real time indication of the characteristics of the monitored events; presenting the real time indications in respective cells of the report; and using at least one of the reporting device or one of the monitoring devices to provide a real-time, dynamically updated output to an individual machine operator of a selected machine regarding current operation of the selected machine, wherein: the real-time, dynamically updated output comprises a plurality of cells, a first set of the cells provides at least one indication of a machine or equipment involved in at least one of the monitored events, a second set of the cells provides an indication of a status of a machine or equipment having an indication in the first set of the cells, a third set of the cells provides an indication of a total run time for a machine or equipment having an indication in the first set of cells, a fourth set of the cells provides an indication of a number of cycles performed by a machine or equipment having an indication in the first set of cells, the at least one of the monitoring devices includes a housing mounted in a selected location relative to the selected machine, the at least one of the monitoring devices includes a memory and a processor in the housing, the at least one of the monitoring devices includes a plurality of user-defined inputs embedded in the memory or the processor, and the user-defined inputs configure the at least one of the monitoring devices to obtain selected information regarding operation of the selected machine. 11. The method of claim 10, comprising
displaying the report in a visually perceivable format on a display. 12. The method of claim 10, comprising providing the report in a spreadsheet format. 13. The method of claim 10, comprising maintaining a record of the indications of the report over time in a memory associated with the reporting device. 14. The method of claim 10, comprising communicating the data from the monitoring devices to the reporting device. 15. The method of claim 10, comprising
communicating the data from the monitoring devices to a communication hub; and communicating at least one of the data or the report information from the communication hub to the reporting device. 16. The method of claim 10, comprising providing the real-time, dynamically updated output to the machine operator on a display screen. 17. A manufacturing machine, comprising:
a machine portion that is configured to at least partially complete at least one manufacturing process in an automated fashion; and at least one monitoring device including a housing mounted in a selected location relative to the machine portion, the at least one monitoring device including a memory and a processor in the housing, the at least one monitoring device including a plurality of user-defined inputs embedded in the memory or the processor, the user-defined inputs configuring the at least one monitoring device to obtain selected information regarding operation of the machine portion while completing the at least one process; and a reporting device that receives the selected information obtained by the monitoring devices, wherein: at least one of the reporting device and the at least one monitoring device provides a real-time, dynamically updated output to an individual machine operator of the machine regarding current operation of the selected machine, the real-time, dynamically updated output comprises a plurality of cells, a first set of the cells provides at least one indication of a machine or equipment involved in at least one of the monitored events, a second set of the cells provides an indication of a status of a machine or equipment having an indication in the first set of the cells, a third set of the cells provides an indication of a total run time for a machine or equipment having an indication in the first set of cells, and a fourth set of the cells provides an indication of a number of cycles performed by a machine or equipment having an indication in the first set of cells. 18. The machine of claim 17, comprising a display screen associated with the reporting device, the display screen providing the real-time, dynamically updated output to the machine operator. | 2,100 |
6,004 | 6,004 | 15,851,742 | 2,199 | The present invention relates to a method and system for installing software onto a client in the NIM environment and corresponding client. Said method includes: initializing said client, wherein a virtual mapping device associated with a memory driver of the client is created, the virtual mapping device for scheduling between the client's memory driver and the remote NIM server with respect to the I/O operation for running the software so as to direct the I/O operation for running said software to the client's memory driver or the remote NIM server; running said software on the client; acquiring the resources desired for running software; and conducting data migration operation from the NIM server to the client while running said software, wherein the migrated data is the resource data obtained from NIM server and desired for installing said software; and the software installation being completed when all the data desired for installing said software are migrated to the memory driver of the client. It is unnecessary for the present invention to copy all the installation images to the local client before installing software, therefore time delay of installing OSs or application programs can be shortened or even eliminated. | 1-14. (canceled) 15. A computer-implemented method for installing software, comprising:
receiving, by a Network Installation Management (NIM) server and from a client, a request to establish communication between the NIM server and the client; and sending, to the client and from the NIM server and while the software is executing on the client, migrated data, wherein a virtual mapping device associated with a memory driver of the client is created in the client responsive to installation of the software being initialized, the migrated data is resource data obtained from NIM server and used for installing the software, and the virtual mapping device is used for scheduling between the memory driver and the NIM server with respect to an I/O operation for running the software so as to direct the I/O operation to the memory driver or the remote NIM server. 16. The method of claim 15, wherein
the I/O operation directed to the memory driver is redirected to the virtual mapping device. 17. The method of claim 15, wherein
an address space mapping table is created for the memory driver, and a location of a resource for the I/O operation is determined based upon the address space mapping table. 18. The method of claim 17, wherein
the address space mapping table records physical locations of resources used for executing the software, and the physical locations include both the client and the NIM server. 19. The method of claim 17, wherein
the address space mapping table is updated as a resource is received from the NIM server. 20. The method of claim 17, wherein
upon the I/O operation being a write request operation, data is written onto a corresponding address the memory driver. 21. The method of claim 15, wherein
an I/O operation for running the software is scheduled by the virtual mapping device so as to direct the I/O operation for running software to at least one of the following:
the memory driver of the client, or
the NIM server that is remote from the client. 22. A Network Installation Management (NIM) server configured to install software, comprising:
a hardware processor configured to initiate the following executable operations:
receiving, from a client, a request to establish communication between the NIM server and the client; and
sending, to the client and while the software is executing on the client, migrated data, wherein
a virtual mapping device associated with a memory driver of the client is created in the client responsive to installation of the software being initialized, the migrated data is resource data obtained from NIM server and used for installing the software, and the virtual mapping device is used for scheduling between the memory driver and the NIM server with respect to an I/O operation for running the software so as to direct the I/O operation to the memory driver or the remote NIM server. 23. The system of claim 22, wherein
the I/O operation directed to the memory driver is redirected to the virtual mapping device. 24. The system of claim 22, wherein
an address space mapping table is created for the memory driver, and a location of a resource for the I/O operation is determined based upon the address space mapping table. 25. The system of claim 24, wherein
the address space mapping table records physical locations of resources used for executing the software, and the physical locations include both the client and the NIM server. 26. The system of claim 24, wherein
the address space mapping table is updated as a resource is received from the NIM server. 27. The system of claim 24, wherein
upon the I/O operation being a write request operation, data is written onto a corresponding address the memory driver. 28. The system of claim 22, wherein
an I/O operation for running the software is scheduled by the virtual mapping device so as to direct the I/O operation for running software to at least one of the following:
the memory driver of the client, or
the NIM server that is remote from the client. 29. A computer program product, comprising:
a hardware storage device having stored therein computer usable program code for installing software, the computer usable program code, which when executed by a Network Installation Management (NIM) server, causes the NIM server to perform:
receiving, from a client, a request to establish communication between the NIM server and the client; and
sending, to the client and while the software is executing on the client, migrated data, wherein
a virtual mapping device associated with a memory driver of the client is created in the client responsive to installation of the software being initialized, the migrated data is resource data obtained from NIM server and used for installing the software, and the virtual mapping device is used for scheduling between the memory driver and the NIM server with respect to an I/O operation for running the software so as to direct the I/O operation to the memory driver or the remote NIM server. 30. The computer program product of claim 29, wherein
the I/O operation directed to the memory driver is redirected to the virtual mapping device. 31. The computer program product of claim 29, wherein
an address space mapping table is created for the memory driver, and a location of a resource for the I/O operation is determined based upon the address space mapping table. 32. The computer program product of claim 31, wherein
the address space mapping table records physical locations of resources used for executing the software, and the physical locations include both the client and the NIM server. 33. The computer program product of claim 31, wherein
the address space mapping table is updated as a resource is received from the NIM server. 34. The computer program product of claim 29, wherein
an I/O operation for running the software is scheduled by the virtual mapping device so as to direct the I/O operation for running software to at least one of the following:
the memory driver of the client, or
the NIM server that is remote from the client. | The present invention relates to a method and system for installing software onto a client in the NIM environment and corresponding client. Said method includes: initializing said client, wherein a virtual mapping device associated with a memory driver of the client is created, the virtual mapping device for scheduling between the client's memory driver and the remote NIM server with respect to the I/O operation for running the software so as to direct the I/O operation for running said software to the client's memory driver or the remote NIM server; running said software on the client; acquiring the resources desired for running software; and conducting data migration operation from the NIM server to the client while running said software, wherein the migrated data is the resource data obtained from NIM server and desired for installing said software; and the software installation being completed when all the data desired for installing said software are migrated to the memory driver of the client. It is unnecessary for the present invention to copy all the installation images to the local client before installing software, therefore time delay of installing OSs or application programs can be shortened or even eliminated.1-14. (canceled) 15. A computer-implemented method for installing software, comprising:
receiving, by a Network Installation Management (NIM) server and from a client, a request to establish communication between the NIM server and the client; and sending, to the client and from the NIM server and while the software is executing on the client, migrated data, wherein a virtual mapping device associated with a memory driver of the client is created in the client responsive to installation of the software being initialized, the migrated data is resource data obtained from NIM server and used for installing the software, and the virtual mapping device is used for scheduling between the memory driver and the NIM server with respect to an I/O operation for running the software so as to direct the I/O operation to the memory driver or the remote NIM server. 16. The method of claim 15, wherein
the I/O operation directed to the memory driver is redirected to the virtual mapping device. 17. The method of claim 15, wherein
an address space mapping table is created for the memory driver, and a location of a resource for the I/O operation is determined based upon the address space mapping table. 18. The method of claim 17, wherein
the address space mapping table records physical locations of resources used for executing the software, and the physical locations include both the client and the NIM server. 19. The method of claim 17, wherein
the address space mapping table is updated as a resource is received from the NIM server. 20. The method of claim 17, wherein
upon the I/O operation being a write request operation, data is written onto a corresponding address the memory driver. 21. The method of claim 15, wherein
an I/O operation for running the software is scheduled by the virtual mapping device so as to direct the I/O operation for running software to at least one of the following:
the memory driver of the client, or
the NIM server that is remote from the client. 22. A Network Installation Management (NIM) server configured to install software, comprising:
a hardware processor configured to initiate the following executable operations:
receiving, from a client, a request to establish communication between the NIM server and the client; and
sending, to the client and while the software is executing on the client, migrated data, wherein
a virtual mapping device associated with a memory driver of the client is created in the client responsive to installation of the software being initialized, the migrated data is resource data obtained from NIM server and used for installing the software, and the virtual mapping device is used for scheduling between the memory driver and the NIM server with respect to an I/O operation for running the software so as to direct the I/O operation to the memory driver or the remote NIM server. 23. The system of claim 22, wherein
the I/O operation directed to the memory driver is redirected to the virtual mapping device. 24. The system of claim 22, wherein
an address space mapping table is created for the memory driver, and a location of a resource for the I/O operation is determined based upon the address space mapping table. 25. The system of claim 24, wherein
the address space mapping table records physical locations of resources used for executing the software, and the physical locations include both the client and the NIM server. 26. The system of claim 24, wherein
the address space mapping table is updated as a resource is received from the NIM server. 27. The system of claim 24, wherein
upon the I/O operation being a write request operation, data is written onto a corresponding address the memory driver. 28. The system of claim 22, wherein
an I/O operation for running the software is scheduled by the virtual mapping device so as to direct the I/O operation for running software to at least one of the following:
the memory driver of the client, or
the NIM server that is remote from the client. 29. A computer program product, comprising:
a hardware storage device having stored therein computer usable program code for installing software, the computer usable program code, which when executed by a Network Installation Management (NIM) server, causes the NIM server to perform:
receiving, from a client, a request to establish communication between the NIM server and the client; and
sending, to the client and while the software is executing on the client, migrated data, wherein
a virtual mapping device associated with a memory driver of the client is created in the client responsive to installation of the software being initialized, the migrated data is resource data obtained from NIM server and used for installing the software, and the virtual mapping device is used for scheduling between the memory driver and the NIM server with respect to an I/O operation for running the software so as to direct the I/O operation to the memory driver or the remote NIM server. 30. The computer program product of claim 29, wherein
the I/O operation directed to the memory driver is redirected to the virtual mapping device. 31. The computer program product of claim 29, wherein
an address space mapping table is created for the memory driver, and a location of a resource for the I/O operation is determined based upon the address space mapping table. 32. The computer program product of claim 31, wherein
the address space mapping table records physical locations of resources used for executing the software, and the physical locations include both the client and the NIM server. 33. The computer program product of claim 31, wherein
the address space mapping table is updated as a resource is received from the NIM server. 34. The computer program product of claim 29, wherein
an I/O operation for running the software is scheduled by the virtual mapping device so as to direct the I/O operation for running software to at least one of the following:
the memory driver of the client, or
the NIM server that is remote from the client. | 2,100 |
6,005 | 6,005 | 15,006,230 | 2,119 | A part analysis tool is used to analyze aspects of a composite part. The part analysis tool includes a verification control unit that compares numerical control data used to control operation of a forming system that is used to form the composite part to computer-aided design (CAD) data that includes an authoritative part definition for the composite part. The verification control unit determines whether the numerical control data is within one or more conformance thresholds related to the CAD data. The part analysis tool may also include an inspection control unit that compares inspection data of one or more plies of the composite part to the CAD data. The inspection control unit determines whether the inspection data is within the conformance threshold(s) related to the CAD data. | 1. A part analysis tool for analyzing aspects of a composite part, the part analysis tool comprising:
a verification control unit that compares numerical control data used to control operation of a forming system that is used to form the composite part to computer-aided design (CAD) data that includes an authoritative part definition for the composite part, wherein the verification control unit determines whether the numerical control data is within one or more conformance thresholds related to the CAD data. 2. The part analysis tool of claim 1, wherein the verification control unit disregards non-essential data within the numerical control data. 3. The part analysis tool of claim 2, wherein the non-essential data is unrelated to laying up plies of composite material that form the composite part. 4. The part analysis tool of claim 1, wherein the numerical control data comprises structural and geometric data of the composite part. 5. The part analysis tool of claim 4, wherein the structural and geometric data of the composite part comprises part length, number of plies of composite material, ply boundary areas, stagger between plies, ply orientation, and angular deviation between plies. 6. The part analysis tool of claim 1, further comprising an inspection control unit that compares inspection data of one or more plies of the composite part to the CAD data, wherein the inspection control unit determines whether the inspection data is within the one or more conformance thresholds related to the CAD data. 7. The part analysis tool of claim 6, wherein the inspection control unit compares the inspection data to the CAD data after the verification control unit compares the numerical control data to the CAD data. 8. The part analysis tool of claim 6, wherein the inspection control unit compares the inspection data to the CAD data as the verification control unit compares the numerical control data to the CAD data. 9. The part analysis tool of claim 6, wherein the inspection control unit analyzes the inspection data of a virtual representation of the composite part. 10. A composite part forming system configured to form a composite part, wherein the composite part forming system comprises:
a computer-aided design (CAD) system operable to generate CAD data that includes an authoritative part definition for the composite part; a forming system operable to form the composite part based on numerical control data; an inspection system operable to inspect the composite part before, during, or after formation of the composite part and generate inspection data that relates to inspection of the composite part; and a part analysis tool comprising: (a) a verification control unit that compares the numerical control data used to control operation of the forming system to the CAD data, wherein the verification control unit determines whether the numerical control data is within one or more conformance thresholds related to the CAD data, and (b) an inspection control unit that compares the inspection data to the CAD data, wherein the inspection control unit determines whether the inspection data is within the one or more conformance thresholds related to the CAD data. 11. The composite part forming system of claim 10, wherein the verification control unit disregards non-essential data within the numerical control data, wherein the non-essential data is unrelated to laying up plies of composite material that form the composite part, and wherein the numerical control data comprises structural and geometric data of the composite part. 12. The composite part forming system of claim 11, wherein the structural and geometric data of the composite part comprises part length, number of plies of composite material, ply boundary areas, stagger between plies, ply orientation, and angular deviation between plies. 13. The composite part forming system of claim 11, wherein the inspection control unit compares the inspection data to the CAD data after the verification control unit compares the numerical control data to the CAD data. 14. The composite part forming system of claim 11, wherein the inspection control unit compares the inspection data to the CAD data as the verification control unit compares the numerical control data to the CAD data. 15. The composite part forming system of claim 11, wherein the inspection control unit analyzes the inspection data of a virtual representation of the composite part. 16. A method for analyzing aspects of a composite part, the method comprising:
generating computer-aided design (CAD) data that includes an authoritative part definition for the composite part; receiving numerical control data used to control operation of a forming system that is used to form the composite part; comparing the numerical control data to the CAD data; determining, through the comparing the numerical control data to the CAD data, whether the numerical control data is within one or more conformance thresholds related to the CAD data; receiving inspection data of one or more plies of the composite part; comparing the inspection data to the CAD data; and determining, through the comparing the inspection data to the CAD data, whether the inspection data is within the one or more conformance thresholds related to the CAD data. 17. The method of claim 16, wherein the comparing the numerical control data to the CAD data comprises disregarding non-essential data within the numerical control data, wherein the non-essential data is unrelated to laying up plies of composite material that form the composite part, and wherein the numerical control data comprises structural and geometric data of the composite part. 18. The method of claim 17, wherein the structural and geometric data of the composite part comprises part length, number of plies of composite material, ply boundary areas, stagger between plies, ply orientation, and angular deviation between plies. 19. The method of claim 16, wherein the comparing the inspection data to the CAD data is concurrent with the comparing the numerical control data to the CAD data. 20. The method of claim 16, wherein the receiving the inspection data comprises receiving the inspection data of a virtual representation of the composite part. | A part analysis tool is used to analyze aspects of a composite part. The part analysis tool includes a verification control unit that compares numerical control data used to control operation of a forming system that is used to form the composite part to computer-aided design (CAD) data that includes an authoritative part definition for the composite part. The verification control unit determines whether the numerical control data is within one or more conformance thresholds related to the CAD data. The part analysis tool may also include an inspection control unit that compares inspection data of one or more plies of the composite part to the CAD data. The inspection control unit determines whether the inspection data is within the conformance threshold(s) related to the CAD data.1. A part analysis tool for analyzing aspects of a composite part, the part analysis tool comprising:
a verification control unit that compares numerical control data used to control operation of a forming system that is used to form the composite part to computer-aided design (CAD) data that includes an authoritative part definition for the composite part, wherein the verification control unit determines whether the numerical control data is within one or more conformance thresholds related to the CAD data. 2. The part analysis tool of claim 1, wherein the verification control unit disregards non-essential data within the numerical control data. 3. The part analysis tool of claim 2, wherein the non-essential data is unrelated to laying up plies of composite material that form the composite part. 4. The part analysis tool of claim 1, wherein the numerical control data comprises structural and geometric data of the composite part. 5. The part analysis tool of claim 4, wherein the structural and geometric data of the composite part comprises part length, number of plies of composite material, ply boundary areas, stagger between plies, ply orientation, and angular deviation between plies. 6. The part analysis tool of claim 1, further comprising an inspection control unit that compares inspection data of one or more plies of the composite part to the CAD data, wherein the inspection control unit determines whether the inspection data is within the one or more conformance thresholds related to the CAD data. 7. The part analysis tool of claim 6, wherein the inspection control unit compares the inspection data to the CAD data after the verification control unit compares the numerical control data to the CAD data. 8. The part analysis tool of claim 6, wherein the inspection control unit compares the inspection data to the CAD data as the verification control unit compares the numerical control data to the CAD data. 9. The part analysis tool of claim 6, wherein the inspection control unit analyzes the inspection data of a virtual representation of the composite part. 10. A composite part forming system configured to form a composite part, wherein the composite part forming system comprises:
a computer-aided design (CAD) system operable to generate CAD data that includes an authoritative part definition for the composite part; a forming system operable to form the composite part based on numerical control data; an inspection system operable to inspect the composite part before, during, or after formation of the composite part and generate inspection data that relates to inspection of the composite part; and a part analysis tool comprising: (a) a verification control unit that compares the numerical control data used to control operation of the forming system to the CAD data, wherein the verification control unit determines whether the numerical control data is within one or more conformance thresholds related to the CAD data, and (b) an inspection control unit that compares the inspection data to the CAD data, wherein the inspection control unit determines whether the inspection data is within the one or more conformance thresholds related to the CAD data. 11. The composite part forming system of claim 10, wherein the verification control unit disregards non-essential data within the numerical control data, wherein the non-essential data is unrelated to laying up plies of composite material that form the composite part, and wherein the numerical control data comprises structural and geometric data of the composite part. 12. The composite part forming system of claim 11, wherein the structural and geometric data of the composite part comprises part length, number of plies of composite material, ply boundary areas, stagger between plies, ply orientation, and angular deviation between plies. 13. The composite part forming system of claim 11, wherein the inspection control unit compares the inspection data to the CAD data after the verification control unit compares the numerical control data to the CAD data. 14. The composite part forming system of claim 11, wherein the inspection control unit compares the inspection data to the CAD data as the verification control unit compares the numerical control data to the CAD data. 15. The composite part forming system of claim 11, wherein the inspection control unit analyzes the inspection data of a virtual representation of the composite part. 16. A method for analyzing aspects of a composite part, the method comprising:
generating computer-aided design (CAD) data that includes an authoritative part definition for the composite part; receiving numerical control data used to control operation of a forming system that is used to form the composite part; comparing the numerical control data to the CAD data; determining, through the comparing the numerical control data to the CAD data, whether the numerical control data is within one or more conformance thresholds related to the CAD data; receiving inspection data of one or more plies of the composite part; comparing the inspection data to the CAD data; and determining, through the comparing the inspection data to the CAD data, whether the inspection data is within the one or more conformance thresholds related to the CAD data. 17. The method of claim 16, wherein the comparing the numerical control data to the CAD data comprises disregarding non-essential data within the numerical control data, wherein the non-essential data is unrelated to laying up plies of composite material that form the composite part, and wherein the numerical control data comprises structural and geometric data of the composite part. 18. The method of claim 17, wherein the structural and geometric data of the composite part comprises part length, number of plies of composite material, ply boundary areas, stagger between plies, ply orientation, and angular deviation between plies. 19. The method of claim 16, wherein the comparing the inspection data to the CAD data is concurrent with the comparing the numerical control data to the CAD data. 20. The method of claim 16, wherein the receiving the inspection data comprises receiving the inspection data of a virtual representation of the composite part. | 2,100 |
6,006 | 6,006 | 14,792,746 | 2,176 | Managing document annotations in a publish/subscribe system is described. A publishing system creates annotations of a document that include references to where the annotations are to be displayed; stores the annotations separately from the document; names an annotation set using tags; sets roles and permissions for use of the annotation set, including access permissions based on a time and/or location constraint of a subscribing user; and publishes the annotation set to a publish/subscribe broker for access by the subscribing users. A subscribing system subscribes a user to annotations of a document, wherein each annotation is separate from the document and includes reference to where the annotations are to be displayed. The subscribing system also defines a role of the subscribing user, wherein use permissions of the annotations by the subscribing user are controlled based on the role, including time and/or location constraints of the subscribing user. | 1-14. (canceled) 15. A publishing system for managing document annotations in a publish/subscribe system, comprising:
an annotation creation component for creating annotations of a document, the annotations including reference for display of the annotations in relation to display of the document, the annotation creation component further for storing the annotations separately from the document; an annotation control component including:
a tagging component for naming a set of the annotations using at least one tag; and
a role and permission component for setting roles and permissions for use of the set of the annotations by subscribing users including setting access permissions based on at least one constraint selected from a group consisting of a time constraint and a location constraint of a subscribing user; and
an annotation publication component for publishing the set of the annotations to a publish/subscribe broker for access by subscribing users. 16. The publishing system of claim 15, wherein the setting the access permissions based on the at least one constraint is applied based on at least one of a group consisting of a subscription time, a subscription location of the subscribing user, a display time, and a display location of the subscribing user. 17. The publishing system of claim 15, further comprising:
an annotation update publication component for re-publishing updates of the set of the annotations. 18. A subscribing system for managing document annotations in a publish/subscribe system, comprising:
an annotation subscription component for subscribing a user to annotations of a document, wherein each annotation is separate from the document and includes reference to display of the annotation in relation to display of the document; and a role and permission component for defining a role of the subscribing user, wherein use permissions of a set of the annotations by the subscribing user are controlled based on the role, the use permissions including access permissions based on at least one constraint selected from a group consisting of a time constraint and a location constraint of the subscribing user. 19. The subscribing system as claimed in claim 18, further comprising:
a filter component for filtering, using at least one tag, the subscription of the subscribing user to the set of the annotations. 20. The subscribing system as claimed in claim 18, further comprising:
a display options component for displaying the set of the annotations on the document at the subscribing user as pseudo annotations and further for enabling the subscribing user to select to burn the set of the annotations into a local copy of the document. 21. A computer program product for managing document annotations in a publish/subscribe system as carried out at a publishing system, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
create annotations of a document, the annotations including reference to locations for display of the annotations in relation to display of the document; store the annotations separately from the document; name a set of the annotations using at least one tag; set roles and permissions for use of the set of the annotations by subscribing users including setting access permissions based on at least one constraint selected from a group consisting of a time constraint and a location constraint of a subscribing user; and publish the set of the annotations to a publish/subscribe broker for access by the subscribing users. 22. The computer program product of claim 21, wherein the setting the access permissions based on the at least one constraint is applied based on at least one item selected from the group consisting of a subscription time of the subscribing user and a subscription location of the subscribing user. 23. The computer program product of claim 21, wherein the setting the access permissions based on the at least one constraint is applied based on at least one item selected from the group consisting of a displaying time of the subscribing user and a displaying location of the subscribing user. 24. The computer program product of claim 21, wherein the setting the roles and the permissions further includes setting editing permissions for the subscribing users. 25. The computer program product of claim 21, wherein the program instructions are executable by the processor to further cause the processor to:
edit the set of the annotations; and re-publish the edited set of the annotations. 26. A computer program product for managing document annotations in a publish/subscribe system as carried out at a subscribing system, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
subscribe a user to annotations of a document, wherein each annotation is separate from the document and includes reference to display of the annotation in relation to display of the document; and define a role of the subscribing user, wherein use permissions of a set of the annotations by the subscribing user are controlled based on the role, the use permissions including access permissions based on at least one constraint selected from a group consisting of a time constraint and a location constraint of the subscribing user. 27. The computer program product of claim 26, wherein the program instructions are executable by the processor to further cause the processor to:
filter, using at least one tag, the subscription of the subscribing user to the set of the annotations based on a publishing user. 28. The computer program product of claim 26, wherein the access permissions based on the at least one constraint include subscription access permissions including subscription access based on at least one item selected from the group consisting of the time constraint and the location of the subscribing user. 29. The computer program product of claim 26, wherein the access permissions based on the at least one constraint include display access permissions including display access based on at least one item selected from the group consisting of the time constraint and the location of the subscribing user. 30. The computer program product of claim 26, wherein the use permissions include editing permissions for the subscribing user. 31. The computer program product of claim 26, wherein the program instructions are executable by the processor to further cause the processor to:
subscribe to updates of annotations as re-published by a publishing user. 32. The computer program product of claim 26, wherein the program instructions are executable by the processor to further cause the processor to:
display the set of the annotations on the document at the subscribing user as pseudo annotations; and enable the subscribing user to select to burn the set of the annotations into a local copy of the document. 33. The computer program product of claim 26, wherein the program instructions are executable by the processor to further cause the processor to:
enable the subscribing user to filter a display of the set of the annotations at the subscribing user. 34. The computer program product of claim 26, wherein the program instructions are executable by the processor to further cause the processor to:
select to display the set of the annotations based on a version of the set of the annotations. | Managing document annotations in a publish/subscribe system is described. A publishing system creates annotations of a document that include references to where the annotations are to be displayed; stores the annotations separately from the document; names an annotation set using tags; sets roles and permissions for use of the annotation set, including access permissions based on a time and/or location constraint of a subscribing user; and publishes the annotation set to a publish/subscribe broker for access by the subscribing users. A subscribing system subscribes a user to annotations of a document, wherein each annotation is separate from the document and includes reference to where the annotations are to be displayed. The subscribing system also defines a role of the subscribing user, wherein use permissions of the annotations by the subscribing user are controlled based on the role, including time and/or location constraints of the subscribing user.1-14. (canceled) 15. A publishing system for managing document annotations in a publish/subscribe system, comprising:
an annotation creation component for creating annotations of a document, the annotations including reference for display of the annotations in relation to display of the document, the annotation creation component further for storing the annotations separately from the document; an annotation control component including:
a tagging component for naming a set of the annotations using at least one tag; and
a role and permission component for setting roles and permissions for use of the set of the annotations by subscribing users including setting access permissions based on at least one constraint selected from a group consisting of a time constraint and a location constraint of a subscribing user; and
an annotation publication component for publishing the set of the annotations to a publish/subscribe broker for access by subscribing users. 16. The publishing system of claim 15, wherein the setting the access permissions based on the at least one constraint is applied based on at least one of a group consisting of a subscription time, a subscription location of the subscribing user, a display time, and a display location of the subscribing user. 17. The publishing system of claim 15, further comprising:
an annotation update publication component for re-publishing updates of the set of the annotations. 18. A subscribing system for managing document annotations in a publish/subscribe system, comprising:
an annotation subscription component for subscribing a user to annotations of a document, wherein each annotation is separate from the document and includes reference to display of the annotation in relation to display of the document; and a role and permission component for defining a role of the subscribing user, wherein use permissions of a set of the annotations by the subscribing user are controlled based on the role, the use permissions including access permissions based on at least one constraint selected from a group consisting of a time constraint and a location constraint of the subscribing user. 19. The subscribing system as claimed in claim 18, further comprising:
a filter component for filtering, using at least one tag, the subscription of the subscribing user to the set of the annotations. 20. The subscribing system as claimed in claim 18, further comprising:
a display options component for displaying the set of the annotations on the document at the subscribing user as pseudo annotations and further for enabling the subscribing user to select to burn the set of the annotations into a local copy of the document. 21. A computer program product for managing document annotations in a publish/subscribe system as carried out at a publishing system, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
create annotations of a document, the annotations including reference to locations for display of the annotations in relation to display of the document; store the annotations separately from the document; name a set of the annotations using at least one tag; set roles and permissions for use of the set of the annotations by subscribing users including setting access permissions based on at least one constraint selected from a group consisting of a time constraint and a location constraint of a subscribing user; and publish the set of the annotations to a publish/subscribe broker for access by the subscribing users. 22. The computer program product of claim 21, wherein the setting the access permissions based on the at least one constraint is applied based on at least one item selected from the group consisting of a subscription time of the subscribing user and a subscription location of the subscribing user. 23. The computer program product of claim 21, wherein the setting the access permissions based on the at least one constraint is applied based on at least one item selected from the group consisting of a displaying time of the subscribing user and a displaying location of the subscribing user. 24. The computer program product of claim 21, wherein the setting the roles and the permissions further includes setting editing permissions for the subscribing users. 25. The computer program product of claim 21, wherein the program instructions are executable by the processor to further cause the processor to:
edit the set of the annotations; and re-publish the edited set of the annotations. 26. A computer program product for managing document annotations in a publish/subscribe system as carried out at a subscribing system, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
subscribe a user to annotations of a document, wherein each annotation is separate from the document and includes reference to display of the annotation in relation to display of the document; and define a role of the subscribing user, wherein use permissions of a set of the annotations by the subscribing user are controlled based on the role, the use permissions including access permissions based on at least one constraint selected from a group consisting of a time constraint and a location constraint of the subscribing user. 27. The computer program product of claim 26, wherein the program instructions are executable by the processor to further cause the processor to:
filter, using at least one tag, the subscription of the subscribing user to the set of the annotations based on a publishing user. 28. The computer program product of claim 26, wherein the access permissions based on the at least one constraint include subscription access permissions including subscription access based on at least one item selected from the group consisting of the time constraint and the location of the subscribing user. 29. The computer program product of claim 26, wherein the access permissions based on the at least one constraint include display access permissions including display access based on at least one item selected from the group consisting of the time constraint and the location of the subscribing user. 30. The computer program product of claim 26, wherein the use permissions include editing permissions for the subscribing user. 31. The computer program product of claim 26, wherein the program instructions are executable by the processor to further cause the processor to:
subscribe to updates of annotations as re-published by a publishing user. 32. The computer program product of claim 26, wherein the program instructions are executable by the processor to further cause the processor to:
display the set of the annotations on the document at the subscribing user as pseudo annotations; and enable the subscribing user to select to burn the set of the annotations into a local copy of the document. 33. The computer program product of claim 26, wherein the program instructions are executable by the processor to further cause the processor to:
enable the subscribing user to filter a display of the set of the annotations at the subscribing user. 34. The computer program product of claim 26, wherein the program instructions are executable by the processor to further cause the processor to:
select to display the set of the annotations based on a version of the set of the annotations. | 2,100 |
6,007 | 6,007 | 15,168,967 | 2,144 | A computer-implemented method includes a webpage design server comparing a current date to a start date associated with a version of a webpage and when the current date is after the start date, the webpage design server automatically altering a webpage delivery system so that the version of the webpage is returned by the webpage delivery system when the webpage is requested. | 1. A computer-implemented method comprising:
comparing, by a webpage design server, a current date to a start date associated with a version of a webpage; and when the current date is after the start date, the webpage design server automatically altering a webpage delivery system so that the version of the webpage is returned by the webpage delivery system when the webpage is requested. 2. The computer-implemented method of claim 1 wherein a database contains multiple versions of the webpage, each with a respective different start date. 3. The computer-implemented method of claim 2 wherein each version of the webpage has a start date and an end date and wherein the webpage design server automatically alters the webpage delivery system so that the version of the webpage with the latest start date before the current date and an end date after the current date is returned by the webpage delivery system when the webpage is requested. 4. The computer-implemented method of claim 3 wherein a first version of the webpage has a start date that is after a start date of a second version of the webpage and before the end date of the second version of the webpage. 5. The computer-implemented method of claim 1 wherein the webpage design server provides a user interface for selecting a start date that a version of a webpage is to begin being returned by the webpage delivery system when the webpage is requested. 6. The computer-implemented method of claim 1 wherein the webpage design server alters the webpage delivery system by accessing at least one rule associated with the version of the webpage for populating the webpage with items to purchase, using the at least one rule to identify each item that is to populate the version of the webpage, writing an association between each of the identified items and the version of the webpage that can be used to retrieve information for the items to return on the version of the webpage. 7. The computer-implemented method of claim 1 wherein the version of the webpage is the first version of the webpage to appear on a website and wherein automatically altering a webpage delivery system so that the version of the webpage is returned by the webpage delivery system comprises altering a website taxonomy so that the webpage becomes part of the taxonomy. 8. The computer-implemented method of claim 1 wherein the webpage design server further receives a future date and returns attributes of a version of the webpage that will be returned by the webpage delivery system on the future date. 9. A website design server comprising:
a memory storing attributes for versions of a webpage, the attributes for each version of the webpage including an activation date and time for the version of the webpage and a rule to use to construct the version of the webpage; a processor:
determining when a current date and time is after an activation date and time of a version of a webpage, and in response to the determination, using the rule for the webpage to alter what appears on the webpage. 10. The website design server of claim 9 wherein the memory stores multiple versions for a single webpage, each version having an activation date and time. 11. The website design server of claim 10 wherein each version further has an end date and time and wherein a first version has an activation date and time and an end date and time that are both between an activation date and time and end date and time of a second version and wherein the processor uses a first rule associated with the first version to alter what appears on the webpage when the current date and time is after the activation date and time of the first version and uses a second rule associated with the second version to alter what appears on the webpage when the current date and time is after the end date and time of the first version. 12. The website design server of claim 9 wherein the processor further receives a date and time and a webpage identifier and in response identifies a version of the webpage that will be active on the received date and time. 13. The website design server of claim 12 wherein the processor provides a taxonomy for an entire website that will be active on the received date and time. 14. The website design server of claim 9 wherein the processor uses the rule to alter what appears on the webpage by using the rule to identify each item that is to populate the webpage, and writing an association between each of the identified items and the webpage that can be used to retrieve information for the items to return on the webpage. 15. A method comprising:
displaying a user interface that accepts a future date as input; receiving the input future date; searching for a taxonomy of a website that will be active on the input future date; and generating a user interface showing the taxonomy of the website. 16. The method of claim 15 wherein the taxonomy comprises one or more rule sets, each rule set defining what appears on a webpage of the website. 17. The method of claim 15 wherein generating a user interface showing the taxonomy of the website comprises generating a user interface that allows selection of a webpage and access to a preview of what will be displayed on the webpage. 18. The method of claim 17 wherein access to what will be displayed on the webpage comprises a display of rules used to construct the webpage. 19. The method of claim 15 further comprising executing an application that automatically activates a version of a webpage in the taxonomy when a current date is after a start date for the version of the webpage. 20. The method of claim 19 wherein when the application determines that a version of a webpage should be automatically activated, the application accesses a rule associated with the version of the webpage, wherein the rule defines what items are to appear on the version of the webpage. | A computer-implemented method includes a webpage design server comparing a current date to a start date associated with a version of a webpage and when the current date is after the start date, the webpage design server automatically altering a webpage delivery system so that the version of the webpage is returned by the webpage delivery system when the webpage is requested.1. A computer-implemented method comprising:
comparing, by a webpage design server, a current date to a start date associated with a version of a webpage; and when the current date is after the start date, the webpage design server automatically altering a webpage delivery system so that the version of the webpage is returned by the webpage delivery system when the webpage is requested. 2. The computer-implemented method of claim 1 wherein a database contains multiple versions of the webpage, each with a respective different start date. 3. The computer-implemented method of claim 2 wherein each version of the webpage has a start date and an end date and wherein the webpage design server automatically alters the webpage delivery system so that the version of the webpage with the latest start date before the current date and an end date after the current date is returned by the webpage delivery system when the webpage is requested. 4. The computer-implemented method of claim 3 wherein a first version of the webpage has a start date that is after a start date of a second version of the webpage and before the end date of the second version of the webpage. 5. The computer-implemented method of claim 1 wherein the webpage design server provides a user interface for selecting a start date that a version of a webpage is to begin being returned by the webpage delivery system when the webpage is requested. 6. The computer-implemented method of claim 1 wherein the webpage design server alters the webpage delivery system by accessing at least one rule associated with the version of the webpage for populating the webpage with items to purchase, using the at least one rule to identify each item that is to populate the version of the webpage, writing an association between each of the identified items and the version of the webpage that can be used to retrieve information for the items to return on the version of the webpage. 7. The computer-implemented method of claim 1 wherein the version of the webpage is the first version of the webpage to appear on a website and wherein automatically altering a webpage delivery system so that the version of the webpage is returned by the webpage delivery system comprises altering a website taxonomy so that the webpage becomes part of the taxonomy. 8. The computer-implemented method of claim 1 wherein the webpage design server further receives a future date and returns attributes of a version of the webpage that will be returned by the webpage delivery system on the future date. 9. A website design server comprising:
a memory storing attributes for versions of a webpage, the attributes for each version of the webpage including an activation date and time for the version of the webpage and a rule to use to construct the version of the webpage; a processor:
determining when a current date and time is after an activation date and time of a version of a webpage, and in response to the determination, using the rule for the webpage to alter what appears on the webpage. 10. The website design server of claim 9 wherein the memory stores multiple versions for a single webpage, each version having an activation date and time. 11. The website design server of claim 10 wherein each version further has an end date and time and wherein a first version has an activation date and time and an end date and time that are both between an activation date and time and end date and time of a second version and wherein the processor uses a first rule associated with the first version to alter what appears on the webpage when the current date and time is after the activation date and time of the first version and uses a second rule associated with the second version to alter what appears on the webpage when the current date and time is after the end date and time of the first version. 12. The website design server of claim 9 wherein the processor further receives a date and time and a webpage identifier and in response identifies a version of the webpage that will be active on the received date and time. 13. The website design server of claim 12 wherein the processor provides a taxonomy for an entire website that will be active on the received date and time. 14. The website design server of claim 9 wherein the processor uses the rule to alter what appears on the webpage by using the rule to identify each item that is to populate the webpage, and writing an association between each of the identified items and the webpage that can be used to retrieve information for the items to return on the webpage. 15. A method comprising:
displaying a user interface that accepts a future date as input; receiving the input future date; searching for a taxonomy of a website that will be active on the input future date; and generating a user interface showing the taxonomy of the website. 16. The method of claim 15 wherein the taxonomy comprises one or more rule sets, each rule set defining what appears on a webpage of the website. 17. The method of claim 15 wherein generating a user interface showing the taxonomy of the website comprises generating a user interface that allows selection of a webpage and access to a preview of what will be displayed on the webpage. 18. The method of claim 17 wherein access to what will be displayed on the webpage comprises a display of rules used to construct the webpage. 19. The method of claim 15 further comprising executing an application that automatically activates a version of a webpage in the taxonomy when a current date is after a start date for the version of the webpage. 20. The method of claim 19 wherein when the application determines that a version of a webpage should be automatically activated, the application accesses a rule associated with the version of the webpage, wherein the rule defines what items are to appear on the version of the webpage. | 2,100 |
6,008 | 6,008 | 15,687,057 | 2,191 | The current document is directed to virtualized PMUs provided by virtualization layers. The currently disclosed virtualized PMUs are decoupled from the underlying PMU hardware features of processors on which the virtualization layer executes. The decoupling is achieved, in part, by time multiplexing the underlying hardware PMU registers to provide a greater number of virtualized PMU registers than the number of hardware-PMU registers provided by at least some of the underlying hardware PMUs. The decoupling is also achieved by providing for monitoring, by the virtualized PMU registers, of computed processor events and approximated processor events in addition to the processor events monitored by the underlying hardware PMUs. In addition, the virtualized PMU registers are implemented, in certain implementations, to support a variety of different monitoring modes, including monitoring of processor events that occur only during execution of the virtualization layer and monitoring of hardware-thread-specific processor events. | 1. A cloud-computing facility comprising:
multiple computer systems, each including
one or more processors,
one or more memories, and
a virtualization layer comprising computer instructions, stored in a physical data-storage device within the computer system, that, when executed by one or more of the one or more processors, control the computer system to
provide a virtual hardware interface to a virtual machine that includes a guest operating system; and
provide, as a component of the virtual hardware interface, a set of hardware-decoupled virtual performance monitoring registers that are accessed by the guest operating system, that are provided by the virtualization layers of the other of the multiple computer systems so that the guest operating system accesses the same set of hardware-decoupled virtual performance monitoring registers when the virtual machine migrates among the multiple computer systems, and that includes a hardware-decoupled virtual performance monitoring register that accumulates a count of the occurrence of an event of a type that is not accumulated by the hardware performance monitoring registers of one or more of the processors orfone or more of the multiple computer systems. 2. The cloud-computing facility of claim 1 wherein the hardware-decoupled virtual performance monitoring register that accumulates the count of the occurrence of the event of the type that is not accumulated by the hardware performance monitoring registers of one or more of the processors of one or more of the multiple computer systems accumulates a count of an event derived from counts accumulated by two or more hardware performance monitoring registers. 3. The cloud-computing facility of claim 2 wherein the count of the event derived from counts accumulated by two or more hardware performance monitoring registers is derived by computing an exact count of the derived event from counts accumulated by two or more hardware performance monitoring registers. 4. The cloud-computing facility of claim 2 wherein the count of the event derived from counts accumulated by two or more hardware performance monitoring registers is derived by computing an approximate count of the derived event from counts accumulated by two or more hardware performance monitoring registers. 5. The cloud-computing facility of claim 1 wherein the set of hardware-decoupled virtual performance monitoring registers includes a larger number of hardware-decoupled virtual performance monitoring registers than a number of hardware performance monitoring registers of one or more of the one or more processors of the computer system on which the virtual machine is executing. 6. The cloud-computing facility of claim 5 wherein the counts accumulated by the hardware-decoupled virtual performance monitoring registers are obtained by time multiplexing the hardware performance monitoring registers. 7. The cloud-computing facility of claim 1 wherein the set of hardware-decoupled virtual performance monitoring registers includes a hardware-decoupled virtual performance monitoring register associated with a specifiable mode that controls the virtualization layer to count events during execution of a subset of the instructions executed by one or more of the one or more processors of the computer system on which the virtual machine is executing. 8. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of instructions that implement a virtual machine and the virtualization layer. 9. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of instructions other than those implement a virtual machine and the virtualization layer. 10. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of instructions on behalf of a specific hardware thread. 11. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of virtualization-layer instructions. 12. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of instructions that implement a specific virtual machine. 13. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of instructions that implement a specific guest operating system. 14. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of instructions that implement a specific application program. 15. A method that provides for performance monitoring of a virtual machine as the virtual machine migrates among multiple computer systems of a cloud-computing facility, the method comprising:
installing, within each of the multiple computer systems that each includes one or more processors and one or more memories, a virtualization layer comprising computer instructions, stored in a physical data-storage device within the computer system, that, when executed by one or more of the one or more processors, control the computer system to
provide a virtual hardware interface to a virtual machine that includes a guest operating system; and
provide, as a component of the virtual hardware interface, a set of hardware-decoupled virtual performance monitoring registers that can be accessed by the guest operating system, that are commonly provided by the virtualization layers of the multiple computer systems; and
accumulating a count of the occurrence of an event of a type that is not accumulated by the hardware performance monitoring registers of one or more of the processors of one or more of the multiple computer systems in a hardware-decoupled virtual performance monitoring register. 16. The method of claim 15 wherein the hardware-decoupled virtual performance monitoring register that accumulates the count of the occurrence of the event of the type that is not accumulated by the hardware performance monitoring registers of one or more of the processors of one or more of the multiple computer systems accumulates a count of an event derived from counts accumulated by two or more hardware performance monitoring registers. 17. The method of claim 16 wherein the count of the event derived from counts accumulated by two or more hardware performance monitoring registers is derived by computing an exact count of the derived event from counts accumulated by two or more hardware performance monitoring registers. 18. The method of claim 16 wherein the count of the event derived from counts accumulated by two or more hardware performance monitoring registers is derived by computing an approximate count of the derived event from counts accumulated by two or more hardware performance monitoring registers. 19. The method of claim 15 wherein the set of hardware-decoupled virtual performance monitoring registers includes a larger number of hardware-decoupled virtual performance monitoring registers than a number of hardware performance monitoring registers of one or more of the one or more processors of the computer system on which the virtual machine is executing. 20. The cloud-computing facility of claim 19 wherein the counts accumulated by the hardware-decoupled virtual performance monitoring registers are obtained by time multiplexing the hardware performance monitoring registers. | The current document is directed to virtualized PMUs provided by virtualization layers. The currently disclosed virtualized PMUs are decoupled from the underlying PMU hardware features of processors on which the virtualization layer executes. The decoupling is achieved, in part, by time multiplexing the underlying hardware PMU registers to provide a greater number of virtualized PMU registers than the number of hardware-PMU registers provided by at least some of the underlying hardware PMUs. The decoupling is also achieved by providing for monitoring, by the virtualized PMU registers, of computed processor events and approximated processor events in addition to the processor events monitored by the underlying hardware PMUs. In addition, the virtualized PMU registers are implemented, in certain implementations, to support a variety of different monitoring modes, including monitoring of processor events that occur only during execution of the virtualization layer and monitoring of hardware-thread-specific processor events.1. A cloud-computing facility comprising:
multiple computer systems, each including
one or more processors,
one or more memories, and
a virtualization layer comprising computer instructions, stored in a physical data-storage device within the computer system, that, when executed by one or more of the one or more processors, control the computer system to
provide a virtual hardware interface to a virtual machine that includes a guest operating system; and
provide, as a component of the virtual hardware interface, a set of hardware-decoupled virtual performance monitoring registers that are accessed by the guest operating system, that are provided by the virtualization layers of the other of the multiple computer systems so that the guest operating system accesses the same set of hardware-decoupled virtual performance monitoring registers when the virtual machine migrates among the multiple computer systems, and that includes a hardware-decoupled virtual performance monitoring register that accumulates a count of the occurrence of an event of a type that is not accumulated by the hardware performance monitoring registers of one or more of the processors orfone or more of the multiple computer systems. 2. The cloud-computing facility of claim 1 wherein the hardware-decoupled virtual performance monitoring register that accumulates the count of the occurrence of the event of the type that is not accumulated by the hardware performance monitoring registers of one or more of the processors of one or more of the multiple computer systems accumulates a count of an event derived from counts accumulated by two or more hardware performance monitoring registers. 3. The cloud-computing facility of claim 2 wherein the count of the event derived from counts accumulated by two or more hardware performance monitoring registers is derived by computing an exact count of the derived event from counts accumulated by two or more hardware performance monitoring registers. 4. The cloud-computing facility of claim 2 wherein the count of the event derived from counts accumulated by two or more hardware performance monitoring registers is derived by computing an approximate count of the derived event from counts accumulated by two or more hardware performance monitoring registers. 5. The cloud-computing facility of claim 1 wherein the set of hardware-decoupled virtual performance monitoring registers includes a larger number of hardware-decoupled virtual performance monitoring registers than a number of hardware performance monitoring registers of one or more of the one or more processors of the computer system on which the virtual machine is executing. 6. The cloud-computing facility of claim 5 wherein the counts accumulated by the hardware-decoupled virtual performance monitoring registers are obtained by time multiplexing the hardware performance monitoring registers. 7. The cloud-computing facility of claim 1 wherein the set of hardware-decoupled virtual performance monitoring registers includes a hardware-decoupled virtual performance monitoring register associated with a specifiable mode that controls the virtualization layer to count events during execution of a subset of the instructions executed by one or more of the one or more processors of the computer system on which the virtual machine is executing. 8. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of instructions that implement a virtual machine and the virtualization layer. 9. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of instructions other than those implement a virtual machine and the virtualization layer. 10. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of instructions on behalf of a specific hardware thread. 11. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of virtualization-layer instructions. 12. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of instructions that implement a specific virtual machine. 13. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of instructions that implement a specific guest operating system. 14. The cloud-computing facility of claim 7 wherein the specifiable mode controls the virtualization layer to count events during execution of instructions that implement a specific application program. 15. A method that provides for performance monitoring of a virtual machine as the virtual machine migrates among multiple computer systems of a cloud-computing facility, the method comprising:
installing, within each of the multiple computer systems that each includes one or more processors and one or more memories, a virtualization layer comprising computer instructions, stored in a physical data-storage device within the computer system, that, when executed by one or more of the one or more processors, control the computer system to
provide a virtual hardware interface to a virtual machine that includes a guest operating system; and
provide, as a component of the virtual hardware interface, a set of hardware-decoupled virtual performance monitoring registers that can be accessed by the guest operating system, that are commonly provided by the virtualization layers of the multiple computer systems; and
accumulating a count of the occurrence of an event of a type that is not accumulated by the hardware performance monitoring registers of one or more of the processors of one or more of the multiple computer systems in a hardware-decoupled virtual performance monitoring register. 16. The method of claim 15 wherein the hardware-decoupled virtual performance monitoring register that accumulates the count of the occurrence of the event of the type that is not accumulated by the hardware performance monitoring registers of one or more of the processors of one or more of the multiple computer systems accumulates a count of an event derived from counts accumulated by two or more hardware performance monitoring registers. 17. The method of claim 16 wherein the count of the event derived from counts accumulated by two or more hardware performance monitoring registers is derived by computing an exact count of the derived event from counts accumulated by two or more hardware performance monitoring registers. 18. The method of claim 16 wherein the count of the event derived from counts accumulated by two or more hardware performance monitoring registers is derived by computing an approximate count of the derived event from counts accumulated by two or more hardware performance monitoring registers. 19. The method of claim 15 wherein the set of hardware-decoupled virtual performance monitoring registers includes a larger number of hardware-decoupled virtual performance monitoring registers than a number of hardware performance monitoring registers of one or more of the one or more processors of the computer system on which the virtual machine is executing. 20. The cloud-computing facility of claim 19 wherein the counts accumulated by the hardware-decoupled virtual performance monitoring registers are obtained by time multiplexing the hardware performance monitoring registers. | 2,100 |
6,009 | 6,009 | 14,807,141 | 2,129 | A system for an agnostic runtime architecture. The system includes a system emulation/virtualization converter, an application code converter, and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image. The system converter further comprises an instruction fetch component for fetching an incoming microinstruction sequence, a decoding component coupled to the instruction fetch component to receive the fetched macro instruction sequence and decode into a microinstruction sequence, and an allocation and issue stage coupled to the decoding component to receive the microinstruction sequence perform optimization processing by reordering the microinstruction sequence into an optimized microinstruction sequence comprising a plurality of dependent code groups. A microprocessor pipeline is coupled to the allocation and issue stage to receive and execute the optimized microinstruction sequence. A sequence cache is coupled to the allocation and issue stage to receive and store a copy of the optimized microinstruction sequence for subsequent use upon a subsequent hit on the optimized microinstruction sequence, and a hardware component is coupled for moving instructions in the incoming microinstruction sequence. | 1. A system for an agnostic runtime architecture, comprising:
a system emulation/virtualization converter; an application code converter; and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image, wherein the system converter further comprises: an instruction fetch component for fetching an incoming microinstruction sequence; a decoding component coupled to the instruction fetch component to receive the fetched macro instruction sequence and decode into a microinstruction sequence; an allocation and issue stage coupled to the decoding component to receive the microinstruction sequence perform optimization processing by reordering the microinstruction sequence into an optimized microinstruction sequence comprising a plurality of dependent code groups; a microprocessor pipeline coupled to the allocation and issue stage to receive and execute the optimized microinstruction sequence; a sequence cache coupled to the allocation and issue stage to receive and store a copy of the optimized microinstruction sequence for subsequent use upon a subsequent hit on the optimized microinstruction sequence; and a hardware component for moving instructions in the incoming microinstruction sequence. 2. The method of claim 1, wherein a copy of the decoded microinstructions are stored in a microinstruction cache. 3. The method of claim 1, wherein the optimization processing is performed using an allocation and issue stage of the microprocessor. 4. The method of claim 3, wherein the allocation and issue stage further comprises an instruction scheduling and optimizer component that reorders the microinstruction sequence into the optimized micro instruction sequence. 5. The method of claim 1, wherein the optimization processing further comprises dynamically unrolling microinstruction sequences. 6. The method of claim 1, wherein the optimization processing is implemented through a plurality of iterations. 7. The method of claim 1, wherein the optimization processing is implemented through a register renaming process to enable the reordering. 8. A microprocessor, comprising:
a system emulation/virtualization converter; an application code converter; and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image, wherein the system converter further comprises: an instruction fetch component for fetching an incoming microinstruction sequence; a decoding component coupled to the instruction fetch component to receive the fetched macro instruction sequence and decode into a microinstruction sequence; an allocation and issue stage coupled to the decoding component to receive the microinstruction sequence perform optimization processing by reordering the microinstruction sequence into an optimized microinstruction sequence comprising a plurality of dependent code groups; a microprocessor pipeline coupled to the allocation and issue stage to receive and execute the optimized microinstruction sequence; a sequence cache coupled to the allocation and issue stage to receive and store a copy of the optimized microinstruction sequence for subsequent use upon a subsequent hit on the optimized microinstruction sequence; and a hardware component for moving instructions in the incoming microinstruction sequence. 9. The microprocessor of claim 8, wherein a copy of the decoded microinstructions are stored in a microinstruction cache. 10. The microprocessor of claim 8, wherein the optimization processing is performed using an allocation and issue stage of the microprocessor. 11. The microprocessor of claim 10, wherein the allocation and issue stage further comprises an instruction scheduling and optimizer component that reorders the microinstruction sequence into the optimized micro instruction sequence. 12. The microprocessor of claim 8, wherein the optimization processing further comprises dynamically unrolling microinstruction sequences. 13. The microprocessor of claim 8, wherein the optimization processing is implemented through a plurality of iterations. 14. The microprocessor of claim 8, wherein the optimization processing is implemented through a register renaming process to enable the reordering. 15. A microprocessor, comprising:
a system emulation/virtualization converter; an application code converter; and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image, wherein the system converter further comprises: an instruction fetch component for fetching an incoming microinstruction sequence; a decoding component coupled to the instruction fetch component to receive the fetched macro instruction sequence and decode into a microinstruction sequence; an allocation and issue stage coupled to the decoding component to receive the microinstruction sequence perform optimization processing by reordering the microinstruction sequence into an optimized microinstruction sequence comprising a plurality of dependent code groups; a microprocessor pipeline coupled to the allocation and issue stage to receive and execute the optimized microinstruction sequence; a sequence cache coupled to the allocation and issue stage to receive and store a copy of the optimized microinstruction sequence for subsequent use upon a subsequent hit on the optimized microinstruction sequence; and a hardware component for moving instructions in the incoming microinstruction sequence. 16. The microprocessor of claim 15, wherein optimization processing further includes scanning the plurality of rows of the dependency matrix to identify matching instructions. 17. The microprocessor of claim 16, wherein optimization processing further includes analyzing the matching instructions to determine whether the matching instructions comprise a blocking dependency, and wherein renaming is performed to remove the blocking dependency. 18. The microprocessor of claim 17, wherein instructions corresponding to first matches of each row of the dependency matrix are moved into a corresponding dependency group. 19. The microprocessor of claim 15, wherein copies of the optimized microinstruction sequences are stored in a memory hierarchy of the microprocessor. 20. The microprocessor of claim 19, wherein the memory hierarchy comprises an L1 cache and an L2 cache and a system memory. | A system for an agnostic runtime architecture. The system includes a system emulation/virtualization converter, an application code converter, and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image. The system converter further comprises an instruction fetch component for fetching an incoming microinstruction sequence, a decoding component coupled to the instruction fetch component to receive the fetched macro instruction sequence and decode into a microinstruction sequence, and an allocation and issue stage coupled to the decoding component to receive the microinstruction sequence perform optimization processing by reordering the microinstruction sequence into an optimized microinstruction sequence comprising a plurality of dependent code groups. A microprocessor pipeline is coupled to the allocation and issue stage to receive and execute the optimized microinstruction sequence. A sequence cache is coupled to the allocation and issue stage to receive and store a copy of the optimized microinstruction sequence for subsequent use upon a subsequent hit on the optimized microinstruction sequence, and a hardware component is coupled for moving instructions in the incoming microinstruction sequence.1. A system for an agnostic runtime architecture, comprising:
a system emulation/virtualization converter; an application code converter; and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image, wherein the system converter further comprises: an instruction fetch component for fetching an incoming microinstruction sequence; a decoding component coupled to the instruction fetch component to receive the fetched macro instruction sequence and decode into a microinstruction sequence; an allocation and issue stage coupled to the decoding component to receive the microinstruction sequence perform optimization processing by reordering the microinstruction sequence into an optimized microinstruction sequence comprising a plurality of dependent code groups; a microprocessor pipeline coupled to the allocation and issue stage to receive and execute the optimized microinstruction sequence; a sequence cache coupled to the allocation and issue stage to receive and store a copy of the optimized microinstruction sequence for subsequent use upon a subsequent hit on the optimized microinstruction sequence; and a hardware component for moving instructions in the incoming microinstruction sequence. 2. The method of claim 1, wherein a copy of the decoded microinstructions are stored in a microinstruction cache. 3. The method of claim 1, wherein the optimization processing is performed using an allocation and issue stage of the microprocessor. 4. The method of claim 3, wherein the allocation and issue stage further comprises an instruction scheduling and optimizer component that reorders the microinstruction sequence into the optimized micro instruction sequence. 5. The method of claim 1, wherein the optimization processing further comprises dynamically unrolling microinstruction sequences. 6. The method of claim 1, wherein the optimization processing is implemented through a plurality of iterations. 7. The method of claim 1, wherein the optimization processing is implemented through a register renaming process to enable the reordering. 8. A microprocessor, comprising:
a system emulation/virtualization converter; an application code converter; and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image, wherein the system converter further comprises: an instruction fetch component for fetching an incoming microinstruction sequence; a decoding component coupled to the instruction fetch component to receive the fetched macro instruction sequence and decode into a microinstruction sequence; an allocation and issue stage coupled to the decoding component to receive the microinstruction sequence perform optimization processing by reordering the microinstruction sequence into an optimized microinstruction sequence comprising a plurality of dependent code groups; a microprocessor pipeline coupled to the allocation and issue stage to receive and execute the optimized microinstruction sequence; a sequence cache coupled to the allocation and issue stage to receive and store a copy of the optimized microinstruction sequence for subsequent use upon a subsequent hit on the optimized microinstruction sequence; and a hardware component for moving instructions in the incoming microinstruction sequence. 9. The microprocessor of claim 8, wherein a copy of the decoded microinstructions are stored in a microinstruction cache. 10. The microprocessor of claim 8, wherein the optimization processing is performed using an allocation and issue stage of the microprocessor. 11. The microprocessor of claim 10, wherein the allocation and issue stage further comprises an instruction scheduling and optimizer component that reorders the microinstruction sequence into the optimized micro instruction sequence. 12. The microprocessor of claim 8, wherein the optimization processing further comprises dynamically unrolling microinstruction sequences. 13. The microprocessor of claim 8, wherein the optimization processing is implemented through a plurality of iterations. 14. The microprocessor of claim 8, wherein the optimization processing is implemented through a register renaming process to enable the reordering. 15. A microprocessor, comprising:
a system emulation/virtualization converter; an application code converter; and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image, wherein the system converter further comprises: an instruction fetch component for fetching an incoming microinstruction sequence; a decoding component coupled to the instruction fetch component to receive the fetched macro instruction sequence and decode into a microinstruction sequence; an allocation and issue stage coupled to the decoding component to receive the microinstruction sequence perform optimization processing by reordering the microinstruction sequence into an optimized microinstruction sequence comprising a plurality of dependent code groups; a microprocessor pipeline coupled to the allocation and issue stage to receive and execute the optimized microinstruction sequence; a sequence cache coupled to the allocation and issue stage to receive and store a copy of the optimized microinstruction sequence for subsequent use upon a subsequent hit on the optimized microinstruction sequence; and a hardware component for moving instructions in the incoming microinstruction sequence. 16. The microprocessor of claim 15, wherein optimization processing further includes scanning the plurality of rows of the dependency matrix to identify matching instructions. 17. The microprocessor of claim 16, wherein optimization processing further includes analyzing the matching instructions to determine whether the matching instructions comprise a blocking dependency, and wherein renaming is performed to remove the blocking dependency. 18. The microprocessor of claim 17, wherein instructions corresponding to first matches of each row of the dependency matrix are moved into a corresponding dependency group. 19. The microprocessor of claim 15, wherein copies of the optimized microinstruction sequences are stored in a memory hierarchy of the microprocessor. 20. The microprocessor of claim 19, wherein the memory hierarchy comprises an L1 cache and an L2 cache and a system memory. | 2,100 |
6,010 | 6,010 | 15,621,613 | 2,176 | An image processing apparatus is described comprising a processor configured to receive a video and digital ink annotated on the video. For at least a first frame of the video, the processor is configured to compute a model describing pixels of a bounding region of the ink. For a frame of the video, the processor is configured to compute a second region corresponding to the bounding region. The processor is configured to compute a comparison between the second region and the model and update the ink using the comparison. | 1. An image processing apparatus configured to detect occlusion of digital ink in a digitally annotated video, comprising a processor configured to:
receive a video; receive digital ink annotated on the video; for at least a first frame of the video, compute a model describing pixels in a bounding region of the digital ink; for a frame of the video, compute a second region corresponding to the bounding region; compute a comparison between the second region and the model; and update the ink using the comparison. 2. The image processing apparatus of claim 1, wherein the model comprises a statistical model of at least one channel of the pixels in the bounding region, and the processor is configured to compute the comparison by comparing the intensity of the at least one channel of the pixels in the second region to the model. 3. The image processing apparatus of claim 1, wherein:
the model comprises a set of sub-models describing pixels of the at least first frame in a set of respective first sub-regions making up the bounding region; the second region comprises a set of second sub-regions corresponding to the set of first sub-regions; and the processor is configured to compute a comparison between each pixel of each second sub-region and the corresponding sub-model. 4. The image processing apparatus of claim 3, wherein each sub-model describes a cell of a grid of pixels. 5. The image processing apparatus of claim 3, wherein the processor is configured to interpolate the comparison at the boundaries between neighboring sub-regions. 6. The image processing apparatus of claim 1, wherein the comparison comprises a computed similarity value between pixels of the second region and the model. 7. The image processing apparatus of claim 6, wherein the comparison comprises an occlusion map indicating pixels of the second region which have a similarity value below a predetermined threshold value. 8. The image processing apparatus of claim 6, wherein the comparison comprises an occlusion probability map calculated from the similarity values of the individual pixels of the second region. 9. The image processing apparatus of claim 8, wherein the probability map is filtered using a cross bilateral filter to generate the comparison. 10. The image processing apparatus of claim 8, wherein the processor is configured to update the ink by applying the probability map to the ink. 11. The image processing apparatus of claim 6, wherein the processor is further configured to update the model to describe pixels of the second region which have a similarity value above a predetermined threshold value if data from the second region has not yet been included in the model. 12. The image processing apparatus of claim 11, wherein the model is updated according to a learning algorithm having a learning rate. 13. The image processing apparatus of claim 12, wherein the processor is configured to change the learning rate. 14. The image processing apparatus of claim 6, wherein the processor is configured to compute the comparison by:
generating an occlusion map indicating occluded pixels of the second region which have a similarity value below a predetermined threshold value; and for each pixel not indicated as occluded, marking the pixel as occluded if the number of occluded pixels in a selected neighborhood of the pixel is above a predetermined threshold value. 15. The image processing apparatus of claim 1, wherein the processor is further configured to, prior to updating the ink or prior to generating the comparison:
check a set of criteria for the video, the criteria being indicative of the occlusion mechanism being effective; and if the criteria is not fulfilled, then abort any remaining steps for detecting occlusion. 16. The image processing apparatus of claim 1, wherein the processor is configured to compute a second region corresponding to the bounding region by:
selecting a plurality of template pixels of the bounding region; matching the template pixels of the bounding region to corresponding matching template pixels in the subsequent frame: generating a homography transform matrix using the matching; and applying the homography transform matrix to the bounding region to generate the second region. 17. The image processing apparatus of claim 16, wherein the processor is configured to match the template pixels by searching the subsequent frame for a similar plurality of pixels, using template matching. 18. The image processing apparatus of claim 1, wherein the processor is configured to update the ink by segmenting the comparison between the second region and the first model using a graph cut algorithm. 19. A computer-implemented method for detecting occlusion of digital ink in a digitally annotated video, comprising operations including:
receiving a video; receiving digital ink annotated on the video; for at least a first frame of the video, computing a model describing pixels of a bounding region of the ink; for a frame of the video, computing a second region corresponding to the bounding region; computing a comparison between the second region and the model; and updating the ink using the comparison. 20. One or more device-readable media with device-executable instructions that, when executed by a computing system, direct the computing system to perform operations comprising:
receiving a video; receiving digital ink annotated on the video; for at least a first frame of the video, computing a model describing pixels of a bounding region of the ink; for a frame of the video, computing a second region corresponding to the bounding region; computing a comparison between the second region and the model; and updating the ink using the comparison. | An image processing apparatus is described comprising a processor configured to receive a video and digital ink annotated on the video. For at least a first frame of the video, the processor is configured to compute a model describing pixels of a bounding region of the ink. For a frame of the video, the processor is configured to compute a second region corresponding to the bounding region. The processor is configured to compute a comparison between the second region and the model and update the ink using the comparison.1. An image processing apparatus configured to detect occlusion of digital ink in a digitally annotated video, comprising a processor configured to:
receive a video; receive digital ink annotated on the video; for at least a first frame of the video, compute a model describing pixels in a bounding region of the digital ink; for a frame of the video, compute a second region corresponding to the bounding region; compute a comparison between the second region and the model; and update the ink using the comparison. 2. The image processing apparatus of claim 1, wherein the model comprises a statistical model of at least one channel of the pixels in the bounding region, and the processor is configured to compute the comparison by comparing the intensity of the at least one channel of the pixels in the second region to the model. 3. The image processing apparatus of claim 1, wherein:
the model comprises a set of sub-models describing pixels of the at least first frame in a set of respective first sub-regions making up the bounding region; the second region comprises a set of second sub-regions corresponding to the set of first sub-regions; and the processor is configured to compute a comparison between each pixel of each second sub-region and the corresponding sub-model. 4. The image processing apparatus of claim 3, wherein each sub-model describes a cell of a grid of pixels. 5. The image processing apparatus of claim 3, wherein the processor is configured to interpolate the comparison at the boundaries between neighboring sub-regions. 6. The image processing apparatus of claim 1, wherein the comparison comprises a computed similarity value between pixels of the second region and the model. 7. The image processing apparatus of claim 6, wherein the comparison comprises an occlusion map indicating pixels of the second region which have a similarity value below a predetermined threshold value. 8. The image processing apparatus of claim 6, wherein the comparison comprises an occlusion probability map calculated from the similarity values of the individual pixels of the second region. 9. The image processing apparatus of claim 8, wherein the probability map is filtered using a cross bilateral filter to generate the comparison. 10. The image processing apparatus of claim 8, wherein the processor is configured to update the ink by applying the probability map to the ink. 11. The image processing apparatus of claim 6, wherein the processor is further configured to update the model to describe pixels of the second region which have a similarity value above a predetermined threshold value if data from the second region has not yet been included in the model. 12. The image processing apparatus of claim 11, wherein the model is updated according to a learning algorithm having a learning rate. 13. The image processing apparatus of claim 12, wherein the processor is configured to change the learning rate. 14. The image processing apparatus of claim 6, wherein the processor is configured to compute the comparison by:
generating an occlusion map indicating occluded pixels of the second region which have a similarity value below a predetermined threshold value; and for each pixel not indicated as occluded, marking the pixel as occluded if the number of occluded pixels in a selected neighborhood of the pixel is above a predetermined threshold value. 15. The image processing apparatus of claim 1, wherein the processor is further configured to, prior to updating the ink or prior to generating the comparison:
check a set of criteria for the video, the criteria being indicative of the occlusion mechanism being effective; and if the criteria is not fulfilled, then abort any remaining steps for detecting occlusion. 16. The image processing apparatus of claim 1, wherein the processor is configured to compute a second region corresponding to the bounding region by:
selecting a plurality of template pixels of the bounding region; matching the template pixels of the bounding region to corresponding matching template pixels in the subsequent frame: generating a homography transform matrix using the matching; and applying the homography transform matrix to the bounding region to generate the second region. 17. The image processing apparatus of claim 16, wherein the processor is configured to match the template pixels by searching the subsequent frame for a similar plurality of pixels, using template matching. 18. The image processing apparatus of claim 1, wherein the processor is configured to update the ink by segmenting the comparison between the second region and the first model using a graph cut algorithm. 19. A computer-implemented method for detecting occlusion of digital ink in a digitally annotated video, comprising operations including:
receiving a video; receiving digital ink annotated on the video; for at least a first frame of the video, computing a model describing pixels of a bounding region of the ink; for a frame of the video, computing a second region corresponding to the bounding region; computing a comparison between the second region and the model; and updating the ink using the comparison. 20. One or more device-readable media with device-executable instructions that, when executed by a computing system, direct the computing system to perform operations comprising:
receiving a video; receiving digital ink annotated on the video; for at least a first frame of the video, computing a model describing pixels of a bounding region of the ink; for a frame of the video, computing a second region corresponding to the bounding region; computing a comparison between the second region and the model; and updating the ink using the comparison. | 2,100 |
6,011 | 6,011 | 16,021,935 | 2,117 | A model formation module (25) is provided for creating a model for controlling a pressure regulating system (7) of a water supply network (5), wherein the water supply network (5) is equipped with one or more pressure sensors of which at least one remote pressure sensor (17a,b) is arranged remotely from the pressure regulating system (7), the model formation module (25) being configured to communicate with the at least one remote pressure sensor (17a,b). The model formation module (25) is configured to create said model without a measured, determined or estimated flow value on the basis of at least one remote pressure value determined by the at least one remote pressure sensor (17a,b) and on the basis of at least one load-dependent variable of the pressure regulating system (7), said model representing at least one pressure control curve for controlling the pressure regulating system (7). | 1. A model formation module for creating a model for controlling a pressure regulating system of a water supply network, wherein the water supply network is equipped with one or more pressure sensors of which at least one remote pressure sensor is arranged remotely from the pressure regulating system, the model formation module being configured to:
communicate with the at least one remote pressure sensor; and create said model, without a measured, determined or estimated flow value, on the basis of at least one remote pressure value determined by the at least one remote pressure sensor and on the basis of at least one load-dependent variable of the pressure regulating system, said model representing at least one pressure control curve for controlling the pressure regulating system. 2. The model formation module according to claim 1, wherein at least one of the at least one load-dependent variable is an electrical power consumption of at least one pump of the pressure regulating system or a speed of at least one pump of the pressure regulating system or both an electrical power consumption and a speed of at least one pump of the pressure regulating system. 3. The model formation module according to claim 1, wherein at least one of the at least one load-dependent variable represents an opening degree of a pressure reduction valve of the pressure regulating system or a pressure difference before and after a pressure reduction valve of the pressure regulating system or both an opening degree of a pressure reduction valve of the pressure regulating system and a pressure difference before and after a pressure reduction valve of the pressure regulating system. 4. The model formation module according to claim 1, wherein the model formation module is further configured to be in communication connection with a control unit for controlling the pressure regulating system. 5. The model formation module according to claim 1, wherein the model formation module is part of a control unit for controlling the pressure regulating system. 6. The model formation module according to claim 1, wherein the model formation module is further configured to take into account, for creating said model, a pressure difference between the at least one remote pressure value determined by the least one remote pressure sensor and at least one outlet pressure value determined by at least one outlet pressure sensor of the one or more pressure sensors, the at least one outlet pressure sensor being arranged at an outlet side of the pressure regulating system. 7. The model formation module according to claim 1, wherein the model formation module is further configured to take into account, for creating said model, at least one inlet pressure value determined by at least one inlet pressure sensor of the one or more pressure sensors, the at least one inlet pressure sensor being arranged at an inlet side of the pressure regulating system. 8. The model formation module according to claim 1, wherein the model formation module is further configured to update the model continuously, regularly or sporadically before, during or after operation of the pressure regulation system on the basis of changes in the at least one remote pressure value or on the basis of the at least one load-dependent variable or on the basis of changes in the at least one remote pressure value and on the basis of the at least one load-dependent variable. 9. The model formation module according to claim 1, wherein the model formation module is further configured to take into account, for creating said model, at least one first section pressure value determined by at least one first section pressure sensor of the one or more pressure sensors, the at least one first section pressure sensor being arranged in a first section of the water supply network, and at least one second section pressure value determined by at least one second section pressure sensor of the one or more pressure sensors, the at least one second section pressure sensor being arranged in a second section of the water supply network, wherein the first and the second sections of the water supply network differ from each other and are arranged downstream of the pressure regulating system. 10. The model formation module according to claim 9, wherein:
the model represents a first pressure control curve for the first section and a second pressure control curve for the second section; and a first pressure demand is determinable from the first pressure control curve and a second pressure demand is determinable from the second pressure control curve based on the load-dependent variable, such that the higher of the first pressure demand and the second pressure demand is identifiable. 11. The model formation module according to claim 1, wherein:
the model formation module is further configured to update the model continuously, regularly or sporadically; and a previous or pre-determined pressure control curve of the model is compared with an updated pressure control curve for a given load-dependent variable, such that a leakage in the water supply network or a blockage in the water supply network or both a leakage and a blockage in the water supply network is identifiable based on such a comparison. 12. The model formation module according to claim 1, wherein:
the model formation module is further configured to create the model representing at least one pressure control curve such that at least one critical pressure value is kept above a pre-determined threshold value; and the at least one critical pressure value is determined by at least one critical pressure sensor of the one or more pressure sensors, the at least one critical pressure sensor being arranged in a critical pressure section of the water supply network. 13. The model formation module according to claim 1, wherein the model formation module comprises a data memory and is configured to store one or more of the at least one remote pressure value or the at least one load-dependent variable or the at least one remote pressure value and the at least one load-dependent variable at one or more different points in time. 14. The model formation module according to claim 1, wherein the model formation module is further configured to receive continuously, regularly or sporadically data comprising one or more of the at least one remote pressure value or the at least one load-dependent variable or the at least one remote pressure value and the at least one load-dependent variable, said data being stored at one or more different points in time in at least one data storage of the one or more pressure sensors. 15. The model formation module according to claim 1, wherein the model represents at least one pressure control curve representing a necessary outlet pressure value at an outlet of the pressure regulating system as a function of the at least one load-dependent variable and at least one model parameter for achieving a desired remote pressure value at the at least one remote pressure sensor. 16. The model formation module according to claim 15, wherein the model comprises a time dependency of the necessary outlet pressure. 17. A method for controlling a pressure regulating system of a water supply network, wherein the water supply network is equipped with one or more pressure sensors of which at least one remote pressure sensor is arranged remotely from the pressure regulating system, the method comprising the steps of:
creating a model without a measured, determined or estimated flow value on the basis of at least one remote pressure value determined by the at least one remote pressure sensor and on the basis of at least one load-dependent variable of the pressure regulating system, said model representing at least one pressure control curve for controlling the pressure regulating system; and controlling the pressure regulating system based on said model. 18. The method according to claim 17, wherein at least one of the at least one load-dependent variable is an electrical power consumption of at least one pump of the pressure regulating system or a speed of at least one pump of the pressure regulating system or an electrical power consumption and a speed of at least one pump of the pressure regulating system. 19. The method according to claim 17, wherein at least one of the at least one load-dependent variable represents an opening degree of a pressure reduction valve of the pressure regulating system or a pressure difference before and after a pressure reduction valve of the pressure regulating system or both an opening degree and a pressure difference before and after a pressure reduction valve of the pressure regulating system. 20. The method according to claim 17, wherein creating said model comprises taking into account a pressure difference between the at least one remote pressure value determined by the least one remote pressure sensor and at least one outlet pressure value determined by at least one outlet pressure sensor of the one or more pressure sensors, the at least one outlet pressure sensor being arranged at an outlet side of the pressure regulating system. 21. The method according to claim 17, wherein creating the model or controlling the pressure regulating system or both creating the model and controlling the pressure regulating system comprises taking into account at least one inlet pressure value determined by at least one inlet pressure sensor of the one or more pressure sensors, the at least one inlet pressure sensor being arranged at an inlet side of the pressure regulating system. 22. The method according to claim 17, further comprising updating the model continuously, regularly or sporadically before, during or after operation of the pressure regulation system based on changes in the at least one remote pressure value or based on changes in the at least one load-dependent variable or based both on changes in the at least one remote pressure value and changes in the at least one load-dependent variable. 23. The method according to claim 17, wherein creating the model or controlling the pressure regulating system or both creating the model and controlling the pressure regulating system comprises taking into account at least one first section pressure value determined by at least one first section pressure sensor of the one or more pressure sensors, the at least one first section pressure sensor being arranged in a first section of the water supply network, and at least one second section pressure value determined by at least one second section pressure sensor of the one or more pressure sensors, the at least one second section pressure sensor being arranged in a second section of the water supply network, wherein the first and the second sections of the water supply network differ from each other and are arranged downstream of the pressure regulating system. 24. The method according to claim 23, wherein:
the model represents a first pressure control curve for the first section and a second pressure control curve for the second section; creating the model or updating the model or both creating and updating the model comprises determining a first pressure demand from the first pressure control curve and a second pressure demand from the second pressure control curve based on the load-dependent variable; and controlling the pressure regulating system comprises controlling the pressure regulating system according to the higher of the first pressure demand and the second pressure demand. 25. The method according to claim 17, further comprising:
updating the model continuously, regularly or sporadically; comparing a previous or pre-determined pressure control curve with an updated pressure control curve for a given load-dependent variable; and identifying a leakage in the water supply network or identifying a blockage in the water supply network or identifying both a leakage and a blockage in the water supply network based on comparing the previous or pre-determined pressure control curve with an updated pressure control curve. 26. The method according to claim 17, wherein:
controlling the pressure regulating system comprises keeping at least one critical pressure value above a pre-determined threshold value; and the at least one critical pressure value is determined by at least one critical pressure sensor of the one or more pressure sensors, the at least one critical pressure sensor being arranged in a critical pressure section of the water supply network. 27. The method according to claim 17, further comprising storing one or more of the at least one remote pressure value or storing the at least one load-dependent variable or storing both the at least one remote pressure value and the at least one load-dependent variable at one or more different points in time. 28. The method according to claim 17, further comprising receiving continuously, regularly or sporadically data comprising one or more of the at least one remote pressure value or data comprising the at least one load-dependent variable or data comprising both one or more of the at least one remote pressure value and the at least one load-dependent variable, said data being stored at one or more different points in time in at least one data storage of the one or more pressure sensors. 29. The method according to claim 17, wherein the model represents at least one pressure control curve representing a necessary outlet pressure value at an outlet of the pressure regulating system as a function of the at least one load-dependent variable and at least one model parameter for achieving a desired remote pressure value at the at least one remote pressure sensor. 30. The method according to claim 29, wherein the model comprises a day time dependency of the necessary outlet pressure. | A model formation module (25) is provided for creating a model for controlling a pressure regulating system (7) of a water supply network (5), wherein the water supply network (5) is equipped with one or more pressure sensors of which at least one remote pressure sensor (17a,b) is arranged remotely from the pressure regulating system (7), the model formation module (25) being configured to communicate with the at least one remote pressure sensor (17a,b). The model formation module (25) is configured to create said model without a measured, determined or estimated flow value on the basis of at least one remote pressure value determined by the at least one remote pressure sensor (17a,b) and on the basis of at least one load-dependent variable of the pressure regulating system (7), said model representing at least one pressure control curve for controlling the pressure regulating system (7).1. A model formation module for creating a model for controlling a pressure regulating system of a water supply network, wherein the water supply network is equipped with one or more pressure sensors of which at least one remote pressure sensor is arranged remotely from the pressure regulating system, the model formation module being configured to:
communicate with the at least one remote pressure sensor; and create said model, without a measured, determined or estimated flow value, on the basis of at least one remote pressure value determined by the at least one remote pressure sensor and on the basis of at least one load-dependent variable of the pressure regulating system, said model representing at least one pressure control curve for controlling the pressure regulating system. 2. The model formation module according to claim 1, wherein at least one of the at least one load-dependent variable is an electrical power consumption of at least one pump of the pressure regulating system or a speed of at least one pump of the pressure regulating system or both an electrical power consumption and a speed of at least one pump of the pressure regulating system. 3. The model formation module according to claim 1, wherein at least one of the at least one load-dependent variable represents an opening degree of a pressure reduction valve of the pressure regulating system or a pressure difference before and after a pressure reduction valve of the pressure regulating system or both an opening degree of a pressure reduction valve of the pressure regulating system and a pressure difference before and after a pressure reduction valve of the pressure regulating system. 4. The model formation module according to claim 1, wherein the model formation module is further configured to be in communication connection with a control unit for controlling the pressure regulating system. 5. The model formation module according to claim 1, wherein the model formation module is part of a control unit for controlling the pressure regulating system. 6. The model formation module according to claim 1, wherein the model formation module is further configured to take into account, for creating said model, a pressure difference between the at least one remote pressure value determined by the least one remote pressure sensor and at least one outlet pressure value determined by at least one outlet pressure sensor of the one or more pressure sensors, the at least one outlet pressure sensor being arranged at an outlet side of the pressure regulating system. 7. The model formation module according to claim 1, wherein the model formation module is further configured to take into account, for creating said model, at least one inlet pressure value determined by at least one inlet pressure sensor of the one or more pressure sensors, the at least one inlet pressure sensor being arranged at an inlet side of the pressure regulating system. 8. The model formation module according to claim 1, wherein the model formation module is further configured to update the model continuously, regularly or sporadically before, during or after operation of the pressure regulation system on the basis of changes in the at least one remote pressure value or on the basis of the at least one load-dependent variable or on the basis of changes in the at least one remote pressure value and on the basis of the at least one load-dependent variable. 9. The model formation module according to claim 1, wherein the model formation module is further configured to take into account, for creating said model, at least one first section pressure value determined by at least one first section pressure sensor of the one or more pressure sensors, the at least one first section pressure sensor being arranged in a first section of the water supply network, and at least one second section pressure value determined by at least one second section pressure sensor of the one or more pressure sensors, the at least one second section pressure sensor being arranged in a second section of the water supply network, wherein the first and the second sections of the water supply network differ from each other and are arranged downstream of the pressure regulating system. 10. The model formation module according to claim 9, wherein:
the model represents a first pressure control curve for the first section and a second pressure control curve for the second section; and a first pressure demand is determinable from the first pressure control curve and a second pressure demand is determinable from the second pressure control curve based on the load-dependent variable, such that the higher of the first pressure demand and the second pressure demand is identifiable. 11. The model formation module according to claim 1, wherein:
the model formation module is further configured to update the model continuously, regularly or sporadically; and a previous or pre-determined pressure control curve of the model is compared with an updated pressure control curve for a given load-dependent variable, such that a leakage in the water supply network or a blockage in the water supply network or both a leakage and a blockage in the water supply network is identifiable based on such a comparison. 12. The model formation module according to claim 1, wherein:
the model formation module is further configured to create the model representing at least one pressure control curve such that at least one critical pressure value is kept above a pre-determined threshold value; and the at least one critical pressure value is determined by at least one critical pressure sensor of the one or more pressure sensors, the at least one critical pressure sensor being arranged in a critical pressure section of the water supply network. 13. The model formation module according to claim 1, wherein the model formation module comprises a data memory and is configured to store one or more of the at least one remote pressure value or the at least one load-dependent variable or the at least one remote pressure value and the at least one load-dependent variable at one or more different points in time. 14. The model formation module according to claim 1, wherein the model formation module is further configured to receive continuously, regularly or sporadically data comprising one or more of the at least one remote pressure value or the at least one load-dependent variable or the at least one remote pressure value and the at least one load-dependent variable, said data being stored at one or more different points in time in at least one data storage of the one or more pressure sensors. 15. The model formation module according to claim 1, wherein the model represents at least one pressure control curve representing a necessary outlet pressure value at an outlet of the pressure regulating system as a function of the at least one load-dependent variable and at least one model parameter for achieving a desired remote pressure value at the at least one remote pressure sensor. 16. The model formation module according to claim 15, wherein the model comprises a time dependency of the necessary outlet pressure. 17. A method for controlling a pressure regulating system of a water supply network, wherein the water supply network is equipped with one or more pressure sensors of which at least one remote pressure sensor is arranged remotely from the pressure regulating system, the method comprising the steps of:
creating a model without a measured, determined or estimated flow value on the basis of at least one remote pressure value determined by the at least one remote pressure sensor and on the basis of at least one load-dependent variable of the pressure regulating system, said model representing at least one pressure control curve for controlling the pressure regulating system; and controlling the pressure regulating system based on said model. 18. The method according to claim 17, wherein at least one of the at least one load-dependent variable is an electrical power consumption of at least one pump of the pressure regulating system or a speed of at least one pump of the pressure regulating system or an electrical power consumption and a speed of at least one pump of the pressure regulating system. 19. The method according to claim 17, wherein at least one of the at least one load-dependent variable represents an opening degree of a pressure reduction valve of the pressure regulating system or a pressure difference before and after a pressure reduction valve of the pressure regulating system or both an opening degree and a pressure difference before and after a pressure reduction valve of the pressure regulating system. 20. The method according to claim 17, wherein creating said model comprises taking into account a pressure difference between the at least one remote pressure value determined by the least one remote pressure sensor and at least one outlet pressure value determined by at least one outlet pressure sensor of the one or more pressure sensors, the at least one outlet pressure sensor being arranged at an outlet side of the pressure regulating system. 21. The method according to claim 17, wherein creating the model or controlling the pressure regulating system or both creating the model and controlling the pressure regulating system comprises taking into account at least one inlet pressure value determined by at least one inlet pressure sensor of the one or more pressure sensors, the at least one inlet pressure sensor being arranged at an inlet side of the pressure regulating system. 22. The method according to claim 17, further comprising updating the model continuously, regularly or sporadically before, during or after operation of the pressure regulation system based on changes in the at least one remote pressure value or based on changes in the at least one load-dependent variable or based both on changes in the at least one remote pressure value and changes in the at least one load-dependent variable. 23. The method according to claim 17, wherein creating the model or controlling the pressure regulating system or both creating the model and controlling the pressure regulating system comprises taking into account at least one first section pressure value determined by at least one first section pressure sensor of the one or more pressure sensors, the at least one first section pressure sensor being arranged in a first section of the water supply network, and at least one second section pressure value determined by at least one second section pressure sensor of the one or more pressure sensors, the at least one second section pressure sensor being arranged in a second section of the water supply network, wherein the first and the second sections of the water supply network differ from each other and are arranged downstream of the pressure regulating system. 24. The method according to claim 23, wherein:
the model represents a first pressure control curve for the first section and a second pressure control curve for the second section; creating the model or updating the model or both creating and updating the model comprises determining a first pressure demand from the first pressure control curve and a second pressure demand from the second pressure control curve based on the load-dependent variable; and controlling the pressure regulating system comprises controlling the pressure regulating system according to the higher of the first pressure demand and the second pressure demand. 25. The method according to claim 17, further comprising:
updating the model continuously, regularly or sporadically; comparing a previous or pre-determined pressure control curve with an updated pressure control curve for a given load-dependent variable; and identifying a leakage in the water supply network or identifying a blockage in the water supply network or identifying both a leakage and a blockage in the water supply network based on comparing the previous or pre-determined pressure control curve with an updated pressure control curve. 26. The method according to claim 17, wherein:
controlling the pressure regulating system comprises keeping at least one critical pressure value above a pre-determined threshold value; and the at least one critical pressure value is determined by at least one critical pressure sensor of the one or more pressure sensors, the at least one critical pressure sensor being arranged in a critical pressure section of the water supply network. 27. The method according to claim 17, further comprising storing one or more of the at least one remote pressure value or storing the at least one load-dependent variable or storing both the at least one remote pressure value and the at least one load-dependent variable at one or more different points in time. 28. The method according to claim 17, further comprising receiving continuously, regularly or sporadically data comprising one or more of the at least one remote pressure value or data comprising the at least one load-dependent variable or data comprising both one or more of the at least one remote pressure value and the at least one load-dependent variable, said data being stored at one or more different points in time in at least one data storage of the one or more pressure sensors. 29. The method according to claim 17, wherein the model represents at least one pressure control curve representing a necessary outlet pressure value at an outlet of the pressure regulating system as a function of the at least one load-dependent variable and at least one model parameter for achieving a desired remote pressure value at the at least one remote pressure sensor. 30. The method according to claim 29, wherein the model comprises a day time dependency of the necessary outlet pressure. | 2,100 |
6,012 | 6,012 | 14,621,382 | 2,163 | Methods and system are disclosed that assist improving user experience, when consuming business data. In one aspect, a framework middleware receives a request via an application to establish connection with a multiple systems. Upon establishing the connection, the business data from the multiple systems may be retrieved. The retrieved business data may be transformed by triggering system landscape transformation data model. From the transformed business data, contextual information associated with the business data may be determined. The determined contextual information may be displayed on a user interface or a dashboard that is instantiated by the application. The contextual information displayed on the user interface is customized based on user preferences that enhances and improves user experience when consuming business data. | 1. A system to improve user experience when consuming business data, comprising:
a processor, and one or more memory devices communicatively coupled with the processor and storing instructions related to:
receiving a request, at a framework middleware via an application, to establish a connection with a plurality of business management systems;
upon establishing the connection, the framework middleware retrieving business data from the plurality of business management systems;
based on an execution of a plurality of routines in the framework middleware, triggering a system landscape transformation model to transform the retrieved business data;
determining a contextual information associated with the transformed business data; and
rendering the determined contextual information on a user interface of the application, wherein the contextual information is customizable based on one or more parameters. 2. The system of claim 1, further comprising: replicating the business data from the plurality of business management systems and storing the replicated business data in the application. 3. The system of claim 1, wherein the framework middleware further comprises: a network gateway including a generic layer and a database in communication with the plurality of business management systems. 4. The system of claim 3, wherein: upon successful validation of the business data in the database using a global business rule, replicate the business data from the database in the network layer to the plurality of business management systems. 5. The system of claim 1, wherein the framework middleware executes a plurality of routines related to web content management service, document management service, dashboard management service, widget management service and workflow management service. 6. The system of claim 1, wherein the framework middleware executes the plurality of routines to validate the business data from the plurality of business management systems, using one or more local business rules. 7. The system of claim 1, wherein the framework middleware executes the plurality of routines to encrypt the business data by a sequential data encryption algorithm. 8. A computer implemented method to improve user experience when consuming business data, comprising:
receiving a request, at a framework middleware via an application, to establish a connection with a plurality of business management systems; upon establishing the connection, the framework middleware retrieving business data from the plurality of business management systems; based on an execution of a plurality of routines in the framework middleware, triggering a system landscape transformation model to transform the retrieved business data; determining a contextual information associated with the transformed business data; and rendering the determined contextual information on a user interface of the application, wherein the contextual information is customizable based on one or more parameters. 9. The computer implemented method of claim 8, further comprising: replicating the business data from the plurality of business management systems and storing the replicated business data in the application. 10. The computer implemented method of claim 8, wherein the framework middleware further comprises: a network gateway including a generic layer and a database in communication with the plurality of systems. 11. The computer implemented method of claim 8, wherein: upon successful validation of the business data in the database using a global business rule, replicate the business data from the database in the network layer to the plurality of business management systems. 12. The computer implemented method of claim 8, wherein the framework middleware executes the plurality of routines related to web content management service, document management service, dashboard management service, widget management service and workflow management service. 13. The computer implemented method of claim 8, wherein the framework middleware executes the plurality of routines to validate the business data from the plurality of business management systems, using one or more local business rules. 14. The computer implemented method of claim 8, wherein the framework middleware executes the plurality of routines to encrypt the business data by a sequential data encryption algorithm. 15. A non-transitory computer readable storage medium tangibly storing instructions, which when executed by a computer, cause the computer to execute operations comprising:
receiving a request, at a framework middleware via an application, to establish a connection with a plurality of business management systems; upon establishing the connection, the framework middleware retrieving business data from the plurality of business management systems; based on an execution of a plurality of routines in the framework middleware, triggering a system landscape transformation model to transform the retrieved business data; determining a contextual information associated with the transformed business data; and rendering the determined contextual information on a user interface of the application, wherein the contextual information is customizable based on one or more parameters. 16. The non-transitory computer readable storage medium of claim 15, further comprising instructions that cause the computer to execute operations comprising:
replicating the business data from the plurality of business management systems and storing the replicated business data in the application. 17. The non-transitory computer readable storage medium of claim 15, further comprising instructions that cause the computer to execute operations comprising: a network gateway that includes a generic layer and a database in communication with the plurality of business management systems. 18. The non-transitory computer readable storage medium of claim 17, wherein: upon successful validation of the business data in the database using a global business rule, replicate the business data from the database in the network layer to the plurality of business management systems. 19. The non-transitory computer readable storage medium of claim 15, wherein the framework middleware executes the plurality of routines related to web content management service, document management service, dashboard management service, widget management service and workflow management service. 20. The non-transitory computer readable storage medium of claim 15, wherein the framework middleware executes the plurality of routines to validate the business data from the plurality of business management systems, using one or more local business rules. | Methods and system are disclosed that assist improving user experience, when consuming business data. In one aspect, a framework middleware receives a request via an application to establish connection with a multiple systems. Upon establishing the connection, the business data from the multiple systems may be retrieved. The retrieved business data may be transformed by triggering system landscape transformation data model. From the transformed business data, contextual information associated with the business data may be determined. The determined contextual information may be displayed on a user interface or a dashboard that is instantiated by the application. The contextual information displayed on the user interface is customized based on user preferences that enhances and improves user experience when consuming business data.1. A system to improve user experience when consuming business data, comprising:
a processor, and one or more memory devices communicatively coupled with the processor and storing instructions related to:
receiving a request, at a framework middleware via an application, to establish a connection with a plurality of business management systems;
upon establishing the connection, the framework middleware retrieving business data from the plurality of business management systems;
based on an execution of a plurality of routines in the framework middleware, triggering a system landscape transformation model to transform the retrieved business data;
determining a contextual information associated with the transformed business data; and
rendering the determined contextual information on a user interface of the application, wherein the contextual information is customizable based on one or more parameters. 2. The system of claim 1, further comprising: replicating the business data from the plurality of business management systems and storing the replicated business data in the application. 3. The system of claim 1, wherein the framework middleware further comprises: a network gateway including a generic layer and a database in communication with the plurality of business management systems. 4. The system of claim 3, wherein: upon successful validation of the business data in the database using a global business rule, replicate the business data from the database in the network layer to the plurality of business management systems. 5. The system of claim 1, wherein the framework middleware executes a plurality of routines related to web content management service, document management service, dashboard management service, widget management service and workflow management service. 6. The system of claim 1, wherein the framework middleware executes the plurality of routines to validate the business data from the plurality of business management systems, using one or more local business rules. 7. The system of claim 1, wherein the framework middleware executes the plurality of routines to encrypt the business data by a sequential data encryption algorithm. 8. A computer implemented method to improve user experience when consuming business data, comprising:
receiving a request, at a framework middleware via an application, to establish a connection with a plurality of business management systems; upon establishing the connection, the framework middleware retrieving business data from the plurality of business management systems; based on an execution of a plurality of routines in the framework middleware, triggering a system landscape transformation model to transform the retrieved business data; determining a contextual information associated with the transformed business data; and rendering the determined contextual information on a user interface of the application, wherein the contextual information is customizable based on one or more parameters. 9. The computer implemented method of claim 8, further comprising: replicating the business data from the plurality of business management systems and storing the replicated business data in the application. 10. The computer implemented method of claim 8, wherein the framework middleware further comprises: a network gateway including a generic layer and a database in communication with the plurality of systems. 11. The computer implemented method of claim 8, wherein: upon successful validation of the business data in the database using a global business rule, replicate the business data from the database in the network layer to the plurality of business management systems. 12. The computer implemented method of claim 8, wherein the framework middleware executes the plurality of routines related to web content management service, document management service, dashboard management service, widget management service and workflow management service. 13. The computer implemented method of claim 8, wherein the framework middleware executes the plurality of routines to validate the business data from the plurality of business management systems, using one or more local business rules. 14. The computer implemented method of claim 8, wherein the framework middleware executes the plurality of routines to encrypt the business data by a sequential data encryption algorithm. 15. A non-transitory computer readable storage medium tangibly storing instructions, which when executed by a computer, cause the computer to execute operations comprising:
receiving a request, at a framework middleware via an application, to establish a connection with a plurality of business management systems; upon establishing the connection, the framework middleware retrieving business data from the plurality of business management systems; based on an execution of a plurality of routines in the framework middleware, triggering a system landscape transformation model to transform the retrieved business data; determining a contextual information associated with the transformed business data; and rendering the determined contextual information on a user interface of the application, wherein the contextual information is customizable based on one or more parameters. 16. The non-transitory computer readable storage medium of claim 15, further comprising instructions that cause the computer to execute operations comprising:
replicating the business data from the plurality of business management systems and storing the replicated business data in the application. 17. The non-transitory computer readable storage medium of claim 15, further comprising instructions that cause the computer to execute operations comprising: a network gateway that includes a generic layer and a database in communication with the plurality of business management systems. 18. The non-transitory computer readable storage medium of claim 17, wherein: upon successful validation of the business data in the database using a global business rule, replicate the business data from the database in the network layer to the plurality of business management systems. 19. The non-transitory computer readable storage medium of claim 15, wherein the framework middleware executes the plurality of routines related to web content management service, document management service, dashboard management service, widget management service and workflow management service. 20. The non-transitory computer readable storage medium of claim 15, wherein the framework middleware executes the plurality of routines to validate the business data from the plurality of business management systems, using one or more local business rules. | 2,100 |
6,013 | 6,013 | 13,903,906 | 2,127 | An apparatus that searches an input stream having a sequence of N-bit wide data words for a pattern using a plurality of small FSMs is disclosed. The apparatus includes a plurality of sub-word FSMs and a combiner. Each sub-word FSM has an input word size less than N-bits. Each FSM processes a corresponding segment of the N-bit words and generates a match output indicative of a possible match to the pattern when one of the input words to that FSM is received and that FSM moves to a predetermined match state. The combiner receives the match outputs from all of the sub-word FSMs and generates a pattern match output if all of the sub-word FSMs indicate a match to the pattern. The pattern is a variable pattern. In one embodiment, the FSMs are single bit FSMs. | 1. An apparatus that searches an input stream comprising a sequence of N-bit wide words for a pattern, said apparatus comprising
a plurality of sub-word FSMs, each sub-word FSM having a word size less than N-bits, each sub-word FSM processing a corresponding segment of said N-bit words and generating a match output indicative of a possible match to said pattern when one of said corresponding segments of one of said words is received by that sub-word FSM; and a combiner that receives said match outputs and generates a pattern match output if all of FSMs indicate a match of said pattern, wherein said pattern is a variable pattern. 2. The apparatus of claim 1 wherein said apparatus emulates a single FSM operating on said N-bit wide words to match said pattern, and wherein said match output corresponds to different possible match states in said single FSM. 3. The apparatus of claim 1 wherein said sub-word FSMs are single bit FSMs. 4. The apparatus of claim 1 wherein said apparatus emulates a single FSM operating simultaneously on a plurality of said N-bit wide words. 5. The apparatus of claim 1 wherein said pattern is a regular expression having a variable length. 6. The apparatus of claim 1 wherein said pattern has multiple tokens on an edge that needs to be distinguished. 7. The apparatus of claim 1 wherein at one bit of said N-bit wide words is not processed by any of said sub-word FSMs. 8. A method for finding a match to a variable pattern in an input stream comprising a sequence of input words, each input word being characterized by a plurality of sub-words, each of said sub-words having less bits than said input words, said method comprising:
providing a plurality of sub-word FSMs, each sub-word FSM operating on a different sub-word of each of said input words, each sub-word FSM providing a matched output indicative of a possible pattern match when that sub-word FSM enters a matched state; determining if said matched output of each of said sub-word FSMs indicate a common matched state; and outputting that common matched state. 9. The method of claim 8 wherein said plurality of sub-word FSMs emulate a single FSM operating simultaneously on a plurality of said input words. 10. The method of claim 8 wherein said pattern is a regular expression having a variable length. 11. The method of claim 8 wherein said pattern has multiple tokens on an edge that needs to be distinguished. 12. The method of claim 8 wherein at one bit of said input words is not processed by any of said sub-word FSMs. | An apparatus that searches an input stream having a sequence of N-bit wide data words for a pattern using a plurality of small FSMs is disclosed. The apparatus includes a plurality of sub-word FSMs and a combiner. Each sub-word FSM has an input word size less than N-bits. Each FSM processes a corresponding segment of the N-bit words and generates a match output indicative of a possible match to the pattern when one of the input words to that FSM is received and that FSM moves to a predetermined match state. The combiner receives the match outputs from all of the sub-word FSMs and generates a pattern match output if all of the sub-word FSMs indicate a match to the pattern. The pattern is a variable pattern. In one embodiment, the FSMs are single bit FSMs.1. An apparatus that searches an input stream comprising a sequence of N-bit wide words for a pattern, said apparatus comprising
a plurality of sub-word FSMs, each sub-word FSM having a word size less than N-bits, each sub-word FSM processing a corresponding segment of said N-bit words and generating a match output indicative of a possible match to said pattern when one of said corresponding segments of one of said words is received by that sub-word FSM; and a combiner that receives said match outputs and generates a pattern match output if all of FSMs indicate a match of said pattern, wherein said pattern is a variable pattern. 2. The apparatus of claim 1 wherein said apparatus emulates a single FSM operating on said N-bit wide words to match said pattern, and wherein said match output corresponds to different possible match states in said single FSM. 3. The apparatus of claim 1 wherein said sub-word FSMs are single bit FSMs. 4. The apparatus of claim 1 wherein said apparatus emulates a single FSM operating simultaneously on a plurality of said N-bit wide words. 5. The apparatus of claim 1 wherein said pattern is a regular expression having a variable length. 6. The apparatus of claim 1 wherein said pattern has multiple tokens on an edge that needs to be distinguished. 7. The apparatus of claim 1 wherein at one bit of said N-bit wide words is not processed by any of said sub-word FSMs. 8. A method for finding a match to a variable pattern in an input stream comprising a sequence of input words, each input word being characterized by a plurality of sub-words, each of said sub-words having less bits than said input words, said method comprising:
providing a plurality of sub-word FSMs, each sub-word FSM operating on a different sub-word of each of said input words, each sub-word FSM providing a matched output indicative of a possible pattern match when that sub-word FSM enters a matched state; determining if said matched output of each of said sub-word FSMs indicate a common matched state; and outputting that common matched state. 9. The method of claim 8 wherein said plurality of sub-word FSMs emulate a single FSM operating simultaneously on a plurality of said input words. 10. The method of claim 8 wherein said pattern is a regular expression having a variable length. 11. The method of claim 8 wherein said pattern has multiple tokens on an edge that needs to be distinguished. 12. The method of claim 8 wherein at one bit of said input words is not processed by any of said sub-word FSMs. | 2,100 |
6,014 | 6,014 | 14,316,250 | 2,156 | A metal fabrication resource performance data management method, includes storing a first set of data representative of a first plurality of parameters sampled during a metal fabrication operation of a first metal fabrication resource, selecting a second metal fabrication resource from the listing, and changing a first identifier of a portion of the first set of data to a second identifier associated with the second metal fabrication resource. The first metal fabrication resource is selectable by a user from a listing of individual and groups of resources, and the first set of data includes the first identifier corresponding to the first metal fabrication resource. A second set of data includes the second identifier corresponding to the second metal fabrication resource. | 1. A method of managing data of a metal fabrication resource performance system comprising:
storing in a non-transitory computer readable media a first set of data representative of a first plurality of parameters sampled during a metal fabrication operation of a first metal fabrication resource, wherein the resource is selectable by a user from a listing of individual and groups of resources, and the first set of data comprises a first identifier corresponding to the first metal fabrication resource; selecting a second metal fabrication resource from the listing, wherein a second set of data comprises a second identifier corresponding to the second metal fabrication resource; and changing the first identifier of a portion of the first set of data to the second identifier. 2. The method of claim 1, comprising copying the portion of the first set of data from a first memory area corresponding to the first metal fabrication resource to a second memory area corresponding to the second metal fabrication resource. 3. The method of claim 2, comprising:
storing the second set of data representative of a second plurality of parameters sampled during a metal fabrication operation of the second metal fabrication resource; and appending the copied portion of the first set of data to the second set of data. 4. The method of claim 3, comprising deleting the portion of the first set of data from the first memory area after appending the portion to the second set of data. 5. The method of claim 3, comprising presenting the second set of data and the appended copied portion as data corresponding to the second metal fabrication resource. 6. The method of claim 2, wherein at least one of the first memory area or the second memory area comprises a cloud based resource. 7. The method of claim 1, wherein the first set of data comprises a weld history or an event log. 8. The method of claim 1, comprising deleting references to the first identifier in the metal fabrication resource performance system after changing the first identifier of the portion of the first set of data. 9. The method of claim 1, comprising presenting a notification to an operator prior to changing the first identifier of the portion of the first set of data. 10. A metal fabrication resource performance monitoring interface comprising:
at least one user viewable configuration page defined by computer executed code transmitted to a user viewing device, the configuration page comprising:
a listing of individual and groups of metal fabrication resources;
user configurable inputs modifying properties of a selected metal fabrication resource from the listing;
a target merge list comprising a subset metal fabrication resources from the listing; and
a merge control configured to merge data records associated with the selected metal fabrication resource into data records associated with a target metal fabrication resource selected from the target merge list. 11. The interface of claim 10, wherein the code is executable by a processor for viewing in a general purpose browser. 12. The interface of claim 10, wherein the merge control is configured to delete data records associated with the selected metal fabrication resource from a memory or a cloud resource. 13. A metal fabrication resource performance monitoring system configured to:
store in a non-transitory computer readable media a first set of data representative of a first plurality of parameters sampled during a metal fabrication operation of a first metal fabrication resource, wherein the resource is selectable by a user from a listing of individual and groups of resources viewable via a viewable configuration page of a user viewing device, and the first set of data comprises a first identifier corresponding to the first metal fabrication resource; enable selection of a second metal fabrication resource from the listing, wherein a second set of data comprises a second identifier corresponding to the second metal fabrication resource; and change the first identifier of a portion of the first set of data to the second identifier. 14. The system of claim 13, wherein the system is configured to copy the portion of the first set of data from a first memory area corresponding to the first metal fabrication resource to a second memory area corresponding to the second metal fabrication resource. 15. The system of claim 14, wherein the system is configured to:
store the second set of data representative of a second plurality of parameters sampled during a metal fabrication operation of the second metal fabrication resource; and append the copied portion of the first set of data to the second set of data. 16. The system of claim 15, wherein the system is configured to delete the portion of the first set of data from the first memory area after appending the portion to the second set of data. 17. The system of claim 15, wherein the system is configured to present, via the viewable configuration page, the second set of data and the appended copied portion as data corresponding to the second metal fabrication resource. 18. The system of claim 14, wherein at least one of the first memory area or the second memory area comprises a cloud based resource. 19. The system of claim 13, wherein the first set of data comprises a weld history or an event log. 20. The system of claim 13, wherein the system is configured to delete references to the first identifier after changing the first identifier of the portion of the first set of data. 21. The system of claim 13, wherein the system is configured to present, via the viewable configuration page, a notification to an operator prior to changing the first identifier of the portion of the first set of data. | A metal fabrication resource performance data management method, includes storing a first set of data representative of a first plurality of parameters sampled during a metal fabrication operation of a first metal fabrication resource, selecting a second metal fabrication resource from the listing, and changing a first identifier of a portion of the first set of data to a second identifier associated with the second metal fabrication resource. The first metal fabrication resource is selectable by a user from a listing of individual and groups of resources, and the first set of data includes the first identifier corresponding to the first metal fabrication resource. A second set of data includes the second identifier corresponding to the second metal fabrication resource.1. A method of managing data of a metal fabrication resource performance system comprising:
storing in a non-transitory computer readable media a first set of data representative of a first plurality of parameters sampled during a metal fabrication operation of a first metal fabrication resource, wherein the resource is selectable by a user from a listing of individual and groups of resources, and the first set of data comprises a first identifier corresponding to the first metal fabrication resource; selecting a second metal fabrication resource from the listing, wherein a second set of data comprises a second identifier corresponding to the second metal fabrication resource; and changing the first identifier of a portion of the first set of data to the second identifier. 2. The method of claim 1, comprising copying the portion of the first set of data from a first memory area corresponding to the first metal fabrication resource to a second memory area corresponding to the second metal fabrication resource. 3. The method of claim 2, comprising:
storing the second set of data representative of a second plurality of parameters sampled during a metal fabrication operation of the second metal fabrication resource; and appending the copied portion of the first set of data to the second set of data. 4. The method of claim 3, comprising deleting the portion of the first set of data from the first memory area after appending the portion to the second set of data. 5. The method of claim 3, comprising presenting the second set of data and the appended copied portion as data corresponding to the second metal fabrication resource. 6. The method of claim 2, wherein at least one of the first memory area or the second memory area comprises a cloud based resource. 7. The method of claim 1, wherein the first set of data comprises a weld history or an event log. 8. The method of claim 1, comprising deleting references to the first identifier in the metal fabrication resource performance system after changing the first identifier of the portion of the first set of data. 9. The method of claim 1, comprising presenting a notification to an operator prior to changing the first identifier of the portion of the first set of data. 10. A metal fabrication resource performance monitoring interface comprising:
at least one user viewable configuration page defined by computer executed code transmitted to a user viewing device, the configuration page comprising:
a listing of individual and groups of metal fabrication resources;
user configurable inputs modifying properties of a selected metal fabrication resource from the listing;
a target merge list comprising a subset metal fabrication resources from the listing; and
a merge control configured to merge data records associated with the selected metal fabrication resource into data records associated with a target metal fabrication resource selected from the target merge list. 11. The interface of claim 10, wherein the code is executable by a processor for viewing in a general purpose browser. 12. The interface of claim 10, wherein the merge control is configured to delete data records associated with the selected metal fabrication resource from a memory or a cloud resource. 13. A metal fabrication resource performance monitoring system configured to:
store in a non-transitory computer readable media a first set of data representative of a first plurality of parameters sampled during a metal fabrication operation of a first metal fabrication resource, wherein the resource is selectable by a user from a listing of individual and groups of resources viewable via a viewable configuration page of a user viewing device, and the first set of data comprises a first identifier corresponding to the first metal fabrication resource; enable selection of a second metal fabrication resource from the listing, wherein a second set of data comprises a second identifier corresponding to the second metal fabrication resource; and change the first identifier of a portion of the first set of data to the second identifier. 14. The system of claim 13, wherein the system is configured to copy the portion of the first set of data from a first memory area corresponding to the first metal fabrication resource to a second memory area corresponding to the second metal fabrication resource. 15. The system of claim 14, wherein the system is configured to:
store the second set of data representative of a second plurality of parameters sampled during a metal fabrication operation of the second metal fabrication resource; and append the copied portion of the first set of data to the second set of data. 16. The system of claim 15, wherein the system is configured to delete the portion of the first set of data from the first memory area after appending the portion to the second set of data. 17. The system of claim 15, wherein the system is configured to present, via the viewable configuration page, the second set of data and the appended copied portion as data corresponding to the second metal fabrication resource. 18. The system of claim 14, wherein at least one of the first memory area or the second memory area comprises a cloud based resource. 19. The system of claim 13, wherein the first set of data comprises a weld history or an event log. 20. The system of claim 13, wherein the system is configured to delete references to the first identifier after changing the first identifier of the portion of the first set of data. 21. The system of claim 13, wherein the system is configured to present, via the viewable configuration page, a notification to an operator prior to changing the first identifier of the portion of the first set of data. | 2,100 |
6,015 | 6,015 | 14,806,169 | 2,148 | A system for an agnostic runtime architecture is disclosed. The system includes a system emulation/virtualization converter, an application code converter, and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image. The system converter further comprises a guest fetch logic component for accessing a plurality of guest instructions, a guest fetch buffer coupled to the guest fetch logic component and a branch prediction component for assembling the plurality of guest instructions into a guest instruction block, and a plurality of conversion tables including a first level conversion table and a second level conversion table coupled to the guest fetch buffer for translating the guest instruction block into a corresponding native conversion block. The system further includes a native cache coupled to the conversion tables for storing the corresponding native conversion block, a conversion look aside buffer coupled to the native cache for storing a mapping of the guest instruction block to corresponding native conversion block. Upon a subsequent request for a guest instruction, the conversion look aside buffer is indexed to determine whether a hit occurred, wherein the mapping indicates the guest instruction has a corresponding converted native instruction in the native cache, and in response to the hit the conversion look aside buffer forwards the translated native instruction for execution. | 1. A system for an agnostic runtime architecture, comprising:
a system emulation/virtualization converter; an application code converter; and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image, wherein the system converter further comprises: a guest fetch logic component for accessing a plurality of guest instructions; a guest fetch buffer coupled to the guest fetch logic component and a branch prediction component for assembling the plurality of guest instructions into a guest instruction block; a plurality of conversion tables including a first level conversion table and a second level conversion table coupled to the guest fetch buffer for translating the guest instruction block into a corresponding native conversion block; a native cache coupled to the conversion tables for storing the corresponding native conversion block; a conversion look aside buffer coupled to the native cache for storing a mapping of the guest instruction block to corresponding native conversion block; wherein upon a subsequent request for a guest instruction, the conversion look aside buffer is indexed to determine whether a hit occurred, wherein the mapping indicates the guest instruction has a corresponding converted native instruction in the native cache; and in response to the hit the conversion look aside buffer forwards the translated native instruction for execution. 2. The system of claim 1, wherein the first level conversion table and the second level conversion table are implemented as a high-speed low latency cache that is maintained coherently with a conversion table buffer stored in system memory. 3. The system of claim 1, wherein the first level conversion table and the second level conversion table include substitute fields for substituting native instructions for guest instructions and control fields for controlling the first level conversion table and a second level conversion table. 4. The system of claim 1, wherein the first level conversion table is used to perform first level translation on the guest instruction. 5. The system of claim 4, wherein the first level conversion table comprises a hash used to recognize a plurality of guest instructions. 6. The system of claim 5, wherein the plurality of guest instructions comprises at least one prefix guest instruction and a plurality of opcodes associated with the prefix guest instruction. 7. A system for translating instructions for a processor, comprising:
a system emulation/virtualization converter; an application code converter; and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image, wherein the system converter further comprises: a guest fetch logic component for accessing a plurality of guest instructions; a guest fetch buffer coupled to the guest fetch logic component and a branch prediction component for assembling the plurality of guest instructions into a guest instruction block; a plurality of conversion tables including a first level conversion table and a second level conversion table coupled to the guest fetch buffer for translating the guest instruction block into a corresponding native conversion block; a native cache coupled to the conversion tables for storing the corresponding native conversion block; a conversion look aside buffer coupled to the native cache for storing a mapping of the guest instruction block to corresponding native conversion block; wherein upon a subsequent request for a guest instruction, the conversion look aside buffer is indexed to determine whether a hit occurred, wherein the mapping indicates the guest instruction has a corresponding converted native instruction in the native cache; and in response to the hit the conversion look aside buffer forwards the translated native instruction for execution. 8. The system of claim 7, wherein the first level conversion table and the second level conversion table are implemented as a high-speed low latency cache that is maintained coherently with a conversion table buffer stored in system memory. 9. The system of claim 7, wherein the first level conversion table and the second level conversion table include substitute fields for substituting native instructions for guest instructions and control fields for controlling the first level conversion table and a second level conversion table. 10. The system of claim 7, wherein the first level conversion table is used to perform first level translation on the guest instruction. 11. The system of claim 10, wherein the first level conversion table comprises a hash used to recognize a plurality of guest instructions. 12. The system of claim 11, wherein the plurality of guest instructions comprises at least one prefix guest instruction and a plurality of opcodes associated with the prefix guest instruction. 13. A microprocessor that implements a method of translating instructions, said microprocessor comprises:
a microprocessor pipeline; a system emulation/virtualization converter; an application code converter; and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image, wherein the system converter further comprises: a guest fetch logic component for accessing a plurality of guest instructions; a guest fetch buffer coupled to the guest fetch logic component and a branch prediction component for assembling the plurality of guest instructions into a guest instruction block; a plurality of conversion tables including a first level conversion table and a second level conversion table coupled to the guest fetch buffer for translating the guest instruction block into a corresponding native conversion block; a native cache coupled to the conversion tables for storing the corresponding native conversion block; a conversion look aside buffer coupled to the native cache for storing a mapping of the guest instruction block to corresponding native conversion block; wherein upon a subsequent request for a guest instruction, the conversion look aside buffer is indexed to determine whether a hit occurred, wherein the mapping indicates the guest instruction has a corresponding converted native instruction in the native cache; and in response to the hit the conversion look aside buffer forwards the translated native instruction for execution. 14. The microprocessor of claim 13, wherein the first level conversion table and the second level conversion table are implemented as a high-speed low latency cache that is maintained coherently with a conversion table buffer stored in system memory. 15. The microprocessor of claim 13, wherein the first level conversion table and the second level conversion table include substitute fields for substituting native instructions for guest instructions and control fields for controlling the first level conversion table and a second level conversion table. 16. The microprocessor of claim 13, wherein the first level conversion table is used to perform first level translation on the guest instruction. 17. The microprocessor of claim 16, wherein the first level conversion table comprises a hash used to recognize a plurality of guest instructions. 18. The microprocessor of claim 17, wherein the plurality of guest instructions comprises at least one prefix guest instruction and a plurality of opcodes associated with the prefix guest instruction. 19. The microprocessor of claim 13 wherein the first level conversion table and the second level conversion table comprise a plurality of masks and a plurality of tags, wherein the tags determine pattern matches and the masks hid non-relevant bits of patterns. 20. The microprocessor of claim 19, wherein the plurality of masks and the plurality of tags are software loadable to enable configurable decoding. | A system for an agnostic runtime architecture is disclosed. The system includes a system emulation/virtualization converter, an application code converter, and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image. The system converter further comprises a guest fetch logic component for accessing a plurality of guest instructions, a guest fetch buffer coupled to the guest fetch logic component and a branch prediction component for assembling the plurality of guest instructions into a guest instruction block, and a plurality of conversion tables including a first level conversion table and a second level conversion table coupled to the guest fetch buffer for translating the guest instruction block into a corresponding native conversion block. The system further includes a native cache coupled to the conversion tables for storing the corresponding native conversion block, a conversion look aside buffer coupled to the native cache for storing a mapping of the guest instruction block to corresponding native conversion block. Upon a subsequent request for a guest instruction, the conversion look aside buffer is indexed to determine whether a hit occurred, wherein the mapping indicates the guest instruction has a corresponding converted native instruction in the native cache, and in response to the hit the conversion look aside buffer forwards the translated native instruction for execution.1. A system for an agnostic runtime architecture, comprising:
a system emulation/virtualization converter; an application code converter; and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image, wherein the system converter further comprises: a guest fetch logic component for accessing a plurality of guest instructions; a guest fetch buffer coupled to the guest fetch logic component and a branch prediction component for assembling the plurality of guest instructions into a guest instruction block; a plurality of conversion tables including a first level conversion table and a second level conversion table coupled to the guest fetch buffer for translating the guest instruction block into a corresponding native conversion block; a native cache coupled to the conversion tables for storing the corresponding native conversion block; a conversion look aside buffer coupled to the native cache for storing a mapping of the guest instruction block to corresponding native conversion block; wherein upon a subsequent request for a guest instruction, the conversion look aside buffer is indexed to determine whether a hit occurred, wherein the mapping indicates the guest instruction has a corresponding converted native instruction in the native cache; and in response to the hit the conversion look aside buffer forwards the translated native instruction for execution. 2. The system of claim 1, wherein the first level conversion table and the second level conversion table are implemented as a high-speed low latency cache that is maintained coherently with a conversion table buffer stored in system memory. 3. The system of claim 1, wherein the first level conversion table and the second level conversion table include substitute fields for substituting native instructions for guest instructions and control fields for controlling the first level conversion table and a second level conversion table. 4. The system of claim 1, wherein the first level conversion table is used to perform first level translation on the guest instruction. 5. The system of claim 4, wherein the first level conversion table comprises a hash used to recognize a plurality of guest instructions. 6. The system of claim 5, wherein the plurality of guest instructions comprises at least one prefix guest instruction and a plurality of opcodes associated with the prefix guest instruction. 7. A system for translating instructions for a processor, comprising:
a system emulation/virtualization converter; an application code converter; and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image, wherein the system converter further comprises: a guest fetch logic component for accessing a plurality of guest instructions; a guest fetch buffer coupled to the guest fetch logic component and a branch prediction component for assembling the plurality of guest instructions into a guest instruction block; a plurality of conversion tables including a first level conversion table and a second level conversion table coupled to the guest fetch buffer for translating the guest instruction block into a corresponding native conversion block; a native cache coupled to the conversion tables for storing the corresponding native conversion block; a conversion look aside buffer coupled to the native cache for storing a mapping of the guest instruction block to corresponding native conversion block; wherein upon a subsequent request for a guest instruction, the conversion look aside buffer is indexed to determine whether a hit occurred, wherein the mapping indicates the guest instruction has a corresponding converted native instruction in the native cache; and in response to the hit the conversion look aside buffer forwards the translated native instruction for execution. 8. The system of claim 7, wherein the first level conversion table and the second level conversion table are implemented as a high-speed low latency cache that is maintained coherently with a conversion table buffer stored in system memory. 9. The system of claim 7, wherein the first level conversion table and the second level conversion table include substitute fields for substituting native instructions for guest instructions and control fields for controlling the first level conversion table and a second level conversion table. 10. The system of claim 7, wherein the first level conversion table is used to perform first level translation on the guest instruction. 11. The system of claim 10, wherein the first level conversion table comprises a hash used to recognize a plurality of guest instructions. 12. The system of claim 11, wherein the plurality of guest instructions comprises at least one prefix guest instruction and a plurality of opcodes associated with the prefix guest instruction. 13. A microprocessor that implements a method of translating instructions, said microprocessor comprises:
a microprocessor pipeline; a system emulation/virtualization converter; an application code converter; and a system converter wherein the system emulation/virtualization converter and the application code converter implement a system emulation process, and wherein the system converter implements a system conversion process for executing code from a guest image, wherein the system converter further comprises: a guest fetch logic component for accessing a plurality of guest instructions; a guest fetch buffer coupled to the guest fetch logic component and a branch prediction component for assembling the plurality of guest instructions into a guest instruction block; a plurality of conversion tables including a first level conversion table and a second level conversion table coupled to the guest fetch buffer for translating the guest instruction block into a corresponding native conversion block; a native cache coupled to the conversion tables for storing the corresponding native conversion block; a conversion look aside buffer coupled to the native cache for storing a mapping of the guest instruction block to corresponding native conversion block; wherein upon a subsequent request for a guest instruction, the conversion look aside buffer is indexed to determine whether a hit occurred, wherein the mapping indicates the guest instruction has a corresponding converted native instruction in the native cache; and in response to the hit the conversion look aside buffer forwards the translated native instruction for execution. 14. The microprocessor of claim 13, wherein the first level conversion table and the second level conversion table are implemented as a high-speed low latency cache that is maintained coherently with a conversion table buffer stored in system memory. 15. The microprocessor of claim 13, wherein the first level conversion table and the second level conversion table include substitute fields for substituting native instructions for guest instructions and control fields for controlling the first level conversion table and a second level conversion table. 16. The microprocessor of claim 13, wherein the first level conversion table is used to perform first level translation on the guest instruction. 17. The microprocessor of claim 16, wherein the first level conversion table comprises a hash used to recognize a plurality of guest instructions. 18. The microprocessor of claim 17, wherein the plurality of guest instructions comprises at least one prefix guest instruction and a plurality of opcodes associated with the prefix guest instruction. 19. The microprocessor of claim 13 wherein the first level conversion table and the second level conversion table comprise a plurality of masks and a plurality of tags, wherein the tags determine pattern matches and the masks hid non-relevant bits of patterns. 20. The microprocessor of claim 19, wherein the plurality of masks and the plurality of tags are software loadable to enable configurable decoding. | 2,100 |
6,016 | 6,016 | 13,970,525 | 2,159 | While connected to cloud storage, a computing device writes data and metadata to the cloud storage, indicates success of the write to an application of the computing device, and, after indicating success to the application, writes the data and metadata to local storage of the computing device. The data and metadata may be written to different areas of the local storage. The computing device may also determine that it has recovered from a crash or has connected to the cloud storage after operating disconnected and reconcile the local storage with the cloud storage. The reconciliation may be based at least on a comparison of the metadata stored in the area of the local storage with metadata received from the cloud storage. The cloud storage may store each item of data contiguously with its metadata as an expanded block. | 1. A computer-implemented method comprising:
writing to local storage of a computing device, the writing mirroring a write to cloud storage and including writing data to a first area of the local storage and metadata for the data to a second area of the local storage; determining that the computing device has recovered from a crash or has connected to the cloud storage after operating disconnected from the cloud storage; and reconciling the local storage with the cloud storage based at least on a comparison of the metadata stored in the second area of the local storage with metadata received from the cloud storage. 2. The method of claim 1, wherein the writing is performed while the computing device is connected to the cloud storage and, subsequent to the writing but before the determining, the computing device crashes or becomes disconnected from the cloud storage. 3. The method of claim 2, wherein, while the computing device is disconnected from the cloud storage, the computing device reads from and writes to the local storage. 4. The method of claim 1, wherein the determining comprises determining that the computing device has recovered from a crash and the reconciling comprises:
comparing version identifiers included in the metadata stored in the second area of the local storage with version identifiers included in the metadata received from the cloud storage, and when the comparing indicates that the cloud storage has a more recent version of the data than the local storage, updating the local storage with the data from the cloud storage. 5. The method of claim 4, further comprising, while the computing device is connected to the cloud storage, writing the data to the first area of the local storage before writing the metadata to the second area of the local storage. 6. The method of claim 1, wherein the determining comprises determining that the computing device has connected to the cloud storage after operating disconnected from the cloud storage and the reconciling comprises:
comparing version identifiers included in the metadata stored in the second area of the local storage with version identifiers included in the metadata received from the cloud storage, and when the comparison indicates that the local storage has a more recent version of the data than the cloud storage, updating the cloud storage with the data from the local storage. 7. The method of claim 6, further comprising, while the computing device is disconnected from the cloud storage, writing metadata to the second area of the local storage before writing data to the first area of local storage. 8. The method of claim 1, wherein the determining comprises determining that the computing device has connected to the cloud storage after both operating disconnected from the cloud storage and crashing while operating disconnected, and the reconciling comprises:
scanning the local storage to detect torn writes, the detecting being based at least on calculating checksums, repairing the torn writes, comparing version identifiers included in the metadata stored in the first area of the local storage with version identifiers included in the metadata received from the cloud storage, and when the comparison indicates that the local storage has a more recent version of the data than the cloud storage, updating the cloud storage with the data from the local storage. 9. The method of claim 1, wherein the metadata stored in the second area of the local storage and the metadata received from the cloud storage include version identifiers. 10. One or more computer storage devices having stored thereon computer-executable instructions configured to program a computing device to perform operations comprising:
receiving a write request from an application of the computing device; writing data specified by the write request to cloud storage; indicating success of the write request to the application; and after indicating success to the application, writing the data to local storage of the computing device. 11. The one or more computer storage devices of claim 10, the operations further comprising, prior to writing the data to the cloud storage, determining that the computing device is connected to the cloud storage. 12. The one or more computer storage devices of claim 10, the operations further comprising:
determining that the computing device is not connected to the cloud storage; and while not connected to the cloud storage,
receiving a second write request, and
writing second data and metadata for the second data to the local storage, the writing the second data and metadata including writing the metadata to a first area of the local storage and, upon completion of writing the metadata, writing the second data to a second area of the local storage. 13. The one or more computer storage devices of claim 10, the operations further comprising reading from the cloud storage when the computing device is connected to the cloud storage and reading from the local storage when the computing device is not connected to the cloud storage. 14. The one or more computer storage devices of claim 10, wherein the writing includes writing the data to a first area of the local storage and, upon completing the writing of the data, writing metadata for the data to a second area of the local storage. 15. The one or more computer storage devices of claim 10, the operations further comprising incrementing a version identifier associated with the data,
wherein writing the data to the cloud storage includes writing the incremented version identifier as metadata for the data to the cloud storage, and wherein writing the data to the local storage includes writing the incremented version identifier as metadata for the data to the local storage. 16. A system comprising:
a cloud storage device having a first processor and first one or more modules that, when operated by the first processor, receive writes including data items and metadata for the data items and store each data item contiguously with its metadata as an expanded block; and a client device having a second processor and second one or more modules that, when operated by the second processor, write the data items and metadata to the cloud storage device and store the data items and metadata in local storage of the client device, wherein the data items are stored in a first area of the local storage and the metadata is stored in a second area of the local storage. 17. The system of claim 16, wherein the client device further includes a memory bitmap and the client device utilizes the memory bitmap to track writes to the local storage while the client device is disconnected from the cloud storage device. 18. The system of claim 16, wherein the second one or more modules include a virtual disk driver and a cloud client. 19. The system of claim 18, wherein the virtual disk driver receives write requests from applications of the client device and provides those write requests to the cloud client. 20. The system of claim 18, wherein the cloud client receives write requests from the virtual disk driver and performs the writing of the data items and metadata to the cloud storage device and the storing of the data items and metadata in the local storage. | While connected to cloud storage, a computing device writes data and metadata to the cloud storage, indicates success of the write to an application of the computing device, and, after indicating success to the application, writes the data and metadata to local storage of the computing device. The data and metadata may be written to different areas of the local storage. The computing device may also determine that it has recovered from a crash or has connected to the cloud storage after operating disconnected and reconcile the local storage with the cloud storage. The reconciliation may be based at least on a comparison of the metadata stored in the area of the local storage with metadata received from the cloud storage. The cloud storage may store each item of data contiguously with its metadata as an expanded block.1. A computer-implemented method comprising:
writing to local storage of a computing device, the writing mirroring a write to cloud storage and including writing data to a first area of the local storage and metadata for the data to a second area of the local storage; determining that the computing device has recovered from a crash or has connected to the cloud storage after operating disconnected from the cloud storage; and reconciling the local storage with the cloud storage based at least on a comparison of the metadata stored in the second area of the local storage with metadata received from the cloud storage. 2. The method of claim 1, wherein the writing is performed while the computing device is connected to the cloud storage and, subsequent to the writing but before the determining, the computing device crashes or becomes disconnected from the cloud storage. 3. The method of claim 2, wherein, while the computing device is disconnected from the cloud storage, the computing device reads from and writes to the local storage. 4. The method of claim 1, wherein the determining comprises determining that the computing device has recovered from a crash and the reconciling comprises:
comparing version identifiers included in the metadata stored in the second area of the local storage with version identifiers included in the metadata received from the cloud storage, and when the comparing indicates that the cloud storage has a more recent version of the data than the local storage, updating the local storage with the data from the cloud storage. 5. The method of claim 4, further comprising, while the computing device is connected to the cloud storage, writing the data to the first area of the local storage before writing the metadata to the second area of the local storage. 6. The method of claim 1, wherein the determining comprises determining that the computing device has connected to the cloud storage after operating disconnected from the cloud storage and the reconciling comprises:
comparing version identifiers included in the metadata stored in the second area of the local storage with version identifiers included in the metadata received from the cloud storage, and when the comparison indicates that the local storage has a more recent version of the data than the cloud storage, updating the cloud storage with the data from the local storage. 7. The method of claim 6, further comprising, while the computing device is disconnected from the cloud storage, writing metadata to the second area of the local storage before writing data to the first area of local storage. 8. The method of claim 1, wherein the determining comprises determining that the computing device has connected to the cloud storage after both operating disconnected from the cloud storage and crashing while operating disconnected, and the reconciling comprises:
scanning the local storage to detect torn writes, the detecting being based at least on calculating checksums, repairing the torn writes, comparing version identifiers included in the metadata stored in the first area of the local storage with version identifiers included in the metadata received from the cloud storage, and when the comparison indicates that the local storage has a more recent version of the data than the cloud storage, updating the cloud storage with the data from the local storage. 9. The method of claim 1, wherein the metadata stored in the second area of the local storage and the metadata received from the cloud storage include version identifiers. 10. One or more computer storage devices having stored thereon computer-executable instructions configured to program a computing device to perform operations comprising:
receiving a write request from an application of the computing device; writing data specified by the write request to cloud storage; indicating success of the write request to the application; and after indicating success to the application, writing the data to local storage of the computing device. 11. The one or more computer storage devices of claim 10, the operations further comprising, prior to writing the data to the cloud storage, determining that the computing device is connected to the cloud storage. 12. The one or more computer storage devices of claim 10, the operations further comprising:
determining that the computing device is not connected to the cloud storage; and while not connected to the cloud storage,
receiving a second write request, and
writing second data and metadata for the second data to the local storage, the writing the second data and metadata including writing the metadata to a first area of the local storage and, upon completion of writing the metadata, writing the second data to a second area of the local storage. 13. The one or more computer storage devices of claim 10, the operations further comprising reading from the cloud storage when the computing device is connected to the cloud storage and reading from the local storage when the computing device is not connected to the cloud storage. 14. The one or more computer storage devices of claim 10, wherein the writing includes writing the data to a first area of the local storage and, upon completing the writing of the data, writing metadata for the data to a second area of the local storage. 15. The one or more computer storage devices of claim 10, the operations further comprising incrementing a version identifier associated with the data,
wherein writing the data to the cloud storage includes writing the incremented version identifier as metadata for the data to the cloud storage, and wherein writing the data to the local storage includes writing the incremented version identifier as metadata for the data to the local storage. 16. A system comprising:
a cloud storage device having a first processor and first one or more modules that, when operated by the first processor, receive writes including data items and metadata for the data items and store each data item contiguously with its metadata as an expanded block; and a client device having a second processor and second one or more modules that, when operated by the second processor, write the data items and metadata to the cloud storage device and store the data items and metadata in local storage of the client device, wherein the data items are stored in a first area of the local storage and the metadata is stored in a second area of the local storage. 17. The system of claim 16, wherein the client device further includes a memory bitmap and the client device utilizes the memory bitmap to track writes to the local storage while the client device is disconnected from the cloud storage device. 18. The system of claim 16, wherein the second one or more modules include a virtual disk driver and a cloud client. 19. The system of claim 18, wherein the virtual disk driver receives write requests from applications of the client device and provides those write requests to the cloud client. 20. The system of claim 18, wherein the cloud client receives write requests from the virtual disk driver and performs the writing of the data items and metadata to the cloud storage device and the storing of the data items and metadata in the local storage. | 2,100 |
6,017 | 6,017 | 15,346,903 | 2,168 | A method includes allocating a cloud-based information repository to a customer. The information repository is hosted by a vendor and includes a plurality of compartments. The compartments include first, second, and third compartments, and each compartment has a different level of access. The information repository is accessible to the customer over a network connection. The method also includes receiving one or more first documents from the customer and saving the one or more first documents in the information repository. The method further includes receiving a request from the customer for a report associated with the information repository. In addition, the method includes generating the report and sending the report to the customer. The method could also include storing at least one second document in the information repository, where the at least one second document is associated with a life-cycle of a customer product. | 1. A method comprising:
allocating a cloud-based information repository to a customer, the information repository hosted by a vendor and comprising a plurality of compartments, the compartments comprising a first compartment, a second compartment, and a third compartment, each compartment having a different level of access, the information repository accessible to the customer over a network connection; receiving one or more first documents from the customer and saving the one or more first documents in the information repository; receiving a request from the customer for a report associated with the information repository; and generating the report and sending the report to the customer. 2. The method of claim 1, further comprising:
receiving a request from the customer for allocation and use of the cloud-based information repository; and approving the request for the allocation and use of the information repository. 3. The method of claim 1, wherein:
the first compartment is configured to be accessed and maintained by the customer only; the second compartment is configured to be accessed by the customer and the vendor at any time; and the third compartment is configured to be accessed jointly by the customer and the vendor and is accessible to the customer only at predetermined times. 4. The method of claim 1, wherein:
the first compartment is configured to store intellectual property of the customer, the intellectual property including at least one of: piping and instrumentation diagrams (P&IDs), control system configuration documents, and standards-related build documents; the second compartment is configured to store at least one of: non-disclosure agreements (NDAs), software patches and hot fixes, and release management information; and the third compartment is configured to store information that is distributable according to a time-bound license. 5. The method of claim 1, wherein the information repository is accessible by the customer via a web browser. 6. The method of claim 1, further comprising:
storing at least one second document in the information repository, the at least one second document associated with a life-cycle of a customer product. 7. The method of claim 6, further comprising:
automatically backing up the one or more first documents and the at least one second document according to a predetermined backup scheme. 8. An apparatus comprising:
at least one memory configured to store a cloud-based information repository for a customer, the information repository hosted by a vendor and comprising a plurality of compartments, the compartments comprising a first compartment, a second compartment, and a third compartment, each compartment having a different level of access, the information repository accessible to the customer over a network connection; and at least one processing device is configured to:
allocate the information repository to the customer;
receive one or more first documents from the customer and save the one or more first documents in the information repository;
receive a request from the customer for a report associated with the information repository; and
generate the report and send the report to the customer. 9. The apparatus of claim 8, wherein the at least one processing device is further configured to:
receive a request from the customer for allocation and use of the cloud-based information repository; and approve the request for the allocation and use of the information repository. 10. The apparatus of claim 20, wherein:
the first compartment is configured to be accessed and maintained by the customer only; the second compartment is configured to be accessed by the customer and the vendor at any time; and the third compartment is configured to be accessed jointly by the customer and the vendor and is accessible to the customer only at predetermined times. 11. The apparatus of claim 8, wherein:
the first compartment is configured to store intellectual property of the customer, the intellectual property including at least one of: piping and instrumentation diagrams (P&IDs), control system configuration documents, and standards-related build documents; the second compartment is configured to store at least one of: non-disclosure agreements (NDAs), software patches and hot fixes, and release management information; and the third compartment is configured to store information that is distributable according to a time-bound license. 12. The apparatus of claim 8, wherein the at least one processing device is configured to provide a web-based interface to the information repository. 13. The apparatus of claim 8, wherein the at least one processing device is further configured to store at least one second document in the information repository, the at least one second document associated with a life-cycle of a customer product. 14. The apparatus of claim 13, wherein the at least one processing device is further configured to automatically back up the one or more first documents and the at least one second document according to a predetermined backup scheme. 15. A non-transitory computer readable medium containing instructions that, when executed by at least one processing device, cause the at least one processing device to:
allocate a cloud-based information repository to a customer, the information repository hosted by a vendor and comprising a plurality of compartments, the compartments comprising a first compartment, a second compartment, and a third compartment, each compartment having a different level of access, the information repository accessible to the customer over a network connection; receive one or more first documents from the customer and save the one or more first documents in the information repository; receive a request from the customer for a report associated with the information repository; and generate the report and send the report to the customer. 16. The non-transitory computer readable medium of claim 15, further containing instructions that, when executed by the at least one processing device, cause the at least one processing device to:
receive a request from the customer for allocation and use of the cloud-based information repository; and approve the request for the allocation and use of the information repository. 17. The non-transitory computer readable medium of claim 15, wherein:
the first compartment is configured to be accessed and maintained by the customer only; the second compartment is configured to be accessed by the customer and the vendor at any time; and the third compartment is configured to be accessed jointly by the customer and the vendor and is accessible to the customer only at predetermined times. 18. The non-transitory computer readable medium of claim 15, wherein:
the first compartment is configured to store intellectual property of the customer, the intellectual property including at least one of: piping and instrumentation diagrams (P&IDs), control system configuration documents, and standards-related build documents; the second compartment is configured to store at least one of: non-disclosure agreements (NDAs), software patches and hot fixes, and release management information; and the third compartment is configured to store information that is distributable according to a time-bound license. 19. The non-transitory computer readable medium of claim 15, further containing instructions that, when executed by the at least one processing device, cause the at least one processing device to:
store at least one second document in the information repository, the at least one second document associated with a life-cycle of a customer product. 20. The non-transitory computer readable medium of claim 19, further containing instructions that, when executed by the at least one processing device, cause the at least one processing device to:
automatically back up the one or more first documents and the at least one second document according to a predetermined backup scheme. | A method includes allocating a cloud-based information repository to a customer. The information repository is hosted by a vendor and includes a plurality of compartments. The compartments include first, second, and third compartments, and each compartment has a different level of access. The information repository is accessible to the customer over a network connection. The method also includes receiving one or more first documents from the customer and saving the one or more first documents in the information repository. The method further includes receiving a request from the customer for a report associated with the information repository. In addition, the method includes generating the report and sending the report to the customer. The method could also include storing at least one second document in the information repository, where the at least one second document is associated with a life-cycle of a customer product.1. A method comprising:
allocating a cloud-based information repository to a customer, the information repository hosted by a vendor and comprising a plurality of compartments, the compartments comprising a first compartment, a second compartment, and a third compartment, each compartment having a different level of access, the information repository accessible to the customer over a network connection; receiving one or more first documents from the customer and saving the one or more first documents in the information repository; receiving a request from the customer for a report associated with the information repository; and generating the report and sending the report to the customer. 2. The method of claim 1, further comprising:
receiving a request from the customer for allocation and use of the cloud-based information repository; and approving the request for the allocation and use of the information repository. 3. The method of claim 1, wherein:
the first compartment is configured to be accessed and maintained by the customer only; the second compartment is configured to be accessed by the customer and the vendor at any time; and the third compartment is configured to be accessed jointly by the customer and the vendor and is accessible to the customer only at predetermined times. 4. The method of claim 1, wherein:
the first compartment is configured to store intellectual property of the customer, the intellectual property including at least one of: piping and instrumentation diagrams (P&IDs), control system configuration documents, and standards-related build documents; the second compartment is configured to store at least one of: non-disclosure agreements (NDAs), software patches and hot fixes, and release management information; and the third compartment is configured to store information that is distributable according to a time-bound license. 5. The method of claim 1, wherein the information repository is accessible by the customer via a web browser. 6. The method of claim 1, further comprising:
storing at least one second document in the information repository, the at least one second document associated with a life-cycle of a customer product. 7. The method of claim 6, further comprising:
automatically backing up the one or more first documents and the at least one second document according to a predetermined backup scheme. 8. An apparatus comprising:
at least one memory configured to store a cloud-based information repository for a customer, the information repository hosted by a vendor and comprising a plurality of compartments, the compartments comprising a first compartment, a second compartment, and a third compartment, each compartment having a different level of access, the information repository accessible to the customer over a network connection; and at least one processing device is configured to:
allocate the information repository to the customer;
receive one or more first documents from the customer and save the one or more first documents in the information repository;
receive a request from the customer for a report associated with the information repository; and
generate the report and send the report to the customer. 9. The apparatus of claim 8, wherein the at least one processing device is further configured to:
receive a request from the customer for allocation and use of the cloud-based information repository; and approve the request for the allocation and use of the information repository. 10. The apparatus of claim 20, wherein:
the first compartment is configured to be accessed and maintained by the customer only; the second compartment is configured to be accessed by the customer and the vendor at any time; and the third compartment is configured to be accessed jointly by the customer and the vendor and is accessible to the customer only at predetermined times. 11. The apparatus of claim 8, wherein:
the first compartment is configured to store intellectual property of the customer, the intellectual property including at least one of: piping and instrumentation diagrams (P&IDs), control system configuration documents, and standards-related build documents; the second compartment is configured to store at least one of: non-disclosure agreements (NDAs), software patches and hot fixes, and release management information; and the third compartment is configured to store information that is distributable according to a time-bound license. 12. The apparatus of claim 8, wherein the at least one processing device is configured to provide a web-based interface to the information repository. 13. The apparatus of claim 8, wherein the at least one processing device is further configured to store at least one second document in the information repository, the at least one second document associated with a life-cycle of a customer product. 14. The apparatus of claim 13, wherein the at least one processing device is further configured to automatically back up the one or more first documents and the at least one second document according to a predetermined backup scheme. 15. A non-transitory computer readable medium containing instructions that, when executed by at least one processing device, cause the at least one processing device to:
allocate a cloud-based information repository to a customer, the information repository hosted by a vendor and comprising a plurality of compartments, the compartments comprising a first compartment, a second compartment, and a third compartment, each compartment having a different level of access, the information repository accessible to the customer over a network connection; receive one or more first documents from the customer and save the one or more first documents in the information repository; receive a request from the customer for a report associated with the information repository; and generate the report and send the report to the customer. 16. The non-transitory computer readable medium of claim 15, further containing instructions that, when executed by the at least one processing device, cause the at least one processing device to:
receive a request from the customer for allocation and use of the cloud-based information repository; and approve the request for the allocation and use of the information repository. 17. The non-transitory computer readable medium of claim 15, wherein:
the first compartment is configured to be accessed and maintained by the customer only; the second compartment is configured to be accessed by the customer and the vendor at any time; and the third compartment is configured to be accessed jointly by the customer and the vendor and is accessible to the customer only at predetermined times. 18. The non-transitory computer readable medium of claim 15, wherein:
the first compartment is configured to store intellectual property of the customer, the intellectual property including at least one of: piping and instrumentation diagrams (P&IDs), control system configuration documents, and standards-related build documents; the second compartment is configured to store at least one of: non-disclosure agreements (NDAs), software patches and hot fixes, and release management information; and the third compartment is configured to store information that is distributable according to a time-bound license. 19. The non-transitory computer readable medium of claim 15, further containing instructions that, when executed by the at least one processing device, cause the at least one processing device to:
store at least one second document in the information repository, the at least one second document associated with a life-cycle of a customer product. 20. The non-transitory computer readable medium of claim 19, further containing instructions that, when executed by the at least one processing device, cause the at least one processing device to:
automatically back up the one or more first documents and the at least one second document according to a predetermined backup scheme. | 2,100 |
6,018 | 6,018 | 14,574,352 | 2,184 | An apparatus includes a first port set that includes an input port and an output port. The apparatus further includes a plurality of second port sets. Each of the second port sets includes an input port coupled to the output port of the first port set and an output port coupled to the input port of the first port set. The plurality of second port sets are to each communicate at a first maximum bandwidth and the first port set is to communicate at a second maximum bandwidth that is higher than the first maximum bandwidth. | 1. A processor to comprise:
a first router to comprise a plurality of port sets, wherein the plurality of port sets are to comprise:
a first port set to comprise an input port and an output port;
a second plurality of port sets, wherein each port set of the second plurality of port sets is to comprise:
an input port to be coupled to the output port of the first port set; and
an output port to be coupled to the input port of the first port set; and
wherein the input port of the first port set is to simultaneously provide circuit-switched data from a core of the processor to each port set of the second plurality of port sets, and wherein the output port of the first port set is to simultaneously provide circuit-switched data from each port set of the second plurality of port sets to the core. 2. The processor of claim 1, wherein an output port of a port set of the second plurality of port sets is further to be coupled to an input port of a second port set of the second plurality of port sets, and wherein an input port of the port set of the second plurality of port sets is further to be coupled to an output port of the second port set of the second plurality of port sets. 3. The processor of claim 1, wherein the input port of the first port set is further to simultaneously provide packet-switched data from the core to the second plurality of port sets. 4. The processor of claim 1, wherein the output port of the first port set is further to simultaneously provide packet-switched data from the second plurality of port sets to the core. 5. The processor of claim 1, wherein an input port of a port set of the second plurality of port sets is to receive data from a corresponding port of another router of the processor. 6. The processor of claim 1, wherein an output port of a port set of the second plurality of port sets is to provide data received from the core to a corresponding port of another router of the processor. 7. The processor of claim 1, wherein the processor is further to comprise a plurality of routers to communicate with the first router through the second plurality of port sets. 8. The processor of claim 7, wherein a die is to comprise the processor. 9. The processor of claim 7, wherein the plurality of routers are to communicate according to a source-synchronous protocol. 10. The processor of claim 7, wherein the plurality of routers are to communicate according to a synchronous protocol. 11. The processor of claim 1, wherein the output port of the first port set is further to comprise a first plurality of flip flops sets, each flip flop set of the first plurality of flip flop sets to store packet data provided by a distinct input port of the second plurality of port sets, wherein each flip flop set of the first plurality of flip flop sets is to be enabled simultaneously. 12. The processor of claim 11, wherein an output port of the second plurality of port sets is further to comprise a plurality of flip flops, each flip flop of the plurality of flip flops to store packet data provided by an input port of the second plurality of port sets or the input port of the first port set. 13. The processor of claim 1, wherein:
the input port and the output port of the first port set are each to comprise an equal number of circuit-switched data carrying wires entering the respective port and exiting the respective port; and the input port and the output port of the first port set are each to comprise an equal number of packet-switched data carrying wires entering the respective port and exiting the respective port. 14. The processor of claim 1, wherein:
the first port set does not arbitrate between data received simultaneously at the output port of the first set from the input ports of the second plurality of port sets; and the first port set does not arbitrate between data sent simultaneously from the input port of the first set to the output ports of the second plurality of port sets. 15. An apparatus to comprise:
a first port set to comprise an input port and an output port; a plurality of second port sets, wherein each of the second port sets is to comprise:
an input port coupled to the output port of the first port set;
an output port coupled to the input port of the first port set; and
wherein the plurality of second port sets are to each communicate at a first maximum bandwidth and the first port set is to communicate at a second maximum bandwidth that is higher than the first maximum bandwidth. 16. The apparatus of claim 15, further to comprise a core that is to receive data from the output port of the first port set and to provide data to the input port of the first port set. 17. The apparatus of claim 15, further to comprise a plurality of connections, each connection to couple the input port of the first port set to a distinct output port of the second port sets. 18. The apparatus of claim 17, wherein:
a first connection of the plurality of connections is to communicate first circuit-switched data from the input port of the first port set to an output port of a port set of the plurality of second port sets; a second connection of the plurality of connections is to communicate second circuit-switched data from the input port of the first port set to an output port of a second port set of the plurality of second port sets; and the first circuit-switched data and the second circuit-switched data are simultaneously communicated by the first connection and second connection. 19. The apparatus of claim 17, wherein:
a first connection of the plurality of connections is to communicate a first control data to establish a first circuit-switched data connection from the input port of the first port set; a second connection of the plurality of connections is to communicate a second control data to establish a second circuit-switched data connection from the input port of the first port set; and the first control data and the second control data are simultaneously communicated by the first connection and the second connection. 20. A non-transitory machine readable medium including information to represent structures, when manufactured, to be configured to:
provide, from a core of a processor, first circuit-switched data to a first input port of a router; and simultaneously communicate a first portion of the first circuit-switched data from the first input port of the router to a first output port of the router and a second portion of the first circuit-switched data from the first input port of the router to a second output port of the router. 21. The medium of claim 20, the structures, when manufactured, to be further configured to:
receive a first portion of second circuit-switched data at a second input port of the router and a second portion of second circuit-switched data at a third input port of the router; and simultaneously communicate, by the second and third input ports, the first and second portions of the second circuit-switched data to the core of the processor via a third output port of the router. 22. A system to comprise:
a plurality of cores each associated with a router of a network on a chip, each of the routers comprising:
a first port set to comprise an input port and an output port;
a plurality of second port sets, wherein each of the second port sets is to comprise:
an input port coupled to the output port of the first port set;
an output port coupled to the input port of the first port set; and
wherein the plurality of second port sets are to each communicate at a first maximum bandwidth and the first port set is to communicate at a second maximum bandwidth that is higher than the first maximum bandwidth. | An apparatus includes a first port set that includes an input port and an output port. The apparatus further includes a plurality of second port sets. Each of the second port sets includes an input port coupled to the output port of the first port set and an output port coupled to the input port of the first port set. The plurality of second port sets are to each communicate at a first maximum bandwidth and the first port set is to communicate at a second maximum bandwidth that is higher than the first maximum bandwidth.1. A processor to comprise:
a first router to comprise a plurality of port sets, wherein the plurality of port sets are to comprise:
a first port set to comprise an input port and an output port;
a second plurality of port sets, wherein each port set of the second plurality of port sets is to comprise:
an input port to be coupled to the output port of the first port set; and
an output port to be coupled to the input port of the first port set; and
wherein the input port of the first port set is to simultaneously provide circuit-switched data from a core of the processor to each port set of the second plurality of port sets, and wherein the output port of the first port set is to simultaneously provide circuit-switched data from each port set of the second plurality of port sets to the core. 2. The processor of claim 1, wherein an output port of a port set of the second plurality of port sets is further to be coupled to an input port of a second port set of the second plurality of port sets, and wherein an input port of the port set of the second plurality of port sets is further to be coupled to an output port of the second port set of the second plurality of port sets. 3. The processor of claim 1, wherein the input port of the first port set is further to simultaneously provide packet-switched data from the core to the second plurality of port sets. 4. The processor of claim 1, wherein the output port of the first port set is further to simultaneously provide packet-switched data from the second plurality of port sets to the core. 5. The processor of claim 1, wherein an input port of a port set of the second plurality of port sets is to receive data from a corresponding port of another router of the processor. 6. The processor of claim 1, wherein an output port of a port set of the second plurality of port sets is to provide data received from the core to a corresponding port of another router of the processor. 7. The processor of claim 1, wherein the processor is further to comprise a plurality of routers to communicate with the first router through the second plurality of port sets. 8. The processor of claim 7, wherein a die is to comprise the processor. 9. The processor of claim 7, wherein the plurality of routers are to communicate according to a source-synchronous protocol. 10. The processor of claim 7, wherein the plurality of routers are to communicate according to a synchronous protocol. 11. The processor of claim 1, wherein the output port of the first port set is further to comprise a first plurality of flip flops sets, each flip flop set of the first plurality of flip flop sets to store packet data provided by a distinct input port of the second plurality of port sets, wherein each flip flop set of the first plurality of flip flop sets is to be enabled simultaneously. 12. The processor of claim 11, wherein an output port of the second plurality of port sets is further to comprise a plurality of flip flops, each flip flop of the plurality of flip flops to store packet data provided by an input port of the second plurality of port sets or the input port of the first port set. 13. The processor of claim 1, wherein:
the input port and the output port of the first port set are each to comprise an equal number of circuit-switched data carrying wires entering the respective port and exiting the respective port; and the input port and the output port of the first port set are each to comprise an equal number of packet-switched data carrying wires entering the respective port and exiting the respective port. 14. The processor of claim 1, wherein:
the first port set does not arbitrate between data received simultaneously at the output port of the first set from the input ports of the second plurality of port sets; and the first port set does not arbitrate between data sent simultaneously from the input port of the first set to the output ports of the second plurality of port sets. 15. An apparatus to comprise:
a first port set to comprise an input port and an output port; a plurality of second port sets, wherein each of the second port sets is to comprise:
an input port coupled to the output port of the first port set;
an output port coupled to the input port of the first port set; and
wherein the plurality of second port sets are to each communicate at a first maximum bandwidth and the first port set is to communicate at a second maximum bandwidth that is higher than the first maximum bandwidth. 16. The apparatus of claim 15, further to comprise a core that is to receive data from the output port of the first port set and to provide data to the input port of the first port set. 17. The apparatus of claim 15, further to comprise a plurality of connections, each connection to couple the input port of the first port set to a distinct output port of the second port sets. 18. The apparatus of claim 17, wherein:
a first connection of the plurality of connections is to communicate first circuit-switched data from the input port of the first port set to an output port of a port set of the plurality of second port sets; a second connection of the plurality of connections is to communicate second circuit-switched data from the input port of the first port set to an output port of a second port set of the plurality of second port sets; and the first circuit-switched data and the second circuit-switched data are simultaneously communicated by the first connection and second connection. 19. The apparatus of claim 17, wherein:
a first connection of the plurality of connections is to communicate a first control data to establish a first circuit-switched data connection from the input port of the first port set; a second connection of the plurality of connections is to communicate a second control data to establish a second circuit-switched data connection from the input port of the first port set; and the first control data and the second control data are simultaneously communicated by the first connection and the second connection. 20. A non-transitory machine readable medium including information to represent structures, when manufactured, to be configured to:
provide, from a core of a processor, first circuit-switched data to a first input port of a router; and simultaneously communicate a first portion of the first circuit-switched data from the first input port of the router to a first output port of the router and a second portion of the first circuit-switched data from the first input port of the router to a second output port of the router. 21. The medium of claim 20, the structures, when manufactured, to be further configured to:
receive a first portion of second circuit-switched data at a second input port of the router and a second portion of second circuit-switched data at a third input port of the router; and simultaneously communicate, by the second and third input ports, the first and second portions of the second circuit-switched data to the core of the processor via a third output port of the router. 22. A system to comprise:
a plurality of cores each associated with a router of a network on a chip, each of the routers comprising:
a first port set to comprise an input port and an output port;
a plurality of second port sets, wherein each of the second port sets is to comprise:
an input port coupled to the output port of the first port set;
an output port coupled to the input port of the first port set; and
wherein the plurality of second port sets are to each communicate at a first maximum bandwidth and the first port set is to communicate at a second maximum bandwidth that is higher than the first maximum bandwidth. | 2,100 |
6,019 | 6,019 | 15,795,650 | 2,132 | A method includes receiving data objects, determining a predicted lifespan of each data object, and instantiating multiple shard files. Each shard file has an associated predicted lifespan range. The method also includes writing each data object into a corresponding shard file having the associated predicted lifespan range that includes the predicted lifespan of the respective data object and storing the shard files in a distributed system. The method also includes determining whether any stored shard files satisfy a compaction criteria based on a number of deleted data objects in each corresponding stored shard file. For each stored shard file satisfying the compaction criteria, the method also includes compacting the stored shard file by rewriting the remaining data objects of the stored shard file into a new shard file. | 1. A method comprising:
receiving, at data processing hardware, data objects; determining, by the data processing hardware, a predicted lifespan of each data object; instantiating, by the data processing hardware, multiple shard files, each shard file having an associated predicted lifespan range; writing, by the data processing hardware, each data object into a corresponding shard file having the associated predicted lifespan range that includes the predicted lifespan of the respective data object; storing, by the data processing hardware, the shard files in a distributed storage system; determining, by the data processing hardware, whether any stored shard files satisfy a compaction criteria based on a number of deleted data objects in each corresponding stored shard file; and for each stored shard files satisfying the compaction criteria, compacting, by the data processing hardware, the stored shard file by rewriting the remaining data objects of the stored shard file into a new shard file. 2. The method of claim 1, wherein the predicted lifespan ranges of the shard files collectively cover zero to infinite days. 3. The method of claim 1, further comprising:
determining, by the data processing hardware, whether each shard file satisfies a storage criteria; and for each shard file satisfying the storage criteria, storing, by the data processing hardware, the respective shard file in the distributed storage system. 4. The method of claim 3, wherein the storage criteria is satisfied when the respective shard file contains a threshold number of data objects or the respective shard file exists for a threshold period of time after instantiation. 5. The method of claim 1, wherein determining the predicted lifespan of a respective data object is based on at least one of a source of the respective data object, a name of the respective data object, a size of the respective data object, or a creation time of the respective data object. 6. The method of claim 1, wherein determining the predicted lifespan of a respective data object comprises:
receiving features of the respective data object; and classifying the respective data object by executing a classifier on a machine learning model trained on a dataset of previously stored data objects using the received features as inputs for the classification. 7. The method of claim 6, wherein the machine learning model comprises at least one of a random forest predictive model or a neural net based predictive model. 8. The method of claim 6, wherein the features comprise at least one of:
a data bucket name for a data bucket holding the respective data object, the data bucket name being user specific at a bucket creation time; a historical lifespan pattern for past data objects in the data bucket; an upload time corresponding to when the respective data object was uploaded to the data bucket; a bucket location indicating a location of the respective data object within the distributed system; an upload location indicating a geographical location of the respective data object when the respective data object was uploaded to the data bucket; a size of the respective data object; or a storage class of the respective data object, each storage class having a different level of data availability. 9. The method of claim 1, wherein the compaction criteria is satisfied when:
the associated predicted lifespan range of the stored shard file has expired; a majority of the data objects of the stored shard file have been deleted; or all of the data objects of the stored shard file have been deleted. 10. The method of claim 1, wherein rewriting the remaining data objects of the stored shard file into the new shard file comprises:
identifying, by the data processing hardware, non-deleted, live data chunks that are constituents of the remaining data objects of the stored shard file; and associating, by the data processing hardware, the non-deleted, live data chunks with the new shard file. 11. A system comprising:
data processing hardware; and memory hardware in communication with the data processing hardware, the memory hardware storing instructions that when executed on the data processing hardware cause the data processing hardware to perform operations comprising: receiving data objects; determining a predicted lifespan of each data object; instantiating multiple shard files, each shard file having an associated predicted lifespan range; writing each data object into a corresponding shard file having the associated predicted lifespan range that includes the predicted lifespan of the respective data object; storing the shard files in a distributed storage system; determining whether any stored shard files satisfy a compaction criteria based on a number of deleted data objects in each corresponding stored shard file; and for each stored shard files satisfying the compaction criteria, compacting the stored shard file by rewriting the remaining data objects of the stored shard file into a new shard file. 12. The system of claim 11, wherein the predicted lifespan ranges of the shard files collectively cover zero to infinite days. 13. The system of claim 11, wherein the operations further comprise:
determining whether each shard file satisfies a storage criteria; and for each shard file satisfying the storage criteria, storing the respective shard file in the distributed storage system. 14. The system of claim 13, wherein the storage criteria is satisfied when the respective shard file contains a threshold number of data objects or the respective shard file exists for a threshold period of time after instantiation. 15. The system of claim 11, wherein determining the predicted lifespan of a respective data object is based on at least one of a source of the respective data object, a name of the respective data object, a size of the respective data object, or a creation time of the respective data object. 16. The system of claim 11, wherein determining the predicted lifespan of a respective data object comprises:
receiving features of the respective data object; and classifying the respective data object by executing a classifier on a machine learning model trained on a dataset of previously stored data objects using the received features as inputs for the classification. 17. The system of claim 16, wherein the machine learning model comprises at least one of a random forest predictive model or a neural net based predictive model. 18. The system of claim 16, wherein the features comprise at least one of:
a data bucket name for a data bucket holding the respective data object, the data bucket name being user specific at a bucket creation time; a historical lifespan pattern for past data objects in the data bucket; an upload time corresponding to when the respective data object was uploaded to the data bucket; a bucket location indicating a location of the respective data object within the distributed system; an upload location indicating a geographical location of the respective data object when the respective data object was uploaded to the data bucket; a size of the respective data object; or a storage class of the respective data object, each storage class having a different level of data availability. 19. The system of claim 11, wherein the compaction criteria is satisfied when:
the associated predicted lifespan range of the stored shard file has expired; a majority of the data objects of the stored shard file have been deleted; or all of the data objects of the stored shard file have been deleted. 20. The system of claim 11, wherein rewriting the remaining data objects of the stored shard file into the new shard file comprises:
identifying, by the data processing hardware, non-deleted, live data chunks that are constituents of the remaining data objects of the stored shard file; and associating, by the data processing hardware, the non-deleted, live data chunks with the new shard file. | A method includes receiving data objects, determining a predicted lifespan of each data object, and instantiating multiple shard files. Each shard file has an associated predicted lifespan range. The method also includes writing each data object into a corresponding shard file having the associated predicted lifespan range that includes the predicted lifespan of the respective data object and storing the shard files in a distributed system. The method also includes determining whether any stored shard files satisfy a compaction criteria based on a number of deleted data objects in each corresponding stored shard file. For each stored shard file satisfying the compaction criteria, the method also includes compacting the stored shard file by rewriting the remaining data objects of the stored shard file into a new shard file.1. A method comprising:
receiving, at data processing hardware, data objects; determining, by the data processing hardware, a predicted lifespan of each data object; instantiating, by the data processing hardware, multiple shard files, each shard file having an associated predicted lifespan range; writing, by the data processing hardware, each data object into a corresponding shard file having the associated predicted lifespan range that includes the predicted lifespan of the respective data object; storing, by the data processing hardware, the shard files in a distributed storage system; determining, by the data processing hardware, whether any stored shard files satisfy a compaction criteria based on a number of deleted data objects in each corresponding stored shard file; and for each stored shard files satisfying the compaction criteria, compacting, by the data processing hardware, the stored shard file by rewriting the remaining data objects of the stored shard file into a new shard file. 2. The method of claim 1, wherein the predicted lifespan ranges of the shard files collectively cover zero to infinite days. 3. The method of claim 1, further comprising:
determining, by the data processing hardware, whether each shard file satisfies a storage criteria; and for each shard file satisfying the storage criteria, storing, by the data processing hardware, the respective shard file in the distributed storage system. 4. The method of claim 3, wherein the storage criteria is satisfied when the respective shard file contains a threshold number of data objects or the respective shard file exists for a threshold period of time after instantiation. 5. The method of claim 1, wherein determining the predicted lifespan of a respective data object is based on at least one of a source of the respective data object, a name of the respective data object, a size of the respective data object, or a creation time of the respective data object. 6. The method of claim 1, wherein determining the predicted lifespan of a respective data object comprises:
receiving features of the respective data object; and classifying the respective data object by executing a classifier on a machine learning model trained on a dataset of previously stored data objects using the received features as inputs for the classification. 7. The method of claim 6, wherein the machine learning model comprises at least one of a random forest predictive model or a neural net based predictive model. 8. The method of claim 6, wherein the features comprise at least one of:
a data bucket name for a data bucket holding the respective data object, the data bucket name being user specific at a bucket creation time; a historical lifespan pattern for past data objects in the data bucket; an upload time corresponding to when the respective data object was uploaded to the data bucket; a bucket location indicating a location of the respective data object within the distributed system; an upload location indicating a geographical location of the respective data object when the respective data object was uploaded to the data bucket; a size of the respective data object; or a storage class of the respective data object, each storage class having a different level of data availability. 9. The method of claim 1, wherein the compaction criteria is satisfied when:
the associated predicted lifespan range of the stored shard file has expired; a majority of the data objects of the stored shard file have been deleted; or all of the data objects of the stored shard file have been deleted. 10. The method of claim 1, wherein rewriting the remaining data objects of the stored shard file into the new shard file comprises:
identifying, by the data processing hardware, non-deleted, live data chunks that are constituents of the remaining data objects of the stored shard file; and associating, by the data processing hardware, the non-deleted, live data chunks with the new shard file. 11. A system comprising:
data processing hardware; and memory hardware in communication with the data processing hardware, the memory hardware storing instructions that when executed on the data processing hardware cause the data processing hardware to perform operations comprising: receiving data objects; determining a predicted lifespan of each data object; instantiating multiple shard files, each shard file having an associated predicted lifespan range; writing each data object into a corresponding shard file having the associated predicted lifespan range that includes the predicted lifespan of the respective data object; storing the shard files in a distributed storage system; determining whether any stored shard files satisfy a compaction criteria based on a number of deleted data objects in each corresponding stored shard file; and for each stored shard files satisfying the compaction criteria, compacting the stored shard file by rewriting the remaining data objects of the stored shard file into a new shard file. 12. The system of claim 11, wherein the predicted lifespan ranges of the shard files collectively cover zero to infinite days. 13. The system of claim 11, wherein the operations further comprise:
determining whether each shard file satisfies a storage criteria; and for each shard file satisfying the storage criteria, storing the respective shard file in the distributed storage system. 14. The system of claim 13, wherein the storage criteria is satisfied when the respective shard file contains a threshold number of data objects or the respective shard file exists for a threshold period of time after instantiation. 15. The system of claim 11, wherein determining the predicted lifespan of a respective data object is based on at least one of a source of the respective data object, a name of the respective data object, a size of the respective data object, or a creation time of the respective data object. 16. The system of claim 11, wherein determining the predicted lifespan of a respective data object comprises:
receiving features of the respective data object; and classifying the respective data object by executing a classifier on a machine learning model trained on a dataset of previously stored data objects using the received features as inputs for the classification. 17. The system of claim 16, wherein the machine learning model comprises at least one of a random forest predictive model or a neural net based predictive model. 18. The system of claim 16, wherein the features comprise at least one of:
a data bucket name for a data bucket holding the respective data object, the data bucket name being user specific at a bucket creation time; a historical lifespan pattern for past data objects in the data bucket; an upload time corresponding to when the respective data object was uploaded to the data bucket; a bucket location indicating a location of the respective data object within the distributed system; an upload location indicating a geographical location of the respective data object when the respective data object was uploaded to the data bucket; a size of the respective data object; or a storage class of the respective data object, each storage class having a different level of data availability. 19. The system of claim 11, wherein the compaction criteria is satisfied when:
the associated predicted lifespan range of the stored shard file has expired; a majority of the data objects of the stored shard file have been deleted; or all of the data objects of the stored shard file have been deleted. 20. The system of claim 11, wherein rewriting the remaining data objects of the stored shard file into the new shard file comprises:
identifying, by the data processing hardware, non-deleted, live data chunks that are constituents of the remaining data objects of the stored shard file; and associating, by the data processing hardware, the non-deleted, live data chunks with the new shard file. | 2,100 |
6,020 | 6,020 | 14,939,138 | 2,153 | Methods, systems, and computer-readable storage media for range queries over encrypted data include actions of receiving a range query token, determining one or more of whether a tree list of an encrypted search index is empty and a range of the token intersects with a range accounted of a tree in the tree list, the encrypted search index including the tree list and a point list, receiving encrypted query results based on one of a search tree, if the tree list is not empty and a range of the token is at least a sub-range of a range accounted for in the tree list, and the point list, if the tree list is empty or the range of the token is not at least a sub-range of a range accounted for in the tree list, and updating the encrypted search index based on the token. | 1. A computer-implemented method for performing range queries over encrypted data, the method being executed by a server-side computing device and comprising:
receiving, by the server-side computing device, a range query token from a client-side computing device; determining, by the server-side computing device, one or more of whether a tree list of an encrypted search index is empty and a range of the range query token is intersecting with a range accounted by at least one tree in the tree list, the encrypted search index comprising the tree list and a point list; receiving, by the server-side computing device, encrypted query results based on one of a search tree, if the tree list is not empty and a range of the range query token is at least a sub-range of a range accounted for in the tree list, and the point list, if the tree list is empty or the range of the range query token is not at least a sub-range of a range accounted for in the tree list; and updating, by the server-side computing device, the encrypted search index based on the range query token and a client-server protocol. 2. The method of claim 1, wherein updating the encrypted search index comprises refining a search tree of the tree list at least partially based on transmitting the range query token and a previously received range query token to the client-side computing device, and receiving refined range tokens from the client-side computing device, the encrypted search index being updated based on the refined range tokens. 3. The method of claim 1, wherein updating the encrypted search index comprises extending a search tree of the tree list to provide an extended search tree at least partially based on transmitting a root node of the search tree and a previously received query corresponding to the search tree to the client-side computing device to provide a new range query token corresponding to the extended search tree. 4. The method of claim 1, wherein updating the encrypted search index comprises merging multiple search trees of the tree list to provide a merged search tree at least partially based on transmitting respective root nodes of the multiple search trees to the client-side computing device, and receiving a revised token corresponding to the merged search tree. 5. The method of claim 4, wherein the multiple trees are merged in response to determining that there is no value gap between the multiple trees. 6. The method of claim 1, further comprising receiving the encrypted search index and ciphertext from the client-side computing device. 7. The method of claim 1, wherein the tree list comprises at least one search tree based on a previously received range query token. 8. A non-transitory computer-readable storage medium coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for performing range queries over encrypted data, the operations comprising:
receiving, by a server-side computing device, a range query token from a client-side computing device; determining, by the server-side computing device, one or more of whether a tree list of an encrypted search index is empty and a range of the range query token is intersecting with a range accounted by at least one tree in the tree list, the encrypted search index comprising the tree list and a point list; receiving, by the server-side computing device, encrypted query results based on one of a search tree, if the tree list is not empty and a range of the range query token is at least a sub-range of a range accounted for in the tree list, and the point list, if the tree list is empty or the range of the range query token is not at least a sub-range of a range accounted for in the tree list; and updating, by the server-side computing device, the encrypted search index based on the range query token and a client-server protocol. 9. The computer-readable storage medium of claim 8, wherein updating the encrypted search index comprises refining a search tree of the tree list at least partially based on transmitting the range query token and a previously received range query token to the client-side computing device, and receiving refined range tokens from the client-side computing device, the encrypted search index being updated based on the refined range tokens. 10. The computer-readable storage medium of claim 8, wherein updating the encrypted search index comprises extending a search tree of the tree list to provide an extended search tree at least partially based on transmitting a root node of the search tree and a previously received query corresponding to the search tree to the client-side computing device to provide a new range query token corresponding to the extended search tree. 11. The computer-readable storage medium of claim 8, wherein updating the encrypted search index comprises merging multiple search trees of the tree list to provide a merged search tree at least partially based on transmitting respective root nodes of the multiple search trees to the client-side computing device, and receiving a revised token corresponding to the merged search tree. 12. The computer-readable storage medium of claim 11, wherein the multiple trees are merged in response to determining that there is no value gap between the multiple trees. 13. The computer-readable storage medium of claim 8, wherein operations further comprise receiving the encrypted search index and ciphertext from the client-side computing device. 14. The computer-readable storage medium of claim 8, wherein the tree list comprises at least one search tree based on a previously received range query token. 15. A system, comprising:
a server-side computing device; and a computer-readable storage device coupled to the server-side computing device and having instructions stored thereon which, when executed by the server-side computing device, cause the server-side computing device to perform operations for performing range queries over encrypted data, the operations comprising:
receiving a range query token from a client-side computing device;
determining one or more of whether a tree list of an encrypted search index is empty and a range of the range query token is intersecting with a range accounted by at least one tree in the tree list, the encrypted search index comprising the tree list and a point list;
receiving encrypted query results based on one of a search tree, if the tree list is not empty and a range of the range query token is at least a sub-range of a range accounted for in the tree list, and the point list, if the tree list is empty or the range of the range query token is not at least a sub-range of a range accounted for in the tree list; and
updating the encrypted search index based on the range query token and a client-server protocol. 16. The system of claim 15, wherein updating the encrypted search index comprises refining a search tree of the tree list at least partially based on transmitting the range query token and a previously received range query token to the client-side computing device, and receiving refined range tokens from the client-side computing device, the encrypted search index being updated based on the refined range tokens. 17. The system of claim 15, wherein updating the encrypted search index comprises extending a search tree of the tree list to provide an extended search tree at least partially based on transmitting a root node of the search tree and a previously received query corresponding to the search tree to the client-side computing device to provide a new range query token corresponding to the extended search tree. 18. The system of claim 15, wherein updating the encrypted search index comprises merging multiple search trees of the tree list to provide a merged search tree at least partially based on transmitting respective root nodes of the multiple search trees to the client-side computing device, and receiving a revised token corresponding to the merged search tree. 19. The system of claim 18, wherein the multiple trees are merged in response to determining that there is no value gap between the multiple trees. 20. The system of claim 15, wherein operations further comprise receiving the encrypted search index and ciphertext from the client-side computing device. | Methods, systems, and computer-readable storage media for range queries over encrypted data include actions of receiving a range query token, determining one or more of whether a tree list of an encrypted search index is empty and a range of the token intersects with a range accounted of a tree in the tree list, the encrypted search index including the tree list and a point list, receiving encrypted query results based on one of a search tree, if the tree list is not empty and a range of the token is at least a sub-range of a range accounted for in the tree list, and the point list, if the tree list is empty or the range of the token is not at least a sub-range of a range accounted for in the tree list, and updating the encrypted search index based on the token.1. A computer-implemented method for performing range queries over encrypted data, the method being executed by a server-side computing device and comprising:
receiving, by the server-side computing device, a range query token from a client-side computing device; determining, by the server-side computing device, one or more of whether a tree list of an encrypted search index is empty and a range of the range query token is intersecting with a range accounted by at least one tree in the tree list, the encrypted search index comprising the tree list and a point list; receiving, by the server-side computing device, encrypted query results based on one of a search tree, if the tree list is not empty and a range of the range query token is at least a sub-range of a range accounted for in the tree list, and the point list, if the tree list is empty or the range of the range query token is not at least a sub-range of a range accounted for in the tree list; and updating, by the server-side computing device, the encrypted search index based on the range query token and a client-server protocol. 2. The method of claim 1, wherein updating the encrypted search index comprises refining a search tree of the tree list at least partially based on transmitting the range query token and a previously received range query token to the client-side computing device, and receiving refined range tokens from the client-side computing device, the encrypted search index being updated based on the refined range tokens. 3. The method of claim 1, wherein updating the encrypted search index comprises extending a search tree of the tree list to provide an extended search tree at least partially based on transmitting a root node of the search tree and a previously received query corresponding to the search tree to the client-side computing device to provide a new range query token corresponding to the extended search tree. 4. The method of claim 1, wherein updating the encrypted search index comprises merging multiple search trees of the tree list to provide a merged search tree at least partially based on transmitting respective root nodes of the multiple search trees to the client-side computing device, and receiving a revised token corresponding to the merged search tree. 5. The method of claim 4, wherein the multiple trees are merged in response to determining that there is no value gap between the multiple trees. 6. The method of claim 1, further comprising receiving the encrypted search index and ciphertext from the client-side computing device. 7. The method of claim 1, wherein the tree list comprises at least one search tree based on a previously received range query token. 8. A non-transitory computer-readable storage medium coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for performing range queries over encrypted data, the operations comprising:
receiving, by a server-side computing device, a range query token from a client-side computing device; determining, by the server-side computing device, one or more of whether a tree list of an encrypted search index is empty and a range of the range query token is intersecting with a range accounted by at least one tree in the tree list, the encrypted search index comprising the tree list and a point list; receiving, by the server-side computing device, encrypted query results based on one of a search tree, if the tree list is not empty and a range of the range query token is at least a sub-range of a range accounted for in the tree list, and the point list, if the tree list is empty or the range of the range query token is not at least a sub-range of a range accounted for in the tree list; and updating, by the server-side computing device, the encrypted search index based on the range query token and a client-server protocol. 9. The computer-readable storage medium of claim 8, wherein updating the encrypted search index comprises refining a search tree of the tree list at least partially based on transmitting the range query token and a previously received range query token to the client-side computing device, and receiving refined range tokens from the client-side computing device, the encrypted search index being updated based on the refined range tokens. 10. The computer-readable storage medium of claim 8, wherein updating the encrypted search index comprises extending a search tree of the tree list to provide an extended search tree at least partially based on transmitting a root node of the search tree and a previously received query corresponding to the search tree to the client-side computing device to provide a new range query token corresponding to the extended search tree. 11. The computer-readable storage medium of claim 8, wherein updating the encrypted search index comprises merging multiple search trees of the tree list to provide a merged search tree at least partially based on transmitting respective root nodes of the multiple search trees to the client-side computing device, and receiving a revised token corresponding to the merged search tree. 12. The computer-readable storage medium of claim 11, wherein the multiple trees are merged in response to determining that there is no value gap between the multiple trees. 13. The computer-readable storage medium of claim 8, wherein operations further comprise receiving the encrypted search index and ciphertext from the client-side computing device. 14. The computer-readable storage medium of claim 8, wherein the tree list comprises at least one search tree based on a previously received range query token. 15. A system, comprising:
a server-side computing device; and a computer-readable storage device coupled to the server-side computing device and having instructions stored thereon which, when executed by the server-side computing device, cause the server-side computing device to perform operations for performing range queries over encrypted data, the operations comprising:
receiving a range query token from a client-side computing device;
determining one or more of whether a tree list of an encrypted search index is empty and a range of the range query token is intersecting with a range accounted by at least one tree in the tree list, the encrypted search index comprising the tree list and a point list;
receiving encrypted query results based on one of a search tree, if the tree list is not empty and a range of the range query token is at least a sub-range of a range accounted for in the tree list, and the point list, if the tree list is empty or the range of the range query token is not at least a sub-range of a range accounted for in the tree list; and
updating the encrypted search index based on the range query token and a client-server protocol. 16. The system of claim 15, wherein updating the encrypted search index comprises refining a search tree of the tree list at least partially based on transmitting the range query token and a previously received range query token to the client-side computing device, and receiving refined range tokens from the client-side computing device, the encrypted search index being updated based on the refined range tokens. 17. The system of claim 15, wherein updating the encrypted search index comprises extending a search tree of the tree list to provide an extended search tree at least partially based on transmitting a root node of the search tree and a previously received query corresponding to the search tree to the client-side computing device to provide a new range query token corresponding to the extended search tree. 18. The system of claim 15, wherein updating the encrypted search index comprises merging multiple search trees of the tree list to provide a merged search tree at least partially based on transmitting respective root nodes of the multiple search trees to the client-side computing device, and receiving a revised token corresponding to the merged search tree. 19. The system of claim 18, wherein the multiple trees are merged in response to determining that there is no value gap between the multiple trees. 20. The system of claim 15, wherein operations further comprise receiving the encrypted search index and ciphertext from the client-side computing device. | 2,100 |
6,021 | 6,021 | 15,427,421 | 2,135 | Data processing apparatus comprises a data access requesting node; data access circuitry to receive a data access request from the data access requesting node and to route the data access request for fulfilment by one or more data storage nodes selected from a group of two or more data storage nodes; and indication circuitry to provide a source indication to the data access requesting node, to indicate an attribute of the one or more data storage nodes which fulfilled the data access request; the data access requesting node being configured to vary its operation in response to the source indication. | 1. Data processing apparatus comprising:
a data access requesting node; data access circuitry to receive a data access request from the data access requesting node and to route the data access request for fulfilment by one or more data storage nodes selected from a group of two or more data storage nodes; and indication circuitry to provide a source indication to the data access requesting node, to indicate an attribute of the one or more data storage nodes which fulfilled the data access request; the data access requesting node being configured to vary its operation in response to the source indication. 2. Apparatus according to claim 1, in which the attribute comprises information identifying which of the data storage nodes fulfilled the data access request. 3. Apparatus according to claim 1, in which the attribute comprises classification information identifying a classification of the one or more data storage nodes which fulfilled the data access request. 4. Apparatus according to claim 3, in which the classification indicates an attribute of a data transfer path between the data access requesting node and the one or more data storage nodes which fulfilled the data access request. 5. Apparatus according to claim 4, in which the attribute of the data transfer path is indicative of a latency of the data transfer path. 6. Apparatus according to claim 3, in which the data storage nodes are arranged as a hierarchy of storage levels, and the classification indicates the level of the one or more data storage nodes which fulfilled the request. 7. Apparatus according to claim 6, in which, for at least one of the levels, data storage nodes at that level comprise cache memories, and for at least another of the levels, data storage nodes at that level comprise main memories. 8. Apparatus according to claim 1, in which the data access requesting node is configured to vary the issuing of data access requests by that data access requesting node in response to the source indication. 9. Apparatus according to claim 1, in which the attribute comprises a loading indication, indicating a level of loading of the one or more data storage nodes which fulfilled the data access request. 10. Apparatus according to claim 9, in which:
the data access requesting node is configured to access two or more data types; and the data access requesting node is configured to vary a priority of accessing data of the two or more data types in response to the loading indication. 11. Apparatus according to claim 9, in which:
the data access requesting node comprises prefetch circuitry; and the data access requesting node comprises control circuitry to vary the operation of the prefetch circuitry in response to the loading indication. 12. Apparatus according to claim 11, in which the data access requesting node is configured, in response to the loading indication, to vary one or more of:
a request rate of the prefetch circuitry; an operational status of the prefetch circuitry; a status indication of prefetch data access requests; an accuracy requirement of the prefetch circuitry; a priority of latency-critical data access requests with respect to non-latency-critical data access requests; and a priority of prefetch operations with respect to demand-based data access operations. 13. Apparatus according to claim 1, in which the data access requesting node comprises:
predictor circuitry to predict whether a next data access request will be fulfilled by a first data storage node or a second data storage node, the first and second data storage nodes being arranged so that if a data access request is not fulfilled by the first data storage node, it is fulfilled by the second data storage node; and issue circuitry to issue data access requests for fulfilment by the first data storage node, the issue circuitry being configured to issue an indication, for routing to the second data storage node, that a given data access request may need to be fulfilled by the second data storage node, in response to the predictor circuitry predicting that the given data access request will be fulfilled by the second data storage node. 14. Apparatus according to claim 13, in which:
the attribute indicates whether the data access request was fulfilled by the first data storage node or the second data storage node; and the predictor circuitry is configured to vary its prediction operation in response to the source indication. 15. Apparatus according to claim 14, in which the attribute comprises a success indication, indicating whether the data access request was fulfilled by the data storage node initiating that data access in response to a data access hint message and fulfilling that data access in response to a subsequent data access request. 16. Apparatus according to claim 1, comprising:
acknowledgement circuitry to provide an acknowledgement message to the data access requesting node to indicate fulfilment of the data access request; in which the indication circuitry is configured to associate the source indication with the acknowledgement message. 17. Apparatus according to claim 16, in which the indication circuitry is configured to propagate the source indication with the acknowledgement message 18. Data storage apparatus comprising:
data access circuitry to receive a data access request from a data access requesting node in data communication with the data access circuitry and to route the data access request for fulfilment by one or more data storage nodes selected from a group of two or more data storage nodes; acknowledgement circuitry to provide an acknowledgement message to the data access requesting node to indicate fulfilment of the data access request; and indication circuitry to associate with the acknowledgement message a source indication, indicating an attribute of one or more of the group of data storage nodes which fulfilled the data access request. 19. Apparatus according to claim 18, in which the attribute comprises information identifying which of the data storage nodes fulfilled the data access request. 20. Apparatus according to claim 18, in which the attribute comprises classification information identifying a classification of the one or more data storage nodes which fulfilled the data access request. 21. Apparatus according to claim 18, in which the attribute comprises a loading indication, indicating a level of loading of the one or more data storage nodes indicated by the source indication. 22. Apparatus according to claim 18, in which at least one of the data storage nodes comprises memory access circuitry configured:
to initiate a data access of data stored in a memory in response to a data access hint message received from another node in data communication with the memory access circuitry and to fulfil a data access of data stored in the memory in response to a subsequent data access request received from another node in data communication with the memory access circuitry. 23. Apparatus according to claim 22, in which:
the attribute comprises a success indication, indicating whether the data access request was fulfilled by the data storage node initiating that data access in response to a data access hint message and fulfilling that data access in response to a subsequent data access request. 24. A data processing method comprising:
receiving a data access request from a data access requesting node; routing the data access request for fulfilment by one or more data storage nodes selected from a group of two or more data storage nodes; providing a source indication to the data access requesting node, to indicate an attribute of the one or more data storage nodes which fulfilled the data access request; and varying the operation of the data access requesting node in response to the source indication. 25. A data storage method comprising:
receiving a data access request from a data access requesting node; routing the data access request for fulfilment by one or more data storage nodes selected from a group of two or more data storage nodes; providing an acknowledgement message to the data access requesting node to indicate fulfilment of the data access request; and associating with the acknowledgement message a source indication, indicating an attribute of one or more of the group of data storage nodes which fulfilled the data access request. | Data processing apparatus comprises a data access requesting node; data access circuitry to receive a data access request from the data access requesting node and to route the data access request for fulfilment by one or more data storage nodes selected from a group of two or more data storage nodes; and indication circuitry to provide a source indication to the data access requesting node, to indicate an attribute of the one or more data storage nodes which fulfilled the data access request; the data access requesting node being configured to vary its operation in response to the source indication.1. Data processing apparatus comprising:
a data access requesting node; data access circuitry to receive a data access request from the data access requesting node and to route the data access request for fulfilment by one or more data storage nodes selected from a group of two or more data storage nodes; and indication circuitry to provide a source indication to the data access requesting node, to indicate an attribute of the one or more data storage nodes which fulfilled the data access request; the data access requesting node being configured to vary its operation in response to the source indication. 2. Apparatus according to claim 1, in which the attribute comprises information identifying which of the data storage nodes fulfilled the data access request. 3. Apparatus according to claim 1, in which the attribute comprises classification information identifying a classification of the one or more data storage nodes which fulfilled the data access request. 4. Apparatus according to claim 3, in which the classification indicates an attribute of a data transfer path between the data access requesting node and the one or more data storage nodes which fulfilled the data access request. 5. Apparatus according to claim 4, in which the attribute of the data transfer path is indicative of a latency of the data transfer path. 6. Apparatus according to claim 3, in which the data storage nodes are arranged as a hierarchy of storage levels, and the classification indicates the level of the one or more data storage nodes which fulfilled the request. 7. Apparatus according to claim 6, in which, for at least one of the levels, data storage nodes at that level comprise cache memories, and for at least another of the levels, data storage nodes at that level comprise main memories. 8. Apparatus according to claim 1, in which the data access requesting node is configured to vary the issuing of data access requests by that data access requesting node in response to the source indication. 9. Apparatus according to claim 1, in which the attribute comprises a loading indication, indicating a level of loading of the one or more data storage nodes which fulfilled the data access request. 10. Apparatus according to claim 9, in which:
the data access requesting node is configured to access two or more data types; and the data access requesting node is configured to vary a priority of accessing data of the two or more data types in response to the loading indication. 11. Apparatus according to claim 9, in which:
the data access requesting node comprises prefetch circuitry; and the data access requesting node comprises control circuitry to vary the operation of the prefetch circuitry in response to the loading indication. 12. Apparatus according to claim 11, in which the data access requesting node is configured, in response to the loading indication, to vary one or more of:
a request rate of the prefetch circuitry; an operational status of the prefetch circuitry; a status indication of prefetch data access requests; an accuracy requirement of the prefetch circuitry; a priority of latency-critical data access requests with respect to non-latency-critical data access requests; and a priority of prefetch operations with respect to demand-based data access operations. 13. Apparatus according to claim 1, in which the data access requesting node comprises:
predictor circuitry to predict whether a next data access request will be fulfilled by a first data storage node or a second data storage node, the first and second data storage nodes being arranged so that if a data access request is not fulfilled by the first data storage node, it is fulfilled by the second data storage node; and issue circuitry to issue data access requests for fulfilment by the first data storage node, the issue circuitry being configured to issue an indication, for routing to the second data storage node, that a given data access request may need to be fulfilled by the second data storage node, in response to the predictor circuitry predicting that the given data access request will be fulfilled by the second data storage node. 14. Apparatus according to claim 13, in which:
the attribute indicates whether the data access request was fulfilled by the first data storage node or the second data storage node; and the predictor circuitry is configured to vary its prediction operation in response to the source indication. 15. Apparatus according to claim 14, in which the attribute comprises a success indication, indicating whether the data access request was fulfilled by the data storage node initiating that data access in response to a data access hint message and fulfilling that data access in response to a subsequent data access request. 16. Apparatus according to claim 1, comprising:
acknowledgement circuitry to provide an acknowledgement message to the data access requesting node to indicate fulfilment of the data access request; in which the indication circuitry is configured to associate the source indication with the acknowledgement message. 17. Apparatus according to claim 16, in which the indication circuitry is configured to propagate the source indication with the acknowledgement message 18. Data storage apparatus comprising:
data access circuitry to receive a data access request from a data access requesting node in data communication with the data access circuitry and to route the data access request for fulfilment by one or more data storage nodes selected from a group of two or more data storage nodes; acknowledgement circuitry to provide an acknowledgement message to the data access requesting node to indicate fulfilment of the data access request; and indication circuitry to associate with the acknowledgement message a source indication, indicating an attribute of one or more of the group of data storage nodes which fulfilled the data access request. 19. Apparatus according to claim 18, in which the attribute comprises information identifying which of the data storage nodes fulfilled the data access request. 20. Apparatus according to claim 18, in which the attribute comprises classification information identifying a classification of the one or more data storage nodes which fulfilled the data access request. 21. Apparatus according to claim 18, in which the attribute comprises a loading indication, indicating a level of loading of the one or more data storage nodes indicated by the source indication. 22. Apparatus according to claim 18, in which at least one of the data storage nodes comprises memory access circuitry configured:
to initiate a data access of data stored in a memory in response to a data access hint message received from another node in data communication with the memory access circuitry and to fulfil a data access of data stored in the memory in response to a subsequent data access request received from another node in data communication with the memory access circuitry. 23. Apparatus according to claim 22, in which:
the attribute comprises a success indication, indicating whether the data access request was fulfilled by the data storage node initiating that data access in response to a data access hint message and fulfilling that data access in response to a subsequent data access request. 24. A data processing method comprising:
receiving a data access request from a data access requesting node; routing the data access request for fulfilment by one or more data storage nodes selected from a group of two or more data storage nodes; providing a source indication to the data access requesting node, to indicate an attribute of the one or more data storage nodes which fulfilled the data access request; and varying the operation of the data access requesting node in response to the source indication. 25. A data storage method comprising:
receiving a data access request from a data access requesting node; routing the data access request for fulfilment by one or more data storage nodes selected from a group of two or more data storage nodes; providing an acknowledgement message to the data access requesting node to indicate fulfilment of the data access request; and associating with the acknowledgement message a source indication, indicating an attribute of one or more of the group of data storage nodes which fulfilled the data access request. | 2,100 |
6,022 | 6,022 | 16,052,083 | 2,119 | A building management system includes a meter configured to provide data samples of a real point. The real point corresponds to a first physical parameter measured by the meter. The building management system also includes an analytics circuit configured to store a real point object representing the real point and store a meter object representing the meter. The meter object includes a points attribute that lists one or more point objects associated with the meter object including at least the real point object. The analytics circuit is also configured to store a virtual point object representing a virtual point. The virtual point corresponds to a second physical parameter not measured by the meter. The analytics circuit is also configured to update the points attribute in the meter object to list the virtual point object as one of the point objects associated with the meter object. | 1. A building management system comprising:
a meter configured to provide data samples of a real point, the real point corresponding to a first physical parameter measured by the meter; an analytics circuit configured to:
store a real point object representing the real point;
store a meter object representing the meter, the meter object comprising a points attribute that lists one or more point objects associated with the meter object including at least the real point object; and
store a virtual point object representing a virtual point, the virtual point corresponding to a second physical parameter not measured by the meter; and
update the points attribute in the meter object to list the virtual point object as one of the point objects associated with the meter object;
receive a data sample of the real point from the meter;
calculate a value of the virtual point; and
calculate a metric based on the data sample of the real point and the value of the virtual point; and
a system manager configured to control building equipment using the metric to affect the first physical parameter and the second physical parameter. 2. The building management system of claim 1, wherein the analytics circuit is configured to calculate the value of the virtual point using a formula stored in the virtual point object. 3. The building management system of claim 2, wherein the analytics circuit is configured to generate a graphical user interface that allows a user to input the formula. 4. The building management system of claim 2, wherein the formula defines the value of the virtual point as a function of the data sample of the real point. 5. The building management system of claim 1, wherein the first physical parameter and the second physical parameter characterize operation of the building equipment. 6. The building management system of claim 5, wherein the analytics circuit is further configured to generate a graphical user interface that includes a graphical representation of the operation of the building equipment based on the data sample of the real point and the value of the virtual point. 7. The building management system of claim 6, wherein the graphical user interface comprises a first indicator identifying the real point as real and a second indicator identifying the virtual point as virtual. 8. A method for managing a building, comprising:
collecting, by a meter, data samples of a real point, the real point corresponding to a first physical parameter measured by the meter; storing a real point object representing the real point; storing a meter object representing the meter, the meter object comprising a points attribute that lists one or more point objects associated with the meter object including at least the real point object; and storing a virtual point object representing a virtual point, the virtual point corresponding to a second physical parameter not measured by the meter; and updating the points attribute in the meter object to list the virtual point object in as one of the point objects associated with the meter object: receiving a data sample of the real point from the meter; calculating a value of the virtual point; calculating a metric based on the data sample of the real point and the value of the virtual point; and controlling, based on the metric, building equipment to affect the first physical parameter and the second physical parameter. 9. The method of claim 8, wherein calculating the value of the virtual point comprises:
storing a formula in the virtual point object; and calculating the value using the formula. 10. The method of claim 9, comprising generating a graphical user interface that allows the user to input the formula. 11. The method of claim 9, wherein the formula defines the value of the virtual point as a function of the data sample for the real point. 12. The method of claim 9, wherein the first physical parameter and the second physical parameter characterize operation of the building equipment. 13. The method of claim 8, comprising generating a graphical user interface that includes a graphical representation of the operation of the building equipment based on the data sample of the real point and the value of the virtual point. 14. The method of claim 13 comprising providing, on the graphical user interface, a first indicator identifying the real point as real and a second indicator identifying the virtual point as virtual. 15. A building management system, comprising:
building equipment operable to affect a variable state or condition of a building; a plurality of meters configured to collect data samples of a plurality of real points relating to an operation of the building equipment; an analytics circuit configured to:
generate a graphical user interface, the graphical user interface comprising:
a points tree widget comprising a list of the plurality of real points;
a meter distribution tree widget comprising a list of the plurality of meters; and
a meter details widget configured to allow a user to add a virtual point to the list of real points; and
receive data samples of the plurality of real points;
calculate a value of the virtual point; and
calculate a metric based on the data samples of the plurality of real points and the value of the virtual point; and
a system manager configured to control the building equipment based on the metric. 16. The building management system of claim 15, wherein the graphical user interface comprises a virtual point definition widget configured to allow a user to input a formula that defines the virtual point. 17. The building management system of claim 16, wherein the analytics circuit is configured to generate the value of the virtual point using the formula and a first data sample of a first real point of the plurality of real points. 18. The building management of claim 16, wherein the analytics circuit is configured to generate a graphical representation of an operation of the building equipment using the formula and the data samples of the plurality of real points. 19. The building management system of claim 16, wherein the virtual point definition widget comprises:
a formula field; a list of the plurality of real points, each real point on the list of real points selectable to add the real point to the formula field; and a plurality of operator buttons, each operator button selectable to add an operator to the formula field; wherein the formula comprises one or more real points and one or more operators to define the virtual point as a function of the one or more real points. 20. The building management system of claim 19, wherein the analytics circuit is configured to check the formula input by the user for syntax errors. | A building management system includes a meter configured to provide data samples of a real point. The real point corresponds to a first physical parameter measured by the meter. The building management system also includes an analytics circuit configured to store a real point object representing the real point and store a meter object representing the meter. The meter object includes a points attribute that lists one or more point objects associated with the meter object including at least the real point object. The analytics circuit is also configured to store a virtual point object representing a virtual point. The virtual point corresponds to a second physical parameter not measured by the meter. The analytics circuit is also configured to update the points attribute in the meter object to list the virtual point object as one of the point objects associated with the meter object.1. A building management system comprising:
a meter configured to provide data samples of a real point, the real point corresponding to a first physical parameter measured by the meter; an analytics circuit configured to:
store a real point object representing the real point;
store a meter object representing the meter, the meter object comprising a points attribute that lists one or more point objects associated with the meter object including at least the real point object; and
store a virtual point object representing a virtual point, the virtual point corresponding to a second physical parameter not measured by the meter; and
update the points attribute in the meter object to list the virtual point object as one of the point objects associated with the meter object;
receive a data sample of the real point from the meter;
calculate a value of the virtual point; and
calculate a metric based on the data sample of the real point and the value of the virtual point; and
a system manager configured to control building equipment using the metric to affect the first physical parameter and the second physical parameter. 2. The building management system of claim 1, wherein the analytics circuit is configured to calculate the value of the virtual point using a formula stored in the virtual point object. 3. The building management system of claim 2, wherein the analytics circuit is configured to generate a graphical user interface that allows a user to input the formula. 4. The building management system of claim 2, wherein the formula defines the value of the virtual point as a function of the data sample of the real point. 5. The building management system of claim 1, wherein the first physical parameter and the second physical parameter characterize operation of the building equipment. 6. The building management system of claim 5, wherein the analytics circuit is further configured to generate a graphical user interface that includes a graphical representation of the operation of the building equipment based on the data sample of the real point and the value of the virtual point. 7. The building management system of claim 6, wherein the graphical user interface comprises a first indicator identifying the real point as real and a second indicator identifying the virtual point as virtual. 8. A method for managing a building, comprising:
collecting, by a meter, data samples of a real point, the real point corresponding to a first physical parameter measured by the meter; storing a real point object representing the real point; storing a meter object representing the meter, the meter object comprising a points attribute that lists one or more point objects associated with the meter object including at least the real point object; and storing a virtual point object representing a virtual point, the virtual point corresponding to a second physical parameter not measured by the meter; and updating the points attribute in the meter object to list the virtual point object in as one of the point objects associated with the meter object: receiving a data sample of the real point from the meter; calculating a value of the virtual point; calculating a metric based on the data sample of the real point and the value of the virtual point; and controlling, based on the metric, building equipment to affect the first physical parameter and the second physical parameter. 9. The method of claim 8, wherein calculating the value of the virtual point comprises:
storing a formula in the virtual point object; and calculating the value using the formula. 10. The method of claim 9, comprising generating a graphical user interface that allows the user to input the formula. 11. The method of claim 9, wherein the formula defines the value of the virtual point as a function of the data sample for the real point. 12. The method of claim 9, wherein the first physical parameter and the second physical parameter characterize operation of the building equipment. 13. The method of claim 8, comprising generating a graphical user interface that includes a graphical representation of the operation of the building equipment based on the data sample of the real point and the value of the virtual point. 14. The method of claim 13 comprising providing, on the graphical user interface, a first indicator identifying the real point as real and a second indicator identifying the virtual point as virtual. 15. A building management system, comprising:
building equipment operable to affect a variable state or condition of a building; a plurality of meters configured to collect data samples of a plurality of real points relating to an operation of the building equipment; an analytics circuit configured to:
generate a graphical user interface, the graphical user interface comprising:
a points tree widget comprising a list of the plurality of real points;
a meter distribution tree widget comprising a list of the plurality of meters; and
a meter details widget configured to allow a user to add a virtual point to the list of real points; and
receive data samples of the plurality of real points;
calculate a value of the virtual point; and
calculate a metric based on the data samples of the plurality of real points and the value of the virtual point; and
a system manager configured to control the building equipment based on the metric. 16. The building management system of claim 15, wherein the graphical user interface comprises a virtual point definition widget configured to allow a user to input a formula that defines the virtual point. 17. The building management system of claim 16, wherein the analytics circuit is configured to generate the value of the virtual point using the formula and a first data sample of a first real point of the plurality of real points. 18. The building management of claim 16, wherein the analytics circuit is configured to generate a graphical representation of an operation of the building equipment using the formula and the data samples of the plurality of real points. 19. The building management system of claim 16, wherein the virtual point definition widget comprises:
a formula field; a list of the plurality of real points, each real point on the list of real points selectable to add the real point to the formula field; and a plurality of operator buttons, each operator button selectable to add an operator to the formula field; wherein the formula comprises one or more real points and one or more operators to define the virtual point as a function of the one or more real points. 20. The building management system of claim 19, wherein the analytics circuit is configured to check the formula input by the user for syntax errors. | 2,100 |
6,023 | 6,023 | 15,249,013 | 2,159 | User interaction efficiency is improved by providing automatic enrichment of content with contextually relevant information. While a user is utilizing a productivity application, the system may receive a content item, such as an email or calendar event, to display within an application user interface. The system analyzes and identifies contextually relevant information based on the content item. Thereafter, the system displays the application user interface including the content item which is modified to display the contextually relevant information within the content item. | 1. A method of providing automatic enrichment of content with contextually relevant information, comprising:
receiving a content item to display within an application user interface; determining an entity associated with the content item; querying one or more data sources for results that relate to the entity; retrieving context information relating to the content item; parsing the results in view of the context information; identifying contextually relevant information; and displaying the content item within the application user interface, wherein the content item is modified to display the contextually relevant information. 2. The method of claim 1, wherein the content item is an email or calendar entry. 3. The method of claim 2, wherein the calendar entry is automatically populated into a calendar. 4. The method of claim 1, wherein parsing the results in view of the context information is based on the content item or the entity. 5. The method of claim 1, further comprising determining the strength of the entity relative to other entities. 6. The method of claim 1, wherein the contextually relevant information is displayed in-line with the content item. 7. The method of claim 1, wherein objects within the content item are associated with the contextually relevant information. 8. The method of claim 7, wherein selection of the object causes the contextually relevant information to be displayed in-line with the content item. 9. The method of claim 1, wherein the contextually relevant information includes promotional information relating to the entity. 10. 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:
receiving a calendar event to display within an application user interface;
determining an entity associated with the calendar event;
querying one or more data sources for results that relate to the entity;
retrieving context information relating to the calendar event;
parsing the results in view of the context information;
identifying contextually relevant information; and
displaying the calendar event within the application user interface, wherein the calendar event is modified to display the contextually relevant information, and wherein the contextually relevant information is displayed in-line with the calendar event. 11. The computing device of claim 10, wherein the entities include cities or promotions providers. 12. The computing device of claim 10, wherein parsing the results in view of the context information is based on the calendar event or the entity. 13. The computing device of claim 10, further comprising determining the strength of the entity relative to other entities. 14. The computing device of claim 10, wherein the contextually relevant information includes promotional information relating to the entity. 15. A computer readable storage device including computer readable instructions, which when executed by a processing unit is operable to:
receiving an email to display within an application user interface; determining an entity associated with the email; querying one or more data sources for results that relate to the entity; retrieving context information relating to the email; parsing the results in view of the context information; identifying contextually relevant information; and displaying the email within the application user interface, wherein the email is modified to display the contextually relevant information, and wherein the contextually relevant information is embedded within the email. 16. The computing readable storage device of claim 15, wherein the entities include cities or promotions providers. 17. The computing readable storage device of claim 15, wherein parsing the results in view of the context information is based on the entity. 18. The computing readable storage device of claim 15, further comprising determining the strength of the entity relative to other entities. 19. The computing readable storage device of claim 15, wherein the contextually relevant information is displayed in-line with the email. 20. The computing readable storage device of claim 15, wherein the contextually relevant information includes promotional information relating to the entity. | User interaction efficiency is improved by providing automatic enrichment of content with contextually relevant information. While a user is utilizing a productivity application, the system may receive a content item, such as an email or calendar event, to display within an application user interface. The system analyzes and identifies contextually relevant information based on the content item. Thereafter, the system displays the application user interface including the content item which is modified to display the contextually relevant information within the content item.1. A method of providing automatic enrichment of content with contextually relevant information, comprising:
receiving a content item to display within an application user interface; determining an entity associated with the content item; querying one or more data sources for results that relate to the entity; retrieving context information relating to the content item; parsing the results in view of the context information; identifying contextually relevant information; and displaying the content item within the application user interface, wherein the content item is modified to display the contextually relevant information. 2. The method of claim 1, wherein the content item is an email or calendar entry. 3. The method of claim 2, wherein the calendar entry is automatically populated into a calendar. 4. The method of claim 1, wherein parsing the results in view of the context information is based on the content item or the entity. 5. The method of claim 1, further comprising determining the strength of the entity relative to other entities. 6. The method of claim 1, wherein the contextually relevant information is displayed in-line with the content item. 7. The method of claim 1, wherein objects within the content item are associated with the contextually relevant information. 8. The method of claim 7, wherein selection of the object causes the contextually relevant information to be displayed in-line with the content item. 9. The method of claim 1, wherein the contextually relevant information includes promotional information relating to the entity. 10. 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:
receiving a calendar event to display within an application user interface;
determining an entity associated with the calendar event;
querying one or more data sources for results that relate to the entity;
retrieving context information relating to the calendar event;
parsing the results in view of the context information;
identifying contextually relevant information; and
displaying the calendar event within the application user interface, wherein the calendar event is modified to display the contextually relevant information, and wherein the contextually relevant information is displayed in-line with the calendar event. 11. The computing device of claim 10, wherein the entities include cities or promotions providers. 12. The computing device of claim 10, wherein parsing the results in view of the context information is based on the calendar event or the entity. 13. The computing device of claim 10, further comprising determining the strength of the entity relative to other entities. 14. The computing device of claim 10, wherein the contextually relevant information includes promotional information relating to the entity. 15. A computer readable storage device including computer readable instructions, which when executed by a processing unit is operable to:
receiving an email to display within an application user interface; determining an entity associated with the email; querying one or more data sources for results that relate to the entity; retrieving context information relating to the email; parsing the results in view of the context information; identifying contextually relevant information; and displaying the email within the application user interface, wherein the email is modified to display the contextually relevant information, and wherein the contextually relevant information is embedded within the email. 16. The computing readable storage device of claim 15, wherein the entities include cities or promotions providers. 17. The computing readable storage device of claim 15, wherein parsing the results in view of the context information is based on the entity. 18. The computing readable storage device of claim 15, further comprising determining the strength of the entity relative to other entities. 19. The computing readable storage device of claim 15, wherein the contextually relevant information is displayed in-line with the email. 20. The computing readable storage device of claim 15, wherein the contextually relevant information includes promotional information relating to the entity. | 2,100 |
6,024 | 6,024 | 15,906,642 | 2,193 | Communication program code is communication program code incorporated into an application and continuously displays a startup button on an application screen, operates as a function of the application when the startup button is operated, and allows a talk between a user and a developer. A communication function allows the developer and the user to talk in real time, and hence the user of the application can easily give feedback, such as report of usability and problems, to the developer in real time. | 1. A computer program product comprising a non-transitory computer-readable medium storing communication program code that is incorporated into an application program, the communication program code being for causing a computer to function as:
an image display control unit for continuously displaying a prescribed image on a screen on which the application program is operating; and a communication unit operating as a function of the application program when the prescribed image is operated and allowing communication between a user and a developer. 2. The computer program product according to claim 1, wherein the communication program code is for causing the computer, when the user performs communication using the communication unit, to perform functions of causing the communication unit in the application program on the developer side to display communication content from the user so as to allow the developer to make a reply. 3. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to display communication content made by another user. 4. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to allow an operator to search for past communication content. 5. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of moving the prescribed image to a position according to a drag operation performed by an operator. 6. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to transmit a screen image showing the screen on which the application program is operating. 7. The computer program product according to claim 6, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to transmit the screen image to which writing is performed. 8. The computer program product according to claim 6, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to capture the screen image for each prescribed operation performed on the application program and perform a process based on the prescribed operation on the screen image. 9. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to transmit a moving image showing a change in the screen on which the application program is operating. 10. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to transmit a log of an information processing apparatus in which the application program is operating. 11. The computer program product according to claim 10, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to transmit the log when the operating application program abnormally ends. 12. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to synchronize communication content with another pre-registered application program or another pre-registered web service. 13. The computer program product according to claim 1, wherein the communication program code is incorporated into a web site instead of the application program. 14. A computer program product comprising a non-transitory computer-readable medium storing communication program code that is incorporated into an application program, the communication program code being for causing a computer to function as:
an image display control unit for continuously displaying a prescribed image on a screen on which the application program is operating; and a startup unit for starting up a communication program that allows communication between a user and a developer when the prescribed image is operated. 15. An information processing apparatus in which an application program having a communication program incorporated thereinto is installed, the information processing apparatus comprising:
an image display control unit for continuously displaying a prescribed image on a screen on which the application program is operating; and a communication unit operating as a function of the application program when the prescribed image is operated and allowing communication between a user and a developer. 16. A communication method using a communication program incorporated into an application program, the communication method comprising:
a first step of continuously displaying a prescribed image on a screen on which the application program is operating; and a second step of operating as a function of the application program when the prescribed image is operated and allowing communication between a user and a developer. | Communication program code is communication program code incorporated into an application and continuously displays a startup button on an application screen, operates as a function of the application when the startup button is operated, and allows a talk between a user and a developer. A communication function allows the developer and the user to talk in real time, and hence the user of the application can easily give feedback, such as report of usability and problems, to the developer in real time.1. A computer program product comprising a non-transitory computer-readable medium storing communication program code that is incorporated into an application program, the communication program code being for causing a computer to function as:
an image display control unit for continuously displaying a prescribed image on a screen on which the application program is operating; and a communication unit operating as a function of the application program when the prescribed image is operated and allowing communication between a user and a developer. 2. The computer program product according to claim 1, wherein the communication program code is for causing the computer, when the user performs communication using the communication unit, to perform functions of causing the communication unit in the application program on the developer side to display communication content from the user so as to allow the developer to make a reply. 3. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to display communication content made by another user. 4. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to allow an operator to search for past communication content. 5. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of moving the prescribed image to a position according to a drag operation performed by an operator. 6. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to transmit a screen image showing the screen on which the application program is operating. 7. The computer program product according to claim 6, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to transmit the screen image to which writing is performed. 8. The computer program product according to claim 6, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to capture the screen image for each prescribed operation performed on the application program and perform a process based on the prescribed operation on the screen image. 9. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to transmit a moving image showing a change in the screen on which the application program is operating. 10. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to transmit a log of an information processing apparatus in which the application program is operating. 11. The computer program product according to claim 10, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to transmit the log when the operating application program abnormally ends. 12. The computer program product according to claim 1, wherein the communication program code is for causing the computer to perform functions of causing the communication unit to synchronize communication content with another pre-registered application program or another pre-registered web service. 13. The computer program product according to claim 1, wherein the communication program code is incorporated into a web site instead of the application program. 14. A computer program product comprising a non-transitory computer-readable medium storing communication program code that is incorporated into an application program, the communication program code being for causing a computer to function as:
an image display control unit for continuously displaying a prescribed image on a screen on which the application program is operating; and a startup unit for starting up a communication program that allows communication between a user and a developer when the prescribed image is operated. 15. An information processing apparatus in which an application program having a communication program incorporated thereinto is installed, the information processing apparatus comprising:
an image display control unit for continuously displaying a prescribed image on a screen on which the application program is operating; and a communication unit operating as a function of the application program when the prescribed image is operated and allowing communication between a user and a developer. 16. A communication method using a communication program incorporated into an application program, the communication method comprising:
a first step of continuously displaying a prescribed image on a screen on which the application program is operating; and a second step of operating as a function of the application program when the prescribed image is operated and allowing communication between a user and a developer. | 2,100 |
6,025 | 6,025 | 15,887,185 | 2,132 | A method for storing data includes establishing an extended generation group comprising a plurality of data sets. The plurality of data sets includes a first data set containing primary members and a first number of generations of each of the primary members, and a second data set containing a second number of generations of each of the primary members. The method further indicates, in the metadata of the first data set, a maximum number of generations allowable in each of the first and second data sets When a primary member is modified in the first data set, the method automatically moves an oldest generation in the first data set to the second data set, and deletes an oldest generation in the second data set to ensure that the extended generation group does not exceed the maximum number. | 1. A method for storing data, the method comprising:
establishing an extended generation group comprising a plurality of data sets, the plurality of data sets comprising a first data set containing primary members and a first number of generations of each of the primary members, and a second data set containing a second number of generations of each of the primary members, wherein the first data set and the second data set are stored on different tiers of a tiered storage system; indicating, in the metadata of the first data set, a maximum number of generations allowable in each of the first data set and the second data set; and upon modifying a primary member in the first data set, automatically moving an oldest generation in the first data set to the second data set, and deleting an oldest generation in the second data set to ensure that the extended generation group does not exceed the maximum number. 2. The method of claim 1, wherein, for each primary member, the generations in the second data set are older than the generations in the first data set. 3. The method of claim 1, wherein the second number is greater than the first number. 4. The method of claim 3, wherein the second number is a multiple of the first number. 5. The method of claim 1, further comprising indicating, in the metadata of the first data set, that the first data set and the second data set are associated with the extended generation group. 6. The method of claim 1, further comprising storing the first and second data sets on different volumes. 7. The method of claim 1, further comprising providing, in the metadata of the first data set, a root directory that provides a starting point to locate generations in each of the first data set and the second data set. 8. A computer program product for storing data, 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 establish an extended generation group comprising a plurality of data sets, the plurality of data sets comprising a first data set containing primary members and a first number of generations of each of the primary members, and a second data set containing a second number of generations of each of the primary members, wherein the first data set and the second data set are stored on different tiers of a tiered storage system; computer-usable program code to indicate, in the metadata of the first data set, a maximum number of generations allowable in each of the first data set and the second data set; and computer-usable program code to, upon modifying a primary member in the first data set, automatically move an oldest generation in the first data set to the second data set, and delete an oldest generation in the second data set to ensure that the extended generation group does not exceed the maximum number. 9. The computer program product of claim 8, wherein, for each primary member, the generations in the second data set are older than the generations in the first data set. 10. The computer program product of claim 8, wherein the second number is greater than the first number. 11. The computer program product of claim 10, wherein the second number is a multiple of the first number. 12. The computer program product of claim 8, further comprising computer-usable program code to provide, in each of the first data set and the second data set, a type flag that indicates whether the associated data set includes primary members or generations only. 13. The computer program product of claim 8, further comprising computer-usable program code to store the first and second data sets on different volumes. 14. The computer program product of claim 8, further comprising computer-usable program code to provide, in the metadata of the first data set, a root directory that provides a starting point to locate generations in each of the first data set and the second data set. 15. A system for storing data, 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:
establish an extended generation group comprising a plurality of data sets, the plurality of data sets comprising a first data set containing primary members and a first number of generations of each of the primary members, and a second data set containing a second number of generations of each of the primary members, wherein the first data set and the second data set are stored on different tiers of a tiered storage system;
indicate, in the metadata of the first data set, a maximum number of generations allowable in each of the first data set and the second data set; and
upon modifying a primary member in the first data set, automatically move an oldest generation in the first data set to the second data set, and delete an oldest generation in the second data set to ensure that the extended generation group does not exceed the maximum number. 16. The system of claim 15, wherein, for each primary member, the generations in the second data set are older than the generations in the first data set. 17. The system of claim 15, wherein the second number is a multiple of the first number. 18. The system of claim 15, wherein the instructions further cause the at least one processor to indicate, in the metadata of the first data set, that the first data set and the second data set are associated with the extended generation group. 19. The system of claim 15, wherein the instructions further cause the at least one processor to store the first and second data sets on different volumes. 20. The system of claim 15, wherein the instructions further cause the at least one processor to provide, in the metadata of the first data set, a root directory that provides a starting point to locate generations in each of the first data set and the second data set. | A method for storing data includes establishing an extended generation group comprising a plurality of data sets. The plurality of data sets includes a first data set containing primary members and a first number of generations of each of the primary members, and a second data set containing a second number of generations of each of the primary members. The method further indicates, in the metadata of the first data set, a maximum number of generations allowable in each of the first and second data sets When a primary member is modified in the first data set, the method automatically moves an oldest generation in the first data set to the second data set, and deletes an oldest generation in the second data set to ensure that the extended generation group does not exceed the maximum number.1. A method for storing data, the method comprising:
establishing an extended generation group comprising a plurality of data sets, the plurality of data sets comprising a first data set containing primary members and a first number of generations of each of the primary members, and a second data set containing a second number of generations of each of the primary members, wherein the first data set and the second data set are stored on different tiers of a tiered storage system; indicating, in the metadata of the first data set, a maximum number of generations allowable in each of the first data set and the second data set; and upon modifying a primary member in the first data set, automatically moving an oldest generation in the first data set to the second data set, and deleting an oldest generation in the second data set to ensure that the extended generation group does not exceed the maximum number. 2. The method of claim 1, wherein, for each primary member, the generations in the second data set are older than the generations in the first data set. 3. The method of claim 1, wherein the second number is greater than the first number. 4. The method of claim 3, wherein the second number is a multiple of the first number. 5. The method of claim 1, further comprising indicating, in the metadata of the first data set, that the first data set and the second data set are associated with the extended generation group. 6. The method of claim 1, further comprising storing the first and second data sets on different volumes. 7. The method of claim 1, further comprising providing, in the metadata of the first data set, a root directory that provides a starting point to locate generations in each of the first data set and the second data set. 8. A computer program product for storing data, 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 establish an extended generation group comprising a plurality of data sets, the plurality of data sets comprising a first data set containing primary members and a first number of generations of each of the primary members, and a second data set containing a second number of generations of each of the primary members, wherein the first data set and the second data set are stored on different tiers of a tiered storage system; computer-usable program code to indicate, in the metadata of the first data set, a maximum number of generations allowable in each of the first data set and the second data set; and computer-usable program code to, upon modifying a primary member in the first data set, automatically move an oldest generation in the first data set to the second data set, and delete an oldest generation in the second data set to ensure that the extended generation group does not exceed the maximum number. 9. The computer program product of claim 8, wherein, for each primary member, the generations in the second data set are older than the generations in the first data set. 10. The computer program product of claim 8, wherein the second number is greater than the first number. 11. The computer program product of claim 10, wherein the second number is a multiple of the first number. 12. The computer program product of claim 8, further comprising computer-usable program code to provide, in each of the first data set and the second data set, a type flag that indicates whether the associated data set includes primary members or generations only. 13. The computer program product of claim 8, further comprising computer-usable program code to store the first and second data sets on different volumes. 14. The computer program product of claim 8, further comprising computer-usable program code to provide, in the metadata of the first data set, a root directory that provides a starting point to locate generations in each of the first data set and the second data set. 15. A system for storing data, 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:
establish an extended generation group comprising a plurality of data sets, the plurality of data sets comprising a first data set containing primary members and a first number of generations of each of the primary members, and a second data set containing a second number of generations of each of the primary members, wherein the first data set and the second data set are stored on different tiers of a tiered storage system;
indicate, in the metadata of the first data set, a maximum number of generations allowable in each of the first data set and the second data set; and
upon modifying a primary member in the first data set, automatically move an oldest generation in the first data set to the second data set, and delete an oldest generation in the second data set to ensure that the extended generation group does not exceed the maximum number. 16. The system of claim 15, wherein, for each primary member, the generations in the second data set are older than the generations in the first data set. 17. The system of claim 15, wherein the second number is a multiple of the first number. 18. The system of claim 15, wherein the instructions further cause the at least one processor to indicate, in the metadata of the first data set, that the first data set and the second data set are associated with the extended generation group. 19. The system of claim 15, wherein the instructions further cause the at least one processor to store the first and second data sets on different volumes. 20. The system of claim 15, wherein the instructions further cause the at least one processor to provide, in the metadata of the first data set, a root directory that provides a starting point to locate generations in each of the first data set and the second data set. | 2,100 |
6,026 | 6,026 | 14,885,989 | 2,159 | The present invention is a web-based and mobile device application service that enables customizable product or service information retrieval from the Internet through the input of a unique product or service identifier and a location parameter. The unique product or service identifier is an alpha numeric number, UPC code, SKU, MLS or other product or service identifying parameter and the location parameter, which may be a zip code, address, town, city, state, country, GPS coordinate, or other location identifier, to provide a user with listings of the exact locations of a product or service from or within the described location. The retrieved data may include information regarding the product or service, including but not limited to price, size, availability, product or service description, web site information or links, promotional codes or sale information or any other data made available by the seller. The system may further enable a user to input a common product or service name which is converted into a unique product or service identifier. | 1. A method for a web-based system of retrieving data from the Internet using a computing device including:
(a) accessing the Internet; (b) contacting a remote, centralized web-based search function; (c) accessing the search page of the remote, centralized web-based search function; (d) imputing a unique product or service code and a location identifier into the remote, centralized web-based search function; (e) activating a search function; and, (f) retrieving search results based upon the search criteria. 2. The method of claim 1 wherein the unique product or service code is a standardized code. 3. The method of claim 1 wherein the unique product or service code is a user promulgated product descriptor, the product descriptor then converted into a standardized code. 4. The standardized code of claim 2 being selected from the group comprising but not limiting to, either singly or in combination, UPC, SKU, EAN, MLS, VIN, and GTIN. 5. The method of claim 1 wherein the location identifier is selected from the group comprising but not limed to, either singly or in combination, zip code, GPS coordinate, location, cellular triangulation, address, city, town, state, and country. 6. The method of claim 1 wherein the retrieved data includes information selected singly or in combination from the group comprising but not limited to product or service name, price, location name, distance to location, inventory count, product size, promotion information, availability, local competition, and coupons. 7. The method of claim 1 including the further step of sorting the retrieved search results to a user's preference. 8. The step of claim 7 wherein the user's preference is selected singly or in combination from the group comprising but not limited to product or service name, price, location name, distance to location, inventory count, product size, promotion information, availability, local competition, and coupons. 9. The method of claim 1 wherein the search function is contacted through the group comprising an app, Internet sharing via hardwired systems, Wi-Fi, QR code scanning uplink, application program interface (API), or near field communication. 10. The method of claim 1 including the further step of a seller of a product or service uploading to the Internet information regarding their goods or services using a unique encrypted alpha numeric hash or using a recognized industry standardized alpha numeric value, the hash creation including the further steps of compiling data for dissemination; converting the data into a standard code; converting the standard code into a unique numeric value; and converting the unique numeric value into a unique alpha numeric hash. 11. The method of claim 10 wherein the data for dissemination is selected singly or in combination from the group comprising but not limited to product name, size, UPC and SKU codes or industry standardized alpha numeric values, service description, sales and promotion information, availability, direction for taking advantage of a promotion, facility location information like GPS, street address, map coordinates, store number or email address, and social media information. 12. The method of claim 10 wherein the standard code is a tag. 13. The method of claim 1 including the further step of selecting one or more individual search results and adding them to a list. 14. The method of claim 1 including the further step of disseminating search results to but not limited to search engines and or social media. 15. The social media information of claim 14 wherein the social media is selected singly or in combination from the group comprising but not limiting to Facebook, Twitter, LinkedIn, Google+, Path, MySpace, Pinterest, browsers, and search engines. 16. A method for sharing data between a seller and a customer comprising:
(a) uploading data by a seller using a remote computing device to contact a web-based, centralized digital information site; (b) accessing the Internet by a customer; (c) contacting a remote, centralized web-based search function; (d) accessing the search page of the remote, centralized web-based search function; (e) imputing search criteria into the remote, centralized web-based search function, the search criteria comprising at least a unique product or service code and a location identifier; (f) activating a search function; and, (g) retrieving search results based upon the search criteria. 17. The method of claim 16 wherein the unique product or service code is a standardized code. 18. The method of claim 16 wherein the unique product or service code is a user promulgated product descriptor, the product descriptor then converted into a standardized code. 19. The standardized code of claim 17 being selected from the group comprising but not limiting to, either singly or in combination, UPC, SKU, EAN, MLS, VIN, and GTIN. 20. The method of claim 16 wherein the location identifier is selected from the group comprising but not limed to, either singly or in combination, zip code, GPS coordinate, location, cellular triangulation, address, city, town, state, and country. 21. The method of claim 16 wherein the retrieved data includes information selected singly or in combination from the group comprising but not limited to product or service name, price, location name, distance to location, inventory count, product size, promotion information, availability, local competition, and coupons. 22. The method of claim 16 including the further step of sorting the retrieved search results to a user's preference. 23. The step of claim 22 wherein the user's preference is selected singly or in combination from the group comprising but not limited to product or service name, price, location name, distance to location, inventory count, product size, promotion information, availability, local competition, and coupons. 24. The method of claim 16 wherein the search function is contacted through the group comprising an app, Internet sharing via hardwired systems, Wi-Fi, QR code scanning uplink, application program interface (API), or near field communication. 25. The method of claim 16 including the further step of a seller of a product or service uploading to the Internet information regarding their goods or services using a unique encrypted alpha numeric hash or using a recognized industry standardized alpha numeric value, the hash creation including the further steps of compiling data for dissemination; converting the data into a standard code; converting the standard code into a unique numeric value; and converting the unique numeric value into a unique alpha numeric hash. 26. The method of claim 25 wherein the data for dissemination is selected singly or in combination from the group comprising but not limited to product name, size, UPC and SKU codes or industry standardized alpha numeric values, service description, sales and promotion information, availability, direction for taking advantage of a promotion, facility location information like GPS, street address, map coordinates, store number or email address, and social media information. 27. The method of claim 26 wherein the standard code is a tag. 28. The method of claim 16 including the further step of selecting one or more individual search results and adding them to a list. 29. The method of claim 16 including the further step of disseminating search results to but not limited to search engines and or social media. 30. The social media information of claim 29 wherein the social media is selected singly or in combination from the group comprising but not limiting to Facebook, Twitter, LinkedIn, Google+, Path, MySpace, Pinterest, browsers, and search engines. | The present invention is a web-based and mobile device application service that enables customizable product or service information retrieval from the Internet through the input of a unique product or service identifier and a location parameter. The unique product or service identifier is an alpha numeric number, UPC code, SKU, MLS or other product or service identifying parameter and the location parameter, which may be a zip code, address, town, city, state, country, GPS coordinate, or other location identifier, to provide a user with listings of the exact locations of a product or service from or within the described location. The retrieved data may include information regarding the product or service, including but not limited to price, size, availability, product or service description, web site information or links, promotional codes or sale information or any other data made available by the seller. The system may further enable a user to input a common product or service name which is converted into a unique product or service identifier.1. A method for a web-based system of retrieving data from the Internet using a computing device including:
(a) accessing the Internet; (b) contacting a remote, centralized web-based search function; (c) accessing the search page of the remote, centralized web-based search function; (d) imputing a unique product or service code and a location identifier into the remote, centralized web-based search function; (e) activating a search function; and, (f) retrieving search results based upon the search criteria. 2. The method of claim 1 wherein the unique product or service code is a standardized code. 3. The method of claim 1 wherein the unique product or service code is a user promulgated product descriptor, the product descriptor then converted into a standardized code. 4. The standardized code of claim 2 being selected from the group comprising but not limiting to, either singly or in combination, UPC, SKU, EAN, MLS, VIN, and GTIN. 5. The method of claim 1 wherein the location identifier is selected from the group comprising but not limed to, either singly or in combination, zip code, GPS coordinate, location, cellular triangulation, address, city, town, state, and country. 6. The method of claim 1 wherein the retrieved data includes information selected singly or in combination from the group comprising but not limited to product or service name, price, location name, distance to location, inventory count, product size, promotion information, availability, local competition, and coupons. 7. The method of claim 1 including the further step of sorting the retrieved search results to a user's preference. 8. The step of claim 7 wherein the user's preference is selected singly or in combination from the group comprising but not limited to product or service name, price, location name, distance to location, inventory count, product size, promotion information, availability, local competition, and coupons. 9. The method of claim 1 wherein the search function is contacted through the group comprising an app, Internet sharing via hardwired systems, Wi-Fi, QR code scanning uplink, application program interface (API), or near field communication. 10. The method of claim 1 including the further step of a seller of a product or service uploading to the Internet information regarding their goods or services using a unique encrypted alpha numeric hash or using a recognized industry standardized alpha numeric value, the hash creation including the further steps of compiling data for dissemination; converting the data into a standard code; converting the standard code into a unique numeric value; and converting the unique numeric value into a unique alpha numeric hash. 11. The method of claim 10 wherein the data for dissemination is selected singly or in combination from the group comprising but not limited to product name, size, UPC and SKU codes or industry standardized alpha numeric values, service description, sales and promotion information, availability, direction for taking advantage of a promotion, facility location information like GPS, street address, map coordinates, store number or email address, and social media information. 12. The method of claim 10 wherein the standard code is a tag. 13. The method of claim 1 including the further step of selecting one or more individual search results and adding them to a list. 14. The method of claim 1 including the further step of disseminating search results to but not limited to search engines and or social media. 15. The social media information of claim 14 wherein the social media is selected singly or in combination from the group comprising but not limiting to Facebook, Twitter, LinkedIn, Google+, Path, MySpace, Pinterest, browsers, and search engines. 16. A method for sharing data between a seller and a customer comprising:
(a) uploading data by a seller using a remote computing device to contact a web-based, centralized digital information site; (b) accessing the Internet by a customer; (c) contacting a remote, centralized web-based search function; (d) accessing the search page of the remote, centralized web-based search function; (e) imputing search criteria into the remote, centralized web-based search function, the search criteria comprising at least a unique product or service code and a location identifier; (f) activating a search function; and, (g) retrieving search results based upon the search criteria. 17. The method of claim 16 wherein the unique product or service code is a standardized code. 18. The method of claim 16 wherein the unique product or service code is a user promulgated product descriptor, the product descriptor then converted into a standardized code. 19. The standardized code of claim 17 being selected from the group comprising but not limiting to, either singly or in combination, UPC, SKU, EAN, MLS, VIN, and GTIN. 20. The method of claim 16 wherein the location identifier is selected from the group comprising but not limed to, either singly or in combination, zip code, GPS coordinate, location, cellular triangulation, address, city, town, state, and country. 21. The method of claim 16 wherein the retrieved data includes information selected singly or in combination from the group comprising but not limited to product or service name, price, location name, distance to location, inventory count, product size, promotion information, availability, local competition, and coupons. 22. The method of claim 16 including the further step of sorting the retrieved search results to a user's preference. 23. The step of claim 22 wherein the user's preference is selected singly or in combination from the group comprising but not limited to product or service name, price, location name, distance to location, inventory count, product size, promotion information, availability, local competition, and coupons. 24. The method of claim 16 wherein the search function is contacted through the group comprising an app, Internet sharing via hardwired systems, Wi-Fi, QR code scanning uplink, application program interface (API), or near field communication. 25. The method of claim 16 including the further step of a seller of a product or service uploading to the Internet information regarding their goods or services using a unique encrypted alpha numeric hash or using a recognized industry standardized alpha numeric value, the hash creation including the further steps of compiling data for dissemination; converting the data into a standard code; converting the standard code into a unique numeric value; and converting the unique numeric value into a unique alpha numeric hash. 26. The method of claim 25 wherein the data for dissemination is selected singly or in combination from the group comprising but not limited to product name, size, UPC and SKU codes or industry standardized alpha numeric values, service description, sales and promotion information, availability, direction for taking advantage of a promotion, facility location information like GPS, street address, map coordinates, store number or email address, and social media information. 27. The method of claim 26 wherein the standard code is a tag. 28. The method of claim 16 including the further step of selecting one or more individual search results and adding them to a list. 29. The method of claim 16 including the further step of disseminating search results to but not limited to search engines and or social media. 30. The social media information of claim 29 wherein the social media is selected singly or in combination from the group comprising but not limiting to Facebook, Twitter, LinkedIn, Google+, Path, MySpace, Pinterest, browsers, and search engines. | 2,100 |
6,027 | 6,027 | 15,527,138 | 2,135 | Memory modules and associated devices and methods are provided using a memory copy function between a cache memory and a main memory that may be implemented in hardware. Address translation may additionally be provided. | 1-13. (canceled) 14. A memory module for a computing device, the memory module comprising:
a main memory, at least one cache memory, and a memory copy device being connected with the main memory and with the cache memory, wherein the memory copy device comprises at least one Direct Memory Access (DMA) port for accessing data in the main memory and data in the cache memory, the memory copy device being configured to reading and writing data between the cache memory and the main memory via the DMA port. 15. The memory module of claim 14, wherein the memory copy device further comprises:
an address translation device for translating between a memory physical address and a memory virtual address. 16. The memory module of claim 14, wherein the memory copy device further comprises:
a cached access module device for the reading and writing data between the cache memory and the main memory via the DMA port and for maintaining data integrity and coherence between the cache memory and the main memory. 17. The memory module of claim 14, wherein the memory copy device is implemented in hardware. 18. The memory module of claim 14, wherein the memory copy device is configured to perform the reading and writing without having to use a processor external to the memory copy device. 19. A computing device comprising:
at least one processing core module; and a memory module comprising:
a main memory,
at least one cache memory, and
a memory copy device being connected with the main memory and with the cache memory, wherein the memory copy device comprises at least one Direct Memory Access (DMA) port for accessing data in the main memory and data in the cache memory, the memory copy device being configured to reading and writing data between the cache memory and the main memory via the DMA port,
wherein the processing core module is configured to store data in the memory module and to reads data from the memory module. 20. The computing device of claim 19, wherein the memory copy device further comprises:
an address translation device for translating between a memory physical address and a memory virtual address. 21. The computing device of claim 19, wherein the memory copy device further comprises:
a cached access module device for the reading and writing data between the cache memory and the main memory via the DMA port and for maintaining data integrity and coherence between the cache memory and the main memory. 22. The computing device of claim 19, wherein the memory copy device is implemented in hardware. 23. The computing device of claim 19, wherein the memory copy device is configured to perform the reading and writing without having to use a processor external to the memory copy device. 24. The computing device of claim 19, wherein the memory copy device of the memory module is configured to perform memory copy operations between the main memory and the cache memory of the memory module without using the processing core module. 25. The computing device of claim 19, further comprising a network module to operate in a network. 26. The computing device of claim 25, wherein the network module comprises one or more devices selected from a group consisting of a router device, a gateway device, and a Network Attached Storage (NAS) device. 27. A method of operating a memory module comprising:
translating, in a hardware device, between a memory physical address and memory virtual address; and, in the hardware device, reading and writing data between a cache memory and a main memory via Direct Memory Access. 28. The method of claim 27, wherein the reading and writing is in order to maintain data integrity and coherence between the cache memory and the main memory. 29. The method of claim 27, wherein the memory module is a memory module comprising:
a main memory, at least one cache memory, and a memory copy device being connected with the main memory and with the cache memory, wherein the memory copy device comprises at least one Direct Memory Access (DMA) port for accessing data in the main memory and data in the cache memory, the memory copy device being configured to reading and writing data between the cache memory and the main memory via the DMA port, and the hardware device is the memory copy device of the memory module. 30. The method of claim 27, wherein the reading and writing is performed at least in part using the translating. | Memory modules and associated devices and methods are provided using a memory copy function between a cache memory and a main memory that may be implemented in hardware. Address translation may additionally be provided.1-13. (canceled) 14. A memory module for a computing device, the memory module comprising:
a main memory, at least one cache memory, and a memory copy device being connected with the main memory and with the cache memory, wherein the memory copy device comprises at least one Direct Memory Access (DMA) port for accessing data in the main memory and data in the cache memory, the memory copy device being configured to reading and writing data between the cache memory and the main memory via the DMA port. 15. The memory module of claim 14, wherein the memory copy device further comprises:
an address translation device for translating between a memory physical address and a memory virtual address. 16. The memory module of claim 14, wherein the memory copy device further comprises:
a cached access module device for the reading and writing data between the cache memory and the main memory via the DMA port and for maintaining data integrity and coherence between the cache memory and the main memory. 17. The memory module of claim 14, wherein the memory copy device is implemented in hardware. 18. The memory module of claim 14, wherein the memory copy device is configured to perform the reading and writing without having to use a processor external to the memory copy device. 19. A computing device comprising:
at least one processing core module; and a memory module comprising:
a main memory,
at least one cache memory, and
a memory copy device being connected with the main memory and with the cache memory, wherein the memory copy device comprises at least one Direct Memory Access (DMA) port for accessing data in the main memory and data in the cache memory, the memory copy device being configured to reading and writing data between the cache memory and the main memory via the DMA port,
wherein the processing core module is configured to store data in the memory module and to reads data from the memory module. 20. The computing device of claim 19, wherein the memory copy device further comprises:
an address translation device for translating between a memory physical address and a memory virtual address. 21. The computing device of claim 19, wherein the memory copy device further comprises:
a cached access module device for the reading and writing data between the cache memory and the main memory via the DMA port and for maintaining data integrity and coherence between the cache memory and the main memory. 22. The computing device of claim 19, wherein the memory copy device is implemented in hardware. 23. The computing device of claim 19, wherein the memory copy device is configured to perform the reading and writing without having to use a processor external to the memory copy device. 24. The computing device of claim 19, wherein the memory copy device of the memory module is configured to perform memory copy operations between the main memory and the cache memory of the memory module without using the processing core module. 25. The computing device of claim 19, further comprising a network module to operate in a network. 26. The computing device of claim 25, wherein the network module comprises one or more devices selected from a group consisting of a router device, a gateway device, and a Network Attached Storage (NAS) device. 27. A method of operating a memory module comprising:
translating, in a hardware device, between a memory physical address and memory virtual address; and, in the hardware device, reading and writing data between a cache memory and a main memory via Direct Memory Access. 28. The method of claim 27, wherein the reading and writing is in order to maintain data integrity and coherence between the cache memory and the main memory. 29. The method of claim 27, wherein the memory module is a memory module comprising:
a main memory, at least one cache memory, and a memory copy device being connected with the main memory and with the cache memory, wherein the memory copy device comprises at least one Direct Memory Access (DMA) port for accessing data in the main memory and data in the cache memory, the memory copy device being configured to reading and writing data between the cache memory and the main memory via the DMA port, and the hardware device is the memory copy device of the memory module. 30. The method of claim 27, wherein the reading and writing is performed at least in part using the translating. | 2,100 |
6,028 | 6,028 | 13,860,676 | 2,147 | A model-management system includes a cycles map generator, object registry generator and runtime code generator. The cycles map generator is configured to create a cycles map that, for a cycle in an information model having a plurality of objects, identifies a non-dominant association of a second or later object to a first object. The object registry generator is configured to create an object registry map. And the runtime code generator is configured to generate an instantiable information model and object registry based on the information model and maps. Generation of the instantiable information model includes generation of a plurality of instantiable objects including a second/later instantiable object that, for the non-dominant association, includes an object qualifier that identifies a referenced object for the first object to be instantiated through the object registry, instead of a contained first instantiable object to be instantiated from within the second/later instantiable object. | 1. A model-management system comprising:
a cycles map generator configured to traverse an information model having a plurality of objects at least some of which form a cycle, the cycles map generator being configured to create a cycles map that, for the cycle, identifies a non-dominant association of a second or later object to a first object; an object registry generator configured to create an object registry map that identifies the non-dominant association and includes one or more lifecycle policies for a second or later instantiable object for the respective second or later object; and a runtime code generator configured to generate an instantiable information model and object registry based on the information model, cycles map and object registry map, wherein generation of the instantiable information model includes generation of a plurality of instantiable objects for respective ones of the objects of the information model, including generation of the second or later instantiable object that, for the non-dominant association, includes an object qualifier that identifies a referenced object for the first object to be instantiated through the object registry, instead of a contained first instantiable object to be instantiated from within the second or later instantiable object. 2. The model-management system of claim 1, wherein the runtime code generator is configured to generate the second or later instantiable object including the contained first instantiable object, and then remove the contained first instantiable object and replace it with the object qualifier. 3. The model-management system of claim 1, wherein the first object is related to the second object through a dominant association, and the second or later object is related back to the first object through the non-dominant association, and
wherein generation of the instantiable objects includes generation of the first instantiable object that, for the dominant association, contains the second instantiable object for instantiation from therewithin. 4. The model-management system of claim 1, wherein the runtime code generator is configured to generate the instantiable information model using a plurality of object-oriented design patterns including a proxy pattern and factory method pattern, and
wherein the object registry generated by the runtime code generator includes an object manager configured to implement the proxy pattern to manage instantiation of the referenced object, and an object factory configured to implement the factory method pattern to instantiate the referenced object. 5. The model-management system of claim 4, wherein the object-oriented design patterns further include a singleton pattern, and
wherein object factory is configured to implement the factory method pattern according to the singleton pattern to restrict instances of the referenced pattern according to a cardinality value. 6. The model-management system of claim 1 further comprising:
a model repository configured to store one or more information models at least some of which are removable according to a weighted first-in-first-out technique, the cycles map generator being configured to receive the information model from the model repository. 7. The model-management system of claim 1 further comprising:
an adapter component configured to convert the information model from any of a plurality of different formats to a common format in which the information model is traversed. 8. A method comprising:
traversing an information model having a plurality of objects at least some of which form a cycle, and creating a cycles map that, for the cycle, identifies a non-dominant association of a second or later object to a first object; creating an object registry map that identifies the non-dominant association and includes one or more lifecycle policies for a second or later instantiable object for the respective second or later object; and generating an instantiable information model and object registry based on the information model, cycles map and object registry map, wherein generation of the instantiable information model includes generation of a plurality of instantiable objects for respective ones of the objects of the information model, including generation of the second or later instantiable object that, for the non-dominant association, includes an object qualifier that identifies a referenced object for the first object to be instantiated through the object registry, instead of a contained first instantiable object to be instantiated from within the second or later instantiable object. 9. The method of claim 8, wherein generating the instantiable information model includes generating the second or later instantiable object including the contained first instantiable object, and then removing the contained first instantiable object and replacing it with the object qualifier. 10. The method of claim 8, wherein the first object is related to the second object through a dominant association, and the second or later object is related back to the first object through the non-dominant association, and
wherein generation of the instantiable objects includes generation of the first instantiable object that, for the dominant association, contains the second instantiable object for instantiation from therewithin. 11. The method of claim 8, wherein the instantiable information model is generated using a plurality of object-oriented design patterns including a proxy pattern and factory method pattern, and
wherein the object registry includes an object manager configured to implement the proxy pattern to manage instantiation of the referenced object, and an object factory configured to implement the factory method pattern to instantiate the referenced object. 12. The method of claim 11, wherein the instantiable information model is generated using the plurality of object-oriented design patterns further including a singleton pattern, and
wherein object factory is configured to implement the factory method pattern according to the singleton pattern to restrict instances of the referenced pattern according to a cardinality value. 13. The method of claim 8 further comprising:
receiving the information model for traversal from a model repository configured to store one or more information models at least some of which are removable according to a weighted first-in-first-out technique. 14. The method of claim 8 further comprising:
converting the information model from any of a plurality of different formats to a common format in which the information model is traversed. 15. A computer-readable storage medium having computer-readable program code portions stored therein that, in response to execution by a processor, cause an apparatus to at least:
traverse an information model having a plurality of objects at least some of which form a cycle, and create a cycles map that, for the cycle, identifies a non-dominant association of a second or later object to a first object; create an object registry map that identifies the non-dominant association and includes one or more lifecycle policies for a second or later instantiable object for the respective second or later object; and generate an instantiable information model and object registry based on the information model, cycles map and object registry map, wherein generation of the instantiable information model includes generation of a plurality of instantiable objects for respective ones of the objects of the information model, including generation of the second or later instantiable object that, for the non-dominant association, includes an object qualifier that identifies a referenced object for the first object to be instantiated through the object registry, instead of a contained first instantiable object to be instantiated from within the second or later instantiable object. 16. The computer-readable storage medium of claim 15, wherein the apparatus is caused to generate the second or later instantiable object including the contained first instantiable object, and then remove the contained first instantiable object and replace it with the object qualifier. 17. The computer-readable storage medium of claim 15, wherein the first object is related to the second object through a dominant association, and the second or later object is related back to the first object through the non-dominant association, and
wherein generation of the instantiable objects includes generation of the first instantiable object that, for the dominant association, contains the second instantiable object for instantiation from therewithin. 18. The computer-readable storage medium of claim 15, wherein the apparatus is caused to generate the instantiable information model using a plurality of object-oriented design patterns including a proxy pattern and factory method pattern, and
wherein the object registry generated by the apparatus includes an object manager configured to implement the proxy pattern to manage instantiation of the referenced object, and an object factory configured to implement the factory method pattern to instantiate the referenced object. 19. The computer-readable storage medium of claim 18, wherein the object-oriented design patterns further include a singleton pattern, and
wherein object factory is configured to implement the factory method pattern according to the singleton pattern to restrict instances of the referenced pattern according to a cardinality value. 20. The computer-readable storage medium of claim 15 having further computer-readable program code portions stored therein that, in response to execution by the processor, cause the apparatus to further:
receive the information model for traversal from a model repository configured to store one or more information models at least some of which are removable according to a weighted first-in-first-out technique. 21. The computer-readable storage medium -management system of claim 15 having further computer-readable program code portions stored therein that, in response to execution by the processor, cause the apparatus to further:
convert the information model from any of a plurality of different formats to a common format in which the information model is traversed. | A model-management system includes a cycles map generator, object registry generator and runtime code generator. The cycles map generator is configured to create a cycles map that, for a cycle in an information model having a plurality of objects, identifies a non-dominant association of a second or later object to a first object. The object registry generator is configured to create an object registry map. And the runtime code generator is configured to generate an instantiable information model and object registry based on the information model and maps. Generation of the instantiable information model includes generation of a plurality of instantiable objects including a second/later instantiable object that, for the non-dominant association, includes an object qualifier that identifies a referenced object for the first object to be instantiated through the object registry, instead of a contained first instantiable object to be instantiated from within the second/later instantiable object.1. A model-management system comprising:
a cycles map generator configured to traverse an information model having a plurality of objects at least some of which form a cycle, the cycles map generator being configured to create a cycles map that, for the cycle, identifies a non-dominant association of a second or later object to a first object; an object registry generator configured to create an object registry map that identifies the non-dominant association and includes one or more lifecycle policies for a second or later instantiable object for the respective second or later object; and a runtime code generator configured to generate an instantiable information model and object registry based on the information model, cycles map and object registry map, wherein generation of the instantiable information model includes generation of a plurality of instantiable objects for respective ones of the objects of the information model, including generation of the second or later instantiable object that, for the non-dominant association, includes an object qualifier that identifies a referenced object for the first object to be instantiated through the object registry, instead of a contained first instantiable object to be instantiated from within the second or later instantiable object. 2. The model-management system of claim 1, wherein the runtime code generator is configured to generate the second or later instantiable object including the contained first instantiable object, and then remove the contained first instantiable object and replace it with the object qualifier. 3. The model-management system of claim 1, wherein the first object is related to the second object through a dominant association, and the second or later object is related back to the first object through the non-dominant association, and
wherein generation of the instantiable objects includes generation of the first instantiable object that, for the dominant association, contains the second instantiable object for instantiation from therewithin. 4. The model-management system of claim 1, wherein the runtime code generator is configured to generate the instantiable information model using a plurality of object-oriented design patterns including a proxy pattern and factory method pattern, and
wherein the object registry generated by the runtime code generator includes an object manager configured to implement the proxy pattern to manage instantiation of the referenced object, and an object factory configured to implement the factory method pattern to instantiate the referenced object. 5. The model-management system of claim 4, wherein the object-oriented design patterns further include a singleton pattern, and
wherein object factory is configured to implement the factory method pattern according to the singleton pattern to restrict instances of the referenced pattern according to a cardinality value. 6. The model-management system of claim 1 further comprising:
a model repository configured to store one or more information models at least some of which are removable according to a weighted first-in-first-out technique, the cycles map generator being configured to receive the information model from the model repository. 7. The model-management system of claim 1 further comprising:
an adapter component configured to convert the information model from any of a plurality of different formats to a common format in which the information model is traversed. 8. A method comprising:
traversing an information model having a plurality of objects at least some of which form a cycle, and creating a cycles map that, for the cycle, identifies a non-dominant association of a second or later object to a first object; creating an object registry map that identifies the non-dominant association and includes one or more lifecycle policies for a second or later instantiable object for the respective second or later object; and generating an instantiable information model and object registry based on the information model, cycles map and object registry map, wherein generation of the instantiable information model includes generation of a plurality of instantiable objects for respective ones of the objects of the information model, including generation of the second or later instantiable object that, for the non-dominant association, includes an object qualifier that identifies a referenced object for the first object to be instantiated through the object registry, instead of a contained first instantiable object to be instantiated from within the second or later instantiable object. 9. The method of claim 8, wherein generating the instantiable information model includes generating the second or later instantiable object including the contained first instantiable object, and then removing the contained first instantiable object and replacing it with the object qualifier. 10. The method of claim 8, wherein the first object is related to the second object through a dominant association, and the second or later object is related back to the first object through the non-dominant association, and
wherein generation of the instantiable objects includes generation of the first instantiable object that, for the dominant association, contains the second instantiable object for instantiation from therewithin. 11. The method of claim 8, wherein the instantiable information model is generated using a plurality of object-oriented design patterns including a proxy pattern and factory method pattern, and
wherein the object registry includes an object manager configured to implement the proxy pattern to manage instantiation of the referenced object, and an object factory configured to implement the factory method pattern to instantiate the referenced object. 12. The method of claim 11, wherein the instantiable information model is generated using the plurality of object-oriented design patterns further including a singleton pattern, and
wherein object factory is configured to implement the factory method pattern according to the singleton pattern to restrict instances of the referenced pattern according to a cardinality value. 13. The method of claim 8 further comprising:
receiving the information model for traversal from a model repository configured to store one or more information models at least some of which are removable according to a weighted first-in-first-out technique. 14. The method of claim 8 further comprising:
converting the information model from any of a plurality of different formats to a common format in which the information model is traversed. 15. A computer-readable storage medium having computer-readable program code portions stored therein that, in response to execution by a processor, cause an apparatus to at least:
traverse an information model having a plurality of objects at least some of which form a cycle, and create a cycles map that, for the cycle, identifies a non-dominant association of a second or later object to a first object; create an object registry map that identifies the non-dominant association and includes one or more lifecycle policies for a second or later instantiable object for the respective second or later object; and generate an instantiable information model and object registry based on the information model, cycles map and object registry map, wherein generation of the instantiable information model includes generation of a plurality of instantiable objects for respective ones of the objects of the information model, including generation of the second or later instantiable object that, for the non-dominant association, includes an object qualifier that identifies a referenced object for the first object to be instantiated through the object registry, instead of a contained first instantiable object to be instantiated from within the second or later instantiable object. 16. The computer-readable storage medium of claim 15, wherein the apparatus is caused to generate the second or later instantiable object including the contained first instantiable object, and then remove the contained first instantiable object and replace it with the object qualifier. 17. The computer-readable storage medium of claim 15, wherein the first object is related to the second object through a dominant association, and the second or later object is related back to the first object through the non-dominant association, and
wherein generation of the instantiable objects includes generation of the first instantiable object that, for the dominant association, contains the second instantiable object for instantiation from therewithin. 18. The computer-readable storage medium of claim 15, wherein the apparatus is caused to generate the instantiable information model using a plurality of object-oriented design patterns including a proxy pattern and factory method pattern, and
wherein the object registry generated by the apparatus includes an object manager configured to implement the proxy pattern to manage instantiation of the referenced object, and an object factory configured to implement the factory method pattern to instantiate the referenced object. 19. The computer-readable storage medium of claim 18, wherein the object-oriented design patterns further include a singleton pattern, and
wherein object factory is configured to implement the factory method pattern according to the singleton pattern to restrict instances of the referenced pattern according to a cardinality value. 20. The computer-readable storage medium of claim 15 having further computer-readable program code portions stored therein that, in response to execution by the processor, cause the apparatus to further:
receive the information model for traversal from a model repository configured to store one or more information models at least some of which are removable according to a weighted first-in-first-out technique. 21. The computer-readable storage medium -management system of claim 15 having further computer-readable program code portions stored therein that, in response to execution by the processor, cause the apparatus to further:
convert the information model from any of a plurality of different formats to a common format in which the information model is traversed. | 2,100 |
6,029 | 6,029 | 15,723,489 | 2,163 | Disclosed herein are system, method, and computer program product embodiments for identifying and monitoring social media accounts belonging to offenders, inmates, and relevant third parties. In an embodiment, a social media monitoring system retrieves information from a criminal history database to identify and verify social media account information. In an embodiment, a social media monitoring system retrieves information from an offender communication device, such as a computer, phone, or tablet, to identify and verify social media account information. The social media monitoring system analyzes this information, retrieves social media accounts, and generates a confidence score and/or relevance score for each retrieved social media account. Social media monitoring system organizes links to the social media accounts based on the scores and also generates alerts when a security threat associated with the social media accounts is detected. | 1. A social media monitoring system, comprising:
a memory; and one or more processors and/or circuits coupled to the memory, wherein the one or more processors are configured to:
receive identification data related to an individual accused of committing a crime;
search a criminal history record database using the identification data for a criminal history record related to the individual;
generate a search packet including the criminal history record and identification data;
transmit the search packet to a first social media server and a second social media server different from the first social media server to receive a first social media account associated with the individual from the first social media server and a second social media account associated with the individual from the second social media server;
determine a first confidence score for the first social media account and a second confidence score for the second social media account, wherein the first confidence score and the second confidence score are indicative of the amount of information associated with the first or second social media account confirmed by the identification data and the criminal history record; and
generate a graphical user interface displaying the first social media account with a first account preview displaying information from the first social media account and the second social media account with a second account preview displaying information from the second social media account, wherein the first account preview and the second account preview are displayed in a list of social media accounts ranked by confidence score. 2. The social media monitoring system of claim 1, wherein the criminal history record includes information related to a party other than the individual. 3. The social media monitoring system of claim 1, wherein the one or more processors and/or circuits are further configured to:
identify a third social media account associated with a party other than the individual based on the first or second social media account associated with the individual. 4. The social media monitoring system of claim 1, wherein the one or more processors and/or circuits are further configured to:
retrieve second identification data from a mobile electronic communication device, and wherein the search packet includes the second identification data. 5. The social media monitoring system of claim 1, wherein to determine the first confidence score of the first social media account, the one or more processors and/or circuits are further configured to:
increase a numerical value based on a number of information matches detected between the identification data and account data of the first social media account; increase a numerical value based on a number of information matches detected between the criminal history record and account data of the first social media account; decrease the numerical value based on a number of information mismatches detected between the identification data and account data of the first social media account; and decrease the numerical value based on a number of information mismatches detected between the criminal history record and account data of the first social media account. 6. The social media monitoring system of claim 1, wherein to determine the first confidence score of the first social media account, the one or more processors and/or circuits are further configured to:
compare image data included in the identification data with image data associated with the first social media account. 7. The social media monitoring system of claim 1, wherein to determine the first confidence score of the first social media account, the one or more processors and/or circuits are further configured to:
compare texting patterns utilized in the identification data with texting patterns associated with the first social media account. 8. The social media monitoring system of claim 1, wherein to generate the graphical user interface, the one or more processors and/or circuits are further configured to:
compare the first confidence score to a predetermined confidence score threshold; and include the first social media account in the graphical user interface in response to determining that the first confidence score is greater than the predetermined confidence score threshold. 9. A social media monitoring system, comprising:
a memory storing a list of social media accounts belonging to an inmate and a non-incarcerated third party, wherein the list includes a first social media account and a second social media account belonging to the inmate and wherein the list of social media accounts is ranked by confidence score; and one or more processors and/or circuits communicatively coupled to the memory and configured to:
generate a graphical user interface displaying the list of social media accounts, wherein the list includes a first account preview displaying information from the first social media account and a second account preview displaying information from the second social media account;
monitor updates to social media accounts from the list of social media accounts;
analyze the updates to determine the presence of predetermined keywords related to criminal activity; and
in response to detecting a predetermined keyword, displaying an alert on the graphical user interface displaying the list of social media accounts. 10. The social media monitoring system of claim 9, wherein the keywords include a time associated with an update to the first social media account. 11. The social media monitoring system of claim 9, wherein the keywords include a location associated with an update to the first social media account. 12. The social media monitoring system of claim 9, wherein the alert includes a preview of the updates including the predetermined keyword. 13. The social media monitoring system of claim 9, wherein detecting a predetermined keyword occurs at the first social media account and the alert includes a link to the first social media account including the predetermined keyword. 14. The social media monitoring system of claim 9, wherein the one or more processors and/or circuits are further configured to:
analyze the updates to determine the presence of images related to criminal activity; and in response to detecting the presence of images related to criminal activity, transmit an alert to an application accessible by law enforcement officials. 15. The presence monitoring system of claim 9, wherein the updates include postings to public Internet message boards. 16. A computer-implemented method, comprising:
receiving identification data related to an individual accused of committing a crime; determining a first social media account belonging to the individual based on the identification information; determining a first account score associated with the first social media account; determining a second social media account from a second social media service belonging to the individual based on the identification information; determining a second account score associated with the second social media account; searching a criminal history database using the identification data to identify a second party associated with the individual; based on the searching, determining a third social media account belonging to the second party; determining a third account score associated with the third social media account based on the frequency of interaction measured between the first and second social media accounts; and generating a graphical user interface displaying a first account preview displaying information from the first social media account, a second account preview displaying information from the second social media account, and a third account preview displaying information from the third social media account in a list of social media accounts ranked by account score. 17. The computer-implemented method of claim 16, wherein determining the third account score further comprises:
increasing a numerical value in response to detecting an interaction between the first and third social media accounts. 18. The computer-implemented method of claim 17, wherein the interaction is detected on the third social media account. 19. The computer-implemented method of claim 16, wherein the individual and the second party are inmates. 20. The computer-implemented method of claim 16, further comprising:
based on the searching, determining a fourth social media account belonging to the second party; and generating a fourth account score associated with the third social media account based on the frequency of interaction measured between the first and third social media accounts. 21. The computer-implemented method of claim 16, further comprising:
searching a communication device belonging to the individual to identify a third party associated with the individual; and determining a fourth social media account belonging to the third party. 22. The computer-implemented method of claim 21, further comprising:
generating a fourth account score associated with the fourth social media account based on the frequency of interaction measured between the first and fourth social media accounts. | Disclosed herein are system, method, and computer program product embodiments for identifying and monitoring social media accounts belonging to offenders, inmates, and relevant third parties. In an embodiment, a social media monitoring system retrieves information from a criminal history database to identify and verify social media account information. In an embodiment, a social media monitoring system retrieves information from an offender communication device, such as a computer, phone, or tablet, to identify and verify social media account information. The social media monitoring system analyzes this information, retrieves social media accounts, and generates a confidence score and/or relevance score for each retrieved social media account. Social media monitoring system organizes links to the social media accounts based on the scores and also generates alerts when a security threat associated with the social media accounts is detected.1. A social media monitoring system, comprising:
a memory; and one or more processors and/or circuits coupled to the memory, wherein the one or more processors are configured to:
receive identification data related to an individual accused of committing a crime;
search a criminal history record database using the identification data for a criminal history record related to the individual;
generate a search packet including the criminal history record and identification data;
transmit the search packet to a first social media server and a second social media server different from the first social media server to receive a first social media account associated with the individual from the first social media server and a second social media account associated with the individual from the second social media server;
determine a first confidence score for the first social media account and a second confidence score for the second social media account, wherein the first confidence score and the second confidence score are indicative of the amount of information associated with the first or second social media account confirmed by the identification data and the criminal history record; and
generate a graphical user interface displaying the first social media account with a first account preview displaying information from the first social media account and the second social media account with a second account preview displaying information from the second social media account, wherein the first account preview and the second account preview are displayed in a list of social media accounts ranked by confidence score. 2. The social media monitoring system of claim 1, wherein the criminal history record includes information related to a party other than the individual. 3. The social media monitoring system of claim 1, wherein the one or more processors and/or circuits are further configured to:
identify a third social media account associated with a party other than the individual based on the first or second social media account associated with the individual. 4. The social media monitoring system of claim 1, wherein the one or more processors and/or circuits are further configured to:
retrieve second identification data from a mobile electronic communication device, and wherein the search packet includes the second identification data. 5. The social media monitoring system of claim 1, wherein to determine the first confidence score of the first social media account, the one or more processors and/or circuits are further configured to:
increase a numerical value based on a number of information matches detected between the identification data and account data of the first social media account; increase a numerical value based on a number of information matches detected between the criminal history record and account data of the first social media account; decrease the numerical value based on a number of information mismatches detected between the identification data and account data of the first social media account; and decrease the numerical value based on a number of information mismatches detected between the criminal history record and account data of the first social media account. 6. The social media monitoring system of claim 1, wherein to determine the first confidence score of the first social media account, the one or more processors and/or circuits are further configured to:
compare image data included in the identification data with image data associated with the first social media account. 7. The social media monitoring system of claim 1, wherein to determine the first confidence score of the first social media account, the one or more processors and/or circuits are further configured to:
compare texting patterns utilized in the identification data with texting patterns associated with the first social media account. 8. The social media monitoring system of claim 1, wherein to generate the graphical user interface, the one or more processors and/or circuits are further configured to:
compare the first confidence score to a predetermined confidence score threshold; and include the first social media account in the graphical user interface in response to determining that the first confidence score is greater than the predetermined confidence score threshold. 9. A social media monitoring system, comprising:
a memory storing a list of social media accounts belonging to an inmate and a non-incarcerated third party, wherein the list includes a first social media account and a second social media account belonging to the inmate and wherein the list of social media accounts is ranked by confidence score; and one or more processors and/or circuits communicatively coupled to the memory and configured to:
generate a graphical user interface displaying the list of social media accounts, wherein the list includes a first account preview displaying information from the first social media account and a second account preview displaying information from the second social media account;
monitor updates to social media accounts from the list of social media accounts;
analyze the updates to determine the presence of predetermined keywords related to criminal activity; and
in response to detecting a predetermined keyword, displaying an alert on the graphical user interface displaying the list of social media accounts. 10. The social media monitoring system of claim 9, wherein the keywords include a time associated with an update to the first social media account. 11. The social media monitoring system of claim 9, wherein the keywords include a location associated with an update to the first social media account. 12. The social media monitoring system of claim 9, wherein the alert includes a preview of the updates including the predetermined keyword. 13. The social media monitoring system of claim 9, wherein detecting a predetermined keyword occurs at the first social media account and the alert includes a link to the first social media account including the predetermined keyword. 14. The social media monitoring system of claim 9, wherein the one or more processors and/or circuits are further configured to:
analyze the updates to determine the presence of images related to criminal activity; and in response to detecting the presence of images related to criminal activity, transmit an alert to an application accessible by law enforcement officials. 15. The presence monitoring system of claim 9, wherein the updates include postings to public Internet message boards. 16. A computer-implemented method, comprising:
receiving identification data related to an individual accused of committing a crime; determining a first social media account belonging to the individual based on the identification information; determining a first account score associated with the first social media account; determining a second social media account from a second social media service belonging to the individual based on the identification information; determining a second account score associated with the second social media account; searching a criminal history database using the identification data to identify a second party associated with the individual; based on the searching, determining a third social media account belonging to the second party; determining a third account score associated with the third social media account based on the frequency of interaction measured between the first and second social media accounts; and generating a graphical user interface displaying a first account preview displaying information from the first social media account, a second account preview displaying information from the second social media account, and a third account preview displaying information from the third social media account in a list of social media accounts ranked by account score. 17. The computer-implemented method of claim 16, wherein determining the third account score further comprises:
increasing a numerical value in response to detecting an interaction between the first and third social media accounts. 18. The computer-implemented method of claim 17, wherein the interaction is detected on the third social media account. 19. The computer-implemented method of claim 16, wherein the individual and the second party are inmates. 20. The computer-implemented method of claim 16, further comprising:
based on the searching, determining a fourth social media account belonging to the second party; and generating a fourth account score associated with the third social media account based on the frequency of interaction measured between the first and third social media accounts. 21. The computer-implemented method of claim 16, further comprising:
searching a communication device belonging to the individual to identify a third party associated with the individual; and determining a fourth social media account belonging to the third party. 22. The computer-implemented method of claim 21, further comprising:
generating a fourth account score associated with the fourth social media account based on the frequency of interaction measured between the first and fourth social media accounts. | 2,100 |
6,030 | 6,030 | 15,675,319 | 2,193 | A computer system receives an account creation request for a social media platform created and sent using a frontend component. An application programming interface (API) call sequence associated with the account creation request is received from the frontend component. The API call sequence can reflect API calls registered by the frontend component in connection with creation of the account creation request, and timings of the registered API calls. An API call sequence model is applied to the API call sequence. The API call sequence model can be generated by providing training API call sequences to a machine learning component. At least one action is taken in response to the application of the API call sequence model indicating that the API call sequence is anomalous. The action can be taken with regard to the account creation request, or with regard to an account created in response to the account creation request. | 1. A method comprising:
receiving, in a computer system, an account creation request for a social media platform, the account creation request created and sent to the computer system using a frontend component; receiving, from the frontend component, an application programming interface (API) call sequence associated with the account creation request, the API call sequence reflecting API calls registered by the frontend component in connection with creation of the account creation request, and timings of the registered API calls; applying an API call sequence model to the received API call sequence, the API call sequence model generated by providing training API call sequences to a machine learning component; and in response to the application of the API call sequence model indicating that the received API call sequence is anomalous, taking at least one action with regard to the account creation request, or with regard to an account created in response to the account creation request. 2. The method of claim 1, wherein applying the API call sequence model comprises an evaluation of whether the received API call sequence is missing a particular API call of the frontend component. 3. The method of claim 2, wherein some of the training API call sequences correspond to valid account creation requests and others of the training API call sequences correspond to invalid account creation requests, and wherein the particular API call is identified for use in the evaluation based on the particular API call having a greater frequency of occurrence for the valid account creation requests than for the invalid account creation requests. 4. The method of claim 2, further comprising, in response to determining that the received API call sequence is missing the particular API call of the frontend component, evaluating whether the received API call sequence is missing another particular API call of the frontend component. 5. The method of claim 1, wherein applying the API call sequence model comprises evaluating the timing of the API calls. 6. The method of claim 5, wherein evaluating the timing of the API calls comprises determining whether a temporal separation of the API calls is less than a threshold. 7. The method of claim 5, wherein evaluating the timing of the API calls comprises determining whether a temporal separation of the API calls is randomized. 8. The method of claim 1, wherein applying the API call sequence model comprises counting the API calls in the received API call sequence. 9. The method of claim 1, wherein multiple API call sequences are received, the multiple API call sequences corresponding to respective account creation requests, the method further comprising storing the received API call sequences in a log, and evaluating the log to determine whether any of the received API call sequences are essentially identical to each other. 10. The method of claim 1, wherein the account is created in response to the account creation request, the method further comprising:
receiving engagement data regarding the account, the engagement data reflecting use of the frontend component to interact with the social media platform; applying an engagement model to the received engagement data, the engagement model generated by providing training engagement data to the machine learning component; and in response to the application of the engagement model indicating that the use of the frontend component is anomalous, taking at least one action with regard to the account. 11. The method of claim 1, wherein applying the API call sequence model comprises determining a score for the received API call sequence, wherein the application of the API call sequence model indicates that the received API call sequence is anomalous in response to the determined score not meeting a threshold for account creation normalcy. 12. The method of claim 1, wherein the connection between the API calls and the creation of the account creation request comprises that at least one of the API calls was registered by the frontend component during a predefined period of time after the account generation request was generated. 13. The method of claim 1, wherein taking the at least one action comprises attempting to contact a person associated with the account generation request, and determining whether the account generation request was generated by a script interacting with the frontend component. 14. The method of claim 1, further comprising:
receiving additional training API call sequences after applying the API call sequence model to the received API call sequence; generating an updated API call sequence model by providing the additional training API call sequences to the machine learning component; receiving another account creation request for the social media platform after generating the updated API call sequence model; applying the updated API call sequence model to the received other API call sequence; and in response to the application of the updated API call sequence model indicating that the received other API call sequence is anomalous, taking at least one action with regard to the other account creation request, or with regard to an other account created in response to the other account creation request. 15. The method of claim 14, further comprising applying the updated API call sequence model to a previous account creation request, including at least the received account creation request. 16. A non-transitory computer-readable storage medium having stored therein instructions that when executed cause at least one processor to perform operations including:
receiving, in a computer system, an account creation request for a social media platform, the account creation request created and sent to the computer system using a frontend component; receiving, from the frontend component, an application programming interface (API) call sequence associated with the account creation request, the API call sequence reflecting API calls registered by the frontend component in connection with creation of the account creation request, and timings of the registered API calls; applying an API call sequence model to the received API call sequence, the API call sequence model generated by providing training API call sequences to a machine learning component; and in response to the application of the API call sequence model indicating that the received API call sequence is anomalous, taking at least one action with regard to the account creation request, or with regard to an account created in response to the account creation request. 17. A computer system comprising:
an interface configured to receive an account creation request for a social media platform, the account creation request created and sent to the computer system using a frontend component, the interface also configured to receive an application programming interface (API) call sequence associated with the account creation request, the API call sequence reflecting API calls registered by the frontend component in connection with creation of the account creation request, and timings of the registered API calls; a log in which the computer system records received API call sequences; and a bot configured to apply an API call sequence model to at least the received API call sequence record in the log, the API call sequence model generated by providing training API call sequences to a machine learning component, wherein in response to the bot indicating that the received API call sequence is anomalous, the computer system takes at least one action with regard to the account creation request, or with regard to an account created in response to the account creation request. 18. The computer system of claim 17, wherein in applying the API call sequence model the bot evaluates the timing of the API calls. 19. The computer system of claim 18, wherein in evaluating the timing of the API calls the bot determines whether a temporal separation of the API calls is less than a threshold. 20. The computer system of claim 18, wherein in evaluating the timing of the API calls the bot determines whether a temporal separation of the API calls is randomized. | A computer system receives an account creation request for a social media platform created and sent using a frontend component. An application programming interface (API) call sequence associated with the account creation request is received from the frontend component. The API call sequence can reflect API calls registered by the frontend component in connection with creation of the account creation request, and timings of the registered API calls. An API call sequence model is applied to the API call sequence. The API call sequence model can be generated by providing training API call sequences to a machine learning component. At least one action is taken in response to the application of the API call sequence model indicating that the API call sequence is anomalous. The action can be taken with regard to the account creation request, or with regard to an account created in response to the account creation request.1. A method comprising:
receiving, in a computer system, an account creation request for a social media platform, the account creation request created and sent to the computer system using a frontend component; receiving, from the frontend component, an application programming interface (API) call sequence associated with the account creation request, the API call sequence reflecting API calls registered by the frontend component in connection with creation of the account creation request, and timings of the registered API calls; applying an API call sequence model to the received API call sequence, the API call sequence model generated by providing training API call sequences to a machine learning component; and in response to the application of the API call sequence model indicating that the received API call sequence is anomalous, taking at least one action with regard to the account creation request, or with regard to an account created in response to the account creation request. 2. The method of claim 1, wherein applying the API call sequence model comprises an evaluation of whether the received API call sequence is missing a particular API call of the frontend component. 3. The method of claim 2, wherein some of the training API call sequences correspond to valid account creation requests and others of the training API call sequences correspond to invalid account creation requests, and wherein the particular API call is identified for use in the evaluation based on the particular API call having a greater frequency of occurrence for the valid account creation requests than for the invalid account creation requests. 4. The method of claim 2, further comprising, in response to determining that the received API call sequence is missing the particular API call of the frontend component, evaluating whether the received API call sequence is missing another particular API call of the frontend component. 5. The method of claim 1, wherein applying the API call sequence model comprises evaluating the timing of the API calls. 6. The method of claim 5, wherein evaluating the timing of the API calls comprises determining whether a temporal separation of the API calls is less than a threshold. 7. The method of claim 5, wherein evaluating the timing of the API calls comprises determining whether a temporal separation of the API calls is randomized. 8. The method of claim 1, wherein applying the API call sequence model comprises counting the API calls in the received API call sequence. 9. The method of claim 1, wherein multiple API call sequences are received, the multiple API call sequences corresponding to respective account creation requests, the method further comprising storing the received API call sequences in a log, and evaluating the log to determine whether any of the received API call sequences are essentially identical to each other. 10. The method of claim 1, wherein the account is created in response to the account creation request, the method further comprising:
receiving engagement data regarding the account, the engagement data reflecting use of the frontend component to interact with the social media platform; applying an engagement model to the received engagement data, the engagement model generated by providing training engagement data to the machine learning component; and in response to the application of the engagement model indicating that the use of the frontend component is anomalous, taking at least one action with regard to the account. 11. The method of claim 1, wherein applying the API call sequence model comprises determining a score for the received API call sequence, wherein the application of the API call sequence model indicates that the received API call sequence is anomalous in response to the determined score not meeting a threshold for account creation normalcy. 12. The method of claim 1, wherein the connection between the API calls and the creation of the account creation request comprises that at least one of the API calls was registered by the frontend component during a predefined period of time after the account generation request was generated. 13. The method of claim 1, wherein taking the at least one action comprises attempting to contact a person associated with the account generation request, and determining whether the account generation request was generated by a script interacting with the frontend component. 14. The method of claim 1, further comprising:
receiving additional training API call sequences after applying the API call sequence model to the received API call sequence; generating an updated API call sequence model by providing the additional training API call sequences to the machine learning component; receiving another account creation request for the social media platform after generating the updated API call sequence model; applying the updated API call sequence model to the received other API call sequence; and in response to the application of the updated API call sequence model indicating that the received other API call sequence is anomalous, taking at least one action with regard to the other account creation request, or with regard to an other account created in response to the other account creation request. 15. The method of claim 14, further comprising applying the updated API call sequence model to a previous account creation request, including at least the received account creation request. 16. A non-transitory computer-readable storage medium having stored therein instructions that when executed cause at least one processor to perform operations including:
receiving, in a computer system, an account creation request for a social media platform, the account creation request created and sent to the computer system using a frontend component; receiving, from the frontend component, an application programming interface (API) call sequence associated with the account creation request, the API call sequence reflecting API calls registered by the frontend component in connection with creation of the account creation request, and timings of the registered API calls; applying an API call sequence model to the received API call sequence, the API call sequence model generated by providing training API call sequences to a machine learning component; and in response to the application of the API call sequence model indicating that the received API call sequence is anomalous, taking at least one action with regard to the account creation request, or with regard to an account created in response to the account creation request. 17. A computer system comprising:
an interface configured to receive an account creation request for a social media platform, the account creation request created and sent to the computer system using a frontend component, the interface also configured to receive an application programming interface (API) call sequence associated with the account creation request, the API call sequence reflecting API calls registered by the frontend component in connection with creation of the account creation request, and timings of the registered API calls; a log in which the computer system records received API call sequences; and a bot configured to apply an API call sequence model to at least the received API call sequence record in the log, the API call sequence model generated by providing training API call sequences to a machine learning component, wherein in response to the bot indicating that the received API call sequence is anomalous, the computer system takes at least one action with regard to the account creation request, or with regard to an account created in response to the account creation request. 18. The computer system of claim 17, wherein in applying the API call sequence model the bot evaluates the timing of the API calls. 19. The computer system of claim 18, wherein in evaluating the timing of the API calls the bot determines whether a temporal separation of the API calls is less than a threshold. 20. The computer system of claim 18, wherein in evaluating the timing of the API calls the bot determines whether a temporal separation of the API calls is randomized. | 2,100 |
6,031 | 6,031 | 16,030,142 | 2,182 | A Gaussian similarity matrix is computed between observation vectors. An inverse Gaussian similarity matrix is computed from the Gaussian similarity matrix. A row sum vector is computed that includes a row sum value computed from each row of the inverse Gaussian similarity matrix. (a) A new observation vector is selected. (b) An acceptance value is computed for the new observation vector using the set of boundary support vectors, the row sum vector, and the new observation vector. (c) (a) and (b) are repeated when the computed acceptance value is less than or equal to zero. (d) An incremental vector is computed from the inverse Gaussian similarity matrix and the new observation vector when the computed acceptance value is greater than zero. (e) the selected new observation vector is output as an outlier observation vector when a maximum value of the incremental vector is less than a first predefined tolerance value. | 1. A non-transitory computer-readable medium having stored thereon computer-readable instructions that when executed by a computing device cause the computing device to:
compute a Gaussian similarity matrix between a plurality of observation vectors, wherein each observation vector of the plurality of observation vectors includes a variable value for each variable of a plurality of variables; compute an inverse Gaussian similarity matrix from the computed Gaussian similarity matrix; compute a row sum vector that includes a row sum value computed from each row of the computed inverse Gaussian similarity matrix; select a set of boundary support vectors from the plurality of observation vectors; (a) select a new observation vector from an event stream or from an input dataset; (b) compute an acceptance value for the selected new observation vector using the selected set of boundary support vectors, the computed row sum vector, and the new observation vector; (c) when the computed acceptance value is greater than zero, compute an incremental vector from the computed inverse Gaussian similarity matrix and the selected new observation vector; (d) when the computed acceptance value is greater than zero and when a maximum value of the computed incremental vector is less than a first predefined tolerance value, output an indicator that the selected new observation vector is an abnormal observation vector relative to the selected set of boundary support vectors; and (e) repeat (a) to (d) until the event stream is stopped or a last observation vector is selected from the input dataset in (a). 2. The non-transitory computer-readable medium of claim 1, wherein the Gaussian similarity matrix is computed using
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where x(i) and x(j) are the plurality of observation vectors, s is a Gaussian bandwidth parameter, and NBV is a number of the plurality of observation vectors. 3. The non-transitory computer-readable medium of claim 2, wherein the number of the plurality of observation vectors is a predefined number to initialize the Gaussian similarity matrix. 4. The non-transitory computer-readable medium of claim 3, wherein the predefined number is a predefined subset of an input dataset. 5. The non-transitory computer-readable medium of claim 2, wherein the inverse Gaussian similarity matrix is computed using A−1=adj(A)/det(A), where adj(A) is an adjugate of the Gaussian similarity matrix and det(A) is a determinant of the Gaussian similarity matrix. 6. The non-transitory computer-readable medium of claim 1, wherein the row sum vector is computed using αu(j)=Σi=1 N BV A−1(i,j), j=1, . . . , NBV, where NBV is a number of the plurality of observation vectors, and A−1(i,j) is the inverse Gaussian similarity matrix. 7. The non-transitory computer-readable medium of claim 6, wherein a Lagrange multiplier for each observation vector is computed using α(k)=αu(k)/∥αu(k)∥1,k=1, . . . , NBV, where ∥αu(k)∥1 is a 1-norm of a kth row sum value. 8. The non-transitory computer-readable medium of claim 1, wherein outputting the selected new observation vector as the outlier observation vector comprises presenting the selected new observation vector on a display. 9. The non-transitory computer-readable medium of claim 1, wherein the acceptance value is computed using Q=Σi=1 N BV αu(i)K(x(k),x(i))−Σi=1 N BV αu(i)K(z,x(i)), where z is the selected new observation vector, x(k) is any vector of the selected set of boundary support vectors, x(i) is an ith vector of the selected set of boundary support vectors, αu(i) is an ith row sum value selected from the computed row sum vector, NBV is a number of the selected set of boundary support vectors, and K(x(k),x(i)) and K(z,x(i)) are a Gaussian kernel function. 10. The non-transitory computer-readable medium of claim 1, wherein outputting the selected new observation vector as the outlier observation vector comprises sending a message to a second computing device. 11. The non-transitory computer-readable medium of claim 10, wherein the message indicates that a system fault has occurred or that a system state has shifted. 12. The non-transitory computer-readable medium of claim 1, wherein the incremental vector is computed using
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,
where z is the selected new observation vector, x(i) is an ith vector of the selected set of boundary support vectors, s is a Gaussian bandwidth parameter, and NBV is a number of the selected set of boundary support vectors. 13. The non-transitory computer-readable medium of claim 1, wherein the computer-readable instructions further cause the computing device to repeat (a) to (d) when the maximum value of the computed incremental vector is greater than one minus a second predefined tolerance value. 14. The non-transitory computer-readable medium of claim 13, wherein the second predefined tolerance value is selected between √{square root over (2)}×10−7≤ϵ2≤√{square root over (2)}×10−5. 15. The non-transitory computer-readable medium of claim 13, wherein, when the maximum value of the computed incremental vector is less than or equal to one minus the second predefined tolerance value, the computer-readable instructions further cause the computing device to:
compute an updated inverse Gaussian similarity matrix from the computed inverse Gaussian similarity matrix using the computed incremental vector; compute an updated row sum vector that includes the row sum value computed from each row of the computed, updated inverse Gaussian similarity matrix; and when αu(i)>0, add the selected new observation vector to the set of boundary support vectors, wherein αu(i) is an ith row sum value selected from the computed, updated row sum vector, wherein the ith row sum value is associated with the computed incremental vector. 16. The non-transitory computer-readable medium of claim 15, wherein, before adding the selected new observation vector to the set of boundary support vectors, the computer-readable instructions further cause the computing device to:
compare a number of the selected set of boundary support vectors to a predefined maximum number of support vectors; and when the number of the selected set of boundary support vectors is greater than or equal to the predefined maximum number of support vectors and αu(i)>0, replace a boundary vector of the set of boundary vectors with the selected new observation vector instead of adding the selected new observation vector to the set of boundary support vectors. 17. The non-transitory computer-readable medium of claim 16, wherein the boundary vector is selected from the set of boundary support vectors based on a reduction value in the row sum value for the boundary vector. 18. The non-transitory computer-readable medium of claim 17, wherein the reduction value for the selected boundary vector is computed using Δαu(k)=αu′(k)−αu(k), where k is an index to the for the boundary vector, αu′(k) is the row sum value for the boundary vector from the computed, updated row sum vector, and αu(k) is the row sum value for the boundary vector from the computed row sum vector. 19. The non-transitory computer-readable medium of claim 17, wherein the selected boundary vector has a largest reduction value relative to any other vector of the set of boundary support vectors. 20. The non-transitory computer-readable medium of claim 1, wherein the set of boundary support vectors are selected from the plurality of observation vectors by removing any interior vectors from the plurality of observation vectors. 21. The non-transitory computer-readable medium of claim 20, wherein an interior vector is identified when αu(i)<0, where αu(i) is an ith row sum value selected from the computed row sum vector. 22. The non-transitory computer-readable medium of claim 21, wherein the row sum vector is computed using αu(j)=Σi=1 N BV A−1(i,j), j=1, . . . , NBV, where NBV is a number of the plurality of observation vectors, and A−1(i,j) is the inverse Gaussian similarity matrix. 23. The non-transitory computer-readable medium of claim 21, wherein, when the interior vector is identified, the computer-readable instructions further cause the computing device to:
compute an updated inverse Gaussian similarity matrix from the computed inverse Gaussian similarity matrix based on the removed identified interior vector; compute an updated row sum vector that includes the row sum value computed from each row of the computed, updated inverse Gaussian similarity matrix; compute a second acceptance value for the removed identified interior vector using the selected set of boundary support vectors, the computed, updated row sum vector, and the removed identified interior vector; when the computed second acceptance value is greater than zero, compute a second incremental vector from the computed, updated inverse Gaussian similarity matrix and the removed identified interior vector; compute a second updated inverse Gaussian similarity matrix from the computed, updated inverse Gaussian similarity matrix based on the computed second incremental vector; compute a second updated row sum vector that includes the row sum value computed from each row of the computed, second updated inverse Gaussian similarity matrix; and when αu(i)>0, add the removed identified interior vector to the set of boundary support vectors, wherein αu(i) is an ith row sum value selected from the computed, second updated row sum vector, wherein the ith row sum value is associated with the computed second incremental vector. 24. The non-transitory computer-readable medium of claim 1, wherein the plurality of observation vectors is received by the computing device in a stream of event block objects sent from one or more publisher computing devices to the computing device. 25. The non-transitory computer-readable medium of claim 24, wherein a number of the plurality of observation vectors included in the selected set of boundary support vectors is a predefined number of observation vectors received first by the computing device in the stream of event block objects. 26. The non-transitory computer-readable medium of claim 1, wherein the new observation vector is selected from a stream of event block objects received by the computing device from a publisher computing device. 27. The non-transitory computer-readable medium of claim 1, wherein the selected new observation vector is output by streaming the selected new observation vector to a second computing device that subscribes to receive the outlier observation vector. 28. The non-transitory computer-readable medium of claim 1, wherein the computing device is executing an event stream processing engine that performs the computer-readable instructions, wherein the new observation vector was received from a publisher computing device by injecting the new observation vector into a source window of the event stream processing engine, and the outlier observation vector is output to a second computing device that subscribes to receive the outlier observation vector from the event stream processing engine. 29. A computing device comprising:
a processor; and a non-transitory computer-readable medium operably coupled to the processor, the computer-readable medium having computer-readable instructions stored thereon that, when executed by the processor, cause the computing device to
compute a Gaussian similarity matrix between a plurality of observation vectors, wherein each observation vector of the plurality of observation vectors includes a variable value for each variable of a plurality of variables;
compute an inverse Gaussian similarity matrix from the computed Gaussian similarity matrix;
compute a row sum vector that includes a row sum value computed from each row of the computed inverse Gaussian similarity matrix;
select a set of boundary support vectors from the plurality of observation vectors;
(a) select a new observation vector from an event stream or from an input dataset;
(b) compute an acceptance value for the selected new observation vector using the selected set of boundary support vectors, the computed row sum vector, and the new observation vector;
(c) when the computed acceptance value is greater than zero, compute an incremental vector from the computed inverse Gaussian similarity matrix and the selected new observation vector;
(d) when the computed acceptance value is greater than zero and when a maximum value of the computed incremental vector is less than a first predefined tolerance value, output an indicator that the selected new observation vector is an abnormal observation vector relative to the selected set of boundary support vectors; and
(e) repeat (a) to (d) until the event stream is stopped or a last observation vector is selected from the input dataset in (a). 30. A method of iteratively updating a support vector data description for outlier identification, the method comprising:
computing, by a computing device, a Gaussian similarity matrix between a plurality of observation vectors, wherein each observation vector of the plurality of observation vectors includes a variable value for each variable of a plurality of variables; computing, by the computing device, an inverse Gaussian similarity matrix from the computed Gaussian similarity matrix; computing, by the computing device, a row sum vector that includes a row sum value computed from each row of the computed inverse Gaussian similarity matrix; selecting, by the computing device, a set of boundary support vectors from the plurality of observation vectors; (a) selecting, by the computing device, a new observation vector from an event stream or from an input dataset; (b) computing, by the computing device, an acceptance value for the selected new observation vector using the selected set of boundary support vectors, the computed row sum vector, and the new observation vector; (c) when the computed acceptance value is greater than zero, computing, by the computing device, an incremental vector from the computed inverse Gaussian similarity matrix and the selected new observation vector; (d) when the computed acceptance value is greater than zero and when a maximum value of the computed incremental vector is less than a first predefined tolerance value, outputting, by the computing device, an indicator that the selected new observation vector is an abnormal observation vector relative to the selected set of boundary support vectors; and (e) repeating, by the computing device, (a) to (d) until the event stream is stopped or a last observation vector is selected from the input dataset in (a). | A Gaussian similarity matrix is computed between observation vectors. An inverse Gaussian similarity matrix is computed from the Gaussian similarity matrix. A row sum vector is computed that includes a row sum value computed from each row of the inverse Gaussian similarity matrix. (a) A new observation vector is selected. (b) An acceptance value is computed for the new observation vector using the set of boundary support vectors, the row sum vector, and the new observation vector. (c) (a) and (b) are repeated when the computed acceptance value is less than or equal to zero. (d) An incremental vector is computed from the inverse Gaussian similarity matrix and the new observation vector when the computed acceptance value is greater than zero. (e) the selected new observation vector is output as an outlier observation vector when a maximum value of the incremental vector is less than a first predefined tolerance value.1. A non-transitory computer-readable medium having stored thereon computer-readable instructions that when executed by a computing device cause the computing device to:
compute a Gaussian similarity matrix between a plurality of observation vectors, wherein each observation vector of the plurality of observation vectors includes a variable value for each variable of a plurality of variables; compute an inverse Gaussian similarity matrix from the computed Gaussian similarity matrix; compute a row sum vector that includes a row sum value computed from each row of the computed inverse Gaussian similarity matrix; select a set of boundary support vectors from the plurality of observation vectors; (a) select a new observation vector from an event stream or from an input dataset; (b) compute an acceptance value for the selected new observation vector using the selected set of boundary support vectors, the computed row sum vector, and the new observation vector; (c) when the computed acceptance value is greater than zero, compute an incremental vector from the computed inverse Gaussian similarity matrix and the selected new observation vector; (d) when the computed acceptance value is greater than zero and when a maximum value of the computed incremental vector is less than a first predefined tolerance value, output an indicator that the selected new observation vector is an abnormal observation vector relative to the selected set of boundary support vectors; and (e) repeat (a) to (d) until the event stream is stopped or a last observation vector is selected from the input dataset in (a). 2. The non-transitory computer-readable medium of claim 1, wherein the Gaussian similarity matrix is computed using
A
=
exp
-
x
(
i
)
-
x
(
j
)
2
2
s
2
,
i
=
1
,
…
,
N
BV
and
j
=
1
,
…
,
N
BV
,
where x(i) and x(j) are the plurality of observation vectors, s is a Gaussian bandwidth parameter, and NBV is a number of the plurality of observation vectors. 3. The non-transitory computer-readable medium of claim 2, wherein the number of the plurality of observation vectors is a predefined number to initialize the Gaussian similarity matrix. 4. The non-transitory computer-readable medium of claim 3, wherein the predefined number is a predefined subset of an input dataset. 5. The non-transitory computer-readable medium of claim 2, wherein the inverse Gaussian similarity matrix is computed using A−1=adj(A)/det(A), where adj(A) is an adjugate of the Gaussian similarity matrix and det(A) is a determinant of the Gaussian similarity matrix. 6. The non-transitory computer-readable medium of claim 1, wherein the row sum vector is computed using αu(j)=Σi=1 N BV A−1(i,j), j=1, . . . , NBV, where NBV is a number of the plurality of observation vectors, and A−1(i,j) is the inverse Gaussian similarity matrix. 7. The non-transitory computer-readable medium of claim 6, wherein a Lagrange multiplier for each observation vector is computed using α(k)=αu(k)/∥αu(k)∥1,k=1, . . . , NBV, where ∥αu(k)∥1 is a 1-norm of a kth row sum value. 8. The non-transitory computer-readable medium of claim 1, wherein outputting the selected new observation vector as the outlier observation vector comprises presenting the selected new observation vector on a display. 9. The non-transitory computer-readable medium of claim 1, wherein the acceptance value is computed using Q=Σi=1 N BV αu(i)K(x(k),x(i))−Σi=1 N BV αu(i)K(z,x(i)), where z is the selected new observation vector, x(k) is any vector of the selected set of boundary support vectors, x(i) is an ith vector of the selected set of boundary support vectors, αu(i) is an ith row sum value selected from the computed row sum vector, NBV is a number of the selected set of boundary support vectors, and K(x(k),x(i)) and K(z,x(i)) are a Gaussian kernel function. 10. The non-transitory computer-readable medium of claim 1, wherein outputting the selected new observation vector as the outlier observation vector comprises sending a message to a second computing device. 11. The non-transitory computer-readable medium of claim 10, wherein the message indicates that a system fault has occurred or that a system state has shifted. 12. The non-transitory computer-readable medium of claim 1, wherein the incremental vector is computed using
v
(
i
)
=
exp
-
z
-
x
(
i
)
2
2
s
2
,
i
=
1
,
…
,
N
BV
,
where z is the selected new observation vector, x(i) is an ith vector of the selected set of boundary support vectors, s is a Gaussian bandwidth parameter, and NBV is a number of the selected set of boundary support vectors. 13. The non-transitory computer-readable medium of claim 1, wherein the computer-readable instructions further cause the computing device to repeat (a) to (d) when the maximum value of the computed incremental vector is greater than one minus a second predefined tolerance value. 14. The non-transitory computer-readable medium of claim 13, wherein the second predefined tolerance value is selected between √{square root over (2)}×10−7≤ϵ2≤√{square root over (2)}×10−5. 15. The non-transitory computer-readable medium of claim 13, wherein, when the maximum value of the computed incremental vector is less than or equal to one minus the second predefined tolerance value, the computer-readable instructions further cause the computing device to:
compute an updated inverse Gaussian similarity matrix from the computed inverse Gaussian similarity matrix using the computed incremental vector; compute an updated row sum vector that includes the row sum value computed from each row of the computed, updated inverse Gaussian similarity matrix; and when αu(i)>0, add the selected new observation vector to the set of boundary support vectors, wherein αu(i) is an ith row sum value selected from the computed, updated row sum vector, wherein the ith row sum value is associated with the computed incremental vector. 16. The non-transitory computer-readable medium of claim 15, wherein, before adding the selected new observation vector to the set of boundary support vectors, the computer-readable instructions further cause the computing device to:
compare a number of the selected set of boundary support vectors to a predefined maximum number of support vectors; and when the number of the selected set of boundary support vectors is greater than or equal to the predefined maximum number of support vectors and αu(i)>0, replace a boundary vector of the set of boundary vectors with the selected new observation vector instead of adding the selected new observation vector to the set of boundary support vectors. 17. The non-transitory computer-readable medium of claim 16, wherein the boundary vector is selected from the set of boundary support vectors based on a reduction value in the row sum value for the boundary vector. 18. The non-transitory computer-readable medium of claim 17, wherein the reduction value for the selected boundary vector is computed using Δαu(k)=αu′(k)−αu(k), where k is an index to the for the boundary vector, αu′(k) is the row sum value for the boundary vector from the computed, updated row sum vector, and αu(k) is the row sum value for the boundary vector from the computed row sum vector. 19. The non-transitory computer-readable medium of claim 17, wherein the selected boundary vector has a largest reduction value relative to any other vector of the set of boundary support vectors. 20. The non-transitory computer-readable medium of claim 1, wherein the set of boundary support vectors are selected from the plurality of observation vectors by removing any interior vectors from the plurality of observation vectors. 21. The non-transitory computer-readable medium of claim 20, wherein an interior vector is identified when αu(i)<0, where αu(i) is an ith row sum value selected from the computed row sum vector. 22. The non-transitory computer-readable medium of claim 21, wherein the row sum vector is computed using αu(j)=Σi=1 N BV A−1(i,j), j=1, . . . , NBV, where NBV is a number of the plurality of observation vectors, and A−1(i,j) is the inverse Gaussian similarity matrix. 23. The non-transitory computer-readable medium of claim 21, wherein, when the interior vector is identified, the computer-readable instructions further cause the computing device to:
compute an updated inverse Gaussian similarity matrix from the computed inverse Gaussian similarity matrix based on the removed identified interior vector; compute an updated row sum vector that includes the row sum value computed from each row of the computed, updated inverse Gaussian similarity matrix; compute a second acceptance value for the removed identified interior vector using the selected set of boundary support vectors, the computed, updated row sum vector, and the removed identified interior vector; when the computed second acceptance value is greater than zero, compute a second incremental vector from the computed, updated inverse Gaussian similarity matrix and the removed identified interior vector; compute a second updated inverse Gaussian similarity matrix from the computed, updated inverse Gaussian similarity matrix based on the computed second incremental vector; compute a second updated row sum vector that includes the row sum value computed from each row of the computed, second updated inverse Gaussian similarity matrix; and when αu(i)>0, add the removed identified interior vector to the set of boundary support vectors, wherein αu(i) is an ith row sum value selected from the computed, second updated row sum vector, wherein the ith row sum value is associated with the computed second incremental vector. 24. The non-transitory computer-readable medium of claim 1, wherein the plurality of observation vectors is received by the computing device in a stream of event block objects sent from one or more publisher computing devices to the computing device. 25. The non-transitory computer-readable medium of claim 24, wherein a number of the plurality of observation vectors included in the selected set of boundary support vectors is a predefined number of observation vectors received first by the computing device in the stream of event block objects. 26. The non-transitory computer-readable medium of claim 1, wherein the new observation vector is selected from a stream of event block objects received by the computing device from a publisher computing device. 27. The non-transitory computer-readable medium of claim 1, wherein the selected new observation vector is output by streaming the selected new observation vector to a second computing device that subscribes to receive the outlier observation vector. 28. The non-transitory computer-readable medium of claim 1, wherein the computing device is executing an event stream processing engine that performs the computer-readable instructions, wherein the new observation vector was received from a publisher computing device by injecting the new observation vector into a source window of the event stream processing engine, and the outlier observation vector is output to a second computing device that subscribes to receive the outlier observation vector from the event stream processing engine. 29. A computing device comprising:
a processor; and a non-transitory computer-readable medium operably coupled to the processor, the computer-readable medium having computer-readable instructions stored thereon that, when executed by the processor, cause the computing device to
compute a Gaussian similarity matrix between a plurality of observation vectors, wherein each observation vector of the plurality of observation vectors includes a variable value for each variable of a plurality of variables;
compute an inverse Gaussian similarity matrix from the computed Gaussian similarity matrix;
compute a row sum vector that includes a row sum value computed from each row of the computed inverse Gaussian similarity matrix;
select a set of boundary support vectors from the plurality of observation vectors;
(a) select a new observation vector from an event stream or from an input dataset;
(b) compute an acceptance value for the selected new observation vector using the selected set of boundary support vectors, the computed row sum vector, and the new observation vector;
(c) when the computed acceptance value is greater than zero, compute an incremental vector from the computed inverse Gaussian similarity matrix and the selected new observation vector;
(d) when the computed acceptance value is greater than zero and when a maximum value of the computed incremental vector is less than a first predefined tolerance value, output an indicator that the selected new observation vector is an abnormal observation vector relative to the selected set of boundary support vectors; and
(e) repeat (a) to (d) until the event stream is stopped or a last observation vector is selected from the input dataset in (a). 30. A method of iteratively updating a support vector data description for outlier identification, the method comprising:
computing, by a computing device, a Gaussian similarity matrix between a plurality of observation vectors, wherein each observation vector of the plurality of observation vectors includes a variable value for each variable of a plurality of variables; computing, by the computing device, an inverse Gaussian similarity matrix from the computed Gaussian similarity matrix; computing, by the computing device, a row sum vector that includes a row sum value computed from each row of the computed inverse Gaussian similarity matrix; selecting, by the computing device, a set of boundary support vectors from the plurality of observation vectors; (a) selecting, by the computing device, a new observation vector from an event stream or from an input dataset; (b) computing, by the computing device, an acceptance value for the selected new observation vector using the selected set of boundary support vectors, the computed row sum vector, and the new observation vector; (c) when the computed acceptance value is greater than zero, computing, by the computing device, an incremental vector from the computed inverse Gaussian similarity matrix and the selected new observation vector; (d) when the computed acceptance value is greater than zero and when a maximum value of the computed incremental vector is less than a first predefined tolerance value, outputting, by the computing device, an indicator that the selected new observation vector is an abnormal observation vector relative to the selected set of boundary support vectors; and (e) repeating, by the computing device, (a) to (d) until the event stream is stopped or a last observation vector is selected from the input dataset in (a). | 2,100 |
6,032 | 6,032 | 15,439,024 | 2,184 | A data storage array has a backplane at the base of an enclosure. A plurality of data storage drives are coupled to connectors of the backplane. A hot-swappable protocol expander module is coupled between the drives and the backplane through a top of the enclosure or to the backplane through a side of the enclosure. | 1. A data storage array, comprising:
an enclosure; a backplane at the base of the enclosure, the backplane comprising a plurality of connectors; a plurality of data storage drives coupled to the connectors of the backplane, a major surface of the data storage drives normal to the backplane; and a protocol expander module coupled to the backplane between at least one of the data storage drives and the backplane, the protocol expander module hot-swappable from the backplane through a top of the enclosure. 2. The data storage array of claim 1, wherein the data storage drives are slidably removable via the top of the enclosure, and wherein the protocol expander module is removable by first removing one or more of the storage drives that cover the protocol expander module and then lifting the expander module though the top of the enclosure. 3. The data storage array of claim 1, wherein the backplane comprises a void to facilitate at least part of the protocol expander module that extends toward a bottom cover of the enclosure. 4. The data storage array of claim 1, wherein the protocol expander module comprises a body portion and at least two arms extending from the body portion, each of the at least two arms located between a pair of adjacent connectors of the backplane. 5. The data storage array of claim 4, wherein ends of the at least two arms comprise tool-less mechanical locking elements that interface with the backplane. 6. The data storage array of claim 4, wherein the at least two arms comprise four arms each located between respective pairs of the adjacent connectors, the four arms including two outer arms comprising mechanical locking elements that interface with the backplane and two inner arms that include. 7. The data storage array of claim 4, wherein the body comprises an electrical connector that interfaces with a corresponding connector on the backplane. 8. The data storage array of claim 1, wherein the protocol expander module provides a point-to-point protocol that couples the data storage drives to a controller. 9. The data storage array of claim 1, wherein the protocol expander module is capable of providing at least two communications protocols for the data storage drives, the at least two communications protocols comprising any two of Small Computer System Interface (SCSI), Serial Attached SCSI, Serial AT Attachment, Peripheral Component Interconnect (PCI), PCI Express (PCIe), Fibre Channel, and Ethernet. 10. An data storage array, comprising:
an enclosure; a backplane at the base of the enclosure; a plurality of connectors on a top surface of the backplane, the connectors configured to couple to an array of data storage drives; and a protocol expander module slidably removably via an opening in a side of the enclosure, the side of the enclosure being covered by a corresponding side of a rack in a rack-mounted configuration of the enclosure, the protocol expander module interfacing via a connector to a lower surface of the backplane that is opposed to the top surface. 11. The data storage array of claim 10, wherein the protocol expander module comprises a heat sink, and wherein the backplane comprises a cutout that provides clearance for the heat sink. 12. The data storage array of claim 10, wherein the protocol expander module comprises an upper circuit board and lower circuit board, the lower circuit board interfacing with the backplane via the connector. 13. The data storage array of claim 12, wherein the upper circuit board interfaces with the backplane via a second connector at an edge of a cutout of the backplane. 14. The data storage array of claim 12, wherein the upper circuit board is co-planar with the backplane when the protocol expander module is installed. 15. The data storage array of claim 10, wherein the protocol expander module provides a point-to-point protocol that couples the data storage drives to a controller. 16. The data storage array of claim 10, wherein the protocol expander module is capable of providing at least two communications protocols for the data storage drives, the at least two communications protocols comprising any two of Small Computer System Interface (SCSI), Serial Attached SCSI, Serial AT Attachment, Peripheral Component Interconnect (PCI), PCI Express (PCIe), Fibre Channel, and Ethernet. 17. A method comprising:
while power is applied to a data storage array, removing at least one data storage drive from a backplane of the data storage array, the data storage drive being removed through a top of the data storage array; and after removing the drive and with the power applied, removing a protocol expander module that is coupled to the backplane between the at least one data storage drive and the backplane, the protocol expander module being hot-swappable from the backplane through the top of the data storage array. 18. The method of claim 17, further comprising, with the power applied:
installing one of the protocol expander module or a replacement protocol expander module to the backplane through the top of the data storage array; and installing the at least one data storage drive to the backplane through the top of the data storage array. 19. The method of claim 18, wherein the protocol module comprises a body portion and at least two arms extending from the body portion, each of the at least two arms located between a pair of adjacent connectors of the backplane, ends of the at least two arms comprising tool-less mechanical locking elements that interface with the backplane, and wherein removing the protocol expander module comprises unlocking the mechanical locking element. 20. The method of claim 18, wherein the protocol expander module provides a point-to-point protocol that couples one or more drives of the data storage array to a controller. | A data storage array has a backplane at the base of an enclosure. A plurality of data storage drives are coupled to connectors of the backplane. A hot-swappable protocol expander module is coupled between the drives and the backplane through a top of the enclosure or to the backplane through a side of the enclosure.1. A data storage array, comprising:
an enclosure; a backplane at the base of the enclosure, the backplane comprising a plurality of connectors; a plurality of data storage drives coupled to the connectors of the backplane, a major surface of the data storage drives normal to the backplane; and a protocol expander module coupled to the backplane between at least one of the data storage drives and the backplane, the protocol expander module hot-swappable from the backplane through a top of the enclosure. 2. The data storage array of claim 1, wherein the data storage drives are slidably removable via the top of the enclosure, and wherein the protocol expander module is removable by first removing one or more of the storage drives that cover the protocol expander module and then lifting the expander module though the top of the enclosure. 3. The data storage array of claim 1, wherein the backplane comprises a void to facilitate at least part of the protocol expander module that extends toward a bottom cover of the enclosure. 4. The data storage array of claim 1, wherein the protocol expander module comprises a body portion and at least two arms extending from the body portion, each of the at least two arms located between a pair of adjacent connectors of the backplane. 5. The data storage array of claim 4, wherein ends of the at least two arms comprise tool-less mechanical locking elements that interface with the backplane. 6. The data storage array of claim 4, wherein the at least two arms comprise four arms each located between respective pairs of the adjacent connectors, the four arms including two outer arms comprising mechanical locking elements that interface with the backplane and two inner arms that include. 7. The data storage array of claim 4, wherein the body comprises an electrical connector that interfaces with a corresponding connector on the backplane. 8. The data storage array of claim 1, wherein the protocol expander module provides a point-to-point protocol that couples the data storage drives to a controller. 9. The data storage array of claim 1, wherein the protocol expander module is capable of providing at least two communications protocols for the data storage drives, the at least two communications protocols comprising any two of Small Computer System Interface (SCSI), Serial Attached SCSI, Serial AT Attachment, Peripheral Component Interconnect (PCI), PCI Express (PCIe), Fibre Channel, and Ethernet. 10. An data storage array, comprising:
an enclosure; a backplane at the base of the enclosure; a plurality of connectors on a top surface of the backplane, the connectors configured to couple to an array of data storage drives; and a protocol expander module slidably removably via an opening in a side of the enclosure, the side of the enclosure being covered by a corresponding side of a rack in a rack-mounted configuration of the enclosure, the protocol expander module interfacing via a connector to a lower surface of the backplane that is opposed to the top surface. 11. The data storage array of claim 10, wherein the protocol expander module comprises a heat sink, and wherein the backplane comprises a cutout that provides clearance for the heat sink. 12. The data storage array of claim 10, wherein the protocol expander module comprises an upper circuit board and lower circuit board, the lower circuit board interfacing with the backplane via the connector. 13. The data storage array of claim 12, wherein the upper circuit board interfaces with the backplane via a second connector at an edge of a cutout of the backplane. 14. The data storage array of claim 12, wherein the upper circuit board is co-planar with the backplane when the protocol expander module is installed. 15. The data storage array of claim 10, wherein the protocol expander module provides a point-to-point protocol that couples the data storage drives to a controller. 16. The data storage array of claim 10, wherein the protocol expander module is capable of providing at least two communications protocols for the data storage drives, the at least two communications protocols comprising any two of Small Computer System Interface (SCSI), Serial Attached SCSI, Serial AT Attachment, Peripheral Component Interconnect (PCI), PCI Express (PCIe), Fibre Channel, and Ethernet. 17. A method comprising:
while power is applied to a data storage array, removing at least one data storage drive from a backplane of the data storage array, the data storage drive being removed through a top of the data storage array; and after removing the drive and with the power applied, removing a protocol expander module that is coupled to the backplane between the at least one data storage drive and the backplane, the protocol expander module being hot-swappable from the backplane through the top of the data storage array. 18. The method of claim 17, further comprising, with the power applied:
installing one of the protocol expander module or a replacement protocol expander module to the backplane through the top of the data storage array; and installing the at least one data storage drive to the backplane through the top of the data storage array. 19. The method of claim 18, wherein the protocol module comprises a body portion and at least two arms extending from the body portion, each of the at least two arms located between a pair of adjacent connectors of the backplane, ends of the at least two arms comprising tool-less mechanical locking elements that interface with the backplane, and wherein removing the protocol expander module comprises unlocking the mechanical locking element. 20. The method of claim 18, wherein the protocol expander module provides a point-to-point protocol that couples one or more drives of the data storage array to a controller. | 2,100 |
6,033 | 6,033 | 15,835,076 | 2,173 | Generating a geographical map usable for initiating discovery of network subnets within a computer network can include receiving a hierarchy of geo-location identifiers corresponding to levels of geographical abstraction and network subnets having associated geo-location identifiers included in the hierarchy. Geo-location identifiers of the network subnets can be mapped to corresponding first levels according to the hierarchy. A graphical user interface can be generated to include a geographical map and user interface elements such that a selection of a geo-location identifier can be received using a user interface element. A set of network subnets associated with the selected geo-location identifier and at least one agent software instance usable for performing discovery against the set of network subnets can be determined to initiate discovery of the set. | 1. A graphical user interface (GUI) for an information technology operations management (ITOM) tool for managing a computer network, the GUI comprising:
a geographical map of a portion of Earth, the geographical map having a geo-location indicator that indicates a geographic location of at least one discovered component of the computer network. 2. The GUI, as set forth in claim 1, wherein the geographical map comprises a map of a continent, a country, a state, or a city, or any combination thereof. 3. The GUI, as set forth in claim 1, wherein the at least one discovered component of the computer network comprises a subnet of the computer network, hardware associated with the computer network, or software associated with the computer network, or any combination thereof. 4. The GUI, as set forth in claim 1, wherein the geo-location indicator comprises an icon positioned at the geographic location of the at least one discovered component of the computer network. 5. The GUI, as set forth in claim 4, wherein the icon is selectable by a user of the GUI, and wherein selection of the icon initiates discovery of components of the computer network associated with the geographic location. 6. The GUI, as set forth in claim 4, wherein the icon is selectable by a user of the GUI, and wherein selection of the icon initiates a test of credentials for the at least one discovered component of the computer network. 7. The GUI, as set forth in claim 4, wherein the icon is selectable by a user of the GUI, and wherein selection of the icon initiates retrieval of configuration elements (CIs) for the at least one discovered component of the computer network. 8. The GUI, as set forth in claim 1, wherein the geographical map comprises a listing of network subnets associated with components of the computer network affected by a power outage at the geographic location. 9. The GUI, as set forth in claim 1, wherein the geographical map comprises a listing of network subnets associated with components of the computer network involved in an update at the geographic location. 10. The GUI, as set forth in claim 1, wherein the geographical map comprises a listing of network subnets associated with components of the computer network involved in an incident reported by a customer at the geographic location. 11. The GUI, as set forth in claim 1, wherein the geographical map comprises a plurality of hierarchical geographical maps depicting different levels of geographical abstraction. 12. The GUI, as set forth in claim 11, wherein the plurality of hierarchical geographical maps depicting different levels of geographical abstraction comprise a first level of geographical abstraction corresponding to a country, a second level of geographical abstraction corresponding to a state or province, and a third level of geographical abstraction corresponding to a city or town. 13. The GUI, as set forth in claim 12, wherein each of the plurality of hierarchical geographical maps comprise a respective geo-location indicator that indicates a geographic location of at least one respective component of the computer network. 14. The GUI, as set forth in claim 11, wherein the plurality of hierarchical geographical maps depicting different levels of geographical abstraction each comprise one or more visual elements that are selectable by a user to switch from one of the plurality of hierarchical geographical maps to another. 15. A tangible computer-readable medium comprising:
instructions stored on the medium that, when executed by a processor, cause an electronic display to display a graphical user interface (GUI) for an information technology operations management (ITOM) tool for managing a computer network, the GUI comprising a geographical map of a portion of Earth, the geographical map having a geo-location indicator that indicates a geographic location of at least one discovered component of the computer network. 16. The medium, as set forth in claim 15, wherein the geo-location indicator comprises an icon positioned at the geographic location of the at least one discovered component of the computer network. 17. The medium, as set forth in claim 16, wherein the icon is selectable by a user of the GUI, and wherein selection of the icon initiates discovery of components of the computer network associated with the geographic location. 18. A computer comprising:
a processor; a display operably coupled to the processor; a memory operably coupled to the processor, the memory storing instructions that, when executed by the processor, cause the display to display a graphical user interface (GUI) for an information technology operations management (ITOM) tool for managing a computer network, the GUI comprising a geographical map of a portion of Earth, the geographical map having a geo-location indicator that indicates a geographic location of at least one discovered component of the computer network. 19. The computer, as set forth in claim 18, wherein the geographical map comprises a plurality of hierarchical geographical maps depicting different levels of geographical abstraction. 20. The computer, as set forth in claim 19, wherein the plurality of hierarchical geographical maps depicting different levels of geographical abstraction comprise a first level of geographical abstraction corresponding to a country, a second level of geographical abstraction corresponding to a state or province, and a third level of geographical abstraction corresponding to a city or town. | Generating a geographical map usable for initiating discovery of network subnets within a computer network can include receiving a hierarchy of geo-location identifiers corresponding to levels of geographical abstraction and network subnets having associated geo-location identifiers included in the hierarchy. Geo-location identifiers of the network subnets can be mapped to corresponding first levels according to the hierarchy. A graphical user interface can be generated to include a geographical map and user interface elements such that a selection of a geo-location identifier can be received using a user interface element. A set of network subnets associated with the selected geo-location identifier and at least one agent software instance usable for performing discovery against the set of network subnets can be determined to initiate discovery of the set.1. A graphical user interface (GUI) for an information technology operations management (ITOM) tool for managing a computer network, the GUI comprising:
a geographical map of a portion of Earth, the geographical map having a geo-location indicator that indicates a geographic location of at least one discovered component of the computer network. 2. The GUI, as set forth in claim 1, wherein the geographical map comprises a map of a continent, a country, a state, or a city, or any combination thereof. 3. The GUI, as set forth in claim 1, wherein the at least one discovered component of the computer network comprises a subnet of the computer network, hardware associated with the computer network, or software associated with the computer network, or any combination thereof. 4. The GUI, as set forth in claim 1, wherein the geo-location indicator comprises an icon positioned at the geographic location of the at least one discovered component of the computer network. 5. The GUI, as set forth in claim 4, wherein the icon is selectable by a user of the GUI, and wherein selection of the icon initiates discovery of components of the computer network associated with the geographic location. 6. The GUI, as set forth in claim 4, wherein the icon is selectable by a user of the GUI, and wherein selection of the icon initiates a test of credentials for the at least one discovered component of the computer network. 7. The GUI, as set forth in claim 4, wherein the icon is selectable by a user of the GUI, and wherein selection of the icon initiates retrieval of configuration elements (CIs) for the at least one discovered component of the computer network. 8. The GUI, as set forth in claim 1, wherein the geographical map comprises a listing of network subnets associated with components of the computer network affected by a power outage at the geographic location. 9. The GUI, as set forth in claim 1, wherein the geographical map comprises a listing of network subnets associated with components of the computer network involved in an update at the geographic location. 10. The GUI, as set forth in claim 1, wherein the geographical map comprises a listing of network subnets associated with components of the computer network involved in an incident reported by a customer at the geographic location. 11. The GUI, as set forth in claim 1, wherein the geographical map comprises a plurality of hierarchical geographical maps depicting different levels of geographical abstraction. 12. The GUI, as set forth in claim 11, wherein the plurality of hierarchical geographical maps depicting different levels of geographical abstraction comprise a first level of geographical abstraction corresponding to a country, a second level of geographical abstraction corresponding to a state or province, and a third level of geographical abstraction corresponding to a city or town. 13. The GUI, as set forth in claim 12, wherein each of the plurality of hierarchical geographical maps comprise a respective geo-location indicator that indicates a geographic location of at least one respective component of the computer network. 14. The GUI, as set forth in claim 11, wherein the plurality of hierarchical geographical maps depicting different levels of geographical abstraction each comprise one or more visual elements that are selectable by a user to switch from one of the plurality of hierarchical geographical maps to another. 15. A tangible computer-readable medium comprising:
instructions stored on the medium that, when executed by a processor, cause an electronic display to display a graphical user interface (GUI) for an information technology operations management (ITOM) tool for managing a computer network, the GUI comprising a geographical map of a portion of Earth, the geographical map having a geo-location indicator that indicates a geographic location of at least one discovered component of the computer network. 16. The medium, as set forth in claim 15, wherein the geo-location indicator comprises an icon positioned at the geographic location of the at least one discovered component of the computer network. 17. The medium, as set forth in claim 16, wherein the icon is selectable by a user of the GUI, and wherein selection of the icon initiates discovery of components of the computer network associated with the geographic location. 18. A computer comprising:
a processor; a display operably coupled to the processor; a memory operably coupled to the processor, the memory storing instructions that, when executed by the processor, cause the display to display a graphical user interface (GUI) for an information technology operations management (ITOM) tool for managing a computer network, the GUI comprising a geographical map of a portion of Earth, the geographical map having a geo-location indicator that indicates a geographic location of at least one discovered component of the computer network. 19. The computer, as set forth in claim 18, wherein the geographical map comprises a plurality of hierarchical geographical maps depicting different levels of geographical abstraction. 20. The computer, as set forth in claim 19, wherein the plurality of hierarchical geographical maps depicting different levels of geographical abstraction comprise a first level of geographical abstraction corresponding to a country, a second level of geographical abstraction corresponding to a state or province, and a third level of geographical abstraction corresponding to a city or town. | 2,100 |
6,034 | 6,034 | 15,582,669 | 2,152 | Embodiments are directed towards real time display of event records and extracted values based on at least one extraction rule, such as a regular expression. A user interface may be employed to enable a user to have an extraction rule automatically generate and/or to manually enter an extraction rule. The user may be enabled to manually edit a previously provided extraction rule, which may result in real time display of updated extracted values. The extraction rule may be utilized to extract values from each of a plurality of records, including event records of unstructured machine data. Statistics may be determined for each unique extracted value, and may be displayed to the user in real time. The user interface may also enable the user to select at least one unique extracted value to display those event records that include an extracted value that matches the selected value. | 1. A computer-implemented method, comprising:
organizing received machine data into a plurality of time-stamped events, wherein the machine data included in each event in the plurality of events retains its original format; determining one or more unique field values for a particular field in the plurality of events; determining a statistic associated with each of the one or more unique field values in the sub set; causing display of a subset of the one or more unique field values; causing display of information related to the statistic associated with the displayed unique field value among the subset of the one or more unique field values; wherein the method is performed by one or more computing devices. 2. The method of claim 1, further comprising:
receiving input corresponding to a selection of a particular unique field value among the subset of the one or more unique field values that have been displayed; based on receiving the selection, determining a second set of events of the plurality of time-stamped events such that each event of the second set of events includes the selected particular unique field value in the particular field; and causing display of the second set of events and their corresponding time stamps. 3. The method of claim 1, wherein the plurality of time-stamped events is a sample subset of a larger dataset of events. 4. The method of claim 1, wherein the statistic includes a percentage of the set of events having the unique field value in the particular field. 5. The method of claim 1, wherein the statistic includes a total number of times the unique field value occurs in the particular field in the set of events. 6. The method of claim 1, wherein the statistic includes a percent of a number of times the unique field value occurs in the particular field in the set of events compared to a total number of field values in the particular field in the set of events. 7. The method of claim 1, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule. 8. The method of claim 1, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule; wherein the extraction rule is a regular expression. 9. The method of claim 1, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule; wherein the extraction rule is automatically generated based on a user interaction with a graphical user interface. 10. The method of claim 1, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule; wherein the extraction rule is selected by a user via a graphical user interface. 11. An apparatus, comprising:
a machine data organizer, implemented at least partially in hardware, that organizes received machine data into a plurality of time-stamped events, wherein the machine data included in each event in the plurality of events retains its original format; a field value extractor, implemented at least partially in hardware, that determines one or more unique field values for a particular field in the plurality of events; a statistical processor, implemented at least partially in hardware, that determines a statistic associated with each of the one or more unique field values in the subset; wherein the display formatter causes display of a subset of the one or more unique field values; wherein the display formatter causes display of information related to the statistic associated with the displayed unique field value among the subset of the one or more unique field values. 12. The apparatus of claim 11, further comprising:
a user input receiver, implemented at least partially in hardware, that receives input corresponding to a selection of a particular unique field value among the subset of the one or more unique field values that have been displayed; an event selector, implemented at least partially in hardware, that, based on receiving the selection, determines a second set of events of the plurality of time-stamped events such that each event of the second set of events includes the selected particular unique field value in the particular field; and wherein the display formatter causes display of the second set of events and their corresponding time stamps. 13. The apparatus of claim 11, wherein the plurality of time-stamped events is a sample subset of a larger dataset of events. 14. The apparatus of claim 11, wherein the statistic includes a percentage of the set of events having the unique field value in the particular field. 15. The apparatus of claim 11, wherein the statistic includes a total number of times the unique field value occurs in the particular field in the set of events. 16. The apparatus of claim 11, wherein the statistic includes a percent of a number of times the unique field value occurs in the particular field in the set of events compared to a total number of field values in the particular field in the set of events. 17. The apparatus of claim 11, wherein the field extractor, to determine the one or more unique field values, extracts the one or more unique field values from the particular field in the plurality of events using an extraction rule. 18. The apparatus of claim 11, wherein the field extractor, to determine the one or more unique field values, extracts the one or more unique field values from the particular field in the plurality of events using an extraction rule, wherein the extraction rule is a regular expression. 19. The apparatus of claim 11, wherein the field extractor, to determine the one or more unique field values, extracts the one or more unique field values from the particular field in the plurality of events using an extraction rule, wherein the extraction rule is automatically generated based on a user interaction with a graphical user interface. 20. The apparatus of claim 11, wherein the field extractor, to determine the one or more unique field values, extracts the one or more unique field values from the particular field in the plurality of events using an extraction rule, wherein the extraction rule is selected by a user via a graphical user interface. 21. One or more non-transitory computer-readable storage media, storing one or more sequences of instructions, which when executed by one or more processors cause performance of:
organizing received machine data into a plurality of time-stamped events, wherein the machine data included in each event in the plurality of events retains its original format; determining one or more unique field values for a particular field in the plurality of events; determining a statistic associated with each of the one or more unique field values in the sub set; causing display of a subset of the one or more unique field values; causing display of information related to the statistic associated with the displayed unique field value among the subset of the one or more unique field values. 22. The one or more non-transitory computer-readable storage media of claim 21, wherein the one or more sequences of instructions, which when executed by the one or more processors cause further performance of:
receiving input corresponding to a selection of a particular unique field value among the subset of the one or more unique field values that have been displayed; based on receiving the selection, determining a second set of events of the plurality of time-stamped events such that each event of the second set of events includes the selected particular unique field value in the particular field; and causing display of the second set of events and their corresponding time stamps. 23. The one or more non-transitory computer-readable storage media of claim 21, wherein the plurality of time-stamped events is a sample subset of a larger dataset of events. 24. The one or more non-transitory computer-readable storage media of claim 21, wherein the statistic includes a percentage of the set of events having the unique field value in the particular field. 25. The one or more non-transitory computer-readable storage media of claim 21, wherein the statistic includes a total number of times the unique field value occurs in the particular field in the set of events. 26. The one or more non-transitory computer-readable storage media of claim 21, wherein the statistic includes a percent of a number of times the unique field value occurs in the particular field in the set of events compared to a total number of field values in the particular field in the set of events. 27. The one or more non-transitory computer-readable storage media of claim 21, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule. 28. The one or more non-transitory computer-readable storage media of claim 21, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule, wherein the extraction rule is a regular expression. 29. The one or more non-transitory computer-readable storage media of claim 21, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule, wherein the extraction rule is automatically generated based on a user interaction with a graphical user interface. 30. The one or more non-transitory computer-readable storage media of claim 21, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule; wherein the extraction rule is selected by a user via a graphical user interface. | Embodiments are directed towards real time display of event records and extracted values based on at least one extraction rule, such as a regular expression. A user interface may be employed to enable a user to have an extraction rule automatically generate and/or to manually enter an extraction rule. The user may be enabled to manually edit a previously provided extraction rule, which may result in real time display of updated extracted values. The extraction rule may be utilized to extract values from each of a plurality of records, including event records of unstructured machine data. Statistics may be determined for each unique extracted value, and may be displayed to the user in real time. The user interface may also enable the user to select at least one unique extracted value to display those event records that include an extracted value that matches the selected value.1. A computer-implemented method, comprising:
organizing received machine data into a plurality of time-stamped events, wherein the machine data included in each event in the plurality of events retains its original format; determining one or more unique field values for a particular field in the plurality of events; determining a statistic associated with each of the one or more unique field values in the sub set; causing display of a subset of the one or more unique field values; causing display of information related to the statistic associated with the displayed unique field value among the subset of the one or more unique field values; wherein the method is performed by one or more computing devices. 2. The method of claim 1, further comprising:
receiving input corresponding to a selection of a particular unique field value among the subset of the one or more unique field values that have been displayed; based on receiving the selection, determining a second set of events of the plurality of time-stamped events such that each event of the second set of events includes the selected particular unique field value in the particular field; and causing display of the second set of events and their corresponding time stamps. 3. The method of claim 1, wherein the plurality of time-stamped events is a sample subset of a larger dataset of events. 4. The method of claim 1, wherein the statistic includes a percentage of the set of events having the unique field value in the particular field. 5. The method of claim 1, wherein the statistic includes a total number of times the unique field value occurs in the particular field in the set of events. 6. The method of claim 1, wherein the statistic includes a percent of a number of times the unique field value occurs in the particular field in the set of events compared to a total number of field values in the particular field in the set of events. 7. The method of claim 1, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule. 8. The method of claim 1, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule; wherein the extraction rule is a regular expression. 9. The method of claim 1, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule; wherein the extraction rule is automatically generated based on a user interaction with a graphical user interface. 10. The method of claim 1, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule; wherein the extraction rule is selected by a user via a graphical user interface. 11. An apparatus, comprising:
a machine data organizer, implemented at least partially in hardware, that organizes received machine data into a plurality of time-stamped events, wherein the machine data included in each event in the plurality of events retains its original format; a field value extractor, implemented at least partially in hardware, that determines one or more unique field values for a particular field in the plurality of events; a statistical processor, implemented at least partially in hardware, that determines a statistic associated with each of the one or more unique field values in the subset; wherein the display formatter causes display of a subset of the one or more unique field values; wherein the display formatter causes display of information related to the statistic associated with the displayed unique field value among the subset of the one or more unique field values. 12. The apparatus of claim 11, further comprising:
a user input receiver, implemented at least partially in hardware, that receives input corresponding to a selection of a particular unique field value among the subset of the one or more unique field values that have been displayed; an event selector, implemented at least partially in hardware, that, based on receiving the selection, determines a second set of events of the plurality of time-stamped events such that each event of the second set of events includes the selected particular unique field value in the particular field; and wherein the display formatter causes display of the second set of events and their corresponding time stamps. 13. The apparatus of claim 11, wherein the plurality of time-stamped events is a sample subset of a larger dataset of events. 14. The apparatus of claim 11, wherein the statistic includes a percentage of the set of events having the unique field value in the particular field. 15. The apparatus of claim 11, wherein the statistic includes a total number of times the unique field value occurs in the particular field in the set of events. 16. The apparatus of claim 11, wherein the statistic includes a percent of a number of times the unique field value occurs in the particular field in the set of events compared to a total number of field values in the particular field in the set of events. 17. The apparatus of claim 11, wherein the field extractor, to determine the one or more unique field values, extracts the one or more unique field values from the particular field in the plurality of events using an extraction rule. 18. The apparatus of claim 11, wherein the field extractor, to determine the one or more unique field values, extracts the one or more unique field values from the particular field in the plurality of events using an extraction rule, wherein the extraction rule is a regular expression. 19. The apparatus of claim 11, wherein the field extractor, to determine the one or more unique field values, extracts the one or more unique field values from the particular field in the plurality of events using an extraction rule, wherein the extraction rule is automatically generated based on a user interaction with a graphical user interface. 20. The apparatus of claim 11, wherein the field extractor, to determine the one or more unique field values, extracts the one or more unique field values from the particular field in the plurality of events using an extraction rule, wherein the extraction rule is selected by a user via a graphical user interface. 21. One or more non-transitory computer-readable storage media, storing one or more sequences of instructions, which when executed by one or more processors cause performance of:
organizing received machine data into a plurality of time-stamped events, wherein the machine data included in each event in the plurality of events retains its original format; determining one or more unique field values for a particular field in the plurality of events; determining a statistic associated with each of the one or more unique field values in the sub set; causing display of a subset of the one or more unique field values; causing display of information related to the statistic associated with the displayed unique field value among the subset of the one or more unique field values. 22. The one or more non-transitory computer-readable storage media of claim 21, wherein the one or more sequences of instructions, which when executed by the one or more processors cause further performance of:
receiving input corresponding to a selection of a particular unique field value among the subset of the one or more unique field values that have been displayed; based on receiving the selection, determining a second set of events of the plurality of time-stamped events such that each event of the second set of events includes the selected particular unique field value in the particular field; and causing display of the second set of events and their corresponding time stamps. 23. The one or more non-transitory computer-readable storage media of claim 21, wherein the plurality of time-stamped events is a sample subset of a larger dataset of events. 24. The one or more non-transitory computer-readable storage media of claim 21, wherein the statistic includes a percentage of the set of events having the unique field value in the particular field. 25. The one or more non-transitory computer-readable storage media of claim 21, wherein the statistic includes a total number of times the unique field value occurs in the particular field in the set of events. 26. The one or more non-transitory computer-readable storage media of claim 21, wherein the statistic includes a percent of a number of times the unique field value occurs in the particular field in the set of events compared to a total number of field values in the particular field in the set of events. 27. The one or more non-transitory computer-readable storage media of claim 21, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule. 28. The one or more non-transitory computer-readable storage media of claim 21, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule, wherein the extraction rule is a regular expression. 29. The one or more non-transitory computer-readable storage media of claim 21, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule, wherein the extraction rule is automatically generated based on a user interaction with a graphical user interface. 30. The one or more non-transitory computer-readable storage media of claim 21, wherein determining one or more unique field values for the particular field in the plurality of events further comprises:
extracting the one or more unique field values from the particular field in the plurality of events using an extraction rule; wherein the extraction rule is selected by a user via a graphical user interface. | 2,100 |
6,035 | 6,035 | 14,361,132 | 2,169 | Techniques for parallel frequent sequential pattern detection are provided. A sequence database is split into separate datasets and each node is given a specific dataset to resolve specific frequent items occurring in its specific dataset based on counts. Then, each node groups its item frequent items into “n” (varying) length sequences representing sequential patterns present in the original sequence database. The nodes process in parallel with one another and collectively produce a complete set of the sequential patterns defined in the original sequence database. | 1. A method implemented and programmed within a non-transitory computer-readable storage medium and processed by machine, the machine configured to execute the method, comprising:
(a) obtaining, at the machine, a subsequence for each sequence in a sequence database and group the subsequence with a first item; (b) redistributing, at the machine, the subsequences to nodes of a parallel processing networking by a prefix value; (c) counting, at each node and in parallel, a specific prefix with a predefined length and maintaining at each node a high frequency prefix and its postfix; (d) generating, at each node and in parallel, new prefixes that combine the specific prefix and specific subsequences of its postfix; (e) iterating, at each node and in parallel, (c) and (d) until no new prefixes are generated or until a given prefix length exceeds a specified value; and (f) outputting, by the machine, all the prefixes. 2. The method of claim 1, wherein obtaining further includes recognizing the first item as a first prefix. 3. The method of claim 1, wherein redistributing further includes redistributing each subsequence based on its prefix value. 4. The method of claim 1, wherein counting further includes having each node filter out infrequent items. 5. The method of claim 1, wherein counting further includes keeping track of counts on each node for each frequent item found. 6. The method of claim 4, wherein keeping further includes merging counts for each frequent item across all the nodes. 7. The method of claim 1, wherein generating further includes grouping a particular prefix of a first length with another prefix of the first length or a different length to create a longer prefix. 8. The method of claim 1, wherein generating further includes producing each prefix of a predefined minimum length. 9. The method of claim 1, wherein outputting further includes providing all the prefixes as sequential patterns to a third-party application for further analysis. 10. The method of claim 1, wherein outputting further includes producing all the prefixes as a complete set of sequential patterns available in the sequenced database. 11. A method implemented and programmed within a non-transitory computer-readable storage medium and processed by a processing node (node), the node configured to execute the method, comprising:
(a) acquiring, at the node, a subsequence grouped with a first item representing one unique portion of a sequence database, the subsequence redistributed to the node as part of a map/reduce process; (b) counting, at the node, frequent items discovered in the subsequence; (c) grouping, at the node, some of the frequent items with other frequent items to create prefixes of varying lengths; (d) iterating, at the node, (b) and (c) until no additional prefixes are created or a specific prefix having a specific length greater than a specific value is discovered; and (e) reporting, via the node, the prefixes to a parallel pattern detection manager. 12. The method of claim 11 further comprising, processing the method and other instances of the method in a parallel processing network. 13. The method of claim 11, wherein acquiring further includes receiving the subsequence from the parallel pattern detection manager. 14. The method of claim 11, wherein counting further includes filtering out other items that are determined to not be one of the frequent items. 15. The method of claim 11, wherein grouping further includes ensuring that each prefix is of a predefined minimum length. 16. The method of claim 15, wherein ensuring further includes filtering out any prefix that is of a length that is less than the predefined minimum length. 17. The method of claim 11, wherein grouping further includes producing at least some prefixes as sequential concatenations of other smaller prefixes. 18. A system, comprising:
memory configured with a parallel pattern detection manager that processes on a server of a network; wherein the parallel pattern detection manager is configured to manage and to use a plurality of nodes in a parallel processing network to resolve a complete set of sequential patterns mined from a sequence database by breaking the sequence database into datasets and have each node process a particular dataset to resolve specific patterns in that node's dataset. 19. The system of claim 18, wherein parallel pattern detection manager is configured to merge and collect the specific patterns and produce the complete set of sequential patterns when each node has completed processing on that node's dataset. 20. The system of claim 18, wherein the parallel pattern detection manager is configured to automatically feed the complete set of sequential patterns to a variety of analysis services. | Techniques for parallel frequent sequential pattern detection are provided. A sequence database is split into separate datasets and each node is given a specific dataset to resolve specific frequent items occurring in its specific dataset based on counts. Then, each node groups its item frequent items into “n” (varying) length sequences representing sequential patterns present in the original sequence database. The nodes process in parallel with one another and collectively produce a complete set of the sequential patterns defined in the original sequence database.1. A method implemented and programmed within a non-transitory computer-readable storage medium and processed by machine, the machine configured to execute the method, comprising:
(a) obtaining, at the machine, a subsequence for each sequence in a sequence database and group the subsequence with a first item; (b) redistributing, at the machine, the subsequences to nodes of a parallel processing networking by a prefix value; (c) counting, at each node and in parallel, a specific prefix with a predefined length and maintaining at each node a high frequency prefix and its postfix; (d) generating, at each node and in parallel, new prefixes that combine the specific prefix and specific subsequences of its postfix; (e) iterating, at each node and in parallel, (c) and (d) until no new prefixes are generated or until a given prefix length exceeds a specified value; and (f) outputting, by the machine, all the prefixes. 2. The method of claim 1, wherein obtaining further includes recognizing the first item as a first prefix. 3. The method of claim 1, wherein redistributing further includes redistributing each subsequence based on its prefix value. 4. The method of claim 1, wherein counting further includes having each node filter out infrequent items. 5. The method of claim 1, wherein counting further includes keeping track of counts on each node for each frequent item found. 6. The method of claim 4, wherein keeping further includes merging counts for each frequent item across all the nodes. 7. The method of claim 1, wherein generating further includes grouping a particular prefix of a first length with another prefix of the first length or a different length to create a longer prefix. 8. The method of claim 1, wherein generating further includes producing each prefix of a predefined minimum length. 9. The method of claim 1, wherein outputting further includes providing all the prefixes as sequential patterns to a third-party application for further analysis. 10. The method of claim 1, wherein outputting further includes producing all the prefixes as a complete set of sequential patterns available in the sequenced database. 11. A method implemented and programmed within a non-transitory computer-readable storage medium and processed by a processing node (node), the node configured to execute the method, comprising:
(a) acquiring, at the node, a subsequence grouped with a first item representing one unique portion of a sequence database, the subsequence redistributed to the node as part of a map/reduce process; (b) counting, at the node, frequent items discovered in the subsequence; (c) grouping, at the node, some of the frequent items with other frequent items to create prefixes of varying lengths; (d) iterating, at the node, (b) and (c) until no additional prefixes are created or a specific prefix having a specific length greater than a specific value is discovered; and (e) reporting, via the node, the prefixes to a parallel pattern detection manager. 12. The method of claim 11 further comprising, processing the method and other instances of the method in a parallel processing network. 13. The method of claim 11, wherein acquiring further includes receiving the subsequence from the parallel pattern detection manager. 14. The method of claim 11, wherein counting further includes filtering out other items that are determined to not be one of the frequent items. 15. The method of claim 11, wherein grouping further includes ensuring that each prefix is of a predefined minimum length. 16. The method of claim 15, wherein ensuring further includes filtering out any prefix that is of a length that is less than the predefined minimum length. 17. The method of claim 11, wherein grouping further includes producing at least some prefixes as sequential concatenations of other smaller prefixes. 18. A system, comprising:
memory configured with a parallel pattern detection manager that processes on a server of a network; wherein the parallel pattern detection manager is configured to manage and to use a plurality of nodes in a parallel processing network to resolve a complete set of sequential patterns mined from a sequence database by breaking the sequence database into datasets and have each node process a particular dataset to resolve specific patterns in that node's dataset. 19. The system of claim 18, wherein parallel pattern detection manager is configured to merge and collect the specific patterns and produce the complete set of sequential patterns when each node has completed processing on that node's dataset. 20. The system of claim 18, wherein the parallel pattern detection manager is configured to automatically feed the complete set of sequential patterns to a variety of analysis services. | 2,100 |
6,036 | 6,036 | 15,596,269 | 2,116 | A method for operating a redundant automation system having a plurality of subsystems, wherein one subsystem of the plurality of subsystems operates as a master and assumes process control and the other subsystem operates as a reserve during redundant operation, where measures are provided by which the availability of the redundant automation system is increased, and where regardless of whether transient errors occur on the subsystem of the plurality of subsystems operating as the master or on the subsystem operating as the reserve, a total failure of the automation system is largely avoided. | 1.-6. (canceled) 7. A method for operating a redundant automation system having a plurality of subsystems, a subsystem of the plurality of subsystems operating as a master and assumes process control and another subsystem of the plurality of systems operating as a reserve during redundant operation, and the master and the reserve systems being synchronized via communication and in an the event of a loss of synchronization, the method comprising:
comparing process inputs of a process image of the master subsystem with process inputs of a process image of the reserve subsystem; adjusting a communication of the reserve subsystem with additional components of the automation system; assuming process control as a new master subsystem by the reserve subsystem if the master subsystem fails during a predefined period of time; initiating, by the reserve subsystem, in an event that the master subsystem does not fail during the predefined period of time, troubleshooting to determine a cause of the loss of synchronization after the predefined period of time; providing the reserve subsystem with relevant process control data in context of an update after troubleshooting the master subsystem, if the reserve subsystem is not faulty; and assuming process control by the reserve system as the new master subsystem and after the update and initiating by the master subsystem further troubleshooting as the new reserve subsystem. 8. The method as claimed in claim 7, wherein the reserve subsystem adopts a defective status if the reserve detects an error during troubleshooting. 9. The method as claimed in claim 7, wherein the master subsystem transfers internal master data to the reserve subsystem and displays a defective status if the master subsystem is interrupted during troubleshooting, and wherein the reserve subsystem assumes process control as the new master subsystem. 10. The method as claimed in claim 7, wherein the predefined period of time is configurable via an engineering system. 11. The method as claimed in claim 8, wherein the predefined period of time is configurable via an engineering system. 12. The method as claimed in claim 9, wherein the predefined period of time is configurable via an engineering system. 13. A redundant automation system comprising:
a plurality of subsystems, a subsystems of the plurality of subsystems operating as a master subsystem and assuming process control and another subsystem of the plurality of subsystem operating as a reserve subsystem during redundant operation; wherein the master subsystem and the reserve subsystem are each configured to: compare process inputs of a process image of the master subsystem with process inputs of a process image of the reserve subsystem; adjust a communication of the reserve subsystem with additional components of the automation system; assume process control as a new master subsystem by the reserve subsystem if the master subsystem fails during a predefined period of time; initiate, by the reserve subsystem, in an event that the master subsystem does not fail during the predefined period of time, troubleshooting to determine a cause of the loss of synchronization after the predefined period of time; provide the reserve subsystem with relevant process control data in context of an update after troubleshooting the master subsystem, if the reserve subsystem is not faulty; and assume process control by the reserve system as the new master subsystem and after the update and initiate by the master subsystem further troubleshooting as the new reserve subsystem. 14. The redundant automation system as claimed in claim 13, wherein the predefined period of time is configurable via an engineering system of the automation system. | A method for operating a redundant automation system having a plurality of subsystems, wherein one subsystem of the plurality of subsystems operates as a master and assumes process control and the other subsystem operates as a reserve during redundant operation, where measures are provided by which the availability of the redundant automation system is increased, and where regardless of whether transient errors occur on the subsystem of the plurality of subsystems operating as the master or on the subsystem operating as the reserve, a total failure of the automation system is largely avoided.1.-6. (canceled) 7. A method for operating a redundant automation system having a plurality of subsystems, a subsystem of the plurality of subsystems operating as a master and assumes process control and another subsystem of the plurality of systems operating as a reserve during redundant operation, and the master and the reserve systems being synchronized via communication and in an the event of a loss of synchronization, the method comprising:
comparing process inputs of a process image of the master subsystem with process inputs of a process image of the reserve subsystem; adjusting a communication of the reserve subsystem with additional components of the automation system; assuming process control as a new master subsystem by the reserve subsystem if the master subsystem fails during a predefined period of time; initiating, by the reserve subsystem, in an event that the master subsystem does not fail during the predefined period of time, troubleshooting to determine a cause of the loss of synchronization after the predefined period of time; providing the reserve subsystem with relevant process control data in context of an update after troubleshooting the master subsystem, if the reserve subsystem is not faulty; and assuming process control by the reserve system as the new master subsystem and after the update and initiating by the master subsystem further troubleshooting as the new reserve subsystem. 8. The method as claimed in claim 7, wherein the reserve subsystem adopts a defective status if the reserve detects an error during troubleshooting. 9. The method as claimed in claim 7, wherein the master subsystem transfers internal master data to the reserve subsystem and displays a defective status if the master subsystem is interrupted during troubleshooting, and wherein the reserve subsystem assumes process control as the new master subsystem. 10. The method as claimed in claim 7, wherein the predefined period of time is configurable via an engineering system. 11. The method as claimed in claim 8, wherein the predefined period of time is configurable via an engineering system. 12. The method as claimed in claim 9, wherein the predefined period of time is configurable via an engineering system. 13. A redundant automation system comprising:
a plurality of subsystems, a subsystems of the plurality of subsystems operating as a master subsystem and assuming process control and another subsystem of the plurality of subsystem operating as a reserve subsystem during redundant operation; wherein the master subsystem and the reserve subsystem are each configured to: compare process inputs of a process image of the master subsystem with process inputs of a process image of the reserve subsystem; adjust a communication of the reserve subsystem with additional components of the automation system; assume process control as a new master subsystem by the reserve subsystem if the master subsystem fails during a predefined period of time; initiate, by the reserve subsystem, in an event that the master subsystem does not fail during the predefined period of time, troubleshooting to determine a cause of the loss of synchronization after the predefined period of time; provide the reserve subsystem with relevant process control data in context of an update after troubleshooting the master subsystem, if the reserve subsystem is not faulty; and assume process control by the reserve system as the new master subsystem and after the update and initiate by the master subsystem further troubleshooting as the new reserve subsystem. 14. The redundant automation system as claimed in claim 13, wherein the predefined period of time is configurable via an engineering system of the automation system. | 2,100 |
6,037 | 6,037 | 14,032,910 | 2,119 | A computer-based method for generating a physical payment card for a consumer is provided. The method is implemented using a computer device including a processor. The method includes identifying a consumer account. The method also includes creating, by the processor, a model data file associated with the physical payment card for the consumer account. The model data file includes data representing the physical payment card. The method further includes transmitting the model data file to a 3-dimensional printer device. The model data file is configured to enable the printer device to print the physical payment card. | 1. A computer-based method for generating a physical payment card for a consumer, the method implemented using a computer device including a processor, said method comprising:
identifying a consumer account; creating, by the processor, a model data file associated with the physical payment card for the consumer account, wherein the model data file includes data representing the physical payment card; and transmitting the model data file to a 3-dimensional printer device, the model data file is configured to enable the printer device to print the physical payment card. 2. The method of claim 1 further comprising:
configuring one or more components for coupling to the physical payment card, wherein the one or more components include at least one of a magnetic strip and an identification microchip, wherein creating a model data file comprises creating a model data file defining instructions for printing a receiving surface on the physical payment card to assist coupling of the one or more components to the physical payment card; and
providing to a third party the one or more physical components. 3. The method of claim 1, wherein transmitting the model data file comprises transmitting the model data file to at least one of a consumer and a printing service supplier for printing on the 3-dimensional printer device. 4. The method of claim 1, wherein creating a model data file comprises creating a model data file including 3-dimensional printing definition data representing the payment card. 5. The method of claim 1, wherein creating a model data file comprises creating a model data file including one or more of a raised account number and a raised consumer name associated with the consumer account. 6. The method of claim 1, wherein creating a model data file comprises creating a model data file for the 3-dimensional printer device that uses one or more of extrusion deposition, granular material binding, and stereolithography. 7. The method of claim 1, wherein creating a model data file comprises creating a model data file including instructions for printing a magnetic portion within the physical payment card. 8. The method of claim 1, wherein creating a model data file comprises creating a model data file including instructions for printing a microchip within the physical payment card. 9. A computing device for generating a physical payment card for a consumer, said computer device comprising a processor communicatively coupled to a memory, said computing device programmed to:
identify a consumer account; create a model data file associated with the physical payment card for the consumer account, wherein the model data file includes data representing the physical payment card; and transmit the model data file to a 3-dimensional printer device, the model data file is configured to enable the printer device to print the physical payment card. 10. The computing device of claim 9, wherein the computing device is further programmed to transmit the model data file to at least one of a consumer and a printing service supplier for printing on the 3-dimensional printer device. 11. The computing device of claim 9, wherein the computing device is further programmed to:
configure one or more components for coupling to the physical payment card, wherein the one or more components include at least one of a magnetic strip and an identification microchip; and create the model data file including instructions for printing a receiving surface on the physical payment card to assist coupling of the one or more components to the physical payment card. 12. A computer-based method for generating a physical payment card for a consumer, the method implemented using a computer device in communication with a 3-dimensional printer, said method comprising:
receiving, by the computer device, a model data file including 3-dimensional printing definition data for printing the payment card, wherein the printing definition data includes card body data representing a card body of the physical payment card; and printing the payment card using at least the computing device, the 3-dimensional printer, and the model data file, thereby generating a payment card including at least the card body. 13. The method of claim 12, wherein the printing definition data further includes component data, wherein the method further comprises:
receiving, by a third party associated with the computer device, one or more components for coupling to the card body, wherein the one or more components include at least one of a magnetic strip and an identification microchip for use with the payment card, wherein the component data includes instructions for printing a receiving surface on or within the card body to assist coupling of the one or more components to the card body; and coupling the one or more components to the card body. 14. The method of claim 12, wherein the printing definition data further includes component data, wherein printing the payment card further comprises printing one or more components, wherein the one or more components include at least one of a magnetic strip and an identification microchip for use with the payment card, wherein the component data includes instructions for printing the one or more components integral with the card body. 15. The method of claim 12, wherein printing the payment card further comprises printing the payment card with a 3-dimensional printer using one or more of extrusion deposition, granular material binding, and stereolithography. 16. The method of claim 12, wherein receiving a model data file further comprises receiving a model data file defining instructions for printing the payment card including payment card account information associated with the consumer. 17. The method of claim 12, wherein receiving a model data file further comprises receiving a model data file defining instructions for printing identifying information for an issuing bank associated with the payment card. 18. A computer system for generating a physical payment card for a consumer, said computer system comprising:
at least one processor; a user interaction device communicatively coupled with said at least one processor, said user interaction device comprising a display device and an input device, said user interaction device configured to identify and authenticate the consumer associated with a consumer account; and a 3-dimensional printer communicatively coupled with said at least one processor, said 3-dimensional printer configured to:
receive, from said at least one processor after authentication of the consumer, a model data file associated with the physical payment card for the consumer account, wherein the model data file includes data representing the physical payment card; and
print the physical payment card using at least the model data file and the 3-dimensional printer. 19. The computer system of claim 18, wherein said 3-dimensional printer is further configured to print one or more components on or within the physical payment card, the one or more components including at least one of a magnetic strip and a microchip. 20. The computer system of claim 18 further comprising a component dispenser in communication with said processor, said component dispenser programmed to configure one or more components for the consumer account. 21. The computer system of claim 20, wherein the physical component includes one or more of a magnetic strip and a microchip. 22. The computer system of claim 20, wherein said physical component dispenser is further configured to couple the physical component to the physical payment card. 23. The computer system of claim 18, wherein said 3-dimensional printer comprises a 3-dimensional printer that uses one or more of extrusion deposition, granular material binding, and stereolithography. | A computer-based method for generating a physical payment card for a consumer is provided. The method is implemented using a computer device including a processor. The method includes identifying a consumer account. The method also includes creating, by the processor, a model data file associated with the physical payment card for the consumer account. The model data file includes data representing the physical payment card. The method further includes transmitting the model data file to a 3-dimensional printer device. The model data file is configured to enable the printer device to print the physical payment card.1. A computer-based method for generating a physical payment card for a consumer, the method implemented using a computer device including a processor, said method comprising:
identifying a consumer account; creating, by the processor, a model data file associated with the physical payment card for the consumer account, wherein the model data file includes data representing the physical payment card; and transmitting the model data file to a 3-dimensional printer device, the model data file is configured to enable the printer device to print the physical payment card. 2. The method of claim 1 further comprising:
configuring one or more components for coupling to the physical payment card, wherein the one or more components include at least one of a magnetic strip and an identification microchip, wherein creating a model data file comprises creating a model data file defining instructions for printing a receiving surface on the physical payment card to assist coupling of the one or more components to the physical payment card; and
providing to a third party the one or more physical components. 3. The method of claim 1, wherein transmitting the model data file comprises transmitting the model data file to at least one of a consumer and a printing service supplier for printing on the 3-dimensional printer device. 4. The method of claim 1, wherein creating a model data file comprises creating a model data file including 3-dimensional printing definition data representing the payment card. 5. The method of claim 1, wherein creating a model data file comprises creating a model data file including one or more of a raised account number and a raised consumer name associated with the consumer account. 6. The method of claim 1, wherein creating a model data file comprises creating a model data file for the 3-dimensional printer device that uses one or more of extrusion deposition, granular material binding, and stereolithography. 7. The method of claim 1, wherein creating a model data file comprises creating a model data file including instructions for printing a magnetic portion within the physical payment card. 8. The method of claim 1, wherein creating a model data file comprises creating a model data file including instructions for printing a microchip within the physical payment card. 9. A computing device for generating a physical payment card for a consumer, said computer device comprising a processor communicatively coupled to a memory, said computing device programmed to:
identify a consumer account; create a model data file associated with the physical payment card for the consumer account, wherein the model data file includes data representing the physical payment card; and transmit the model data file to a 3-dimensional printer device, the model data file is configured to enable the printer device to print the physical payment card. 10. The computing device of claim 9, wherein the computing device is further programmed to transmit the model data file to at least one of a consumer and a printing service supplier for printing on the 3-dimensional printer device. 11. The computing device of claim 9, wherein the computing device is further programmed to:
configure one or more components for coupling to the physical payment card, wherein the one or more components include at least one of a magnetic strip and an identification microchip; and create the model data file including instructions for printing a receiving surface on the physical payment card to assist coupling of the one or more components to the physical payment card. 12. A computer-based method for generating a physical payment card for a consumer, the method implemented using a computer device in communication with a 3-dimensional printer, said method comprising:
receiving, by the computer device, a model data file including 3-dimensional printing definition data for printing the payment card, wherein the printing definition data includes card body data representing a card body of the physical payment card; and printing the payment card using at least the computing device, the 3-dimensional printer, and the model data file, thereby generating a payment card including at least the card body. 13. The method of claim 12, wherein the printing definition data further includes component data, wherein the method further comprises:
receiving, by a third party associated with the computer device, one or more components for coupling to the card body, wherein the one or more components include at least one of a magnetic strip and an identification microchip for use with the payment card, wherein the component data includes instructions for printing a receiving surface on or within the card body to assist coupling of the one or more components to the card body; and coupling the one or more components to the card body. 14. The method of claim 12, wherein the printing definition data further includes component data, wherein printing the payment card further comprises printing one or more components, wherein the one or more components include at least one of a magnetic strip and an identification microchip for use with the payment card, wherein the component data includes instructions for printing the one or more components integral with the card body. 15. The method of claim 12, wherein printing the payment card further comprises printing the payment card with a 3-dimensional printer using one or more of extrusion deposition, granular material binding, and stereolithography. 16. The method of claim 12, wherein receiving a model data file further comprises receiving a model data file defining instructions for printing the payment card including payment card account information associated with the consumer. 17. The method of claim 12, wherein receiving a model data file further comprises receiving a model data file defining instructions for printing identifying information for an issuing bank associated with the payment card. 18. A computer system for generating a physical payment card for a consumer, said computer system comprising:
at least one processor; a user interaction device communicatively coupled with said at least one processor, said user interaction device comprising a display device and an input device, said user interaction device configured to identify and authenticate the consumer associated with a consumer account; and a 3-dimensional printer communicatively coupled with said at least one processor, said 3-dimensional printer configured to:
receive, from said at least one processor after authentication of the consumer, a model data file associated with the physical payment card for the consumer account, wherein the model data file includes data representing the physical payment card; and
print the physical payment card using at least the model data file and the 3-dimensional printer. 19. The computer system of claim 18, wherein said 3-dimensional printer is further configured to print one or more components on or within the physical payment card, the one or more components including at least one of a magnetic strip and a microchip. 20. The computer system of claim 18 further comprising a component dispenser in communication with said processor, said component dispenser programmed to configure one or more components for the consumer account. 21. The computer system of claim 20, wherein the physical component includes one or more of a magnetic strip and a microchip. 22. The computer system of claim 20, wherein said physical component dispenser is further configured to couple the physical component to the physical payment card. 23. The computer system of claim 18, wherein said 3-dimensional printer comprises a 3-dimensional printer that uses one or more of extrusion deposition, granular material binding, and stereolithography. | 2,100 |
6,038 | 6,038 | 14,136,661 | 2,196 | Embodiments support instant forking of virtual machines (VMs) and state customization. Virtual device state and persistent storage of a child VM are defined based on virtual device state and persistent storage of parent VMs. After forking, a state of the child VM is customized based on configuration data. Customizing the state includes configuring one or more identities of the child VM, before bootup completes on the child VM. | 1. A system for creating customized, forked virtual machines (VMs), said system comprising:
memory associated with a computing device, said memory storing a virtual device state and a memory state of a suspended first VM; storage for the first VM, said storage further including configuration data for a second VM; and a processor programmed to:
suspend execution of the first VM;
tag the persistent storage of the suspended first VM as copy-on-write (COW);
define a virtual device state of the second VM based on the virtual device state of the suspended first VM;
define a memory state of the second VM based on the memory state of the suspended first VM;
define persistent storage for the second VM based on the persistent storage of the first VM; and
execute the second VM to configure an identity of the second VM based on the configuration data. 2. The system of claim 1, wherein the processor is further programmed to obtain the virtual device state of the suspended first VM and store the obtained virtual device state in the memory. 3. The system of claim 1, wherein the configuration data stored in the storage comprises at least one of an Internet Protocol (IP) address, a media access control (MAC) address, a hostname, or a domain identity. 4. The system of claim 1, wherein the processor is programmed to suspend the execution of the first VM and tag the persistent storage of the suspended first VM in response to a request from a user for the second VM. 5. The system of claim 1, wherein the processor is programmed to define the virtual device state of the second VM, define the persistent storage for the second VM, and execute the second VM to configure the identity of the second VM, in response to a request from a management level application executing on the computing device. 6. The system of claim 1, wherein the processor is programmed to define the persistent storage for the second VM by:
creating a read-only base disk referencing the persistent storage of the first VM; and creating a delta disk storing changes made by the second VM to the created read-only base disk. 7. A method comprising:
defining, by a computing device based on a virtual device state of a suspended first virtual machine (VM), a virtual device state of a second VM; defining a memory state for the second VM based on a memory state of the suspended first VM; defining persistent storage for the second VM based on persistent storage of the suspended first VM; and configuring, by the computing device, an identity of the second VM based on configuration data associated with the second VM. 8. The method of claim 7, wherein defining the virtual device state of the second VM comprises copying the virtual device state of the suspended first VM. 9. The method of claim 7, wherein the identity comprises at least one of an Internet Protocol (IP) address, a media access control (MAC) address, a hostname, or a domain identity. 10. The method of claim 7, wherein defining the memory state for the second VM comprises creating copy-on-write (COW) sharing of the memory state of the suspended first VM. 11. The method of claim 7, wherein defining the persistent storage for the second VM comprises creating a delta disk referencing the persistent storage of the suspended first VM. 12. The method of claim 7, wherein defining the persistent storage for the second VM comprises using array-level disk snapshots of the suspended first VM. 13. The method of claim 7, wherein configuring the identity of the second VM comprises executing the second VM, the second VM customizing itself during bootup. 14. The method of claim 7, further comprising accessing the configuration data associated with the second VM, the configuration data being registered with virtualization software executing on the computing device. 15. The method of claim 7, wherein defining the virtual device state of the second VM comprises defining, based on a virtual device state of a suspended parent VM, a virtual device state of a child VM. 16. One or more computer-readable storage media including computer-executable instructions that, when executed, cause at least one processor to fork a virtual machine (VM) and configure an identity thereof, by:
defining, by a computing device based on a virtual device state of a suspended first VM, a virtual device state of a second VM; defining persistent storage for the second VM based on persistent storage of the suspended first VM; and configuring an identity of the second VM based on configuration data associated with the second VM. 17. The computer storage media of claim 16, wherein the computer-executable instructions cause the processor to configure the identity of the second VM by configuring a boot process of the second VM, the second VM performing the boot process to configure the identity of the second VM. 18. The computer storage media of claim 16, wherein the computer-executable instructions further cause the processor to create the plurality of domain identities prior to defining the virtual device state of the second VM and prior to defining the persistent storage for the second VM. 19. The computer storage media of claim 16, wherein the computer-executable instructions further cause the processor block completion of bootup of the second VM until after the identity is applied to the second VM. 20. The computer storage media of claim 16, wherein computer-executable instructions further cause the processor to suspend the first VM by quiescing the first VM. | Embodiments support instant forking of virtual machines (VMs) and state customization. Virtual device state and persistent storage of a child VM are defined based on virtual device state and persistent storage of parent VMs. After forking, a state of the child VM is customized based on configuration data. Customizing the state includes configuring one or more identities of the child VM, before bootup completes on the child VM.1. A system for creating customized, forked virtual machines (VMs), said system comprising:
memory associated with a computing device, said memory storing a virtual device state and a memory state of a suspended first VM; storage for the first VM, said storage further including configuration data for a second VM; and a processor programmed to:
suspend execution of the first VM;
tag the persistent storage of the suspended first VM as copy-on-write (COW);
define a virtual device state of the second VM based on the virtual device state of the suspended first VM;
define a memory state of the second VM based on the memory state of the suspended first VM;
define persistent storage for the second VM based on the persistent storage of the first VM; and
execute the second VM to configure an identity of the second VM based on the configuration data. 2. The system of claim 1, wherein the processor is further programmed to obtain the virtual device state of the suspended first VM and store the obtained virtual device state in the memory. 3. The system of claim 1, wherein the configuration data stored in the storage comprises at least one of an Internet Protocol (IP) address, a media access control (MAC) address, a hostname, or a domain identity. 4. The system of claim 1, wherein the processor is programmed to suspend the execution of the first VM and tag the persistent storage of the suspended first VM in response to a request from a user for the second VM. 5. The system of claim 1, wherein the processor is programmed to define the virtual device state of the second VM, define the persistent storage for the second VM, and execute the second VM to configure the identity of the second VM, in response to a request from a management level application executing on the computing device. 6. The system of claim 1, wherein the processor is programmed to define the persistent storage for the second VM by:
creating a read-only base disk referencing the persistent storage of the first VM; and creating a delta disk storing changes made by the second VM to the created read-only base disk. 7. A method comprising:
defining, by a computing device based on a virtual device state of a suspended first virtual machine (VM), a virtual device state of a second VM; defining a memory state for the second VM based on a memory state of the suspended first VM; defining persistent storage for the second VM based on persistent storage of the suspended first VM; and configuring, by the computing device, an identity of the second VM based on configuration data associated with the second VM. 8. The method of claim 7, wherein defining the virtual device state of the second VM comprises copying the virtual device state of the suspended first VM. 9. The method of claim 7, wherein the identity comprises at least one of an Internet Protocol (IP) address, a media access control (MAC) address, a hostname, or a domain identity. 10. The method of claim 7, wherein defining the memory state for the second VM comprises creating copy-on-write (COW) sharing of the memory state of the suspended first VM. 11. The method of claim 7, wherein defining the persistent storage for the second VM comprises creating a delta disk referencing the persistent storage of the suspended first VM. 12. The method of claim 7, wherein defining the persistent storage for the second VM comprises using array-level disk snapshots of the suspended first VM. 13. The method of claim 7, wherein configuring the identity of the second VM comprises executing the second VM, the second VM customizing itself during bootup. 14. The method of claim 7, further comprising accessing the configuration data associated with the second VM, the configuration data being registered with virtualization software executing on the computing device. 15. The method of claim 7, wherein defining the virtual device state of the second VM comprises defining, based on a virtual device state of a suspended parent VM, a virtual device state of a child VM. 16. One or more computer-readable storage media including computer-executable instructions that, when executed, cause at least one processor to fork a virtual machine (VM) and configure an identity thereof, by:
defining, by a computing device based on a virtual device state of a suspended first VM, a virtual device state of a second VM; defining persistent storage for the second VM based on persistent storage of the suspended first VM; and configuring an identity of the second VM based on configuration data associated with the second VM. 17. The computer storage media of claim 16, wherein the computer-executable instructions cause the processor to configure the identity of the second VM by configuring a boot process of the second VM, the second VM performing the boot process to configure the identity of the second VM. 18. The computer storage media of claim 16, wherein the computer-executable instructions further cause the processor to create the plurality of domain identities prior to defining the virtual device state of the second VM and prior to defining the persistent storage for the second VM. 19. The computer storage media of claim 16, wherein the computer-executable instructions further cause the processor block completion of bootup of the second VM until after the identity is applied to the second VM. 20. The computer storage media of claim 16, wherein computer-executable instructions further cause the processor to suspend the first VM by quiescing the first VM. | 2,100 |
6,039 | 6,039 | 13,923,630 | 2,127 | This patent (application) discloses for a claimed invention 10 tests (+their 5 controls) enabled by its inventive concepts, automatically prompting their user through exploratively checking its meeting the requirements stated by
§112, “well-definedness of its inventive concepts”, i.e. their 1) disaggregation into elementary ones, 2) disclosures, 3) definitiveness, and 4) enablement; §§102/103, “novelty/nonobviousness of this invention”, i.e. its 7) creativity/inventivity, after having assessed their 5) independence, and 6) non-equivalence; §101, “patent-eligibility of it and its claim”, i.e. its not only being 8) a natural law, or 9) idempotent, or 10) an abstract idea alias preemptive,
and then being automatically affirmatively reproducible in real-time.
These inventive concepts represent this claimed invention's legal and technical facts under 35 USC §§112/102/103/101—and other patent laws' peer sections, e.g. EPC's §§52-57, 69—required by Highest Courts for “model based” inventions, i.e. from advanced technologies. | 1) A computer-implemented method for updating a given data structure PTRCT-DS in a BAD-KR, both in given formats, by a set of Binary Elementary Disclosed (“BED”) inventive concepts of PTR's TT.0, called BED-TT.0, input to it by the user and by appendices to it and to BAD-KR for controlling an Innovation Expert System IES—the method (performing, for a claimed invention of PTR, its refined claim construction by here first disaggregating its compound inventive concepts, if these are not yet elementary) using a memory for storing the so updated PTRCT-DS, generated by executing this method on TT.0's compound inventive concepts BAD-X.0.n of TT.0 representing their mirror predicates BAD-X.0.n of its X.0.n, 1≦n≦N—which:
(a) writes the PTRCT-DS in a given BAD-KR into the memory
(b) automatically prompts the user to determine the KR_R&S_S to be obeyed during its execution, being
(b).1 either given by the IES as a default KR_R&S_S for both strategies, based on the BAD-KR of (a),
(b).2 or a KR_R&S_S input, in a given notation, by the user additionally to the BAD-KR of (a);
(c) automatically identifies in said PTRCT-DS and said KR_R&S_S, in given formats,
(c).1 for a given 0≦I≦IRSI, all document.i's and all their doc.i-MUIs, 0≦i≦l, and
(c).2 the document.CT in doc.0 and all its doc.CT-MUIs, and
(c).3 all elements X.0.n and their predicates BAD-X.0.n, 1≦n≦N, for any BAD-KR in KR_R&S_S;
(d) automatically performs for any BAD-KR in KR_R&S_S, controlled by this KR_R&S_S, the steps (d).1-(d).6:
(d).1 prompt the user to input a set of BED-cr-C.0.k's—in a given notation—of TT.0, 1≦k≦K, and
(d).2 prompt the user to disaggregate any BAD-X.0.n, 1≦n≦N, into a set {BED-cr-C.0.kn|1≦kn≦Kn}⊂{BED-cr-C.0.k|1≦k≦K}: BAD-X.0.n=Λ1sknKnBED-cr-C.0kn, whereby BED-cr-C.0.kn≠BED-cr-C.0.kn′∀n≠n′, and |{∪1≦n≦sN{BED-cr-C.0kn|1≦kn≦Kn}}|=K,
(d).3 prompt the user to input, in a given notation, ∀BAD-X.0.n a set of justifications by doc.0-/.CT-MUIs of this disaggregation into {BED-cr-C.0.kn|1≦kn≦Kn}, denoted as SoJUSdagr(BAD-X.0.n), 1≦n≦N;
(d).4 automatically append any SoJUSdagr(BAD-X.0.n) to BAD-X.0.n, 1≦n≦N;
(d).5 automatically generate BED-TT.0::={{BED-cr-C.0.k|1≦k≦K}}∪{{BED-cr-C.0.kn|1≦kn≦Kn}|1≦n≦N};
(d).6 automatically update the PTRCT-DS in the memory as of (a), according to (d).4 and (d).5. 2) A method according to claim 1 (explaining the lawful disclosures of the BED-cr-C.0.kn and completing them to BED-in-C.0.kn by), updating PTRCT-DS by the sets SoDIS(TT.0) and SoJUS(TT.0), which
(a) automatically prompts the user through each BED-cr-C.0.kn in each BAD-X.0.n of the KR at issue, 1≦kn≦Kn, 1≦n≦N—to identify for BED-cr-C.0.kn a set of disclosures, SoDIS(BED-C.0.kn)::={MUI.0s disclosing this BED-cr-C.0.kn}, SoDIS(BED-cr-C.0.kn) being justified by SoJUSdagr(BAD-X.0.n) and hence linked to it;
(b) automatically prompts the user to select at least one disclosure DISsel(BED-cr-C.0.kn) from any set SoDIS(BED-cr-C.0.kn) of (a), and to identify for it a set of legal justifications, SoJUS(DISsel(BED-cr-C.0.kn)) ::={I.CTs and/or MUI.CTs and MUI.0s justifying DISsel(BED-cr-C.0.kn)} and hence linked to it;
(c) automatically appends to any BED-cr-C.0.kn its SoDIS(BED-cr-C.0.kn), 1≦kn≦Kn, 1≦n≦N;
(d) automatically appends to any selected disclosure DISsel(BED-cr-C.0.kn) the SoJUS(DISsel(BED-cr-C.0.kn)) of (b), 1≦kn≦Kn, 1≦n≦N;
(e) automatically updates BED-TT.0 in the memory by {BED-cr-C.0.k expanded by its appendix (c)-(d), 1≦k≦K}. 3) A method according to claim 2 (explaining the definitiveness of the BED-in-C.0.kn involved in a means-plus-function-clause), which
(a) automatically prompts the user for any BED-cr-C.0.kn of claim 2 involved in a means-plus-function-clause, 1≦kn≦Kn, through its disclosures DISsel(BED-cr-C.0.mn), 1≦mn≦Mn, 1≦n≦N, until a DISsel0(BED-cr-C.0.mn) enables the user to state this BED-cr-C.0.kn′s definitiveness;
(b) automatically appends this statement of (a), JUSdef(DISsel0(BED-cr-C.0.mn)), to BED-cr-C.0.kn;
(c) automatically updates BED-TT.0 in the memory by {BED-cr-C.0.kn expanded by JUSdef(DISsel0(BED-cr-C.0.mn)), 1≦kn≦Kn, 1≦n≦N}. 4) A method according to claim 3 (explaining the BED-in-C.0.kn's being enabling), which
(a) automatically prompts the user through any of its BED-cr-C.0.kns and any of its disclosures DISsel(BED-cr-C.0.kn), 1≦kn≦Kn, 1≦n≦N—until one DISsel(BED-cr-C.0.kn) entitles the user to state that BED-cr-C.0.kn is enablingly disclosed;
(b) automatically appends this statement of (a), JUSend(DISsel(BED-cr-C.0.kn)), to DISsel(BED-cr-C.0.kn);
(c) automatically updates BED-TT.0 in the memory by {BED-cr-C.0.kn expanded by DISsel(BED-cr-C.0.kn) which is expanded by JUSend(DISsel(BED-cr-C.0.kn)), 1≦n≦N, 1≦kn≦Kn}. 5) A method according to claim 4 (explaining the BID-in-C.0.kn′s being independent), which
(a) automatically prompts the user to select from the {BED-cr-C.0.k l 1≦k≦K}, occurrences of which passed claim 4, a subset {BID-cr-C.0.k*, 1≦k*≦K*≦K};
(b) automatically determines, which value of k* identifies which value of k;
(c) automatically prompts the user, for any k*, through any combinations of BID-cr-C.0.k*′, 1≦k*′≠k*≦K*, thus enabling the user to state thereafter that and why BID-cr-C.0.k* is independent of any BID-cr-C.0.k*′ and combinations thereof;
(d) automatically appends {BID-cr-C.0.k*, 1≦k*≦K*} to {BED-cr-C.0.k, 1≦k≦K} as of (a);
(e) automatically appends this statement of (c), JUSind({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(f) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (e), 1≦k*≦K*}. 6) A method according to claim 5 (explaining the BID-in-C.0.kn′s being nonequivalent)
(a) automatically prompts the user, for any BID-cr-C.0.k*, through any doc.0-MUIs, thus that the user may state thereafter that and why it is non-equivalent to a BID-cr-C.0.k*′, 1≦k*′≠k*≦K*;
(b) automatically appends this statement of (a), JUSnequ({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(c) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (b), 1≦k*≦K*}. 7) A method according to claim 6 (showing the claimed invention being novel and nonobvious), which
(a) automatically prompts the user to execute the NANO test on the current PTRCT-DS;
(b) automatically appends the result of (a), JUSNANO({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(c) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (b), 1≦k*≦K*}. 8) A method according to claim 7 (showing the claimed invention being not natural law(s) only), which
(a) automatically prompts the user to state that and why the claimed invention is not natural law only;
(b) automatically appends this statement of (a), JUSNNLO({BID-cr-C.0.k*, 1≦k≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(c) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (b), 1≦k*≦K*}. 9) A method according to claim 8 (showing the claimed invention being not idempotent), which
(a) automatically prompts the user to select from {BID-cr-C.0.k*, 1≦k*≦K*} a set {BID-cr-C.0.k″, 1≦k″≦K″≦K*};
(b) automatically prompts the user to execute the NANO test [set of (a)] on the current PTRCT-DS;
(c) automatically appends the set of (a) to {BID-cr-C.0.k*, 1≦k*≦K*};
(d) automatically appends the result of (b), JUSNI({BID-cr-C.0.k″, 1≦k″≦K″}), to {BID-cr-C.0.k”, 1≦k″≦K″};
(e) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (c) and (d), 1≦k*≦K*}. 10) A method according to claim 9 (showing the claimed invention being not an abstract idea only), which
(a) automatically prompts the user to state the problem P.0 to be solved by the claimed invention;
(b) automatically prompts the user to identify the set of doc.0-MUIs describing this P.0, SoDIS(P.0);
(c) automatically appends this statement of (a) to {BID-cr-C.0.k″, 1≦k″K″};
(d) automatically appends SoDIS(P.0) to {BID-cr-C.0.k″, 1≦k″≦K″};
(e) automatically prompts the user, for any BID-cr-C.0.k″, through any doc.0-MUI, thus enabling it to state that this BID-cr-C.0.k″ is indispensable in the claimed invention for making it solve P.0;
(f) automatically appends this statement, JUSNAIO(P.0), to {BID-cr-C.0.k″, 1≦k″≦K″};
(g) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (a)-(f), 1≦k″≦K″}. 11) A method according to claim 1, subject to the additional limitations that part of the information input uses a given predesigned wording. 12) A method according to claim 1, subject to the additional limitations that part of the information input comprises confirmation of correctness by some given authority. 13) A method according to claim 1, subject to the additional limitations that part of the information input represents enrichments of various kinds of the PTR-DS. 14) A method according to claim 1, subject to the additional limitations that part of the information input represents given modifications of the volume of a set of alternatives. 15) A method according to claim 1, subject to the additional limitations that part of the information input represents given determinations of test specific execution sequences. 16) A system executing a computer-implemented method for updating a given data structure PTRCT-DS in a BAD-KR, both in given formats, by a set of Binary Elementary Disclosed (“BED”) inventive concepts of PTR's TT.0, called BED-TT.0, input to it by the user and by appendices to it and to BAD-KR for controlling an Innovation Expert System IES—the method (performing, for a claimed invention of PTR, its refined claim construction by here first disaggregating its compound inventive concepts, if these are not yet elementary) using a memory for storing the so updated PTRCT-DS, generated by executing this method on TT.0's compound inventive concepts BAD-X.0.n of TT.0 representing their mirror predicates BAD-X.0.n of its X.0.n, 1≦n≦N—which:
(a) writes the PTRCT-DS in a given BAD-KR into the memory
(b) automatically prompts the user to determine the KR_R&S_S to be obeyed during its execution, being
(b).3 either given by the IES as a default KR_R&S_S for both strategies, based on the BAD-KR of (a),
(b).4 or a KR_R&S_S input, in a given notation, by the user additionally to the BAD-KR of (a);
(c) automatically identifies in said PTRCT-DS and said KR_R&S_S, in given formats,
(c).4 for a given 0≦I≦IRSI, all document's and all their doc.i-MUIs, 0≦i≦Il, and
(c).5 the document.CT in doc.0 and all its doc.CT-MUIs, and
(c).6 all elements X.0.n and their predicates BAD-X.0.n, 1≦n≦N, for any BAD-KR in KR_R&S_S;
(d) automatically performs for any BAD-KR in KR_R&S_S, controlled by this KR_R&S_S, the steps (d).1-(d).6:
(d).7 prompt the user to input a set of BED-cr-C.0.k′s—in a given notation—of TT.0, 1≦k≦K, and
(d).8 prompt the user to disaggregate any BAD-X.0.n, 1≦n≦N, into a set {BED-cr-C.0.kn|1≦kn≦Kn}⊂{BED-cr-C.0.k|1≦k≦K}: BAD-X.0.n=Λ1≦kn≦KnBED-cr-C.0.kn, whereby BED-cr-C.0.kn≠BED-cr-C.0.kn′∀V n′, and |∪ 1≦n≦N{BED-cr-C.0.kn|1≦kn≦Kn}}l=K,
(d).9 prompt the user to input, in a given notation, ∀BAD-X.0.n a set of justifications by doc.0-/.CT-MUIs of this disaggregation into {BED-cr-C.0.kn|1≦kn≦Kn}, denoted as SoJUSdagr(BAD-X.0.n), 1≦n≦N;
(d).10 automatically append any SoJUSdagr(BAD-X.0.n) to BAD-X.0.n, 123 n≦N;
(d).11 automatically generate BED-TT.0::={{BED-cr-C.0.k|1≦k≦K}}∪{{BED-cr-C.0.kn|1≦kn≦Kn}|1≦n≦N};
(d).12 automatically update the PTRCT-DS in the memory as of (a), according to (d).4 and (d).5. 17) A system executing a computer-implemented method according to claim 16 (explaining the lawful disclosures of the BED-cr-C.0.kn and completing them to BED-in-C.0.kn by), updating PTRCT-DS by the sets SoDIS(TT.0) and SoJUS(TT.0), which
(a) automatically prompts the user through each BED-cr-C.0.kn in each BAD-X.0.n of the KR at issue, 1≦kn≦Kn, 1≦n≦N—to identify for BED-cr-C.0.kn a set of disclosures, SoDIS(BED-C.0.kn)::={MUI.0s disclosing this BED-cr-C.0.kn}, SoDIS(BED-cr-C.0.kn) being justified by SoJUSdagr(BAD-X.0.n) and hence linked to it;
(b) automatically prompts the user to select at least one disclosure DISsel(BED-cr-C.0.kn) from any set SoDIS(BED-cr-C.0.kn) of (a), and to identify for it a set of legal justifications, SoJUS(DISsel(BED-cr-C.0.kn))::=I.CTs and/or MUI.CTs and MUI.0s justifying DISsel(BED-cr-C.0.kn)} and hence linked to it;
(c) automatically appends to any BED-cr-C.0.kn its SoDIS(BED-cr-C.0.kn), 1≦kn≦Kn, 1≦n≦N;
(d) automatically appends to any selected disclosure DISsel(BED-cr-C.0.kn) the SoJUS(DISsel(BED-cr-C.0.kn)) of (b), 1≦kn≦Kn, 1≦n≦N;
(e) automatically updates BED-TT.0 in the memory by {BED-cr-C.0.k expanded by its appendix (c)-(d), 1≦k≦K}. 18) A system executing a computer-implemented method according to claim 17 (explaining the definitiveness of the BED-in-C.0.kn involved in a means-plus-function-clause), which
(a) automatically prompts the user for any BED-cr-C.0.kn of claim 17 involved in a means-plus-function-clause, 1≦kn≦Kn, through its disclosures DISsel(BED-cr-C.0.mn), 1≦mn≦Mn, 1≦n≦N, until a DISsel0(BED-cr-C.0.mn) enables the user to state this BED-cr-C.0.kn′s definitiveness;
(b) automatically appends this statement of (a), JUSdef(DISsel0(BED-cr-C.0.mn)), to BED-cr-C.0.kn;
(c) automatically updates BED-TT.0 in the memory by {BED-cr-C.0.kn expanded by JUSdef(DISsel0(BED-cr-C.0.mn)), 1≦kn≦Kn, 1≦n≦N}. 19) A system executing a computer-implemented method according to claim 18 (explaining the BED-in-C.0.kn′s being enabling), which
(a) automatically prompts the user through any of its BED-cr-C.0.kns and any of its disclosures DISsel(BED-cr-C.0.kn), 1≦kn≦Kn, 1≦n≦N—until one DISsel(BED-cr-C.0.kn) entitles the user to state that BED-cr-C.0.kn is enablingly disclosed;
(b) automatically appends this statement of (a), JUSend(DISsel(BED-cr-C.0.kn)), to DISsel(BED-cr-C.0.kn);
(c) automatically updates BED-TT.0 in the memory by {BED-cr-C.0.kn expanded by DISsel(BED-cr-C.0.kn) which is expanded by JUSend(DISsel(BED-cr-C.0.kn)), 1≦n≦N, 1≦kn≦Kn}. 20) A system executing a computer-implemented method according to claim 19 (explaining the BID-in-C.0.kn's being independent), which
(a) automatically prompts the user to select from the {BED-cr-C.0.k|1≦k≦K}, occurrences of which passed claim 4, a subset {BID-cr-C.0.k*, 1≦k*≦K*≦K};
(b) automatically determines, which value of k* identifies which value of k;
(c) automatically prompts the user, for any k*, through any combinations of BID-cr-C.0.k*′, 1≦k*′≠k*≦K*, thus enabling the user to state thereafter that and why BID-cr-C.0.k* is independent of any BID-cr-C.0.k*′ and combinations thereof;
(d) automatically appends {BID-cr-C.0.k*, 1≦k*≦K*} to {BED-cr-C.0.k, 1≦k≦K} as of (a);
(e) automatically appends this statement of (c), JUSind({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(f) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (e), 1≦k*≦K*}. 21) A system executing a computer-implemented method according to claim 20 (explaining the BID-in-C.0.kn′s being nonequivalent)
(a) automatically prompts the user, for any BID-cr-C.0.k*, through any doc.0-MUIs, thus that the user may state thereafter that and why it is non-equivalent to a BID-cr-C.0.k*′, 1≦k*′≠k*≦K*;
(b) automatically appends this statement of (a), JUSnequ({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(c) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (b), 1≦k*≦K*}. 22) A system executing a computer-implemented method according to claim 21 (showing the claimed invention being novel and nonobvious), which
(a) automatically prompts the user to execute the NANO test on the current PTRCT-DS;
(b) automatically appends the result of (a), JUSNANO({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(c) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (b), 1≦k*≦K*}. 23) A system executing a computer-implemented method according to claim 22 (showing the claimed invention being not natural law(s) only), which
(a) automatically prompts the user to state that and why the claimed invention is not natural law only;
(b) automatically appends this statement of (a), JUSNNLO({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(c) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (b), 1≦k*≦K*}. 24) A system executing a computer-implemented method according to claim 23 (showing the claimed invention being not idempotent), which
(a) automatically prompts the user to select from {BID-cr-C.0.k*, 1≦k*≦K*} a set {BID-cr-C.0.k″, 1≦k″≦K″≦K*};
(b) automatically prompts the user to execute the NANO test [set of (a)] on the current PTRCT-DS;
(c) automatically appends the set of (a) to {BID-cr-C.0.k*, 1≦k *—K*};
(d) automatically appends the result of (b), JUSNI({BID-cr-C.0.k″, 1≦k″≦K″}), to {BID-cr-C.0.k″, 1≦k″≦K″};
(e) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (c) and (d), 1≦k*≦K*}. 25) A system executing a computer-implemented method according to claim 24 (showing the claimed invention being not an abstract idea only), which
(a) automatically prompts the user to state the problem P.0 to be solved by the claimed invention;
(b) automatically prompts the user to identify the set of doc.0-MUIs describing this P.0, SoDIS(P.0);
(c) automatically appends this statement of (a) to {BID-cr-C.0.k″, 1≦kΔ≦K″};
(d) automatically appends SoDIS(P.0) to {BID-cr-C.0.k″, 1≦k″≦K″};
(e) automatically prompts the user, for any BID-cr-C.0.k″, through any doc.0-MUI, thus enabling it to state that this BID-cr-C.0.k″ is indispensable in the claimed invention for making it solve P.0;
(f) automatically appends this statement, JUSNAIO(P.0), to {BID-cr-C.0.k″, 1≦k″≦K″};
(g) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (a)-(f), 1≦k″≦K″}. 26) A system executing a computer-implemented method according to claim 16, subject to the additional limitations that part of the information input uses a given predesigned wording. 27) A system executing a computer-implemented method according to claim 16, subject to the additional limitations that part of the information input comprises confirmation of correctness by some given authority. 28) A system executing a computer-implemented method according to claim 16, subject to the additional limitations that part of the information input represents enrichments of various kinds of the PTR-DS. 29) A system executing a computer-implemented method according to claim 16, subject to the additional limitations that part of the information input represents given modifications of the volume of a set of alternatives. 30) A system executing a computer-implemented method according to claim 16, subject to the additional limitations that part of the information input represents given determinations of test specific execution sequences. | This patent (application) discloses for a claimed invention 10 tests (+their 5 controls) enabled by its inventive concepts, automatically prompting their user through exploratively checking its meeting the requirements stated by
§112, “well-definedness of its inventive concepts”, i.e. their 1) disaggregation into elementary ones, 2) disclosures, 3) definitiveness, and 4) enablement; §§102/103, “novelty/nonobviousness of this invention”, i.e. its 7) creativity/inventivity, after having assessed their 5) independence, and 6) non-equivalence; §101, “patent-eligibility of it and its claim”, i.e. its not only being 8) a natural law, or 9) idempotent, or 10) an abstract idea alias preemptive,
and then being automatically affirmatively reproducible in real-time.
These inventive concepts represent this claimed invention's legal and technical facts under 35 USC §§112/102/103/101—and other patent laws' peer sections, e.g. EPC's §§52-57, 69—required by Highest Courts for “model based” inventions, i.e. from advanced technologies.1) A computer-implemented method for updating a given data structure PTRCT-DS in a BAD-KR, both in given formats, by a set of Binary Elementary Disclosed (“BED”) inventive concepts of PTR's TT.0, called BED-TT.0, input to it by the user and by appendices to it and to BAD-KR for controlling an Innovation Expert System IES—the method (performing, for a claimed invention of PTR, its refined claim construction by here first disaggregating its compound inventive concepts, if these are not yet elementary) using a memory for storing the so updated PTRCT-DS, generated by executing this method on TT.0's compound inventive concepts BAD-X.0.n of TT.0 representing their mirror predicates BAD-X.0.n of its X.0.n, 1≦n≦N—which:
(a) writes the PTRCT-DS in a given BAD-KR into the memory
(b) automatically prompts the user to determine the KR_R&S_S to be obeyed during its execution, being
(b).1 either given by the IES as a default KR_R&S_S for both strategies, based on the BAD-KR of (a),
(b).2 or a KR_R&S_S input, in a given notation, by the user additionally to the BAD-KR of (a);
(c) automatically identifies in said PTRCT-DS and said KR_R&S_S, in given formats,
(c).1 for a given 0≦I≦IRSI, all document.i's and all their doc.i-MUIs, 0≦i≦l, and
(c).2 the document.CT in doc.0 and all its doc.CT-MUIs, and
(c).3 all elements X.0.n and their predicates BAD-X.0.n, 1≦n≦N, for any BAD-KR in KR_R&S_S;
(d) automatically performs for any BAD-KR in KR_R&S_S, controlled by this KR_R&S_S, the steps (d).1-(d).6:
(d).1 prompt the user to input a set of BED-cr-C.0.k's—in a given notation—of TT.0, 1≦k≦K, and
(d).2 prompt the user to disaggregate any BAD-X.0.n, 1≦n≦N, into a set {BED-cr-C.0.kn|1≦kn≦Kn}⊂{BED-cr-C.0.k|1≦k≦K}: BAD-X.0.n=Λ1sknKnBED-cr-C.0kn, whereby BED-cr-C.0.kn≠BED-cr-C.0.kn′∀n≠n′, and |{∪1≦n≦sN{BED-cr-C.0kn|1≦kn≦Kn}}|=K,
(d).3 prompt the user to input, in a given notation, ∀BAD-X.0.n a set of justifications by doc.0-/.CT-MUIs of this disaggregation into {BED-cr-C.0.kn|1≦kn≦Kn}, denoted as SoJUSdagr(BAD-X.0.n), 1≦n≦N;
(d).4 automatically append any SoJUSdagr(BAD-X.0.n) to BAD-X.0.n, 1≦n≦N;
(d).5 automatically generate BED-TT.0::={{BED-cr-C.0.k|1≦k≦K}}∪{{BED-cr-C.0.kn|1≦kn≦Kn}|1≦n≦N};
(d).6 automatically update the PTRCT-DS in the memory as of (a), according to (d).4 and (d).5. 2) A method according to claim 1 (explaining the lawful disclosures of the BED-cr-C.0.kn and completing them to BED-in-C.0.kn by), updating PTRCT-DS by the sets SoDIS(TT.0) and SoJUS(TT.0), which
(a) automatically prompts the user through each BED-cr-C.0.kn in each BAD-X.0.n of the KR at issue, 1≦kn≦Kn, 1≦n≦N—to identify for BED-cr-C.0.kn a set of disclosures, SoDIS(BED-C.0.kn)::={MUI.0s disclosing this BED-cr-C.0.kn}, SoDIS(BED-cr-C.0.kn) being justified by SoJUSdagr(BAD-X.0.n) and hence linked to it;
(b) automatically prompts the user to select at least one disclosure DISsel(BED-cr-C.0.kn) from any set SoDIS(BED-cr-C.0.kn) of (a), and to identify for it a set of legal justifications, SoJUS(DISsel(BED-cr-C.0.kn)) ::={I.CTs and/or MUI.CTs and MUI.0s justifying DISsel(BED-cr-C.0.kn)} and hence linked to it;
(c) automatically appends to any BED-cr-C.0.kn its SoDIS(BED-cr-C.0.kn), 1≦kn≦Kn, 1≦n≦N;
(d) automatically appends to any selected disclosure DISsel(BED-cr-C.0.kn) the SoJUS(DISsel(BED-cr-C.0.kn)) of (b), 1≦kn≦Kn, 1≦n≦N;
(e) automatically updates BED-TT.0 in the memory by {BED-cr-C.0.k expanded by its appendix (c)-(d), 1≦k≦K}. 3) A method according to claim 2 (explaining the definitiveness of the BED-in-C.0.kn involved in a means-plus-function-clause), which
(a) automatically prompts the user for any BED-cr-C.0.kn of claim 2 involved in a means-plus-function-clause, 1≦kn≦Kn, through its disclosures DISsel(BED-cr-C.0.mn), 1≦mn≦Mn, 1≦n≦N, until a DISsel0(BED-cr-C.0.mn) enables the user to state this BED-cr-C.0.kn′s definitiveness;
(b) automatically appends this statement of (a), JUSdef(DISsel0(BED-cr-C.0.mn)), to BED-cr-C.0.kn;
(c) automatically updates BED-TT.0 in the memory by {BED-cr-C.0.kn expanded by JUSdef(DISsel0(BED-cr-C.0.mn)), 1≦kn≦Kn, 1≦n≦N}. 4) A method according to claim 3 (explaining the BED-in-C.0.kn's being enabling), which
(a) automatically prompts the user through any of its BED-cr-C.0.kns and any of its disclosures DISsel(BED-cr-C.0.kn), 1≦kn≦Kn, 1≦n≦N—until one DISsel(BED-cr-C.0.kn) entitles the user to state that BED-cr-C.0.kn is enablingly disclosed;
(b) automatically appends this statement of (a), JUSend(DISsel(BED-cr-C.0.kn)), to DISsel(BED-cr-C.0.kn);
(c) automatically updates BED-TT.0 in the memory by {BED-cr-C.0.kn expanded by DISsel(BED-cr-C.0.kn) which is expanded by JUSend(DISsel(BED-cr-C.0.kn)), 1≦n≦N, 1≦kn≦Kn}. 5) A method according to claim 4 (explaining the BID-in-C.0.kn′s being independent), which
(a) automatically prompts the user to select from the {BED-cr-C.0.k l 1≦k≦K}, occurrences of which passed claim 4, a subset {BID-cr-C.0.k*, 1≦k*≦K*≦K};
(b) automatically determines, which value of k* identifies which value of k;
(c) automatically prompts the user, for any k*, through any combinations of BID-cr-C.0.k*′, 1≦k*′≠k*≦K*, thus enabling the user to state thereafter that and why BID-cr-C.0.k* is independent of any BID-cr-C.0.k*′ and combinations thereof;
(d) automatically appends {BID-cr-C.0.k*, 1≦k*≦K*} to {BED-cr-C.0.k, 1≦k≦K} as of (a);
(e) automatically appends this statement of (c), JUSind({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(f) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (e), 1≦k*≦K*}. 6) A method according to claim 5 (explaining the BID-in-C.0.kn′s being nonequivalent)
(a) automatically prompts the user, for any BID-cr-C.0.k*, through any doc.0-MUIs, thus that the user may state thereafter that and why it is non-equivalent to a BID-cr-C.0.k*′, 1≦k*′≠k*≦K*;
(b) automatically appends this statement of (a), JUSnequ({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(c) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (b), 1≦k*≦K*}. 7) A method according to claim 6 (showing the claimed invention being novel and nonobvious), which
(a) automatically prompts the user to execute the NANO test on the current PTRCT-DS;
(b) automatically appends the result of (a), JUSNANO({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(c) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (b), 1≦k*≦K*}. 8) A method according to claim 7 (showing the claimed invention being not natural law(s) only), which
(a) automatically prompts the user to state that and why the claimed invention is not natural law only;
(b) automatically appends this statement of (a), JUSNNLO({BID-cr-C.0.k*, 1≦k≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(c) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (b), 1≦k*≦K*}. 9) A method according to claim 8 (showing the claimed invention being not idempotent), which
(a) automatically prompts the user to select from {BID-cr-C.0.k*, 1≦k*≦K*} a set {BID-cr-C.0.k″, 1≦k″≦K″≦K*};
(b) automatically prompts the user to execute the NANO test [set of (a)] on the current PTRCT-DS;
(c) automatically appends the set of (a) to {BID-cr-C.0.k*, 1≦k*≦K*};
(d) automatically appends the result of (b), JUSNI({BID-cr-C.0.k″, 1≦k″≦K″}), to {BID-cr-C.0.k”, 1≦k″≦K″};
(e) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (c) and (d), 1≦k*≦K*}. 10) A method according to claim 9 (showing the claimed invention being not an abstract idea only), which
(a) automatically prompts the user to state the problem P.0 to be solved by the claimed invention;
(b) automatically prompts the user to identify the set of doc.0-MUIs describing this P.0, SoDIS(P.0);
(c) automatically appends this statement of (a) to {BID-cr-C.0.k″, 1≦k″K″};
(d) automatically appends SoDIS(P.0) to {BID-cr-C.0.k″, 1≦k″≦K″};
(e) automatically prompts the user, for any BID-cr-C.0.k″, through any doc.0-MUI, thus enabling it to state that this BID-cr-C.0.k″ is indispensable in the claimed invention for making it solve P.0;
(f) automatically appends this statement, JUSNAIO(P.0), to {BID-cr-C.0.k″, 1≦k″≦K″};
(g) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (a)-(f), 1≦k″≦K″}. 11) A method according to claim 1, subject to the additional limitations that part of the information input uses a given predesigned wording. 12) A method according to claim 1, subject to the additional limitations that part of the information input comprises confirmation of correctness by some given authority. 13) A method according to claim 1, subject to the additional limitations that part of the information input represents enrichments of various kinds of the PTR-DS. 14) A method according to claim 1, subject to the additional limitations that part of the information input represents given modifications of the volume of a set of alternatives. 15) A method according to claim 1, subject to the additional limitations that part of the information input represents given determinations of test specific execution sequences. 16) A system executing a computer-implemented method for updating a given data structure PTRCT-DS in a BAD-KR, both in given formats, by a set of Binary Elementary Disclosed (“BED”) inventive concepts of PTR's TT.0, called BED-TT.0, input to it by the user and by appendices to it and to BAD-KR for controlling an Innovation Expert System IES—the method (performing, for a claimed invention of PTR, its refined claim construction by here first disaggregating its compound inventive concepts, if these are not yet elementary) using a memory for storing the so updated PTRCT-DS, generated by executing this method on TT.0's compound inventive concepts BAD-X.0.n of TT.0 representing their mirror predicates BAD-X.0.n of its X.0.n, 1≦n≦N—which:
(a) writes the PTRCT-DS in a given BAD-KR into the memory
(b) automatically prompts the user to determine the KR_R&S_S to be obeyed during its execution, being
(b).3 either given by the IES as a default KR_R&S_S for both strategies, based on the BAD-KR of (a),
(b).4 or a KR_R&S_S input, in a given notation, by the user additionally to the BAD-KR of (a);
(c) automatically identifies in said PTRCT-DS and said KR_R&S_S, in given formats,
(c).4 for a given 0≦I≦IRSI, all document's and all their doc.i-MUIs, 0≦i≦Il, and
(c).5 the document.CT in doc.0 and all its doc.CT-MUIs, and
(c).6 all elements X.0.n and their predicates BAD-X.0.n, 1≦n≦N, for any BAD-KR in KR_R&S_S;
(d) automatically performs for any BAD-KR in KR_R&S_S, controlled by this KR_R&S_S, the steps (d).1-(d).6:
(d).7 prompt the user to input a set of BED-cr-C.0.k′s—in a given notation—of TT.0, 1≦k≦K, and
(d).8 prompt the user to disaggregate any BAD-X.0.n, 1≦n≦N, into a set {BED-cr-C.0.kn|1≦kn≦Kn}⊂{BED-cr-C.0.k|1≦k≦K}: BAD-X.0.n=Λ1≦kn≦KnBED-cr-C.0.kn, whereby BED-cr-C.0.kn≠BED-cr-C.0.kn′∀V n′, and |∪ 1≦n≦N{BED-cr-C.0.kn|1≦kn≦Kn}}l=K,
(d).9 prompt the user to input, in a given notation, ∀BAD-X.0.n a set of justifications by doc.0-/.CT-MUIs of this disaggregation into {BED-cr-C.0.kn|1≦kn≦Kn}, denoted as SoJUSdagr(BAD-X.0.n), 1≦n≦N;
(d).10 automatically append any SoJUSdagr(BAD-X.0.n) to BAD-X.0.n, 123 n≦N;
(d).11 automatically generate BED-TT.0::={{BED-cr-C.0.k|1≦k≦K}}∪{{BED-cr-C.0.kn|1≦kn≦Kn}|1≦n≦N};
(d).12 automatically update the PTRCT-DS in the memory as of (a), according to (d).4 and (d).5. 17) A system executing a computer-implemented method according to claim 16 (explaining the lawful disclosures of the BED-cr-C.0.kn and completing them to BED-in-C.0.kn by), updating PTRCT-DS by the sets SoDIS(TT.0) and SoJUS(TT.0), which
(a) automatically prompts the user through each BED-cr-C.0.kn in each BAD-X.0.n of the KR at issue, 1≦kn≦Kn, 1≦n≦N—to identify for BED-cr-C.0.kn a set of disclosures, SoDIS(BED-C.0.kn)::={MUI.0s disclosing this BED-cr-C.0.kn}, SoDIS(BED-cr-C.0.kn) being justified by SoJUSdagr(BAD-X.0.n) and hence linked to it;
(b) automatically prompts the user to select at least one disclosure DISsel(BED-cr-C.0.kn) from any set SoDIS(BED-cr-C.0.kn) of (a), and to identify for it a set of legal justifications, SoJUS(DISsel(BED-cr-C.0.kn))::=I.CTs and/or MUI.CTs and MUI.0s justifying DISsel(BED-cr-C.0.kn)} and hence linked to it;
(c) automatically appends to any BED-cr-C.0.kn its SoDIS(BED-cr-C.0.kn), 1≦kn≦Kn, 1≦n≦N;
(d) automatically appends to any selected disclosure DISsel(BED-cr-C.0.kn) the SoJUS(DISsel(BED-cr-C.0.kn)) of (b), 1≦kn≦Kn, 1≦n≦N;
(e) automatically updates BED-TT.0 in the memory by {BED-cr-C.0.k expanded by its appendix (c)-(d), 1≦k≦K}. 18) A system executing a computer-implemented method according to claim 17 (explaining the definitiveness of the BED-in-C.0.kn involved in a means-plus-function-clause), which
(a) automatically prompts the user for any BED-cr-C.0.kn of claim 17 involved in a means-plus-function-clause, 1≦kn≦Kn, through its disclosures DISsel(BED-cr-C.0.mn), 1≦mn≦Mn, 1≦n≦N, until a DISsel0(BED-cr-C.0.mn) enables the user to state this BED-cr-C.0.kn′s definitiveness;
(b) automatically appends this statement of (a), JUSdef(DISsel0(BED-cr-C.0.mn)), to BED-cr-C.0.kn;
(c) automatically updates BED-TT.0 in the memory by {BED-cr-C.0.kn expanded by JUSdef(DISsel0(BED-cr-C.0.mn)), 1≦kn≦Kn, 1≦n≦N}. 19) A system executing a computer-implemented method according to claim 18 (explaining the BED-in-C.0.kn′s being enabling), which
(a) automatically prompts the user through any of its BED-cr-C.0.kns and any of its disclosures DISsel(BED-cr-C.0.kn), 1≦kn≦Kn, 1≦n≦N—until one DISsel(BED-cr-C.0.kn) entitles the user to state that BED-cr-C.0.kn is enablingly disclosed;
(b) automatically appends this statement of (a), JUSend(DISsel(BED-cr-C.0.kn)), to DISsel(BED-cr-C.0.kn);
(c) automatically updates BED-TT.0 in the memory by {BED-cr-C.0.kn expanded by DISsel(BED-cr-C.0.kn) which is expanded by JUSend(DISsel(BED-cr-C.0.kn)), 1≦n≦N, 1≦kn≦Kn}. 20) A system executing a computer-implemented method according to claim 19 (explaining the BID-in-C.0.kn's being independent), which
(a) automatically prompts the user to select from the {BED-cr-C.0.k|1≦k≦K}, occurrences of which passed claim 4, a subset {BID-cr-C.0.k*, 1≦k*≦K*≦K};
(b) automatically determines, which value of k* identifies which value of k;
(c) automatically prompts the user, for any k*, through any combinations of BID-cr-C.0.k*′, 1≦k*′≠k*≦K*, thus enabling the user to state thereafter that and why BID-cr-C.0.k* is independent of any BID-cr-C.0.k*′ and combinations thereof;
(d) automatically appends {BID-cr-C.0.k*, 1≦k*≦K*} to {BED-cr-C.0.k, 1≦k≦K} as of (a);
(e) automatically appends this statement of (c), JUSind({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(f) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (e), 1≦k*≦K*}. 21) A system executing a computer-implemented method according to claim 20 (explaining the BID-in-C.0.kn′s being nonequivalent)
(a) automatically prompts the user, for any BID-cr-C.0.k*, through any doc.0-MUIs, thus that the user may state thereafter that and why it is non-equivalent to a BID-cr-C.0.k*′, 1≦k*′≠k*≦K*;
(b) automatically appends this statement of (a), JUSnequ({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(c) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (b), 1≦k*≦K*}. 22) A system executing a computer-implemented method according to claim 21 (showing the claimed invention being novel and nonobvious), which
(a) automatically prompts the user to execute the NANO test on the current PTRCT-DS;
(b) automatically appends the result of (a), JUSNANO({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(c) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (b), 1≦k*≦K*}. 23) A system executing a computer-implemented method according to claim 22 (showing the claimed invention being not natural law(s) only), which
(a) automatically prompts the user to state that and why the claimed invention is not natural law only;
(b) automatically appends this statement of (a), JUSNNLO({BID-cr-C.0.k*, 1≦k*≦K*}), to {BID-cr-C.0.k*, 1≦k*≦K*};
(c) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (b), 1≦k*≦K*}. 24) A system executing a computer-implemented method according to claim 23 (showing the claimed invention being not idempotent), which
(a) automatically prompts the user to select from {BID-cr-C.0.k*, 1≦k*≦K*} a set {BID-cr-C.0.k″, 1≦k″≦K″≦K*};
(b) automatically prompts the user to execute the NANO test [set of (a)] on the current PTRCT-DS;
(c) automatically appends the set of (a) to {BID-cr-C.0.k*, 1≦k *—K*};
(d) automatically appends the result of (b), JUSNI({BID-cr-C.0.k″, 1≦k″≦K″}), to {BID-cr-C.0.k″, 1≦k″≦K″};
(e) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (c) and (d), 1≦k*≦K*}. 25) A system executing a computer-implemented method according to claim 24 (showing the claimed invention being not an abstract idea only), which
(a) automatically prompts the user to state the problem P.0 to be solved by the claimed invention;
(b) automatically prompts the user to identify the set of doc.0-MUIs describing this P.0, SoDIS(P.0);
(c) automatically appends this statement of (a) to {BID-cr-C.0.k″, 1≦kΔ≦K″};
(d) automatically appends SoDIS(P.0) to {BID-cr-C.0.k″, 1≦k″≦K″};
(e) automatically prompts the user, for any BID-cr-C.0.k″, through any doc.0-MUI, thus enabling it to state that this BID-cr-C.0.k″ is indispensable in the claimed invention for making it solve P.0;
(f) automatically appends this statement, JUSNAIO(P.0), to {BID-cr-C.0.k″, 1≦k″≦K″};
(g) automatically updates BED-TT.0 in the memory by {BID-cr-C.0.k* as expanded by (a)-(f), 1≦k″≦K″}. 26) A system executing a computer-implemented method according to claim 16, subject to the additional limitations that part of the information input uses a given predesigned wording. 27) A system executing a computer-implemented method according to claim 16, subject to the additional limitations that part of the information input comprises confirmation of correctness by some given authority. 28) A system executing a computer-implemented method according to claim 16, subject to the additional limitations that part of the information input represents enrichments of various kinds of the PTR-DS. 29) A system executing a computer-implemented method according to claim 16, subject to the additional limitations that part of the information input represents given modifications of the volume of a set of alternatives. 30) A system executing a computer-implemented method according to claim 16, subject to the additional limitations that part of the information input represents given determinations of test specific execution sequences. | 2,100 |
6,040 | 6,040 | 15,033,200 | 2,113 | Various methods and systems for analyzing event log elements are described that utilize numerous techniques to group and compare the large event log files logged by different computers and programs. In one example, a method includes receiving a first set of event log elements from a plurality of computers, and receiving a second set of event log elements from a target computer. The method continues by comparing the first set of event log elements and the second set of event log elements to identify a configuration difference between the target computer and the plurality of computers. The differences can be displayed to a user of the target computer. | 1. A method, comprising:
receiving a first set of event log elements from a plurality of computers; receiving a second set of event log elements from a target computer; comparing the first set of event log elements and the second set of event log elements to identify a configuration difference between the target computer and the plurality of computers; and displaying the difference to a user of the target computer. 2. The method of claim 1, wherein the event log elements are compiled through clustering into message templates before comparing. 3. The method of claim 2, wherein each set of event log elements are assigned to a message cluster according to a message template of similarity between the respective text of the event log element and the template text of the message cluster. 4. The method of claim 2, wherein a message cluster is periodically divided on the basis of pre-determined splitting criteria that includes greater than a minimum number of event messages being assigned to a message cluster. 5. The method of claim 2, wherein the clustered message templates are used in generating a set of machine-readable atoms grouped by flows, wherein:
an atom is a set of elements that is common in a plurality of data sets such that a new or existing set can be sparsely represented using such atoms. 6. The method of claim 5, wherein generating a set of atoms comprises minimizing a cost function using an iterative process to identify the one or more atoms. 7. The method of claim 5, wherein training data representing an initial data set including text representing at least one concept embodied by the data set is received; the training data is processed in order to generate a set of atoms, each atom comprising at least one word that represents one or more concepts of the initial data set: and wherein an initial data set represents a user, and an atom is used in order to predict an item of interest for the user. 8. A system for analyzing event log elements, comprising:
a storage engine to receive and store system event log elements as machine-readable data sets; a comparison engine to compare event log elements from a plurality of computers to event log elements from a target computer; a differentiation engine to identify a configuration difference between the event log elements from the target computer and the event log elements from the plurality of computers; and a display engine to display the configuration difference that is identified. 9. The system of claim 8, wherein the comparison engine compares event log elements based on pre-determined distribution parameters that can be configured and reconfigured. 10. The system of claim 9, wherein the distribution parameters are user defined based on event log error messages received at the target computer. 11. The system of claim 8, wherein the comparison engine organizes the event leg elements into sets of message clusters and compares the message clusters. 12. The system of claim 8, wherein the comparison engine organizes the event log elements by atomic flows and compares the flows. 13. A non-transitory, computer-readable medium, comprising instruction configured to direct a processor to:
receive system event log elements as organized data sets; compare the received event log elements of a target processor on a network of processors to other processors on the network of processors; and automatically identity configuration differences between the event log element distribution of the target network processor and the event log element distribution of the entire network system of processors. 14. The non-transitory, computer-readable medium of claim 13, wherein the target network processor comprises a personal computer, a server, a digital printer, or any other processor connected to the network system of processors. 15. The non-transitory, computer readable medium of claim 13, wherein the target network processor requires troubleshooting, and the event log elements of interest relate to error logs that are being logged by the target network processor. | Various methods and systems for analyzing event log elements are described that utilize numerous techniques to group and compare the large event log files logged by different computers and programs. In one example, a method includes receiving a first set of event log elements from a plurality of computers, and receiving a second set of event log elements from a target computer. The method continues by comparing the first set of event log elements and the second set of event log elements to identify a configuration difference between the target computer and the plurality of computers. The differences can be displayed to a user of the target computer.1. A method, comprising:
receiving a first set of event log elements from a plurality of computers; receiving a second set of event log elements from a target computer; comparing the first set of event log elements and the second set of event log elements to identify a configuration difference between the target computer and the plurality of computers; and displaying the difference to a user of the target computer. 2. The method of claim 1, wherein the event log elements are compiled through clustering into message templates before comparing. 3. The method of claim 2, wherein each set of event log elements are assigned to a message cluster according to a message template of similarity between the respective text of the event log element and the template text of the message cluster. 4. The method of claim 2, wherein a message cluster is periodically divided on the basis of pre-determined splitting criteria that includes greater than a minimum number of event messages being assigned to a message cluster. 5. The method of claim 2, wherein the clustered message templates are used in generating a set of machine-readable atoms grouped by flows, wherein:
an atom is a set of elements that is common in a plurality of data sets such that a new or existing set can be sparsely represented using such atoms. 6. The method of claim 5, wherein generating a set of atoms comprises minimizing a cost function using an iterative process to identify the one or more atoms. 7. The method of claim 5, wherein training data representing an initial data set including text representing at least one concept embodied by the data set is received; the training data is processed in order to generate a set of atoms, each atom comprising at least one word that represents one or more concepts of the initial data set: and wherein an initial data set represents a user, and an atom is used in order to predict an item of interest for the user. 8. A system for analyzing event log elements, comprising:
a storage engine to receive and store system event log elements as machine-readable data sets; a comparison engine to compare event log elements from a plurality of computers to event log elements from a target computer; a differentiation engine to identify a configuration difference between the event log elements from the target computer and the event log elements from the plurality of computers; and a display engine to display the configuration difference that is identified. 9. The system of claim 8, wherein the comparison engine compares event log elements based on pre-determined distribution parameters that can be configured and reconfigured. 10. The system of claim 9, wherein the distribution parameters are user defined based on event log error messages received at the target computer. 11. The system of claim 8, wherein the comparison engine organizes the event leg elements into sets of message clusters and compares the message clusters. 12. The system of claim 8, wherein the comparison engine organizes the event log elements by atomic flows and compares the flows. 13. A non-transitory, computer-readable medium, comprising instruction configured to direct a processor to:
receive system event log elements as organized data sets; compare the received event log elements of a target processor on a network of processors to other processors on the network of processors; and automatically identity configuration differences between the event log element distribution of the target network processor and the event log element distribution of the entire network system of processors. 14. The non-transitory, computer-readable medium of claim 13, wherein the target network processor comprises a personal computer, a server, a digital printer, or any other processor connected to the network system of processors. 15. The non-transitory, computer readable medium of claim 13, wherein the target network processor requires troubleshooting, and the event log elements of interest relate to error logs that are being logged by the target network processor. | 2,100 |
6,041 | 6,041 | 15,990,741 | 2,177 | Implementations include a batch-optimized render and fetch architecture. An example method performed by the architecture includes receiving a request from a batch process to render a web page and initializing a virtual clock and a task list for rendering the web page. The virtual clock stands still when a request for an embedded item is outstanding and when a task is ready to run. The method may also include generating a rendering result for the web page when the virtual clock matches a run time for a stop task in the task list, and providing the rendering result to the batch process. Another example method includes receiving a request from a batch process to render a web page, identifying an embedded item in the web page, and determining, based on a rewrite rule, that the embedded item has content that is duplicative of content for a previously fetched embedded item. | 1. A computer system comprising:
at least one processor; and a batch rendering engine configured to:
receive a request to render a web page from a requesting process,
initialize a virtual clock for the web page,
generate a task list for rendering the web page, wherein each task in the task list has an associated start time,
adding a stop task to the task list, the stop task having a start time set to a predetermined time,
perform the tasks in the task list according to the virtual clock for the web page, wherein the virtual clock for the web page advances by being set to a time represented by a next-occurring task in a task list for the web page, the virtual clock remaining unchanged while a pending task in the task list has a run time matching the virtual clock
generate a rendering result for the web page when the virtual clock-matches a start time for the stop task in the task list, and
provide the rendering result to the requesting process. 2. The system of claim 1, wherein the predetermined time is a predetermined time added to the virtual clock. 3. The system of claim 1, wherein the task list includes a first task with a first start time and a second task with the first start time, the first task being a fetch of an embedded resource, and the rendering engine is further configured to:
request the embedded resource from a server; and work on the second task while waiting for a response to the request. 4. The system of claim 3, wherein the rendering engine is further configured to:
receive content for the embedded resource from the server; and add a task to the task list, responsive to receiving the content for the embedded item, the task having a respective start time set equal to a current value of the virtual clock. 5. The system of claim 4, wherein the task added to the task list runs a script identified in the content for the embedded item. 6. The system of claim 4, wherein the task added to the task list fetches a second embedded item identified in the content. 7. The system of claim 1, wherein the actual time spent processing the task list is less than the predetermined time for a web page that lacks an embedded item. 8. The system of claim 1, wherein the start time of the stop task is set independent of start times of other tasks in the task list. 9. A method comprising:
receiving a request, from a requesting process, to render a web page; initializing, using at least one processor, a virtual clock for the web page; generating a task list for rendering the web page, wherein each task has an associated start time; adding a stop task with a start time that is independent of a final task in the task list; performing the tasks in the task list according to the virtual clock for the web page, wherein the virtual clock for the web page advances to a time represented by a next-occurring task in the task list ; generating, using the at least one processor, a rendering result for the web page when the virtual clock matches a run time for a stop task in the task list; and providing the rendering result to the requesting process. 10. The method of claim 9, wherein the start time of the stop task is set to a predetermined time. 11. The method of claim 10, wherein the predetermined time is a time added to the initialized virtual clock. 12. The method of claim 10, wherein the predetermined time for the stop task represents an average web page loading time. 13. The method of claim 9, further comprising:
identifying an embedded item in the web page; requesting content for the embedded item; receiving, in response to the request, the content; and adding a task to the task list for processing the content, the added task having a start time equal to the virtual clock. 14. The method of claim 13, wherein outstanding requests for embedded items are not complete tasks. 15. The method of claim 13, wherein requesting the content for the embedded item includes:
responsive to a task to the task list for processing the content, the added task having a start time equal to the virtual clock. 16. The method of claim 13, wherein the actual time spent processing the task list is greater than the predetermined time due to an amount of time waiting for the content.
applying a rewrite rule to a URL of the embedded item, the rewrite rule including a template and a redirect URL; and responsive to determining that the URL of the embedded item matches the template, substituting the redirect URL for the URL of the embedded item so that the content corresponds to the redirect URL. 17. The method of claim 9, wherein the virtual clock advances to a time represented by the next-occurring task in the task list upon determining that all tasks with a start time equal to the virtual clock are complete. | Implementations include a batch-optimized render and fetch architecture. An example method performed by the architecture includes receiving a request from a batch process to render a web page and initializing a virtual clock and a task list for rendering the web page. The virtual clock stands still when a request for an embedded item is outstanding and when a task is ready to run. The method may also include generating a rendering result for the web page when the virtual clock matches a run time for a stop task in the task list, and providing the rendering result to the batch process. Another example method includes receiving a request from a batch process to render a web page, identifying an embedded item in the web page, and determining, based on a rewrite rule, that the embedded item has content that is duplicative of content for a previously fetched embedded item.1. A computer system comprising:
at least one processor; and a batch rendering engine configured to:
receive a request to render a web page from a requesting process,
initialize a virtual clock for the web page,
generate a task list for rendering the web page, wherein each task in the task list has an associated start time,
adding a stop task to the task list, the stop task having a start time set to a predetermined time,
perform the tasks in the task list according to the virtual clock for the web page, wherein the virtual clock for the web page advances by being set to a time represented by a next-occurring task in a task list for the web page, the virtual clock remaining unchanged while a pending task in the task list has a run time matching the virtual clock
generate a rendering result for the web page when the virtual clock-matches a start time for the stop task in the task list, and
provide the rendering result to the requesting process. 2. The system of claim 1, wherein the predetermined time is a predetermined time added to the virtual clock. 3. The system of claim 1, wherein the task list includes a first task with a first start time and a second task with the first start time, the first task being a fetch of an embedded resource, and the rendering engine is further configured to:
request the embedded resource from a server; and work on the second task while waiting for a response to the request. 4. The system of claim 3, wherein the rendering engine is further configured to:
receive content for the embedded resource from the server; and add a task to the task list, responsive to receiving the content for the embedded item, the task having a respective start time set equal to a current value of the virtual clock. 5. The system of claim 4, wherein the task added to the task list runs a script identified in the content for the embedded item. 6. The system of claim 4, wherein the task added to the task list fetches a second embedded item identified in the content. 7. The system of claim 1, wherein the actual time spent processing the task list is less than the predetermined time for a web page that lacks an embedded item. 8. The system of claim 1, wherein the start time of the stop task is set independent of start times of other tasks in the task list. 9. A method comprising:
receiving a request, from a requesting process, to render a web page; initializing, using at least one processor, a virtual clock for the web page; generating a task list for rendering the web page, wherein each task has an associated start time; adding a stop task with a start time that is independent of a final task in the task list; performing the tasks in the task list according to the virtual clock for the web page, wherein the virtual clock for the web page advances to a time represented by a next-occurring task in the task list ; generating, using the at least one processor, a rendering result for the web page when the virtual clock matches a run time for a stop task in the task list; and providing the rendering result to the requesting process. 10. The method of claim 9, wherein the start time of the stop task is set to a predetermined time. 11. The method of claim 10, wherein the predetermined time is a time added to the initialized virtual clock. 12. The method of claim 10, wherein the predetermined time for the stop task represents an average web page loading time. 13. The method of claim 9, further comprising:
identifying an embedded item in the web page; requesting content for the embedded item; receiving, in response to the request, the content; and adding a task to the task list for processing the content, the added task having a start time equal to the virtual clock. 14. The method of claim 13, wherein outstanding requests for embedded items are not complete tasks. 15. The method of claim 13, wherein requesting the content for the embedded item includes:
responsive to a task to the task list for processing the content, the added task having a start time equal to the virtual clock. 16. The method of claim 13, wherein the actual time spent processing the task list is greater than the predetermined time due to an amount of time waiting for the content.
applying a rewrite rule to a URL of the embedded item, the rewrite rule including a template and a redirect URL; and responsive to determining that the URL of the embedded item matches the template, substituting the redirect URL for the URL of the embedded item so that the content corresponds to the redirect URL. 17. The method of claim 9, wherein the virtual clock advances to a time represented by the next-occurring task in the task list upon determining that all tasks with a start time equal to the virtual clock are complete. | 2,100 |
6,042 | 6,042 | 15,339,571 | 2,184 | A physiological data collection device obtains physiological data from a subject interface on a subject. The physiological data collection device includes a data connector such as a USB connector for connecting directly to a computer. When the physiological data collection device is connected to the computer, the physiological data is uploaded to a remote data processing center for computer-based analysis and review by a medical professional. A report can be provided to the subject based on the analysis and review. When the subject interface is physically connected to the physiological data collection device, the data connector is prevented from being connected to an external device such as the computer. | 1-27. (canceled) 28. An ECG interface comprising:
a first electrode lead and a second electrode lead, each having a first end and a second end; a first lead socket and a second lead socket mechanically and electrically connected to the first ends of the first and second electrode leads, respectively, wherein each of the first and second lead sockets is configured to connect to an ECG electrode; and a connector head mechanically and electrically connected to the second ends of the first and second electrode leads, the connector head comprising a connector receptacle configured to receive a male USB connector. 29. The ECG interface of claim 28, wherein the connector head comprises a plurality of electrical contacts in electrical communication with the first and second electrode leads. 30. The ECG interface of claim 29, wherein the plurality of electrical contacts includes five electrical contacts. 31. The ECG interface of claim 29, wherein a first contact of the plurality of electrical contacts is in electrical communication with the first electrode lead. 32. The ECG interface of claim 31, wherein a second contact of the plurality of electrical contacts is in electrical communication with the second electrode lead. 33. The ECG interface of claim 32, wherein the ECG interface includes a power source. 34. The ECG interface of claim 29, wherein the connector head comprises an engagement mechanism for supporting a weight of a portable ECG data collection unit. 35. The ECG interface of claim 34, wherein the engagement mechanism comprises a clip. 36. The ECG interface of claim 35, wherein the engagement mechanism comprises a tab which, when pressed, disengages the clip from the data collection unit. 37. The ECG interface of claim 36, wherein the ECG interface further comprises a lanyard connected to the connector head. 38. The ECG interface of claim 37, wherein the connector head comprises a male electrode connector. 39. The ECG interface of claim 38, wherein the male electrode connector comprises the plurality of electrical contacts. 40. A lead-wire set comprising an electrode lead having a first end and a second end, the first end terminating in a socket for connecting to an ECG electrode, and the second end terminating in a connector head having a connector receptacle configured to receive a male USB connector. 41. The lead-wire set of claim 40, wherein the connector head comprises at least one electrical contact in electrical communication with the electrode lead. 42. The lead-wire set of claim 41, wherein the connector head comprises five electrical contacts. 43. The lead-wire set of claim 41, wherein the ECG interface includes a power source. 44. The lead-wire set of claim 41, wherein the connector head comprises an engagement mechanism for supporting a weight of a portable ECG data collection unit. 45. The lead-wire set of claim 44, wherein the engagement mechanism comprises a clip. 46. The lead-wire set of claim 45, wherein the engagement mechanism comprises a tab which, when pressed, disengages the clip from the ECG data collection unit. 47. The ECG interface of claim 46, wherein the connector head comprises a male electrode connector. | A physiological data collection device obtains physiological data from a subject interface on a subject. The physiological data collection device includes a data connector such as a USB connector for connecting directly to a computer. When the physiological data collection device is connected to the computer, the physiological data is uploaded to a remote data processing center for computer-based analysis and review by a medical professional. A report can be provided to the subject based on the analysis and review. When the subject interface is physically connected to the physiological data collection device, the data connector is prevented from being connected to an external device such as the computer.1-27. (canceled) 28. An ECG interface comprising:
a first electrode lead and a second electrode lead, each having a first end and a second end; a first lead socket and a second lead socket mechanically and electrically connected to the first ends of the first and second electrode leads, respectively, wherein each of the first and second lead sockets is configured to connect to an ECG electrode; and a connector head mechanically and electrically connected to the second ends of the first and second electrode leads, the connector head comprising a connector receptacle configured to receive a male USB connector. 29. The ECG interface of claim 28, wherein the connector head comprises a plurality of electrical contacts in electrical communication with the first and second electrode leads. 30. The ECG interface of claim 29, wherein the plurality of electrical contacts includes five electrical contacts. 31. The ECG interface of claim 29, wherein a first contact of the plurality of electrical contacts is in electrical communication with the first electrode lead. 32. The ECG interface of claim 31, wherein a second contact of the plurality of electrical contacts is in electrical communication with the second electrode lead. 33. The ECG interface of claim 32, wherein the ECG interface includes a power source. 34. The ECG interface of claim 29, wherein the connector head comprises an engagement mechanism for supporting a weight of a portable ECG data collection unit. 35. The ECG interface of claim 34, wherein the engagement mechanism comprises a clip. 36. The ECG interface of claim 35, wherein the engagement mechanism comprises a tab which, when pressed, disengages the clip from the data collection unit. 37. The ECG interface of claim 36, wherein the ECG interface further comprises a lanyard connected to the connector head. 38. The ECG interface of claim 37, wherein the connector head comprises a male electrode connector. 39. The ECG interface of claim 38, wherein the male electrode connector comprises the plurality of electrical contacts. 40. A lead-wire set comprising an electrode lead having a first end and a second end, the first end terminating in a socket for connecting to an ECG electrode, and the second end terminating in a connector head having a connector receptacle configured to receive a male USB connector. 41. The lead-wire set of claim 40, wherein the connector head comprises at least one electrical contact in electrical communication with the electrode lead. 42. The lead-wire set of claim 41, wherein the connector head comprises five electrical contacts. 43. The lead-wire set of claim 41, wherein the ECG interface includes a power source. 44. The lead-wire set of claim 41, wherein the connector head comprises an engagement mechanism for supporting a weight of a portable ECG data collection unit. 45. The lead-wire set of claim 44, wherein the engagement mechanism comprises a clip. 46. The lead-wire set of claim 45, wherein the engagement mechanism comprises a tab which, when pressed, disengages the clip from the ECG data collection unit. 47. The ECG interface of claim 46, wherein the connector head comprises a male electrode connector. | 2,100 |
6,043 | 6,043 | 13,967,301 | 2,124 | In embodiments, a sentiment analyzer identifies a first event and accesses a first set of messages. The sentiment analyzer associates the first set of messages with the first event and analyzes the messages to identify a set of sentiment features. The set of sentiment features is used to analyze a second set of messages to form a prediction associated with a second event. The prediction may be used to facilitate an event-related service. | 1. A computer-implemented method for forming a prediction associated with an event, the method comprising:
accessing, using a computing device having a processor and a memory, event information from an event information source; identifying, using the processor and the event information, a first event based on event criteria; accessing, using the computing device, a first set of messages from a message source, wherein the first set of messages is generated by a plurality of messaging users; associating, using the processor, the first set of messages with the first event; identifying, using the processor, a set of sentiment features, the set of sentiment features comprising at least one text feature representing a user sentiment associated with the first event, wherein identifying the set of sentiment features comprises analyzing the first set of messages based on the first event; storing the set of sentiment features in a dynamic dictionary in the memory; accessing, using the computing device, a second set of messages from the message source; analyzing, using the processor, the second set of messages, based on the set of sentiment features, to form a prediction associated with a second event; and storing the prediction in the memory. 2. The method of claim 1, further comprising facilitating an event-based service based on the prediction. 3. The method of claim 2, wherein the second event comprises a gain event associated with a stock price or a loss event associated with the stock price. 4. The method of claim 3, wherein facilitating the event-based service comprises establishing a securities trading strategy based on the prediction, the securities trading strategy comprising:
taking a long position with respect to the stock if the second event comprises a gain event; and taking a short position with respect to the stock if the second event comprises a loss event. 5. The method of claim 1, wherein the set of sentiment features comprises at least one of a phrase, a word, a character, and a special notation. 6. The method of claim 1, wherein at least one of the first and second sets of messages comprises social media messages. 7. The method of claim 6, wherein the social media messages comprise tweets. 8. The method of claim 6, wherein each of the first set of social media messages was generated prior to the occurrence of the first event. 9. The method of claim 1, further comprising updating the dynamic dictionary by identifying an additional set of sentiment features based upon the prediction, and storing the additional set of sentiment features in the dynamic dictionary. 10. The method of claim 1, wherein analyzing the first set of messages comprises:
assigning, based on the event criteria, a label to each of the first set of messages to create a first set of labeled messages, wherein the label corresponds to a predetermined sentiment value; training a classifier using the first set of labeled messages; and identifying the set of sentiment features using the classifier. 11. The method of claim 10, wherein analyzing the second set of messages comprises:
identifying, using the classifier, a sentiment value for each of the second set of messages; aggregating at least a portion of the identified sentiment values; determining a sentiment score based on the aggregated identified sentiment values; and forming the prediction based on the sentiment score. 12. The method of claim 11, wherein the sentiment score comprises a number in the range of −1 to 1. 13. The method of claim 1, wherein the first event comprises a gain event associated with a stock price or a loss event associated with the stock price,
wherein a gain event is defined as a relative increase of the stock price, over a period of time, that exceeds three percent more than a return associated with a market index; and wherein a loss event is defined as a relative decrease of the stock price, over a period of time, that exceeds three percent less than the return associated with the market index. 14. The method of claim 13, wherein the market index comprises at least one of the S&P 500, the AMEX Composite, the NASDAQ Global Market Composite, the NYSE Composite, the Russell 1000, the Wilshire 5000, the Dow Industrials, the KBW Bank Index, the NASDAQ Financial-100, the PHLX Chemicals Sector, the Russell 1000 Growth, and the SIG Energy MLP Index. 15. The method of claim 13, wherein assigning the label to each of the first set of messages comprises:
labeling each of the first set of messages as positive when the first event is a gain event; and labeling each of the first set of messages as negative when the first event is a loss event. 16. The method of claim 1, wherein analyzing the first set of messages comprises applying an autoregressive model. 17. A computer-implemented method for forming a prediction associated with an event, the method comprising:
accessing, using a computing device having a processor and a memory, a set of messages from a message source, wherein the set of messages is generated by a plurality of messaging users; accessing, using the processor, a dynamic dictionary stored in the memory, the dynamic dictionary comprising a set of sentiment features, the set of sentiment features comprising at least one text feature representing a user sentiment associated with a first event; analyzing, using the processor, the set of messages, based on the set of sentiment features, to form a prediction associated with a second event; and storing the prediction in the memory. 18. The method of claim 17, further comprising facilitating an event-related service based on the prediction. 19. The method of claim 17, wherein the set of messages comprises social media messages. 20. The method of claim 19, wherein the social media messages comprises tweets. 21. A system for predicting events, the system comprising:
a server configured to receive, from a message source, a plurality of messages generated by a plurality of messaging users, the server comprising a processor that instantiates a plurality of software components stored in a memory, the plurality of software components comprising: a sentiment analyzer configured to: (a) identify a set of sentiment features, the set of sentiment features comprising at least one text feature representing a user sentiment associated with a first event, wherein the sentiment analyzer is configured to identify the set of sentiment features by analyzing, based on the first event, a first set of the plurality of messages; and (b) based on the set of sentiment features, form a prediction associated with a second event, wherein the sentiment analyzer is configured to form the prediction by analyzing a second set of the plurality of messages; and a services component configured to facilitate an event-related service based on the prediction. 22. The system of claim 21, wherein the sentiment analyzer comprises a sentiment classifier and an extraction module, and wherein the extraction module is configured to:
assign, based on event criteria, a label to each of the first set of messages to create a set of labeled messages, wherein the label corresponds to a predetermined sentiment value; and train the classifier using the set of labeled messages. 23. The system of claim 21, wherein the plurality of messages comprises a set of social media messages. 24. The system of claim 23, wherein the set of social media messages comprises a set of tweets. | In embodiments, a sentiment analyzer identifies a first event and accesses a first set of messages. The sentiment analyzer associates the first set of messages with the first event and analyzes the messages to identify a set of sentiment features. The set of sentiment features is used to analyze a second set of messages to form a prediction associated with a second event. The prediction may be used to facilitate an event-related service.1. A computer-implemented method for forming a prediction associated with an event, the method comprising:
accessing, using a computing device having a processor and a memory, event information from an event information source; identifying, using the processor and the event information, a first event based on event criteria; accessing, using the computing device, a first set of messages from a message source, wherein the first set of messages is generated by a plurality of messaging users; associating, using the processor, the first set of messages with the first event; identifying, using the processor, a set of sentiment features, the set of sentiment features comprising at least one text feature representing a user sentiment associated with the first event, wherein identifying the set of sentiment features comprises analyzing the first set of messages based on the first event; storing the set of sentiment features in a dynamic dictionary in the memory; accessing, using the computing device, a second set of messages from the message source; analyzing, using the processor, the second set of messages, based on the set of sentiment features, to form a prediction associated with a second event; and storing the prediction in the memory. 2. The method of claim 1, further comprising facilitating an event-based service based on the prediction. 3. The method of claim 2, wherein the second event comprises a gain event associated with a stock price or a loss event associated with the stock price. 4. The method of claim 3, wherein facilitating the event-based service comprises establishing a securities trading strategy based on the prediction, the securities trading strategy comprising:
taking a long position with respect to the stock if the second event comprises a gain event; and taking a short position with respect to the stock if the second event comprises a loss event. 5. The method of claim 1, wherein the set of sentiment features comprises at least one of a phrase, a word, a character, and a special notation. 6. The method of claim 1, wherein at least one of the first and second sets of messages comprises social media messages. 7. The method of claim 6, wherein the social media messages comprise tweets. 8. The method of claim 6, wherein each of the first set of social media messages was generated prior to the occurrence of the first event. 9. The method of claim 1, further comprising updating the dynamic dictionary by identifying an additional set of sentiment features based upon the prediction, and storing the additional set of sentiment features in the dynamic dictionary. 10. The method of claim 1, wherein analyzing the first set of messages comprises:
assigning, based on the event criteria, a label to each of the first set of messages to create a first set of labeled messages, wherein the label corresponds to a predetermined sentiment value; training a classifier using the first set of labeled messages; and identifying the set of sentiment features using the classifier. 11. The method of claim 10, wherein analyzing the second set of messages comprises:
identifying, using the classifier, a sentiment value for each of the second set of messages; aggregating at least a portion of the identified sentiment values; determining a sentiment score based on the aggregated identified sentiment values; and forming the prediction based on the sentiment score. 12. The method of claim 11, wherein the sentiment score comprises a number in the range of −1 to 1. 13. The method of claim 1, wherein the first event comprises a gain event associated with a stock price or a loss event associated with the stock price,
wherein a gain event is defined as a relative increase of the stock price, over a period of time, that exceeds three percent more than a return associated with a market index; and wherein a loss event is defined as a relative decrease of the stock price, over a period of time, that exceeds three percent less than the return associated with the market index. 14. The method of claim 13, wherein the market index comprises at least one of the S&P 500, the AMEX Composite, the NASDAQ Global Market Composite, the NYSE Composite, the Russell 1000, the Wilshire 5000, the Dow Industrials, the KBW Bank Index, the NASDAQ Financial-100, the PHLX Chemicals Sector, the Russell 1000 Growth, and the SIG Energy MLP Index. 15. The method of claim 13, wherein assigning the label to each of the first set of messages comprises:
labeling each of the first set of messages as positive when the first event is a gain event; and labeling each of the first set of messages as negative when the first event is a loss event. 16. The method of claim 1, wherein analyzing the first set of messages comprises applying an autoregressive model. 17. A computer-implemented method for forming a prediction associated with an event, the method comprising:
accessing, using a computing device having a processor and a memory, a set of messages from a message source, wherein the set of messages is generated by a plurality of messaging users; accessing, using the processor, a dynamic dictionary stored in the memory, the dynamic dictionary comprising a set of sentiment features, the set of sentiment features comprising at least one text feature representing a user sentiment associated with a first event; analyzing, using the processor, the set of messages, based on the set of sentiment features, to form a prediction associated with a second event; and storing the prediction in the memory. 18. The method of claim 17, further comprising facilitating an event-related service based on the prediction. 19. The method of claim 17, wherein the set of messages comprises social media messages. 20. The method of claim 19, wherein the social media messages comprises tweets. 21. A system for predicting events, the system comprising:
a server configured to receive, from a message source, a plurality of messages generated by a plurality of messaging users, the server comprising a processor that instantiates a plurality of software components stored in a memory, the plurality of software components comprising: a sentiment analyzer configured to: (a) identify a set of sentiment features, the set of sentiment features comprising at least one text feature representing a user sentiment associated with a first event, wherein the sentiment analyzer is configured to identify the set of sentiment features by analyzing, based on the first event, a first set of the plurality of messages; and (b) based on the set of sentiment features, form a prediction associated with a second event, wherein the sentiment analyzer is configured to form the prediction by analyzing a second set of the plurality of messages; and a services component configured to facilitate an event-related service based on the prediction. 22. The system of claim 21, wherein the sentiment analyzer comprises a sentiment classifier and an extraction module, and wherein the extraction module is configured to:
assign, based on event criteria, a label to each of the first set of messages to create a set of labeled messages, wherein the label corresponds to a predetermined sentiment value; and train the classifier using the set of labeled messages. 23. The system of claim 21, wherein the plurality of messages comprises a set of social media messages. 24. The system of claim 23, wherein the set of social media messages comprises a set of tweets. | 2,100 |
6,044 | 6,044 | 16,584,783 | 2,145 | The present disclosure generally relates to navigating a collection of media items. In accordance with one embodiment, a device displays a plurality of content items in a first layout, including a first content item at a first aspect ratio and a first size, a second content item, and a third content item. While displaying the plurality of content items in the first layout, the device detects a user input that includes a gesture, wherein the user input corresponds to a request to change a size of the first content item. In response to detecting the user input, and as the gesture progresses, the device changes the size of the first content item from the first size to a second size while concurrently gradually changing an aspect ratio of the first content item from the first aspect ratio to a second aspect ratio. | 1. An electronic device, comprising:
a display device; one or more processors; and memory storing one or more programs configured to be executed by the one or more processors, the one or more programs including instructions for:
displaying, via the display device, a plurality of media items in a first layout that includes a plurality of rows and a plurality of columns, including displaying:
a first media item of the plurality of media items at a first aspect ratio and a first size,
a second media item of the plurality of media items at the first aspect ratio, and
a third media item of the plurality of media items;
while displaying, via the display device, the plurality of media items in the first layout that includes the plurality of rows and the plurality of columns, detecting a user input that includes a gesture, wherein the user input corresponds to a request to change a size of the first media item; and in response to detecting the user input:
gradually changing, as the gesture progresses, the size of the first media item from the first size to a second size that is different from the first size while concurrently gradually changing, as the gesture progresses, an aspect ratio of the first media item from the first aspect ratio to a second aspect ratio that is different from the first aspect ratio; and
changing an aspect ratio of the second media item from the first aspect ratio to a third aspect ratio that is different from the first aspect ratio. 2. The electronic device of claim 1, wherein:
gradually changing the size of the first media item from the first size to the second size includes:
gradually changing the size of the first media item from the first size to the second size in conjunction with movement of the gesture; and
gradually changing the aspect ratio of the first media item from the first aspect ratio to the second aspect ratio includes:
gradually changing the aspect ratio of the first media item from the first aspect ratio to the second aspect ratio in conjunction with movement of the gesture. 3. The electronic device of claim 1, wherein:
gradually changing the aspect ratio of the first media item from the first aspect ratio to the second aspect ratio includes:
gradually changing the aspect ratio of the first media item from the first aspect ratio to an intermediate aspect ratio while maintaining a magnification of the first media item; and
gradually changing the aspect ratio of the first media item from the intermediate aspect ratio to the second aspect ratio while changing a magnification of the first media item. 4. The electronic device of claim 1, wherein changing the aspect ratio of the first media item from the first aspect ratio to the second aspect ratio includes:
cropping portions of the first media item or revealing previously cropped portions of the first media item. 5. The electronic device of claim 1, wherein:
displaying the second media item in the first layout includes displaying the second media item at the first aspect ratio; and displaying the third media item in the first layout includes displaying the third media item at the first aspect ratio. 6. The electronic device of claim 1, wherein:
the first aspect ratio is square; and the second aspect ratio is rectangular with unequal adjacent sides. 7. The electronic device of claim 1, wherein displaying the second media item in the first layout includes displaying the second media item at the first aspect ratio, the one or more programs further including instructions for:
in response to detecting the user input, changing an aspect ratio of the second media item from the first aspect ratio to a third aspect ratio that is different from the first aspect ratio and the second aspect ratio, so that at least a subset of the plurality of media items are displayed in a second layout that includes concurrently displaying the first media item in the second aspect ratio and at least a portion of the second media item in the third aspect ratio. 8. The electronic device of claim 1, the one or more programs further including instructions for:
in response to detecting the user input:
displaying, via the display device, a subset of the plurality of media items in a second layout that includes a single row or a single column, including:
concurrently displaying, on the display device, with the first media item at the second aspect ratio, the second media item of the plurality of media items at a third aspect ratio, wherein the third aspect ratio is different from the first aspect ratio, and
without concurrently displaying the third media item of the plurality of media items. 9. The electronic device of claim 1, the one or more programs further including instructions for:
while displaying, via the display device, the first media item at the second size and at the second aspect ratio, detecting a second user input that corresponds to a request to change a size of the first media item; and in response to detecting the second user input, gradually changing the size of the first media item from the second size to the first size while concurrently gradually changing the aspect ratio of the first media item from the second aspect ratio to the first aspect ratio. 10. The electronic device of claim 9, wherein changing the aspect ratio of the first media item from the second aspect ratio to the first aspect ratio includes:
in accordance with a determination that the first media item is in a portrait format, reducing the height of the first media item. 11. The electronic device of claim 9, wherein changing the aspect ratio of the first media item from the second aspect ratio to the first aspect ratio includes:
in accordance with a determination that the first media item is in a landscape format, reducing the width of the first media item. 12. The electronic device of claim 9, the one or more programs further including instructions for:
while displaying, via the display device, the plurality of media items, including the first media item at the first size and at the first aspect ratio, in the first layout that includes the plurality of rows and the plurality of columns, detecting a third user input that corresponds to a request to change a size of the first media item; and in response to detecting the third user input, displaying, via the display device, a second plurality of media items in a third layout that includes a second plurality of rows and a second plurality of columns, including:
gradually changing the size of the first media item from the first size to a third size without changing the aspect ratio of the first media item. 13. The electronic device of claim 8, wherein:
the second layout is different from the first layout; in the first layout the second media item has a first location relative to the first media item; in the second layout the third media item has the first location relative to the first media item; and displaying, on the display device, the subset of the plurality of media items in the second layout includes:
transitioning, as the gesture of the user input progresses, from displaying the first media item in the first layout to displaying the first media item in the second layout, including displaying a combination of the second media item and the third media item at the first location relative to the first media item during the transition from displaying the first media item in the first layout to displaying the first media item in the second layout. 14. The electronic device of claim 9, the one or more programs further including instructions for:
while displaying, via the display device, the plurality of media items, including the first media item at the first size and at the first aspect ratio, in the first layout that includes the plurality of rows and the plurality of columns, detecting a fourth user input that corresponds to a request to change an aspect ratio of the first media item; and in response to detecting the fourth user input, changing the aspect ratio of at least some of the plurality of media items while continuing to display the plurality of media items in the first layout, including changing the aspect ratio of the first media item from the first aspect ratio to a third aspect ratio. 15. The electronic device of claim 1, the one or more programs further including instructions for:
while displaying the plurality of media items in the first layout that includes the plurality of rows and the plurality of columns, providing an option to change aspect ratios of at least some of the plurality of media items while continuing to display the plurality of media items in the first layout; and subsequent to displaying the plurality of media items in the first layout, displaying the plurality of media items in a fourth layout that includes a third plurality of rows and a third plurality of columns without providing the option to change aspect ratios of at least some of the plurality of media items. 16. A non-transitory computer-readable storage medium storing one or more programs configured to be executed by one or more processors of an electronic device with a display device, the one or more programs including instructions for:
displaying, via the display device, a plurality of media items in a first layout that includes a plurality of rows and a plurality of columns, including displaying:
a first media item of the plurality of media items at a first aspect ratio and a first size,
a second media item of the plurality of media items at the first aspect ratio, and
a third media item of the plurality of media items;
while displaying, via the display device, the plurality of media items in the first layout that includes the plurality of rows and the plurality of columns, detecting a user input that includes a gesture, wherein the user input corresponds to a request to change a size of the first media item; and in response to detecting the user input:
gradually changing, as the gesture progresses, the size of the first media item from the first size to a second size that is different from the first size while concurrently gradually changing, as the gesture progresses, an aspect ratio of the first media item from the first aspect ratio to a second aspect ratio that is different from the first aspect ratio; and
changing an aspect ratio of the second media item from the first aspect ratio to a third aspect ratio that is different from the first aspect ratio. 17. A method, comprising:
at an electronic device with a display device:
displaying, via the display device, a plurality of media items in a first layout that includes a plurality of rows and a plurality of columns, including displaying:
a first media item of the plurality of media items at a first aspect ratio and a first size,
a second media item of the plurality of media items at the first aspect ratio, and
a third media item of the plurality of media items;
while displaying, via the display device, the plurality of media items in the first layout that includes the plurality of rows and the plurality of columns, detecting a user input that includes a gesture, wherein the user input corresponds to a request to change a size of the first media item; and in response to detecting the user input; gradually changing, as the gesture progresses, the size of the first media item from the first size to a second size that is different from the first size while concurrently gradually changing, as the gesture progresses, an aspect ratio of the first media item from the first aspect ratio to a second aspect ratio that is different from the first aspect ratio; and
changing an aspect ratio of the second media item from the first aspect ratio to a third aspect ratio that is different from the first aspect ratio. | The present disclosure generally relates to navigating a collection of media items. In accordance with one embodiment, a device displays a plurality of content items in a first layout, including a first content item at a first aspect ratio and a first size, a second content item, and a third content item. While displaying the plurality of content items in the first layout, the device detects a user input that includes a gesture, wherein the user input corresponds to a request to change a size of the first content item. In response to detecting the user input, and as the gesture progresses, the device changes the size of the first content item from the first size to a second size while concurrently gradually changing an aspect ratio of the first content item from the first aspect ratio to a second aspect ratio.1. An electronic device, comprising:
a display device; one or more processors; and memory storing one or more programs configured to be executed by the one or more processors, the one or more programs including instructions for:
displaying, via the display device, a plurality of media items in a first layout that includes a plurality of rows and a plurality of columns, including displaying:
a first media item of the plurality of media items at a first aspect ratio and a first size,
a second media item of the plurality of media items at the first aspect ratio, and
a third media item of the plurality of media items;
while displaying, via the display device, the plurality of media items in the first layout that includes the plurality of rows and the plurality of columns, detecting a user input that includes a gesture, wherein the user input corresponds to a request to change a size of the first media item; and in response to detecting the user input:
gradually changing, as the gesture progresses, the size of the first media item from the first size to a second size that is different from the first size while concurrently gradually changing, as the gesture progresses, an aspect ratio of the first media item from the first aspect ratio to a second aspect ratio that is different from the first aspect ratio; and
changing an aspect ratio of the second media item from the first aspect ratio to a third aspect ratio that is different from the first aspect ratio. 2. The electronic device of claim 1, wherein:
gradually changing the size of the first media item from the first size to the second size includes:
gradually changing the size of the first media item from the first size to the second size in conjunction with movement of the gesture; and
gradually changing the aspect ratio of the first media item from the first aspect ratio to the second aspect ratio includes:
gradually changing the aspect ratio of the first media item from the first aspect ratio to the second aspect ratio in conjunction with movement of the gesture. 3. The electronic device of claim 1, wherein:
gradually changing the aspect ratio of the first media item from the first aspect ratio to the second aspect ratio includes:
gradually changing the aspect ratio of the first media item from the first aspect ratio to an intermediate aspect ratio while maintaining a magnification of the first media item; and
gradually changing the aspect ratio of the first media item from the intermediate aspect ratio to the second aspect ratio while changing a magnification of the first media item. 4. The electronic device of claim 1, wherein changing the aspect ratio of the first media item from the first aspect ratio to the second aspect ratio includes:
cropping portions of the first media item or revealing previously cropped portions of the first media item. 5. The electronic device of claim 1, wherein:
displaying the second media item in the first layout includes displaying the second media item at the first aspect ratio; and displaying the third media item in the first layout includes displaying the third media item at the first aspect ratio. 6. The electronic device of claim 1, wherein:
the first aspect ratio is square; and the second aspect ratio is rectangular with unequal adjacent sides. 7. The electronic device of claim 1, wherein displaying the second media item in the first layout includes displaying the second media item at the first aspect ratio, the one or more programs further including instructions for:
in response to detecting the user input, changing an aspect ratio of the second media item from the first aspect ratio to a third aspect ratio that is different from the first aspect ratio and the second aspect ratio, so that at least a subset of the plurality of media items are displayed in a second layout that includes concurrently displaying the first media item in the second aspect ratio and at least a portion of the second media item in the third aspect ratio. 8. The electronic device of claim 1, the one or more programs further including instructions for:
in response to detecting the user input:
displaying, via the display device, a subset of the plurality of media items in a second layout that includes a single row or a single column, including:
concurrently displaying, on the display device, with the first media item at the second aspect ratio, the second media item of the plurality of media items at a third aspect ratio, wherein the third aspect ratio is different from the first aspect ratio, and
without concurrently displaying the third media item of the plurality of media items. 9. The electronic device of claim 1, the one or more programs further including instructions for:
while displaying, via the display device, the first media item at the second size and at the second aspect ratio, detecting a second user input that corresponds to a request to change a size of the first media item; and in response to detecting the second user input, gradually changing the size of the first media item from the second size to the first size while concurrently gradually changing the aspect ratio of the first media item from the second aspect ratio to the first aspect ratio. 10. The electronic device of claim 9, wherein changing the aspect ratio of the first media item from the second aspect ratio to the first aspect ratio includes:
in accordance with a determination that the first media item is in a portrait format, reducing the height of the first media item. 11. The electronic device of claim 9, wherein changing the aspect ratio of the first media item from the second aspect ratio to the first aspect ratio includes:
in accordance with a determination that the first media item is in a landscape format, reducing the width of the first media item. 12. The electronic device of claim 9, the one or more programs further including instructions for:
while displaying, via the display device, the plurality of media items, including the first media item at the first size and at the first aspect ratio, in the first layout that includes the plurality of rows and the plurality of columns, detecting a third user input that corresponds to a request to change a size of the first media item; and in response to detecting the third user input, displaying, via the display device, a second plurality of media items in a third layout that includes a second plurality of rows and a second plurality of columns, including:
gradually changing the size of the first media item from the first size to a third size without changing the aspect ratio of the first media item. 13. The electronic device of claim 8, wherein:
the second layout is different from the first layout; in the first layout the second media item has a first location relative to the first media item; in the second layout the third media item has the first location relative to the first media item; and displaying, on the display device, the subset of the plurality of media items in the second layout includes:
transitioning, as the gesture of the user input progresses, from displaying the first media item in the first layout to displaying the first media item in the second layout, including displaying a combination of the second media item and the third media item at the first location relative to the first media item during the transition from displaying the first media item in the first layout to displaying the first media item in the second layout. 14. The electronic device of claim 9, the one or more programs further including instructions for:
while displaying, via the display device, the plurality of media items, including the first media item at the first size and at the first aspect ratio, in the first layout that includes the plurality of rows and the plurality of columns, detecting a fourth user input that corresponds to a request to change an aspect ratio of the first media item; and in response to detecting the fourth user input, changing the aspect ratio of at least some of the plurality of media items while continuing to display the plurality of media items in the first layout, including changing the aspect ratio of the first media item from the first aspect ratio to a third aspect ratio. 15. The electronic device of claim 1, the one or more programs further including instructions for:
while displaying the plurality of media items in the first layout that includes the plurality of rows and the plurality of columns, providing an option to change aspect ratios of at least some of the plurality of media items while continuing to display the plurality of media items in the first layout; and subsequent to displaying the plurality of media items in the first layout, displaying the plurality of media items in a fourth layout that includes a third plurality of rows and a third plurality of columns without providing the option to change aspect ratios of at least some of the plurality of media items. 16. A non-transitory computer-readable storage medium storing one or more programs configured to be executed by one or more processors of an electronic device with a display device, the one or more programs including instructions for:
displaying, via the display device, a plurality of media items in a first layout that includes a plurality of rows and a plurality of columns, including displaying:
a first media item of the plurality of media items at a first aspect ratio and a first size,
a second media item of the plurality of media items at the first aspect ratio, and
a third media item of the plurality of media items;
while displaying, via the display device, the plurality of media items in the first layout that includes the plurality of rows and the plurality of columns, detecting a user input that includes a gesture, wherein the user input corresponds to a request to change a size of the first media item; and in response to detecting the user input:
gradually changing, as the gesture progresses, the size of the first media item from the first size to a second size that is different from the first size while concurrently gradually changing, as the gesture progresses, an aspect ratio of the first media item from the first aspect ratio to a second aspect ratio that is different from the first aspect ratio; and
changing an aspect ratio of the second media item from the first aspect ratio to a third aspect ratio that is different from the first aspect ratio. 17. A method, comprising:
at an electronic device with a display device:
displaying, via the display device, a plurality of media items in a first layout that includes a plurality of rows and a plurality of columns, including displaying:
a first media item of the plurality of media items at a first aspect ratio and a first size,
a second media item of the plurality of media items at the first aspect ratio, and
a third media item of the plurality of media items;
while displaying, via the display device, the plurality of media items in the first layout that includes the plurality of rows and the plurality of columns, detecting a user input that includes a gesture, wherein the user input corresponds to a request to change a size of the first media item; and in response to detecting the user input; gradually changing, as the gesture progresses, the size of the first media item from the first size to a second size that is different from the first size while concurrently gradually changing, as the gesture progresses, an aspect ratio of the first media item from the first aspect ratio to a second aspect ratio that is different from the first aspect ratio; and
changing an aspect ratio of the second media item from the first aspect ratio to a third aspect ratio that is different from the first aspect ratio. | 2,100 |
6,045 | 6,045 | 14,520,716 | 2,176 | A method can include receiving an unstructured grid of a multi-dimensional region; partitioning at least a portion of the unstructured grid into subdomains based at least in part on a cell number criterion; generating a hierarchical representation of the at least a portion of the unstructured grid that includes the subdomains and the cells; indexing cells in the subdomains based at least in part on the cell number criterion to define a data structure; and assigning respective property values to respective indexed cells for at least a portion of the data structure. | 1. A method comprising:
receiving an unstructured grid of a multi-dimensional region; partitioning at least a portion of the unstructured grid into subdomains based at least in part on a cell number criterion; generating a hierarchical representation of the at least a portion of the unstructured grid that comprises the subdomains and the cells; indexing cells in the subdomains based at least in part on the cell number criterion to define a data structure; and assigning respective property values to respective indexed cells for at least a portion of the data structure. 2. The method of claim 1 further comprising rendering a visualization of at least some of the property values of respective indexed cells to a display. 3. The method of claim 1 wherein the indexing comprises space-filling via a space-filling curve technique. 4. The method of claim 1 wherein the cell number criterion comprises a maximum cell number per subdomain and wherein the data structure is defined to comprise fill that accounts for at least one of the subdomains including a number of cells that is less than the maximum cell number per subdomain. 5. The method of claim 1 wherein the partitioning comprises recursive partitioning wherein each recursion generates a level of detail. 6. The method of claim 1 further comprising identifying at least one feature of the multi-dimensional region and partitioning the at least a portion of the unstructured grid into subdomains based at least in part on the at least one identified feature. 7. The method of claim 6 wherein the at least one feature comprises a low transmissibility feature. 8. The method of claim 1 wherein the indexing comprises parallel processing of a plurality of the subdomains. 9. The method of claim 1 wherein the partitioning comprises generating a subdomain for a portion of the unstructured grid that comprises a locally refined grid. 10. The method of claim 1 wherein the property values correspond to a time and further comprising repeating at least the assigning for property values that correspond to a different time. 11. The method of claim 1 further comprising filtering at least a portion of the property values based at least in part on at least one filter criterion and at least in part on the hierarchical representation. 15. A system comprising:
a processor; memory operatively coupled to the processor; and one or more modules that comprise processor-executable instructions stored in the memory to instruct the system, the instructions comprising instructions to
receive an unstructured grid of a multi-dimensional region;
partition at least a portion of the unstructured grid into subdomains based at least in part on a cell number criterion;
generate a hierarchical representation of the at least a portion of the unstructured grid that comprises the subdomains and the cells;
index cells in the subdomains based at least in part on the cell number criterion to define a data structure; and
assign respective property values to respective indexed cells for at least a portion of the data structure. 16. The system of claim 15 wherein the instructions to index cells comprise instructions to index cells at least in part via a space-filling curve technique. 17. The system of claim 15 further comprising instructions to identify at least one feature of the multi-dimensional region and to partition the at least a portion of the unstructured grid into subdomains based at least in part on the at least one identified feature. 18. The system of claim 15 further comprising instructions to filter at least a portion of the property values based at least in part on at least one filter criterion and at least in part on the hierarchical representation. 19. One or more computer-readable storage media comprising computer-executable instructions to instruct a computer, the instructions comprising instructions to:
receive an unstructured grid of a multi-dimensional region; partition at least a portion of the unstructured grid into subdomains based at least in part on a cell number criterion; generate a hierarchical representation of the at least a portion of the unstructured grid that comprises the subdomains and the cells; index cells in the subdomains based at least in part on the cell number criterion to define a data structure; and assign respective property values to respective indexed cells for at least a portion of the data structure. 20. The one or more computer-readable storage media of claim 19 wherein the instructions to index cells comprise instructions to index cells at least in part via a space-filling via a space-filling curve technique. | A method can include receiving an unstructured grid of a multi-dimensional region; partitioning at least a portion of the unstructured grid into subdomains based at least in part on a cell number criterion; generating a hierarchical representation of the at least a portion of the unstructured grid that includes the subdomains and the cells; indexing cells in the subdomains based at least in part on the cell number criterion to define a data structure; and assigning respective property values to respective indexed cells for at least a portion of the data structure.1. A method comprising:
receiving an unstructured grid of a multi-dimensional region; partitioning at least a portion of the unstructured grid into subdomains based at least in part on a cell number criterion; generating a hierarchical representation of the at least a portion of the unstructured grid that comprises the subdomains and the cells; indexing cells in the subdomains based at least in part on the cell number criterion to define a data structure; and assigning respective property values to respective indexed cells for at least a portion of the data structure. 2. The method of claim 1 further comprising rendering a visualization of at least some of the property values of respective indexed cells to a display. 3. The method of claim 1 wherein the indexing comprises space-filling via a space-filling curve technique. 4. The method of claim 1 wherein the cell number criterion comprises a maximum cell number per subdomain and wherein the data structure is defined to comprise fill that accounts for at least one of the subdomains including a number of cells that is less than the maximum cell number per subdomain. 5. The method of claim 1 wherein the partitioning comprises recursive partitioning wherein each recursion generates a level of detail. 6. The method of claim 1 further comprising identifying at least one feature of the multi-dimensional region and partitioning the at least a portion of the unstructured grid into subdomains based at least in part on the at least one identified feature. 7. The method of claim 6 wherein the at least one feature comprises a low transmissibility feature. 8. The method of claim 1 wherein the indexing comprises parallel processing of a plurality of the subdomains. 9. The method of claim 1 wherein the partitioning comprises generating a subdomain for a portion of the unstructured grid that comprises a locally refined grid. 10. The method of claim 1 wherein the property values correspond to a time and further comprising repeating at least the assigning for property values that correspond to a different time. 11. The method of claim 1 further comprising filtering at least a portion of the property values based at least in part on at least one filter criterion and at least in part on the hierarchical representation. 15. A system comprising:
a processor; memory operatively coupled to the processor; and one or more modules that comprise processor-executable instructions stored in the memory to instruct the system, the instructions comprising instructions to
receive an unstructured grid of a multi-dimensional region;
partition at least a portion of the unstructured grid into subdomains based at least in part on a cell number criterion;
generate a hierarchical representation of the at least a portion of the unstructured grid that comprises the subdomains and the cells;
index cells in the subdomains based at least in part on the cell number criterion to define a data structure; and
assign respective property values to respective indexed cells for at least a portion of the data structure. 16. The system of claim 15 wherein the instructions to index cells comprise instructions to index cells at least in part via a space-filling curve technique. 17. The system of claim 15 further comprising instructions to identify at least one feature of the multi-dimensional region and to partition the at least a portion of the unstructured grid into subdomains based at least in part on the at least one identified feature. 18. The system of claim 15 further comprising instructions to filter at least a portion of the property values based at least in part on at least one filter criterion and at least in part on the hierarchical representation. 19. One or more computer-readable storage media comprising computer-executable instructions to instruct a computer, the instructions comprising instructions to:
receive an unstructured grid of a multi-dimensional region; partition at least a portion of the unstructured grid into subdomains based at least in part on a cell number criterion; generate a hierarchical representation of the at least a portion of the unstructured grid that comprises the subdomains and the cells; index cells in the subdomains based at least in part on the cell number criterion to define a data structure; and assign respective property values to respective indexed cells for at least a portion of the data structure. 20. The one or more computer-readable storage media of claim 19 wherein the instructions to index cells comprise instructions to index cells at least in part via a space-filling via a space-filling curve technique. | 2,100 |
6,046 | 6,046 | 15,287,807 | 2,179 | A method of operating an elevator call system includes displaying a plurality of elevator destination selections associated with a building on a display screen of a mobile device. For ease of use, the elevator destination selections may be prioritized. | 1. A method of operating an elevator call system comprising:
displaying a first plurality of elevator destination selections associated with a first building on a display screen of a mobile device, wherein the first plurality of elevator destination selections is prioritized. 2. The method set forth in claim 1, wherein the plurality of elevator destination selections are a plurality of elevator destination combination selections. 3. The method set forth in claim 1, wherein the prioritization of the first plurality of elevator destination selections is based at least on frequency of use. 4. The method set forth in claim 1, wherein the prioritization of the first plurality of elevator destination selections is based at least on time. 5. The method set forth in claim 3, wherein the first plurality of elevator destination selections include a first selection based on time and a second selection based on frequency of use. 6. The method set forth in claim 1, wherein each one of the first plurality of elevator destination selections depict a boarding description and a departure description. 7. The method set forth in claim 6, wherein the boarding and departure descriptions are associated with different floors of the first building. 8. The method set forth in claim 7, wherein the boarding description is automatically known via positioning circuitry of the mobile device. 9. The method set forth in claim 1 further comprising:
displaying a second plurality of elevator destination selections associated with a second building on the display screen of the mobile device. 10. The method set forth in claim 9, wherein the second plurality of elevator destination selections are prioritized. 11. The method set forth in claim 10, wherein the first and second buildings are associated with respective first and second building selections that are prioritized. 12. The method set forth in claim 11, wherein prioritization of the first and second building selections is based on geographic proximity enabled by positioning circuitry of the mobile device. 13. The method set forth in claim 1, wherein the mobile device is a smartphone. 14. A method of operating an elevator call system comprising:
depicting a first interactive grid display on a display screen of a mobile device, wherein the first interactive grid display depicts a plurality of harbor selections associated with a first building and a my-buildings selection; selecting the my-buildings view selection; and depicting an interactive my-buildings display on the display screen, wherein the interactive my-building display depicts the first building associated with at least one elevator destination selection, and a second building associated with at least one second elevator destination selection. 15. The method set forth in claim 14, wherein the first and second elevator destination selections are each a prioritized plurality of elevator destination selections. 16. The method set forth in claim 14 further comprising:
selecting an interactive grid view selection of the interactive my-buildings display to depict one of the first interactive grid display and a second interactive grid display, wherein the second interactive grid display depicts a plurality of harbor selections associated with the second building. 17. The method set forth in claim 16, wherein the first and second buildings depicted on the interactive my-buildings display are respective first and second building selections. 18. The method set forth in claim 17 further comprising:
selecting one of the first and second building selections from the my-buildings display; and
depicting the respective one of the first and second interactive grid displays. 19. The method set forth in claim 17, wherein the first and second building selections are prioritized. 20. The method set forth in claim 19, wherein prioritization of the first and second building selections is based on geographic proximity enabled by positioning circuitry of the mobile device. | A method of operating an elevator call system includes displaying a plurality of elevator destination selections associated with a building on a display screen of a mobile device. For ease of use, the elevator destination selections may be prioritized.1. A method of operating an elevator call system comprising:
displaying a first plurality of elevator destination selections associated with a first building on a display screen of a mobile device, wherein the first plurality of elevator destination selections is prioritized. 2. The method set forth in claim 1, wherein the plurality of elevator destination selections are a plurality of elevator destination combination selections. 3. The method set forth in claim 1, wherein the prioritization of the first plurality of elevator destination selections is based at least on frequency of use. 4. The method set forth in claim 1, wherein the prioritization of the first plurality of elevator destination selections is based at least on time. 5. The method set forth in claim 3, wherein the first plurality of elevator destination selections include a first selection based on time and a second selection based on frequency of use. 6. The method set forth in claim 1, wherein each one of the first plurality of elevator destination selections depict a boarding description and a departure description. 7. The method set forth in claim 6, wherein the boarding and departure descriptions are associated with different floors of the first building. 8. The method set forth in claim 7, wherein the boarding description is automatically known via positioning circuitry of the mobile device. 9. The method set forth in claim 1 further comprising:
displaying a second plurality of elevator destination selections associated with a second building on the display screen of the mobile device. 10. The method set forth in claim 9, wherein the second plurality of elevator destination selections are prioritized. 11. The method set forth in claim 10, wherein the first and second buildings are associated with respective first and second building selections that are prioritized. 12. The method set forth in claim 11, wherein prioritization of the first and second building selections is based on geographic proximity enabled by positioning circuitry of the mobile device. 13. The method set forth in claim 1, wherein the mobile device is a smartphone. 14. A method of operating an elevator call system comprising:
depicting a first interactive grid display on a display screen of a mobile device, wherein the first interactive grid display depicts a plurality of harbor selections associated with a first building and a my-buildings selection; selecting the my-buildings view selection; and depicting an interactive my-buildings display on the display screen, wherein the interactive my-building display depicts the first building associated with at least one elevator destination selection, and a second building associated with at least one second elevator destination selection. 15. The method set forth in claim 14, wherein the first and second elevator destination selections are each a prioritized plurality of elevator destination selections. 16. The method set forth in claim 14 further comprising:
selecting an interactive grid view selection of the interactive my-buildings display to depict one of the first interactive grid display and a second interactive grid display, wherein the second interactive grid display depicts a plurality of harbor selections associated with the second building. 17. The method set forth in claim 16, wherein the first and second buildings depicted on the interactive my-buildings display are respective first and second building selections. 18. The method set forth in claim 17 further comprising:
selecting one of the first and second building selections from the my-buildings display; and
depicting the respective one of the first and second interactive grid displays. 19. The method set forth in claim 17, wherein the first and second building selections are prioritized. 20. The method set forth in claim 19, wherein prioritization of the first and second building selections is based on geographic proximity enabled by positioning circuitry of the mobile device. | 2,100 |
6,047 | 6,047 | 14,574,183 | 2,195 | Systems, methods, and interfaces for the management of virtual machine instances and other programmatically controlled networks are provided. The hosted virtual networks are configured in a manner such that a virtual machine manager of the virtual network may monitor activity such as user requests, network traffic, and the status and execution of various virtual machine instances to determine possible security assessments. Aspects of the virtual network may be assessed for vulnerabilities at varying levels of granularity and sophistication when a suspicious event or triggering activity is detected. Illustrative embodiments of the systems and methods may be implemented on a virtual network overlaid on one or more intermediate physical networks that are used as a substrate network. | 1. A computer implemented method for managing a virtual machine network comprising:
detecting an activity associated with execution of a virtual machine network or a request for executing an activity on the virtual machine network; determining a security assessment event from a plurality of security assessment events based, at least in part, on the detected activity or request, wherein individual security assessment events of the plurality of security assessment events each correspond to a respective activity associated with the execution of the virtual machine network or a respective request for executing an activity on the virtual machine network and are associated with at least one respective assessment preference; and causing performance of a security assessment on the virtual machine network based, at least in part, on the determined security assessment event. 2. The method of claim 1, wherein the at least one respective assessment preference includes at least one of a respective assessment timing, assessment type, or assessment extent. 3. The method of claim 1, wherein causing performance of the security assessment comprises causing performance of the security assessment at least one of before, after, or simultaneous to the execution of the activity associated with the security assessment event. 4. The method of claim 1 further comprising causing instantiation of a set of virtual machine instances in order to perform the security assessment. 5. The method of claim 4, wherein the security assessment is performed on the set of virtual machine instances without affecting a state or performance of the virtual machine network. 6. The method of claim 1, wherein the causing performance of the security assessment includes causing performance of procedures corresponding to at least one of computer virus scans, tests against known exploits, software bug detection, input and validation checking, load testing, and the identification of flaws in hardware or software design or implementation, password handling, or privilege management. 7. The method of claim 1 further comprising storing results of the security assessment. 8. The method of claim 1 further comprising determining whether results of the security assessment are satisfactory. 9. The method of claim 8, wherein determining whether the results of the security assessment are satisfactory is based on at least one of a success of a particular set of tests performed as part of the security assessment, whether the security assessment identifies a certain number or combination of virtual machine network vulnerabilities, a security threat level value based on an assessment of potential threats and vulnerabilities, or whether an aggregate security value based on the results of the assessment crosses a threshold value. 10. A system comprising:
a data store configured to at least store computer-executable instructions; and a hardware processor in communication with the data store, the hardware processor configured to execute the computer-executable instructions to at least:
determine a security assessment event from a plurality of security assessment events based, at least in part, on a detected virtual machine network activity or request for a virtual machine network activity, wherein individual security assessment events of the plurality of security assessment events each correspond to a respective activity associated with execution of a virtual machine network activity or a respective request for executing an activity on the virtual machine network and are associated with at least one respective assessment preference; and
cause performance of a security assessment on the virtual machine network based, at least in part, on the determined security assessment event. 11. The system of claim 10, wherein the hardware processor is further configured to generate one or more results of the security assessment. 12. The system of claim 11, wherein the hardware processor is further configured to cause at least one corrective action based on the one or more results of the security assessment. 13. The system of claim 12, wherein the at least one corrective action includes at least one action to notify, modify, correct, isolate, or reveal any aspect of the virtual machine network. 14. The system of claim 11, wherein the one or more results of the security assessment are associated with respective expiration time or date. 15. The system of claim 10, wherein the hardware processor is further configured to charge a user a fee for causing performance of the security assessment. 16. The system of claim 15, wherein an amount of the fee is based on a type of the security assessment performed. 17. A non-transitory computer-readable medium storing computer executable instructions that when executed by a processor perform operations comprising:
detecting an activity associated with execution of a virtual machine network or a request for executing an activity on the virtual machine network; determining a security assessment event from a plurality of security assessment events based, at least in part, on the detected activity or request, wherein individual security assessment events of the plurality of security assessment events each correspond to a respective activity associated with the execution of the virtual machine network or a respective request for executing an activity on the virtual machine network and are associated with at least one respective assessment preference; and causing performance of a security assessment on the virtual machine network based, at least in part, on the determined security assessment event. 18. The non-transitory computer-readable medium of claim 17, wherein the operations further comprise obtaining external information concerning security vulnerabilities. 19. The non-transitory computer-readable medium of claim 18, wherein the at least one respective assessment preference is determined based, at least in part, on the external information concerning security vulnerabilities. 20. The non-transitory computer-readable medium of claim 17, wherein the operations further comprise rewarding a user for the performance of the security assessment. | Systems, methods, and interfaces for the management of virtual machine instances and other programmatically controlled networks are provided. The hosted virtual networks are configured in a manner such that a virtual machine manager of the virtual network may monitor activity such as user requests, network traffic, and the status and execution of various virtual machine instances to determine possible security assessments. Aspects of the virtual network may be assessed for vulnerabilities at varying levels of granularity and sophistication when a suspicious event or triggering activity is detected. Illustrative embodiments of the systems and methods may be implemented on a virtual network overlaid on one or more intermediate physical networks that are used as a substrate network.1. A computer implemented method for managing a virtual machine network comprising:
detecting an activity associated with execution of a virtual machine network or a request for executing an activity on the virtual machine network; determining a security assessment event from a plurality of security assessment events based, at least in part, on the detected activity or request, wherein individual security assessment events of the plurality of security assessment events each correspond to a respective activity associated with the execution of the virtual machine network or a respective request for executing an activity on the virtual machine network and are associated with at least one respective assessment preference; and causing performance of a security assessment on the virtual machine network based, at least in part, on the determined security assessment event. 2. The method of claim 1, wherein the at least one respective assessment preference includes at least one of a respective assessment timing, assessment type, or assessment extent. 3. The method of claim 1, wherein causing performance of the security assessment comprises causing performance of the security assessment at least one of before, after, or simultaneous to the execution of the activity associated with the security assessment event. 4. The method of claim 1 further comprising causing instantiation of a set of virtual machine instances in order to perform the security assessment. 5. The method of claim 4, wherein the security assessment is performed on the set of virtual machine instances without affecting a state or performance of the virtual machine network. 6. The method of claim 1, wherein the causing performance of the security assessment includes causing performance of procedures corresponding to at least one of computer virus scans, tests against known exploits, software bug detection, input and validation checking, load testing, and the identification of flaws in hardware or software design or implementation, password handling, or privilege management. 7. The method of claim 1 further comprising storing results of the security assessment. 8. The method of claim 1 further comprising determining whether results of the security assessment are satisfactory. 9. The method of claim 8, wherein determining whether the results of the security assessment are satisfactory is based on at least one of a success of a particular set of tests performed as part of the security assessment, whether the security assessment identifies a certain number or combination of virtual machine network vulnerabilities, a security threat level value based on an assessment of potential threats and vulnerabilities, or whether an aggregate security value based on the results of the assessment crosses a threshold value. 10. A system comprising:
a data store configured to at least store computer-executable instructions; and a hardware processor in communication with the data store, the hardware processor configured to execute the computer-executable instructions to at least:
determine a security assessment event from a plurality of security assessment events based, at least in part, on a detected virtual machine network activity or request for a virtual machine network activity, wherein individual security assessment events of the plurality of security assessment events each correspond to a respective activity associated with execution of a virtual machine network activity or a respective request for executing an activity on the virtual machine network and are associated with at least one respective assessment preference; and
cause performance of a security assessment on the virtual machine network based, at least in part, on the determined security assessment event. 11. The system of claim 10, wherein the hardware processor is further configured to generate one or more results of the security assessment. 12. The system of claim 11, wherein the hardware processor is further configured to cause at least one corrective action based on the one or more results of the security assessment. 13. The system of claim 12, wherein the at least one corrective action includes at least one action to notify, modify, correct, isolate, or reveal any aspect of the virtual machine network. 14. The system of claim 11, wherein the one or more results of the security assessment are associated with respective expiration time or date. 15. The system of claim 10, wherein the hardware processor is further configured to charge a user a fee for causing performance of the security assessment. 16. The system of claim 15, wherein an amount of the fee is based on a type of the security assessment performed. 17. A non-transitory computer-readable medium storing computer executable instructions that when executed by a processor perform operations comprising:
detecting an activity associated with execution of a virtual machine network or a request for executing an activity on the virtual machine network; determining a security assessment event from a plurality of security assessment events based, at least in part, on the detected activity or request, wherein individual security assessment events of the plurality of security assessment events each correspond to a respective activity associated with the execution of the virtual machine network or a respective request for executing an activity on the virtual machine network and are associated with at least one respective assessment preference; and causing performance of a security assessment on the virtual machine network based, at least in part, on the determined security assessment event. 18. The non-transitory computer-readable medium of claim 17, wherein the operations further comprise obtaining external information concerning security vulnerabilities. 19. The non-transitory computer-readable medium of claim 18, wherein the at least one respective assessment preference is determined based, at least in part, on the external information concerning security vulnerabilities. 20. The non-transitory computer-readable medium of claim 17, wherein the operations further comprise rewarding a user for the performance of the security assessment. | 2,100 |
6,048 | 6,048 | 15,562,807 | 2,178 | A method, an apparatus, and a device for enabling a task management interface, where the method includes receiving an instruction for enabling the task management interface, displaying the task management interface in response to the instruction for enabling the task management interface, where the task management interface includes a preview interface of at least one application program and an icon corresponding to at least one function of the application program, receiving an operation instruction for the icon, and switching the application program corresponding to the icon to a foreground, and executing the function in response to the operation instruction. Therefore, it is convenient for a user to quickly enable a function of an application program included in the task management interface, thereby improving user experience. | 1. A method for displaying a task management interface, comprising:
receiving an operation of double-tapping a Home key; selecting at least one application program from installed application programs according to a habit of using an application program by a user in response to the operation of double-tapping the Home key; and displaying the task management interface, and wherein the task management interface comprises information about the selected at least one application program. 2. The method according to claim 1, wherein the information about the selected at least one application program comprises an icon corresponding to the at least one application program and a preview interface of the at least one application program. 3. The method according to claim 1, wherein selecting the at least one application program from the installed application programs comprises selecting the at least one application program from the installed application programs according to use of the application program by the user in daily life. 4. The method according to claim 3, wherein selecting the at least one application program from the installed application programs comprises selecting the at least one application program from the installed application programs according to a frequency of using the application program by the user in different time periods. 5. The method according to claim 3, wherein selecting the at least one application program from the installed application programs according to the use of the application program by the user in daily life is comprises selecting the at least one application program from the installed application programs according to a frequency of using the application program by the user when human body characteristic parameters of the user comprise different thresholds. 6. The method according to claim 3, wherein selecting the at least one application program from the installed application programs according to the use of the application program by the user in daily life comprises selecting the at least one application program from the installed application programs according to a frequency of using the application program by the user in different locations. 7. The method according to claim 1, wherein after displaying the task management interface, the method further comprises:
receiving an operation instruction for the information about the selected at least one application program; switching the at least one application program to a foreground in response to the operation instruction; and running the at least one application program. 8.-9. (canceled) 10. A method for running an application program, comprising:
receiving a first operation instruction; displaying a user interface in response to the first operation instruction, wherein the user interface comprises an icon of at least one application program, and wherein the application program is selected from installed application programs according to a habit of using the application program by a user; receiving a second operation instruction for an icon of the application program; switching the application program to a foreground in response to the second operation instruction; and running the application program. 11. The method according to claim 10, wherein the application program is selected from the installed application programs according to use of the application program by the user in daily life. 12. The method according to claim 10, wherein the application program is selected from the installed application programs according to a frequency of using the application program by the user in different time periods. 13. The method according to claim 10, wherein the application program is selected from the installed application programs according to a frequency of using the application program by the user when human body characteristic parameters of the user comprise different thresholds. 14. The method according to claim 10, wherein the application program is selected from the installed application programs according to a frequency of using the application program by the user in different locations. 15.-31. (canceled) 32. An apparatus for running an application program, comprising:
a memory configured to store instructions; and a processor coupled to the memory, wherein the instructions cause the processor to be configured to:
receive an operation of double-tapping a Home key;
select at least one application program from installed application programs according to a habit of using an application program by a user in response to the operation of double-tapping the Home key; and
display a task management interface, and
wherein the task management interface comprises information about the selected at least one application program. 33. The apparatus of claim 32, wherein the information about the at least one application program comprises an icon corresponding to the at least one application program or a preview interface of the at least one application program. 34. The apparatus of claim 32, wherein when selecting the at least one application program from the installed application programs, the instructions further cause the processor to be configured to select the at least one application program from the installed application programs according to use of the application program by the user in daily life. 35. The apparatus of claim 34, wherein when selecting the at least one application program, the instructions further cause the processor to be configured to select the at least one application program from the installed application programs according to a frequency of using the application program by the user in different time periods. 36. The apparatus of claim 34, wherein when selecting the at least one application program, the instructions further cause the processor to be configured to select the at least one application program from the installed application programs according to a frequency of using the application program by the user when human body characteristic parameters of the user comprise different thresholds. 37. The apparatus of claim 34, wherein when selecting the at least one application program, the instructions further cause the processor to be configured to select the at least one application program from the installed application programs according to a frequency of using the application program by the user in different locations. 38. The apparatus of claim 32, wherein the instructions further cause the processor to be configured to:
receive an operation instruction for the information about the selected at least one application program after displaying the task management interface; switch the at least one application program to a foreground in response to the operation instruction; and run the at least one application program. 39. The method according to claim 1, wherein the information about the at least one application program comprises an icon corresponding to the at least one application program or a preview interface of the at least one application program. | A method, an apparatus, and a device for enabling a task management interface, where the method includes receiving an instruction for enabling the task management interface, displaying the task management interface in response to the instruction for enabling the task management interface, where the task management interface includes a preview interface of at least one application program and an icon corresponding to at least one function of the application program, receiving an operation instruction for the icon, and switching the application program corresponding to the icon to a foreground, and executing the function in response to the operation instruction. Therefore, it is convenient for a user to quickly enable a function of an application program included in the task management interface, thereby improving user experience.1. A method for displaying a task management interface, comprising:
receiving an operation of double-tapping a Home key; selecting at least one application program from installed application programs according to a habit of using an application program by a user in response to the operation of double-tapping the Home key; and displaying the task management interface, and wherein the task management interface comprises information about the selected at least one application program. 2. The method according to claim 1, wherein the information about the selected at least one application program comprises an icon corresponding to the at least one application program and a preview interface of the at least one application program. 3. The method according to claim 1, wherein selecting the at least one application program from the installed application programs comprises selecting the at least one application program from the installed application programs according to use of the application program by the user in daily life. 4. The method according to claim 3, wherein selecting the at least one application program from the installed application programs comprises selecting the at least one application program from the installed application programs according to a frequency of using the application program by the user in different time periods. 5. The method according to claim 3, wherein selecting the at least one application program from the installed application programs according to the use of the application program by the user in daily life is comprises selecting the at least one application program from the installed application programs according to a frequency of using the application program by the user when human body characteristic parameters of the user comprise different thresholds. 6. The method according to claim 3, wherein selecting the at least one application program from the installed application programs according to the use of the application program by the user in daily life comprises selecting the at least one application program from the installed application programs according to a frequency of using the application program by the user in different locations. 7. The method according to claim 1, wherein after displaying the task management interface, the method further comprises:
receiving an operation instruction for the information about the selected at least one application program; switching the at least one application program to a foreground in response to the operation instruction; and running the at least one application program. 8.-9. (canceled) 10. A method for running an application program, comprising:
receiving a first operation instruction; displaying a user interface in response to the first operation instruction, wherein the user interface comprises an icon of at least one application program, and wherein the application program is selected from installed application programs according to a habit of using the application program by a user; receiving a second operation instruction for an icon of the application program; switching the application program to a foreground in response to the second operation instruction; and running the application program. 11. The method according to claim 10, wherein the application program is selected from the installed application programs according to use of the application program by the user in daily life. 12. The method according to claim 10, wherein the application program is selected from the installed application programs according to a frequency of using the application program by the user in different time periods. 13. The method according to claim 10, wherein the application program is selected from the installed application programs according to a frequency of using the application program by the user when human body characteristic parameters of the user comprise different thresholds. 14. The method according to claim 10, wherein the application program is selected from the installed application programs according to a frequency of using the application program by the user in different locations. 15.-31. (canceled) 32. An apparatus for running an application program, comprising:
a memory configured to store instructions; and a processor coupled to the memory, wherein the instructions cause the processor to be configured to:
receive an operation of double-tapping a Home key;
select at least one application program from installed application programs according to a habit of using an application program by a user in response to the operation of double-tapping the Home key; and
display a task management interface, and
wherein the task management interface comprises information about the selected at least one application program. 33. The apparatus of claim 32, wherein the information about the at least one application program comprises an icon corresponding to the at least one application program or a preview interface of the at least one application program. 34. The apparatus of claim 32, wherein when selecting the at least one application program from the installed application programs, the instructions further cause the processor to be configured to select the at least one application program from the installed application programs according to use of the application program by the user in daily life. 35. The apparatus of claim 34, wherein when selecting the at least one application program, the instructions further cause the processor to be configured to select the at least one application program from the installed application programs according to a frequency of using the application program by the user in different time periods. 36. The apparatus of claim 34, wherein when selecting the at least one application program, the instructions further cause the processor to be configured to select the at least one application program from the installed application programs according to a frequency of using the application program by the user when human body characteristic parameters of the user comprise different thresholds. 37. The apparatus of claim 34, wherein when selecting the at least one application program, the instructions further cause the processor to be configured to select the at least one application program from the installed application programs according to a frequency of using the application program by the user in different locations. 38. The apparatus of claim 32, wherein the instructions further cause the processor to be configured to:
receive an operation instruction for the information about the selected at least one application program after displaying the task management interface; switch the at least one application program to a foreground in response to the operation instruction; and run the at least one application program. 39. The method according to claim 1, wherein the information about the at least one application program comprises an icon corresponding to the at least one application program or a preview interface of the at least one application program. | 2,100 |
6,049 | 6,049 | 15,261,598 | 2,186 | A circuit for modifying a clock signal, the circuit comprising: a delay unit configured to receive the clock signal and delay the clock signal so as to output a plurality of delayed versions of the clock signal, each delayed version being delayed by a different amount of delay to the other delayed versions; a delay estimator configured to determine an amount of delay for modifying the clock signal; and a multiplexer configured to: receive each of the delayed versions of the clock signal; select a delayed version of the clock signal in dependence on the determined amount of delay; and output the selected version of the clock signal. | 1. A circuit for modifying a clock signal, the circuit comprising:
a delay unit configured to receive the clock signal and delay the clock signal so as to output a plurality of delayed versions of the clock signal, each delayed version being delayed by a different amount of delay to the other delayed versions; a delay estimator configured to determine an amount of delay for modifying the clock signal; and a multiplexer configured to: receive each of the delayed versions of the clock signal; select a delayed version of the clock signal in dependence on the determined amount of delay; and output the selected version of the clock signal. 2. A circuit as claimed in claim 1, wherein the multiplexer is further configured to, prior to selecting and outputting said delayed version, select and output an intermediate delayed version of the clock signal, the intermediate delayed version having a delay that is smaller than the determined amount of delay. 3. A circuit as claimed in claim 2, wherein the multiplexer is configured to output the intermediate delayed version of the clock signal for more than one clock period prior to outputting the selected delayed version of the clock signal. 4. A circuit as claimed in claim 1, wherein the circuit further comprises a signal modifier configured to gate the clock signal so as to cause one or more pulses from the clock signal to be removed. 5. A circuit as claimed in claim 4, wherein the signal modifier is configured to gate the clock signal if the amount of delay determined by the delay estimator is greater than one clock period of the clock signal. 6. A circuit as claimed in claim 1, wherein the delay unit comprises a series of delay signal lines, each delay signal line being coupled to a clock signal line for receiving the clock signal, each delay signal line being configured to delay the clock signal by a different amount of delay to the other delay signal lines so as to provide the plurality of delayed versions of the clock signal. 7. A circuit as claimed in claim 6, wherein each delay line comprises a number of buffers, the number of buffers for each delay line being different to the other delay lines, each buffer being configured to delay the second signal by a predetermined amount of time. 8. A circuit as claimed in claim 1, wherein the delay unit is configured to provide n delayed versions of the clock signal, wherein the delay for the ith delayed version is delay(i)=iT, where i=1, 2, 3 . . . n and T is a predetermined amount of time. 9. A circuit as claimed in claim 8, wherein the predetermined amount of time is 2, 3 or 4 nanoseconds. 10. A circuit as claimed in claim 1, wherein the amount of delay for modifying the clock signal is less than one clock period of the clock signal. 11. A circuit as claimed in claim 1, wherein:
the determined amount of delay for modifying the clock signal is equal to or greater than one clock period of the clock signal; and the amount of delay for each of the delayed versions of the clock signal is less than a clock period of the clock signal, the multiplexer being further configured to: select and output a first delayed version of the clock signal; and one or more clock periods subsequent to selecting and outputting the first delayed version, select and output a second delayed version of the clock signal, the combined delay of the first and second delayed versions corresponding to the determined amount of delay for modifying the clock signal. 12. A device comprising the circuit of claim 1 and a clock for generating the clock signal, the clock signal being provided to the circuit, the device being configured to perform a time-sensitive task in dependence on the modified clock signal from the circuit. 13. A method of modifying a clock signal, the method comprising:
delaying the clock signal so as to provide a plurality of delayed versions of the clock signal, each delayed version being delayed by a different amount of delay to the other delayed versions; determining an amount of delay for modifying the clock signal; and selecting a delayed version of the clock signal in dependence on the determined amount of delay; and outputting the selected version of the clock signal. 14. A method as claimed in claim 13, further comprising: prior to selecting and outputting said delayed version, selecting and outputting an intermediate delayed version of the clock signal, the intermediate delayed version having a delay that is smaller than the determined amount of delay. 15. A method as claimed in claim 14, wherein the intermediate delayed version of the clock signal is outputted for more than one clock period prior to outputting the selected delayed version of the clock signal. 16. A method as claimed in claim 13, further comprising gating the clock signal so as to cause one or more pulses from the clock signal to be removed. 17. A method as claimed in claim 16, wherein performing the gating step if the amount of delay determined by the delay estimator is greater than one clock period of the clock signal. 18. A method as claimed in claim 13, wherein performing said delaying using a series of delay signal lines, each delay signal line being coupled to a clock signal line for receiving the clock signal, each delay signal line being configured to delay the clock signal by a different amount of delay to the other delay signal lines so as to provide the plurality of delayed versions of the clock signal. 19. A method as claimed in claim 18, wherein each delay line comprises a number of buffers, the number of buffers for each delay line being different to the other delay lines, each buffer being configured to delay the second signal by a predetermined amount of time. 20. A method as claimed in claim 13, wherein:
the determined amount of delay for modifying the clock signal is equal to or greater than one clock period of the clock signal; and the amount of delay for each of the delayed versions of the clock signal is less than a clock period of the clock signal; the method comprising: selecting and outputting a first delayed version of the clock signal; and one or more clock periods subsequent to selecting and outputting the first delayed version, selecting and outputting a second delayed version of the clock signal, wherein the combined delay of the first and second delayed versions corresponds to the determined amount of delay for modifying the clock signal. | A circuit for modifying a clock signal, the circuit comprising: a delay unit configured to receive the clock signal and delay the clock signal so as to output a plurality of delayed versions of the clock signal, each delayed version being delayed by a different amount of delay to the other delayed versions; a delay estimator configured to determine an amount of delay for modifying the clock signal; and a multiplexer configured to: receive each of the delayed versions of the clock signal; select a delayed version of the clock signal in dependence on the determined amount of delay; and output the selected version of the clock signal.1. A circuit for modifying a clock signal, the circuit comprising:
a delay unit configured to receive the clock signal and delay the clock signal so as to output a plurality of delayed versions of the clock signal, each delayed version being delayed by a different amount of delay to the other delayed versions; a delay estimator configured to determine an amount of delay for modifying the clock signal; and a multiplexer configured to: receive each of the delayed versions of the clock signal; select a delayed version of the clock signal in dependence on the determined amount of delay; and output the selected version of the clock signal. 2. A circuit as claimed in claim 1, wherein the multiplexer is further configured to, prior to selecting and outputting said delayed version, select and output an intermediate delayed version of the clock signal, the intermediate delayed version having a delay that is smaller than the determined amount of delay. 3. A circuit as claimed in claim 2, wherein the multiplexer is configured to output the intermediate delayed version of the clock signal for more than one clock period prior to outputting the selected delayed version of the clock signal. 4. A circuit as claimed in claim 1, wherein the circuit further comprises a signal modifier configured to gate the clock signal so as to cause one or more pulses from the clock signal to be removed. 5. A circuit as claimed in claim 4, wherein the signal modifier is configured to gate the clock signal if the amount of delay determined by the delay estimator is greater than one clock period of the clock signal. 6. A circuit as claimed in claim 1, wherein the delay unit comprises a series of delay signal lines, each delay signal line being coupled to a clock signal line for receiving the clock signal, each delay signal line being configured to delay the clock signal by a different amount of delay to the other delay signal lines so as to provide the plurality of delayed versions of the clock signal. 7. A circuit as claimed in claim 6, wherein each delay line comprises a number of buffers, the number of buffers for each delay line being different to the other delay lines, each buffer being configured to delay the second signal by a predetermined amount of time. 8. A circuit as claimed in claim 1, wherein the delay unit is configured to provide n delayed versions of the clock signal, wherein the delay for the ith delayed version is delay(i)=iT, where i=1, 2, 3 . . . n and T is a predetermined amount of time. 9. A circuit as claimed in claim 8, wherein the predetermined amount of time is 2, 3 or 4 nanoseconds. 10. A circuit as claimed in claim 1, wherein the amount of delay for modifying the clock signal is less than one clock period of the clock signal. 11. A circuit as claimed in claim 1, wherein:
the determined amount of delay for modifying the clock signal is equal to or greater than one clock period of the clock signal; and the amount of delay for each of the delayed versions of the clock signal is less than a clock period of the clock signal, the multiplexer being further configured to: select and output a first delayed version of the clock signal; and one or more clock periods subsequent to selecting and outputting the first delayed version, select and output a second delayed version of the clock signal, the combined delay of the first and second delayed versions corresponding to the determined amount of delay for modifying the clock signal. 12. A device comprising the circuit of claim 1 and a clock for generating the clock signal, the clock signal being provided to the circuit, the device being configured to perform a time-sensitive task in dependence on the modified clock signal from the circuit. 13. A method of modifying a clock signal, the method comprising:
delaying the clock signal so as to provide a plurality of delayed versions of the clock signal, each delayed version being delayed by a different amount of delay to the other delayed versions; determining an amount of delay for modifying the clock signal; and selecting a delayed version of the clock signal in dependence on the determined amount of delay; and outputting the selected version of the clock signal. 14. A method as claimed in claim 13, further comprising: prior to selecting and outputting said delayed version, selecting and outputting an intermediate delayed version of the clock signal, the intermediate delayed version having a delay that is smaller than the determined amount of delay. 15. A method as claimed in claim 14, wherein the intermediate delayed version of the clock signal is outputted for more than one clock period prior to outputting the selected delayed version of the clock signal. 16. A method as claimed in claim 13, further comprising gating the clock signal so as to cause one or more pulses from the clock signal to be removed. 17. A method as claimed in claim 16, wherein performing the gating step if the amount of delay determined by the delay estimator is greater than one clock period of the clock signal. 18. A method as claimed in claim 13, wherein performing said delaying using a series of delay signal lines, each delay signal line being coupled to a clock signal line for receiving the clock signal, each delay signal line being configured to delay the clock signal by a different amount of delay to the other delay signal lines so as to provide the plurality of delayed versions of the clock signal. 19. A method as claimed in claim 18, wherein each delay line comprises a number of buffers, the number of buffers for each delay line being different to the other delay lines, each buffer being configured to delay the second signal by a predetermined amount of time. 20. A method as claimed in claim 13, wherein:
the determined amount of delay for modifying the clock signal is equal to or greater than one clock period of the clock signal; and the amount of delay for each of the delayed versions of the clock signal is less than a clock period of the clock signal; the method comprising: selecting and outputting a first delayed version of the clock signal; and one or more clock periods subsequent to selecting and outputting the first delayed version, selecting and outputting a second delayed version of the clock signal, wherein the combined delay of the first and second delayed versions corresponds to the determined amount of delay for modifying the clock signal. | 2,100 |
6,050 | 6,050 | 15,186,223 | 2,167 | The technology described herein provides for a match fix-up stage that removes matching documents identified for a search query that don't actually contain terms from the search query. A representation of each document (e.g., a forward index storing a list of terms for each document) is used to identify valid matching documents (i.e., documents containing terms from the search query) and invalid matching documents (i.e., documents that don't contain terms from the search query). Any invalid matching documents are removed from further processing and ranking for the search query. | 1. A computer-implemented method, carried out by at least one server having one or more processors, the method comprising:
receiving a plurality of documents found to be relevant to at least a portion of a search query, wherein the plurality of documents includes one or more invalid matching documents; accessing a representation for each document of the plurality of documents, wherein the representation includes each term present within each document; comparing the terms present within each document to one or more terms associated with the search query; determining that the one or more invalid matching documents do not include the one or more terms associated with the search query; and upon determining that the one or more invalid matching documents do not include the one or more terms associated with the search query, removing the one or more invalid matching documents from the plurality of documents found to be relevant to the at least a portion of the search query. 2. The method of claim 1, wherein the one or more invalid matching documents are documents that are not relevant to the at least a portion of the search but are included in the plurality of documents found to be relevant to the at least a portion of the search query. 3. The method of claim 1, wherein the representation includes a forward index for each document of the plurality of documents. 4. The method of claim 3, wherein the forward index includes each term included within each document of the plurality of documents. 5. The method of claim 3, wherein the forward index includes a portion of terms that is included within each document of the plurality of documents. 6. The method of claim 1, wherein, prior to removal of the one or more invalid matching documents, the plurality of documents found to be relevant to the at least a portion of the search query is associated with a false positive rate greater than 0%. 7. The method of claim 1, wherein the representation is a data structure. 8. The method of claim 1, further comprising communicating the plurality of documents found to be relevant to the at least a portion of the search query on to a ranker subsequent to removing the one or more invalid matching documents. 9. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method, the method comprising:
receiving a first plurality of documents found to be relevant to at least a portion of a search query, wherein the first plurality of documents includes one or more invalid matching documents; receiving a forward index for each document of the first plurality of documents, wherein the forward index includes one or more terms included in each document; using the forward index for each document of the first plurality of documents, identifying one or more valid matching documents that include one or more terms associated with the search query; using the forward index for each document of the first plurality of documents, identifying one or more invalid matching documents that do not include the one or more terms associated with the search query; removing the one or more invalid matching documents from the first plurality of documents to create a filtered set of one or more documents found to be relevant to the at least a portion of the search query; and communicating the filtered set of one or more documents found to be relevant to the at least a portion of the search query for ranking each document of the filtered set of one or more documents for the search query. 10. The media of claim 9, wherein the forward index for each document is associated with a data structure. 11. The media of claim 9, wherein the first plurality of documents are received from a preliminary ranker that ranked each document of the first plurality of documents for the search query. 12. The media of claim 9, wherein the forward index for each document includes each term included in each document. 13. The media of claim 9, wherein the forward index for each document includes a portion of terms included in each document. 14. The media of claim 9, wherein a false positive rate of greater than 0% is associated with the first plurality of documents. 15. A computerized system embodied on one or more computer storage media having computer-executable instructions provided thereon, the system comprising:
a preliminary ranker component to rank a first set of documents that are found to be relevant to at least a portion of a search query by a matcher component, wherein the initial set of documents includes one or more invalid matching documents; a match fix-up component to identify when the first set of documents includes one or more invalid matching documents utilizing a forward index for each document of the initial set of documents; and a subsequent ranker to rank a second set of documents received from the match fix-up component, wherein the second set of documents includes fewer invalid matching documents that the first set of documents. 16. The system of claim 15, wherein the match fix-up component includes the forward index for each document including each term associated with each document. 17. The system of claim 15, wherein the match fix-up component includes the forward index for each document including a portion of terms associated with each document. 18. The system of claim 15, wherein the match fix-up component includes a data structure associated with the forward index. 19. The system of claim 15, wherein the match fix-up component removes the one or more invalid matching documents from the first set of documents. 20. The system of claim 19, wherein, prior to removal of the one or more invalid matching documents, the first set of documents is associated with a false positive rate greater than 0%. | The technology described herein provides for a match fix-up stage that removes matching documents identified for a search query that don't actually contain terms from the search query. A representation of each document (e.g., a forward index storing a list of terms for each document) is used to identify valid matching documents (i.e., documents containing terms from the search query) and invalid matching documents (i.e., documents that don't contain terms from the search query). Any invalid matching documents are removed from further processing and ranking for the search query.1. A computer-implemented method, carried out by at least one server having one or more processors, the method comprising:
receiving a plurality of documents found to be relevant to at least a portion of a search query, wherein the plurality of documents includes one or more invalid matching documents; accessing a representation for each document of the plurality of documents, wherein the representation includes each term present within each document; comparing the terms present within each document to one or more terms associated with the search query; determining that the one or more invalid matching documents do not include the one or more terms associated with the search query; and upon determining that the one or more invalid matching documents do not include the one or more terms associated with the search query, removing the one or more invalid matching documents from the plurality of documents found to be relevant to the at least a portion of the search query. 2. The method of claim 1, wherein the one or more invalid matching documents are documents that are not relevant to the at least a portion of the search but are included in the plurality of documents found to be relevant to the at least a portion of the search query. 3. The method of claim 1, wherein the representation includes a forward index for each document of the plurality of documents. 4. The method of claim 3, wherein the forward index includes each term included within each document of the plurality of documents. 5. The method of claim 3, wherein the forward index includes a portion of terms that is included within each document of the plurality of documents. 6. The method of claim 1, wherein, prior to removal of the one or more invalid matching documents, the plurality of documents found to be relevant to the at least a portion of the search query is associated with a false positive rate greater than 0%. 7. The method of claim 1, wherein the representation is a data structure. 8. The method of claim 1, further comprising communicating the plurality of documents found to be relevant to the at least a portion of the search query on to a ranker subsequent to removing the one or more invalid matching documents. 9. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method, the method comprising:
receiving a first plurality of documents found to be relevant to at least a portion of a search query, wherein the first plurality of documents includes one or more invalid matching documents; receiving a forward index for each document of the first plurality of documents, wherein the forward index includes one or more terms included in each document; using the forward index for each document of the first plurality of documents, identifying one or more valid matching documents that include one or more terms associated with the search query; using the forward index for each document of the first plurality of documents, identifying one or more invalid matching documents that do not include the one or more terms associated with the search query; removing the one or more invalid matching documents from the first plurality of documents to create a filtered set of one or more documents found to be relevant to the at least a portion of the search query; and communicating the filtered set of one or more documents found to be relevant to the at least a portion of the search query for ranking each document of the filtered set of one or more documents for the search query. 10. The media of claim 9, wherein the forward index for each document is associated with a data structure. 11. The media of claim 9, wherein the first plurality of documents are received from a preliminary ranker that ranked each document of the first plurality of documents for the search query. 12. The media of claim 9, wherein the forward index for each document includes each term included in each document. 13. The media of claim 9, wherein the forward index for each document includes a portion of terms included in each document. 14. The media of claim 9, wherein a false positive rate of greater than 0% is associated with the first plurality of documents. 15. A computerized system embodied on one or more computer storage media having computer-executable instructions provided thereon, the system comprising:
a preliminary ranker component to rank a first set of documents that are found to be relevant to at least a portion of a search query by a matcher component, wherein the initial set of documents includes one or more invalid matching documents; a match fix-up component to identify when the first set of documents includes one or more invalid matching documents utilizing a forward index for each document of the initial set of documents; and a subsequent ranker to rank a second set of documents received from the match fix-up component, wherein the second set of documents includes fewer invalid matching documents that the first set of documents. 16. The system of claim 15, wherein the match fix-up component includes the forward index for each document including each term associated with each document. 17. The system of claim 15, wherein the match fix-up component includes the forward index for each document including a portion of terms associated with each document. 18. The system of claim 15, wherein the match fix-up component includes a data structure associated with the forward index. 19. The system of claim 15, wherein the match fix-up component removes the one or more invalid matching documents from the first set of documents. 20. The system of claim 19, wherein, prior to removal of the one or more invalid matching documents, the first set of documents is associated with a false positive rate greater than 0%. | 2,100 |
6,051 | 6,051 | 14,498,325 | 2,168 | The present embodiments relate generally to a computer device, system and method of identifying an application type of unknown data. The method may include: determining that the unknown data corresponds to database information, the database information comprising at least one table with at least one column; for a column of a table in the database information, determining if a column identifier of the column comprises a keyword associated with a particular application type; and if the column identifier comprises the keyword, identifying data stored in the database as belonging to an application that is of the particular application type. | 1. A method of identifying an application type of unknown data, the method comprising:
determining that the unknown data corresponds to database information, the database information comprising at least one table with at least one column; for a column of a table in the database information, determining if a column identifier of the column comprises a keyword associated with a particular application type; and if the column identifier comprises the keyword, identifying data stored in the database as belonging to an application that is of the particular application type. 2. The method of claim 1, wherein the keyword is associated with a data field that is commonly used by an application of the particular application type. 3. The method of claim 2, wherein prior to identifying the data stored in the database as belonging to an application that is of the particular application type, the method further comprises:
sampling a data record in the table; and determining that data for the column in the data record is consistent with data for the data field that would belong to an application of the particular application type. 4. The method of claim 3, wherein the data field comprises a date/time field, and the method further comprises:
converting the data in the column in the data record to each of a plurality of date/time formats; comparing the converted data, in each respective date/time format, to each other to determine which converted data is closest to a reference date/time; and for the converted data that is closest to the reference date/time, identifying the date/time format of the converted data as the date/time format of the data in the column of the table. 5. The method of claim 2, wherein the method further comprises:
storing a mapping between the data field and the column, the mapping being accessible during recovery of data in the database to indicate that data for the column in the table is associated with the data field. 6. The method of claim 5, further comprising:
displaying the mapping between the data field and the column in a user interface, wherein the user interface provides an option to select an alternative column of the table to be mapped to the data field; receiving input indicating that the data field is to be mapped to the alternative column; and storing an updated mapping for the data field, the updated mapping indicating that the data field is mapped to the alternative column. 7. The method of claim 2, wherein the particular application type comprises a messaging application, and the data field that is commonly used comprises one of: a sender field, a recipient field, a message field, and a timestamp field. 8. The method of claim 2, wherein the particular application type comprises a web browser application, and the data field that is commonly used comprises one of: an address field, a date field, a bookmark field, and a title field. 9. The method of claim 2, wherein the particular application type comprises a geographic location-enabled application, and the data field that is commonly used comprises one of: a longitude field, a latitude field, a destination field, a direction field, and a route field. 10. The method of claim 1, wherein the particular application type comprises a messaging application, and the keyword comprises one of the following words: message, subject, text, msg, body, content, date, time, timestamp, from, sender, author, uid, member, to, receiver, conversation, recipient, partner, participant, and party. 11. The method of claim 1, wherein the particular application type comprises a web browser application, and the keyword comprises one of the following words: address, location, loc, URL, visited, date, bookmark, favorite and title. 12. The method of claim 1, wherein the particular application type comprises a geographic location-enabled application, and the keyword comprises one of the following words: coordinate, longitude, latitude, location, loc, home, destination, direction, and route. 13. A computing device comprising a processor and a memory storing instructions which, when executed by the processor, cause the processor to perform the method as claimed in claim 1. 14. A computer readable medium comprising instructions which, when executed by a processor, cause the processor to perform the method as claimed in claim 1. 15. The computer readable medium of claim 14, wherein the computer readable medium is non-transitory. 16. A system adapted to perform any one or more of the methods as described in claim 1. 17. A device comprising at least one processor adapted to perform any one or more of the methods as described in claim 1. | The present embodiments relate generally to a computer device, system and method of identifying an application type of unknown data. The method may include: determining that the unknown data corresponds to database information, the database information comprising at least one table with at least one column; for a column of a table in the database information, determining if a column identifier of the column comprises a keyword associated with a particular application type; and if the column identifier comprises the keyword, identifying data stored in the database as belonging to an application that is of the particular application type.1. A method of identifying an application type of unknown data, the method comprising:
determining that the unknown data corresponds to database information, the database information comprising at least one table with at least one column; for a column of a table in the database information, determining if a column identifier of the column comprises a keyword associated with a particular application type; and if the column identifier comprises the keyword, identifying data stored in the database as belonging to an application that is of the particular application type. 2. The method of claim 1, wherein the keyword is associated with a data field that is commonly used by an application of the particular application type. 3. The method of claim 2, wherein prior to identifying the data stored in the database as belonging to an application that is of the particular application type, the method further comprises:
sampling a data record in the table; and determining that data for the column in the data record is consistent with data for the data field that would belong to an application of the particular application type. 4. The method of claim 3, wherein the data field comprises a date/time field, and the method further comprises:
converting the data in the column in the data record to each of a plurality of date/time formats; comparing the converted data, in each respective date/time format, to each other to determine which converted data is closest to a reference date/time; and for the converted data that is closest to the reference date/time, identifying the date/time format of the converted data as the date/time format of the data in the column of the table. 5. The method of claim 2, wherein the method further comprises:
storing a mapping between the data field and the column, the mapping being accessible during recovery of data in the database to indicate that data for the column in the table is associated with the data field. 6. The method of claim 5, further comprising:
displaying the mapping between the data field and the column in a user interface, wherein the user interface provides an option to select an alternative column of the table to be mapped to the data field; receiving input indicating that the data field is to be mapped to the alternative column; and storing an updated mapping for the data field, the updated mapping indicating that the data field is mapped to the alternative column. 7. The method of claim 2, wherein the particular application type comprises a messaging application, and the data field that is commonly used comprises one of: a sender field, a recipient field, a message field, and a timestamp field. 8. The method of claim 2, wherein the particular application type comprises a web browser application, and the data field that is commonly used comprises one of: an address field, a date field, a bookmark field, and a title field. 9. The method of claim 2, wherein the particular application type comprises a geographic location-enabled application, and the data field that is commonly used comprises one of: a longitude field, a latitude field, a destination field, a direction field, and a route field. 10. The method of claim 1, wherein the particular application type comprises a messaging application, and the keyword comprises one of the following words: message, subject, text, msg, body, content, date, time, timestamp, from, sender, author, uid, member, to, receiver, conversation, recipient, partner, participant, and party. 11. The method of claim 1, wherein the particular application type comprises a web browser application, and the keyword comprises one of the following words: address, location, loc, URL, visited, date, bookmark, favorite and title. 12. The method of claim 1, wherein the particular application type comprises a geographic location-enabled application, and the keyword comprises one of the following words: coordinate, longitude, latitude, location, loc, home, destination, direction, and route. 13. A computing device comprising a processor and a memory storing instructions which, when executed by the processor, cause the processor to perform the method as claimed in claim 1. 14. A computer readable medium comprising instructions which, when executed by a processor, cause the processor to perform the method as claimed in claim 1. 15. The computer readable medium of claim 14, wherein the computer readable medium is non-transitory. 16. A system adapted to perform any one or more of the methods as described in claim 1. 17. A device comprising at least one processor adapted to perform any one or more of the methods as described in claim 1. | 2,100 |
6,052 | 6,052 | 14,678,532 | 2,128 | A system for machine learning model parameters for image compression, including partitioning image files into a first set of regions, determining a first set of machine learned model parameters based on the regions, the first set of machine learned model parameters representing a first level of patterns in the image files, constructing a representation of each of the regions based on the first set of machine learned model parameters, constructing representations of the image files by combining the representations of the regions in the first set of regions, partitioning the representations of the image files into a second set of regions, and determining a second set of machine learned model parameters based on the second set of regions, the second set of machine learned model parameters representing a second level of patterns in the image files. | 1. A computer implemented method for machine learning model parameters for image compression, comprising:
partitioning a plurality of image files stored on a first computer memory into a first set of regions; determining a first set of machine learned model parameters based on the first set of regions, the first set of machine learned model parameters representing a first level of patterns in the plurality of image files; constructing a representation of each region in the first set of regions based on the first set of machine learned model parameters; constructing representations of the plurality of image files by combining the representations of the regions in the first set of regions; partitioning the representations of the plurality of image files into a second set of regions; determining a second set of machine learned model parameters based on the second set of regions, the second set of machine learned model parameters representing a second level of patterns in the plurality of image files; and storing the first set of machine learned model parameters and the second set of machine learned model parameters on one or more computer memories. 2. The computer implemented method of claim 1, wherein the first set of machine learned model parameters and the second set of machine learned model parameters are used to compress and decompress a digital image file stored on a second computer memory. 3. The computer implemented method of claim 1, wherein:
each of the image files comprises pixel values for rendering an image on a display and each of the regions in the first set of regions comprises a subset of the pixel values for rendering a corresponding region of the image on the display. 4. The computer implemented method of claim 1, wherein:
each region in the first set of regions overlaps at least one other region in the first set of regions; and each region in the second set of regions overlaps at least one other region in the second set of regions. 5. The computer implemented method of claim 4, wherein each of the first set of regions comprises an M by M array of pixel values, wherein M is an integer. 6. The computer implemented method of claim 5, wherein each of the second set of regions comprises an N by N array of pixel values, wherein N is greater than M. 7. The computer implemented method of claim 1, wherein:
the first set of machine learned model parameters and the second set of machine learned model parameters are determined based on a statistical method for estimating a structure underlying a set of data. 8. The computer implemented method of claim 1, wherein:
determining a first set of machine learned model parameters comprises machine learning a first union of subspaces that estimates each of the regions in the first set of regions, wherein the first set of machine learned model parameters includes basis vectors and offsets for subspaces in the first union of subspaces; and determining a second set of machine learned model parameters comprises machine learning a second union of subspaces that estimates each of the regions in the second set of region, wherein the second set of machine learned model parameters includes basis vectors and offsets for subspaces in the second union of subspaces. 9. The computer implemented method of claim 8, wherein:
the first union of subspaces and the second union of subspaces are machine learned based on a Mixture of Factor Analyzers. 10. The computer implemented method of claim 8, wherein:
a quantity and a dimension of subspaces in the first union of subspaces are determined based on the plurality of image files; and a quantity and a dimension of subspaces in the second union of subspaces is determined based on the representations of the plurality of image files. 11. A computer implemented method for compressing an image file, comprising:
partitioning an image file into a first set of regions; constructing a representation of each region in the first set of regions based on a first set of machine learned model parameters, the first set of machine learned model parameters representing a first level of image patterns; constructing a first representation of the image file by combining the representations of the regions in the first set of regions; partitioning the first representation of the image file into a second set of regions; constructing a representation of each region in the second set of regions based on a second set of machine learned model parameters, the second set of machine learned model parameters representing a second level of image patterns; constructing a second representation of the image file by combining the representations of the regions in the second set of regions, wherein the second representation comprises coefficients of the machine learned model parameters in the second set of machine learned model parameters; selecting a plurality of elements from a predetermined list of elements to represent the model parameter coefficients; and storing a plurality of indices to the plurality of elements in a memory. 12. The computer implemented method of claim 11, wherein
each region in the first set of regions overlaps at least one other region in the first set of regions; and each region in the second set of regions overlaps at least one other region in the second set of regions. 13. The computer implemented method of claim 11, wherein the first set of machine learned model parameters and the second set of machine learned model parameters are based on a statistical model for estimating a structure underlying a set of training data. 14. The computer implemented method of claim 12, wherein the statistical model comprises a Mixture of Factor Analyzers. 15. The computer implemented method of claim 11, wherein the first representation comprises coefficients of the machine learned model parameters in the first set of machine learned model parameters; the method further comprising:
selecting a second plurality of elements from a second predetermined list of elements to represent the coefficients of the machine learned model parameters in the first set of machine learned model parameters; and storing a second plurality of indices to the second plurality of elements in the memory. 16. A computer implemented method for decompressing an image file comprising:
opening a compressed image file comprising a plurality of indices to a plurality of elements from a predetermined list of elements, wherein the predetermined list of elements is based on a first set of machine learned model parameters representing a first level of image patterns and a second set of machine learned model parameters representing a second level of image patterns; retrieving the plurality of elements from the predetermined list of elements based on the plurality of indices; constructing a plurality of regions of an image file by combining the plurality of elements with the second set of machine learned model parameters; and blending the plurality of regions to generate a decompressed image file. 17. The computer implemented method of claim 16, wherein the first set of machine learned model parameters and the second set of machine learned model parameters are based on a statistical model for estimating a structure underlying a set of training data. 18. The computer implemented method of claim 16, wherein the statistical model comprises a Mixture of Factor Analyzers. 19. A computer implemented method for decompressing an image file comprising:
opening a compressed image file comprising:
a first plurality of indices to a first plurality of elements from a first predetermined list of elements, wherein the first predetermined list of elements is based on a first set of machine learned model parameters representing a first level of image patterns, and
a second plurality of indices to a second plurality of elements from a second predetermined list of elements, wherein the second predetermined list of elements is based on a second set of machine learned model parameters representing a second level of image patterns;
retrieving the first plurality of elements from the first predetermined list of elements based on the first plurality of indices; constructing a first plurality of regions of an image file by combining the first plurality of elements with the first set of machine learned model parameters; retrieving the second plurality of elements from the second predetermined list of elements based on the second plurality of indices; constructing a second plurality of regions of an image file by combining the second plurality of elements with the second set of machine learned model parameters and the first plurality of regions; and blending the second plurality of regions to generate a decompressed image file. 20. A system for compressing an image file comprising:
a training module for learning model parameters comprising a processor and a memory and one or more applications stored in the memory that include instructions for:
partitioning a plurality of image files into a first set of regions;
determining a first set of machine learned model parameters based on the first set of regions, the first set of machine learned model parameters representing a first level of patterns in the plurality of image files;
constructing a representation of each region in the first set of regions based on the first set of machine learned model parameters;
constructing representations of the plurality of image files by combining the representations of the regions in the first set of regions;
partitioning the representations of the plurality of image files into a second set of regions; and
determining a second set of machine learned model parameters based on the second set of regions, the second set of machine learned model parameters representing a second level of patterns in the plurality of image files; and
a compression module configured to generate a compressed image file based on the first set of machine learned model parameters and the second set of machine learned model parameters. 21. The system of claim 20, comprising a decompression module configured to decompress the compressed image file based on the second set of machine learned model parameters. 22. 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, cause the device to:
partition an image file into a first set of regions; construct a representation of each region in the first set of regions based on a first set of machine learned model parameters, the first set of machine learned model parameters representing a first level of image patterns; construct a first representation of the image file by combining the representations of the regions in the first set of regions; partition the first representation of the image file into a second set of regions; construct a representation of each region in the second set of regions based on a second set of machine learned model parameters, the second set of machine learned model parameters representing a second level of image patterns; construct a second representation of the image file by combining the representations of the regions in the second set of regions, wherein the second representation comprises coefficients of the machine learned model parameters in the second set of machine learned model parameters; select a plurality of elements from a predetermined list of elements to represent the model parameter coefficients; and store a plurality of indices to the plurality of elements in a memory. | A system for machine learning model parameters for image compression, including partitioning image files into a first set of regions, determining a first set of machine learned model parameters based on the regions, the first set of machine learned model parameters representing a first level of patterns in the image files, constructing a representation of each of the regions based on the first set of machine learned model parameters, constructing representations of the image files by combining the representations of the regions in the first set of regions, partitioning the representations of the image files into a second set of regions, and determining a second set of machine learned model parameters based on the second set of regions, the second set of machine learned model parameters representing a second level of patterns in the image files.1. A computer implemented method for machine learning model parameters for image compression, comprising:
partitioning a plurality of image files stored on a first computer memory into a first set of regions; determining a first set of machine learned model parameters based on the first set of regions, the first set of machine learned model parameters representing a first level of patterns in the plurality of image files; constructing a representation of each region in the first set of regions based on the first set of machine learned model parameters; constructing representations of the plurality of image files by combining the representations of the regions in the first set of regions; partitioning the representations of the plurality of image files into a second set of regions; determining a second set of machine learned model parameters based on the second set of regions, the second set of machine learned model parameters representing a second level of patterns in the plurality of image files; and storing the first set of machine learned model parameters and the second set of machine learned model parameters on one or more computer memories. 2. The computer implemented method of claim 1, wherein the first set of machine learned model parameters and the second set of machine learned model parameters are used to compress and decompress a digital image file stored on a second computer memory. 3. The computer implemented method of claim 1, wherein:
each of the image files comprises pixel values for rendering an image on a display and each of the regions in the first set of regions comprises a subset of the pixel values for rendering a corresponding region of the image on the display. 4. The computer implemented method of claim 1, wherein:
each region in the first set of regions overlaps at least one other region in the first set of regions; and each region in the second set of regions overlaps at least one other region in the second set of regions. 5. The computer implemented method of claim 4, wherein each of the first set of regions comprises an M by M array of pixel values, wherein M is an integer. 6. The computer implemented method of claim 5, wherein each of the second set of regions comprises an N by N array of pixel values, wherein N is greater than M. 7. The computer implemented method of claim 1, wherein:
the first set of machine learned model parameters and the second set of machine learned model parameters are determined based on a statistical method for estimating a structure underlying a set of data. 8. The computer implemented method of claim 1, wherein:
determining a first set of machine learned model parameters comprises machine learning a first union of subspaces that estimates each of the regions in the first set of regions, wherein the first set of machine learned model parameters includes basis vectors and offsets for subspaces in the first union of subspaces; and determining a second set of machine learned model parameters comprises machine learning a second union of subspaces that estimates each of the regions in the second set of region, wherein the second set of machine learned model parameters includes basis vectors and offsets for subspaces in the second union of subspaces. 9. The computer implemented method of claim 8, wherein:
the first union of subspaces and the second union of subspaces are machine learned based on a Mixture of Factor Analyzers. 10. The computer implemented method of claim 8, wherein:
a quantity and a dimension of subspaces in the first union of subspaces are determined based on the plurality of image files; and a quantity and a dimension of subspaces in the second union of subspaces is determined based on the representations of the plurality of image files. 11. A computer implemented method for compressing an image file, comprising:
partitioning an image file into a first set of regions; constructing a representation of each region in the first set of regions based on a first set of machine learned model parameters, the first set of machine learned model parameters representing a first level of image patterns; constructing a first representation of the image file by combining the representations of the regions in the first set of regions; partitioning the first representation of the image file into a second set of regions; constructing a representation of each region in the second set of regions based on a second set of machine learned model parameters, the second set of machine learned model parameters representing a second level of image patterns; constructing a second representation of the image file by combining the representations of the regions in the second set of regions, wherein the second representation comprises coefficients of the machine learned model parameters in the second set of machine learned model parameters; selecting a plurality of elements from a predetermined list of elements to represent the model parameter coefficients; and storing a plurality of indices to the plurality of elements in a memory. 12. The computer implemented method of claim 11, wherein
each region in the first set of regions overlaps at least one other region in the first set of regions; and each region in the second set of regions overlaps at least one other region in the second set of regions. 13. The computer implemented method of claim 11, wherein the first set of machine learned model parameters and the second set of machine learned model parameters are based on a statistical model for estimating a structure underlying a set of training data. 14. The computer implemented method of claim 12, wherein the statistical model comprises a Mixture of Factor Analyzers. 15. The computer implemented method of claim 11, wherein the first representation comprises coefficients of the machine learned model parameters in the first set of machine learned model parameters; the method further comprising:
selecting a second plurality of elements from a second predetermined list of elements to represent the coefficients of the machine learned model parameters in the first set of machine learned model parameters; and storing a second plurality of indices to the second plurality of elements in the memory. 16. A computer implemented method for decompressing an image file comprising:
opening a compressed image file comprising a plurality of indices to a plurality of elements from a predetermined list of elements, wherein the predetermined list of elements is based on a first set of machine learned model parameters representing a first level of image patterns and a second set of machine learned model parameters representing a second level of image patterns; retrieving the plurality of elements from the predetermined list of elements based on the plurality of indices; constructing a plurality of regions of an image file by combining the plurality of elements with the second set of machine learned model parameters; and blending the plurality of regions to generate a decompressed image file. 17. The computer implemented method of claim 16, wherein the first set of machine learned model parameters and the second set of machine learned model parameters are based on a statistical model for estimating a structure underlying a set of training data. 18. The computer implemented method of claim 16, wherein the statistical model comprises a Mixture of Factor Analyzers. 19. A computer implemented method for decompressing an image file comprising:
opening a compressed image file comprising:
a first plurality of indices to a first plurality of elements from a first predetermined list of elements, wherein the first predetermined list of elements is based on a first set of machine learned model parameters representing a first level of image patterns, and
a second plurality of indices to a second plurality of elements from a second predetermined list of elements, wherein the second predetermined list of elements is based on a second set of machine learned model parameters representing a second level of image patterns;
retrieving the first plurality of elements from the first predetermined list of elements based on the first plurality of indices; constructing a first plurality of regions of an image file by combining the first plurality of elements with the first set of machine learned model parameters; retrieving the second plurality of elements from the second predetermined list of elements based on the second plurality of indices; constructing a second plurality of regions of an image file by combining the second plurality of elements with the second set of machine learned model parameters and the first plurality of regions; and blending the second plurality of regions to generate a decompressed image file. 20. A system for compressing an image file comprising:
a training module for learning model parameters comprising a processor and a memory and one or more applications stored in the memory that include instructions for:
partitioning a plurality of image files into a first set of regions;
determining a first set of machine learned model parameters based on the first set of regions, the first set of machine learned model parameters representing a first level of patterns in the plurality of image files;
constructing a representation of each region in the first set of regions based on the first set of machine learned model parameters;
constructing representations of the plurality of image files by combining the representations of the regions in the first set of regions;
partitioning the representations of the plurality of image files into a second set of regions; and
determining a second set of machine learned model parameters based on the second set of regions, the second set of machine learned model parameters representing a second level of patterns in the plurality of image files; and
a compression module configured to generate a compressed image file based on the first set of machine learned model parameters and the second set of machine learned model parameters. 21. The system of claim 20, comprising a decompression module configured to decompress the compressed image file based on the second set of machine learned model parameters. 22. 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, cause the device to:
partition an image file into a first set of regions; construct a representation of each region in the first set of regions based on a first set of machine learned model parameters, the first set of machine learned model parameters representing a first level of image patterns; construct a first representation of the image file by combining the representations of the regions in the first set of regions; partition the first representation of the image file into a second set of regions; construct a representation of each region in the second set of regions based on a second set of machine learned model parameters, the second set of machine learned model parameters representing a second level of image patterns; construct a second representation of the image file by combining the representations of the regions in the second set of regions, wherein the second representation comprises coefficients of the machine learned model parameters in the second set of machine learned model parameters; select a plurality of elements from a predetermined list of elements to represent the model parameter coefficients; and store a plurality of indices to the plurality of elements in a memory. | 2,100 |
6,053 | 6,053 | 13,834,098 | 2,153 | Various embodiments herein include one or more of systems, methods, and software providing augmenting middleware communication services. Embodiments generally include services executable to provide communication capabilities between a middleware platform and an application, such as an enterprise-class application, to facilitate access to data and functionality of the application by mobile applications that access application functionality and data via the middleware platform. Some embodiments include augmenting the application with at least one service to receive a call from a middleware object requesting data and to identify data to be included in a response to the request. The identified data may then be retrieved and returned to the calling middleware object. The call of the middleware object is typically received from a mobile device application and the middleware object provides data received in response to the request to the mobile application. | 1. A method comprising:
receiving a service call from a middleware object, the service call including a request for data; with regard to the data request, identifying data to be included in a response to the data request; retrieving the identified data; and calling a data transport process to build a first transport data structure containing the retrieved data and to transmit the first transport data structure to the middleware object. 2. The method of claim 1, wherein the service call is a Hyper-Text Transport Protocol call received over a network. 3. The method of claim 1, wherein identifying data to be included in the response to the data request includes:
retrieving data from a database table that identifies active data items the middleware object is capable of processing. 4. The method of claim 3, wherein the database table that identifies active data items the middleware object is capable of processing includes a row of data for each of a plurality of middleware objects, the row of data for each of the plurality of middleware objects identifying data items the respective middleware object is capable of processing. 5. The method of claim 1, wherein the first transport data structure built by the transport process is encoded in a format that identifies data items included in the transport data structure and values of each included data item. 6. The method of claim 5, wherein the format of the first transport data structure is a JavaScript Object Notation format. 7. The method of 1, further comprising:
receiving, from the middleware object, a second transport data structure including a data update; reading data, including the updated data, from the second transport data structure; determining data storage locations to which the updated data read from the second transport data structure is to be stored; issuing a data update command based on the updated data read from the second transport data structure and the determined data storage locations; upon receipt of a success response to the data update command, calling the data transport process to build a third transport data structure with a reference to the received second transport data structure and including data representative of the successful update and to transmit the third transport data structure to the middleware object; and upon receipt of a failure response to the data update command:
issuing a rollback command; and
calling the data transport process to build a fourth transport data structure with a reference to the received second transport data structure and including data representative of the update failure and to transmit the fourth transport data structure to the middleware object. 8. A non-transitory computer-readable medium, with instructions stored thereon, which when executed by at least one processor of at least one computing device, cause the at least one computing device to:
receive a service call from a middleware object, the service call including a request for data; identify data to be included in a response to the data request; retrieve the identified data; and call a data transport process to build a first transport data structure containing the retrieved data and to transmit the first transport data structure to the middleware object. 9. The non-transitory computer-readable medium of claim 8, wherein the middleware object is one of a plurality of middleware objects that exists within a middleware platform that operates to provide backend data and functionality access to mobile client apps over a network. 10. The non-transitory computer-readable medium of claim 8, wherein identifying data to be included in the response to the data request includes:
retrieving data from a database table that identifies active data items the middleware object is capable of processing. 11. The non-transitory computer-readable medium of claim 10, wherein the database table that identifies active data items the middleware object is capable of processing includes a row of data for each of a plurality of middleware objects, the row of data for each of the plurality of middleware objects identifying data items the respective middleware object is capable of processing. 12. The non-transitory computer-readable medium of claim 10, wherein:
the request for data is received as a remote function call that retrieves data when executed; and retrieving the identified data includes causing the remote function call to be executed to retrieve the data; and identifying data to be included in the response to the data request includes:
reading metadata associated with data items included in the retrieved data to identify any data items the middleware object is not capable of processing; and
removing any data items from the retrieved data that the middleware object is not capable of processing. 13. The non-transitory computer-readable medium of claim 8, wherein the first transport data structure built by the transport process is encoded in a format that identifies data items included in the transport data structure and values of each included data item. 14. The non-transitory computer-readable medium of claim 8, with further instructions stored thereon, which when executed by the at least one processor of the at least one computing device, further cause the at least one computing device to:
receive, from the middleware object, a second transport data structure including a data update; read data, including the updated data, from the second transport data structure; determine data storage locations to which the updated data read from the second transport data structure is to be stored; issue an update command based on the updated data read from the second transport data structure and the determined data storage locations; upon receipt of a success response to the data update command, call the data transport process to build a third transport data structure with a reference to the received second transport data structure and including data representative of the successful update and to transmit the third transport data structure to the middleware object; and upon receipt of a failure response to the data update command:
issue a rollback command; and
call the data transport process to build a fourth transport data structure with a reference to the received second transport data structure and including data representative of the update failure and to transmit the fourth transport data structure to the middleware object. 15. A system comprising:
at least one processor, at least one memory device, and at least one network interface device; an application stored on the at least one memory device and executable by the at least one processor to store data in a database and provide application functionality within a first networked computing environment via the at least one network interface device, at least a portion of the application functionality callable via one or more application services; a middleware interface module stored on the at least one memory device, the middleware interface module including a set of services executable by the at least one processor, the services including:
a download service to receive data download requests with regard to middleware objects, a data download request including at least a middleware object identifier, a response to the data download request generated by:
retrieving, from the database, identifiers of data items relevant to the requesting middleware object;
retrieving, from the database, data items corresponding to the retrieved data item identifiers; and
generating and transmitting a data structure including the retrieved data items to the middleware object of the middleware object identifier. 16. The system of claim 15, wherein the middleware interface module includes at least one further service, the at least once further service including:
an online service to receive and service functionality invoking requests from middleware objects via the at least one network interface device, the processing of a functionality invoking request including calling at least one application service, receiving a response thereto, and transmitting at least a portion of the response to a middleware object from which the functionality invoking request was received. 17. The system of claim 16, wherein the middleware interface module includes at least one further service, the at least once further service including:
an upload service to receive data updates from middleware objects, the upload service executable to:
receive, from a middleware object, a data structure including a data update;
determine database locations to which the updated data is to be stored;
issue at least one data update command to the database based on a the determined storage locations;
upon receipt of a success response to the data update command, transmitting a success response to the middleware object; and
upon receipt of a failure response to the data update command, rollback the data update and transmit a failure response to the middleware object. 18. The system of claim 17, wherein the download, online, and upload services are each remote functions that are callable by middleware objects via remote function calls. 19. The system of claim 17, wherein the middleware interface module includes at least one further service, the at least once further service including:
a transport service that upon receipt of a middleware object identifier and data to be transmitted to the identified middleware object, builds a transport data structure containing data for transmission to the identified middleware object encoded in a format that identifies data items included in the transport data structure and values of each included data item. 20. The system of claim 17, wherein the download, online, and upload services, when transmitting data to middleware objects calls the transport service. | Various embodiments herein include one or more of systems, methods, and software providing augmenting middleware communication services. Embodiments generally include services executable to provide communication capabilities between a middleware platform and an application, such as an enterprise-class application, to facilitate access to data and functionality of the application by mobile applications that access application functionality and data via the middleware platform. Some embodiments include augmenting the application with at least one service to receive a call from a middleware object requesting data and to identify data to be included in a response to the request. The identified data may then be retrieved and returned to the calling middleware object. The call of the middleware object is typically received from a mobile device application and the middleware object provides data received in response to the request to the mobile application.1. A method comprising:
receiving a service call from a middleware object, the service call including a request for data; with regard to the data request, identifying data to be included in a response to the data request; retrieving the identified data; and calling a data transport process to build a first transport data structure containing the retrieved data and to transmit the first transport data structure to the middleware object. 2. The method of claim 1, wherein the service call is a Hyper-Text Transport Protocol call received over a network. 3. The method of claim 1, wherein identifying data to be included in the response to the data request includes:
retrieving data from a database table that identifies active data items the middleware object is capable of processing. 4. The method of claim 3, wherein the database table that identifies active data items the middleware object is capable of processing includes a row of data for each of a plurality of middleware objects, the row of data for each of the plurality of middleware objects identifying data items the respective middleware object is capable of processing. 5. The method of claim 1, wherein the first transport data structure built by the transport process is encoded in a format that identifies data items included in the transport data structure and values of each included data item. 6. The method of claim 5, wherein the format of the first transport data structure is a JavaScript Object Notation format. 7. The method of 1, further comprising:
receiving, from the middleware object, a second transport data structure including a data update; reading data, including the updated data, from the second transport data structure; determining data storage locations to which the updated data read from the second transport data structure is to be stored; issuing a data update command based on the updated data read from the second transport data structure and the determined data storage locations; upon receipt of a success response to the data update command, calling the data transport process to build a third transport data structure with a reference to the received second transport data structure and including data representative of the successful update and to transmit the third transport data structure to the middleware object; and upon receipt of a failure response to the data update command:
issuing a rollback command; and
calling the data transport process to build a fourth transport data structure with a reference to the received second transport data structure and including data representative of the update failure and to transmit the fourth transport data structure to the middleware object. 8. A non-transitory computer-readable medium, with instructions stored thereon, which when executed by at least one processor of at least one computing device, cause the at least one computing device to:
receive a service call from a middleware object, the service call including a request for data; identify data to be included in a response to the data request; retrieve the identified data; and call a data transport process to build a first transport data structure containing the retrieved data and to transmit the first transport data structure to the middleware object. 9. The non-transitory computer-readable medium of claim 8, wherein the middleware object is one of a plurality of middleware objects that exists within a middleware platform that operates to provide backend data and functionality access to mobile client apps over a network. 10. The non-transitory computer-readable medium of claim 8, wherein identifying data to be included in the response to the data request includes:
retrieving data from a database table that identifies active data items the middleware object is capable of processing. 11. The non-transitory computer-readable medium of claim 10, wherein the database table that identifies active data items the middleware object is capable of processing includes a row of data for each of a plurality of middleware objects, the row of data for each of the plurality of middleware objects identifying data items the respective middleware object is capable of processing. 12. The non-transitory computer-readable medium of claim 10, wherein:
the request for data is received as a remote function call that retrieves data when executed; and retrieving the identified data includes causing the remote function call to be executed to retrieve the data; and identifying data to be included in the response to the data request includes:
reading metadata associated with data items included in the retrieved data to identify any data items the middleware object is not capable of processing; and
removing any data items from the retrieved data that the middleware object is not capable of processing. 13. The non-transitory computer-readable medium of claim 8, wherein the first transport data structure built by the transport process is encoded in a format that identifies data items included in the transport data structure and values of each included data item. 14. The non-transitory computer-readable medium of claim 8, with further instructions stored thereon, which when executed by the at least one processor of the at least one computing device, further cause the at least one computing device to:
receive, from the middleware object, a second transport data structure including a data update; read data, including the updated data, from the second transport data structure; determine data storage locations to which the updated data read from the second transport data structure is to be stored; issue an update command based on the updated data read from the second transport data structure and the determined data storage locations; upon receipt of a success response to the data update command, call the data transport process to build a third transport data structure with a reference to the received second transport data structure and including data representative of the successful update and to transmit the third transport data structure to the middleware object; and upon receipt of a failure response to the data update command:
issue a rollback command; and
call the data transport process to build a fourth transport data structure with a reference to the received second transport data structure and including data representative of the update failure and to transmit the fourth transport data structure to the middleware object. 15. A system comprising:
at least one processor, at least one memory device, and at least one network interface device; an application stored on the at least one memory device and executable by the at least one processor to store data in a database and provide application functionality within a first networked computing environment via the at least one network interface device, at least a portion of the application functionality callable via one or more application services; a middleware interface module stored on the at least one memory device, the middleware interface module including a set of services executable by the at least one processor, the services including:
a download service to receive data download requests with regard to middleware objects, a data download request including at least a middleware object identifier, a response to the data download request generated by:
retrieving, from the database, identifiers of data items relevant to the requesting middleware object;
retrieving, from the database, data items corresponding to the retrieved data item identifiers; and
generating and transmitting a data structure including the retrieved data items to the middleware object of the middleware object identifier. 16. The system of claim 15, wherein the middleware interface module includes at least one further service, the at least once further service including:
an online service to receive and service functionality invoking requests from middleware objects via the at least one network interface device, the processing of a functionality invoking request including calling at least one application service, receiving a response thereto, and transmitting at least a portion of the response to a middleware object from which the functionality invoking request was received. 17. The system of claim 16, wherein the middleware interface module includes at least one further service, the at least once further service including:
an upload service to receive data updates from middleware objects, the upload service executable to:
receive, from a middleware object, a data structure including a data update;
determine database locations to which the updated data is to be stored;
issue at least one data update command to the database based on a the determined storage locations;
upon receipt of a success response to the data update command, transmitting a success response to the middleware object; and
upon receipt of a failure response to the data update command, rollback the data update and transmit a failure response to the middleware object. 18. The system of claim 17, wherein the download, online, and upload services are each remote functions that are callable by middleware objects via remote function calls. 19. The system of claim 17, wherein the middleware interface module includes at least one further service, the at least once further service including:
a transport service that upon receipt of a middleware object identifier and data to be transmitted to the identified middleware object, builds a transport data structure containing data for transmission to the identified middleware object encoded in a format that identifies data items included in the transport data structure and values of each included data item. 20. The system of claim 17, wherein the download, online, and upload services, when transmitting data to middleware objects calls the transport service. | 2,100 |
6,054 | 6,054 | 15,281,633 | 2,116 | The invention relates to a method for automated control of at least one machine component ( 1 ) in a plant ( 2 ). The machine component ( 1 ) is connected via a secure bus connection ( 6 ) to an automation component ( 7 ) by which it is controlled. The plant ( 2 ) has a safety area ( 4 ) monitored by means of at least one safety sensor ( 3 ), where a deviation of the measurement pattern (M) measured by the safety sensor ( 3 ) from a definition area (D) indicates a hazardous situation for protection objects ( 5 ), in particular persons and/or valuables. The machine component ( 1 ) triggers a protective action if a hazardous situation arises. The measurement patterns (M) measured by the safety sensor ( 3 ) are transmitted to the automation component ( 7 ) via the secure bus connection ( 6 ). The automation component ( 7 ) defines the definition area (D) using parameter data of the automated control, ascertains the presence of a hazardous situation, and activates the machine component ( 1 ) for performing the protective action. | 1. Method for automated control of a least one machine component (1) in a plant (2) with an automation component (7), the machine component (1) being linked to an automation component (7) via a secure bus connection (6), the plant (2) having a safety area (4) monitored by means of at least one safety sensor (3) and the ma-chine component (1) performing a protective action if a hazardous situation detected by the safety sensor (3) for protection objects (5), in particular persons and/or valuables, arises, characterized in that a measurement pattern (M) measured by the safety sensor (3) is transmitted over the secure bus connection (6) to the automation component (7), the automation component (7) ascertaining the presence of a hazardous situation on the basis of a measurement pattern (M) and activating the machine component (1) to perform a protective action. 2. The method according to claim 1, characterized in that the protective action comprises a deactivation of at least parts of the machine component (1), the assumption of a protective position, an active reaction, for example the stopping of at least parts of the machine component (1), a change in the speed of at least parts of the ma-chine component (1), an evasive movement, the triggering of a safety device such as an airbag or an extinguishing device, the triggering of an alarm or a combination thereof. 3. The method according to claim 1, characterized in that hazardous situation is defined as the detection of foreign objects or persons in the safety area (4), the detection of positional errors of machine component (1) parts and/or the detection of positional errors of plant objects (8). 4. The method according to claim 1, characterized in that the safety sensor (3) has at least one light grid arrangement (9). 5. The method according to claim 4, characterized in that at least two light grid arrangements (9, 9′) can be arranged parallel next to one another in relation to the grid plane and displaced from one another in relation to the longitudinal extension of their light sensors. 6. The method according to claim 4, characterized in that at least one light grid arrangement (9) is arranged diagonally in relation to a direction of movement of a plant object (8). 7. The method according to claim 1, characterized in that the automation component (7) ascertains the hazardous situation on the basis of the measurement pattern (M) and using parameter data and/or process data of the control of the machine component (1) or, as the case may be, the plant (2). 8. The method according to claim 7, characterized in that the process data is selected from a position, a speed and/or an acceleration of elements of the machine component (1) and/or a position, a speed and/or an acceleration of drive means for a plant object (8). 9. The method according to claim 7, characterized in that the parameter data is selected from an operating mode, geometric dimensions of machine parts and/or the presence of optional machine parts. 10. The method according to claim 1, characterized in that the automation component (7) defines a definition area (D), wherein a deviation of the measurement pattern (M) or a portion of this measurement pattern (M) measured by the safety sensor (3) and transmitted to the automatization component (7) from the definition area (D) indicates a hazardous situation. 11. The method according to claim 10, characterized in that the automatization component (7) factors in a current or past measurement pattern (M) of the safety sensor (3) for ascertaining the definition area (D). 12. The method according to claim 11, characterized in that a certain change in the current or past measurement pattern (M) triggers a defined temporal change of the definition area (D). 13. The method according to claim 1, characterized in that the measurement pattern (M) is transmitted synchronously from the at least one safety sensor (3) to the automation component (7) via the secure bus connection (6). 14. The method according to claim 1, characterized in that the data transmitted from the safety sensor (3) to the automation component (7) are each provided with a time stamp. 15. Automation component (7) for controlling at least one machine component (1) in a plant (2), characterized in that the automation component (7) has an interface via a secure bus connection (6) to at least one safety sensor (3), the safety sensor (3) monitoring a safety area (4) and the safety sensor (3) transmitting a measured measurement pattern (M) to the automation component (7) via the secure bus connection (6), the automation component (7) evaluating the measurement pattern (M) to ascertain the presence of a hazardous situation for protection objects (5), in particular persons and/or valuable, and, if a hazardous situation is present, activating the machine component (1) for executing a protective action. 16. The automation component (7) according to claim 15, characterized in that the hazardous situation is ascertained on the basis of the measurement pattern (M) and using parameter data and/or process data of the control of the machine component (1) or, as the case may be, the plant (2). 17. The automation component (7) according to claim 16, characterized in that the automatization component (7) connects the measurement pattern (M) obtained by the at least one safety sensor (3) on the basis of temporal information to the parameter data and/or the process data. 18. The automation component (7) according to claim 17, characterized in that the temporal information of the measurement pattern (M) is ascertained on the basis of a synchronous transmission via the secure bus connection (6) and/or on the basis of a time stamp. | The invention relates to a method for automated control of at least one machine component ( 1 ) in a plant ( 2 ). The machine component ( 1 ) is connected via a secure bus connection ( 6 ) to an automation component ( 7 ) by which it is controlled. The plant ( 2 ) has a safety area ( 4 ) monitored by means of at least one safety sensor ( 3 ), where a deviation of the measurement pattern (M) measured by the safety sensor ( 3 ) from a definition area (D) indicates a hazardous situation for protection objects ( 5 ), in particular persons and/or valuables. The machine component ( 1 ) triggers a protective action if a hazardous situation arises. The measurement patterns (M) measured by the safety sensor ( 3 ) are transmitted to the automation component ( 7 ) via the secure bus connection ( 6 ). The automation component ( 7 ) defines the definition area (D) using parameter data of the automated control, ascertains the presence of a hazardous situation, and activates the machine component ( 1 ) for performing the protective action.1. Method for automated control of a least one machine component (1) in a plant (2) with an automation component (7), the machine component (1) being linked to an automation component (7) via a secure bus connection (6), the plant (2) having a safety area (4) monitored by means of at least one safety sensor (3) and the ma-chine component (1) performing a protective action if a hazardous situation detected by the safety sensor (3) for protection objects (5), in particular persons and/or valuables, arises, characterized in that a measurement pattern (M) measured by the safety sensor (3) is transmitted over the secure bus connection (6) to the automation component (7), the automation component (7) ascertaining the presence of a hazardous situation on the basis of a measurement pattern (M) and activating the machine component (1) to perform a protective action. 2. The method according to claim 1, characterized in that the protective action comprises a deactivation of at least parts of the machine component (1), the assumption of a protective position, an active reaction, for example the stopping of at least parts of the machine component (1), a change in the speed of at least parts of the ma-chine component (1), an evasive movement, the triggering of a safety device such as an airbag or an extinguishing device, the triggering of an alarm or a combination thereof. 3. The method according to claim 1, characterized in that hazardous situation is defined as the detection of foreign objects or persons in the safety area (4), the detection of positional errors of machine component (1) parts and/or the detection of positional errors of plant objects (8). 4. The method according to claim 1, characterized in that the safety sensor (3) has at least one light grid arrangement (9). 5. The method according to claim 4, characterized in that at least two light grid arrangements (9, 9′) can be arranged parallel next to one another in relation to the grid plane and displaced from one another in relation to the longitudinal extension of their light sensors. 6. The method according to claim 4, characterized in that at least one light grid arrangement (9) is arranged diagonally in relation to a direction of movement of a plant object (8). 7. The method according to claim 1, characterized in that the automation component (7) ascertains the hazardous situation on the basis of the measurement pattern (M) and using parameter data and/or process data of the control of the machine component (1) or, as the case may be, the plant (2). 8. The method according to claim 7, characterized in that the process data is selected from a position, a speed and/or an acceleration of elements of the machine component (1) and/or a position, a speed and/or an acceleration of drive means for a plant object (8). 9. The method according to claim 7, characterized in that the parameter data is selected from an operating mode, geometric dimensions of machine parts and/or the presence of optional machine parts. 10. The method according to claim 1, characterized in that the automation component (7) defines a definition area (D), wherein a deviation of the measurement pattern (M) or a portion of this measurement pattern (M) measured by the safety sensor (3) and transmitted to the automatization component (7) from the definition area (D) indicates a hazardous situation. 11. The method according to claim 10, characterized in that the automatization component (7) factors in a current or past measurement pattern (M) of the safety sensor (3) for ascertaining the definition area (D). 12. The method according to claim 11, characterized in that a certain change in the current or past measurement pattern (M) triggers a defined temporal change of the definition area (D). 13. The method according to claim 1, characterized in that the measurement pattern (M) is transmitted synchronously from the at least one safety sensor (3) to the automation component (7) via the secure bus connection (6). 14. The method according to claim 1, characterized in that the data transmitted from the safety sensor (3) to the automation component (7) are each provided with a time stamp. 15. Automation component (7) for controlling at least one machine component (1) in a plant (2), characterized in that the automation component (7) has an interface via a secure bus connection (6) to at least one safety sensor (3), the safety sensor (3) monitoring a safety area (4) and the safety sensor (3) transmitting a measured measurement pattern (M) to the automation component (7) via the secure bus connection (6), the automation component (7) evaluating the measurement pattern (M) to ascertain the presence of a hazardous situation for protection objects (5), in particular persons and/or valuable, and, if a hazardous situation is present, activating the machine component (1) for executing a protective action. 16. The automation component (7) according to claim 15, characterized in that the hazardous situation is ascertained on the basis of the measurement pattern (M) and using parameter data and/or process data of the control of the machine component (1) or, as the case may be, the plant (2). 17. The automation component (7) according to claim 16, characterized in that the automatization component (7) connects the measurement pattern (M) obtained by the at least one safety sensor (3) on the basis of temporal information to the parameter data and/or the process data. 18. The automation component (7) according to claim 17, characterized in that the temporal information of the measurement pattern (M) is ascertained on the basis of a synchronous transmission via the secure bus connection (6) and/or on the basis of a time stamp. | 2,100 |
6,055 | 6,055 | 15,191,415 | 2,137 | In a computer system having multiple memory proximity domains including a first memory proximity domain with a first processor and a first memory and a second memory proximity domain with a second processor and a second memory, latencies of memory access from each memory proximity domain to its local memory as well as to memory at other memory proximity domains are probed. When there is no contention, the local latency will be lower than remote latency. If the contention at the local memory proximity domain increases and the local latency becomes large enough, memory pages associated with a process running on the first processor are placed in the second memory proximity domain, so that after the placement, the process is accessing the memory pages from the memory of the second memory proximity domain during execution. | 1. In a computer system having multiple memory proximity domains including a first memory proximity domain with a first processor and a first memory and a second memory proximity domain with a second processor and a second memory, a method of managing placement of memory pages associated with a process in one of the memory proximity domains, said method comprising:
measuring latencies of memory accesses to the first memory and the second memory by each of the first and second processors; placing memory pages associated with a first process running on the first processor in the second memory proximity domain based on the measured latencies, so that after said placing, the first process is accessing the memory pages from the second memory during execution. 2. The method of claim 1, wherein the measured latencies include a first latency, which is a latency of a memory access to the first memory by the first processor, and a second latency, which is a latency of a memory access to the second memory by the first processor. 3. The method of claim 2, further comprising:
determining that the first latency is greater than the second latency, wherein responsive to the determining, the memory pages associated with the first process are placed in the second memory proximity domain. 4. The method of claim 3, wherein placing the memory pages associated with the first process running on the first processor in the second memory proximity domain includes allocating new memory pages for the first process in the second memory. 5. The method of claim 4, wherein placing the memory pages associated with the first process running on the first processor in the second memory proximity domain further includes copying contents from old memory pages in the first memory to the new memory pages in the second memory and deallocating the old memory pages in the first memory. 6. The method of claim 5, wherein the amount of new memory pages allocated in the second memory is increased in proportion to the difference between the first latency and the second latency. 7. The method of claim 5, wherein the old memory pages represent a subset of all memory pages allocated for the first process in the first memory and are selected randomly. 8. The method of claim 1, wherein the latencies are measured periodically and the measured latencies are stored in the first or second memory, and the memory pages associated with the first process are placed in the second memory proximity domain based on the measured latencies stored in the first or second memory. 9. The method of claim 8, further comprising:
even after the memory pages associated with the first process are placed in the second memory proximity domain, determining that memory contention in the first memory proximity domain is higher than in the second memory proximity domain based on the stored measured latencies; and responsive to the determining, migrating memory pages associated with another process running on the first processor to the second memory proximity domain. 10. The method of claim 8, further comprising:
even after the memory pages associated with the first process are placed in the second memory proximity domain, determining that memory contention in the first memory proximity domain is higher than in the second memory proximity domain based on the stored measured latencies, responsive to the determining, migrating another process running on the first processor and memory pages associated therewith to the second memory proximity domain. 11. A non-transitory computer readable medium comprising instructions to be executed in a computer system having multiple memory proximity domains including a first memory proximity domain with a first processor and a first memory and a second memory proximity domain with a second processor and a second memory, wherein the instructions when executed in the computer system performs a method of managing placement of memory pages associated with a process in one of the memory proximity domains, said method comprising:
measuring latencies of memory accesses to the first memory and the second memory by each of the first and second processors; placing memory pages associated with a first process running on the first processor in the second memory proximity domain based on the measured latencies, so that after said placing, the first process is accessing the memory pages from the second memory during execution. 12. The non-transitory computer readable medium of claim 11, wherein the measured latencies include a first latency, which is a latency of a memory access to the first memory by the first processor, and a second latency, which is a latency of a memory access to the second memory by the first processor. 13. The non-transitory computer readable medium of claim 12, wherein the method further comprises:
determining that the first latency is greater than the second latency, wherein responsive to the determining, the memory pages associated with the first process are placed in the second memory proximity domain. 14. The non-transitory computer readable medium of claim 13, wherein placing the memory pages associated with the first process running on the first processor in the second memory proximity domain includes allocating new memory pages for the first process in the second memory. 15. The non-transitory computer readable medium of claim 14, wherein placing the memory pages associated with the first process running on the first processor in the second memory proximity domain further includes copying contents from old memory pages in the first memory to the new memory pages in the second memory and deallocating the old memory pages in the first memory. 16. The non-transitory computer readable medium of claim 15, wherein the amount of new memory pages allocated in the second memory is increased in proportion to the difference between the first latency and the second latency. 17. The non-transitory computer readable medium of claim 15, wherein the old memory pages represent a subset of all memory pages allocated for the first process in the first memory and are selected randomly. 18. The non-transitory computer readable medium of claim 11, wherein the latencies are measured periodically and the measured latencies are stored in the first or second memory, and the memory pages associated with the first process are placed in the second memory proximity domain based on the measured latencies stored in the first or second memory. 19. A computer system having multiple memory proximity domains including a first memory proximity domain with a first processor and a first memory and a second memory proximity domain with a second processor and a second memory, wherein system software for the computer system is programmed to execute a method of managing placement of memory pages associated with a process in one of the memory proximity domains, said method comprising:
measuring latencies of memory accesses to the first memory and the second memory by each of the first and second processors; placing memory pages associated with a first process running on the first processor in the second memory proximity domain based on the measured latencies, so that after said placing, the first process is accessing the memory pages from the second memory during execution. 20. The computer system of claim 19, wherein the method further comprises:
even after the memory pages associated with the first process are placed in the second memory proximity domain, determining that memory contention in the first memory proximity domain is higher than in the second memory proximity domain based on the stored measured latencies, wherein responsive to the determining, either migrating memory pages associated with another process running on the first processor to the second memory proximity domain, or migrating another process running on the first processor and memory pages associated therewith to the second memory proximity domain. | In a computer system having multiple memory proximity domains including a first memory proximity domain with a first processor and a first memory and a second memory proximity domain with a second processor and a second memory, latencies of memory access from each memory proximity domain to its local memory as well as to memory at other memory proximity domains are probed. When there is no contention, the local latency will be lower than remote latency. If the contention at the local memory proximity domain increases and the local latency becomes large enough, memory pages associated with a process running on the first processor are placed in the second memory proximity domain, so that after the placement, the process is accessing the memory pages from the memory of the second memory proximity domain during execution.1. In a computer system having multiple memory proximity domains including a first memory proximity domain with a first processor and a first memory and a second memory proximity domain with a second processor and a second memory, a method of managing placement of memory pages associated with a process in one of the memory proximity domains, said method comprising:
measuring latencies of memory accesses to the first memory and the second memory by each of the first and second processors; placing memory pages associated with a first process running on the first processor in the second memory proximity domain based on the measured latencies, so that after said placing, the first process is accessing the memory pages from the second memory during execution. 2. The method of claim 1, wherein the measured latencies include a first latency, which is a latency of a memory access to the first memory by the first processor, and a second latency, which is a latency of a memory access to the second memory by the first processor. 3. The method of claim 2, further comprising:
determining that the first latency is greater than the second latency, wherein responsive to the determining, the memory pages associated with the first process are placed in the second memory proximity domain. 4. The method of claim 3, wherein placing the memory pages associated with the first process running on the first processor in the second memory proximity domain includes allocating new memory pages for the first process in the second memory. 5. The method of claim 4, wherein placing the memory pages associated with the first process running on the first processor in the second memory proximity domain further includes copying contents from old memory pages in the first memory to the new memory pages in the second memory and deallocating the old memory pages in the first memory. 6. The method of claim 5, wherein the amount of new memory pages allocated in the second memory is increased in proportion to the difference between the first latency and the second latency. 7. The method of claim 5, wherein the old memory pages represent a subset of all memory pages allocated for the first process in the first memory and are selected randomly. 8. The method of claim 1, wherein the latencies are measured periodically and the measured latencies are stored in the first or second memory, and the memory pages associated with the first process are placed in the second memory proximity domain based on the measured latencies stored in the first or second memory. 9. The method of claim 8, further comprising:
even after the memory pages associated with the first process are placed in the second memory proximity domain, determining that memory contention in the first memory proximity domain is higher than in the second memory proximity domain based on the stored measured latencies; and responsive to the determining, migrating memory pages associated with another process running on the first processor to the second memory proximity domain. 10. The method of claim 8, further comprising:
even after the memory pages associated with the first process are placed in the second memory proximity domain, determining that memory contention in the first memory proximity domain is higher than in the second memory proximity domain based on the stored measured latencies, responsive to the determining, migrating another process running on the first processor and memory pages associated therewith to the second memory proximity domain. 11. A non-transitory computer readable medium comprising instructions to be executed in a computer system having multiple memory proximity domains including a first memory proximity domain with a first processor and a first memory and a second memory proximity domain with a second processor and a second memory, wherein the instructions when executed in the computer system performs a method of managing placement of memory pages associated with a process in one of the memory proximity domains, said method comprising:
measuring latencies of memory accesses to the first memory and the second memory by each of the first and second processors; placing memory pages associated with a first process running on the first processor in the second memory proximity domain based on the measured latencies, so that after said placing, the first process is accessing the memory pages from the second memory during execution. 12. The non-transitory computer readable medium of claim 11, wherein the measured latencies include a first latency, which is a latency of a memory access to the first memory by the first processor, and a second latency, which is a latency of a memory access to the second memory by the first processor. 13. The non-transitory computer readable medium of claim 12, wherein the method further comprises:
determining that the first latency is greater than the second latency, wherein responsive to the determining, the memory pages associated with the first process are placed in the second memory proximity domain. 14. The non-transitory computer readable medium of claim 13, wherein placing the memory pages associated with the first process running on the first processor in the second memory proximity domain includes allocating new memory pages for the first process in the second memory. 15. The non-transitory computer readable medium of claim 14, wherein placing the memory pages associated with the first process running on the first processor in the second memory proximity domain further includes copying contents from old memory pages in the first memory to the new memory pages in the second memory and deallocating the old memory pages in the first memory. 16. The non-transitory computer readable medium of claim 15, wherein the amount of new memory pages allocated in the second memory is increased in proportion to the difference between the first latency and the second latency. 17. The non-transitory computer readable medium of claim 15, wherein the old memory pages represent a subset of all memory pages allocated for the first process in the first memory and are selected randomly. 18. The non-transitory computer readable medium of claim 11, wherein the latencies are measured periodically and the measured latencies are stored in the first or second memory, and the memory pages associated with the first process are placed in the second memory proximity domain based on the measured latencies stored in the first or second memory. 19. A computer system having multiple memory proximity domains including a first memory proximity domain with a first processor and a first memory and a second memory proximity domain with a second processor and a second memory, wherein system software for the computer system is programmed to execute a method of managing placement of memory pages associated with a process in one of the memory proximity domains, said method comprising:
measuring latencies of memory accesses to the first memory and the second memory by each of the first and second processors; placing memory pages associated with a first process running on the first processor in the second memory proximity domain based on the measured latencies, so that after said placing, the first process is accessing the memory pages from the second memory during execution. 20. The computer system of claim 19, wherein the method further comprises:
even after the memory pages associated with the first process are placed in the second memory proximity domain, determining that memory contention in the first memory proximity domain is higher than in the second memory proximity domain based on the stored measured latencies, wherein responsive to the determining, either migrating memory pages associated with another process running on the first processor to the second memory proximity domain, or migrating another process running on the first processor and memory pages associated therewith to the second memory proximity domain. | 2,100 |
6,056 | 6,056 | 13,075,906 | 2,143 | A graphical user interface (GUI) tool is presented to a user for interacting with an underlying database. The GUI tool includes a field selection and attribute selections for the field. The user selects a field and an attribute for that field and is presented with a first list of values retrieved from the database for the selected attribute. Next, the user selects a filter for the attribute within the GUI tool and a second reduced list of values is presented to the user within the GUI tool representing the filtered first list of values acquired by applying the filter. | 1. A method implemented and programmed within a non-transitory computer-readable storage medium and processed by a processor, the processor configured to execute the method, comprising:
presenting a graphical user interface (GUI) tool to a user, the GUI tool acting as an interface for the user to access a database; receiving, from the user, a field selection for a field of the database within the GUI tool; obtaining, from the user, an attribute selection for an attribute assigned to the field within the GUI tool; displaying within the GUI tool a first list of attribute values retrieved from the database and assigned to the attribute for the field; acquiring, from the user, an attribute filter; and filtering the first list to present a reduced second list of attribute values within the GUI tool by applying the filter against the first list. 2. The method of claim 1, wherein presenting further includes providing the GUI tool as a marketing segmentation tool that is used for assisting in developing custom segments for marketing campaigns of an enterprise. 3. The method of claim 1, wherein receiving further includes detecting a drop down menu activation from the user within the GUI tool that presents a field list for available fields to the user, the user selects the field from the field list. 4. The method of claim 1, wherein obtaining further includes presenting an attribute list for available attributes within the GUI tool based on the user selection of the field. 5. The method of claim 4, wherein obtaining further includes inspecting metadata associated with the selected field to determine the attribute list. 6. The method of claim 1, wherein displaying further includes querying the database with the field and the attribute to acquire the attribute values for populating the first list. 7. The method of claim 1, wherein acquiring further includes presenting a filter list to the user within the GUI tool based on selection of the attribute. 8. The method of claim 7, wherein acquiring further includes inspecting metadata associated with the selected attribute to determine the filter list. 9. The method of claim 1, wherein filtering further includes presenting a total count for the second list that identifies a total number of attribute values within the second list, the total count presented within the GUI tool to the user. 10. A method implemented and programmed within a non-transitory computer-readable storage medium and processed by a processor, the processor configured to execute the method, comprising:
providing a graphical user interface (GUI) tool to a user; presenting a field selection mechanism within the GUI tool to the user; displaying an attribute selection mechanism within the GUI tool based on a field selection of the user for a particular field, via the field selection mechanism; presenting an attribute filter mechanism within the GUI tool based on an attribute selection of the user for a particular attribute; filtering attribute values associated with the particular attribute based on a filter selection of the user for a particular filter; and presenting the filtered attribute values within the GUI tool to the user for further review and selection within the GUI tool by the user. 11. The method of claim 10, wherein providing further includes providing the GUI tool as a front-end interface to an enterprise data warehouse. 12. The method of claim 10, wherein presenting the field selection mechanism further includes providing the field selection mechanism as a drop down menu listing within the GUI tool for available fields of a particular database table. 13. The method of claim 10, wherein displaying further includes providing a selectable list of available attributes for the particular field within the GUI tool. 14. The method of claim 10, wherein displaying further includes displaying an original list of attribute values assigned in a database to the particular attribute within the GUI tool based on the attribute selection for the particular attribute. 15. The method of claim 14, wherein presenting the attribute filter mechanism further includes presenting the attribute filter mechanism based on comparison of a size for the original list of attribute values against a threshold number where the size exceeds the threshold number. 16. The method of claim 15, wherein presenting the attribute filter mechanism further includes selecting the threshold number based on the attribute selection for the particular attribute. 17. The method of claim 15, wherein presenting the attribute filter mechanism further includes selecting the threshold number based on a profile associated with the user that defines the threshold number. 18. A processor-implemented system, comprising:
a graphical user interface (GUI) tool programmed within a non-transitory computer-readable medium and to execute on a processor; and an attribute manager programmed within a non-transitory computer-readable medium and to execute on the processor; the GUI tool is configured to be presented to a user and provide access to a database, the GUI tool presents a field selection mechanism and an attribute selection mechanism to the user, the attribute manager configured to monitor selections of the user and provide within the GUI tool an attribute filtering mechanism to the user based on a particular attribute selection, the attribute manager is also configured to filter original attribute values assigned in the database to the particular attribute selection to produce a reduced and filtered list of attribute values based on a filter selection from the attribute filtering mechanism. 19. The system of claim 18, wherein the attribute manager is also configured to resolve and to present within the GUI tool a list of available attributes for the user to make the particular attribute selection based on a field selection for a particular field made by the user via the field selection mechanism of the GUI tool. 20. The system of claim 18, wherein the GUI tool is a marketing segmentation tool. | A graphical user interface (GUI) tool is presented to a user for interacting with an underlying database. The GUI tool includes a field selection and attribute selections for the field. The user selects a field and an attribute for that field and is presented with a first list of values retrieved from the database for the selected attribute. Next, the user selects a filter for the attribute within the GUI tool and a second reduced list of values is presented to the user within the GUI tool representing the filtered first list of values acquired by applying the filter.1. A method implemented and programmed within a non-transitory computer-readable storage medium and processed by a processor, the processor configured to execute the method, comprising:
presenting a graphical user interface (GUI) tool to a user, the GUI tool acting as an interface for the user to access a database; receiving, from the user, a field selection for a field of the database within the GUI tool; obtaining, from the user, an attribute selection for an attribute assigned to the field within the GUI tool; displaying within the GUI tool a first list of attribute values retrieved from the database and assigned to the attribute for the field; acquiring, from the user, an attribute filter; and filtering the first list to present a reduced second list of attribute values within the GUI tool by applying the filter against the first list. 2. The method of claim 1, wherein presenting further includes providing the GUI tool as a marketing segmentation tool that is used for assisting in developing custom segments for marketing campaigns of an enterprise. 3. The method of claim 1, wherein receiving further includes detecting a drop down menu activation from the user within the GUI tool that presents a field list for available fields to the user, the user selects the field from the field list. 4. The method of claim 1, wherein obtaining further includes presenting an attribute list for available attributes within the GUI tool based on the user selection of the field. 5. The method of claim 4, wherein obtaining further includes inspecting metadata associated with the selected field to determine the attribute list. 6. The method of claim 1, wherein displaying further includes querying the database with the field and the attribute to acquire the attribute values for populating the first list. 7. The method of claim 1, wherein acquiring further includes presenting a filter list to the user within the GUI tool based on selection of the attribute. 8. The method of claim 7, wherein acquiring further includes inspecting metadata associated with the selected attribute to determine the filter list. 9. The method of claim 1, wherein filtering further includes presenting a total count for the second list that identifies a total number of attribute values within the second list, the total count presented within the GUI tool to the user. 10. A method implemented and programmed within a non-transitory computer-readable storage medium and processed by a processor, the processor configured to execute the method, comprising:
providing a graphical user interface (GUI) tool to a user; presenting a field selection mechanism within the GUI tool to the user; displaying an attribute selection mechanism within the GUI tool based on a field selection of the user for a particular field, via the field selection mechanism; presenting an attribute filter mechanism within the GUI tool based on an attribute selection of the user for a particular attribute; filtering attribute values associated with the particular attribute based on a filter selection of the user for a particular filter; and presenting the filtered attribute values within the GUI tool to the user for further review and selection within the GUI tool by the user. 11. The method of claim 10, wherein providing further includes providing the GUI tool as a front-end interface to an enterprise data warehouse. 12. The method of claim 10, wherein presenting the field selection mechanism further includes providing the field selection mechanism as a drop down menu listing within the GUI tool for available fields of a particular database table. 13. The method of claim 10, wherein displaying further includes providing a selectable list of available attributes for the particular field within the GUI tool. 14. The method of claim 10, wherein displaying further includes displaying an original list of attribute values assigned in a database to the particular attribute within the GUI tool based on the attribute selection for the particular attribute. 15. The method of claim 14, wherein presenting the attribute filter mechanism further includes presenting the attribute filter mechanism based on comparison of a size for the original list of attribute values against a threshold number where the size exceeds the threshold number. 16. The method of claim 15, wherein presenting the attribute filter mechanism further includes selecting the threshold number based on the attribute selection for the particular attribute. 17. The method of claim 15, wherein presenting the attribute filter mechanism further includes selecting the threshold number based on a profile associated with the user that defines the threshold number. 18. A processor-implemented system, comprising:
a graphical user interface (GUI) tool programmed within a non-transitory computer-readable medium and to execute on a processor; and an attribute manager programmed within a non-transitory computer-readable medium and to execute on the processor; the GUI tool is configured to be presented to a user and provide access to a database, the GUI tool presents a field selection mechanism and an attribute selection mechanism to the user, the attribute manager configured to monitor selections of the user and provide within the GUI tool an attribute filtering mechanism to the user based on a particular attribute selection, the attribute manager is also configured to filter original attribute values assigned in the database to the particular attribute selection to produce a reduced and filtered list of attribute values based on a filter selection from the attribute filtering mechanism. 19. The system of claim 18, wherein the attribute manager is also configured to resolve and to present within the GUI tool a list of available attributes for the user to make the particular attribute selection based on a field selection for a particular field made by the user via the field selection mechanism of the GUI tool. 20. The system of claim 18, wherein the GUI tool is a marketing segmentation tool. | 2,100 |
6,057 | 6,057 | 15,599,621 | 2,178 | A media composition formation program method and device. In one aspect, the invention can be a method of creating a final media composition comprising: a) receiving a plurality of low resolution media streams from a plurality of remote electronic devices; b) displaying visual indicia the low resolution media streams; c) activating one or more of the low resolution media streams in response to user input; d) for each low resolution media stream that is activated in step c), recording a low resolution media clip segment of that low resolution media stream in an interim media composition; e) for each low resolution media clip segment recorded in the interim media composition, receiving a high resolution media clip segment that corresponds to that low resolution media clip segment; and f) automatically replacing the low resolution media clip segments in the interim media composition with the high resolution media clip segments. | 1. A method of creating a video composition comprising:
a) displaying, in a first display device of a first electronic device, a plurality of remote camera views perceived by a plurality of remote camera lenses of a plurality of remote electronic devices; b) activating one or more of the plurality of the remote camera views displayed in the first display device via user input means of the first electronic device; c) for each remote camera view that is activated in step b), recording, on a first memory device of the first electronic device, a low resolution video clip segment of the remote camera view as part of an interim video composition; d) for each low resolution video clip segment recorded in step c), acquiring from the remote electronic devices a high resolution video clip segment that corresponds to that low resolution video clip segment; and e) automatically replacing the low resolution video clip segment in the video composition recorded on the first memory device of the first electronic device with the high resolution video clip segments. 2. The method according to claim 1 wherein step a) further comprises:
a-1) displaying, in the first display device, a list of remote electronic devices that have initiated a sharing status via user input means of the remote electronic devices;
a-2) selecting a plurality of remote electronic devices from the list via user input means of the first electronic device;
a-3) displaying remote camera views of the remote electronic devices selected in step a-2) in the first display device. 3. The method according to claim 2 wherein step a-1) is performed upon initiating a stage status for the first electronic device via user input means of the first electronic device. 4. The method according to claim 3 wherein remote electronic devices selected for the list meet one or more qualification criteria defined by the first electronic device via user input means of the first electronic device, wherein the one or more qualification criteria are selected from a group consisting of local area network connectivity, GPS radius from the first electronic device, location of the remote electronic device and pre-defined group status 5. The method according to claim 1 wherein step a) further comprises: displaying, in the first display device of the first electronic device, a first camera view perceived by a first camera lens of the first electronic device, wherein the first camera view and the plurality of remote camera views are simultaneously displayed in the first display device. 6. The method according to claim 5 wherein step a) further comprises: displaying the plurality of remote camera views in a first window that overlays a primary window in which the first camera view is displayed, and wherein upon a swap function being activated, the first camera view is displayed in the overlay window and a selected one of the remote camera views is displayed in the primary window. 7. A method of creating a final media composition using a media composition program residing on a first electronic device comprising a first display device, a first memory device, and first user input means, the method comprising:
a) receiving, on the first electronic device, a plurality of low resolution media streams of high resolution media clip files from one or more databases, the high resolution media clip files stored on the one or more databases; b) displaying, in the first display device, visual indicia of each of the low resolution media streams being received by the first electronic device; c) activating one or more of the low resolution media streams being received by the first electronic device in response to user input via the first user input means; d) for each low resolution media stream that is activated in step c), recording a low resolution media clip segment of that low resolution media stream in an interim media composition that resides on the first memory device; e) for each low resolution media clip segment recorded in the interim media composition, receiving on the first electronic device a high resolution media clip segment from the one or more databases that corresponds to that low resolution media clip segment; and f) automatically replacing the low resolution media clip segments in the interim media composition with the high resolution media clip segments to create the final media composition comprising the high resolution media clip segments. 8. The method according to claim 7 wherein at least one of the one or more databases resides on a server that is accessible by the first electronic device over a common carrier network. 9. The method according to claim 7 wherein step b) further comprises: displaying, in the first display device, visual indicia of only those low resolution media streams that satisfy qualification criteria. 10. The method according to claim 7 wherein step a) further comprises:
a-1) searching the one or more databases for high resolution video clip files that satisfy qualification criteria;
a-2) selecting a plurality of high resolution video clips from the one or more databases that satisfy the qualification criteria; and
a-3) transmitting, to the first portable electronic device, only those low resolution media streams that correspond to the high resolution video clips determined to satisfy the qualification criteria in step a-2). 11. The method according to claim 10 wherein the qualification criteria comprises user-specified criteria and/or auto-extracted criteria. 12. The method according to claim 11 wherein the user-specified criteria comprises local area network connectivity and GPS radius from the first electronic device and location. 13. The method according to claim 11 wherein the auto-extracted criteria comprises current weather conditions at a GPS location of the first portable electronic device, current time of day, current day and month, and GPS radius from the first electronic device and location. 14. A method of creating a video composition comprising:
a) displaying, in a first display device of a first portable electronic device, a first camera view perceived by a first camera lens of the first portable electronic device; b) transmitting, to the first portable electronic device, a plurality of low resolution video streams of high resolution video clips previously stored in one or more databases; c) displaying, in the first display device of the first electronic device, the low resolution video streams, wherein the first camera view and the low resolution video streams are simultaneously displayed in the first display device; d) recording, on the first memory device of the first portable electronic device, a low resolution video clip for each of the low resolution video streams activated by a user as part of a video composition; e) for each low resolution video clip recorded on the first memory device of the first portable electronic device, transmitting corresponding ones of the high resolution clips from the one or more databases to the first portable electronic device; and f) automatically replacing the low resolution video clips in the video composition recorded on the first memory device of the first portable electronic device with the high resolution video clips. 15. The method according to claim 14 wherein step a) further comprises:
a-1) displaying, in the first display device, a list of high resolution video clips previously stored in the library database that satisfy qualification criteria;
a-2) selecting a plurality of high resolution video clips from the list via user input means of the first electronic device; and
a-3) transmitting, to the first portable electronic device, a plurality of low resolution video streams of the high resolution video clips selected in step a-2). 16. The method according to claim 15 wherein the qualification criteria comprises user-specified criteria and auto-extracted criteria. 17. The method according to claim 16 wherein the auto-extracted criteria comprises current weather conditions at a GPS location of the first portable electronic device, current time of day and current day and month. | A media composition formation program method and device. In one aspect, the invention can be a method of creating a final media composition comprising: a) receiving a plurality of low resolution media streams from a plurality of remote electronic devices; b) displaying visual indicia the low resolution media streams; c) activating one or more of the low resolution media streams in response to user input; d) for each low resolution media stream that is activated in step c), recording a low resolution media clip segment of that low resolution media stream in an interim media composition; e) for each low resolution media clip segment recorded in the interim media composition, receiving a high resolution media clip segment that corresponds to that low resolution media clip segment; and f) automatically replacing the low resolution media clip segments in the interim media composition with the high resolution media clip segments.1. A method of creating a video composition comprising:
a) displaying, in a first display device of a first electronic device, a plurality of remote camera views perceived by a plurality of remote camera lenses of a plurality of remote electronic devices; b) activating one or more of the plurality of the remote camera views displayed in the first display device via user input means of the first electronic device; c) for each remote camera view that is activated in step b), recording, on a first memory device of the first electronic device, a low resolution video clip segment of the remote camera view as part of an interim video composition; d) for each low resolution video clip segment recorded in step c), acquiring from the remote electronic devices a high resolution video clip segment that corresponds to that low resolution video clip segment; and e) automatically replacing the low resolution video clip segment in the video composition recorded on the first memory device of the first electronic device with the high resolution video clip segments. 2. The method according to claim 1 wherein step a) further comprises:
a-1) displaying, in the first display device, a list of remote electronic devices that have initiated a sharing status via user input means of the remote electronic devices;
a-2) selecting a plurality of remote electronic devices from the list via user input means of the first electronic device;
a-3) displaying remote camera views of the remote electronic devices selected in step a-2) in the first display device. 3. The method according to claim 2 wherein step a-1) is performed upon initiating a stage status for the first electronic device via user input means of the first electronic device. 4. The method according to claim 3 wherein remote electronic devices selected for the list meet one or more qualification criteria defined by the first electronic device via user input means of the first electronic device, wherein the one or more qualification criteria are selected from a group consisting of local area network connectivity, GPS radius from the first electronic device, location of the remote electronic device and pre-defined group status 5. The method according to claim 1 wherein step a) further comprises: displaying, in the first display device of the first electronic device, a first camera view perceived by a first camera lens of the first electronic device, wherein the first camera view and the plurality of remote camera views are simultaneously displayed in the first display device. 6. The method according to claim 5 wherein step a) further comprises: displaying the plurality of remote camera views in a first window that overlays a primary window in which the first camera view is displayed, and wherein upon a swap function being activated, the first camera view is displayed in the overlay window and a selected one of the remote camera views is displayed in the primary window. 7. A method of creating a final media composition using a media composition program residing on a first electronic device comprising a first display device, a first memory device, and first user input means, the method comprising:
a) receiving, on the first electronic device, a plurality of low resolution media streams of high resolution media clip files from one or more databases, the high resolution media clip files stored on the one or more databases; b) displaying, in the first display device, visual indicia of each of the low resolution media streams being received by the first electronic device; c) activating one or more of the low resolution media streams being received by the first electronic device in response to user input via the first user input means; d) for each low resolution media stream that is activated in step c), recording a low resolution media clip segment of that low resolution media stream in an interim media composition that resides on the first memory device; e) for each low resolution media clip segment recorded in the interim media composition, receiving on the first electronic device a high resolution media clip segment from the one or more databases that corresponds to that low resolution media clip segment; and f) automatically replacing the low resolution media clip segments in the interim media composition with the high resolution media clip segments to create the final media composition comprising the high resolution media clip segments. 8. The method according to claim 7 wherein at least one of the one or more databases resides on a server that is accessible by the first electronic device over a common carrier network. 9. The method according to claim 7 wherein step b) further comprises: displaying, in the first display device, visual indicia of only those low resolution media streams that satisfy qualification criteria. 10. The method according to claim 7 wherein step a) further comprises:
a-1) searching the one or more databases for high resolution video clip files that satisfy qualification criteria;
a-2) selecting a plurality of high resolution video clips from the one or more databases that satisfy the qualification criteria; and
a-3) transmitting, to the first portable electronic device, only those low resolution media streams that correspond to the high resolution video clips determined to satisfy the qualification criteria in step a-2). 11. The method according to claim 10 wherein the qualification criteria comprises user-specified criteria and/or auto-extracted criteria. 12. The method according to claim 11 wherein the user-specified criteria comprises local area network connectivity and GPS radius from the first electronic device and location. 13. The method according to claim 11 wherein the auto-extracted criteria comprises current weather conditions at a GPS location of the first portable electronic device, current time of day, current day and month, and GPS radius from the first electronic device and location. 14. A method of creating a video composition comprising:
a) displaying, in a first display device of a first portable electronic device, a first camera view perceived by a first camera lens of the first portable electronic device; b) transmitting, to the first portable electronic device, a plurality of low resolution video streams of high resolution video clips previously stored in one or more databases; c) displaying, in the first display device of the first electronic device, the low resolution video streams, wherein the first camera view and the low resolution video streams are simultaneously displayed in the first display device; d) recording, on the first memory device of the first portable electronic device, a low resolution video clip for each of the low resolution video streams activated by a user as part of a video composition; e) for each low resolution video clip recorded on the first memory device of the first portable electronic device, transmitting corresponding ones of the high resolution clips from the one or more databases to the first portable electronic device; and f) automatically replacing the low resolution video clips in the video composition recorded on the first memory device of the first portable electronic device with the high resolution video clips. 15. The method according to claim 14 wherein step a) further comprises:
a-1) displaying, in the first display device, a list of high resolution video clips previously stored in the library database that satisfy qualification criteria;
a-2) selecting a plurality of high resolution video clips from the list via user input means of the first electronic device; and
a-3) transmitting, to the first portable electronic device, a plurality of low resolution video streams of the high resolution video clips selected in step a-2). 16. The method according to claim 15 wherein the qualification criteria comprises user-specified criteria and auto-extracted criteria. 17. The method according to claim 16 wherein the auto-extracted criteria comprises current weather conditions at a GPS location of the first portable electronic device, current time of day and current day and month. | 2,100 |
6,058 | 6,058 | 15,442,514 | 2,169 | Representative embodiments disclose mechanisms to complete partial queries entered by a user. Users enter a partial query. The partial query is used to search a short text index comprising the titles of documents. The search yields a list results. The top k entries of the list are selected and a language model is created from the top k entries. The language model comprises n-grams from the top k entries and an associated probability for each n-gram. A query completion generator creates query completion suggestions by matching n-grams with the partial query, removing candidate suggestions that to not comply with suggestion rules, and filtering the remaining suggestions according to a filtering criteria. The top N results are returned as suggestions to complete the query. | 1. A method for completing a query comprising:
receiving, from a user, a query prefix representing a portion of a query; searching a short text index comprising a plurality of text entries, each entry corresponding to an associated document; identifying a subset of the plurality of short text entries retrieved from the short text index; creating a language model from the subset, the language model comprising a plurality of n-grams each with an n-gram probability; creating a plurality of query completion suggestions based on the language model and the query prefix; and causing presentation of the plurality of query completion suggestions to the user via a user interface. 2. The method of claim 1 wherein the plurality of short text entries each have a probability metric. 3. The method of claim 1 wherein each entry in the short text index comprises the title of a document. 4. The method of claim 2 wherein identifying the subset comprises:
ranking results returned from the short text index by the probability metric; and
selecting as the subset the top k entries in the ranked list. 5. The method of claim 1 wherein creating the plurality of query completion suggestions comprises:
generating a set of candidate completion suggestions based on the query prefix and the language model;
removing from the set of candidate completion suggestions candidate completion suggestions that do not comply with at least one of a plurality of rules to create a subset of candidate completion suggestions; and
filtering the subset of candidate completion suggestions based on a filter criteria; and
ranking the filtered subset. 6. The method of claim 5 wherein the filter criteria selects one candidate completion suggestion associated with an underlying document and removes any other candidate completion suggestions associated with the underlying document. 7. The method of claim 5 wherein the filter criteria selects a highest ranked candidate completion suggestion associated with an underlying document and removes any other candidate completion suggestions associated with the underlying document. 8. The method of claim 1 wherein the short text index is created from a subset of documents identified by a second index. 9. The method of claim 2 wherein the probability metric associated with an entry is derived from at least one of:
a number of times a document associated with the entry has been viewed;
a type of match between the query prefix and the entry; and
a number of times a document comes up in search results. 10. A system for completing a query comprising:
a processor and executable instructions accessible on a computer-storage medium that, when executed, cause the processor to perform operations comprising:
receive, from a user, a query prefix representing a portion of a query;
search a short text index comprising a plurality of text entries, each entry corresponding to an associated document;
identify a subset of the plurality of short text entries retrieved from the short text index;
create a language model from the subset, the language model comprising a plurality of n-grams each with an n-gram probability;
create a plurality of query completion suggestions based on the language model and the query prefix; and
return plurality of query completion suggestions to the user via a user interface. 11. The system of claim 10 wherein the plurality of short text entries each have a probability metric. 12. The system of claim 11 wherein identify the subset comprises:
rank results returned from the short text index by the probability metric; and
select as the subset the top k entries in the ranked list. 13. The system of claim 10 wherein each entry in the short text index comprises the title of a document. 14. The system of claim 10 wherein creating the plurality of query completion suggestions comprises:
generate a set of candidate completion suggestions based on the query prefix and the language model;
remove from the set of candidate completion suggestions candidate completion suggestions that do not comply with at least one of a plurality of rules to create a subset of candidate completion suggestions; and
filter the subset of candidate completion suggestions based on a filter criteria; and
rank the filtered subset. 15. The system of claim 14 wherein the filter criteria selects one candidate completion suggestion associated with an underlying document and removes any other candidate completion suggestions associated with the underlying document. 16. The system of claim 14 wherein the filter criteria selects a highest ranked candidate completion suggestion associated with an underlying document and removes any other candidate completion suggestions associated with the underlying document 17. A computer storage medium comprising executable instructions that, when executed by a processor of a machine, cause the machine to perform operations comprising:
receive, from a user, a query prefix representing a portion of a query; search a short text index comprising a plurality of text entries, each entry comprising the title of an associated document; identify a subset of the plurality of short text entries retrieved from the short text index; create a language model from the subset, the language model comprising a plurality of n-grams each with an n-gram probability; create a plurality of query completion suggestions based on the language model and the query prefix; and return plurality of query completion suggestions to the user via a user interface. 18. The medium of claim 17 wherein the plurality of short text entries each have a probability metric derived from at least one of:
a number of times a document associated with the entry has been viewed;
a type of match between the query prefix and the entry; and
a number of times a document comes up in search results. 19. The medium of claim 17 wherein creating the plurality of query completion suggestions comprises:
generate a set of candidate completion suggestions based on the query prefix and the language model;
remove from the set of candidate completion suggestions candidate completion suggestions that do not comply with at least one of a plurality of rules to create a subset of candidate completion suggestions; and
filter the subset of candidate completion suggestions based on a filter criteria; and
rank the filtered subset. 20. The medium of claim 19 wherein the filter criteria selects one candidate completion suggestion associated with an underlying document and removes any other candidate completion suggestions associated with the underlying document. | Representative embodiments disclose mechanisms to complete partial queries entered by a user. Users enter a partial query. The partial query is used to search a short text index comprising the titles of documents. The search yields a list results. The top k entries of the list are selected and a language model is created from the top k entries. The language model comprises n-grams from the top k entries and an associated probability for each n-gram. A query completion generator creates query completion suggestions by matching n-grams with the partial query, removing candidate suggestions that to not comply with suggestion rules, and filtering the remaining suggestions according to a filtering criteria. The top N results are returned as suggestions to complete the query.1. A method for completing a query comprising:
receiving, from a user, a query prefix representing a portion of a query; searching a short text index comprising a plurality of text entries, each entry corresponding to an associated document; identifying a subset of the plurality of short text entries retrieved from the short text index; creating a language model from the subset, the language model comprising a plurality of n-grams each with an n-gram probability; creating a plurality of query completion suggestions based on the language model and the query prefix; and causing presentation of the plurality of query completion suggestions to the user via a user interface. 2. The method of claim 1 wherein the plurality of short text entries each have a probability metric. 3. The method of claim 1 wherein each entry in the short text index comprises the title of a document. 4. The method of claim 2 wherein identifying the subset comprises:
ranking results returned from the short text index by the probability metric; and
selecting as the subset the top k entries in the ranked list. 5. The method of claim 1 wherein creating the plurality of query completion suggestions comprises:
generating a set of candidate completion suggestions based on the query prefix and the language model;
removing from the set of candidate completion suggestions candidate completion suggestions that do not comply with at least one of a plurality of rules to create a subset of candidate completion suggestions; and
filtering the subset of candidate completion suggestions based on a filter criteria; and
ranking the filtered subset. 6. The method of claim 5 wherein the filter criteria selects one candidate completion suggestion associated with an underlying document and removes any other candidate completion suggestions associated with the underlying document. 7. The method of claim 5 wherein the filter criteria selects a highest ranked candidate completion suggestion associated with an underlying document and removes any other candidate completion suggestions associated with the underlying document. 8. The method of claim 1 wherein the short text index is created from a subset of documents identified by a second index. 9. The method of claim 2 wherein the probability metric associated with an entry is derived from at least one of:
a number of times a document associated with the entry has been viewed;
a type of match between the query prefix and the entry; and
a number of times a document comes up in search results. 10. A system for completing a query comprising:
a processor and executable instructions accessible on a computer-storage medium that, when executed, cause the processor to perform operations comprising:
receive, from a user, a query prefix representing a portion of a query;
search a short text index comprising a plurality of text entries, each entry corresponding to an associated document;
identify a subset of the plurality of short text entries retrieved from the short text index;
create a language model from the subset, the language model comprising a plurality of n-grams each with an n-gram probability;
create a plurality of query completion suggestions based on the language model and the query prefix; and
return plurality of query completion suggestions to the user via a user interface. 11. The system of claim 10 wherein the plurality of short text entries each have a probability metric. 12. The system of claim 11 wherein identify the subset comprises:
rank results returned from the short text index by the probability metric; and
select as the subset the top k entries in the ranked list. 13. The system of claim 10 wherein each entry in the short text index comprises the title of a document. 14. The system of claim 10 wherein creating the plurality of query completion suggestions comprises:
generate a set of candidate completion suggestions based on the query prefix and the language model;
remove from the set of candidate completion suggestions candidate completion suggestions that do not comply with at least one of a plurality of rules to create a subset of candidate completion suggestions; and
filter the subset of candidate completion suggestions based on a filter criteria; and
rank the filtered subset. 15. The system of claim 14 wherein the filter criteria selects one candidate completion suggestion associated with an underlying document and removes any other candidate completion suggestions associated with the underlying document. 16. The system of claim 14 wherein the filter criteria selects a highest ranked candidate completion suggestion associated with an underlying document and removes any other candidate completion suggestions associated with the underlying document 17. A computer storage medium comprising executable instructions that, when executed by a processor of a machine, cause the machine to perform operations comprising:
receive, from a user, a query prefix representing a portion of a query; search a short text index comprising a plurality of text entries, each entry comprising the title of an associated document; identify a subset of the plurality of short text entries retrieved from the short text index; create a language model from the subset, the language model comprising a plurality of n-grams each with an n-gram probability; create a plurality of query completion suggestions based on the language model and the query prefix; and return plurality of query completion suggestions to the user via a user interface. 18. The medium of claim 17 wherein the plurality of short text entries each have a probability metric derived from at least one of:
a number of times a document associated with the entry has been viewed;
a type of match between the query prefix and the entry; and
a number of times a document comes up in search results. 19. The medium of claim 17 wherein creating the plurality of query completion suggestions comprises:
generate a set of candidate completion suggestions based on the query prefix and the language model;
remove from the set of candidate completion suggestions candidate completion suggestions that do not comply with at least one of a plurality of rules to create a subset of candidate completion suggestions; and
filter the subset of candidate completion suggestions based on a filter criteria; and
rank the filtered subset. 20. The medium of claim 19 wherein the filter criteria selects one candidate completion suggestion associated with an underlying document and removes any other candidate completion suggestions associated with the underlying document. | 2,100 |
6,059 | 6,059 | 15,299,730 | 2,173 | A wizard menu option is provided to begin a natural language wizard. A first wizard question page is provided that displays only a menu of colors. A second wizard question page is provided that displays only a menu of change magnitude/orientation phrases. A third wizard question page is provided that displays only a menu of color characteristic terms. A natural language sentence is created by combining a selected color, a selected change magnitude/orientation phrase, and a selected color characteristic term. In response to the natural language sentence, a color item is altered by changing locations of the image that have the selected color according to the selected change magnitude and change orientation phrase, and the selected color characteristic term. | 1. A method comprising:
providing an electronic display image having a wizard menu option to begin a natural language wizard; providing an electronic display image having a first wizard question page in response to selection of said wizard menu option, said first wizard question page displays only a menu of colors; providing an electronic display image having a second wizard question page in response to selection of a selected color from said menu of colors, said second wizard question page displays only a menu of change magnitude and change orientation phrases; providing an electronic display image having a third wizard question page in response to selection of a change magnitude and change orientation phrase from said menu of change magnitude and change orientation phrases, said third wizard question page displays only a menu of color characteristic terms; creating, in response to selection of a color characteristic term from said menu of color characteristic terms, a natural language sentence by combining said selected color, said change magnitude and change orientation phrase, and said color characteristic term; and altering, in response to said natural language sentence, a color item by changing locations of said color item that have said selected color according to said change magnitude and change orientation phrase, and said color characteristic term. 2. The method according to claim 1, said menu of colors includes text asking what color to change,
said menu of change magnitude and change orientation phrases includes text asking how much change, and said menu of color characteristic terms includes text asking what type of change. 3. The method according to claim 1, said menu of colors includes icons of different colors,
said menu of change magnitude and change orientation phrases includes icons of change and orientation, and said menu of color characteristic terms includes icons for types of changes. 4. The method according to claim 1, wizard menu option comprises a first menu option to create said natural language sentence, and a modified menu option to edit said natural language sentence. 5. The method according to claim 1, said menu of colors, said menu of change magnitude and change orientation phrases, and said menu of change magnitude and change orientation phrases include back and cancel buttons. 6. The method according to claim 1, said providing said wizard menu option displays said wizard menu option in a document printing menu. 7. A method comprising:
providing, from a processor to a display device, an electronic display image having a wizard menu option to begin a natural language wizard,
said natural language wizard generates a natural language sentence indicating an intended color change by combining responses to wizard question pages;
providing, from said processor to said display device, an electronic display image having a first wizard question page, of said wizard question pages, in response to selection of said wizard menu option,
said first wizard question page displays only a first menu of colors;
creating, by said processor, in response to selection of an expanded color from said first menu of colors, a modified menu of colors by expanding said first menu of colors to include sub-colors of said expanded color in addition to color choices provided within said first menu of colors; providing, from said processor to said display device, an electronic display image having a second wizard question page, of said wizard question pages, in response to selection of said expanded color from said first menu of colors,
said second wizard question page displays only said modified menu of colors;
providing, from said processor to said display device, an electronic display image having a third wizard question page, of said wizard question pages, in response to selection of a selected color from said modified menu of colors,
said third wizard question page displays only a menu of change magnitude and change orientation phrases;
providing, from said processor to said display device, an electronic display image having a fourth wizard question page, of said wizard question pages, in response to selection of a change magnitude and change orientation phrase from said menu of change magnitude and change orientation phrases,
said fourth wizard question page displays only a menu of color characteristic terms;
creating, by said processor, in response to selection of a color characteristic term from said menu of color characteristic terms, said natural language sentence by combining said selected color, said change magnitude and change orientation phrase, and said color characteristic term; and altering, by said processor, in response to said natural language sentence, printing of a color item by changing pixels of said color item that have said selected color according to said change magnitude and change orientation phrase, and said color characteristic term. 8. The method according to claim 7, said first menu of colors and said modified menu of colors include text asking what color to change,
said menu of change magnitude and change orientation phrases includes text asking how much change, and said menu of color characteristic terms includes text asking what type of change. 9. The method according to claim 7, said first menu of colors and said modified menu of colors include icons of different colors,
said menu of change magnitude and change orientation phrases includes icons of change and orientation, and said menu of color characteristic terms includes icons for types of changes. 10. The method according to claim 7, said wizard menu option comprises a first menu option to create said natural language sentence, and a modified menu option to edit said natural language sentence. 11. The method according to claim 7, said first menu of colors, said modified menu of colors, said menu of change magnitude and change orientation phrases, and said menu of change magnitude and change orientation phrases include back and cancel buttons. 12. The method according to claim 7, said providing said wizard menu option displays said wizard menu option in a document printing menu. 13. The method according to claim 7, said display device comprising a user interface having an electronic display and user input devices and features. 14. A device comprising:
a processor; a display device electrically connected to said processor; and a printer electrically connected to said processor, said processor provides, to said display device, an electronic display image having a wizard menu option to begin a natural language wizard, said natural language wizard generates a natural language sentence indicating an intended color change by combining responses to wizard question pages, said processor provides, to said display device, an electronic display image having a first wizard question page, of said wizard question pages, in response to selection of said wizard menu option, said first wizard question page displays only a first menu of colors, said processor creates, in response to selection of an expanded color from said first menu of colors, a modified menu of colors by expanding said first menu of colors to include sub-colors of said expanded color in addition to color choices provided within said first menu of colors, said processor provides, to said display device, an electronic display image having a second wizard question page, of said wizard question pages, in response to selection of said expanded color from said first menu of colors, said second wizard question page displays only said modified menu of colors, said processor provides, to said display device, an electronic display image having a third wizard question page, of said wizard question pages, in response to selection of a selected color from said modified menu of colors, said third wizard question page displays only a menu of change magnitude and change orientation phrases, said processor provides, to said display device, an electronic display image having a fourth wizard question page, of said wizard question pages, in response to selection of a change magnitude and change orientation phrase from said menu of change magnitude and change orientation phrases, said fourth wizard question page displays only a menu of color characteristic terms, said processor creates, in response to selection of a color characteristic term from said menu of color characteristic terms, said natural language sentence by combining said selected color, said change magnitude and change orientation phrase, and said color characteristic term, and said processor alters, in response to said natural language sentence, printing of a color item performed by said printer by changing pixels of said color item that have said selected color according to said change magnitude and change orientation phrase, and said color characteristic term. 15. The device according to claim 14, said first menu of colors and said modified menu of colors include text asking what color to change,
said menu of change magnitude and change orientation phrases includes text asking how much change, and said menu of color characteristic terms includes text asking what type of change. 16. The device according to claim 14, said first menu of colors and said modified menu of colors include icons of different colors,
said menu of change magnitude and change orientation phrases includes icons of change and orientation, and said menu of color characteristic terms includes icons for types of changes. 17. The device according to claim 14, said wizard menu option comprises a first menu option to create said natural language sentence, and a modified menu option to edit said natural language sentence. 18. The device according to claim 14, said first menu of colors, said modified menu of colors, said menu of change magnitude and change orientation phrases, and said menu of change magnitude and change orientation phrases include back and cancel buttons. 19. The device according to claim 14, said display device displays said wizard menu option in a document printing menu. 20. The device according to claim 14, said display device comprising a user interface having an electronic display and user input devices and features. | A wizard menu option is provided to begin a natural language wizard. A first wizard question page is provided that displays only a menu of colors. A second wizard question page is provided that displays only a menu of change magnitude/orientation phrases. A third wizard question page is provided that displays only a menu of color characteristic terms. A natural language sentence is created by combining a selected color, a selected change magnitude/orientation phrase, and a selected color characteristic term. In response to the natural language sentence, a color item is altered by changing locations of the image that have the selected color according to the selected change magnitude and change orientation phrase, and the selected color characteristic term.1. A method comprising:
providing an electronic display image having a wizard menu option to begin a natural language wizard; providing an electronic display image having a first wizard question page in response to selection of said wizard menu option, said first wizard question page displays only a menu of colors; providing an electronic display image having a second wizard question page in response to selection of a selected color from said menu of colors, said second wizard question page displays only a menu of change magnitude and change orientation phrases; providing an electronic display image having a third wizard question page in response to selection of a change magnitude and change orientation phrase from said menu of change magnitude and change orientation phrases, said third wizard question page displays only a menu of color characteristic terms; creating, in response to selection of a color characteristic term from said menu of color characteristic terms, a natural language sentence by combining said selected color, said change magnitude and change orientation phrase, and said color characteristic term; and altering, in response to said natural language sentence, a color item by changing locations of said color item that have said selected color according to said change magnitude and change orientation phrase, and said color characteristic term. 2. The method according to claim 1, said menu of colors includes text asking what color to change,
said menu of change magnitude and change orientation phrases includes text asking how much change, and said menu of color characteristic terms includes text asking what type of change. 3. The method according to claim 1, said menu of colors includes icons of different colors,
said menu of change magnitude and change orientation phrases includes icons of change and orientation, and said menu of color characteristic terms includes icons for types of changes. 4. The method according to claim 1, wizard menu option comprises a first menu option to create said natural language sentence, and a modified menu option to edit said natural language sentence. 5. The method according to claim 1, said menu of colors, said menu of change magnitude and change orientation phrases, and said menu of change magnitude and change orientation phrases include back and cancel buttons. 6. The method according to claim 1, said providing said wizard menu option displays said wizard menu option in a document printing menu. 7. A method comprising:
providing, from a processor to a display device, an electronic display image having a wizard menu option to begin a natural language wizard,
said natural language wizard generates a natural language sentence indicating an intended color change by combining responses to wizard question pages;
providing, from said processor to said display device, an electronic display image having a first wizard question page, of said wizard question pages, in response to selection of said wizard menu option,
said first wizard question page displays only a first menu of colors;
creating, by said processor, in response to selection of an expanded color from said first menu of colors, a modified menu of colors by expanding said first menu of colors to include sub-colors of said expanded color in addition to color choices provided within said first menu of colors; providing, from said processor to said display device, an electronic display image having a second wizard question page, of said wizard question pages, in response to selection of said expanded color from said first menu of colors,
said second wizard question page displays only said modified menu of colors;
providing, from said processor to said display device, an electronic display image having a third wizard question page, of said wizard question pages, in response to selection of a selected color from said modified menu of colors,
said third wizard question page displays only a menu of change magnitude and change orientation phrases;
providing, from said processor to said display device, an electronic display image having a fourth wizard question page, of said wizard question pages, in response to selection of a change magnitude and change orientation phrase from said menu of change magnitude and change orientation phrases,
said fourth wizard question page displays only a menu of color characteristic terms;
creating, by said processor, in response to selection of a color characteristic term from said menu of color characteristic terms, said natural language sentence by combining said selected color, said change magnitude and change orientation phrase, and said color characteristic term; and altering, by said processor, in response to said natural language sentence, printing of a color item by changing pixels of said color item that have said selected color according to said change magnitude and change orientation phrase, and said color characteristic term. 8. The method according to claim 7, said first menu of colors and said modified menu of colors include text asking what color to change,
said menu of change magnitude and change orientation phrases includes text asking how much change, and said menu of color characteristic terms includes text asking what type of change. 9. The method according to claim 7, said first menu of colors and said modified menu of colors include icons of different colors,
said menu of change magnitude and change orientation phrases includes icons of change and orientation, and said menu of color characteristic terms includes icons for types of changes. 10. The method according to claim 7, said wizard menu option comprises a first menu option to create said natural language sentence, and a modified menu option to edit said natural language sentence. 11. The method according to claim 7, said first menu of colors, said modified menu of colors, said menu of change magnitude and change orientation phrases, and said menu of change magnitude and change orientation phrases include back and cancel buttons. 12. The method according to claim 7, said providing said wizard menu option displays said wizard menu option in a document printing menu. 13. The method according to claim 7, said display device comprising a user interface having an electronic display and user input devices and features. 14. A device comprising:
a processor; a display device electrically connected to said processor; and a printer electrically connected to said processor, said processor provides, to said display device, an electronic display image having a wizard menu option to begin a natural language wizard, said natural language wizard generates a natural language sentence indicating an intended color change by combining responses to wizard question pages, said processor provides, to said display device, an electronic display image having a first wizard question page, of said wizard question pages, in response to selection of said wizard menu option, said first wizard question page displays only a first menu of colors, said processor creates, in response to selection of an expanded color from said first menu of colors, a modified menu of colors by expanding said first menu of colors to include sub-colors of said expanded color in addition to color choices provided within said first menu of colors, said processor provides, to said display device, an electronic display image having a second wizard question page, of said wizard question pages, in response to selection of said expanded color from said first menu of colors, said second wizard question page displays only said modified menu of colors, said processor provides, to said display device, an electronic display image having a third wizard question page, of said wizard question pages, in response to selection of a selected color from said modified menu of colors, said third wizard question page displays only a menu of change magnitude and change orientation phrases, said processor provides, to said display device, an electronic display image having a fourth wizard question page, of said wizard question pages, in response to selection of a change magnitude and change orientation phrase from said menu of change magnitude and change orientation phrases, said fourth wizard question page displays only a menu of color characteristic terms, said processor creates, in response to selection of a color characteristic term from said menu of color characteristic terms, said natural language sentence by combining said selected color, said change magnitude and change orientation phrase, and said color characteristic term, and said processor alters, in response to said natural language sentence, printing of a color item performed by said printer by changing pixels of said color item that have said selected color according to said change magnitude and change orientation phrase, and said color characteristic term. 15. The device according to claim 14, said first menu of colors and said modified menu of colors include text asking what color to change,
said menu of change magnitude and change orientation phrases includes text asking how much change, and said menu of color characteristic terms includes text asking what type of change. 16. The device according to claim 14, said first menu of colors and said modified menu of colors include icons of different colors,
said menu of change magnitude and change orientation phrases includes icons of change and orientation, and said menu of color characteristic terms includes icons for types of changes. 17. The device according to claim 14, said wizard menu option comprises a first menu option to create said natural language sentence, and a modified menu option to edit said natural language sentence. 18. The device according to claim 14, said first menu of colors, said modified menu of colors, said menu of change magnitude and change orientation phrases, and said menu of change magnitude and change orientation phrases include back and cancel buttons. 19. The device according to claim 14, said display device displays said wizard menu option in a document printing menu. 20. The device according to claim 14, said display device comprising a user interface having an electronic display and user input devices and features. | 2,100 |
6,060 | 6,060 | 15,234,020 | 2,153 | A webpage from a network server is received. The content of the received webpage is parsed. A first set of contextual data from one or more sources is collected. A first relationship between the collected first set of contextual data and the parsed content is identified. The identified relationship is determined to satisfy a first threshold. The parsed content is stored in a database for future display in response to the identified relationship satisfying the first threshold. At least a portion of the parsed content not stored in the database is displayed. | 1. A processor-implemented method for dynamically storing parsed content of a webpage for future display, the method comprising:
receiving, by a processor, the webpage from a network server; parsing, by the processor, content of the received webpage; collecting, by the processor, a first set of contextual data from one or more sources; identifying, by the processor a first relationship between the collected first set of contextual data and the parsed content; determining, by the processor, the identified relationship satisfies a first threshold; storing, by the processor, the parsed content in a database for future display in response to the identified relationship satisfying the first threshold; and displaying, by the processor, at least a portion of the parsed content not stored in the database. 2. The method of claim 1, further comprising:
searching, by the processor, the database for previously parsed content; collecting, by the processor, a second set of contextual data from the one or more sources; identifying, by the processor utilizing analytic software, a second relationship between the second set of contextual data and the previously parsed content; determining, by the processor, the second relationship satisfies a second threshold; and displaying, by the processor, a list of the previously parsed content for selection by a user in response to the second relationship satisfying the second threshold. 3. The method of claim 1, wherein the parsed content is stored in the database according to a date the content was parsed. 4. The method of claim 1, wherein the parsed content is stored in the database according to a range of priority. 5. The method of claim 1, wherein the one or more sources are selected from the group consisting of a camera, WIFI network, body temperature sensor, and accelerometer. 6. The method of claim 2, wherein the displayed list of the previously parsed content for selection by the user is displayed within a graphical user interface device coupled to the processor. 7. The method of claim 2, wherein the displayed list of the previously parsed content is categorized according to a priority of the previously parsed content. 8. A computer system for dynamically storing parsed content of a webpage for future display, the computer system comprising:
one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising: receiving, by a processor, the webpage from a network server; parsing, by the processor, content of the received webpage; collecting, by the processor, a first set of contextual data from one or more sources; identifying, by the processor, a first relationship between the collected first set of contextual data and the parsed content; determining, by the processor, the identified relationship satisfies a first threshold; storing, by the processor, the parsed content in a database for future display in response to the identified relationship satisfying the first threshold; and displaying, by the processor, at least a portion of the parsed content not stored in the database. 9. The computer system of claim 8, further comprising:
searching, by the processor, the database for previously parsed content; collecting, by the processor, a second set of contextual data from the one or more sources; identifying, by the processor utilizing analytic software, a second relationship between the second set of contextual data and the previously parsed content; determining, by the processor, the second relationship satisfies a second threshold; and displaying, by the processor, a list of the previously parsed content for selection by a user in response to the second relationship satisfying the second threshold. 10. The computer system of claim 8, wherein the parsed content is stored in the database according to a date the content was parsed. 11. The computer system of claim 8, wherein the parsed content is stored in the database according to a range of priority. 12. The computer system of claim 8, wherein the one or more sources are selected from the group consisting of a camera, WIFI network, body temperature sensor, and accelerometer. 13. The computer system of claim 9, wherein the displayed list of the previously parsed content for selection by a user is displayed within a graphical user interface device coupled to the processor. 14. The computer system of claim 9, wherein the displayed list of the previously parsed content is categorized according to a priority of the previously parsed content. 15. A computer program product for dynamically parsing a webpage, the computer program product comprising:
one or more computer-readable storage medium and program instructions stored on at least one of the one or more tangible storage medium, the program instructions executable by a processor, the program instructions comprising: program instructions to receive by a processor, the webpage from a network server; program instructions to parse, by the processor, content of the received webpage; program instructions to collect, by the processor, a first set of contextual data from one or more sources; program instructions to identify, by the processor, a first relationship between the collected first set of contextual data and the parsed content; program instructions to determine, by the processor, the identified relationship satisfies a first threshold; program instructions to store, by the processor, the parsed content in a database for future display in response to the identified relationship satisfying the first threshold; and program instructions to display, by the processor, at least a portion of the parsed content not stored in the database. 16. The computer program product of claim 15, further comprising:
program instructions to search, by the processor, the database for previously parsed content; program instructions to collect, by the processor, a second set of contextual data from the one or more sources; program instructions to identify, by the processor utilizing analytic software, a second relationship between the second set of contextual data and the previously parsed content; program instructions to determine, by the processor, the second relationship satisfies a second threshold; and program instructions to display, by the processor, a list of the previously parsed content for selection by a user in response to the second relationship satisfying the second threshold. 17. The computer program product of claim 15, wherein the parsed content is stored in the database according to a date the content was parsed. 18. The computer program product of claim 15, wherein the parsed content is stored in the database according to a range of priority. 19. The computer program product of claim 15, wherein the one or more sources are selected from the group consisting of a camera, WIFI network, body temperature sensor, and accelerometer. 20. The computer program product of claim 16, wherein the displayed list of the previously parsed content for selection by the user is displayed within a graphical user interface device coupled to the processor. | A webpage from a network server is received. The content of the received webpage is parsed. A first set of contextual data from one or more sources is collected. A first relationship between the collected first set of contextual data and the parsed content is identified. The identified relationship is determined to satisfy a first threshold. The parsed content is stored in a database for future display in response to the identified relationship satisfying the first threshold. At least a portion of the parsed content not stored in the database is displayed.1. A processor-implemented method for dynamically storing parsed content of a webpage for future display, the method comprising:
receiving, by a processor, the webpage from a network server; parsing, by the processor, content of the received webpage; collecting, by the processor, a first set of contextual data from one or more sources; identifying, by the processor a first relationship between the collected first set of contextual data and the parsed content; determining, by the processor, the identified relationship satisfies a first threshold; storing, by the processor, the parsed content in a database for future display in response to the identified relationship satisfying the first threshold; and displaying, by the processor, at least a portion of the parsed content not stored in the database. 2. The method of claim 1, further comprising:
searching, by the processor, the database for previously parsed content; collecting, by the processor, a second set of contextual data from the one or more sources; identifying, by the processor utilizing analytic software, a second relationship between the second set of contextual data and the previously parsed content; determining, by the processor, the second relationship satisfies a second threshold; and displaying, by the processor, a list of the previously parsed content for selection by a user in response to the second relationship satisfying the second threshold. 3. The method of claim 1, wherein the parsed content is stored in the database according to a date the content was parsed. 4. The method of claim 1, wherein the parsed content is stored in the database according to a range of priority. 5. The method of claim 1, wherein the one or more sources are selected from the group consisting of a camera, WIFI network, body temperature sensor, and accelerometer. 6. The method of claim 2, wherein the displayed list of the previously parsed content for selection by the user is displayed within a graphical user interface device coupled to the processor. 7. The method of claim 2, wherein the displayed list of the previously parsed content is categorized according to a priority of the previously parsed content. 8. A computer system for dynamically storing parsed content of a webpage for future display, the computer system comprising:
one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising: receiving, by a processor, the webpage from a network server; parsing, by the processor, content of the received webpage; collecting, by the processor, a first set of contextual data from one or more sources; identifying, by the processor, a first relationship between the collected first set of contextual data and the parsed content; determining, by the processor, the identified relationship satisfies a first threshold; storing, by the processor, the parsed content in a database for future display in response to the identified relationship satisfying the first threshold; and displaying, by the processor, at least a portion of the parsed content not stored in the database. 9. The computer system of claim 8, further comprising:
searching, by the processor, the database for previously parsed content; collecting, by the processor, a second set of contextual data from the one or more sources; identifying, by the processor utilizing analytic software, a second relationship between the second set of contextual data and the previously parsed content; determining, by the processor, the second relationship satisfies a second threshold; and displaying, by the processor, a list of the previously parsed content for selection by a user in response to the second relationship satisfying the second threshold. 10. The computer system of claim 8, wherein the parsed content is stored in the database according to a date the content was parsed. 11. The computer system of claim 8, wherein the parsed content is stored in the database according to a range of priority. 12. The computer system of claim 8, wherein the one or more sources are selected from the group consisting of a camera, WIFI network, body temperature sensor, and accelerometer. 13. The computer system of claim 9, wherein the displayed list of the previously parsed content for selection by a user is displayed within a graphical user interface device coupled to the processor. 14. The computer system of claim 9, wherein the displayed list of the previously parsed content is categorized according to a priority of the previously parsed content. 15. A computer program product for dynamically parsing a webpage, the computer program product comprising:
one or more computer-readable storage medium and program instructions stored on at least one of the one or more tangible storage medium, the program instructions executable by a processor, the program instructions comprising: program instructions to receive by a processor, the webpage from a network server; program instructions to parse, by the processor, content of the received webpage; program instructions to collect, by the processor, a first set of contextual data from one or more sources; program instructions to identify, by the processor, a first relationship between the collected first set of contextual data and the parsed content; program instructions to determine, by the processor, the identified relationship satisfies a first threshold; program instructions to store, by the processor, the parsed content in a database for future display in response to the identified relationship satisfying the first threshold; and program instructions to display, by the processor, at least a portion of the parsed content not stored in the database. 16. The computer program product of claim 15, further comprising:
program instructions to search, by the processor, the database for previously parsed content; program instructions to collect, by the processor, a second set of contextual data from the one or more sources; program instructions to identify, by the processor utilizing analytic software, a second relationship between the second set of contextual data and the previously parsed content; program instructions to determine, by the processor, the second relationship satisfies a second threshold; and program instructions to display, by the processor, a list of the previously parsed content for selection by a user in response to the second relationship satisfying the second threshold. 17. The computer program product of claim 15, wherein the parsed content is stored in the database according to a date the content was parsed. 18. The computer program product of claim 15, wherein the parsed content is stored in the database according to a range of priority. 19. The computer program product of claim 15, wherein the one or more sources are selected from the group consisting of a camera, WIFI network, body temperature sensor, and accelerometer. 20. The computer program product of claim 16, wherein the displayed list of the previously parsed content for selection by the user is displayed within a graphical user interface device coupled to the processor. | 2,100 |
6,061 | 6,061 | 15,340,826 | 2,181 | Determining and using the ideal size of memory to be transferred from high speed memory to a low speed memory may result in speedier saves to the low speed memory and a longer life for the low speed memory. | 1. A method performed on a computing device, the method comprising:
caching, by the computing device, data in a volatile random access memory, where the data being cached is designated to be stored in first disk-based memory; and backing-up, by the computing device, a first preferred amount of the cached data to an additional memory that comprises flash-based memory or second disk-based memory. 2. The method of claim 1 where the first preferred amount corresponds to a preferred write size of the additional memory. 3. The method of claim 1 further comprising writing a second preferred amount of the cached data to the first disk-based memory. 4. The method of claim 3 where the second preferred amount corresponds to a preferred write size of the first disk-based memory. 5. The method of claim 1 further comprising writing, in response to the first preferred amount of the data being cached in the volatile random access memory, the first preferred amount of the cached data to the flash-based memory or the second disk-based memory. 6. The method of claim 5 where the writing is further in response to a period of low system activity. 7. The method of claim 5 further comprising determining that a portion of the cached data in the volatile random access memory has been replaced with newer cached data prior to the writing. 8. A computing device comprising:
at least one processor; volatile random access memory; first disk-based memory; and computer-executable instructions that, based on execution by the at east one processor, configure the computing device to perform actions comprising:
caching data in the volatile random access memory, where the data being cached is designated to be stored in the first disk-based memory; and
backing-up, by the computing device, a first preferred amount of the cached data to an additional memory that comprises flash-based memory or second disk-based memory. 9. The computing device of claim 8 where the first preferred amount corresponds to a preferred write size of the additional memory. 10. The computing device of claim 8, the actions further comprising writing a second preferred amount of the cached data to the first disk-based memory. 11. The computing device of claim 10 where the second preferred amount corresponds to a preferred write size of the first disk-based memory. 12. The computing device of claim 8, the actions further comprising writing, in response to the first preferred amount of the data being cached in the volatile random access memory, the first preferred amount of the cached data to the flash-based memory or the second disk-based memory. 13. The computing device of claim 12 where the writing is further in response to a period of low system activity. 14. The computing device of claim 12 further comprising determining that a portion of the cached data in the volatile random access memory has been replaced with newer cached data prior to the writing. 15. At least one computer storage device comprising:
memory that comprises computer-executable instructions that, based on execution by a computing device, configure the computing device to perform actions comprising:
caching, by the computing device, data in a volatile random access memory, where the data being cached is designated to be stored in first disk-based memory; and
backing-up, by the computing device, a first preferred amount of the cached data to an additional memory that comprises flash-based memory or second disk-based memory. 16. The at least one computer storage device of claim 15, the actions further comprising writing a second preferred amount of the cached data to the first disk-based memory. 17. The at least one computer storage device of claim 16 where the second preferred amount corresponds to a preferred write size of the first disk-based memory. 18. The at least one computer storage device of claim 15, the actions further comprising writing, in response to the first preferred amount of the data being cached in the volatile random access memory, the first preferred amount of the cached data to the flash-based memory or the second disk-based memory. 19. The at least one computer storage device of claim 18 where the writing is further in response to a period of low system activity. 20. The at least one computer storage device of claim 18 further comprising determining that a portion of the cached data in the volatile random access memory has been replaced with newer cached data prior to the writing. | Determining and using the ideal size of memory to be transferred from high speed memory to a low speed memory may result in speedier saves to the low speed memory and a longer life for the low speed memory.1. A method performed on a computing device, the method comprising:
caching, by the computing device, data in a volatile random access memory, where the data being cached is designated to be stored in first disk-based memory; and backing-up, by the computing device, a first preferred amount of the cached data to an additional memory that comprises flash-based memory or second disk-based memory. 2. The method of claim 1 where the first preferred amount corresponds to a preferred write size of the additional memory. 3. The method of claim 1 further comprising writing a second preferred amount of the cached data to the first disk-based memory. 4. The method of claim 3 where the second preferred amount corresponds to a preferred write size of the first disk-based memory. 5. The method of claim 1 further comprising writing, in response to the first preferred amount of the data being cached in the volatile random access memory, the first preferred amount of the cached data to the flash-based memory or the second disk-based memory. 6. The method of claim 5 where the writing is further in response to a period of low system activity. 7. The method of claim 5 further comprising determining that a portion of the cached data in the volatile random access memory has been replaced with newer cached data prior to the writing. 8. A computing device comprising:
at least one processor; volatile random access memory; first disk-based memory; and computer-executable instructions that, based on execution by the at east one processor, configure the computing device to perform actions comprising:
caching data in the volatile random access memory, where the data being cached is designated to be stored in the first disk-based memory; and
backing-up, by the computing device, a first preferred amount of the cached data to an additional memory that comprises flash-based memory or second disk-based memory. 9. The computing device of claim 8 where the first preferred amount corresponds to a preferred write size of the additional memory. 10. The computing device of claim 8, the actions further comprising writing a second preferred amount of the cached data to the first disk-based memory. 11. The computing device of claim 10 where the second preferred amount corresponds to a preferred write size of the first disk-based memory. 12. The computing device of claim 8, the actions further comprising writing, in response to the first preferred amount of the data being cached in the volatile random access memory, the first preferred amount of the cached data to the flash-based memory or the second disk-based memory. 13. The computing device of claim 12 where the writing is further in response to a period of low system activity. 14. The computing device of claim 12 further comprising determining that a portion of the cached data in the volatile random access memory has been replaced with newer cached data prior to the writing. 15. At least one computer storage device comprising:
memory that comprises computer-executable instructions that, based on execution by a computing device, configure the computing device to perform actions comprising:
caching, by the computing device, data in a volatile random access memory, where the data being cached is designated to be stored in first disk-based memory; and
backing-up, by the computing device, a first preferred amount of the cached data to an additional memory that comprises flash-based memory or second disk-based memory. 16. The at least one computer storage device of claim 15, the actions further comprising writing a second preferred amount of the cached data to the first disk-based memory. 17. The at least one computer storage device of claim 16 where the second preferred amount corresponds to a preferred write size of the first disk-based memory. 18. The at least one computer storage device of claim 15, the actions further comprising writing, in response to the first preferred amount of the data being cached in the volatile random access memory, the first preferred amount of the cached data to the flash-based memory or the second disk-based memory. 19. The at least one computer storage device of claim 18 where the writing is further in response to a period of low system activity. 20. The at least one computer storage device of claim 18 further comprising determining that a portion of the cached data in the volatile random access memory has been replaced with newer cached data prior to the writing. | 2,100 |
6,062 | 6,062 | 15,831,717 | 2,154 | A keycode data structure includes a device type byte, a set of keycodes, system code information, a system data byte, a protocol pointer that points to a protocol table and a number of flagbytes that are used to index a particular key among the keycodes. The keycode data structure also contains a plurality of keycode data structure pointers (KDSPs). Keycode data structures are linked together using KDSPs. A special value in the keycode data structure is used to indicate that the keycode data structure contains multiple KDSPs. The number of pointers is stored in a particular location of the keycode data structure. | 1. A controlling device, comprising
a processing device; a transmitting device coupled to the processing device; an input element coupled to the processing device; and a memory device in which is stored instructions executable by the processing device wherein the instructions, when executed by the processing device, cause the controlling device to respond to a user interaction with the input element by sequentially accessing a plurality of keycode data structures that are linked to each other until a keycode corresponding to the input element is determined to be contained in a one of the plurality of keycode data structures being accessed whereupon the controlling device is caused to use the keycode when transmitting a command, via use of the transmitting device, to control a functional operation of an intended target appliance. 2. The controlling device as recited in claim 1, wherein the transmitting device further uses a system code and a protocol when transmitting the command to control the functional operation of the intended target appliance. 3. The controlling device as recited in claim 2, wherein at least one of the plurality of keycode data structures contains the system code that is used by the transmitting device when transmitting the command to control the functional operation of the intended target device. 4. The controlling device as recited in claim 2, wherein a first accessed one of the plurality of keycode data structures contains the system code that is used by the transmitting device when transmitting the command to control the functional operation of the intended target device. 5. The controlling device as recited in claim 2, wherein the protocol comprises a sequence of indices, wherein the indices identify mark times and space times characterizing digital ones and zeros in a command signal having the command to control the functional operation of the intended target device. 6. The controlling device as recited in claim 2, wherein a one of the plurality of keycode data structures contains a link to the protocol that is used by the transmitting device when transmitting the command to control the functional operation of the intended target device. 7. The controlling device as recited in claim 1, wherein the transmitting device comprises an infrared transmitter. 8. The controlling device as recited in claim 1, wherein the input element comprises a one of a plurality of hard keys of the controlling device. 9. The controlling device as recited in claim 1, wherein the plurality of keycode data structures are linked to each other via use of relative offset values. 10. The controlling device as recited in claim 1, wherein the plurality of keycode data structures are linked to each other via use of absolute address values. | A keycode data structure includes a device type byte, a set of keycodes, system code information, a system data byte, a protocol pointer that points to a protocol table and a number of flagbytes that are used to index a particular key among the keycodes. The keycode data structure also contains a plurality of keycode data structure pointers (KDSPs). Keycode data structures are linked together using KDSPs. A special value in the keycode data structure is used to indicate that the keycode data structure contains multiple KDSPs. The number of pointers is stored in a particular location of the keycode data structure.1. A controlling device, comprising
a processing device; a transmitting device coupled to the processing device; an input element coupled to the processing device; and a memory device in which is stored instructions executable by the processing device wherein the instructions, when executed by the processing device, cause the controlling device to respond to a user interaction with the input element by sequentially accessing a plurality of keycode data structures that are linked to each other until a keycode corresponding to the input element is determined to be contained in a one of the plurality of keycode data structures being accessed whereupon the controlling device is caused to use the keycode when transmitting a command, via use of the transmitting device, to control a functional operation of an intended target appliance. 2. The controlling device as recited in claim 1, wherein the transmitting device further uses a system code and a protocol when transmitting the command to control the functional operation of the intended target appliance. 3. The controlling device as recited in claim 2, wherein at least one of the plurality of keycode data structures contains the system code that is used by the transmitting device when transmitting the command to control the functional operation of the intended target device. 4. The controlling device as recited in claim 2, wherein a first accessed one of the plurality of keycode data structures contains the system code that is used by the transmitting device when transmitting the command to control the functional operation of the intended target device. 5. The controlling device as recited in claim 2, wherein the protocol comprises a sequence of indices, wherein the indices identify mark times and space times characterizing digital ones and zeros in a command signal having the command to control the functional operation of the intended target device. 6. The controlling device as recited in claim 2, wherein a one of the plurality of keycode data structures contains a link to the protocol that is used by the transmitting device when transmitting the command to control the functional operation of the intended target device. 7. The controlling device as recited in claim 1, wherein the transmitting device comprises an infrared transmitter. 8. The controlling device as recited in claim 1, wherein the input element comprises a one of a plurality of hard keys of the controlling device. 9. The controlling device as recited in claim 1, wherein the plurality of keycode data structures are linked to each other via use of relative offset values. 10. The controlling device as recited in claim 1, wherein the plurality of keycode data structures are linked to each other via use of absolute address values. | 2,100 |
6,063 | 6,063 | 14,090,272 | 2,144 | The subject matter of this specification can be implemented in, among other things, a method that includes causing presentation of a collaborative video project to a first user account that includes a set of one or more shared video clips and a set of one or more personal video clips. The method includes receiving from the first user account a first selection of a video clip in the set of personal video clips and, in response, adding the video clip to the set of shared video clips. The method includes causing presentation of the collaborative video project to a second user account, including presentation of the set of shared video clips. The method includes receiving from the second user account a second selection of the video clip and, in response, adding the video clip to a collaborative video for the collaborative video project. | 1. A method comprising:
causing, by a processing device, presentation of a collaborative video project to a first user account in a plurality of user accounts with which the collaborative video project is shared, wherein the collaborative video project presented to the first user account comprises a set of one or more shared video clips that are accessible by the plurality of user accounts and a first set of one or more video clips that are accessible by the first user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the first user account; receiving a first user input from the first user account that comprises a selection of a first video clip in the first set of one or more video clips; in response to receiving the first user input, adding the first video clip to the set of one or more shared video clips; causing, by the processing device, presentation of the collaborative video project to a second user account in the plurality of user accounts, wherein the collaborative video project presented to the second user account comprises the set of one or more shared video clips and a second set of one or more video clips that are accessible by the second user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the second user account; receiving a second user input from the second user account that comprises a selection of the first video clip in the shared set of one or more video clips presented to the second user account; and in response to receiving the second user input, adding the first video clip to a collaborative video for the collaborative video project. 2. The method of claim 1, further comprising:
receiving a third user input from the second user account that comprises a selection of a first video editing operation to perform on the first video clip in the collaborative video; and in response to receiving the third user input, performing the first video editing operation on the first video clip in the collaborative video. 3. The method of claim 2, further comprising:
receiving a fourth user input from the second user account that comprises a selection of a second video clip in the second set of one or more video clips; and in response to receiving the fourth user input, adding the second video clip to both the set of one or more shared video clips and the collaborative video. 4. The method of claim 3, further comprising:
receiving a fifth user input from the second user account that comprises a selection of a second video editing operation to perform on the second video clip in the collaborative video; and in response to receiving the fifth user input, performing the second video editing operation on the second video clip in the collaborative video. 5. The method of claim 1, further comprising:
receiving a sixth user input from the first user account that comprises a request to add the second user account to the plurality of user accounts; and in response to receiving the sixth user input, adding the second user account to the plurality of user accounts with which the collaborative video project is shared. 6. The method of claim 5, further comprising:
in response to adding the second user account to the plurality of user accounts, sending a notification to the second user account that the second user account has been added to the plurality of user accounts, wherein the notification comprises a link to the collaborative video project; and in response to a selection of the link by the second user account, receiving a request to present the collaborative video project, wherein causing the presentation of the collaborative video project to the second user account is in response to receiving the request to present the collaborative video project. 7. The method of claim 6, wherein each user account in the plurality of user accounts comprises a user account that has access to the link. 8. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processing device, cause the processing device to perform operations comprising:
causing, by the processing device, presentation of a collaborative video project to a first user account in a plurality of user accounts with which the collaborative video project is shared, wherein the collaborative video project presented to the first user account comprises a set of one or more shared video clips that are accessible by the plurality of user accounts and a first set of one or more video clips that are accessible by the first user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the first user account; receiving a first user input from the first user account that comprises a selection of a first video clip in the first set of one or more video clips; in response to receiving the first user input, adding the first video clip to the set of one or more shared video clips; causing, by the processing device, presentation of the collaborative video project to a second user account in the plurality of user accounts, wherein the collaborative video project presented to the second user account comprises the set of one or more shared video clips and a second set of one or more video clips that are accessible by the second user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the second user account; receiving a second user input from the second user account that comprises a selection of the first video clip in the shared set of one or more video clips presented to the second user account; and in response to receiving the second user input, adding the first video clip to a collaborative video for the collaborative video project. 9. The non-transitory computer-readable medium of claim 8, wherein the operations further comprise:
receiving a third user input from the second user account that comprises a selection of a first video editing operation to perform on the first video clip in the collaborative video; and in response to receiving the third user input, performing the first video editing operation on the first video clip in the collaborative video. 10. The non-transitory computer-readable medium of claim 9, wherein the operations further comprise:
receiving a fourth user input from the second user account that comprises a selection of a second video clip in the second set of one or more video clips; and in response to receiving the fourth user input, adding the second video clip to both the set of one or more shared video clips and the collaborative video. 11. The non-transitory computer-readable medium of claim 10, wherein the operations further comprise:
receiving a fifth user input from the second user account that comprises a selection of a second video editing operation to perform on the second video clip in the collaborative video; and in response to receiving the fifth user input, performing the second video editing operation on the second video clip in the collaborative video. 12. The non-transitory computer-readable medium of claim 8, wherein the operations further comprise:
receiving a sixth user input from the first user account that comprises a request to add the second user account to the plurality of user accounts; and in response to receiving the sixth user input, adding the second user account to the plurality of user accounts with which the collaborative video project is shared. 13. The non-transitory computer-readable medium of claim 12, wherein the operations further comprise:
in response to adding the second user account to the plurality of user accounts, sending a notification to the second user account that the second user account has been added to the plurality of user accounts, wherein the notification comprises a link to the collaborative video project; and in response to a selection of the link by the second user account, receiving a request to present the collaborative video project, wherein causing the presentation of the collaborative video project to the second user account is in response to receiving the request to present the collaborative video project. 14. A system comprising:
an interface to:
receive a first user input from a first user account in a plurality of user accounts with which a collaborative video project is shared, wherein the collaborative video project presented to the first user account comprises a set of one or more shared video clips that are accessible by the plurality of user accounts and a first set of one or more video clips that are accessible by the first user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the first user account, and wherein the first user input comprises a selection of a first video clip in the first set of one or more video clips;
receive a second user input from a second user account in the plurality of user accounts, wherein the collaborative video project presented to the second user account comprises the set of one or more shared video clips and a second set of one or more video clips that are accessible by the second user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the second user account, and wherein the second user input comprises a selection of the first video clip in the shared set of one or more video clips presented to the second user account; and
a processing device to:
cause presentation of the collaborative video project to the first user account;
in response to receipt of the first user input, add the first video clip to the set of one or more shared video clips;
cause presentation of the collaborative video project to the second user account;
in response to receipt of the second user input, add the first video clip to a collaborative video for the collaborative video project. 15. The system of claim 14, wherein:
the interface is further to receive a third user input from the second user account that comprises a selection of a first video editing operation to perform on the first video clip in the collaborative video; and in response to receipt of the third user input, the processing device is further to perform the first video editing operation on the first video clip in the collaborative video. 16. The system of claim 15, wherein:
the interface is further to receive a fourth user input from the second user account that comprises a selection of a second video clip in the second set of one or more video clips; and in response to receipt of the fourth user input, the processing device is further to add the second video clip to both the set of one or more shared video clips and the collaborative video. 17. The system of claim 16, wherein:
the interface is further to receive a fifth user input from the second user account that comprises a selection of a second video editing operation to perform on the second video clip in the collaborative video; and in response to receipt of the fifth user input, the processing device is further to perform the second video editing operation on the second video clip in the collaborative video. 18. The system of claim 14, wherein:
the interface is further to receive a sixth user input from the first user account that comprises a request to add the second user account to the plurality of user accounts; and in response to receipt of the sixth user input, the processing device is further to add the second user account to the plurality of user accounts with which the collaborative video project is shared. 19. The system of claim 18, wherein:
in response to addition of the second user account to the plurality of user accounts, the processing device is further to send a notification to the second user account that the second user account has been added to the plurality of user accounts, wherein the notification comprises a link to the collaborative video project; and in response to a selection of the link by the second user account, the interface is further to receive a request to present the collaborative video project, wherein the processing device is to cause the presentation of the collaborative video project to the second user account in response to receipt of the request to present the collaborative video project. 20. A system comprising:
an interface to:
receive a second user input from a second user account in a plurality of user accounts with which a collaborative video project is shared, wherein the collaborative video project presented to the second user account comprises a set of one or more shared video clips that are accessible by the plurality of user accounts and a second set of one or more video clips that are accessible by the second user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the second user account, wherein the set of one or more shared video clips comprises a first video clip that was previously within a first set of one or more video clips that are accessible by a first user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the first user account and subsequently added to the set of one or more shared video clips in response to a first user input from the first user account, and wherein the second user input comprises a selection of the first video clip in the shared set of one or more video clips presented to the second user account; and
a processing device to:
cause presentation of the collaborative video project to the second user account;
in response to receipt of the second user input, add the first video clip to a collaborative video for the collaborative video project. | The subject matter of this specification can be implemented in, among other things, a method that includes causing presentation of a collaborative video project to a first user account that includes a set of one or more shared video clips and a set of one or more personal video clips. The method includes receiving from the first user account a first selection of a video clip in the set of personal video clips and, in response, adding the video clip to the set of shared video clips. The method includes causing presentation of the collaborative video project to a second user account, including presentation of the set of shared video clips. The method includes receiving from the second user account a second selection of the video clip and, in response, adding the video clip to a collaborative video for the collaborative video project.1. A method comprising:
causing, by a processing device, presentation of a collaborative video project to a first user account in a plurality of user accounts with which the collaborative video project is shared, wherein the collaborative video project presented to the first user account comprises a set of one or more shared video clips that are accessible by the plurality of user accounts and a first set of one or more video clips that are accessible by the first user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the first user account; receiving a first user input from the first user account that comprises a selection of a first video clip in the first set of one or more video clips; in response to receiving the first user input, adding the first video clip to the set of one or more shared video clips; causing, by the processing device, presentation of the collaborative video project to a second user account in the plurality of user accounts, wherein the collaborative video project presented to the second user account comprises the set of one or more shared video clips and a second set of one or more video clips that are accessible by the second user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the second user account; receiving a second user input from the second user account that comprises a selection of the first video clip in the shared set of one or more video clips presented to the second user account; and in response to receiving the second user input, adding the first video clip to a collaborative video for the collaborative video project. 2. The method of claim 1, further comprising:
receiving a third user input from the second user account that comprises a selection of a first video editing operation to perform on the first video clip in the collaborative video; and in response to receiving the third user input, performing the first video editing operation on the first video clip in the collaborative video. 3. The method of claim 2, further comprising:
receiving a fourth user input from the second user account that comprises a selection of a second video clip in the second set of one or more video clips; and in response to receiving the fourth user input, adding the second video clip to both the set of one or more shared video clips and the collaborative video. 4. The method of claim 3, further comprising:
receiving a fifth user input from the second user account that comprises a selection of a second video editing operation to perform on the second video clip in the collaborative video; and in response to receiving the fifth user input, performing the second video editing operation on the second video clip in the collaborative video. 5. The method of claim 1, further comprising:
receiving a sixth user input from the first user account that comprises a request to add the second user account to the plurality of user accounts; and in response to receiving the sixth user input, adding the second user account to the plurality of user accounts with which the collaborative video project is shared. 6. The method of claim 5, further comprising:
in response to adding the second user account to the plurality of user accounts, sending a notification to the second user account that the second user account has been added to the plurality of user accounts, wherein the notification comprises a link to the collaborative video project; and in response to a selection of the link by the second user account, receiving a request to present the collaborative video project, wherein causing the presentation of the collaborative video project to the second user account is in response to receiving the request to present the collaborative video project. 7. The method of claim 6, wherein each user account in the plurality of user accounts comprises a user account that has access to the link. 8. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processing device, cause the processing device to perform operations comprising:
causing, by the processing device, presentation of a collaborative video project to a first user account in a plurality of user accounts with which the collaborative video project is shared, wherein the collaborative video project presented to the first user account comprises a set of one or more shared video clips that are accessible by the plurality of user accounts and a first set of one or more video clips that are accessible by the first user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the first user account; receiving a first user input from the first user account that comprises a selection of a first video clip in the first set of one or more video clips; in response to receiving the first user input, adding the first video clip to the set of one or more shared video clips; causing, by the processing device, presentation of the collaborative video project to a second user account in the plurality of user accounts, wherein the collaborative video project presented to the second user account comprises the set of one or more shared video clips and a second set of one or more video clips that are accessible by the second user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the second user account; receiving a second user input from the second user account that comprises a selection of the first video clip in the shared set of one or more video clips presented to the second user account; and in response to receiving the second user input, adding the first video clip to a collaborative video for the collaborative video project. 9. The non-transitory computer-readable medium of claim 8, wherein the operations further comprise:
receiving a third user input from the second user account that comprises a selection of a first video editing operation to perform on the first video clip in the collaborative video; and in response to receiving the third user input, performing the first video editing operation on the first video clip in the collaborative video. 10. The non-transitory computer-readable medium of claim 9, wherein the operations further comprise:
receiving a fourth user input from the second user account that comprises a selection of a second video clip in the second set of one or more video clips; and in response to receiving the fourth user input, adding the second video clip to both the set of one or more shared video clips and the collaborative video. 11. The non-transitory computer-readable medium of claim 10, wherein the operations further comprise:
receiving a fifth user input from the second user account that comprises a selection of a second video editing operation to perform on the second video clip in the collaborative video; and in response to receiving the fifth user input, performing the second video editing operation on the second video clip in the collaborative video. 12. The non-transitory computer-readable medium of claim 8, wherein the operations further comprise:
receiving a sixth user input from the first user account that comprises a request to add the second user account to the plurality of user accounts; and in response to receiving the sixth user input, adding the second user account to the plurality of user accounts with which the collaborative video project is shared. 13. The non-transitory computer-readable medium of claim 12, wherein the operations further comprise:
in response to adding the second user account to the plurality of user accounts, sending a notification to the second user account that the second user account has been added to the plurality of user accounts, wherein the notification comprises a link to the collaborative video project; and in response to a selection of the link by the second user account, receiving a request to present the collaborative video project, wherein causing the presentation of the collaborative video project to the second user account is in response to receiving the request to present the collaborative video project. 14. A system comprising:
an interface to:
receive a first user input from a first user account in a plurality of user accounts with which a collaborative video project is shared, wherein the collaborative video project presented to the first user account comprises a set of one or more shared video clips that are accessible by the plurality of user accounts and a first set of one or more video clips that are accessible by the first user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the first user account, and wherein the first user input comprises a selection of a first video clip in the first set of one or more video clips;
receive a second user input from a second user account in the plurality of user accounts, wherein the collaborative video project presented to the second user account comprises the set of one or more shared video clips and a second set of one or more video clips that are accessible by the second user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the second user account, and wherein the second user input comprises a selection of the first video clip in the shared set of one or more video clips presented to the second user account; and
a processing device to:
cause presentation of the collaborative video project to the first user account;
in response to receipt of the first user input, add the first video clip to the set of one or more shared video clips;
cause presentation of the collaborative video project to the second user account;
in response to receipt of the second user input, add the first video clip to a collaborative video for the collaborative video project. 15. The system of claim 14, wherein:
the interface is further to receive a third user input from the second user account that comprises a selection of a first video editing operation to perform on the first video clip in the collaborative video; and in response to receipt of the third user input, the processing device is further to perform the first video editing operation on the first video clip in the collaborative video. 16. The system of claim 15, wherein:
the interface is further to receive a fourth user input from the second user account that comprises a selection of a second video clip in the second set of one or more video clips; and in response to receipt of the fourth user input, the processing device is further to add the second video clip to both the set of one or more shared video clips and the collaborative video. 17. The system of claim 16, wherein:
the interface is further to receive a fifth user input from the second user account that comprises a selection of a second video editing operation to perform on the second video clip in the collaborative video; and in response to receipt of the fifth user input, the processing device is further to perform the second video editing operation on the second video clip in the collaborative video. 18. The system of claim 14, wherein:
the interface is further to receive a sixth user input from the first user account that comprises a request to add the second user account to the plurality of user accounts; and in response to receipt of the sixth user input, the processing device is further to add the second user account to the plurality of user accounts with which the collaborative video project is shared. 19. The system of claim 18, wherein:
in response to addition of the second user account to the plurality of user accounts, the processing device is further to send a notification to the second user account that the second user account has been added to the plurality of user accounts, wherein the notification comprises a link to the collaborative video project; and in response to a selection of the link by the second user account, the interface is further to receive a request to present the collaborative video project, wherein the processing device is to cause the presentation of the collaborative video project to the second user account in response to receipt of the request to present the collaborative video project. 20. A system comprising:
an interface to:
receive a second user input from a second user account in a plurality of user accounts with which a collaborative video project is shared, wherein the collaborative video project presented to the second user account comprises a set of one or more shared video clips that are accessible by the plurality of user accounts and a second set of one or more video clips that are accessible by the second user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the second user account, wherein the set of one or more shared video clips comprises a first video clip that was previously within a first set of one or more video clips that are accessible by a first user account and not accessible within the collaborative video project by ones of the plurality of user accounts other than the first user account and subsequently added to the set of one or more shared video clips in response to a first user input from the first user account, and wherein the second user input comprises a selection of the first video clip in the shared set of one or more video clips presented to the second user account; and
a processing device to:
cause presentation of the collaborative video project to the second user account;
in response to receipt of the second user input, add the first video clip to a collaborative video for the collaborative video project. | 2,100 |
6,064 | 6,064 | 15,212,733 | 2,173 | A method, system, and recorded instructions are provided for displaying an item on a touch display screen of the computing device, the touch display screen being operable to detect a user contact with the touch display screen; defining, with respect to the touch display screen, a first direction of the touch display screen and a second direction of the touch display screen such that the user contact with the touch display screen indicates both a first directional value in the first direction, and a second directional value in the second direction; then detecting the user contact with the touch display screen when the touch display screen is displaying of the item; determining the first directional value and the second directional value of the user contact; and, determining a response to the user contact based on the first directional value, the second directional value and the item. | 1. A computer-implemented method of receiving feedback from a user, the method comprising:
displaying an item on a touch display screen, the touch display screen being operable to detect a user contact with the touch display screen; defining, with respect to the touch display screen, a first direction of the touch display screen and a second direction of the touch display screen such that the user contact with the touch display screen indicates both a first directional value in the first direction, and a second directional value in the second direction; then detecting the user contact with the touch display screen when the touch display screen is displaying of the item; determining the first directional value and the second directional value of the user contact; and, determining a response to the user contact based on the first directional value, the second directional value and the item. 2. The computer implemented method as defined in claim 1 wherein determining the response comprises determining a message based on the first directional value, the second directional value and the item and then sending the message to the user. 3. The computer implemented method as defined in claim 1 wherein determining the response comprises
determining a category comprising the at least one item;
recording a binary value for the user vis-à-vis that category in a memory, the binary value being positive, indicating the user likes the item, or negative, indicating the user dislikes the item, and being determined from the first directional value;
when the binary value for the user is positive, recording a magnitude of a positive value, the magnitude being determined from the second directional value;
when the binary value for the user is positive, sending a message to the user wherein the message differs depending on the magnitude of the positive value. 4. The computer-implemented method as defined in claim 1 wherein the touch display screen is substantially planar, and defining, with respect to the touch display screen, the first direction of the touch display screen and the second direction of the touch display screen comprises defining a substantially Cartesian coordinate system wherein the first direction is substantially orthogonal to the second direction, and both the first direction and the second direction are substantially parallel to the touch display screen. 5. The computer-implemented method as defined in claim 1 further comprising receiving a plurality of judgments regarding the item from a plurality of other users, the plurality of judgments comprising, for each user in the plurality of other users, a user judgment regarding the item, wherein the user judgment regarding the item comprises a user-specific first directional value and a user-specific second directional value representing a judgment of that item by that user. 6. The computer-implemented method as defined in claim 5 further comprising displaying, on the touch display screen, a plurality of other user designators wherein
the plurality of other user designators comprises, for each user in the plurality of other users, a corresponding other user designator, and
each other user designator being displayed, on the touch display screen, at an associated location based on the user-specific first directional value and the user-specific second directional value of the user judgment. 7. The computer-implemented method as defined in claim 6 wherein the displaying, on the touch display screen, the plurality of other user designators overlaps in time with the displaying the item on the touch display screen. 8. The computer-implemented method as defined in claim 6, wherein for each user in the plurality of other users, a corresponding user identifier is displayed in the corresponding other user designator displayed on the touch display screen, such that the other user is identifiable by the user from the corresponding other user designator. 9. The computer-implemented method as defined in claim 1 wherein
displaying the item on the touch display screen comprises displaying the item on a plurality of touch display screens controlled by a plurality of different users, each touch display screen being operable to detect a user contact with the touch display screen;
defining, with respect to the touch display screen, the first direction of the touch display screen and the second direction of the touch display screen comprises defining, for each touch display screen in the plurality of touch display screens, the first direction and the second direction such that the user contact with that touch display screen indicates both the first directional value along the first direction, and the second directional value along the second direction;
detecting the user contact with the touch display screen when the touch display screen is displaying of the item comprises determining, for each touch display screen in the plurality of touch display screens the user contact with the touch display screen when that touch display screen is displaying the item; then
for each touch display screen in the plurality of touch display screens, determining the first directional value and the second directional value of the user contact;
the method further comprises defining a plurality of user groups in relation to the item, each user group in the plurality of user groups having an associated predefined range for the first directional value and the second directional value, and operating the processor to initiate the response to the user contact comprises, for each user in the plurality of users, assigning that user to a corresponding group in the plurality of user groups based on the first directional value and the second directional value of that user falling within the pre-defined range for that group, and then initiating a different response for users in different groups. 10. The computer-implemented method as defined in claim 1 wherein the user contact with the touch display screen defines a vector on the touch display screen, the first directional value being a component of the vector along the first direction of the touch display screen, and the second directional value being a component of the vector along the second direction of the touch display screen. 11. The computer implemented method as defined in claim 10 wherein the user contact is a swiping motion wherein the user moves the user contact along the screen to define the vector. 12. The computer-implemented method as defined in claim 1 further comprising,
when displaying the item on the touch display screen, measuring a variable biometric characteristic of the user; and
communicating the variable biometric characteristic of the user to the processor and then determining the response based on the variable biometric characteristic in addition to the first directional value, the second directional value and the item. 13. The computer-implemented method as defined in claim 1 wherein
displaying the item on the touch display screen comprises providing a stack comprising a sequence of items for display on the touch display screen such that each image, when displayed, displays a corresponding item on the touch display screen;
detecting the user contact with the touch display screen comprises detecting a sequence of user contacts corresponding to the sequence of items;
determining the first directional value and the second directional value of the user contact comprises determining a corresponding first directional value and a corresponding second directional value for each user contact in the sequence of user contacts; and,
the method further comprises after detecting at the first directional value and the second directional value of the user contact in relation to the corresponding item for each image in the sequence of items except for a last item in the sequence of items, automatically displaying the next item in the sequence of items. 14. The computer-implemented method as defined in claim 13 wherein operating the processor to initiate the response to the user contact comprises operating the processor to initiate a corresponding response for each user contact in the plurality of user contacts. 15. The computer-implemented method as defined in claim 14 further comprising,
determining a sequence of biometric measurements corresponding to the sequence of items by, when displaying each item in the sequence of items on the touch display screen, measuring a corresponding variable biometric characteristic of the user; and
for each corresponding variable biometric characteristic of the user,
communicating the variable biometric characteristic of the user to the processor and then determining the response based on the variable biometric characteristic in addition to the first directional value, the second directional value and the item. 16. The computer-implemented method as defined claim 1 wherein determining the response comprises determining a data entry for the displayed item based on the first directional value, the second directional value and the item;
and wherein the method further comprises storing the data entry, the stored data entry being associated with an identifier data entry for the user and indicating an identifier of the displayed item, the first directional value and the second directional value. 17. The computer-implemented method as defined claim 2 wherein determining the message comprises determining a set of sub-options based on the first directional value and the second directional value; and
wherein sending the message to the user comprises displaying on the touch display screen a set of user-selectable items, each user-selectable item corresponding to a unique one of the set of sub-options; and
wherein the method further comprises detecting at least one further user contact with the touch display screen corresponding to selecting at least one of the user-selectable items. 18. The computer-implemented method as defined claim 1 wherein the touch display screen comprises a first pair of opposing sides and a second pair of opposing sides being substantially orthogonal to the first pair of opposing sides;
wherein determining the first directional value is a positive binary value when the user contact is detected inside a region defined within a predetermined distance of one of the first pair of opposing sides;
wherein determining the first directional value is a negative binary value when the user contact is detected inside a region defined within a predetermined distance of the other of the first pair of opposing sides; and
wherein determining the second directional value as a magnitude value based on a distance of the user contact from a given one of the second pair of opposing sides. 19. The computer implemented method as defined claim 18 wherein the first pair of opposing sides are opposing long sides of the touch display screen and the second pair of opposing sides are opposing short sides of the touch display screen. 20. The computer-implemented method as defined claim 1 wherein the user contact comprises a continuous contact of the user with the touch display screen, wherein the first directional value and the second directional value of the user contact are determined from a current location of the contact with the touch display screen;
wherein determining a response comprises determining a feedback indicator representing the current location; and
the method further comprises providing the feedback indicator via a user device of the touch display screen. 21. The computer-implemented method as defined claim 20, wherein the feedback indicator is a visual indicator displayed on the touch display screen, the method further comprising:
adjusting a first visual characteristic of the displayed visual indicator based on a change in the first directional value; and adjusting a second visual characteristics of the displayed visual indicator based on a change in the second directional value. 22. A system for receiving feedback from a user, the system comprising:
a memory for storing a plurality of instructions; a processor coupled to the memory, the processor configured for:
displaying an item on a touch display screen, the touch display screen being operable to detect a user contact with the touch display screen;
defining, with respect to the touch display screen, a first direction of the touch display screen and a second direction of the touch display screen such that the user contact with the touch display screen indicates both a first directional value in the first direction, and a second directional value in the second direction; then
detecting the user contact with the touch display screen when the touch display screen is displaying of the item;
determining the first directional value and the second directional value of the user contact; and
determining a response to the user contact based on the first directional value, the second directional value and the item. 23. A tangible computer-readable medium including computer executable instructions, which, when executed on a computing device using a processor of the computing device, cause the computing device to carry out the steps of:
displaying an item on a touch display screen of the computing device, the touch display screen being operable to detect a user contact with the touch display screen; defining, with respect to the touch display screen, a first direction of the touch display screen and a second direction of the touch display screen such that the user contact with the touch display screen indicates both a first directional value in the first direction, and a second directional value in the second direction; then detecting the user contact with the touch display screen when the touch display screen is displaying of the item; determining the first directional value and the second directional value of the user contact; and, determining a response to the user contact based on the first directional value, the second directional value and the item. | A method, system, and recorded instructions are provided for displaying an item on a touch display screen of the computing device, the touch display screen being operable to detect a user contact with the touch display screen; defining, with respect to the touch display screen, a first direction of the touch display screen and a second direction of the touch display screen such that the user contact with the touch display screen indicates both a first directional value in the first direction, and a second directional value in the second direction; then detecting the user contact with the touch display screen when the touch display screen is displaying of the item; determining the first directional value and the second directional value of the user contact; and, determining a response to the user contact based on the first directional value, the second directional value and the item.1. A computer-implemented method of receiving feedback from a user, the method comprising:
displaying an item on a touch display screen, the touch display screen being operable to detect a user contact with the touch display screen; defining, with respect to the touch display screen, a first direction of the touch display screen and a second direction of the touch display screen such that the user contact with the touch display screen indicates both a first directional value in the first direction, and a second directional value in the second direction; then detecting the user contact with the touch display screen when the touch display screen is displaying of the item; determining the first directional value and the second directional value of the user contact; and, determining a response to the user contact based on the first directional value, the second directional value and the item. 2. The computer implemented method as defined in claim 1 wherein determining the response comprises determining a message based on the first directional value, the second directional value and the item and then sending the message to the user. 3. The computer implemented method as defined in claim 1 wherein determining the response comprises
determining a category comprising the at least one item;
recording a binary value for the user vis-à-vis that category in a memory, the binary value being positive, indicating the user likes the item, or negative, indicating the user dislikes the item, and being determined from the first directional value;
when the binary value for the user is positive, recording a magnitude of a positive value, the magnitude being determined from the second directional value;
when the binary value for the user is positive, sending a message to the user wherein the message differs depending on the magnitude of the positive value. 4. The computer-implemented method as defined in claim 1 wherein the touch display screen is substantially planar, and defining, with respect to the touch display screen, the first direction of the touch display screen and the second direction of the touch display screen comprises defining a substantially Cartesian coordinate system wherein the first direction is substantially orthogonal to the second direction, and both the first direction and the second direction are substantially parallel to the touch display screen. 5. The computer-implemented method as defined in claim 1 further comprising receiving a plurality of judgments regarding the item from a plurality of other users, the plurality of judgments comprising, for each user in the plurality of other users, a user judgment regarding the item, wherein the user judgment regarding the item comprises a user-specific first directional value and a user-specific second directional value representing a judgment of that item by that user. 6. The computer-implemented method as defined in claim 5 further comprising displaying, on the touch display screen, a plurality of other user designators wherein
the plurality of other user designators comprises, for each user in the plurality of other users, a corresponding other user designator, and
each other user designator being displayed, on the touch display screen, at an associated location based on the user-specific first directional value and the user-specific second directional value of the user judgment. 7. The computer-implemented method as defined in claim 6 wherein the displaying, on the touch display screen, the plurality of other user designators overlaps in time with the displaying the item on the touch display screen. 8. The computer-implemented method as defined in claim 6, wherein for each user in the plurality of other users, a corresponding user identifier is displayed in the corresponding other user designator displayed on the touch display screen, such that the other user is identifiable by the user from the corresponding other user designator. 9. The computer-implemented method as defined in claim 1 wherein
displaying the item on the touch display screen comprises displaying the item on a plurality of touch display screens controlled by a plurality of different users, each touch display screen being operable to detect a user contact with the touch display screen;
defining, with respect to the touch display screen, the first direction of the touch display screen and the second direction of the touch display screen comprises defining, for each touch display screen in the plurality of touch display screens, the first direction and the second direction such that the user contact with that touch display screen indicates both the first directional value along the first direction, and the second directional value along the second direction;
detecting the user contact with the touch display screen when the touch display screen is displaying of the item comprises determining, for each touch display screen in the plurality of touch display screens the user contact with the touch display screen when that touch display screen is displaying the item; then
for each touch display screen in the plurality of touch display screens, determining the first directional value and the second directional value of the user contact;
the method further comprises defining a plurality of user groups in relation to the item, each user group in the plurality of user groups having an associated predefined range for the first directional value and the second directional value, and operating the processor to initiate the response to the user contact comprises, for each user in the plurality of users, assigning that user to a corresponding group in the plurality of user groups based on the first directional value and the second directional value of that user falling within the pre-defined range for that group, and then initiating a different response for users in different groups. 10. The computer-implemented method as defined in claim 1 wherein the user contact with the touch display screen defines a vector on the touch display screen, the first directional value being a component of the vector along the first direction of the touch display screen, and the second directional value being a component of the vector along the second direction of the touch display screen. 11. The computer implemented method as defined in claim 10 wherein the user contact is a swiping motion wherein the user moves the user contact along the screen to define the vector. 12. The computer-implemented method as defined in claim 1 further comprising,
when displaying the item on the touch display screen, measuring a variable biometric characteristic of the user; and
communicating the variable biometric characteristic of the user to the processor and then determining the response based on the variable biometric characteristic in addition to the first directional value, the second directional value and the item. 13. The computer-implemented method as defined in claim 1 wherein
displaying the item on the touch display screen comprises providing a stack comprising a sequence of items for display on the touch display screen such that each image, when displayed, displays a corresponding item on the touch display screen;
detecting the user contact with the touch display screen comprises detecting a sequence of user contacts corresponding to the sequence of items;
determining the first directional value and the second directional value of the user contact comprises determining a corresponding first directional value and a corresponding second directional value for each user contact in the sequence of user contacts; and,
the method further comprises after detecting at the first directional value and the second directional value of the user contact in relation to the corresponding item for each image in the sequence of items except for a last item in the sequence of items, automatically displaying the next item in the sequence of items. 14. The computer-implemented method as defined in claim 13 wherein operating the processor to initiate the response to the user contact comprises operating the processor to initiate a corresponding response for each user contact in the plurality of user contacts. 15. The computer-implemented method as defined in claim 14 further comprising,
determining a sequence of biometric measurements corresponding to the sequence of items by, when displaying each item in the sequence of items on the touch display screen, measuring a corresponding variable biometric characteristic of the user; and
for each corresponding variable biometric characteristic of the user,
communicating the variable biometric characteristic of the user to the processor and then determining the response based on the variable biometric characteristic in addition to the first directional value, the second directional value and the item. 16. The computer-implemented method as defined claim 1 wherein determining the response comprises determining a data entry for the displayed item based on the first directional value, the second directional value and the item;
and wherein the method further comprises storing the data entry, the stored data entry being associated with an identifier data entry for the user and indicating an identifier of the displayed item, the first directional value and the second directional value. 17. The computer-implemented method as defined claim 2 wherein determining the message comprises determining a set of sub-options based on the first directional value and the second directional value; and
wherein sending the message to the user comprises displaying on the touch display screen a set of user-selectable items, each user-selectable item corresponding to a unique one of the set of sub-options; and
wherein the method further comprises detecting at least one further user contact with the touch display screen corresponding to selecting at least one of the user-selectable items. 18. The computer-implemented method as defined claim 1 wherein the touch display screen comprises a first pair of opposing sides and a second pair of opposing sides being substantially orthogonal to the first pair of opposing sides;
wherein determining the first directional value is a positive binary value when the user contact is detected inside a region defined within a predetermined distance of one of the first pair of opposing sides;
wherein determining the first directional value is a negative binary value when the user contact is detected inside a region defined within a predetermined distance of the other of the first pair of opposing sides; and
wherein determining the second directional value as a magnitude value based on a distance of the user contact from a given one of the second pair of opposing sides. 19. The computer implemented method as defined claim 18 wherein the first pair of opposing sides are opposing long sides of the touch display screen and the second pair of opposing sides are opposing short sides of the touch display screen. 20. The computer-implemented method as defined claim 1 wherein the user contact comprises a continuous contact of the user with the touch display screen, wherein the first directional value and the second directional value of the user contact are determined from a current location of the contact with the touch display screen;
wherein determining a response comprises determining a feedback indicator representing the current location; and
the method further comprises providing the feedback indicator via a user device of the touch display screen. 21. The computer-implemented method as defined claim 20, wherein the feedback indicator is a visual indicator displayed on the touch display screen, the method further comprising:
adjusting a first visual characteristic of the displayed visual indicator based on a change in the first directional value; and adjusting a second visual characteristics of the displayed visual indicator based on a change in the second directional value. 22. A system for receiving feedback from a user, the system comprising:
a memory for storing a plurality of instructions; a processor coupled to the memory, the processor configured for:
displaying an item on a touch display screen, the touch display screen being operable to detect a user contact with the touch display screen;
defining, with respect to the touch display screen, a first direction of the touch display screen and a second direction of the touch display screen such that the user contact with the touch display screen indicates both a first directional value in the first direction, and a second directional value in the second direction; then
detecting the user contact with the touch display screen when the touch display screen is displaying of the item;
determining the first directional value and the second directional value of the user contact; and
determining a response to the user contact based on the first directional value, the second directional value and the item. 23. A tangible computer-readable medium including computer executable instructions, which, when executed on a computing device using a processor of the computing device, cause the computing device to carry out the steps of:
displaying an item on a touch display screen of the computing device, the touch display screen being operable to detect a user contact with the touch display screen; defining, with respect to the touch display screen, a first direction of the touch display screen and a second direction of the touch display screen such that the user contact with the touch display screen indicates both a first directional value in the first direction, and a second directional value in the second direction; then detecting the user contact with the touch display screen when the touch display screen is displaying of the item; determining the first directional value and the second directional value of the user contact; and, determining a response to the user contact based on the first directional value, the second directional value and the item. | 2,100 |
6,065 | 6,065 | 14,872,004 | 2,157 | A computer-implemented method is provided for managing and sharing picture files. In one embodiment of the present invention, the method comprises providing a server platform and providing a datastore on the server platform for maintaining full resolution copies of the files shared between a plurality of sharing clients. A synchronization engine is provided on the server platform and is configured to send real-time updates to a plurality of sharing clients when at least one of the sharing clients updates or changes one of said files. A web interface may also be provided that allows a user to access files in the datastore through the use of a web browser. | 1-20. (canceled) 21. A method for updating metadata on a synchronization server, the method comprising:
establishing, at the synchronization server, a connection with a client device; and upon establishing the connection, receiving, from the client device, at the synchronization server, a notification of an update to metadata associated with a data object, the update to the metadata occurring prior to the establishing of the connection with the client device and while disconnected from the client device; and receiving, at the synchronization server, a copy of the updated metadata from the client device. 22. The method of claim 21, further comprising maintaining a continuous connection with the client device. 23. The method of claim 22, further comprising receiving, through the continuous connection, update notifications in real time. 24. The method of claim 21, further comprising determining whether an update to the metadata has occurred. 25. The method of claim 24, wherein the determination is based on a time of last update. 26. The method of claim 24, wherein the determination is based on a sequence number scheme. 27. The method of claim 21, further comprising:
disconnecting from the client device; re-establishing a connection to the client device; and upon re-establishing the connection, receiving notification of another update to the metadata at the client device that occurred during the disconnection. 28. A non-transitory computer-readable medium in a synchronization server for updating metadata, comprising:
code for establishing a connection with a client device; and code for receiving, upon establishing the connection, a notification of an update to metadata associated with a data object, the update to the metadata occurring prior to the establishing of the connection with the client device and while disconnected from the client device; and code for receiving a copy of the updated metadata from the client device. 29. The computer-readable medium of claim 28, further comprising code for maintaining a continuous connection with the client device. 30. The computer-readable medium of claim 29, further comprising code for receiving, through the continuous connection, update notifications in real time. 31. The computer-readable medium of claim 28, further comprising code for determining whether an update to the metadata has occurred. 32. The computer-readable medium of claim 31, wherein the determination is based on a time of last update. 33. The computer-readable medium of claim 31, wherein the determination is based on a sequence number scheme. 34. The computer-readable medium of claim 28, further comprising:
code for disconnecting from the client device; code for re-establishing a connection to the client device; and code for receiving notification of another update to the metadata at the client device that occurred during the disconnection upon re-establishing the connection. 35. A synchronization server configured to:
establish a connection with a client device; and receive, upon establishing the connection, a notification of an update to metadata associated with a data object, the update to the metadata occurring prior to the establishing of the connection with the client device and while disconnected from the client device; and receive a copy of the updated metadata from the client device. 36. The server of claim 35, further configured to maintain a continuous connection with the client device. 37. The server of claim 36, further configured to receive, through the continuous connection, update notifications in real time. 38. The server of claim 35, further configured to determine whether an update to the metadata has occurred. 39. The server of claim 38, wherein the determination is based on a time of last update. 40. The server of claim 38, wherein the determination is based on a sequence number scheme. | A computer-implemented method is provided for managing and sharing picture files. In one embodiment of the present invention, the method comprises providing a server platform and providing a datastore on the server platform for maintaining full resolution copies of the files shared between a plurality of sharing clients. A synchronization engine is provided on the server platform and is configured to send real-time updates to a plurality of sharing clients when at least one of the sharing clients updates or changes one of said files. A web interface may also be provided that allows a user to access files in the datastore through the use of a web browser.1-20. (canceled) 21. A method for updating metadata on a synchronization server, the method comprising:
establishing, at the synchronization server, a connection with a client device; and upon establishing the connection, receiving, from the client device, at the synchronization server, a notification of an update to metadata associated with a data object, the update to the metadata occurring prior to the establishing of the connection with the client device and while disconnected from the client device; and receiving, at the synchronization server, a copy of the updated metadata from the client device. 22. The method of claim 21, further comprising maintaining a continuous connection with the client device. 23. The method of claim 22, further comprising receiving, through the continuous connection, update notifications in real time. 24. The method of claim 21, further comprising determining whether an update to the metadata has occurred. 25. The method of claim 24, wherein the determination is based on a time of last update. 26. The method of claim 24, wherein the determination is based on a sequence number scheme. 27. The method of claim 21, further comprising:
disconnecting from the client device; re-establishing a connection to the client device; and upon re-establishing the connection, receiving notification of another update to the metadata at the client device that occurred during the disconnection. 28. A non-transitory computer-readable medium in a synchronization server for updating metadata, comprising:
code for establishing a connection with a client device; and code for receiving, upon establishing the connection, a notification of an update to metadata associated with a data object, the update to the metadata occurring prior to the establishing of the connection with the client device and while disconnected from the client device; and code for receiving a copy of the updated metadata from the client device. 29. The computer-readable medium of claim 28, further comprising code for maintaining a continuous connection with the client device. 30. The computer-readable medium of claim 29, further comprising code for receiving, through the continuous connection, update notifications in real time. 31. The computer-readable medium of claim 28, further comprising code for determining whether an update to the metadata has occurred. 32. The computer-readable medium of claim 31, wherein the determination is based on a time of last update. 33. The computer-readable medium of claim 31, wherein the determination is based on a sequence number scheme. 34. The computer-readable medium of claim 28, further comprising:
code for disconnecting from the client device; code for re-establishing a connection to the client device; and code for receiving notification of another update to the metadata at the client device that occurred during the disconnection upon re-establishing the connection. 35. A synchronization server configured to:
establish a connection with a client device; and receive, upon establishing the connection, a notification of an update to metadata associated with a data object, the update to the metadata occurring prior to the establishing of the connection with the client device and while disconnected from the client device; and receive a copy of the updated metadata from the client device. 36. The server of claim 35, further configured to maintain a continuous connection with the client device. 37. The server of claim 36, further configured to receive, through the continuous connection, update notifications in real time. 38. The server of claim 35, further configured to determine whether an update to the metadata has occurred. 39. The server of claim 38, wherein the determination is based on a time of last update. 40. The server of claim 38, wherein the determination is based on a sequence number scheme. | 2,100 |
6,066 | 6,066 | 13,797,128 | 2,168 | Row locking is performed at the row level of granularity for database data stored in columnar form. Row level locking entails use of a lock vector that is stored in a compression unit in a data block, the compression unit storing rows in columnar-major format. On an as needed basis, the lock vector is expanded to identify more transactions affecting the rows in the compression unit. | 1. A method comprising steps of:
storing a plurality of rows in a plurality of data blocks in column-major format; and locking said plurality of rows at a row-level of granularity, wherein locking said plurality of rows at a row-level of granularity includes:
a first transaction obtaining a lock on a first row having at least one column value of a column in a particular data block of said plurality of data blocks; and
while said first transaction holds said lock on said first row, a second transaction obtaining a lock on a second row having at least one column value of said column in said particular data block. 2. The method of claim 1, wherein each data block of said plurality of data blocks contains a compression unit that contains a subset of said plurality of rows, wherein a compression unit contained in said particular data block contains said first row and said second row. 3. The method of claim 1, wherein each data block of said plurality of data blocks is associated with a limit on a number of transactions that can concurrently hold a lock on a row in said each data block, wherein the limit associated with a first data block of said plurality of data blocks is different than a limit associated with a second data block of said plurality of data blocks. 4. The method of claim 3, further including: for another data block of said plurality of data blocks, increasing the limit associated with said another data block. 5. The method of claim 1, while said first transaction holds said lock on said first row, locking multiple rows of another data block of said plurality of data blocks at a level of granularity higher than said row level of granularity. 6. A method comprising steps of:
storing a plurality of rows in a plurality of data blocks in column-major format, wherein each data block of said plurality of data blocks includes a variable lock vector that is used to identify one or more transactions having a lock on a row in said each data block; and locking a plurality of rows at a row-level of granularity within a particular data block of said plurality of data blocks, said particular data block containing a particular variable lock vector, wherein locking said plurality of rows at a row-level of granularity includes:
setting a first sequence of bits in said variable lock vector to a first value to lock a first row in said particular data block for a first transaction; and
while said first transaction holds said lock on said first row, setting a second sequence of bits in said variable lock vector to a second value to lock a second row in said data block for a second transaction. 7. The method of claim 6, wherein each data block of said plurality of data blocks contains a compression unit that contains a subset of said plurality of rows, wherein said particular data block contains said first row and said second row. 8. The method of claim 6, further including while said first transaction holds said lock on said first row, increasing the size of the variable lock vector in said particular data block to lock a third row in said particular data block for a third transaction. 9. The method of claim 6, after increasing the size of said variable lock vector in said particular data block, decreasing the size of said variable lock vector in said particular data block. 10. The method of claim 6, receiving one or more database commands that indicate a minimum size of a variable lock vector. 11. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of steps:
storing a plurality of rows in a plurality of data blocks in column-major format; locking said plurality of rows at a row-level of granularity, wherein locking said plurality of rows at a row-level of granularity includes:
a first transaction obtaining a lock on a first row having at least one column value of a column in a particular data block of said plurality of data blocks; and
while said first transaction holds said lock on said first row, a second transaction obtaining a lock on a second row having at least one column value of said column in said particular data block. 12. The one or more non-transitory storage media of claim 11, wherein each data block of said plurality of data blocks contains a compression unit that contains a subset of said plurality of rows, wherein a compression unit contained in said particular data block contains said first row and said second row. 13. The one or more non-transitory storage media of claim 11, wherein each data block of said plurality of data blocks is associated with a limit on a number of transactions that can concurrently hold a lock on a row in said each data block, wherein the limit associated with a first data block of said plurality of data blocks is different than a limit associated with a second data block of said plurality of data blocks. 14. The one or more non-transitory storage media of claim 13, further including: for another data block of said plurality of data blocks, increasing the limit associated with said another data block. 15. The one or more non-transitory storage media of claim 11, while said first transaction holds said lock on said first row, locking multiple rows of another data block of said plurality of data blocks at a level of granularity higher than said row level of granularity. 16. One or more non-transitory storage media comprising steps of:
storing a plurality of rows in a plurality of data blocks in column-major format, wherein each data block of said plurality of data blocks includes a variable lock vector that is used to identify one or more transactions having a lock on a row in said each data block; and locking a plurality of rows at a row-level of granularity within a particular data block of said plurality of data blocks, said particular data block containing a particular variable lock vector, wherein locking said plurality of rows at a row-level of granularity includes:
setting said a first sequence of bits in said variable lock vector to a first value to lock a first row in said particular data block for a first transaction; and
while said first transaction holds said lock on said first row, setting a second sequence of bits in said variable lock vector to a second value to lock a second row in said data block for a second transaction. 17. The one or more non-transitory storage media of claim 16, wherein each data block of said plurality of data blocks contains a compression unit that contains a subset of said plurality of rows, wherein said particular data block contains said first row and said second row. 18. The one or more non-transitory storage media of claim 16, further including while said first transaction holds said lock on said first row, increasing the size of the variable lock vector in said particular data block to lock a third row in said particular data block for a third transaction. 19. The one or more non-transitory storage media of claim 16, after increasing the size of said variable lock vector in said particular data block, decreasing the size of said variable lock vector in said particular data block. 20. The one or more non-transitory storage media of claim 16, receiving one or more database commands that indicate a minimum size of a variable lock vector. | Row locking is performed at the row level of granularity for database data stored in columnar form. Row level locking entails use of a lock vector that is stored in a compression unit in a data block, the compression unit storing rows in columnar-major format. On an as needed basis, the lock vector is expanded to identify more transactions affecting the rows in the compression unit.1. A method comprising steps of:
storing a plurality of rows in a plurality of data blocks in column-major format; and locking said plurality of rows at a row-level of granularity, wherein locking said plurality of rows at a row-level of granularity includes:
a first transaction obtaining a lock on a first row having at least one column value of a column in a particular data block of said plurality of data blocks; and
while said first transaction holds said lock on said first row, a second transaction obtaining a lock on a second row having at least one column value of said column in said particular data block. 2. The method of claim 1, wherein each data block of said plurality of data blocks contains a compression unit that contains a subset of said plurality of rows, wherein a compression unit contained in said particular data block contains said first row and said second row. 3. The method of claim 1, wherein each data block of said plurality of data blocks is associated with a limit on a number of transactions that can concurrently hold a lock on a row in said each data block, wherein the limit associated with a first data block of said plurality of data blocks is different than a limit associated with a second data block of said plurality of data blocks. 4. The method of claim 3, further including: for another data block of said plurality of data blocks, increasing the limit associated with said another data block. 5. The method of claim 1, while said first transaction holds said lock on said first row, locking multiple rows of another data block of said plurality of data blocks at a level of granularity higher than said row level of granularity. 6. A method comprising steps of:
storing a plurality of rows in a plurality of data blocks in column-major format, wherein each data block of said plurality of data blocks includes a variable lock vector that is used to identify one or more transactions having a lock on a row in said each data block; and locking a plurality of rows at a row-level of granularity within a particular data block of said plurality of data blocks, said particular data block containing a particular variable lock vector, wherein locking said plurality of rows at a row-level of granularity includes:
setting a first sequence of bits in said variable lock vector to a first value to lock a first row in said particular data block for a first transaction; and
while said first transaction holds said lock on said first row, setting a second sequence of bits in said variable lock vector to a second value to lock a second row in said data block for a second transaction. 7. The method of claim 6, wherein each data block of said plurality of data blocks contains a compression unit that contains a subset of said plurality of rows, wherein said particular data block contains said first row and said second row. 8. The method of claim 6, further including while said first transaction holds said lock on said first row, increasing the size of the variable lock vector in said particular data block to lock a third row in said particular data block for a third transaction. 9. The method of claim 6, after increasing the size of said variable lock vector in said particular data block, decreasing the size of said variable lock vector in said particular data block. 10. The method of claim 6, receiving one or more database commands that indicate a minimum size of a variable lock vector. 11. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of steps:
storing a plurality of rows in a plurality of data blocks in column-major format; locking said plurality of rows at a row-level of granularity, wherein locking said plurality of rows at a row-level of granularity includes:
a first transaction obtaining a lock on a first row having at least one column value of a column in a particular data block of said plurality of data blocks; and
while said first transaction holds said lock on said first row, a second transaction obtaining a lock on a second row having at least one column value of said column in said particular data block. 12. The one or more non-transitory storage media of claim 11, wherein each data block of said plurality of data blocks contains a compression unit that contains a subset of said plurality of rows, wherein a compression unit contained in said particular data block contains said first row and said second row. 13. The one or more non-transitory storage media of claim 11, wherein each data block of said plurality of data blocks is associated with a limit on a number of transactions that can concurrently hold a lock on a row in said each data block, wherein the limit associated with a first data block of said plurality of data blocks is different than a limit associated with a second data block of said plurality of data blocks. 14. The one or more non-transitory storage media of claim 13, further including: for another data block of said plurality of data blocks, increasing the limit associated with said another data block. 15. The one or more non-transitory storage media of claim 11, while said first transaction holds said lock on said first row, locking multiple rows of another data block of said plurality of data blocks at a level of granularity higher than said row level of granularity. 16. One or more non-transitory storage media comprising steps of:
storing a plurality of rows in a plurality of data blocks in column-major format, wherein each data block of said plurality of data blocks includes a variable lock vector that is used to identify one or more transactions having a lock on a row in said each data block; and locking a plurality of rows at a row-level of granularity within a particular data block of said plurality of data blocks, said particular data block containing a particular variable lock vector, wherein locking said plurality of rows at a row-level of granularity includes:
setting said a first sequence of bits in said variable lock vector to a first value to lock a first row in said particular data block for a first transaction; and
while said first transaction holds said lock on said first row, setting a second sequence of bits in said variable lock vector to a second value to lock a second row in said data block for a second transaction. 17. The one or more non-transitory storage media of claim 16, wherein each data block of said plurality of data blocks contains a compression unit that contains a subset of said plurality of rows, wherein said particular data block contains said first row and said second row. 18. The one or more non-transitory storage media of claim 16, further including while said first transaction holds said lock on said first row, increasing the size of the variable lock vector in said particular data block to lock a third row in said particular data block for a third transaction. 19. The one or more non-transitory storage media of claim 16, after increasing the size of said variable lock vector in said particular data block, decreasing the size of said variable lock vector in said particular data block. 20. The one or more non-transitory storage media of claim 16, receiving one or more database commands that indicate a minimum size of a variable lock vector. | 2,100 |
6,067 | 6,067 | 14,609,946 | 2,117 | In a building automation system, a method for automating a building includes a step of acquiring at least one data time history from a sensor or from a meter. The data time history is averaged and the averaged data time history is fitted into at least one occupancy pattern. The occupancy pattern covers a given time span. At least one set point is determined from the occupancy pattern and the at least one set point is fed into a system for heating, ventilation, and/or air-conditioning. In the novel system the at least one data time history is acquired from an element of standard infrastructure. | 1. A method for automating a building having a standard infrastructure, the method comprising:
acquiring at least one data time history from at least one input device being a part of the standard infrastructure; averaging the at least one data time history to form an averaged data time history; arranging the at least one averaged data time history into at least one occupancy pattern, the occupancy pattern covering a given time span; determining at least one set point from said at least one occupancy pattern of the building or of a part thereof; and feeding the at least one set point into a system for heating, ventilation, or air-conditioning. 2. The method for automating a building according to claim 1, which comprises acquiring the at least one data time history from one or more devices selected from the group consisting of a meter, a sensor, a switch, and an Internet gateway. 3. The method for automating a building according to claim 1, which comprises acquiring the at least one data time history from one or more devices selected from the group consisting of an electricity meter, a water meter, a smart electricity meter, an Internet router, a WiFi router, a networked device, a temperature sensor, a humidity sensor, and a light sensor. 4. The method for automating a building according to claim 1, which comprises acquiring a plurality of data time histories. 5. The method for automating a building according to claim 1, which further comprises filtering automated processes out of the at least one data time history. 6. The method for automating a building according to claim 5, wherein the filtering step comprises employing principal component analysis, and/or wavelet analysis, and/or sensor fusion for filtering the automated processes out of the at least one data time history. 7. The method for automating a building according to claim 1, which further comprises enhancing the at least one occupancy pattern through typical behavior patterns. 8. The method for automating a building according to claim 7, wherein the enhancing step relies on a day-night pattern. 9. The method for automating a building according to claim 1, which further comprises a step of obtaining a finer level of granularity of the at least one set point through an algorithmic enhancement. 10. The method for automating a building according to claim 9, wherein the algorithmic enhancement raises or lowers the at least one set point. 11. The method for automating a building according to claim 1, which comprises determining a plurality of set points from the occupancy pattern. 12. The method for automating a building according to claim 1, wherein the at least one set point is a temperature value, or a humidity value, or a luminosity value, or a fan speed of a ventilation system, or a concentration of carbon dioxide, or a concentration of volatile organic compounds. 13. The method for automating a building according to claim 1, which further comprises feeding the at least one set point into a system for assisted living, a system for home safety, or a building automation system. 14. A non-transitory, tangible computer-readable medium having computer-executable instructions executable by a processor for performing the method according to claim 1 when the instructions are executed. 15. A building automation system, comprising:
an acquisition device for acquiring at least one data time history from at least one input device, the at least one input device being a part of standard infrastructure; a device connected to said acquisition device and configured to average the at least one data time history and to form at least one averaged data time history; a patterning device configured to arrange the at least one averaged data time history into at least one occupancy pattern of the building or of a part thereof, the at least one occupancy pattern covering a given time span; means for determining at least one set point from the occupancy pattern; and a device for feeding the at least one set point into a system for heating, ventilation, or air-conditioning. | In a building automation system, a method for automating a building includes a step of acquiring at least one data time history from a sensor or from a meter. The data time history is averaged and the averaged data time history is fitted into at least one occupancy pattern. The occupancy pattern covers a given time span. At least one set point is determined from the occupancy pattern and the at least one set point is fed into a system for heating, ventilation, and/or air-conditioning. In the novel system the at least one data time history is acquired from an element of standard infrastructure.1. A method for automating a building having a standard infrastructure, the method comprising:
acquiring at least one data time history from at least one input device being a part of the standard infrastructure; averaging the at least one data time history to form an averaged data time history; arranging the at least one averaged data time history into at least one occupancy pattern, the occupancy pattern covering a given time span; determining at least one set point from said at least one occupancy pattern of the building or of a part thereof; and feeding the at least one set point into a system for heating, ventilation, or air-conditioning. 2. The method for automating a building according to claim 1, which comprises acquiring the at least one data time history from one or more devices selected from the group consisting of a meter, a sensor, a switch, and an Internet gateway. 3. The method for automating a building according to claim 1, which comprises acquiring the at least one data time history from one or more devices selected from the group consisting of an electricity meter, a water meter, a smart electricity meter, an Internet router, a WiFi router, a networked device, a temperature sensor, a humidity sensor, and a light sensor. 4. The method for automating a building according to claim 1, which comprises acquiring a plurality of data time histories. 5. The method for automating a building according to claim 1, which further comprises filtering automated processes out of the at least one data time history. 6. The method for automating a building according to claim 5, wherein the filtering step comprises employing principal component analysis, and/or wavelet analysis, and/or sensor fusion for filtering the automated processes out of the at least one data time history. 7. The method for automating a building according to claim 1, which further comprises enhancing the at least one occupancy pattern through typical behavior patterns. 8. The method for automating a building according to claim 7, wherein the enhancing step relies on a day-night pattern. 9. The method for automating a building according to claim 1, which further comprises a step of obtaining a finer level of granularity of the at least one set point through an algorithmic enhancement. 10. The method for automating a building according to claim 9, wherein the algorithmic enhancement raises or lowers the at least one set point. 11. The method for automating a building according to claim 1, which comprises determining a plurality of set points from the occupancy pattern. 12. The method for automating a building according to claim 1, wherein the at least one set point is a temperature value, or a humidity value, or a luminosity value, or a fan speed of a ventilation system, or a concentration of carbon dioxide, or a concentration of volatile organic compounds. 13. The method for automating a building according to claim 1, which further comprises feeding the at least one set point into a system for assisted living, a system for home safety, or a building automation system. 14. A non-transitory, tangible computer-readable medium having computer-executable instructions executable by a processor for performing the method according to claim 1 when the instructions are executed. 15. A building automation system, comprising:
an acquisition device for acquiring at least one data time history from at least one input device, the at least one input device being a part of standard infrastructure; a device connected to said acquisition device and configured to average the at least one data time history and to form at least one averaged data time history; a patterning device configured to arrange the at least one averaged data time history into at least one occupancy pattern of the building or of a part thereof, the at least one occupancy pattern covering a given time span; means for determining at least one set point from the occupancy pattern; and a device for feeding the at least one set point into a system for heating, ventilation, or air-conditioning. | 2,100 |
6,068 | 6,068 | 13,454,271 | 2,169 | A method which on determination of an entity replacement request is configured to identify an optimized entity as a replacement based on a predefined set of metadata, wherein the metadata comprises a profile associated with the entity, wherein the profile of the entity is further based on a graph, such as a graphical representation of social links, associated with the entity; and provide the optimized entity as a replacement for the entity to be replaced. Other embodiments are also disclosed. | 1. A computer implemented method comprising:
on determination of an entity replacement request;
identifying, using a processor, an optimized entity as a replacement entity based on a predefined set of metadata, wherein the metadata comprises a profile associated with the entity, wherein the profile of the entity is further based on a graph associated with the entity;
providing the optimized entity as a replacement entity. 2. The method as claimed in claim 1, wherein the metadata further comprises a measurement profile associated with at least one of the entity or replacement entity. 3. The method as claimed in claim 1, wherein the entity and the replacement entity is a human resource. 4. The method as claimed in claim 1, wherein the graph comprises a representation of social links which further comprises a mapping between the entity and other entities. 5. The method as claimed in claim 4, wherein the graph comprises at least roles and activities associated between at least the entity and other entities. 6. The method as claimed in claim 4, wherein the mapping is a lookup table. 7. The method as claimed in claim 4, wherein the graph comprises at least one of a structured or unstructured data. 8. The method as claimed in claim 1, further comprises creating a ranked list of the replacement entity. 9. The method as claimed in claim 2, wherein the measurement profile is a psychometric profile includes measurement of at least of a knowledge, abilities, attitudes, personality traits, educational measurement and sentiment analysis of the entity. 10-23. (canceled) | A method which on determination of an entity replacement request is configured to identify an optimized entity as a replacement based on a predefined set of metadata, wherein the metadata comprises a profile associated with the entity, wherein the profile of the entity is further based on a graph, such as a graphical representation of social links, associated with the entity; and provide the optimized entity as a replacement for the entity to be replaced. Other embodiments are also disclosed.1. A computer implemented method comprising:
on determination of an entity replacement request;
identifying, using a processor, an optimized entity as a replacement entity based on a predefined set of metadata, wherein the metadata comprises a profile associated with the entity, wherein the profile of the entity is further based on a graph associated with the entity;
providing the optimized entity as a replacement entity. 2. The method as claimed in claim 1, wherein the metadata further comprises a measurement profile associated with at least one of the entity or replacement entity. 3. The method as claimed in claim 1, wherein the entity and the replacement entity is a human resource. 4. The method as claimed in claim 1, wherein the graph comprises a representation of social links which further comprises a mapping between the entity and other entities. 5. The method as claimed in claim 4, wherein the graph comprises at least roles and activities associated between at least the entity and other entities. 6. The method as claimed in claim 4, wherein the mapping is a lookup table. 7. The method as claimed in claim 4, wherein the graph comprises at least one of a structured or unstructured data. 8. The method as claimed in claim 1, further comprises creating a ranked list of the replacement entity. 9. The method as claimed in claim 2, wherein the measurement profile is a psychometric profile includes measurement of at least of a knowledge, abilities, attitudes, personality traits, educational measurement and sentiment analysis of the entity. 10-23. (canceled) | 2,100 |
6,069 | 6,069 | 15,492,575 | 2,164 | A translator component implements an interface that allows a plurality of software applications to access a data store. The interface can include methods for reading data from, or writing data to, the data store. The translator component can form requests to be sent to, and executed by, the data store. The requests can be formed based on the type of call and one or more arguments provided in the call. By using the translator component, the plurality of software applications do not need to implement functionality to directly access the data store, which can facilitate application development, as well as allowing a protocol used to access the data store to be updated or changed without impacting the software applications. | 1. One or more computer-readable media comprising computer-executable instructions that when executed cause a computing system to perform processing to process a call for data store services, the processing comprising:
receiving a call through an interface to access a data store, the call comprising one or more arguments; determining an operation associated with the call; retrieving a request template associated with the operation; generating a request, the generating comprising combining at least one of the one or more arguments with the request template; and sending the request to the data store. 2. The one or more computer-readable media of claim 1, wherein the request is specified in a web services data access protocol. 3. The one or more computer-readable media of claim 2, wherein the web services data access protocol is the OData protocol. 4. The one or more computer-readable media of claim 1, the processing further comprising:
receiving data from the data store in response to the request; mapping the data to a schema; and sending the mapped data is response to the call. 5. The one or more computer-readable media of claim 1, the processing further comprising:
extracting one or more values from an instance of an abstract data type provided as an argument of the call; and formatting the extracted one or more values for insertion in a database. 6. The one or more computer-readable media of claim 1, wherein the interface is specified in a web services protocol. 7. The one or more computer-readable media of claim 1, wherein the interface is implemented in the hypertext transfer protocol. 8. The one or more computer-readable media of claim 1, wherein the call is from a plurality of calls to the interface, the plurality of calls originating from a plurality of software applications. 9. The one or more computer-readable media of claim 1, wherein the call is from a plurality of calls to the interface, the plurality of calls originating from a plurality of computer devices. 10. The one or more computer-readable media of claim 1, the processing further comprising:
receiving data form the data store in response to the request; caching at least a portion of the data; and sending at least a portion of the data in response to the call. 11. The one or more computer-readable media of claim 1, wherein at least a portion of the request comprises operations specified in the structured query language. 12. The one or more computer-readable media of claim 1, wherein the call is associated with a user and the processing further comprises:
receiving user metadata; and storing the user metadata. 13. The one or more computer-readable media of claim 1, wherein the generating comprises generating a URI associated with the data store. 14. The one or more computer-readable media of claim 13, wherein the generating comprises generating an instruction body to be processed by the data store. 15. The one or more computer-readable media of claim 1, wherein the request is made to an interface provided by the data store. 16. The one or more computer-readable media of claim 1, wherein the data store is a remote data store as to a source of the call. 17. The one or more computer-readable media of claim 16, wherein the remote data store is coded to service data requests from a plurality of computer devices. 18. A system comprising:
memory; one or more hardware processors coupled to the memory; one or more computer-readable media storing instructions that, when loaded into the memory, cause the one or more hardware processors to perform operations for: implementing an interface for mediating access to a remote data store, the interface providing methods comprising a method to read data at the remote data store and at least one method to modify data at the remote data store; receiving calls from a plurality of applications to interface methods, at least a portion of the plurality of calls providing one or more arguments for a called method; constructing a request to be sent to the remote data store using at least one of the one or more arguments provided in a call of the plurality of calls, the request comprising a URI and a request body; and sending the request to the remote data store. 19. The system of claim 18, the operations further comprising:
receiving a response to the request from the remote data store; formatting data associated with the request response to be sent to the calling application; and sending the formatted data to the calling application. 20. A method implemented at least in part by a computing system, the method comprising:
receiving calls to an interface for facilitating access to a remote data store from a plurality of software applications executed on a plurality of different computer devices, each call being specified in a web services protocol and the interface providing a method to read data from the remote data store and at least one method to modify data at the remote data store; executing methods associated with the calls, wherein, for at least a portion of the calls, the executing comprises generating requests for database operations, the requests specified in a web services data access protocol, the requests having a URI and a request body, and comprising one or more arguments provided in a respective call; sending the requests to a web services interface of the remote data store; receiving execution results from the remote data store; and providing execution results to the calling applications. | A translator component implements an interface that allows a plurality of software applications to access a data store. The interface can include methods for reading data from, or writing data to, the data store. The translator component can form requests to be sent to, and executed by, the data store. The requests can be formed based on the type of call and one or more arguments provided in the call. By using the translator component, the plurality of software applications do not need to implement functionality to directly access the data store, which can facilitate application development, as well as allowing a protocol used to access the data store to be updated or changed without impacting the software applications.1. One or more computer-readable media comprising computer-executable instructions that when executed cause a computing system to perform processing to process a call for data store services, the processing comprising:
receiving a call through an interface to access a data store, the call comprising one or more arguments; determining an operation associated with the call; retrieving a request template associated with the operation; generating a request, the generating comprising combining at least one of the one or more arguments with the request template; and sending the request to the data store. 2. The one or more computer-readable media of claim 1, wherein the request is specified in a web services data access protocol. 3. The one or more computer-readable media of claim 2, wherein the web services data access protocol is the OData protocol. 4. The one or more computer-readable media of claim 1, the processing further comprising:
receiving data from the data store in response to the request; mapping the data to a schema; and sending the mapped data is response to the call. 5. The one or more computer-readable media of claim 1, the processing further comprising:
extracting one or more values from an instance of an abstract data type provided as an argument of the call; and formatting the extracted one or more values for insertion in a database. 6. The one or more computer-readable media of claim 1, wherein the interface is specified in a web services protocol. 7. The one or more computer-readable media of claim 1, wherein the interface is implemented in the hypertext transfer protocol. 8. The one or more computer-readable media of claim 1, wherein the call is from a plurality of calls to the interface, the plurality of calls originating from a plurality of software applications. 9. The one or more computer-readable media of claim 1, wherein the call is from a plurality of calls to the interface, the plurality of calls originating from a plurality of computer devices. 10. The one or more computer-readable media of claim 1, the processing further comprising:
receiving data form the data store in response to the request; caching at least a portion of the data; and sending at least a portion of the data in response to the call. 11. The one or more computer-readable media of claim 1, wherein at least a portion of the request comprises operations specified in the structured query language. 12. The one or more computer-readable media of claim 1, wherein the call is associated with a user and the processing further comprises:
receiving user metadata; and storing the user metadata. 13. The one or more computer-readable media of claim 1, wherein the generating comprises generating a URI associated with the data store. 14. The one or more computer-readable media of claim 13, wherein the generating comprises generating an instruction body to be processed by the data store. 15. The one or more computer-readable media of claim 1, wherein the request is made to an interface provided by the data store. 16. The one or more computer-readable media of claim 1, wherein the data store is a remote data store as to a source of the call. 17. The one or more computer-readable media of claim 16, wherein the remote data store is coded to service data requests from a plurality of computer devices. 18. A system comprising:
memory; one or more hardware processors coupled to the memory; one or more computer-readable media storing instructions that, when loaded into the memory, cause the one or more hardware processors to perform operations for: implementing an interface for mediating access to a remote data store, the interface providing methods comprising a method to read data at the remote data store and at least one method to modify data at the remote data store; receiving calls from a plurality of applications to interface methods, at least a portion of the plurality of calls providing one or more arguments for a called method; constructing a request to be sent to the remote data store using at least one of the one or more arguments provided in a call of the plurality of calls, the request comprising a URI and a request body; and sending the request to the remote data store. 19. The system of claim 18, the operations further comprising:
receiving a response to the request from the remote data store; formatting data associated with the request response to be sent to the calling application; and sending the formatted data to the calling application. 20. A method implemented at least in part by a computing system, the method comprising:
receiving calls to an interface for facilitating access to a remote data store from a plurality of software applications executed on a plurality of different computer devices, each call being specified in a web services protocol and the interface providing a method to read data from the remote data store and at least one method to modify data at the remote data store; executing methods associated with the calls, wherein, for at least a portion of the calls, the executing comprises generating requests for database operations, the requests specified in a web services data access protocol, the requests having a URI and a request body, and comprising one or more arguments provided in a respective call; sending the requests to a web services interface of the remote data store; receiving execution results from the remote data store; and providing execution results to the calling applications. | 2,100 |
6,070 | 6,070 | 15,165,015 | 2,198 | There is provided a method for combining datasets, comprising: receiving a primary training dataset; receiving unclassified secondary dataset(s) comprising secondary data instances including secondary fields; identifying, for a first set of values of primary field(s) of training dataset, a second set of secondary fields of the secondary datasets according to the first set of values matched to corresponding values in respective secondary field(s) of secondary dataset(s) according to a matching requirement; linking each respective matched values to other secondary fields of the respective matched secondary field; generating a set of classification features based at least on the linked secondary fields; selecting a subset of pivotal classification features according to a correlation requirement; identifying a subset of pivotal secondary fields based on the secondary fields associated with each pivotal classification feature; and documenting the selected subset of pivotal features for use in an automated machine learning process. | 1. A computer implemented method for combining datasets for use in an automated machine learning process, comprising:
receiving a designation of a primary training dataset comprising a plurality of primary data instances, each primary data instance including a plurality of primary fields each assigned at least one value, each primary data instance associated with a classification label; receiving a designation of at least one secondary dataset each comprising a plurality of secondary data instances, each secondary data instance including a plurality of secondary fields, each secondary data being unclassified; identifying, for a first set of values of at least one primary field of the plurality of primary fields, a second set of secondary fields of the at least one secondary datasets according to the first set of values matched to corresponding values in at least one respective secondary field of at least one secondary dataset according to a matching requirement; linking each respective matched value of the first set of values, to other secondary fields of at least one respective secondary data instance of the respective matched secondary field; generating a set of classification features based at least on the linked second set of secondary fields, each classification feature for application to at least one field from the linked second set of secondary data fields; applying each classification feature of the generated set of classification features to each linked second set of secondary fields to generate a set of extracted features; selecting a subset of pivotal classification features from the set of classification features according to a correlation requirement between the classification label of the primary data instance corresponding to the linked secondary field used in the respective classification feature, and each respective member of the set of extracted features extracted by the respective classification feature; identifying a subset of pivotal secondary fields based on the secondary fields associated with each selected pivotal classification feature; creating an enhanced training dataset by linking the subset of pivotal secondary fields to the primary training dataset; and documenting at least one of the selected subset of pivotal features and enhanced training dataset for use in an automated machine learning process. 2. The method of claim 1, further comprising iterating the method until a stop condition is met, by designating the enhanced training dataset, and repeating the identifying the second set of secondary fields, linking, generating, applying, selecting, identifying the subset of pivotal secondary fields, and the creating, using the designated enhanced training dataset. 3. The method of claim 1, wherein at least some of the features extracted from at least one secondary field are statistically insignificantly correlated with the classification label. 4. The method of claim 1, wherein the matching requirement includes a percentage of the first set of values of the respective primary field matching the corresponding values in the respective secondary dataset. 5. The method of claim 1, wherein the matching requirement comprises that the first set of values is selected by sampling a subset of values of the at least one primary field. 6. The method of claim 1, further comprising preparing, for each secondary dataset, a set-representation of the plurality of secondary fields, and using the set-representation to match the first set of value and to identify the second set. 7. The method of claim 1, wherein at least one member of the at least one secondary dataset is selected from the group consisting of: a table wherein each row represents a secondary data instance and each column represents a secondary field and a graph comprising linked data. 8. The method of claim 1, wherein at least one primary field includes a third set of data elements each assigned a value, and wherein identifying comprises identifying for the first set of values of a subset including at least one data element of the third set. 9. The method of claim 1, wherein generating the set of classification features comprises generating at least one binary classification feature that extracts a binary value from at least one of the linked secondary data fields. 10. The method of claim 9, wherein the at least one binary classification feature includes at least one mathematical condition applied to at least one value of the linked secondary data fields of other data instances. 11. The method of claim 10, wherein the at least one mathematical condition is selected from the group consisting of: greater than, less than, equal to, greater than or equal to, less than or equal to, and containing the at least one value. 12. The method of claim 1, further comprising automatically designating at least one secondary dataset based at least one object type of at least one secondary field that corresponds to at least one object type of the primary training dataset. 13. The method of claim 1, further comprising analyzing at least one primary data field to extract at least one entity according to at least one object type, and wherein identifying comprises identifying the second set of secondary fields according to the object type of the first set of values of the at least one extracted entity. 14. The method of claim 1, further comprising converting values in at least one of: the primary training dataset and the at least one secondary data set to a canonical representation, and performing the identifying based on the canonical representation. 15. The method of claim 1, further comprising training a statistical classifier based on the selected subset of pivotal features applied to the enhanced training dataset, and the associated data classification labels. 16. The method of claim 1, further comprising classifying a new data instance to at least one of the data classification labels, by applying each classification feature of the selected subset of pivotal features to the new data instance to extract a plurality of features and applying the statistical classifier to the plurality of extracted features to output at least one of the data classification labels. 17. A system to create an enhanced training dataset for use in an automated machine learning process, comprising:
a primary interface for communication with a first storage unit storing thereon a primary training dataset comprising a plurality of primary data instances, each primary data instance including a plurality of primary fields each assigned at least one value, each primary data instance associated with a classification label; a secondary interface for communication with at least one second storage unit storing thereon at least one secondary dataset each comprising a plurality of secondary data instances, each secondary data instance including a plurality of secondary fields, each secondary data being unclassified; a program store storing code; and a processor coupled to the primary interface, the secondary interface, and the program store for implementing the stored code, the code comprising: code to identify, for a first set of values of at least one primary field of the plurality of primary fields, a second set of secondary fields of the at least one secondary datasets according to the first set of values matched to corresponding values in at least one respective secondary field of at least one secondary dataset according to a matching requirement, to link each respective matched value of the first set of values, to other secondary fields of at least one respective secondary data instance of the respective matched secondary field, to generate a set of classification features based at least on the linked second set of secondary fields, each classification feature for application to at least one field from the linked second set of secondary data fields, to apply each classification feature of the generated set of classification features to each linked second set of secondary fields to generate a set of extracted features, to select a subset of pivotal classification features from the set of classification features according to a correlation requirement between the classification label of the primary data instance corresponding to the linked secondary field used in the respective classification feature, and each respective member of the set of extracted features extracted by the respective classification feature, to identify a subset of pivotal secondary fields based on the secondary fields associated with each selected pivotal classification feature, to create an enhanced training dataset by linking the subset of pivotal secondary fields to the primary training dataset; and to store at least one of the selected subset of pivotal features and enhanced training dataset for use in an automated machine learning process. 18. The system of claim 17, further comprising a physical user interface coupled to the processor, the user interface set to allow a user to designate the primary training set and the at least one secondary dataset. 19. The system of claim 17, wherein at least one secondary dataset is a publicly accessible database residing on a remote server, accessible over a network. 20. The system of claim 17, wherein at least one secondary dataset is retrieved from content published by a website. 21. The system of claim 17, wherein the matching requirement is based a maximum number of links and a processing time for creating the enhanced training dataset using a target processing unit. 22. The system of claim 17, further comprising code that automatically crawls along at least one of links on a network and stored file in the at least one second storage unit, the code automatically designates the at least one secondary dataset according to at least one object type that corresponds to at least one object type of the primary training dataset. 23. A computer program product comprising a non-transitory computer readable storage medium storing program code thereon for implementation by a processor of a system for creating enhanced training datasets for use in an automated machine learning process, the program code comprising:
instructions to receive a designation of a primary training dataset comprising a plurality of primary data instances, each primary data instance including a plurality of primary fields each assigned at least one value, each primary data instance associated with a classification label; instructions to receive a designation of at least one secondary dataset each comprising a plurality of secondary data instances, each secondary data instance including a plurality of secondary fields, each secondary data being unclassified; instructions to identify, for a first set of values of at least one primary field of the plurality of primary fields, a second set of secondary fields of the at least one secondary datasets according to the first set of values matched to corresponding values in at least one respective secondary field of at least one secondary dataset according to a matching requirement; instructions to link each respective matched value of the first set of values, to other secondary fields of at least one respective secondary data instance of the respective matched secondary field; instructions to generate a set of classification features based at least on the linked second set of secondary fields, each classification feature for application to at least one field from the linked second set of secondary data fields; instructions to apply each classification feature of the generated set of classification features to each linked second set of secondary fields to generate a set of extracted features; instructions to select a subset of pivotal classification features from the set of classification features according to a correlation requirement between the classification label of the primary data instance corresponding to the linked secondary field used in the respective classification feature, and each respective member of the set of extracted features extracted by the respective classification feature; instructions to identify a subset of pivotal secondary fields based on the secondary fields associated with each selected pivotal classification feature; instructions to create an enhanced training dataset by linking the subset of pivotal secondary fields to the primary training dataset; and instructions to document at least one of the selected subset of pivotal features and enhanced training dataset for use in an automated machine learning process. | There is provided a method for combining datasets, comprising: receiving a primary training dataset; receiving unclassified secondary dataset(s) comprising secondary data instances including secondary fields; identifying, for a first set of values of primary field(s) of training dataset, a second set of secondary fields of the secondary datasets according to the first set of values matched to corresponding values in respective secondary field(s) of secondary dataset(s) according to a matching requirement; linking each respective matched values to other secondary fields of the respective matched secondary field; generating a set of classification features based at least on the linked secondary fields; selecting a subset of pivotal classification features according to a correlation requirement; identifying a subset of pivotal secondary fields based on the secondary fields associated with each pivotal classification feature; and documenting the selected subset of pivotal features for use in an automated machine learning process.1. A computer implemented method for combining datasets for use in an automated machine learning process, comprising:
receiving a designation of a primary training dataset comprising a plurality of primary data instances, each primary data instance including a plurality of primary fields each assigned at least one value, each primary data instance associated with a classification label; receiving a designation of at least one secondary dataset each comprising a plurality of secondary data instances, each secondary data instance including a plurality of secondary fields, each secondary data being unclassified; identifying, for a first set of values of at least one primary field of the plurality of primary fields, a second set of secondary fields of the at least one secondary datasets according to the first set of values matched to corresponding values in at least one respective secondary field of at least one secondary dataset according to a matching requirement; linking each respective matched value of the first set of values, to other secondary fields of at least one respective secondary data instance of the respective matched secondary field; generating a set of classification features based at least on the linked second set of secondary fields, each classification feature for application to at least one field from the linked second set of secondary data fields; applying each classification feature of the generated set of classification features to each linked second set of secondary fields to generate a set of extracted features; selecting a subset of pivotal classification features from the set of classification features according to a correlation requirement between the classification label of the primary data instance corresponding to the linked secondary field used in the respective classification feature, and each respective member of the set of extracted features extracted by the respective classification feature; identifying a subset of pivotal secondary fields based on the secondary fields associated with each selected pivotal classification feature; creating an enhanced training dataset by linking the subset of pivotal secondary fields to the primary training dataset; and documenting at least one of the selected subset of pivotal features and enhanced training dataset for use in an automated machine learning process. 2. The method of claim 1, further comprising iterating the method until a stop condition is met, by designating the enhanced training dataset, and repeating the identifying the second set of secondary fields, linking, generating, applying, selecting, identifying the subset of pivotal secondary fields, and the creating, using the designated enhanced training dataset. 3. The method of claim 1, wherein at least some of the features extracted from at least one secondary field are statistically insignificantly correlated with the classification label. 4. The method of claim 1, wherein the matching requirement includes a percentage of the first set of values of the respective primary field matching the corresponding values in the respective secondary dataset. 5. The method of claim 1, wherein the matching requirement comprises that the first set of values is selected by sampling a subset of values of the at least one primary field. 6. The method of claim 1, further comprising preparing, for each secondary dataset, a set-representation of the plurality of secondary fields, and using the set-representation to match the first set of value and to identify the second set. 7. The method of claim 1, wherein at least one member of the at least one secondary dataset is selected from the group consisting of: a table wherein each row represents a secondary data instance and each column represents a secondary field and a graph comprising linked data. 8. The method of claim 1, wherein at least one primary field includes a third set of data elements each assigned a value, and wherein identifying comprises identifying for the first set of values of a subset including at least one data element of the third set. 9. The method of claim 1, wherein generating the set of classification features comprises generating at least one binary classification feature that extracts a binary value from at least one of the linked secondary data fields. 10. The method of claim 9, wherein the at least one binary classification feature includes at least one mathematical condition applied to at least one value of the linked secondary data fields of other data instances. 11. The method of claim 10, wherein the at least one mathematical condition is selected from the group consisting of: greater than, less than, equal to, greater than or equal to, less than or equal to, and containing the at least one value. 12. The method of claim 1, further comprising automatically designating at least one secondary dataset based at least one object type of at least one secondary field that corresponds to at least one object type of the primary training dataset. 13. The method of claim 1, further comprising analyzing at least one primary data field to extract at least one entity according to at least one object type, and wherein identifying comprises identifying the second set of secondary fields according to the object type of the first set of values of the at least one extracted entity. 14. The method of claim 1, further comprising converting values in at least one of: the primary training dataset and the at least one secondary data set to a canonical representation, and performing the identifying based on the canonical representation. 15. The method of claim 1, further comprising training a statistical classifier based on the selected subset of pivotal features applied to the enhanced training dataset, and the associated data classification labels. 16. The method of claim 1, further comprising classifying a new data instance to at least one of the data classification labels, by applying each classification feature of the selected subset of pivotal features to the new data instance to extract a plurality of features and applying the statistical classifier to the plurality of extracted features to output at least one of the data classification labels. 17. A system to create an enhanced training dataset for use in an automated machine learning process, comprising:
a primary interface for communication with a first storage unit storing thereon a primary training dataset comprising a plurality of primary data instances, each primary data instance including a plurality of primary fields each assigned at least one value, each primary data instance associated with a classification label; a secondary interface for communication with at least one second storage unit storing thereon at least one secondary dataset each comprising a plurality of secondary data instances, each secondary data instance including a plurality of secondary fields, each secondary data being unclassified; a program store storing code; and a processor coupled to the primary interface, the secondary interface, and the program store for implementing the stored code, the code comprising: code to identify, for a first set of values of at least one primary field of the plurality of primary fields, a second set of secondary fields of the at least one secondary datasets according to the first set of values matched to corresponding values in at least one respective secondary field of at least one secondary dataset according to a matching requirement, to link each respective matched value of the first set of values, to other secondary fields of at least one respective secondary data instance of the respective matched secondary field, to generate a set of classification features based at least on the linked second set of secondary fields, each classification feature for application to at least one field from the linked second set of secondary data fields, to apply each classification feature of the generated set of classification features to each linked second set of secondary fields to generate a set of extracted features, to select a subset of pivotal classification features from the set of classification features according to a correlation requirement between the classification label of the primary data instance corresponding to the linked secondary field used in the respective classification feature, and each respective member of the set of extracted features extracted by the respective classification feature, to identify a subset of pivotal secondary fields based on the secondary fields associated with each selected pivotal classification feature, to create an enhanced training dataset by linking the subset of pivotal secondary fields to the primary training dataset; and to store at least one of the selected subset of pivotal features and enhanced training dataset for use in an automated machine learning process. 18. The system of claim 17, further comprising a physical user interface coupled to the processor, the user interface set to allow a user to designate the primary training set and the at least one secondary dataset. 19. The system of claim 17, wherein at least one secondary dataset is a publicly accessible database residing on a remote server, accessible over a network. 20. The system of claim 17, wherein at least one secondary dataset is retrieved from content published by a website. 21. The system of claim 17, wherein the matching requirement is based a maximum number of links and a processing time for creating the enhanced training dataset using a target processing unit. 22. The system of claim 17, further comprising code that automatically crawls along at least one of links on a network and stored file in the at least one second storage unit, the code automatically designates the at least one secondary dataset according to at least one object type that corresponds to at least one object type of the primary training dataset. 23. A computer program product comprising a non-transitory computer readable storage medium storing program code thereon for implementation by a processor of a system for creating enhanced training datasets for use in an automated machine learning process, the program code comprising:
instructions to receive a designation of a primary training dataset comprising a plurality of primary data instances, each primary data instance including a plurality of primary fields each assigned at least one value, each primary data instance associated with a classification label; instructions to receive a designation of at least one secondary dataset each comprising a plurality of secondary data instances, each secondary data instance including a plurality of secondary fields, each secondary data being unclassified; instructions to identify, for a first set of values of at least one primary field of the plurality of primary fields, a second set of secondary fields of the at least one secondary datasets according to the first set of values matched to corresponding values in at least one respective secondary field of at least one secondary dataset according to a matching requirement; instructions to link each respective matched value of the first set of values, to other secondary fields of at least one respective secondary data instance of the respective matched secondary field; instructions to generate a set of classification features based at least on the linked second set of secondary fields, each classification feature for application to at least one field from the linked second set of secondary data fields; instructions to apply each classification feature of the generated set of classification features to each linked second set of secondary fields to generate a set of extracted features; instructions to select a subset of pivotal classification features from the set of classification features according to a correlation requirement between the classification label of the primary data instance corresponding to the linked secondary field used in the respective classification feature, and each respective member of the set of extracted features extracted by the respective classification feature; instructions to identify a subset of pivotal secondary fields based on the secondary fields associated with each selected pivotal classification feature; instructions to create an enhanced training dataset by linking the subset of pivotal secondary fields to the primary training dataset; and instructions to document at least one of the selected subset of pivotal features and enhanced training dataset for use in an automated machine learning process. | 2,100 |
6,071 | 6,071 | 15,396,306 | 2,173 | The presently disclosed inventive concepts encompass capturing video data using a mobile device, streaming the captured video data to a server for processing of the video data in real-time or near-real time, and providing the server's processing result to the mobile device for additional analysis and/or processing of the captured video data, the processing result, or both. In one embodiment an image processing server is configured to: process, in real time, input streamed to the server from a mobile device, the input comprising one or more frames of digital video data; and output a result of processing the input to the mobile device. In another embodiment, a method includes capturing video data using a mobile device, streaming the video data to an image processing server, receiving a processing result from the server, and further processing the captured video data and/or the processing result using the mobile device. | 1. An image processing server, comprising at least one processor, and logic configured, upon execution thereof by the processor, to cause the server to:
process, in real time, input streamed to the server from a mobile device, the input comprising one or more frames of digital video data; and output a result of processing the input to the mobile device. 2. The image processing server as recited in claim 1, wherein the input comprises a plurality of the one or more frames of digital video data, and processing the input comprises at least one of:
transforming a representation of an object depicted in the plurality of frames of digital video data from a native object representation to an improved object representation; determining information of interest regarding the object from the plurality of frames of digital video data; classifying the object depicted in the plurality of frames of digital video data; extracting the information of interest regarding the object from the plurality of frames of digital video data; and validating the information of interest extracted from the plurality of frames of digital video data. 3. The image processing server as recited in claim 1, wherein the input further comprises at least one of:
identifying information corresponding to the mobile device; user-defined processing parameters; and location information corresponding to the mobile device, the one or more frames of digital video data, or both; and wherein processing the input comprises processing the one or more frames of digital video data further based at least in part on the identifying information, the user-defined processing parameters, or the location information. 4. The image processing server as recited in claim 1, wherein the logic is configured to cause the server to process each one of the one or more frames of the digital video data streamed to the server in real-time or near real-time. 5. The image processing server as recited in claim 1, comprising calculating a consensus processing result from among a plurality of processing results each respectively corresponding to one of the one or more frames of digital video data. 6. The image processing server as recited in claim 1, wherein the input comprises a plurality of successive ones of the one or more frames of digital video data. 7. The image processing server as recited in claim 1, wherein the input comprises a plurality of alternating ones of the one or more frames of digital video data. 8. A computer-implemented method, comprising:
capturing, using a camera of a mobile device, a plurality of frames of digital video data; streaming at least some of the plurality of frames of digital video data to an image processing server configured to process frames of digital video data in real-time; receiving, from the image processing server, a processing result corresponding to some or all of the plurality of frames of digital video data streamed to the image processing server; and further processing, using a processor of the mobile device, according to one or more predetermined additional processing operations, some or all of the plurality of frames of digital video data captured using the camera of the mobile device, the processing result received from the image processing server, or both. 9. The computer-implemented method as recited in claim 8, further comprising pre-processing the plurality of frames of digital video data prior to streaming the plurality of frames of digital video data to the image processing server. 10. The computer-implemented method as recited in claim 8, wherein the processing result comprises at least one of:
an improved representation of an object depicted in the plurality of frames of digital video data, wherein the improved representation is generated by transforming at least some of the plurality of frames of digital video data from a native object representation to the improved representation of the object; a determination, from the plurality of frames of digital video data, of information of interest regarding the object; a classification of the object; extracted information of interest regarding the object; a validation status of some or all of the extracted information of interest; and feedback guiding the capture of additional frames of the digital video data. 11. The computer-implemented method as recited in claim 8, wherein the streaming comprises streaming a plurality of successive ones of the plurality of frames of digital video data to the image processing server. 12. The computer-implemented method as recited in claim 8, wherein the streaming comprises either: streaming a plurality of alternate ones of the plurality of frames of digital video data to the image processing server; streaming a limited number of the plurality of frames of digital video data to the image processing server; or both. 13. The computer-implemented method as recited in claim 8, further comprising transmitting to the image processing server, in association with the streamed ones of the plurality of frames of digital video data, one or more of:
identifying information corresponding to the mobile device; user-defined processing parameters; and location information corresponding to the mobile device, the one or more frames of digital video data, or both. 14. The computer-implemented method as recited in claim 8, wherein the one or more predetermined additional processing operations are selected from:
capturing additional video frames depicting a tracked object in the video data, the capture of the additional video frames being characterized by a modification of capture conditions selected from illumination, capture angle, capture distance, and capture device movement; classifying an object whose location within the video data is indicated by the processing result received from the image processing server; extracting information of interest from select locations within one or more frames of the digital video data, the select locations being based on the processing result received from the image processing server and the extraction employing extraction conditions based on the processing result received from the server; and validating information of interest extracted from the digital video data based on the processing result received from the image processing server, wherein the extracted information of interest are indicated in the processing result received from the image processing server. 15. The computer-implemented method as recited in claim 14, wherein the processing result received from the image processing server comprises a consensus processing result. 16. A computer program product, comprising a computer readable medium having embodied therewith computer readable program code configured, upon execution thereof, to cause a mobile device to perform operations comprising:
capturing, using a camera of the mobile device, a plurality of frames of digital video data; streaming at least some of the plurality of frames of digital video data to an image processing server configured to process frames of digital video data in real-time; receiving, from the image processing server, a processing result corresponding to some or all of the plurality of frames of digital video data streamed to the image processing server; and further processing, using a processor of the mobile device and according to one or more predetermined additional processing operations, some or all of the plurality of frames of digital video data captured using the camera of the mobile device, the processing result received from the image processing server, or both. 17. The computer program product as recited in claim 16, further comprising computer readable program code configured, upon execution thereof, to cause a mobile device to pre-process the plurality of frames of digital video data prior to streaming the plurality of frames of digital video data to the image processing server. 18. The computer program product as recited in claim 16, wherein the processing result comprises at least one of:
an improved representation of an object depicted in the plurality of frames of digital video data, wherein the improved representation is generated by transforming at least some of the plurality of frames of digital video data from a native object representation to the improved representation of the object; a determination, from the plurality of frames of digital video data, of information of interest regarding the object; a classification of the object; extracted information of interest regarding the object; a validation status of some or all of the extracted information of interest; and feedback guiding the capture of additional frames of the digital video data. 19. The computer program product as recited in claim 16, wherein the one or more predetermined additional processing operations are selected from:
capturing additional video frames depicting a tracked object in the video data, the capture of the additional video frames being characterized by a modification of capture conditions selected from illumination, capture angle, capture distance, and capture device movement; classifying an object whose location within the video data is indicated by the processing result received from the image processing server; extracting information of interest from select locations within one or more frames of the digital video data, the select locations being based on the processing result received from the image processing server and the extraction employing extraction conditions based on the processing result received from the server; and validating information of interest extracted from the digital video data based on the processing result received from the image processing server, wherein the extracted information of interest are indicated in the processing result received from the image processing server. 20. The computer program product as recited in claim 19, wherein the processing result received from the image processing server comprises a consensus processing result. | The presently disclosed inventive concepts encompass capturing video data using a mobile device, streaming the captured video data to a server for processing of the video data in real-time or near-real time, and providing the server's processing result to the mobile device for additional analysis and/or processing of the captured video data, the processing result, or both. In one embodiment an image processing server is configured to: process, in real time, input streamed to the server from a mobile device, the input comprising one or more frames of digital video data; and output a result of processing the input to the mobile device. In another embodiment, a method includes capturing video data using a mobile device, streaming the video data to an image processing server, receiving a processing result from the server, and further processing the captured video data and/or the processing result using the mobile device.1. An image processing server, comprising at least one processor, and logic configured, upon execution thereof by the processor, to cause the server to:
process, in real time, input streamed to the server from a mobile device, the input comprising one or more frames of digital video data; and output a result of processing the input to the mobile device. 2. The image processing server as recited in claim 1, wherein the input comprises a plurality of the one or more frames of digital video data, and processing the input comprises at least one of:
transforming a representation of an object depicted in the plurality of frames of digital video data from a native object representation to an improved object representation; determining information of interest regarding the object from the plurality of frames of digital video data; classifying the object depicted in the plurality of frames of digital video data; extracting the information of interest regarding the object from the plurality of frames of digital video data; and validating the information of interest extracted from the plurality of frames of digital video data. 3. The image processing server as recited in claim 1, wherein the input further comprises at least one of:
identifying information corresponding to the mobile device; user-defined processing parameters; and location information corresponding to the mobile device, the one or more frames of digital video data, or both; and wherein processing the input comprises processing the one or more frames of digital video data further based at least in part on the identifying information, the user-defined processing parameters, or the location information. 4. The image processing server as recited in claim 1, wherein the logic is configured to cause the server to process each one of the one or more frames of the digital video data streamed to the server in real-time or near real-time. 5. The image processing server as recited in claim 1, comprising calculating a consensus processing result from among a plurality of processing results each respectively corresponding to one of the one or more frames of digital video data. 6. The image processing server as recited in claim 1, wherein the input comprises a plurality of successive ones of the one or more frames of digital video data. 7. The image processing server as recited in claim 1, wherein the input comprises a plurality of alternating ones of the one or more frames of digital video data. 8. A computer-implemented method, comprising:
capturing, using a camera of a mobile device, a plurality of frames of digital video data; streaming at least some of the plurality of frames of digital video data to an image processing server configured to process frames of digital video data in real-time; receiving, from the image processing server, a processing result corresponding to some or all of the plurality of frames of digital video data streamed to the image processing server; and further processing, using a processor of the mobile device, according to one or more predetermined additional processing operations, some or all of the plurality of frames of digital video data captured using the camera of the mobile device, the processing result received from the image processing server, or both. 9. The computer-implemented method as recited in claim 8, further comprising pre-processing the plurality of frames of digital video data prior to streaming the plurality of frames of digital video data to the image processing server. 10. The computer-implemented method as recited in claim 8, wherein the processing result comprises at least one of:
an improved representation of an object depicted in the plurality of frames of digital video data, wherein the improved representation is generated by transforming at least some of the plurality of frames of digital video data from a native object representation to the improved representation of the object; a determination, from the plurality of frames of digital video data, of information of interest regarding the object; a classification of the object; extracted information of interest regarding the object; a validation status of some or all of the extracted information of interest; and feedback guiding the capture of additional frames of the digital video data. 11. The computer-implemented method as recited in claim 8, wherein the streaming comprises streaming a plurality of successive ones of the plurality of frames of digital video data to the image processing server. 12. The computer-implemented method as recited in claim 8, wherein the streaming comprises either: streaming a plurality of alternate ones of the plurality of frames of digital video data to the image processing server; streaming a limited number of the plurality of frames of digital video data to the image processing server; or both. 13. The computer-implemented method as recited in claim 8, further comprising transmitting to the image processing server, in association with the streamed ones of the plurality of frames of digital video data, one or more of:
identifying information corresponding to the mobile device; user-defined processing parameters; and location information corresponding to the mobile device, the one or more frames of digital video data, or both. 14. The computer-implemented method as recited in claim 8, wherein the one or more predetermined additional processing operations are selected from:
capturing additional video frames depicting a tracked object in the video data, the capture of the additional video frames being characterized by a modification of capture conditions selected from illumination, capture angle, capture distance, and capture device movement; classifying an object whose location within the video data is indicated by the processing result received from the image processing server; extracting information of interest from select locations within one or more frames of the digital video data, the select locations being based on the processing result received from the image processing server and the extraction employing extraction conditions based on the processing result received from the server; and validating information of interest extracted from the digital video data based on the processing result received from the image processing server, wherein the extracted information of interest are indicated in the processing result received from the image processing server. 15. The computer-implemented method as recited in claim 14, wherein the processing result received from the image processing server comprises a consensus processing result. 16. A computer program product, comprising a computer readable medium having embodied therewith computer readable program code configured, upon execution thereof, to cause a mobile device to perform operations comprising:
capturing, using a camera of the mobile device, a plurality of frames of digital video data; streaming at least some of the plurality of frames of digital video data to an image processing server configured to process frames of digital video data in real-time; receiving, from the image processing server, a processing result corresponding to some or all of the plurality of frames of digital video data streamed to the image processing server; and further processing, using a processor of the mobile device and according to one or more predetermined additional processing operations, some or all of the plurality of frames of digital video data captured using the camera of the mobile device, the processing result received from the image processing server, or both. 17. The computer program product as recited in claim 16, further comprising computer readable program code configured, upon execution thereof, to cause a mobile device to pre-process the plurality of frames of digital video data prior to streaming the plurality of frames of digital video data to the image processing server. 18. The computer program product as recited in claim 16, wherein the processing result comprises at least one of:
an improved representation of an object depicted in the plurality of frames of digital video data, wherein the improved representation is generated by transforming at least some of the plurality of frames of digital video data from a native object representation to the improved representation of the object; a determination, from the plurality of frames of digital video data, of information of interest regarding the object; a classification of the object; extracted information of interest regarding the object; a validation status of some or all of the extracted information of interest; and feedback guiding the capture of additional frames of the digital video data. 19. The computer program product as recited in claim 16, wherein the one or more predetermined additional processing operations are selected from:
capturing additional video frames depicting a tracked object in the video data, the capture of the additional video frames being characterized by a modification of capture conditions selected from illumination, capture angle, capture distance, and capture device movement; classifying an object whose location within the video data is indicated by the processing result received from the image processing server; extracting information of interest from select locations within one or more frames of the digital video data, the select locations being based on the processing result received from the image processing server and the extraction employing extraction conditions based on the processing result received from the server; and validating information of interest extracted from the digital video data based on the processing result received from the image processing server, wherein the extracted information of interest are indicated in the processing result received from the image processing server. 20. The computer program product as recited in claim 19, wherein the processing result received from the image processing server comprises a consensus processing result. | 2,100 |
6,072 | 6,072 | 15,651,133 | 2,179 | Different techniques of processing user interactions with a computing system are described. In one implementation, an interactive display is configured to depict a graphical user interface which includes a plurality of different types of user interface elements (e.g., button-type element, scroll bar-type element). A user may use one or more user input object (e.g., finger, hand, stylus) to simultaneously interact with the interactive display. A plurality of different user input processing methods are used to process user inputs received by the graphical user interface differently and in accordance with the types of the user interface elements which are displayed. The processing of the user inputs is implemented to determine whether the user inputs control the respective user interface elements. The processing may determine whether the user inputs activate and/or manipulate the displayed user interface elements in but one example. | 1.-20. (canceled) 21. A method for interacting with a device, the method comprising:
receiving a first touch input from at least one finger of a first user via a first region of a multi-touch user interface associated with the device and substantially simultaneously receiving a second touch input from a stylus held by a second user, different from the first user, via a second region of the multi-touch user interface associated with the device; automatically determining by the device, the first touch input as corresponding to the at least one finger of the first user and the second touch input as corresponding to the stylus held by the second user; and processing the first touch input using a first processing method and processing the second touch input using a second processing method, wherein the first processing method is tailored to process inputs corresponding to finger touch events and the second processing method is tailored to process inputs corresponding to input events from the stylus, wherein the first processing method comprises automatically determining a first value corresponding to an area of the activated pixels in the first region of the multi-touch user interface by the first touch input and automatically modifying the first value corresponding to the area of the activated pixels in the first region of the multi-touch user interface to determine a second value corresponding to the area of the activated pixels in the first region of the multi-touch user interface, wherein the second value is different form the first value. 22. The method of claim 21 further comprising automatically determining by the device whether the first touch input interacts with a first type of user interface element of the multi-touch user interface or with a second type of user interface element of the multi-touch user interface, wherein the second type of user interface element is different from the first type of user interface element. 23. The method of claim 22 further comprising processing the first touch input using a processing method corresponding to the first type of user interface element if the first touch input interacts with the first type of user interface element. 24. The method of claim 22 further comprising processing the first touch input using a processing method corresponding to the second type of user interface element if the first touch input interacts with the second type of user interface element. 25. The method of claim 21 further comprising automatically determining by the device whether the second touch input interacts with a first type of user interface element of the multi-touch user interface or with a second type of user interface element of the multi-touch user interface, wherein the second type of user interface element is different from the first type of user interface element. 26. The method of claim 25 further comprising processing the second touch input using a processing method corresponding to the first type of user interface element if the second touch input interacts with the first type of user interface element. 27. The method of claim 25 further comprising processing the second touch input using a processing method corresponding to the second type of user interface element if the second touch input interacts with the second type of user interface element. 28. A computer-readable medium comprising instructions, when executed by at least one processor in a device, configured to:
receive a first touch input from at least one finger of a first user via a first region of a multi-touch user interface associated with the device and substantially simultaneously receive a second touch input from a stylus held by a second user, different from the first user, via a second region of the multi-touch user interface associated with the device; automatically determine by the device the first touch input as corresponding to the at least one finger of the first user and the second touch input as corresponding to the stylus held by the second user; and process the first touch input using a first processing method and process the second touch input using a second processing method, wherein the first processing method is tailored to process inputs corresponding to finger touch events and the second processing method is tailored to process inputs corresponding to input events from the stylus, wherein the first processing method comprises automatically determining a first value corresponding to an area of the activated pixels in the first region of the multi-touch user interface by the first touch input and automatically modifying the first value corresponding to the area of the activated pixels in the first region of the multi-touch user interface to determine a second value corresponding to the area of the activated pixels in the first region of the multi-touch user interface, wherein the second value is different form the first value. 29. The computer-readable medium of claim 28 further comprising instructions, when executed by the at least one processor in the device, configured to automatically determine whether the first touch input interacts with a first type of user interface element of the multi-touch user interface or with a second type of user interface element of the multi-touch user interface, wherein the second type of user interface element is different from the first type of user interface element. 30. The computer-readable medium of claim 29 further comprising instructions, when executed by the at least one processor in the device, configured to process the first touch input using a processing method corresponding to the first type of user interface element if the first touch input interacts with the first type of user interface element. 31. The computer-readable medium of claim 29 further comprising instructions, when executed by the at least one processor in the device, configured to process the first touch input using a processing method corresponding to the second type of user interface element if the first touch input interacts with the second type of user interface element. 32. The computer-readable medium of claim 28 further comprising instructions, when executed by the at least one processor in the device, configured to automatically determine whether the second touch input interacts with a first type of user interface element of the multi-touch user interface or with a second type of user interface element of the multi-touch user interface, wherein the second type of user interface element is different from the first type of user interface element. 33. The computer-readable medium of claim 32 further comprising instructions, when executed by the at least one processor in the device, configured to process the second touch input using a processing method corresponding to the first type of user interface element if the second touch input interacts with the first type of user interface element. 34. The computer-readable medium of claim 32 further comprising instructions, when executed by the at least one processor in the device, configured to process the second touch input using a processing method corresponding to the second type of user interface element if the second touch input interacts with the second type of user interface element. 35. A device comprising at least one processor and a memory comprising instructions, when executed by at least one processor in a device, configured to:
receive a first touch input from at least one finger of a first user via a first region of a multi-touch user interface associated with the device and substantially simultaneously receive a second touch input from a stylus held by a second user, different from the first user, via a second region of the multi-touch user interface associated with the device; automatically determine by the device the first touch input as corresponding to the at least one finger of the first user and the second touch input as corresponding to the stylus held by the second user; and process the first touch input using a first processing method and process the second touch input using a second processing method, wherein the first processing method is tailored to process inputs corresponding to finger touch events and the second processing method is tailored to process inputs corresponding to input events from the stylus, wherein the first processing method comprises automatically determining a first value corresponding to an area of the activated pixels in the first region of the multi-touch user interface by the first touch input and automatically modifying the first value corresponding to the area of the activated pixels in the first region of the multi-touch user interface to determine a second value corresponding to the area of the activated pixels in the first region of the multi-touch user interface, wherein the second value is different form the first value. 36. The device of claim 35, wherein the memory further comprising instructions, when executed by the at least one processor in the device, configured to automatically determine whether the first touch input interacts with a first type of user interface element of the multi-touch user interface or with a second type of user interface element of the multi-touch user interface, wherein the second type of user interface element is different from the first type of user interface element. 37. The device of claim 36, wherein the memory further comprising instructions, when executed by the at least one processor in the device, configured to process the first touch input using a processing method corresponding to the first type of user interface element if the first touch input interacts with the first type of user interface element. 38. The device of claim 36, wherein the memory further comprising instructions, when executed by the at least one processor in the device, configured to process the first touch input using a processing method corresponding to the second type of user interface element if the first touch input interacts with the second type of user interface element. 39. The device of claim 35, wherein the memory further comprising instructions, when executed by the at least one processor in the device, configured to automatically determine whether the second touch input interacts with a first type of user interface element of the multi-touch user interface or with a second type of user interface element of the multi-touch user interface, wherein the second type of user interface element is different from the first type of user interface element. 40. The device of claim 39, wherein the memory further comprising instructions, when executed by the at least one processor in the device, configured to process the second touch input using a processing method corresponding to the first type of user interface element if the second touch input interacts with the first type of user interface element and process the second touch input using a processing method corresponding to the second type of user interface element if the second touch input interacts with the second type of user interface element. | Different techniques of processing user interactions with a computing system are described. In one implementation, an interactive display is configured to depict a graphical user interface which includes a plurality of different types of user interface elements (e.g., button-type element, scroll bar-type element). A user may use one or more user input object (e.g., finger, hand, stylus) to simultaneously interact with the interactive display. A plurality of different user input processing methods are used to process user inputs received by the graphical user interface differently and in accordance with the types of the user interface elements which are displayed. The processing of the user inputs is implemented to determine whether the user inputs control the respective user interface elements. The processing may determine whether the user inputs activate and/or manipulate the displayed user interface elements in but one example.1.-20. (canceled) 21. A method for interacting with a device, the method comprising:
receiving a first touch input from at least one finger of a first user via a first region of a multi-touch user interface associated with the device and substantially simultaneously receiving a second touch input from a stylus held by a second user, different from the first user, via a second region of the multi-touch user interface associated with the device; automatically determining by the device, the first touch input as corresponding to the at least one finger of the first user and the second touch input as corresponding to the stylus held by the second user; and processing the first touch input using a first processing method and processing the second touch input using a second processing method, wherein the first processing method is tailored to process inputs corresponding to finger touch events and the second processing method is tailored to process inputs corresponding to input events from the stylus, wherein the first processing method comprises automatically determining a first value corresponding to an area of the activated pixels in the first region of the multi-touch user interface by the first touch input and automatically modifying the first value corresponding to the area of the activated pixels in the first region of the multi-touch user interface to determine a second value corresponding to the area of the activated pixels in the first region of the multi-touch user interface, wherein the second value is different form the first value. 22. The method of claim 21 further comprising automatically determining by the device whether the first touch input interacts with a first type of user interface element of the multi-touch user interface or with a second type of user interface element of the multi-touch user interface, wherein the second type of user interface element is different from the first type of user interface element. 23. The method of claim 22 further comprising processing the first touch input using a processing method corresponding to the first type of user interface element if the first touch input interacts with the first type of user interface element. 24. The method of claim 22 further comprising processing the first touch input using a processing method corresponding to the second type of user interface element if the first touch input interacts with the second type of user interface element. 25. The method of claim 21 further comprising automatically determining by the device whether the second touch input interacts with a first type of user interface element of the multi-touch user interface or with a second type of user interface element of the multi-touch user interface, wherein the second type of user interface element is different from the first type of user interface element. 26. The method of claim 25 further comprising processing the second touch input using a processing method corresponding to the first type of user interface element if the second touch input interacts with the first type of user interface element. 27. The method of claim 25 further comprising processing the second touch input using a processing method corresponding to the second type of user interface element if the second touch input interacts with the second type of user interface element. 28. A computer-readable medium comprising instructions, when executed by at least one processor in a device, configured to:
receive a first touch input from at least one finger of a first user via a first region of a multi-touch user interface associated with the device and substantially simultaneously receive a second touch input from a stylus held by a second user, different from the first user, via a second region of the multi-touch user interface associated with the device; automatically determine by the device the first touch input as corresponding to the at least one finger of the first user and the second touch input as corresponding to the stylus held by the second user; and process the first touch input using a first processing method and process the second touch input using a second processing method, wherein the first processing method is tailored to process inputs corresponding to finger touch events and the second processing method is tailored to process inputs corresponding to input events from the stylus, wherein the first processing method comprises automatically determining a first value corresponding to an area of the activated pixels in the first region of the multi-touch user interface by the first touch input and automatically modifying the first value corresponding to the area of the activated pixels in the first region of the multi-touch user interface to determine a second value corresponding to the area of the activated pixels in the first region of the multi-touch user interface, wherein the second value is different form the first value. 29. The computer-readable medium of claim 28 further comprising instructions, when executed by the at least one processor in the device, configured to automatically determine whether the first touch input interacts with a first type of user interface element of the multi-touch user interface or with a second type of user interface element of the multi-touch user interface, wherein the second type of user interface element is different from the first type of user interface element. 30. The computer-readable medium of claim 29 further comprising instructions, when executed by the at least one processor in the device, configured to process the first touch input using a processing method corresponding to the first type of user interface element if the first touch input interacts with the first type of user interface element. 31. The computer-readable medium of claim 29 further comprising instructions, when executed by the at least one processor in the device, configured to process the first touch input using a processing method corresponding to the second type of user interface element if the first touch input interacts with the second type of user interface element. 32. The computer-readable medium of claim 28 further comprising instructions, when executed by the at least one processor in the device, configured to automatically determine whether the second touch input interacts with a first type of user interface element of the multi-touch user interface or with a second type of user interface element of the multi-touch user interface, wherein the second type of user interface element is different from the first type of user interface element. 33. The computer-readable medium of claim 32 further comprising instructions, when executed by the at least one processor in the device, configured to process the second touch input using a processing method corresponding to the first type of user interface element if the second touch input interacts with the first type of user interface element. 34. The computer-readable medium of claim 32 further comprising instructions, when executed by the at least one processor in the device, configured to process the second touch input using a processing method corresponding to the second type of user interface element if the second touch input interacts with the second type of user interface element. 35. A device comprising at least one processor and a memory comprising instructions, when executed by at least one processor in a device, configured to:
receive a first touch input from at least one finger of a first user via a first region of a multi-touch user interface associated with the device and substantially simultaneously receive a second touch input from a stylus held by a second user, different from the first user, via a second region of the multi-touch user interface associated with the device; automatically determine by the device the first touch input as corresponding to the at least one finger of the first user and the second touch input as corresponding to the stylus held by the second user; and process the first touch input using a first processing method and process the second touch input using a second processing method, wherein the first processing method is tailored to process inputs corresponding to finger touch events and the second processing method is tailored to process inputs corresponding to input events from the stylus, wherein the first processing method comprises automatically determining a first value corresponding to an area of the activated pixels in the first region of the multi-touch user interface by the first touch input and automatically modifying the first value corresponding to the area of the activated pixels in the first region of the multi-touch user interface to determine a second value corresponding to the area of the activated pixels in the first region of the multi-touch user interface, wherein the second value is different form the first value. 36. The device of claim 35, wherein the memory further comprising instructions, when executed by the at least one processor in the device, configured to automatically determine whether the first touch input interacts with a first type of user interface element of the multi-touch user interface or with a second type of user interface element of the multi-touch user interface, wherein the second type of user interface element is different from the first type of user interface element. 37. The device of claim 36, wherein the memory further comprising instructions, when executed by the at least one processor in the device, configured to process the first touch input using a processing method corresponding to the first type of user interface element if the first touch input interacts with the first type of user interface element. 38. The device of claim 36, wherein the memory further comprising instructions, when executed by the at least one processor in the device, configured to process the first touch input using a processing method corresponding to the second type of user interface element if the first touch input interacts with the second type of user interface element. 39. The device of claim 35, wherein the memory further comprising instructions, when executed by the at least one processor in the device, configured to automatically determine whether the second touch input interacts with a first type of user interface element of the multi-touch user interface or with a second type of user interface element of the multi-touch user interface, wherein the second type of user interface element is different from the first type of user interface element. 40. The device of claim 39, wherein the memory further comprising instructions, when executed by the at least one processor in the device, configured to process the second touch input using a processing method corresponding to the first type of user interface element if the second touch input interacts with the first type of user interface element and process the second touch input using a processing method corresponding to the second type of user interface element if the second touch input interacts with the second type of user interface element. | 2,100 |
6,073 | 6,073 | 14,641,298 | 2,173 | At an electronic device, detecting a compatible external device, where the external device is executing or has executed a first application. The detection may be made wirelessly. The electronic device also receives usage information regarding the first application from the external device. Display an affordance for user selection based on the received information. When the affordance is selected, launch a second application on the electronic device, the second application corresponding to the first application. In some examples, the second application is a different version of the first application. Launching the second application may additionally include bringing the second application to the same state as the first application. For example, if e-mail is being drafted on the external device, the electronic device may launch an e-mail editor showing the draft. In this way, a user can seamlessly transition from the use of one electronic device to another electronic device. | 1. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device with a touch-sensitive display, cause the device to:
detect an external device while the electronic device is in a user-interface locked state, wherein the external device is executing a first application, the first application in a state; display for a predetermined amount of time, on the touch-sensitive display, an affordance corresponding to the first application; detect a contact on the touch-sensitive display at a location of the displayed affordance; and in response to the contact, launch a second application, the second application corresponding to the first application, wherein the state of the second application corresponds to the state of the first application. 2. A non-transitory computer readable storage medium according to claim 1, wherein the contact is a tap on the displayed affordance, and wherein the one or more programs further comprises instructions for:
in response to detecting the tap, launching the second application. 3. A non-transitory computer readable storage medium according to claim 1, wherein the contact is a tap on the displayed affordance, and wherein the one or more programs further comprises instructions for:
in response to detecting the tap:
bouncing the affordance; and
not launching the second application. 4. A non-transitory computer readable storage medium according to claim 1, wherein the contact is a swipe from the displayed affordance, and wherein the one or more programs further comprises instructions for:
in response to detecting the swipe, launching the second application. 5. A non-transitory computer readable storage medium according to claim 4, further comprising:
determining whether a distance of the swipe exceeds a threshold distance; and launching the second application from the locked state only if it is determined that the distance of the swipe exceeds the threshold distance. 6. A non-transitory computer readable storage medium according to claim 5, further comprising:
in accordance with a determination that the distance of the swipe does not exceed the threshold distance, bouncing the affordance. 7. A non-transitory computer readable storage medium according to claim 1, wherein the first application and the second application have at least one application feature in common. 8. A non-transitory computer readable storage medium according to claim 1, wherein the state of the first application corresponds to a position in a navigation hierarchy of the first application. 9. A non-transitory computer readable storage medium according to claim 1, wherein the state of the first application corresponds to a location in a document displayed in the first application. 10. A non-transitory computer readable storage medium according to claim 1, wherein the state of the first application corresponds to whether a feature of the first application is active. 11. A non-transitory computer readable storage medium according to claim 1, wherein the first application and the second application are versions of the same application. 12. A non-transitory computer readable storage medium according to claim 1, further comprising:
receiving, by the electronic device, application data of the first application; and displaying the application data via the second application. 13. A non-transitory computer readable storage medium according to claim 12, wherein the application data represents a portion of a message displayed by the first application, and wherein the one or more programs further comprises instructions for:
displaying the portion of the message in the second application. 14. A non-transitory computer readable storage medium according to claim 12, wherein the application data represents a portion of a web-page, and wherein the one or more programs further comprises instructions for:
displaying the portion of the web-page via the second application. 15. A non-transitory computer readable storage medium according to claim 1, wherein at least one application feature is accessible only from one of the first application and the second application. 16. A non-transitory computer readable storage medium according to claim 1, wherein the first application performs at least one application feature, and wherein launching the second application comprises:
displaying an affordance for invoking, wirelessly from the second application executing on the electronic device, an application feature of the first application executing on the external device. 17. A non-transitory computer readable storage medium according to claim 1, wherein the electronic device is a laptop or desktop computer. 18. A non-transitory computer readable storage medium according to claim 1, wherein the electronic device is a tablet computer. 19. A non-transitory computer readable storage medium according to claim 1, wherein the electronic device is a phone. 20. A non-transitory computer readable storage medium according to claim 1, wherein the external device is a laptop or desktop computer. 21. A non-transitory computer readable storage medium according to claim 1, wherein the external device is a tablet computer. 22. A non-transitory computer readable storage medium according to claim 1, wherein the external device is a phone. 23. An electronic device, comprising:
a touch-sensitive display; one or more processors; a 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:
detecting an external device while the electronic device is in a user-interface locked state, wherein the external device is executing a first application, the first application in a state;
displaying for a predetermined amount of time, on the touch-sensitive display, an affordance corresponding to the first application;
detecting a contact on the touch-sensitive display at a location of the displayed affordance; and
in response to the contact, launching a second application, the second application corresponding to the first application, wherein the state of the second application corresponds to the state of the first application. 24. A method, comprising:
at an electronic device having a touch-sensitive display, the electronic device in a user-interface locked state:
detecting an external device, wherein the external device is executing a first application, the first application in a state;
displaying for a predetermined amount of time, on the touch-sensitive display, an affordance corresponding to the first application;
detecting a contact on the touch-sensitive display at a location of the displayed affordance; and
in response to the contact, launching a second application, the second application corresponding to the first application, wherein the state of the second application corresponds to the state of the first application. | At an electronic device, detecting a compatible external device, where the external device is executing or has executed a first application. The detection may be made wirelessly. The electronic device also receives usage information regarding the first application from the external device. Display an affordance for user selection based on the received information. When the affordance is selected, launch a second application on the electronic device, the second application corresponding to the first application. In some examples, the second application is a different version of the first application. Launching the second application may additionally include bringing the second application to the same state as the first application. For example, if e-mail is being drafted on the external device, the electronic device may launch an e-mail editor showing the draft. In this way, a user can seamlessly transition from the use of one electronic device to another electronic device.1. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device with a touch-sensitive display, cause the device to:
detect an external device while the electronic device is in a user-interface locked state, wherein the external device is executing a first application, the first application in a state; display for a predetermined amount of time, on the touch-sensitive display, an affordance corresponding to the first application; detect a contact on the touch-sensitive display at a location of the displayed affordance; and in response to the contact, launch a second application, the second application corresponding to the first application, wherein the state of the second application corresponds to the state of the first application. 2. A non-transitory computer readable storage medium according to claim 1, wherein the contact is a tap on the displayed affordance, and wherein the one or more programs further comprises instructions for:
in response to detecting the tap, launching the second application. 3. A non-transitory computer readable storage medium according to claim 1, wherein the contact is a tap on the displayed affordance, and wherein the one or more programs further comprises instructions for:
in response to detecting the tap:
bouncing the affordance; and
not launching the second application. 4. A non-transitory computer readable storage medium according to claim 1, wherein the contact is a swipe from the displayed affordance, and wherein the one or more programs further comprises instructions for:
in response to detecting the swipe, launching the second application. 5. A non-transitory computer readable storage medium according to claim 4, further comprising:
determining whether a distance of the swipe exceeds a threshold distance; and launching the second application from the locked state only if it is determined that the distance of the swipe exceeds the threshold distance. 6. A non-transitory computer readable storage medium according to claim 5, further comprising:
in accordance with a determination that the distance of the swipe does not exceed the threshold distance, bouncing the affordance. 7. A non-transitory computer readable storage medium according to claim 1, wherein the first application and the second application have at least one application feature in common. 8. A non-transitory computer readable storage medium according to claim 1, wherein the state of the first application corresponds to a position in a navigation hierarchy of the first application. 9. A non-transitory computer readable storage medium according to claim 1, wherein the state of the first application corresponds to a location in a document displayed in the first application. 10. A non-transitory computer readable storage medium according to claim 1, wherein the state of the first application corresponds to whether a feature of the first application is active. 11. A non-transitory computer readable storage medium according to claim 1, wherein the first application and the second application are versions of the same application. 12. A non-transitory computer readable storage medium according to claim 1, further comprising:
receiving, by the electronic device, application data of the first application; and displaying the application data via the second application. 13. A non-transitory computer readable storage medium according to claim 12, wherein the application data represents a portion of a message displayed by the first application, and wherein the one or more programs further comprises instructions for:
displaying the portion of the message in the second application. 14. A non-transitory computer readable storage medium according to claim 12, wherein the application data represents a portion of a web-page, and wherein the one or more programs further comprises instructions for:
displaying the portion of the web-page via the second application. 15. A non-transitory computer readable storage medium according to claim 1, wherein at least one application feature is accessible only from one of the first application and the second application. 16. A non-transitory computer readable storage medium according to claim 1, wherein the first application performs at least one application feature, and wherein launching the second application comprises:
displaying an affordance for invoking, wirelessly from the second application executing on the electronic device, an application feature of the first application executing on the external device. 17. A non-transitory computer readable storage medium according to claim 1, wherein the electronic device is a laptop or desktop computer. 18. A non-transitory computer readable storage medium according to claim 1, wherein the electronic device is a tablet computer. 19. A non-transitory computer readable storage medium according to claim 1, wherein the electronic device is a phone. 20. A non-transitory computer readable storage medium according to claim 1, wherein the external device is a laptop or desktop computer. 21. A non-transitory computer readable storage medium according to claim 1, wherein the external device is a tablet computer. 22. A non-transitory computer readable storage medium according to claim 1, wherein the external device is a phone. 23. An electronic device, comprising:
a touch-sensitive display; one or more processors; a 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:
detecting an external device while the electronic device is in a user-interface locked state, wherein the external device is executing a first application, the first application in a state;
displaying for a predetermined amount of time, on the touch-sensitive display, an affordance corresponding to the first application;
detecting a contact on the touch-sensitive display at a location of the displayed affordance; and
in response to the contact, launching a second application, the second application corresponding to the first application, wherein the state of the second application corresponds to the state of the first application. 24. A method, comprising:
at an electronic device having a touch-sensitive display, the electronic device in a user-interface locked state:
detecting an external device, wherein the external device is executing a first application, the first application in a state;
displaying for a predetermined amount of time, on the touch-sensitive display, an affordance corresponding to the first application;
detecting a contact on the touch-sensitive display at a location of the displayed affordance; and
in response to the contact, launching a second application, the second application corresponding to the first application, wherein the state of the second application corresponds to the state of the first application. | 2,100 |
6,074 | 6,074 | 14,472,505 | 2,194 | A method can include receiving implicit function values at nodes of a coarse mesh of a region of interest in a geologic environment; receiving data: formulating constraints based at least in part on the data; solving a system of equations for a finer mesh subject to the constraints; and outputting implicit function values at nodes of the finer mesh based at least in part on solving the system of equations. | 1. A method comprising:
receiving implicit function values at nodes of a coarse mesh of a region of interest in a geologic environment; receiving data; formulating constraints based at least in part on the data; solving a system of equations for a finer mesh subject to the constraints; and outputting implicit function values at nodes of the finer mesh based at least in part on solving the system of equations. 2. The method of claim 1 wherein the solving comprises solving the system of equations for residual values. 3. The method of claim 1 comprising interpolating the implicit function values at the nodes of the coarse mesh to provide interpolated implicit function values at the nodes of the finer mesh. 4. The method of claim 3 wherein the outputting comprises adding the residual values and the interpolated implicit function values. 5. The method of claim 1 wherein the solving comprises using at least one processor. 6. The method of claim 1 wherein the implicit function values at the nodes of the finer mesh comprise stratigraphic function values. 7. The method of claim 1 wherein the data comprise dip vectors. 8. The method of claim 7 wherein the constraints comprise linear gradient constraints based at least in part on the dip vectors. 9. The method of claim 8 wherein the linear gradient constraints are formulated according to a Gram-Schmidt algorithm. 10. The method of claim 8 wherein the linear gradient constraints comprise weights. 11. The method of claim 10 wherein the weights correspond to quantifiable qualities of the dip vectors. 12. The method of claim 1 wherein the data comprise confidence values. 13. The method of claim 12 further comprising introducing weights based at least in part on the confidence values. 14. The method of claim 1 wherein the data comprise a spatial resolution for the region of interest that is higher than a spatial resolution for the nodes of the coarse mesh. 15. A system comprising:
a processor; memory operatively coupled to the processor; and one or more modules that comprise instructions stored in the memory and executable by the processor to instruct the system wherein the instructions comprise instructions to:
receive implicit function values at nodes of a coarse mesh of a region of interest in a geologic environment;
receive data;
formulate constraints based at least in part on the data;
solve a system of equations for a finer mesh subject to the constraints to provide a solution; and
output implicit function values at nodes of the finer mesh based at least in part on a solution the system of equations. 16. The system of claim 15 wherein the data comprise dip vectors. 17. The system of claim 15 wherein the data comprise attribute values. 18. One or more computer-readable storage media that comprise computer-executable instructions to instruct a computing device, the instructions comprising instructions to:
receive implicit function values at nodes of a coarse mesh of a region of interest in a geologic environment; receive data: formulate constraints based at least in part on the data; solve a system of equations for a finer mesh subject to the constraints to provide a solution; and output implicit function values at nodes of the finer mesh based at least in part on a solution the system of equations. 19. The one or more computer-readable storage media of claim 18 wherein the data comprise dip vectors. 20. The one or more computer-readable storage media of claim 18 wherein the data comprise attribute values. | A method can include receiving implicit function values at nodes of a coarse mesh of a region of interest in a geologic environment; receiving data: formulating constraints based at least in part on the data; solving a system of equations for a finer mesh subject to the constraints; and outputting implicit function values at nodes of the finer mesh based at least in part on solving the system of equations.1. A method comprising:
receiving implicit function values at nodes of a coarse mesh of a region of interest in a geologic environment; receiving data; formulating constraints based at least in part on the data; solving a system of equations for a finer mesh subject to the constraints; and outputting implicit function values at nodes of the finer mesh based at least in part on solving the system of equations. 2. The method of claim 1 wherein the solving comprises solving the system of equations for residual values. 3. The method of claim 1 comprising interpolating the implicit function values at the nodes of the coarse mesh to provide interpolated implicit function values at the nodes of the finer mesh. 4. The method of claim 3 wherein the outputting comprises adding the residual values and the interpolated implicit function values. 5. The method of claim 1 wherein the solving comprises using at least one processor. 6. The method of claim 1 wherein the implicit function values at the nodes of the finer mesh comprise stratigraphic function values. 7. The method of claim 1 wherein the data comprise dip vectors. 8. The method of claim 7 wherein the constraints comprise linear gradient constraints based at least in part on the dip vectors. 9. The method of claim 8 wherein the linear gradient constraints are formulated according to a Gram-Schmidt algorithm. 10. The method of claim 8 wherein the linear gradient constraints comprise weights. 11. The method of claim 10 wherein the weights correspond to quantifiable qualities of the dip vectors. 12. The method of claim 1 wherein the data comprise confidence values. 13. The method of claim 12 further comprising introducing weights based at least in part on the confidence values. 14. The method of claim 1 wherein the data comprise a spatial resolution for the region of interest that is higher than a spatial resolution for the nodes of the coarse mesh. 15. A system comprising:
a processor; memory operatively coupled to the processor; and one or more modules that comprise instructions stored in the memory and executable by the processor to instruct the system wherein the instructions comprise instructions to:
receive implicit function values at nodes of a coarse mesh of a region of interest in a geologic environment;
receive data;
formulate constraints based at least in part on the data;
solve a system of equations for a finer mesh subject to the constraints to provide a solution; and
output implicit function values at nodes of the finer mesh based at least in part on a solution the system of equations. 16. The system of claim 15 wherein the data comprise dip vectors. 17. The system of claim 15 wherein the data comprise attribute values. 18. One or more computer-readable storage media that comprise computer-executable instructions to instruct a computing device, the instructions comprising instructions to:
receive implicit function values at nodes of a coarse mesh of a region of interest in a geologic environment; receive data: formulate constraints based at least in part on the data; solve a system of equations for a finer mesh subject to the constraints to provide a solution; and output implicit function values at nodes of the finer mesh based at least in part on a solution the system of equations. 19. The one or more computer-readable storage media of claim 18 wherein the data comprise dip vectors. 20. The one or more computer-readable storage media of claim 18 wherein the data comprise attribute values. | 2,100 |
6,075 | 6,075 | 14,442,517 | 2,128 | A method of identifying an optimum treatment for a patient suffering from coronary artery disease, comprising: (i) providing patient information selected from: (a) status in the patient of one or more coronary disease associated biomarkers; (b) one or more items of medical history information selected from prior condition history, intervention history and medication history; (c) one or more items of diagnostic history, if the patient has a diagnostic history; and (d) one or more items of demographic data; (ii) aggregating the patient information in: (a) a Bayesian network; (b) a machine learning and neural network; (c) a rule-based system; and (d) a regression-based system; (iii) deriving a predicted probabilistic adverse event outcome for each intervention comprising percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting; and (iv) determining the intervention having the lowest predicted probabilistic adverse outcome. | 1. A method of identifying an optimum treatment for a patient suffering from coronary artery disease, the method comprising:
(i) providing one or more items of patient information selected from:
(A) status in the patient of one or more biomarkers associated with coronary heart disease;
(B) one or more items of medical history information of the patient selected from prior condition history, medical intervention history and medication history;
(C) one or more items of diagnostic history of the patient, if the patient has a diagnostic history; and
(D) one or more items of patient demographic data;
(ii) aggregating the patient information in:
(a) a Bayesian network;
(b) a machine learning and neural network;
(c) a rule-based system; and
(d) a regression-based system;
(iii) deriving a predicted probabilistic adverse event outcome for each intervention comprising percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting; and (iv) determining the intervention having the lowest predicted probabilistic adverse outcome. 2. The method of claim 1, wherein the lowest probabilistic adverse outcome is for percutaneous coronary intervention by placement of a drug-coated stent. 3. The method of claim 2, wherein the lowest probabilistic adverse outcome is for percutaneous coronary intervention by placement of a bare metal stent. 4. The method of claim 1, wherein the lowest probabilistic adverse outcome is for coronary artery bypass grafting. 5. The method of claim 1, wherein the lowest probabilistic adverse outcome is low probability of a major adverse cardiac event (MACE). 6. The method of claim 2, wherein the lowest probabilistic adverse outcome is low probability of a target vessel revascularization (TVR). 7. The method of claim 6, wherein the lowest probabilistic adverse outcome is low probability of a target vessel revascularization (TVR) and a low probability of a major adverse cardiac event (MACE). 8. The method of claim 1, wherein the biomarkers associated with coronary heart disease comprise one or more biomarkers selected from PIIINP, Tenascin-X, TIMP-1, MMP-3, MMP-9, fibrinogen, D-dimer, Activated protein C: C-inhibitor complex, tPA, IL-6, IL-1, IL-2, TNF, CRP, osteopontin, resistin, leptin, adiponectin, sCD28, sCD86, sCTLA-4, sVCAM-1, sICAM-1, endothelin-1, endthelin-, HDL, LDL, lipoprotein-A and apolipoprotein A/B. 9. A method of categorizing coronary artery disease in a patient, the method comprising:
(i) providing one or more items of patient information selected from:
(A) status in the patient of one or more biomarkers associated with coronary heart disease;
(B) one or more items of medical history information of the patient selected from prior condition history, medical intervention history and medication history;
(C) one or more items of diagnostic history of the patient, if the patient has a diagnostic history; and
(D) one or more items of patient demographic data;
(ii) aggregating the patient information in:
(a) a Bayesian network;
(b) a machine learning and neural network;
(c) a rule-based system; and
(d) a regression-based system;
(iii) deriving a predicted probabilistic adverse event outcome for each coronary intervention selected from a percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by a coronary artery bypass graft; and (iv) categorizing the coronary heart disease of the patient as most susceptible to treatment with percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting, according to the lowest probabilistic adverse outcome prediction outcome for each of coronary intervention. 10. The method of claim 9, wherein the lowest probabilistic adverse outcome is for percutaneous coronary intervention by placement of a bare metal stent. 11. The method of claim 9, wherein the lowest probabilistic adverse outcome is for percutaneous coronary intervention by placement of a drug-coated stent. 12. The method of claim 9, wherein the lowest probabilistic adverse outcome is a low probability of a major adverse cardiac event (MACE). 13. A method of treating a patient suffering from coronary artery disease, the patient having a plurality of biomarkers associated with coronary heart disease, a medical history, a diagnostic history and patient demographic data; the method comprising:
(i) providing one or more items of patient information selected from:
(A) status in the patient of one or more biomarkers associated with coronary heart disease;
(B) one or more items of medical history information of the patient selected from prior condition history, medical intervention history and medication history;
(C) one or more items of diagnostic history of the patient, if the patient has a diagnostic history; and
(D) one or more items of patient demographic data;
(ii) aggregating the patient information in:
(a) a Bayesian network;
(b) a machine learning and neural network;
(c) a rule-based system; and
(d) a regression-based system;
(iii) deriving a predicted probabilistic adverse event outcome for each of percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting; and (iv) initiating treatment of the patient with percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting, whichever has the lowest predicted probabilistic adverse outcome. 14. The method of claim 13, wherein the lowest probabilistic adverse outcome is for percutaneous coronary intervention by placement of a drug-coated stent. 15. The method of claim 13, wherein the lowest probabilistic adverse outcome is for percutaneous coronary intervention by placement of a bare metal stent. 16. The method of claim 14, wherein the lowest probabilistic adverse outcome is for coronary artery bypass grafting. 17. The method of claim 13, wherein the lowest probabilistic adverse outcome is a low probability of a major adverse cardiac event (MACE). 18. The method of claim 14, wherein the lowest probabilistic adverse outcome is a low probability of a target vessel revascularization (TVR). 19. The method of claim 18, wherein the lowest probabilistic adverse outcome is a low probability of a target vessel revascularization (TVR) and a low probability of a major adverse cardiac event (MACE). 20. The method of claim 13, wherein the biomarkers associated with coronary heart disease comprise one or more biomarkers selected from PIIINP, Tenascin-X, TIMP-1, MMP-3, MMP-9, fibrinogen, D-dimer, Activated protein C: C-inhibitor complex, tPA, IL-6, IL-1, IL-2, TNF, CRP, osteopontin, resistin, leptin, adiponectin, sCD28, sCD86, sCTLA-4, sVCAM-1, sICAM-1, endothelin-1, endthelin-2, HDL, LDL, lipoprotein-A and apolipoprotein A/B. | A method of identifying an optimum treatment for a patient suffering from coronary artery disease, comprising: (i) providing patient information selected from: (a) status in the patient of one or more coronary disease associated biomarkers; (b) one or more items of medical history information selected from prior condition history, intervention history and medication history; (c) one or more items of diagnostic history, if the patient has a diagnostic history; and (d) one or more items of demographic data; (ii) aggregating the patient information in: (a) a Bayesian network; (b) a machine learning and neural network; (c) a rule-based system; and (d) a regression-based system; (iii) deriving a predicted probabilistic adverse event outcome for each intervention comprising percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting; and (iv) determining the intervention having the lowest predicted probabilistic adverse outcome.1. A method of identifying an optimum treatment for a patient suffering from coronary artery disease, the method comprising:
(i) providing one or more items of patient information selected from:
(A) status in the patient of one or more biomarkers associated with coronary heart disease;
(B) one or more items of medical history information of the patient selected from prior condition history, medical intervention history and medication history;
(C) one or more items of diagnostic history of the patient, if the patient has a diagnostic history; and
(D) one or more items of patient demographic data;
(ii) aggregating the patient information in:
(a) a Bayesian network;
(b) a machine learning and neural network;
(c) a rule-based system; and
(d) a regression-based system;
(iii) deriving a predicted probabilistic adverse event outcome for each intervention comprising percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting; and (iv) determining the intervention having the lowest predicted probabilistic adverse outcome. 2. The method of claim 1, wherein the lowest probabilistic adverse outcome is for percutaneous coronary intervention by placement of a drug-coated stent. 3. The method of claim 2, wherein the lowest probabilistic adverse outcome is for percutaneous coronary intervention by placement of a bare metal stent. 4. The method of claim 1, wherein the lowest probabilistic adverse outcome is for coronary artery bypass grafting. 5. The method of claim 1, wherein the lowest probabilistic adverse outcome is low probability of a major adverse cardiac event (MACE). 6. The method of claim 2, wherein the lowest probabilistic adverse outcome is low probability of a target vessel revascularization (TVR). 7. The method of claim 6, wherein the lowest probabilistic adverse outcome is low probability of a target vessel revascularization (TVR) and a low probability of a major adverse cardiac event (MACE). 8. The method of claim 1, wherein the biomarkers associated with coronary heart disease comprise one or more biomarkers selected from PIIINP, Tenascin-X, TIMP-1, MMP-3, MMP-9, fibrinogen, D-dimer, Activated protein C: C-inhibitor complex, tPA, IL-6, IL-1, IL-2, TNF, CRP, osteopontin, resistin, leptin, adiponectin, sCD28, sCD86, sCTLA-4, sVCAM-1, sICAM-1, endothelin-1, endthelin-, HDL, LDL, lipoprotein-A and apolipoprotein A/B. 9. A method of categorizing coronary artery disease in a patient, the method comprising:
(i) providing one or more items of patient information selected from:
(A) status in the patient of one or more biomarkers associated with coronary heart disease;
(B) one or more items of medical history information of the patient selected from prior condition history, medical intervention history and medication history;
(C) one or more items of diagnostic history of the patient, if the patient has a diagnostic history; and
(D) one or more items of patient demographic data;
(ii) aggregating the patient information in:
(a) a Bayesian network;
(b) a machine learning and neural network;
(c) a rule-based system; and
(d) a regression-based system;
(iii) deriving a predicted probabilistic adverse event outcome for each coronary intervention selected from a percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by a coronary artery bypass graft; and (iv) categorizing the coronary heart disease of the patient as most susceptible to treatment with percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting, according to the lowest probabilistic adverse outcome prediction outcome for each of coronary intervention. 10. The method of claim 9, wherein the lowest probabilistic adverse outcome is for percutaneous coronary intervention by placement of a bare metal stent. 11. The method of claim 9, wherein the lowest probabilistic adverse outcome is for percutaneous coronary intervention by placement of a drug-coated stent. 12. The method of claim 9, wherein the lowest probabilistic adverse outcome is a low probability of a major adverse cardiac event (MACE). 13. A method of treating a patient suffering from coronary artery disease, the patient having a plurality of biomarkers associated with coronary heart disease, a medical history, a diagnostic history and patient demographic data; the method comprising:
(i) providing one or more items of patient information selected from:
(A) status in the patient of one or more biomarkers associated with coronary heart disease;
(B) one or more items of medical history information of the patient selected from prior condition history, medical intervention history and medication history;
(C) one or more items of diagnostic history of the patient, if the patient has a diagnostic history; and
(D) one or more items of patient demographic data;
(ii) aggregating the patient information in:
(a) a Bayesian network;
(b) a machine learning and neural network;
(c) a rule-based system; and
(d) a regression-based system;
(iii) deriving a predicted probabilistic adverse event outcome for each of percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting; and (iv) initiating treatment of the patient with percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting, whichever has the lowest predicted probabilistic adverse outcome. 14. The method of claim 13, wherein the lowest probabilistic adverse outcome is for percutaneous coronary intervention by placement of a drug-coated stent. 15. The method of claim 13, wherein the lowest probabilistic adverse outcome is for percutaneous coronary intervention by placement of a bare metal stent. 16. The method of claim 14, wherein the lowest probabilistic adverse outcome is for coronary artery bypass grafting. 17. The method of claim 13, wherein the lowest probabilistic adverse outcome is a low probability of a major adverse cardiac event (MACE). 18. The method of claim 14, wherein the lowest probabilistic adverse outcome is a low probability of a target vessel revascularization (TVR). 19. The method of claim 18, wherein the lowest probabilistic adverse outcome is a low probability of a target vessel revascularization (TVR) and a low probability of a major adverse cardiac event (MACE). 20. The method of claim 13, wherein the biomarkers associated with coronary heart disease comprise one or more biomarkers selected from PIIINP, Tenascin-X, TIMP-1, MMP-3, MMP-9, fibrinogen, D-dimer, Activated protein C: C-inhibitor complex, tPA, IL-6, IL-1, IL-2, TNF, CRP, osteopontin, resistin, leptin, adiponectin, sCD28, sCD86, sCTLA-4, sVCAM-1, sICAM-1, endothelin-1, endthelin-2, HDL, LDL, lipoprotein-A and apolipoprotein A/B. | 2,100 |
6,076 | 6,076 | 15,431,998 | 2,164 | An aggregate display of contact data from internal and external sources is provided. Contact data associated with at least one contact is obtained from a plurality of sources, including at least an internal source and an external source. The obtained contact data is processed to generate an aggregated collection of contact data. The aggregated collection of contact data is stored. A display of the aggregated collection of contact data is displayed in a single, interactive interface. | 1. A method for aggregating contact data of a user, comprising:
obtaining contact data associated with at least one contact from a plurality of sources, including at least an internal source and an external source; processing the obtained contact data to generate an aggregated collection of contact data; storing the aggregated collection of contact data; and accessing the memory and presenting a display of the aggregated collection of contact data in a single, interactive interface. 2. The method of claim 1, wherein the obtaining contact data from the internal source includes obtaining contact data from an active directory, a global address list (GAL), local personal information manager contacts, and web application contacts. 3. The method of claim 1, wherein the obtaining contact data from the external source includes obtaining contact data from a third party service capable of integrating contact data into the aggregated collection of contact data. 4. The method of claim 1, wherein the obtaining contact data from the external source includes obtaining contact data from social and business networking sites. 5. The method of claim 1, wherein the processing the obtained contact data to generate the aggregated collection of contact data comprises processing contact data entered and stored by the user, contact data entered and published by the at least one contact, and contact data maintained externally. 6. The method of claim 1, wherein the obtaining contact data associated with at least one contact from the plurality of sources comprises updating contact data when the external source changes contact data at the external source. 7. The method of claim 1, wherein the processing the obtained contact data to generate the aggregated collection of contact data further comprises defining a set of contact data associated with the at least one contact to show in aggregate. 8. The method of claim 1, wherein the obtaining contact data associated with the at least one contact from the plurality of sources further comprises receiving input from the user identifying contact data to obtain from each source compatible with the predetermined contact schema. 9. The method of claim 1, wherein the processing the obtained contact data to generate the aggregated collection of contact data further comprises receiving a user-defined preference order for sources and providing the aggregated collection of contact data for presentation in ranked order according to the user defined preference order in the display of the aggregated collection of contact data in the single, interactive interface. 10. The method of claim 1, wherein the obtaining contact data associated with at least one contact from the plurality of sources further comprises retrieving a profile for each source listed as a profile property when contact data from at least one source is not aggregated to allow the user to search the source for the unaggregated contact data for additional information. 11. The method of claim 1, wherein the accessing the aggregated collection of contact data to present the display of the aggregated collection of contact data in the single, interactive interface further comprises displaying at least one source of contact data with an indication showing where the source of the contact data 12. A system for aggregating contact data of a user, comprising:
memory for storing data; and a processor, coupled to the memory, the processor configured to obtain the contact data associated with at least one contact from a plurality of sources, including at least an internal source and an external source, to process the obtained contact data to generate an aggregated collection of contact data, to store the aggregated collection of contact data and to present a display of the aggregated collection of contact data in a single, interactive interface. 13. The system of claim 12, wherein the contact data from the internal source includes an active directory, a global address list (GAL), local personal information managed contacts, and web application contacts and wherein the contact data from the external source includes the contact data from a third party service capable of integrating contact data into the aggregated collection of contact data. 14. The system of claim 12, wherein the contact data comprises the contact data entered and stored by the user, contact data entered and published by the at least one contact, and the contact data maintained externally. 15. The system of claim 12, wherein the processor monitors the plurality of sources to update the contact data when a source changes the contact data. 16. The system of claim 12, wherein the processing obtains the contact data based on a user-defined set of contact data compatible with a predetermined contact schema. 17. The system of claim 12, wherein the processor generates the aggregated collection of contact data according to a user-defined preference order for sources. 18. The system of claim 12, wherein the processor retrieves a profile for each source listed as a profile property when the contact data from at least one source is not aggregated to allow the user to search the source for the unaggregated contact data for additional information. 19. The system of claim 12, wherein the processor presents the display of the aggregated collection of contact data in the single, interactive interface, wherein at least one source of contact data in the display with an indication showing where the source of the contact data 20. A computer-readable storage medium including executable instructions which, when executed by a processor, aggregates contact data of a user, by:
obtaining contact data associated with at least one contact from a plurality of sources, including at least an internal source and an external source; processing the obtained contact data to generate an aggregated collection of contact data; storing the aggregated collection of contact data; and accessing the aggregated collection of contact data to present a display of the aggregated collection of contact data in a single, interactive interface. | An aggregate display of contact data from internal and external sources is provided. Contact data associated with at least one contact is obtained from a plurality of sources, including at least an internal source and an external source. The obtained contact data is processed to generate an aggregated collection of contact data. The aggregated collection of contact data is stored. A display of the aggregated collection of contact data is displayed in a single, interactive interface.1. A method for aggregating contact data of a user, comprising:
obtaining contact data associated with at least one contact from a plurality of sources, including at least an internal source and an external source; processing the obtained contact data to generate an aggregated collection of contact data; storing the aggregated collection of contact data; and accessing the memory and presenting a display of the aggregated collection of contact data in a single, interactive interface. 2. The method of claim 1, wherein the obtaining contact data from the internal source includes obtaining contact data from an active directory, a global address list (GAL), local personal information manager contacts, and web application contacts. 3. The method of claim 1, wherein the obtaining contact data from the external source includes obtaining contact data from a third party service capable of integrating contact data into the aggregated collection of contact data. 4. The method of claim 1, wherein the obtaining contact data from the external source includes obtaining contact data from social and business networking sites. 5. The method of claim 1, wherein the processing the obtained contact data to generate the aggregated collection of contact data comprises processing contact data entered and stored by the user, contact data entered and published by the at least one contact, and contact data maintained externally. 6. The method of claim 1, wherein the obtaining contact data associated with at least one contact from the plurality of sources comprises updating contact data when the external source changes contact data at the external source. 7. The method of claim 1, wherein the processing the obtained contact data to generate the aggregated collection of contact data further comprises defining a set of contact data associated with the at least one contact to show in aggregate. 8. The method of claim 1, wherein the obtaining contact data associated with the at least one contact from the plurality of sources further comprises receiving input from the user identifying contact data to obtain from each source compatible with the predetermined contact schema. 9. The method of claim 1, wherein the processing the obtained contact data to generate the aggregated collection of contact data further comprises receiving a user-defined preference order for sources and providing the aggregated collection of contact data for presentation in ranked order according to the user defined preference order in the display of the aggregated collection of contact data in the single, interactive interface. 10. The method of claim 1, wherein the obtaining contact data associated with at least one contact from the plurality of sources further comprises retrieving a profile for each source listed as a profile property when contact data from at least one source is not aggregated to allow the user to search the source for the unaggregated contact data for additional information. 11. The method of claim 1, wherein the accessing the aggregated collection of contact data to present the display of the aggregated collection of contact data in the single, interactive interface further comprises displaying at least one source of contact data with an indication showing where the source of the contact data 12. A system for aggregating contact data of a user, comprising:
memory for storing data; and a processor, coupled to the memory, the processor configured to obtain the contact data associated with at least one contact from a plurality of sources, including at least an internal source and an external source, to process the obtained contact data to generate an aggregated collection of contact data, to store the aggregated collection of contact data and to present a display of the aggregated collection of contact data in a single, interactive interface. 13. The system of claim 12, wherein the contact data from the internal source includes an active directory, a global address list (GAL), local personal information managed contacts, and web application contacts and wherein the contact data from the external source includes the contact data from a third party service capable of integrating contact data into the aggregated collection of contact data. 14. The system of claim 12, wherein the contact data comprises the contact data entered and stored by the user, contact data entered and published by the at least one contact, and the contact data maintained externally. 15. The system of claim 12, wherein the processor monitors the plurality of sources to update the contact data when a source changes the contact data. 16. The system of claim 12, wherein the processing obtains the contact data based on a user-defined set of contact data compatible with a predetermined contact schema. 17. The system of claim 12, wherein the processor generates the aggregated collection of contact data according to a user-defined preference order for sources. 18. The system of claim 12, wherein the processor retrieves a profile for each source listed as a profile property when the contact data from at least one source is not aggregated to allow the user to search the source for the unaggregated contact data for additional information. 19. The system of claim 12, wherein the processor presents the display of the aggregated collection of contact data in the single, interactive interface, wherein at least one source of contact data in the display with an indication showing where the source of the contact data 20. A computer-readable storage medium including executable instructions which, when executed by a processor, aggregates contact data of a user, by:
obtaining contact data associated with at least one contact from a plurality of sources, including at least an internal source and an external source; processing the obtained contact data to generate an aggregated collection of contact data; storing the aggregated collection of contact data; and accessing the aggregated collection of contact data to present a display of the aggregated collection of contact data in a single, interactive interface. | 2,100 |
6,077 | 6,077 | 14,521,091 | 2,122 | Methods, systems and computer program products to measure the adaptability of complex systems, including systems of systems, are disclosed. The methods, systems and computer program products provide rigor and defensibility to the analysis and assessment of adaptability. As a result, systems can be designed or acquired that are intrinsically more adaptable and better able to respond to changing environments. | 1. A method for assessing system adaptability, comprising:
a) define a problem having a design and a scenario; b) choose one or more metrics; c) select one or more measures for the one or more chosen metrics; d) evaluate the one or more measures for the design and scenario; e) redefine design; f) repeat steps a through e to create one or more designs; g) compare the one or more designs; and h) select a final design from the one or more designs for recommendation. 2. The method of claim 1, wherein comparing the one or more designs comprises creating an adaptability index form the selected for the one or more designs. 3. The method of claim 1, wherein the one or more metrics is selected from a group consisting essentially of mobility, logistics capability, modifiability, modularity, diversity, substitutability, storage, integratability, self-organizing ability, scalability, complexity, system redundancy, overdesign, repairability, and durability. 4. The method of claim 3, wherein the adaptability metric is modifiability and the selected measure is selected from a group consisting essentially of number of changes to a system, number of changes in system types, average time it takes to replace a system, and number of possible system changes. 5. The method of claim 3, wherein the adaptability metric is modularity and the selected measure is measured by the number of different systems in the system. 6. The method of claim 3, wherein the adaptability metric is modularity and the selected measure is measured by breaking a system of systems into different functional collections and determining an average number of system types per functional collection. 7. The method of claim 3, wherein the adaptability metric is diversity and diversity measure is calculated by the following formula:
diversity_measure
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. 8. The method of claim 3, wherein the adaptability metric is substitutability and the selected measure is selected from a group consisting essentially of quantity of replacement parts, consumables and systems kept on hand. 9. The method of claim 3, wherein the adaptability metric is storage and the selected measure is selected from a group consisting essentially of fraction of spare parts or consumables stored, the average inventory of spare parts or consumables, the ratio of the usage rate of spare parts or consumables to the storage capacity for them, and the storage utilization. 10. The method of claim 3, wherein the adaptability metric is integratability and the selected measure is selected from a group consisting essentially of a degree of standardization, the amount of change needed to a system, and the ability for resources to switch from one type of system to another or to add or subtract systems. 11. The method of claim 3, wherein the adaptability metric is self-organizing ability and the selected measure is selected from a group consisting essentially of the degree of hierarchy or decentralization, the number of strategies that the system uses to respond to needs are a reflection of the ability to self-organize, and the average strength ratio. 12. The method of claim 3, wherein the adaptability metric is scalability and the selected measure is selected from a group consisting essentially of overhead change and efficiency change per unit as the number of units increases. 13. The method of claim 3, wherein the adaptability metric is complexity and the selected measure is selected from a group consisting essentially of nodes, number of connections, number of connections per node, number of dependents, and path length. 14. The method of claim 3, wherein the adaptability metric is system redundancy and the selected measure is selected from a group consisting essentially of the fraction of systems that are redundant or that have backups and possible substitutes. 15. The method of claim 3, wherein the adaptability metric is overdesign and the selected measure is selected from a group consisting essentially of the amount of excess capacity and the average time that the overall system goes without change. 16. The method of claim 3, wherein the adaptability metric is repairability and the selected measure is the mean time to repair. 17. The method of claim 3, wherein the adaptability metric is durability and the selected measure is selected from a group consisting essentially of system lifetime, mean time between failures, and mean downtime. 18. A system comprising a non-transitory computer readable storage medium encoded with programming for interactively analyzing system adaptability, the non-transitory computer readable medium with programming configured to:
a) receive input data that defines a problem having a design and a scenario; b) choose one or more metrics; c) select one or more measures for the one or more chosen metrics; d) evaluate measures for the design and scenario e) receive redefined design input data; f) repeating steps a through e to create evaluation measures for one or more designs. 19. The system of claim 18, wherein evaluating measures comprises creating an adaptability index form the selected measures. 20. The system of claim 18, wherein the one or more metrics is selected from a group consisting essentially of mobility, logistics capability, modifiability, modularity, diversity, substitutability, storage, integratability, self-organizing ability, scalability, complexity, system redundancy, overdesign, repairability, and durability. 21. A computer program product stored on a non-transitory computer readable medium, wherein executed by a process, the computer program product is configured to:
a) receive input data that defines a problem having a design and a scenario; b) choose one or more metrics; c) select one or more measures for the one or more chosen metrics; d) evaluate measures for the design and scenario e) receive redefined design input data; f) repeating steps a through e to create evaluation measures for one or more designs. 22. The computer program product of claim 21, wherein evaluating measures comprises creating an adaptability index form the selected measures. 23. The computer program product of claim 21, wherein the one or more metrics is selected from a group consisting essentially of mobility, logistics capability, modifiability, modularity, diversity, substitutability, storage, integratability, self-organizing ability, scalability, complexity, system redundancy, overdesign, repairability, and durability. | Methods, systems and computer program products to measure the adaptability of complex systems, including systems of systems, are disclosed. The methods, systems and computer program products provide rigor and defensibility to the analysis and assessment of adaptability. As a result, systems can be designed or acquired that are intrinsically more adaptable and better able to respond to changing environments.1. A method for assessing system adaptability, comprising:
a) define a problem having a design and a scenario; b) choose one or more metrics; c) select one or more measures for the one or more chosen metrics; d) evaluate the one or more measures for the design and scenario; e) redefine design; f) repeat steps a through e to create one or more designs; g) compare the one or more designs; and h) select a final design from the one or more designs for recommendation. 2. The method of claim 1, wherein comparing the one or more designs comprises creating an adaptability index form the selected for the one or more designs. 3. The method of claim 1, wherein the one or more metrics is selected from a group consisting essentially of mobility, logistics capability, modifiability, modularity, diversity, substitutability, storage, integratability, self-organizing ability, scalability, complexity, system redundancy, overdesign, repairability, and durability. 4. The method of claim 3, wherein the adaptability metric is modifiability and the selected measure is selected from a group consisting essentially of number of changes to a system, number of changes in system types, average time it takes to replace a system, and number of possible system changes. 5. The method of claim 3, wherein the adaptability metric is modularity and the selected measure is measured by the number of different systems in the system. 6. The method of claim 3, wherein the adaptability metric is modularity and the selected measure is measured by breaking a system of systems into different functional collections and determining an average number of system types per functional collection. 7. The method of claim 3, wherein the adaptability metric is diversity and diversity measure is calculated by the following formula:
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. 8. The method of claim 3, wherein the adaptability metric is substitutability and the selected measure is selected from a group consisting essentially of quantity of replacement parts, consumables and systems kept on hand. 9. The method of claim 3, wherein the adaptability metric is storage and the selected measure is selected from a group consisting essentially of fraction of spare parts or consumables stored, the average inventory of spare parts or consumables, the ratio of the usage rate of spare parts or consumables to the storage capacity for them, and the storage utilization. 10. The method of claim 3, wherein the adaptability metric is integratability and the selected measure is selected from a group consisting essentially of a degree of standardization, the amount of change needed to a system, and the ability for resources to switch from one type of system to another or to add or subtract systems. 11. The method of claim 3, wherein the adaptability metric is self-organizing ability and the selected measure is selected from a group consisting essentially of the degree of hierarchy or decentralization, the number of strategies that the system uses to respond to needs are a reflection of the ability to self-organize, and the average strength ratio. 12. The method of claim 3, wherein the adaptability metric is scalability and the selected measure is selected from a group consisting essentially of overhead change and efficiency change per unit as the number of units increases. 13. The method of claim 3, wherein the adaptability metric is complexity and the selected measure is selected from a group consisting essentially of nodes, number of connections, number of connections per node, number of dependents, and path length. 14. The method of claim 3, wherein the adaptability metric is system redundancy and the selected measure is selected from a group consisting essentially of the fraction of systems that are redundant or that have backups and possible substitutes. 15. The method of claim 3, wherein the adaptability metric is overdesign and the selected measure is selected from a group consisting essentially of the amount of excess capacity and the average time that the overall system goes without change. 16. The method of claim 3, wherein the adaptability metric is repairability and the selected measure is the mean time to repair. 17. The method of claim 3, wherein the adaptability metric is durability and the selected measure is selected from a group consisting essentially of system lifetime, mean time between failures, and mean downtime. 18. A system comprising a non-transitory computer readable storage medium encoded with programming for interactively analyzing system adaptability, the non-transitory computer readable medium with programming configured to:
a) receive input data that defines a problem having a design and a scenario; b) choose one or more metrics; c) select one or more measures for the one or more chosen metrics; d) evaluate measures for the design and scenario e) receive redefined design input data; f) repeating steps a through e to create evaluation measures for one or more designs. 19. The system of claim 18, wherein evaluating measures comprises creating an adaptability index form the selected measures. 20. The system of claim 18, wherein the one or more metrics is selected from a group consisting essentially of mobility, logistics capability, modifiability, modularity, diversity, substitutability, storage, integratability, self-organizing ability, scalability, complexity, system redundancy, overdesign, repairability, and durability. 21. A computer program product stored on a non-transitory computer readable medium, wherein executed by a process, the computer program product is configured to:
a) receive input data that defines a problem having a design and a scenario; b) choose one or more metrics; c) select one or more measures for the one or more chosen metrics; d) evaluate measures for the design and scenario e) receive redefined design input data; f) repeating steps a through e to create evaluation measures for one or more designs. 22. The computer program product of claim 21, wherein evaluating measures comprises creating an adaptability index form the selected measures. 23. The computer program product of claim 21, wherein the one or more metrics is selected from a group consisting essentially of mobility, logistics capability, modifiability, modularity, diversity, substitutability, storage, integratability, self-organizing ability, scalability, complexity, system redundancy, overdesign, repairability, and durability. | 2,100 |
6,078 | 6,078 | 15,400,265 | 2,136 | A replica control system includes software to control replication in virtual environments. The replica control system identifies a plurality of data blocks within an underlying storage volume in response to a request to update a replica of a target storage volume, identifies changed data blocks of the plurality of data blocks within the underlying storage volume, and identifies a subset of the changed data blocks with which to update the replica of the target storage volume based on a characteristic of the changed data blocks. | 1. A computer readable medium having program instructions stored thereon that, when executed by a replica control system, direct the replica control system to:
in response to a request to update a replica of a target storage volume, identify a plurality of data blocks within an underlying storage volume that underlies the target storage volume; identify changed data blocks of the plurality of data blocks within the underlying storage volume; and identify a subset of the changed data blocks, each data block of the subset having a specified characteristic, with which to update the replica of the target storage volume. 2. The computer readable medium of claim 1 wherein the characteristic of each of the changed data blocks comprises an allocation status of each of the changed data blocks. 3. The computer readable medium of claim 1 wherein the characteristic of each of the changed data blocks comprises a transient status of each of the changed data blocks. 4. The computer readable medium of claim 1 wherein the characteristic of each of the changed data blocks comprises a similarity of each of the changed data blocks relative to other changed data blocks, wherein the other changed data blocks are associated with another plurality of data blocks within another underlying storage volume. 5. The computer readable medium of claim 5 wherein the similarity is based on an analysis of fingerprints of each of the changed data blocks and the other changed data blocks. 6. The computer readable medium of claim 5 wherein the programming instructions, when executed by the replica control system, further direct the replica control system to generate an instruction for delivery to a replica virtual machine environment, wherein the instruction indicates the similarity of one or more of the each of the changed data blocks relative to the other changed data blocks. 7. The computer readable medium of claim 1 wherein the target storage volume comprises an enumeration of a virtual machine environment and the underlying storage volume comprises a virtual disk file contained within the virtual machine environment. 8. The computer readable medium of claim 1 wherein the target storage volume comprises a virtual disk file and the underlying storage volume comprises a hard disk drive upon which the virtual disk file is stored. 9. The computer readable medium of claim 1 wherein the underlying storage volume comprises a virtual disk file and the target storage volume comprises a virtual drive contained within the virtual disk file. 10. A replica control system comprising:
a communication interface configured to receive a request to update a replica of a target storage volume, and transfer an identified subset of changed data blocks of a plurality of data blocks within an underlying storage volume that underlies the target storage volume; and a processing system configured to identify the plurality of data blocks within the underlying storage volume in response to receiving the request to update the replica of the target storage volume, identify the changed data blocks of the plurality of data blocks within the underlying storage volume, and identify the subset of the changed data blocks, each data block of the subset having a specified characteristic, with which to update the replica of the target storage volume. 11. The replica control system of claim 10 wherein the characteristic of the changed data blocks comprises an allocation status of each of the changed data blocks. 12. The replica control system of claim 10 wherein the characteristic of each of the changed data blocks comprises a transient status of each of the changed data blocks. 13. The replica control system of claim 10 wherein the characteristic of each of the changed data blocks comprises a similarity of each of the changed data blocks relative to other changed data blocks, wherein the other changed data blocks are associated with another plurality of data blocks within another underlying storage volume. 14. The replica control system of claim 13 wherein the similarity is based on an analysis of fingerprints of the changed data blocks and the other changed data blocks. 15. The replica control system of claim 14 wherein the processing system is further configured to direct the replica control system to generate an instruction for delivery to a replica virtual machine environment, wherein the instruction indicates the similarity of one or more of the each of the changed data blocks relative to the other changed data blocks. 16. The replica control system of claim 10 wherein the target storage volume comprises an enumeration of a virtual machine environment and the underlying storage volume comprises a virtual disk file contained within the virtual machine environment. 17. The replica control system of claim 10 wherein the target storage volume comprises a virtual disk file and the underlying storage volume comprises a hard disk drive upon which the virtual disk file is stored. 18. The replica control system of claim 10 wherein the underlying storage volume comprises a virtual disk file and the target storage volume comprises a virtual drive contained within the virtual disk file. 19. A method comprising:
identifying a plurality of data blocks within an underlying storage volume that underlies a target storage volume in response to a request to update a replica of the target storage volume; identifying changed data blocks of the plurality of data blocks within the underlying storage volume; and identifying a subset of the changed data blocks, each data block of the subset having a specified characteristic, with which to update the replica of the target storage volume. | A replica control system includes software to control replication in virtual environments. The replica control system identifies a plurality of data blocks within an underlying storage volume in response to a request to update a replica of a target storage volume, identifies changed data blocks of the plurality of data blocks within the underlying storage volume, and identifies a subset of the changed data blocks with which to update the replica of the target storage volume based on a characteristic of the changed data blocks.1. A computer readable medium having program instructions stored thereon that, when executed by a replica control system, direct the replica control system to:
in response to a request to update a replica of a target storage volume, identify a plurality of data blocks within an underlying storage volume that underlies the target storage volume; identify changed data blocks of the plurality of data blocks within the underlying storage volume; and identify a subset of the changed data blocks, each data block of the subset having a specified characteristic, with which to update the replica of the target storage volume. 2. The computer readable medium of claim 1 wherein the characteristic of each of the changed data blocks comprises an allocation status of each of the changed data blocks. 3. The computer readable medium of claim 1 wherein the characteristic of each of the changed data blocks comprises a transient status of each of the changed data blocks. 4. The computer readable medium of claim 1 wherein the characteristic of each of the changed data blocks comprises a similarity of each of the changed data blocks relative to other changed data blocks, wherein the other changed data blocks are associated with another plurality of data blocks within another underlying storage volume. 5. The computer readable medium of claim 5 wherein the similarity is based on an analysis of fingerprints of each of the changed data blocks and the other changed data blocks. 6. The computer readable medium of claim 5 wherein the programming instructions, when executed by the replica control system, further direct the replica control system to generate an instruction for delivery to a replica virtual machine environment, wherein the instruction indicates the similarity of one or more of the each of the changed data blocks relative to the other changed data blocks. 7. The computer readable medium of claim 1 wherein the target storage volume comprises an enumeration of a virtual machine environment and the underlying storage volume comprises a virtual disk file contained within the virtual machine environment. 8. The computer readable medium of claim 1 wherein the target storage volume comprises a virtual disk file and the underlying storage volume comprises a hard disk drive upon which the virtual disk file is stored. 9. The computer readable medium of claim 1 wherein the underlying storage volume comprises a virtual disk file and the target storage volume comprises a virtual drive contained within the virtual disk file. 10. A replica control system comprising:
a communication interface configured to receive a request to update a replica of a target storage volume, and transfer an identified subset of changed data blocks of a plurality of data blocks within an underlying storage volume that underlies the target storage volume; and a processing system configured to identify the plurality of data blocks within the underlying storage volume in response to receiving the request to update the replica of the target storage volume, identify the changed data blocks of the plurality of data blocks within the underlying storage volume, and identify the subset of the changed data blocks, each data block of the subset having a specified characteristic, with which to update the replica of the target storage volume. 11. The replica control system of claim 10 wherein the characteristic of the changed data blocks comprises an allocation status of each of the changed data blocks. 12. The replica control system of claim 10 wherein the characteristic of each of the changed data blocks comprises a transient status of each of the changed data blocks. 13. The replica control system of claim 10 wherein the characteristic of each of the changed data blocks comprises a similarity of each of the changed data blocks relative to other changed data blocks, wherein the other changed data blocks are associated with another plurality of data blocks within another underlying storage volume. 14. The replica control system of claim 13 wherein the similarity is based on an analysis of fingerprints of the changed data blocks and the other changed data blocks. 15. The replica control system of claim 14 wherein the processing system is further configured to direct the replica control system to generate an instruction for delivery to a replica virtual machine environment, wherein the instruction indicates the similarity of one or more of the each of the changed data blocks relative to the other changed data blocks. 16. The replica control system of claim 10 wherein the target storage volume comprises an enumeration of a virtual machine environment and the underlying storage volume comprises a virtual disk file contained within the virtual machine environment. 17. The replica control system of claim 10 wherein the target storage volume comprises a virtual disk file and the underlying storage volume comprises a hard disk drive upon which the virtual disk file is stored. 18. The replica control system of claim 10 wherein the underlying storage volume comprises a virtual disk file and the target storage volume comprises a virtual drive contained within the virtual disk file. 19. A method comprising:
identifying a plurality of data blocks within an underlying storage volume that underlies a target storage volume in response to a request to update a replica of the target storage volume; identifying changed data blocks of the plurality of data blocks within the underlying storage volume; and identifying a subset of the changed data blocks, each data block of the subset having a specified characteristic, with which to update the replica of the target storage volume. | 2,100 |
6,079 | 6,079 | 15,655,598 | 2,113 | A computer-implemented method, according to one embodiment, includes: storing information in a specified system memory location, attaching an external process to the specified system memory location in response to experiencing a system halt event, sending the information stored in the specified system memory location to a memory location associated with the external process, restarting the system in a recovery mode, retrieving the information from the external process, and using the retrieved information to restore the system to a state the system was in when the system halt event occurred. Other systems, methods, and computer program products are described in additional embodiments. | 1. A computer-implemented method, comprising:
storing information in a specified system memory location; attaching an external process to the specified system memory location in response to experiencing a system halt event; sending the information stored in the specified system memory location to a memory location associated with the external process; restarting the system in a recovery mode; retrieving the information from the external process; and using the retrieved information to restore the system to a state the system was in when the system halt event occurred. 2. The computer-implemented method of claim 1, wherein the system is a data storage system. 3. The computer-implemented method of claim 1, wherein the system is an operating system configured to run one or more processes. 4. The computer-implemented method of claim 1, wherein the specified system memory location is in random access memory. 5. The computer-implemented method of claim 1, wherein the information includes data and metadata. 6. The computer-implemented method of claim 5, wherein using the retrieved information to restore the system includes:
loading metadata into the specified system memory location; loading data into random access memory; and playing back the data as input/output operations performed on the system. 7. The computer-implemented method of claim 1, wherein retrieving the information from the external process includes:
determining whether any inconsistencies exist in the retrieved information; and creating an improved version of the retrieved information in response to determining that an inconsistency does exist in the retrieved information, wherein the improved version of the retrieved information is used to restore the system. 8. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions readable and/or executable by a processor to cause the processor to perform a method comprising:
storing, by the processor, information in a specified system memory location; attaching, by the processor, an external process to the specified system memory location in response to experiencing a system halt event; sending, by the processor, the information stored in the specified system memory location to a memory location associated with the external process; restarting, by the processor, the system in a recovery mode; retrieving, by the processor, the information from the external process; and using, by the processor, the retrieved information to restore the system to a state the system was in when the system halt event occurred. 9. The computer program product of claim 8, wherein the system is a data storage system. 10. The computer program product of claim 8, wherein the system is an operating system configured to run one or more processes. 11. The computer program product of claim 8, wherein the specified system memory location is in random access memory. 12. The computer program product of claim 8, wherein the information includes data and metadata. 13. The computer program product of claim 12, wherein using the retrieved information to restore the system includes:
loading, by the processor, metadata into the specified system memory location; loading, by the processor, data into random access memory; and playing, by the processor, back the data as input/output operations performed on the system. 14. The computer program product of claim 8, wherein retrieving the information from the external process includes:
determining, by the processor, whether any inconsistencies exist in the retrieved information; and creating, by the processor, an improved version of the retrieved information in response to determining that an inconsistency does exist in the retrieved information, wherein the improved version of the retrieved information is used to restore the system. 15. A computer-implemented method, comprising:
attaching to a specified system memory location in response to detecting that a system halt event occurred at the system; extracting information stored in the specified system memory location; storing the information in local memory; and sending the information back to the specified system memory location in response to detecting that the system has been restarted in a recovery mode. 16. The computer-implemented method of claim 15, wherein the information includes data and metadata. 17. The computer-implemented method of claim 15, wherein the specified system memory location is in random access memory. 18. The computer-implemented method of claim 15, comprising:
determining whether any inconsistencies exist in the information; and creating an improved version of the information in response to determining that an inconsistency does exist in the information, wherein storing the information in local memory includes storing the improved version of the information in the local memory, wherein sending the information back to the specified system memory location includes sending the improved version of the information back to the specified system memory location. 19. The computer-implemented method of claim 15, wherein the local memory is selected from a group consisting of magnetic disk, a solid state drive, and one or more file locations. 20. The computer-implemented method of claim 15, wherein the system is a data storage system or an operating system configured to run one or more processes. | A computer-implemented method, according to one embodiment, includes: storing information in a specified system memory location, attaching an external process to the specified system memory location in response to experiencing a system halt event, sending the information stored in the specified system memory location to a memory location associated with the external process, restarting the system in a recovery mode, retrieving the information from the external process, and using the retrieved information to restore the system to a state the system was in when the system halt event occurred. Other systems, methods, and computer program products are described in additional embodiments.1. A computer-implemented method, comprising:
storing information in a specified system memory location; attaching an external process to the specified system memory location in response to experiencing a system halt event; sending the information stored in the specified system memory location to a memory location associated with the external process; restarting the system in a recovery mode; retrieving the information from the external process; and using the retrieved information to restore the system to a state the system was in when the system halt event occurred. 2. The computer-implemented method of claim 1, wherein the system is a data storage system. 3. The computer-implemented method of claim 1, wherein the system is an operating system configured to run one or more processes. 4. The computer-implemented method of claim 1, wherein the specified system memory location is in random access memory. 5. The computer-implemented method of claim 1, wherein the information includes data and metadata. 6. The computer-implemented method of claim 5, wherein using the retrieved information to restore the system includes:
loading metadata into the specified system memory location; loading data into random access memory; and playing back the data as input/output operations performed on the system. 7. The computer-implemented method of claim 1, wherein retrieving the information from the external process includes:
determining whether any inconsistencies exist in the retrieved information; and creating an improved version of the retrieved information in response to determining that an inconsistency does exist in the retrieved information, wherein the improved version of the retrieved information is used to restore the system. 8. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions readable and/or executable by a processor to cause the processor to perform a method comprising:
storing, by the processor, information in a specified system memory location; attaching, by the processor, an external process to the specified system memory location in response to experiencing a system halt event; sending, by the processor, the information stored in the specified system memory location to a memory location associated with the external process; restarting, by the processor, the system in a recovery mode; retrieving, by the processor, the information from the external process; and using, by the processor, the retrieved information to restore the system to a state the system was in when the system halt event occurred. 9. The computer program product of claim 8, wherein the system is a data storage system. 10. The computer program product of claim 8, wherein the system is an operating system configured to run one or more processes. 11. The computer program product of claim 8, wherein the specified system memory location is in random access memory. 12. The computer program product of claim 8, wherein the information includes data and metadata. 13. The computer program product of claim 12, wherein using the retrieved information to restore the system includes:
loading, by the processor, metadata into the specified system memory location; loading, by the processor, data into random access memory; and playing, by the processor, back the data as input/output operations performed on the system. 14. The computer program product of claim 8, wherein retrieving the information from the external process includes:
determining, by the processor, whether any inconsistencies exist in the retrieved information; and creating, by the processor, an improved version of the retrieved information in response to determining that an inconsistency does exist in the retrieved information, wherein the improved version of the retrieved information is used to restore the system. 15. A computer-implemented method, comprising:
attaching to a specified system memory location in response to detecting that a system halt event occurred at the system; extracting information stored in the specified system memory location; storing the information in local memory; and sending the information back to the specified system memory location in response to detecting that the system has been restarted in a recovery mode. 16. The computer-implemented method of claim 15, wherein the information includes data and metadata. 17. The computer-implemented method of claim 15, wherein the specified system memory location is in random access memory. 18. The computer-implemented method of claim 15, comprising:
determining whether any inconsistencies exist in the information; and creating an improved version of the information in response to determining that an inconsistency does exist in the information, wherein storing the information in local memory includes storing the improved version of the information in the local memory, wherein sending the information back to the specified system memory location includes sending the improved version of the information back to the specified system memory location. 19. The computer-implemented method of claim 15, wherein the local memory is selected from a group consisting of magnetic disk, a solid state drive, and one or more file locations. 20. The computer-implemented method of claim 15, wherein the system is a data storage system or an operating system configured to run one or more processes. | 2,100 |
6,080 | 6,080 | 15,071,009 | 2,143 | A user-defined, structured input which identifies a column in a database and includes an active input associated with the column is received via a UI. A format-related, context-sensitive rule which applies to the active input is determined including by determining an expected format for the active input based at least in part on the format of the column in the database. Guidance associated with satisfying the rule is provided in real time via the UI. This includes displaying format assistance associated with the rule (by identifying the expected format and/or automatically configuring the UI so that the active input has a format which matches the expected format) and/or displaying format validation associated with the rule, including by indicating whether the format of the active input matches the expected format. | 1. A method, comprising:
receiving, via a user interface, a user-defined, structured input which: (1) identifies a column, having a format, in a database and (2) includes an active input having a format and associated with the column; using a processor to determine a format-related, context-sensitive rule which applies to the active input, including by determining an expected format for the active input based at least in part on the format of the column in the database; and providing, in real time via the user interface, guidance associated with satisfying the format-related, context-sensitive rule, including by performing one or more of the following:
displaying, in real time in the user interface, format assistance associated with the format-related, context-sensitive rule, including by performing one or more of the following: (1) identifying the expected format or (2) automatically configuring the user interface so that the active input has a format which matches the expected format; or
displaying, in real time in the user interface, format validation associated with the format-related, context-sensitive rule, including by indicating whether the format of the active input matches the expected format. 2. The method recited in claim 1, wherein:
the expected format includes all caps; and displaying the format validation includes: in response to receiving a lower case letter for the active input, indicating that the format of the active input does not match the expected format of all caps. 3. The method recited in claim 1, wherein:
the expected format includes a value surrounded by quotation marks; and displaying the format validation includes: in response to receiving a character other than a quotation mark for a first character of the active input, indicating that the format of the active input does not match the expected format of a value surrounded by quotation marks. 4. The method recited in claim 1, wherein:
the expected format includes a value surrounded by quotation marks; and automatically configuring the user interface includes automatically populating the user interface with two quotation marks and automatically placing a cursor between the two quotation marks. 5. A system, comprising:
a processor; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to:
receive, via a user interface, a user-defined, structured input which: (1) identifies a column, having a format, in a database and (2) includes an active input having a format and associated with the column;
determine a format-related, context-sensitive rule which applies to the active input, including by determining an expected format for the active input based at least in part on the format of the column in the database; and
provide, in real time via the user interface, guidance associated with satisfying the format-related, context-sensitive rule, including by performing one or more of the following:
displaying, in real time in the user interface, format assistance associated with the format-related, context-sensitive rule, including by performing one or more of the following: (1) identifying the expected format or (2) automatically configuring the user interface so that the active input has a format which matches the expected format; or
displaying, in real time in the user interface, format validation associated with the format-related, context-sensitive rule, including by indicating whether the format of the active input matches the expected format. 6. The system recited in claim 5, wherein:
the expected format includes all caps; and displaying the format validation includes: in response to receiving a lower case letter for the active input, indicating that the format of the active input does not match the expected format of all caps. 7. The system recited in claim 5, wherein:
the expected format includes a value surrounded by quotation marks; and displaying the format validation includes: in response to receiving a character other than a quotation mark for a first character of the active input, indicating that the format of the active input does not match the expected format of a value surrounded by quotation marks. 8. The system recited in claim 5, wherein:
the expected format includes a value surrounded by quotation marks; and automatically configuring the user interface includes automatically populating the user interface with two quotation marks and automatically placing a cursor between the two quotation marks. 9. A computer program product, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:
receiving, via a user interface, a user-defined, structured input which: (1) identifies a column, having a format, in a database and (2) includes an active input having a format and associated with the column; determining a format-related, context-sensitive rule which applies to the active input, including by determining an expected format for the active input based at least in part on the format of the column in the database; and providing, in real time via the user interface, guidance associated with satisfying the format-related, context-sensitive rule, including by performing one or more of the following:
displaying, in real time in the user interface, format assistance associated with the format-related, context-sensitive rule, including by performing one or more of the following: (1) identifying the expected format or (2) automatically configuring the user interface so that the active input has a format which matches the expected format; or
displaying, in real time in the user interface, format validation associated with the format-related, context-sensitive rule, including by indicating whether the format of the active input matches the expected format. 10. The computer program product recited in claim 9, wherein:
the expected format includes all caps; and displaying the format validation includes: in response to receiving a lower case letter for the active input, indicating that the format of the active input does not match the expected format of all caps. 11. The computer program product recited in claim 9, wherein:
the expected format includes a value surrounded by quotation marks; and displaying the format validation includes: in response to receiving a character other than a quotation mark for a first character of the active input, indicating that the format of the active input does not match the expected format of a value surrounded by quotation marks. 12. The computer program product recited in claim 9, wherein:
the expected format includes a value surrounded by quotation marks; and automatically configuring the user interface includes automatically populating the user interface with two quotation marks and automatically placing a cursor between the two quotation marks. | A user-defined, structured input which identifies a column in a database and includes an active input associated with the column is received via a UI. A format-related, context-sensitive rule which applies to the active input is determined including by determining an expected format for the active input based at least in part on the format of the column in the database. Guidance associated with satisfying the rule is provided in real time via the UI. This includes displaying format assistance associated with the rule (by identifying the expected format and/or automatically configuring the UI so that the active input has a format which matches the expected format) and/or displaying format validation associated with the rule, including by indicating whether the format of the active input matches the expected format.1. A method, comprising:
receiving, via a user interface, a user-defined, structured input which: (1) identifies a column, having a format, in a database and (2) includes an active input having a format and associated with the column; using a processor to determine a format-related, context-sensitive rule which applies to the active input, including by determining an expected format for the active input based at least in part on the format of the column in the database; and providing, in real time via the user interface, guidance associated with satisfying the format-related, context-sensitive rule, including by performing one or more of the following:
displaying, in real time in the user interface, format assistance associated with the format-related, context-sensitive rule, including by performing one or more of the following: (1) identifying the expected format or (2) automatically configuring the user interface so that the active input has a format which matches the expected format; or
displaying, in real time in the user interface, format validation associated with the format-related, context-sensitive rule, including by indicating whether the format of the active input matches the expected format. 2. The method recited in claim 1, wherein:
the expected format includes all caps; and displaying the format validation includes: in response to receiving a lower case letter for the active input, indicating that the format of the active input does not match the expected format of all caps. 3. The method recited in claim 1, wherein:
the expected format includes a value surrounded by quotation marks; and displaying the format validation includes: in response to receiving a character other than a quotation mark for a first character of the active input, indicating that the format of the active input does not match the expected format of a value surrounded by quotation marks. 4. The method recited in claim 1, wherein:
the expected format includes a value surrounded by quotation marks; and automatically configuring the user interface includes automatically populating the user interface with two quotation marks and automatically placing a cursor between the two quotation marks. 5. A system, comprising:
a processor; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to:
receive, via a user interface, a user-defined, structured input which: (1) identifies a column, having a format, in a database and (2) includes an active input having a format and associated with the column;
determine a format-related, context-sensitive rule which applies to the active input, including by determining an expected format for the active input based at least in part on the format of the column in the database; and
provide, in real time via the user interface, guidance associated with satisfying the format-related, context-sensitive rule, including by performing one or more of the following:
displaying, in real time in the user interface, format assistance associated with the format-related, context-sensitive rule, including by performing one or more of the following: (1) identifying the expected format or (2) automatically configuring the user interface so that the active input has a format which matches the expected format; or
displaying, in real time in the user interface, format validation associated with the format-related, context-sensitive rule, including by indicating whether the format of the active input matches the expected format. 6. The system recited in claim 5, wherein:
the expected format includes all caps; and displaying the format validation includes: in response to receiving a lower case letter for the active input, indicating that the format of the active input does not match the expected format of all caps. 7. The system recited in claim 5, wherein:
the expected format includes a value surrounded by quotation marks; and displaying the format validation includes: in response to receiving a character other than a quotation mark for a first character of the active input, indicating that the format of the active input does not match the expected format of a value surrounded by quotation marks. 8. The system recited in claim 5, wherein:
the expected format includes a value surrounded by quotation marks; and automatically configuring the user interface includes automatically populating the user interface with two quotation marks and automatically placing a cursor between the two quotation marks. 9. A computer program product, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:
receiving, via a user interface, a user-defined, structured input which: (1) identifies a column, having a format, in a database and (2) includes an active input having a format and associated with the column; determining a format-related, context-sensitive rule which applies to the active input, including by determining an expected format for the active input based at least in part on the format of the column in the database; and providing, in real time via the user interface, guidance associated with satisfying the format-related, context-sensitive rule, including by performing one or more of the following:
displaying, in real time in the user interface, format assistance associated with the format-related, context-sensitive rule, including by performing one or more of the following: (1) identifying the expected format or (2) automatically configuring the user interface so that the active input has a format which matches the expected format; or
displaying, in real time in the user interface, format validation associated with the format-related, context-sensitive rule, including by indicating whether the format of the active input matches the expected format. 10. The computer program product recited in claim 9, wherein:
the expected format includes all caps; and displaying the format validation includes: in response to receiving a lower case letter for the active input, indicating that the format of the active input does not match the expected format of all caps. 11. The computer program product recited in claim 9, wherein:
the expected format includes a value surrounded by quotation marks; and displaying the format validation includes: in response to receiving a character other than a quotation mark for a first character of the active input, indicating that the format of the active input does not match the expected format of a value surrounded by quotation marks. 12. The computer program product recited in claim 9, wherein:
the expected format includes a value surrounded by quotation marks; and automatically configuring the user interface includes automatically populating the user interface with two quotation marks and automatically placing a cursor between the two quotation marks. | 2,100 |
6,081 | 6,081 | 14,550,640 | 2,161 | The claimed subject matter includes techniques for offline evaluation of ranking functions. An example system includes a first module configured to receive production log data, the first module to pre-process the production log data to generate an exploration data set. The example system also includes a second module configured to perform offline estimation of online metrics for ranking functions using the exploration data set. The example system also includes a third module to evaluate a proposed ranking function by comparing the estimated online metrics to a set of baseline metrics of a baseline ranking function and detecting that the estimated online metrics of the proposed ranking function exceed, are lower than, or are within a predetermined range of the baseline metrics. | 1. A system for offline evaluation of ranking functions, comprising:
a first module configured to receive production log data, the first module to pre-process the production log data to generate an exploration data set; a second module configured to perform offline estimation of online metrics for ranking functions using the exploration data set; and a third module to evaluate a proposed ranking function by comparing the estimated online metrics to a set of baseline metrics of a baseline ranking function and detecting that the estimated online metrics of the proposed ranking function exceed, are lower than, or are within a predetermined range of the baseline metrics. 2. The system of claim 1, wherein the first module is configured to pre-process the production log data by simulating randomized data collection based on result diversity when generating the exploration data set. 3. The system of claim 1, wherein the first module is configured to pre-process the production log data by aggregating the production log data by query, by action, by probability of action and by reward value. 4. The system of claim 1, wherein the second module is further configured to use approximate action matching of rankings to estimate online metrics. 5. The system of claim 4, wherein approximate action matching comprises comparing a predetermined number of higher-ranked results for each action generated by a respective ranking function. 6. The system of claim 1, the online metrics comprising at least one of a click-through rate (CTR), a time to click on a search engine results page (SERP), and a mean reciprocal of click positions. 7. The system of claim 1, the preferred ranking function to be used to execute an action on an information retrieval system in response to detecting that a quality of the preferred ranking function exceeds a threshold during the test. 8. The system of claim 7, the action comprising displaying a search engine results page (SERP) in response to a query. 9. The system of claim 1, comprising:
a fourth module generate query results with the proposed ranking function as a test of the proposed ranking function; and a fifth module to display the generated query results. 10. A method for offline evaluation of ranking function performance, the method comprising:
receiving production log data; pre-processing the production log data to generate an exploration data set; performing an offline estimation of online metrics using the exploration data set for a plurality of ranking functions; comparing the plurality of ranking functions based on the estimated online metrics to generate comparison results; identifying one or more preferred ranking functions based on the comparison results; and generating query results with the preferred ranking function during a testing process. 11. The method of claim 10, further comprising approximately matching actions in the exploration data set. 12. The method of claim 11, further comprising approximately matching actions in the exploration data set by matching a predetermined number of higher-ranked results for each action. 13. The method of claim 10, further comprising detecting whether a first ranking function from the plurality of ranking functions has a relevance score that is within a predetermined range of the relevance score of a second ranking function, higher than the predetermined range, or lower than the predetermined range. 14. The method of claim 10, further comprising calculating a confidence score that indicates a level of certainty of the comparison results and displaying the confidence score with an associated comparison result. 15. The method of claim 10, preprocessing the production log data further comprising using result diversity to simulate randomized data collection. 16. The method of claim 10, preprocessing the production log data further comprising aggregating the production log data by query, by action, by probability of action and by reward value. 17. The method of claim 10, further comprising sending the preferred ranking function to a server during the testing process. 18. The method of claim 17, further comprising testing the preferred ranking function on users via the server during the testing process. 19. One or more computer-readable memory storage devices for storing computer readable instructions that, when executed by one or more processing devices, instruct the offline evaluation of ranking function performance, the computer-readable instructions comprising code to:
receive production log data; preprocess the production log data to generate an exploration data set; perform offline estimates of online metrics for a ranking function based at least in part on the exploration data set and an approximate action matching process; detect that the ranking function is a preferred ranking function based on a comparison of the estimated online metrics with baseline ranking function metrics; and execute an action on an information retrieval system based on the preferred ranking function in response to detecting that a quality of the preferred ranking function exceeds a threshold during a testing process. 20. The one or more computer-readable memory storage devices of claim 19, the code for the comparison of online metrics further comprising code to:
calculate a delta metric score between the preferred ranking function and the baseline ranking function; and detect that the delta metric score indicates that the preferred ranking function has a higher estimated online metric than the online metric of the baseline ranking function. | The claimed subject matter includes techniques for offline evaluation of ranking functions. An example system includes a first module configured to receive production log data, the first module to pre-process the production log data to generate an exploration data set. The example system also includes a second module configured to perform offline estimation of online metrics for ranking functions using the exploration data set. The example system also includes a third module to evaluate a proposed ranking function by comparing the estimated online metrics to a set of baseline metrics of a baseline ranking function and detecting that the estimated online metrics of the proposed ranking function exceed, are lower than, or are within a predetermined range of the baseline metrics.1. A system for offline evaluation of ranking functions, comprising:
a first module configured to receive production log data, the first module to pre-process the production log data to generate an exploration data set; a second module configured to perform offline estimation of online metrics for ranking functions using the exploration data set; and a third module to evaluate a proposed ranking function by comparing the estimated online metrics to a set of baseline metrics of a baseline ranking function and detecting that the estimated online metrics of the proposed ranking function exceed, are lower than, or are within a predetermined range of the baseline metrics. 2. The system of claim 1, wherein the first module is configured to pre-process the production log data by simulating randomized data collection based on result diversity when generating the exploration data set. 3. The system of claim 1, wherein the first module is configured to pre-process the production log data by aggregating the production log data by query, by action, by probability of action and by reward value. 4. The system of claim 1, wherein the second module is further configured to use approximate action matching of rankings to estimate online metrics. 5. The system of claim 4, wherein approximate action matching comprises comparing a predetermined number of higher-ranked results for each action generated by a respective ranking function. 6. The system of claim 1, the online metrics comprising at least one of a click-through rate (CTR), a time to click on a search engine results page (SERP), and a mean reciprocal of click positions. 7. The system of claim 1, the preferred ranking function to be used to execute an action on an information retrieval system in response to detecting that a quality of the preferred ranking function exceeds a threshold during the test. 8. The system of claim 7, the action comprising displaying a search engine results page (SERP) in response to a query. 9. The system of claim 1, comprising:
a fourth module generate query results with the proposed ranking function as a test of the proposed ranking function; and a fifth module to display the generated query results. 10. A method for offline evaluation of ranking function performance, the method comprising:
receiving production log data; pre-processing the production log data to generate an exploration data set; performing an offline estimation of online metrics using the exploration data set for a plurality of ranking functions; comparing the plurality of ranking functions based on the estimated online metrics to generate comparison results; identifying one or more preferred ranking functions based on the comparison results; and generating query results with the preferred ranking function during a testing process. 11. The method of claim 10, further comprising approximately matching actions in the exploration data set. 12. The method of claim 11, further comprising approximately matching actions in the exploration data set by matching a predetermined number of higher-ranked results for each action. 13. The method of claim 10, further comprising detecting whether a first ranking function from the plurality of ranking functions has a relevance score that is within a predetermined range of the relevance score of a second ranking function, higher than the predetermined range, or lower than the predetermined range. 14. The method of claim 10, further comprising calculating a confidence score that indicates a level of certainty of the comparison results and displaying the confidence score with an associated comparison result. 15. The method of claim 10, preprocessing the production log data further comprising using result diversity to simulate randomized data collection. 16. The method of claim 10, preprocessing the production log data further comprising aggregating the production log data by query, by action, by probability of action and by reward value. 17. The method of claim 10, further comprising sending the preferred ranking function to a server during the testing process. 18. The method of claim 17, further comprising testing the preferred ranking function on users via the server during the testing process. 19. One or more computer-readable memory storage devices for storing computer readable instructions that, when executed by one or more processing devices, instruct the offline evaluation of ranking function performance, the computer-readable instructions comprising code to:
receive production log data; preprocess the production log data to generate an exploration data set; perform offline estimates of online metrics for a ranking function based at least in part on the exploration data set and an approximate action matching process; detect that the ranking function is a preferred ranking function based on a comparison of the estimated online metrics with baseline ranking function metrics; and execute an action on an information retrieval system based on the preferred ranking function in response to detecting that a quality of the preferred ranking function exceeds a threshold during a testing process. 20. The one or more computer-readable memory storage devices of claim 19, the code for the comparison of online metrics further comprising code to:
calculate a delta metric score between the preferred ranking function and the baseline ranking function; and detect that the delta metric score indicates that the preferred ranking function has a higher estimated online metric than the online metric of the baseline ranking function. | 2,100 |
6,082 | 6,082 | 14,500,417 | 2,144 | A method performed in a web page authoring system having a user input system and an editing screen display for displaying a representation of a tag associated with a display artifact represented on the editing screen display is disclosed. A user action input selecting a reference point on the editing screen display for a web page being authored is received. A reference area on the editing screen display enclosing the selected reference point is set. The display object closest to the reference point is selected as a reference display artifact from among display artifacts in the reference area. A tag associated with the reference display artifact is selected from among tags associated with the display artifacts. A first rectangle is drawn on the editing screen display artifact. A second, larger rectangle is drawn enclosing the first rectangle. A space between the first and second rectangles represents the selected tag. | 1-20. (canceled) 21. A computer-implemented method for editing source code, comprising:
determining, based upon a selection, a reference point on an editing screen display; selecting, as a reference display artifact, a display artifact closest to the reference point; selecting, as a related display artifact, a display artifact related to the reference display artifact; drawing a first rectangle on the editing screen display enclosing the reference display object; and drawing a second rectangle on the editing screen display enclosing the related display artifact, wherein a selectable space between the first and second rectangles represents the related display object. 22. The method of claim 21, wherein
the related displayed object is related to the reference display object as one of a sibling, a parent, and a child. 23. The method of claim 21, further comprising:
setting a reference area enclosing the reference point, wherein the reference display artifact is selected from among display artifacts within the reference area, and the related display artifact is selected from the display artifacts within the reference area. 24. The method of claim 23, wherein
the reference area includes displays objects not visually appearing on the editing screen display. 25. The method of claim 21, further comprising:
receiving a selection, by a user, of the selectable space. 26. The method of claim 21, wherein
each rectangle is associated with an open tag and a corresponding close tag in the source code. 27. A computer hardware system configured to edit source code, comprising:
at least one hardware processor, wherein the at least one hardware processing is configured to initiate and/or perform:
determining, based upon a selection, a reference point on an editing screen display;
selecting, as a reference display artifact, a display artifact closest to the reference point;
selecting, as a related display artifact, a display artifact related to the reference display artifact;
drawing a first rectangle on the editing screen display enclosing the reference display object; and
drawing a second rectangle on the editing screen display enclosing the related display artifact, wherein
a selectable space between the first and second rectangles represents the related display object. 28. The system of claim 27, wherein
the related displayed object is related to the reference display object as one of a sibling, a parent, and a child. 29. The system of claim 27, wherein the at least one hardware processing is further configured to initiate and/or perform:
setting a reference area enclosing the reference point, wherein the reference display artifact is selected from among display artifacts within the reference area, and the related display artifact is selected from the display artifacts within the reference area. 30. The method of claim 29, wherein
the reference area includes displays objects not visually appearing on the editing screen display. 31. The system of claim 27, wherein the at least one hardware processing is further configured to initiate and/or perform:
receiving a selection, by a user, of the selectable space. 32. The system of claim 27, wherein
each rectangle is associated with an open tag and a corresponding close tag in the source code. 33. A computer program product, comprising:
a computer usable storage medium having stored therein computer usable program code for editing source code, the computer usable program code, when executed by a computer hardware system causes the computer hardware system to perform:
determining, based upon a selection, a reference point on an editing screen display;
selecting, as a reference display artifact, a display artifact closest to the reference point;
selecting, as a related display artifact, a display artifact related to the reference display artifact;
drawing a first rectangle on the editing screen display enclosing the reference display object; and
drawing a second rectangle on the editing screen display enclosing the related display artifact, wherein
a selectable space between the first and second rectangles represents the related display object, and the computer usable storage medium is not a transitory signal per se. 34. The computer program product of claim 33, wherein
the related displayed object is related to the reference display object as one of a sibling, a parent, and a child. 35. The computer program product of claim 33, wherein the computer usable program code further causes the computer hardware system to perform:
setting a reference area enclosing the reference point, wherein the reference display artifact is selected from among display artifacts within the reference area, and the related display artifact is selected from the display artifacts within the reference area. 36. The computer program product of claim 35, wherein
the reference area includes displays objects not visually appearing on the editing screen display. 37. The computer program product of claim 33, further comprising:
receiving a selection, by a user, of the selectable space. 38. The computer program product of claim 33, wherein
each rectangle is associated with an open tag and a corresponding close tag in the source code. | A method performed in a web page authoring system having a user input system and an editing screen display for displaying a representation of a tag associated with a display artifact represented on the editing screen display is disclosed. A user action input selecting a reference point on the editing screen display for a web page being authored is received. A reference area on the editing screen display enclosing the selected reference point is set. The display object closest to the reference point is selected as a reference display artifact from among display artifacts in the reference area. A tag associated with the reference display artifact is selected from among tags associated with the display artifacts. A first rectangle is drawn on the editing screen display artifact. A second, larger rectangle is drawn enclosing the first rectangle. A space between the first and second rectangles represents the selected tag.1-20. (canceled) 21. A computer-implemented method for editing source code, comprising:
determining, based upon a selection, a reference point on an editing screen display; selecting, as a reference display artifact, a display artifact closest to the reference point; selecting, as a related display artifact, a display artifact related to the reference display artifact; drawing a first rectangle on the editing screen display enclosing the reference display object; and drawing a second rectangle on the editing screen display enclosing the related display artifact, wherein a selectable space between the first and second rectangles represents the related display object. 22. The method of claim 21, wherein
the related displayed object is related to the reference display object as one of a sibling, a parent, and a child. 23. The method of claim 21, further comprising:
setting a reference area enclosing the reference point, wherein the reference display artifact is selected from among display artifacts within the reference area, and the related display artifact is selected from the display artifacts within the reference area. 24. The method of claim 23, wherein
the reference area includes displays objects not visually appearing on the editing screen display. 25. The method of claim 21, further comprising:
receiving a selection, by a user, of the selectable space. 26. The method of claim 21, wherein
each rectangle is associated with an open tag and a corresponding close tag in the source code. 27. A computer hardware system configured to edit source code, comprising:
at least one hardware processor, wherein the at least one hardware processing is configured to initiate and/or perform:
determining, based upon a selection, a reference point on an editing screen display;
selecting, as a reference display artifact, a display artifact closest to the reference point;
selecting, as a related display artifact, a display artifact related to the reference display artifact;
drawing a first rectangle on the editing screen display enclosing the reference display object; and
drawing a second rectangle on the editing screen display enclosing the related display artifact, wherein
a selectable space between the first and second rectangles represents the related display object. 28. The system of claim 27, wherein
the related displayed object is related to the reference display object as one of a sibling, a parent, and a child. 29. The system of claim 27, wherein the at least one hardware processing is further configured to initiate and/or perform:
setting a reference area enclosing the reference point, wherein the reference display artifact is selected from among display artifacts within the reference area, and the related display artifact is selected from the display artifacts within the reference area. 30. The method of claim 29, wherein
the reference area includes displays objects not visually appearing on the editing screen display. 31. The system of claim 27, wherein the at least one hardware processing is further configured to initiate and/or perform:
receiving a selection, by a user, of the selectable space. 32. The system of claim 27, wherein
each rectangle is associated with an open tag and a corresponding close tag in the source code. 33. A computer program product, comprising:
a computer usable storage medium having stored therein computer usable program code for editing source code, the computer usable program code, when executed by a computer hardware system causes the computer hardware system to perform:
determining, based upon a selection, a reference point on an editing screen display;
selecting, as a reference display artifact, a display artifact closest to the reference point;
selecting, as a related display artifact, a display artifact related to the reference display artifact;
drawing a first rectangle on the editing screen display enclosing the reference display object; and
drawing a second rectangle on the editing screen display enclosing the related display artifact, wherein
a selectable space between the first and second rectangles represents the related display object, and the computer usable storage medium is not a transitory signal per se. 34. The computer program product of claim 33, wherein
the related displayed object is related to the reference display object as one of a sibling, a parent, and a child. 35. The computer program product of claim 33, wherein the computer usable program code further causes the computer hardware system to perform:
setting a reference area enclosing the reference point, wherein the reference display artifact is selected from among display artifacts within the reference area, and the related display artifact is selected from the display artifacts within the reference area. 36. The computer program product of claim 35, wherein
the reference area includes displays objects not visually appearing on the editing screen display. 37. The computer program product of claim 33, further comprising:
receiving a selection, by a user, of the selectable space. 38. The computer program product of claim 33, wherein
each rectangle is associated with an open tag and a corresponding close tag in the source code. | 2,100 |
6,083 | 6,083 | 15,491,978 | 2,191 | To simultaneously deploy software package on hosts such as cloud devices and on-premise device, a request is received at a central server to deploy a software package on hosts in a landscape. A topology file of the hosts in the landscape is generated. The hosts in the landscape include one or more hosts located in the cloud environment and one or more hosts located in the on-premise environment. A server side security certificate corresponding to the central server and host side security certificate corresponding to each of the hosts in the landscape is generated. The server side security certificate from the central server is sent to each of the hosts to establish a trusted communication between the central server and the hosts. Accordingly, the software package is deployed simultaneously on hosts as cloud devices and on-premise device. | 1. A non-transitory computer-readable medium to store instructions, which when executed by a computer, cause the computer to perform operations comprising:
receive a request at a central server to deploy a software package in hosts in a single landscape, wherein the hosts in the single landscape includes one or more hosts located on a cloud environment and one or more hosts located on an on-premise environment; and based on the request, simultaneously deploy the software package in the single landscape including the one or more hosts located on the cloud environment and the one or more hosts located on the on-premise environment. 2. The non-transitory computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to:
generate a topology file of the hosts on the landscape, wherein the hosts in the landscape include the one or more hosts located on the cloud environment and the one or more hosts located on the on-premise environment; and store the topology file in the central server. 3. The non-transitory computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to:
generate a server side security certificate corresponding to the central server and host side security certificates corresponding to each of the hosts in the landscape; and send the server side security certificate from the central server to each of the hosts to establish a trusted communication between the central server and the hosts. 4. The non-transitory computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to:
at the central server, receive selection of the software package and the request to remote deploy the software package from an administrative console in a user device;
in response to the request, initiate simultaneous deployment of the software package by a server agent in the central server; and
using a topology file of the landscape as reference, the server agent in the central server, simultaneously deploy the software package on the hosts in the landscape using host agents. 5. The non-transitory computer-readable medium of claim 4, further comprises instructions which when executed by the computer further cause the computer to:
using the topology file of the landscape as reference, the server agent in the central server, simultaneously deploy the software package on hosts in a first tier using the host agents; and using the topology file of the landscape as reference, the server agent in the central server, deploy in sequence the software package on the hosts in a second tier using the host agents. 6. The non-transitory computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to:
perform a pre-requisite check to determine whether the hosts in the landscape meet the pre-requisite check; generate a summary log with details of the hosts that did not meet the pre-requisite check along with actions; and automatically perform the actions corresponding to the hosts. 7. The non-transitory computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to:
store in a patch forecaster in the central server a list of software packages and corresponding versions deployed on the hosts in the landscape; automatically match the list of software packages and corresponding versions with a new version of a software package release; and in response to the match, automatically notify a user of with matched information. 8. A computer-implemented method of simultaneous deployment on cloud devices and on-premise devices, the method comprising:
receiving a request at a central server to deploy a software package on hosts in a single landscape, wherein the hosts in the single landscape includes one or more hosts located on a cloud environment and one or more hosts located on an on-premise environment; and based on the request, simultaneously deploying the software package in the single landscape including the one or more hosts located on the cloud environment and the one or more hosts located on the on-premise environment. 9. The method of claim 8, further comprising:
generating a topology file of the hosts in the landscape, wherein the hosts in the landscape include the one or more hosts located on the cloud environment and the one or more hosts located on the on-premise environment; and storing the topology file in the central server. 10. The method of claim 8, further comprising:
generating a server side security certificate corresponding to the central server and host side security certificates corresponding to each of the hosts in the landscape; and sending the server side security certificate from the central server to each of the hosts to establish a trusted communication between the central server and the hosts. 11. The method of claim 8, further comprising:
at the central server, receiving selection of the software package and the request to remote deploy the software package from an administrative console in a user device;
in response to the request, initiate simultaneous deployment of the software package by a server agent in the central server; and
using a topology file of the landscape as reference, the server agent in the central server, simultaneously deploying the software package on the hosts in the landscape using host agents. 12. The method of claim 11, further comprising:
using the topology file of the landscape as reference, the server agent in the central server, simultaneously deploying the software package on hosts in a first tier using the host agents; and using the topology file of the landscape as reference, the server agent in the central server, deploying in sequence the software package on the hosts in a second tier using the host agents. 13. The method of claim 8, further comprising:
performing a pre-requisite check to determine whether the hosts in the landscape meet the pre-requisite check; generating a summary log with details of the hosts that did not meet the pre-requisite check along with actions; and automatically performing the actions corresponding to the hosts. 14. The method of claim 8, further comprising:
storing in a patch forecaster in the central server a list of software packages and corresponding versions deployed on the hosts in the landscape; automatically matching the list of software packages and corresponding versions with a new version of a software package release; and in response to the match, automatically notifying a user of with matched information. 15. A computer system for simultaneous deployment on cloud devices and on-premise devices, comprising:
a computer memory to store program code; and a processor to execute the program code to:
receive a request at a central server to deploy a software package on hosts in a single landscape, wherein the hosts in the single landscape includes one or more hosts located on a cloud environment and one or more hosts located on an on-premise environment; and
based on the request, simultaneously deploy the software package in the single landscape including the one or more hosts located on the cloud environment and the one or more hosts located on the on-premise environment. 16. The system of claim 15, wherein the processor further executes the program code to:
generate a topology file of the hosts in the landscape, wherein the hosts in the landscape include the one or more hosts located on the cloud environment and the one or more hosts located on the on-premise environment; and store the topology file in the central server. 17. The system of claim 15, wherein the processor further executes the program code to:
generate a server side security certificate corresponding to the central server and host side security certificates corresponding to each of the hosts in the landscape; and send the server side security certificate from the central server to each of the hosts to establish a trusted communication between the central server and the hosts. 18. The system of claim 15, wherein the processor further executes the program code to:
at the central server, receive selection of the software package and the request to remote deploy the software package from an administrative console in a user device;
in response to the request, initiate simultaneous deployment of the software package by a server agent in the central server; and
using a topology file of the landscape as reference, the server agent in the central server, simultaneously deploy the software package on the hosts in the landscape using host agents. 19. The system of claim 18, wherein the processor further executes the program code to:
using the topology file of the landscape as reference, the server agent in the central server, simultaneously deploy the software package on hosts in a first tier using the host agents; and using the topology file of the landscape as reference, the server agent in the central server, deploy in sequence the software package on the hosts in a second tier using the host agents. 20. The system of claim 15, wherein the processor further executes the program code to:
store in a patch forecaster in the central server a list of software packages and corresponding versions deployed on the hosts in the landscape; automatically match the list of software packages and corresponding versions with a new version of a software package release, and in response to the match, automatically notify a user of with matched information. | To simultaneously deploy software package on hosts such as cloud devices and on-premise device, a request is received at a central server to deploy a software package on hosts in a landscape. A topology file of the hosts in the landscape is generated. The hosts in the landscape include one or more hosts located in the cloud environment and one or more hosts located in the on-premise environment. A server side security certificate corresponding to the central server and host side security certificate corresponding to each of the hosts in the landscape is generated. The server side security certificate from the central server is sent to each of the hosts to establish a trusted communication between the central server and the hosts. Accordingly, the software package is deployed simultaneously on hosts as cloud devices and on-premise device.1. A non-transitory computer-readable medium to store instructions, which when executed by a computer, cause the computer to perform operations comprising:
receive a request at a central server to deploy a software package in hosts in a single landscape, wherein the hosts in the single landscape includes one or more hosts located on a cloud environment and one or more hosts located on an on-premise environment; and based on the request, simultaneously deploy the software package in the single landscape including the one or more hosts located on the cloud environment and the one or more hosts located on the on-premise environment. 2. The non-transitory computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to:
generate a topology file of the hosts on the landscape, wherein the hosts in the landscape include the one or more hosts located on the cloud environment and the one or more hosts located on the on-premise environment; and store the topology file in the central server. 3. The non-transitory computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to:
generate a server side security certificate corresponding to the central server and host side security certificates corresponding to each of the hosts in the landscape; and send the server side security certificate from the central server to each of the hosts to establish a trusted communication between the central server and the hosts. 4. The non-transitory computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to:
at the central server, receive selection of the software package and the request to remote deploy the software package from an administrative console in a user device;
in response to the request, initiate simultaneous deployment of the software package by a server agent in the central server; and
using a topology file of the landscape as reference, the server agent in the central server, simultaneously deploy the software package on the hosts in the landscape using host agents. 5. The non-transitory computer-readable medium of claim 4, further comprises instructions which when executed by the computer further cause the computer to:
using the topology file of the landscape as reference, the server agent in the central server, simultaneously deploy the software package on hosts in a first tier using the host agents; and using the topology file of the landscape as reference, the server agent in the central server, deploy in sequence the software package on the hosts in a second tier using the host agents. 6. The non-transitory computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to:
perform a pre-requisite check to determine whether the hosts in the landscape meet the pre-requisite check; generate a summary log with details of the hosts that did not meet the pre-requisite check along with actions; and automatically perform the actions corresponding to the hosts. 7. The non-transitory computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to:
store in a patch forecaster in the central server a list of software packages and corresponding versions deployed on the hosts in the landscape; automatically match the list of software packages and corresponding versions with a new version of a software package release; and in response to the match, automatically notify a user of with matched information. 8. A computer-implemented method of simultaneous deployment on cloud devices and on-premise devices, the method comprising:
receiving a request at a central server to deploy a software package on hosts in a single landscape, wherein the hosts in the single landscape includes one or more hosts located on a cloud environment and one or more hosts located on an on-premise environment; and based on the request, simultaneously deploying the software package in the single landscape including the one or more hosts located on the cloud environment and the one or more hosts located on the on-premise environment. 9. The method of claim 8, further comprising:
generating a topology file of the hosts in the landscape, wherein the hosts in the landscape include the one or more hosts located on the cloud environment and the one or more hosts located on the on-premise environment; and storing the topology file in the central server. 10. The method of claim 8, further comprising:
generating a server side security certificate corresponding to the central server and host side security certificates corresponding to each of the hosts in the landscape; and sending the server side security certificate from the central server to each of the hosts to establish a trusted communication between the central server and the hosts. 11. The method of claim 8, further comprising:
at the central server, receiving selection of the software package and the request to remote deploy the software package from an administrative console in a user device;
in response to the request, initiate simultaneous deployment of the software package by a server agent in the central server; and
using a topology file of the landscape as reference, the server agent in the central server, simultaneously deploying the software package on the hosts in the landscape using host agents. 12. The method of claim 11, further comprising:
using the topology file of the landscape as reference, the server agent in the central server, simultaneously deploying the software package on hosts in a first tier using the host agents; and using the topology file of the landscape as reference, the server agent in the central server, deploying in sequence the software package on the hosts in a second tier using the host agents. 13. The method of claim 8, further comprising:
performing a pre-requisite check to determine whether the hosts in the landscape meet the pre-requisite check; generating a summary log with details of the hosts that did not meet the pre-requisite check along with actions; and automatically performing the actions corresponding to the hosts. 14. The method of claim 8, further comprising:
storing in a patch forecaster in the central server a list of software packages and corresponding versions deployed on the hosts in the landscape; automatically matching the list of software packages and corresponding versions with a new version of a software package release; and in response to the match, automatically notifying a user of with matched information. 15. A computer system for simultaneous deployment on cloud devices and on-premise devices, comprising:
a computer memory to store program code; and a processor to execute the program code to:
receive a request at a central server to deploy a software package on hosts in a single landscape, wherein the hosts in the single landscape includes one or more hosts located on a cloud environment and one or more hosts located on an on-premise environment; and
based on the request, simultaneously deploy the software package in the single landscape including the one or more hosts located on the cloud environment and the one or more hosts located on the on-premise environment. 16. The system of claim 15, wherein the processor further executes the program code to:
generate a topology file of the hosts in the landscape, wherein the hosts in the landscape include the one or more hosts located on the cloud environment and the one or more hosts located on the on-premise environment; and store the topology file in the central server. 17. The system of claim 15, wherein the processor further executes the program code to:
generate a server side security certificate corresponding to the central server and host side security certificates corresponding to each of the hosts in the landscape; and send the server side security certificate from the central server to each of the hosts to establish a trusted communication between the central server and the hosts. 18. The system of claim 15, wherein the processor further executes the program code to:
at the central server, receive selection of the software package and the request to remote deploy the software package from an administrative console in a user device;
in response to the request, initiate simultaneous deployment of the software package by a server agent in the central server; and
using a topology file of the landscape as reference, the server agent in the central server, simultaneously deploy the software package on the hosts in the landscape using host agents. 19. The system of claim 18, wherein the processor further executes the program code to:
using the topology file of the landscape as reference, the server agent in the central server, simultaneously deploy the software package on hosts in a first tier using the host agents; and using the topology file of the landscape as reference, the server agent in the central server, deploy in sequence the software package on the hosts in a second tier using the host agents. 20. The system of claim 15, wherein the processor further executes the program code to:
store in a patch forecaster in the central server a list of software packages and corresponding versions deployed on the hosts in the landscape; automatically match the list of software packages and corresponding versions with a new version of a software package release, and in response to the match, automatically notify a user of with matched information. | 2,100 |
6,084 | 6,084 | 15,537,012 | 2,175 | Apparatuses, methods and computer programs are provided. A method comprises: determining at least one region of interest in visual virtual reality content; monitoring whether at least a defined proportion of a viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content; and controlling advancement of the visual virtual reality content based on whether the at least a defined proportion of the viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content. | 1. A method, comprising:
determining at least one region of interest in visual virtual reality content; monitoring whether at least a defined proportion of a viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content; and controlling advancement of the visual virtual reality content based on whether the at least a defined proportion of the viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content. 2. The method of claim 1, wherein the controlling advancement of the visual virtual reality content comprises enabling advancement of the visual virtual reality content in response to determining that the at least a defined proportion of the viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content. 3. The method of claim 1, wherein the controlling advancement of the visual virtual reality content comprises ceasing advancement of at least a portion of the visual virtual reality content in response to determining that the at least a defined proportion of the viewer's field of view does not coincide with the determined at least one region of interest in the visual virtual reality content. 4. The method of claim 3, wherein the advancement of a portion of the visual virtual reality content which comprises the determined at least one region of interest is ceased. 5. The method of claim 1, further comprising:
causing playback of at least one audio track to pause in response to determining that the at least a defined proportion of the viewer's field of view does not coincide with the determined at least one region of interest in the visual virtual reality content. 6. The method of claim 5, further comprising:
enabling playback of at least one further audio track, different from the at least one audio track, when playback of the at least one audio track has been paused. 7. The method of claim 1, wherein the visual virtual reality content is virtual reality video content and controlling advancement of the visual virtual reality content comprises controlling playback of the virtual reality video content. 8. The method of claim 1, further comprising:
determining that a previously determined at least one region of interest is no longer a region of interest; determining at least one new region of interest in the visual virtual reality content; monitoring whether at least the defined proportion of a viewer's field of view coincides with the determined at least one new region of interest in the visual virtual reality content; and controlling advancement of the visual virtual reality content based on whether the at least a defined proportion of the viewer's field of view coincides with the determined at least one new region of interest in the visual virtual reality content. 9. The method of claim 1, wherein the visual virtual reality content is provided by virtual reality content data stored in memory and the virtual reality content data comprises a plurality of identifiers that identify regions of interest in the visual virtual reality content. 10. The method of claim 1, wherein monitoring whether at least a defined proportion of a viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content comprises tracking at least one of a viewer's head movements and a viewer's gaze. 11. The method of claim 1, wherein the visual virtual reality content extends beyond a viewer's field of view when viewing the visual virtual reality content. 12. The method of claim 11, wherein the visual virtual reality content is 360° visual virtual reality content. 13. Computer program code embodied on a non-transitory computer-readable medium that, when performed by at least one processor, causes the method of claim 1 to be performed. 14. An apparatus, comprising:
means for determining at least one region of interest in visual virtual reality content; means for monitoring whether at least a defined proportion of a viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content; and means for controlling advancement of the visual virtual reality content based on whether the at least a defined portion of the viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content. 15. (canceled) 16. The apparatus according to claim 14, further comprising:
means for determining that a previously determined at least one region of interest is no longer a region of interest; means for determining at least one new region of interest in the visual virtual reality content; means for monitoring whether at least the defined proportion of a viewer's field of view coincides with the determined at least one new region of interest in the visual virtual reality content; and means for controlling advancement of the visual virtual reality content based on whether the at least a defined proportion of the viewer's field of view coincides with the determined at least one new region of interest in the visual virtual reality content. 17. An apparatus, comprising:
at least one processor; at least one memory including computer program code; the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to perform:
determining at least one region of interest in visual virtual reality content;
monitoring whether at least a defined proportion of a viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content; and
controlling advancement of the visual virtual reality content based on whether the at least a defined proportion of the viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content. 18. The apparatus according to claim 17, wherein said at least one processor, at least one memory, and computer program code are further configured to perform:
determining that a previously determined at least one region of interest is no longer a region of interest; determining at least one new region of interest in the visual virtual reality content; monitoring whether at least the defined proportion of a viewer's field of view coincides with the determined at least one new region of interest in the visual virtual reality content; and controlling advancement of the visual virtual reality content based on whether the at least a defined proportion of the viewer's field of view coincides with the determined at least one new region of interest in the visual virtual reality content. | Apparatuses, methods and computer programs are provided. A method comprises: determining at least one region of interest in visual virtual reality content; monitoring whether at least a defined proportion of a viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content; and controlling advancement of the visual virtual reality content based on whether the at least a defined proportion of the viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content.1. A method, comprising:
determining at least one region of interest in visual virtual reality content; monitoring whether at least a defined proportion of a viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content; and controlling advancement of the visual virtual reality content based on whether the at least a defined proportion of the viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content. 2. The method of claim 1, wherein the controlling advancement of the visual virtual reality content comprises enabling advancement of the visual virtual reality content in response to determining that the at least a defined proportion of the viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content. 3. The method of claim 1, wherein the controlling advancement of the visual virtual reality content comprises ceasing advancement of at least a portion of the visual virtual reality content in response to determining that the at least a defined proportion of the viewer's field of view does not coincide with the determined at least one region of interest in the visual virtual reality content. 4. The method of claim 3, wherein the advancement of a portion of the visual virtual reality content which comprises the determined at least one region of interest is ceased. 5. The method of claim 1, further comprising:
causing playback of at least one audio track to pause in response to determining that the at least a defined proportion of the viewer's field of view does not coincide with the determined at least one region of interest in the visual virtual reality content. 6. The method of claim 5, further comprising:
enabling playback of at least one further audio track, different from the at least one audio track, when playback of the at least one audio track has been paused. 7. The method of claim 1, wherein the visual virtual reality content is virtual reality video content and controlling advancement of the visual virtual reality content comprises controlling playback of the virtual reality video content. 8. The method of claim 1, further comprising:
determining that a previously determined at least one region of interest is no longer a region of interest; determining at least one new region of interest in the visual virtual reality content; monitoring whether at least the defined proportion of a viewer's field of view coincides with the determined at least one new region of interest in the visual virtual reality content; and controlling advancement of the visual virtual reality content based on whether the at least a defined proportion of the viewer's field of view coincides with the determined at least one new region of interest in the visual virtual reality content. 9. The method of claim 1, wherein the visual virtual reality content is provided by virtual reality content data stored in memory and the virtual reality content data comprises a plurality of identifiers that identify regions of interest in the visual virtual reality content. 10. The method of claim 1, wherein monitoring whether at least a defined proportion of a viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content comprises tracking at least one of a viewer's head movements and a viewer's gaze. 11. The method of claim 1, wherein the visual virtual reality content extends beyond a viewer's field of view when viewing the visual virtual reality content. 12. The method of claim 11, wherein the visual virtual reality content is 360° visual virtual reality content. 13. Computer program code embodied on a non-transitory computer-readable medium that, when performed by at least one processor, causes the method of claim 1 to be performed. 14. An apparatus, comprising:
means for determining at least one region of interest in visual virtual reality content; means for monitoring whether at least a defined proportion of a viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content; and means for controlling advancement of the visual virtual reality content based on whether the at least a defined portion of the viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content. 15. (canceled) 16. The apparatus according to claim 14, further comprising:
means for determining that a previously determined at least one region of interest is no longer a region of interest; means for determining at least one new region of interest in the visual virtual reality content; means for monitoring whether at least the defined proportion of a viewer's field of view coincides with the determined at least one new region of interest in the visual virtual reality content; and means for controlling advancement of the visual virtual reality content based on whether the at least a defined proportion of the viewer's field of view coincides with the determined at least one new region of interest in the visual virtual reality content. 17. An apparatus, comprising:
at least one processor; at least one memory including computer program code; the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to perform:
determining at least one region of interest in visual virtual reality content;
monitoring whether at least a defined proportion of a viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content; and
controlling advancement of the visual virtual reality content based on whether the at least a defined proportion of the viewer's field of view coincides with the determined at least one region of interest in the visual virtual reality content. 18. The apparatus according to claim 17, wherein said at least one processor, at least one memory, and computer program code are further configured to perform:
determining that a previously determined at least one region of interest is no longer a region of interest; determining at least one new region of interest in the visual virtual reality content; monitoring whether at least the defined proportion of a viewer's field of view coincides with the determined at least one new region of interest in the visual virtual reality content; and controlling advancement of the visual virtual reality content based on whether the at least a defined proportion of the viewer's field of view coincides with the determined at least one new region of interest in the visual virtual reality content. | 2,100 |
6,085 | 6,085 | 15,342,375 | 2,173 | Changes in display area automatically lead to changes in the format used to display graphical content of a list of items such as thumbnails or application icons, for example. A list display controller transitions between scrollable format and fixed format, and transitions between fixed formats with different numbers of display slots. Transitions may be triggered by window resizing, by moving a graphical user interface from one device to another while the application runs, or by switching between landscape and portrait mode, for example. Even when the format is not changed in response to a display area change, graphical content is automatically resized to match changes in the size of the display area containing the graphical content. Format transitions and content resizing help provide a pleasant user experience by maintaining content density with expected usage patterns for a given device, and reduce proliferation of code versions. | 1. A computational system for dynamically adjusting content density by controlling whether a list displayed in a graphical user interface is scrollable, the system comprising:
a memory; a list of graphical items residing in the memory; a display subsystem having a hardware screen with a display area, a portion of the display area being available through the graphical user interface for displaying one or more of the graphical items in a list format, the list format having a visual orientation which is a vertical orientation or a horizontal orientation, the display area portion having dimensions which include a width and a height; a processor in operable communication with the memory and the display subsystem; and a list display controller which controls the processor to monitor the display subsystem to detect a display area portion change which alters the width or height of the display area portion and to automatically disable scrolling of displayed items along the visual orientation when a predetermined dimension of the display area portion along the visual orientation exceeds a predetermined threshold and to otherwise automatically enable such scrolling. 2. The system of claim 1, wherein each of the graphical items has a respective minimum size along an axis parallel to the visual orientation, and the predetermined threshold is a value which is not more than six times the smallest of the one or more minimum sizes. 3. The system of claim 1, wherein the display subsystem includes at least one hardware screen whose display area portion dimension exceeds the predetermined threshold and also includes at least one other hardware screen whose display area portion dimension does not exceed the predetermined threshold. 4. The system of claim 1, wherein the display subsystem comprises a hardware phone screen having a phone screen display area, the display subsystem also comprises a hardware larger screen, the hardware larger screen has a larger screen display area which is larger than the phone screen display area, and the list display controller controls the processor to transition from a horizontal scroll format as the list format on the hardware phone screen to a fixed format as the list format on the hardware larger screen. 5. The system of claim 1, wherein the display subsystem includes at least three hardware screens with respective display area portions having different respective dimensions, and the list display controller controls the processor to display a different respective number of the graphical items at a time on each respective hardware screen based on the respective dimensions of the hardware screens without scrolling the displayed graphical items along the visual orientation on any of the three hardware screens. 6. The system of claim 1, wherein the list display controller automatically disables scrolling of displayed graphical items along the visual orientation when an entire displayed page of the graphical items can be swiped from display as a unit by a user command directed to the list display controller. 7. The system of claim 1, wherein the visual orientation is a horizontal orientation, the list display controller compares the display area portion width to at least one template width of a group of at least three different template widths, the list display controller identifies the largest template width which fits within the display area portion width, and the list display controller specifies a number of the graphical items to display in a fixed format row in the display area portion based on the identified template width. 8. The system of claim 1, wherein the display subsystem comprises a phone screen and also comprises at least one of the following hardware screens: a tablet screen, a laptop screen, a game system screen, a television screen, a hardware screen which has at least four times as much display area as the phone screen. 9. A computer-implemented method for dynamically adjusting content density by relocating graphical content within an underlying row displayed in a graphical user interface, the method comprising:
displaying graphical content of a first graphical item in a first format in a displayed portion of the row within the graphical user interface on a first hardware screen of a first computing device; displaying at least a portion of graphical content of at least one additional graphical item in the first format in the displayed portion of the row within the graphical user interface; constantly monitoring a width of the displayed portion of the row to detect a format transition condition where the width crosses a predetermined format transition value; and automatically relocating at least a portion of the graphical content, by a processor, to a portion of the row in a second format in response to the format transition condition so that the graphical content displayed in the row to a user changes in at least one of the following ways: (a) graphical content which before the format transition condition was not displayed but was available for display in a horizontal scroll format is displayed after the format transition condition in a fixed format, or (b) graphical content which before the format transition condition was displayed in a fixed format is not displayed after the format transition condition but is available for display in a horizontal scroll format. 10. The method of claim 9, wherein the method further comprises automatically relocating at least a portion of the graphical content, by a processor, to a portion of the row in a third format in response to a format transition condition such that in the third format N graphical items are displayed in a fixed format in the row, and N differs from the number of items displayed in the row in the first format or in the second format. 11. The method of claim 9, wherein the method comprises automatically relocating at least a portion of the graphical content, by a processor, to the displayed portion of the row in each of at least three of the following formats in response to a respective format transition condition: a horizontal scroll format, a fixed format with six graphical items displayed in the row, a fixed format with eight graphical items displayed in the row, a fixed format with ten graphical items displayed in the row, a fixed format with twelve graphical items displayed in the row. 12. The method of claim 9, wherein the method comprises detecting the format transition condition when the width of the row changes as a result of at least one of the following events:
a window of the graphical user interface which contains the displayed portion of the row is resized; the computing device screen or the graphical user interface changes between a landscape mode and a portrait mode; the graphical user interface is relocated from the first hardware screen of the first computing device to a second hardware screen which is also connected to the first computing device; or the graphical user interface is relocated from the first hardware screen of the first computing device to a third hardware screen which is connected to a second computing device. 13. The method of claim 9, wherein the graphical user interface displays a number of the graphical items in a fixed format, the displayed portion of the row has an area which changes to a new area, and the method comprises resizing the graphical items displayed in the row to match the new area without changing the number of graphical items of the row which are displayed. 14. The method of claim 9, wherein each of the graphical items has a minimum width, each of the graphical items has the same minimum width, the predetermined format transition value is within a tolerance of an integer multiple of the minimum width, and the tolerance is a value which is no more than one fifth of the minimum width. 15. A computer-readable storage medium configured with data and instructions which upon execution perform a method for dynamically relocating graphical content that is displayed in a graphical user interface, thereby adjusting content density in response to changes in the area available through the graphical user interface for displaying the graphical content, the method comprising:
displaying a number of graphical items in a first format within the graphical user interface on a first hardware screen of a first computing device, the graphical items including graphical content, the first format being one of: a horizontal scroll format or a fixed format; detecting a change in the number of graphical items to be displayed, the change being such that the number of graphical items to be displayed crosses a predetermined format transition value; and automatically performing, by a processor, at least one of the following format transitions: (a) relocating at least a portion of at least one of the graphical items so that graphical content which, before the format transition was not displayed but was available for display in a horizontal scroll format, is displayed after the format transition in a fixed format; (b) relocating at least a portion of at least one of the graphical items so that graphical content which, before the format transition was displayed in a fixed format, is not displayed after the format transition but is available for display in a horizontal scroll format; (c) as a display area containing the displayed graphical items is continuously resized, continuously resizing the displayed graphical items in a fixed format having M graphical items displayed and then as the display area continues being resized displaying the displayed graphical items in a fixed format having N graphical items displayed, with M and N being different positive integers. 16. The computer-readable storage medium of claim 15, wherein at least one of the following conditions is met:
the number of graphical items displayed in the first format decreases and the format transition changes the display from a fixed format to a horizontal scroll format; the number of graphical items displayed in the first format increases and the format transition changes the display from a horizontal scroll format to a fixed format; the format transition changes the display from a fixed format displaying N items to a fixed format displaying M items, where N and M are each a positive multiple of K, and K is an integer larger than 1. 17. The computer-readable storage medium of claim 15, wherein each of the graphical items has the same width. 18. The computer-readable storage medium of claim 15, wherein the format transition comprises at least one of the relocating steps. 19. The computer-readable storage medium of claim 15, wherein the format transition comprises continuously and correspondingly resizing the displayed graphical items as a display area of the row is continuously resized while displaying M graphical items in a fixed format and then as the display area continues being resized displaying N graphical items in a fixed format, with M and N being different non-consecutive positive integers. 20. The computer-readable storage medium of claim 15, wherein the method comprises transitioning between a fixed format and a horizontal scroll format in conjunction with moving the displayed graphical items between the first hardware screen of the first computing device and a second hardware screen of a second computing device. | Changes in display area automatically lead to changes in the format used to display graphical content of a list of items such as thumbnails or application icons, for example. A list display controller transitions between scrollable format and fixed format, and transitions between fixed formats with different numbers of display slots. Transitions may be triggered by window resizing, by moving a graphical user interface from one device to another while the application runs, or by switching between landscape and portrait mode, for example. Even when the format is not changed in response to a display area change, graphical content is automatically resized to match changes in the size of the display area containing the graphical content. Format transitions and content resizing help provide a pleasant user experience by maintaining content density with expected usage patterns for a given device, and reduce proliferation of code versions.1. A computational system for dynamically adjusting content density by controlling whether a list displayed in a graphical user interface is scrollable, the system comprising:
a memory; a list of graphical items residing in the memory; a display subsystem having a hardware screen with a display area, a portion of the display area being available through the graphical user interface for displaying one or more of the graphical items in a list format, the list format having a visual orientation which is a vertical orientation or a horizontal orientation, the display area portion having dimensions which include a width and a height; a processor in operable communication with the memory and the display subsystem; and a list display controller which controls the processor to monitor the display subsystem to detect a display area portion change which alters the width or height of the display area portion and to automatically disable scrolling of displayed items along the visual orientation when a predetermined dimension of the display area portion along the visual orientation exceeds a predetermined threshold and to otherwise automatically enable such scrolling. 2. The system of claim 1, wherein each of the graphical items has a respective minimum size along an axis parallel to the visual orientation, and the predetermined threshold is a value which is not more than six times the smallest of the one or more minimum sizes. 3. The system of claim 1, wherein the display subsystem includes at least one hardware screen whose display area portion dimension exceeds the predetermined threshold and also includes at least one other hardware screen whose display area portion dimension does not exceed the predetermined threshold. 4. The system of claim 1, wherein the display subsystem comprises a hardware phone screen having a phone screen display area, the display subsystem also comprises a hardware larger screen, the hardware larger screen has a larger screen display area which is larger than the phone screen display area, and the list display controller controls the processor to transition from a horizontal scroll format as the list format on the hardware phone screen to a fixed format as the list format on the hardware larger screen. 5. The system of claim 1, wherein the display subsystem includes at least three hardware screens with respective display area portions having different respective dimensions, and the list display controller controls the processor to display a different respective number of the graphical items at a time on each respective hardware screen based on the respective dimensions of the hardware screens without scrolling the displayed graphical items along the visual orientation on any of the three hardware screens. 6. The system of claim 1, wherein the list display controller automatically disables scrolling of displayed graphical items along the visual orientation when an entire displayed page of the graphical items can be swiped from display as a unit by a user command directed to the list display controller. 7. The system of claim 1, wherein the visual orientation is a horizontal orientation, the list display controller compares the display area portion width to at least one template width of a group of at least three different template widths, the list display controller identifies the largest template width which fits within the display area portion width, and the list display controller specifies a number of the graphical items to display in a fixed format row in the display area portion based on the identified template width. 8. The system of claim 1, wherein the display subsystem comprises a phone screen and also comprises at least one of the following hardware screens: a tablet screen, a laptop screen, a game system screen, a television screen, a hardware screen which has at least four times as much display area as the phone screen. 9. A computer-implemented method for dynamically adjusting content density by relocating graphical content within an underlying row displayed in a graphical user interface, the method comprising:
displaying graphical content of a first graphical item in a first format in a displayed portion of the row within the graphical user interface on a first hardware screen of a first computing device; displaying at least a portion of graphical content of at least one additional graphical item in the first format in the displayed portion of the row within the graphical user interface; constantly monitoring a width of the displayed portion of the row to detect a format transition condition where the width crosses a predetermined format transition value; and automatically relocating at least a portion of the graphical content, by a processor, to a portion of the row in a second format in response to the format transition condition so that the graphical content displayed in the row to a user changes in at least one of the following ways: (a) graphical content which before the format transition condition was not displayed but was available for display in a horizontal scroll format is displayed after the format transition condition in a fixed format, or (b) graphical content which before the format transition condition was displayed in a fixed format is not displayed after the format transition condition but is available for display in a horizontal scroll format. 10. The method of claim 9, wherein the method further comprises automatically relocating at least a portion of the graphical content, by a processor, to a portion of the row in a third format in response to a format transition condition such that in the third format N graphical items are displayed in a fixed format in the row, and N differs from the number of items displayed in the row in the first format or in the second format. 11. The method of claim 9, wherein the method comprises automatically relocating at least a portion of the graphical content, by a processor, to the displayed portion of the row in each of at least three of the following formats in response to a respective format transition condition: a horizontal scroll format, a fixed format with six graphical items displayed in the row, a fixed format with eight graphical items displayed in the row, a fixed format with ten graphical items displayed in the row, a fixed format with twelve graphical items displayed in the row. 12. The method of claim 9, wherein the method comprises detecting the format transition condition when the width of the row changes as a result of at least one of the following events:
a window of the graphical user interface which contains the displayed portion of the row is resized; the computing device screen or the graphical user interface changes between a landscape mode and a portrait mode; the graphical user interface is relocated from the first hardware screen of the first computing device to a second hardware screen which is also connected to the first computing device; or the graphical user interface is relocated from the first hardware screen of the first computing device to a third hardware screen which is connected to a second computing device. 13. The method of claim 9, wherein the graphical user interface displays a number of the graphical items in a fixed format, the displayed portion of the row has an area which changes to a new area, and the method comprises resizing the graphical items displayed in the row to match the new area without changing the number of graphical items of the row which are displayed. 14. The method of claim 9, wherein each of the graphical items has a minimum width, each of the graphical items has the same minimum width, the predetermined format transition value is within a tolerance of an integer multiple of the minimum width, and the tolerance is a value which is no more than one fifth of the minimum width. 15. A computer-readable storage medium configured with data and instructions which upon execution perform a method for dynamically relocating graphical content that is displayed in a graphical user interface, thereby adjusting content density in response to changes in the area available through the graphical user interface for displaying the graphical content, the method comprising:
displaying a number of graphical items in a first format within the graphical user interface on a first hardware screen of a first computing device, the graphical items including graphical content, the first format being one of: a horizontal scroll format or a fixed format; detecting a change in the number of graphical items to be displayed, the change being such that the number of graphical items to be displayed crosses a predetermined format transition value; and automatically performing, by a processor, at least one of the following format transitions: (a) relocating at least a portion of at least one of the graphical items so that graphical content which, before the format transition was not displayed but was available for display in a horizontal scroll format, is displayed after the format transition in a fixed format; (b) relocating at least a portion of at least one of the graphical items so that graphical content which, before the format transition was displayed in a fixed format, is not displayed after the format transition but is available for display in a horizontal scroll format; (c) as a display area containing the displayed graphical items is continuously resized, continuously resizing the displayed graphical items in a fixed format having M graphical items displayed and then as the display area continues being resized displaying the displayed graphical items in a fixed format having N graphical items displayed, with M and N being different positive integers. 16. The computer-readable storage medium of claim 15, wherein at least one of the following conditions is met:
the number of graphical items displayed in the first format decreases and the format transition changes the display from a fixed format to a horizontal scroll format; the number of graphical items displayed in the first format increases and the format transition changes the display from a horizontal scroll format to a fixed format; the format transition changes the display from a fixed format displaying N items to a fixed format displaying M items, where N and M are each a positive multiple of K, and K is an integer larger than 1. 17. The computer-readable storage medium of claim 15, wherein each of the graphical items has the same width. 18. The computer-readable storage medium of claim 15, wherein the format transition comprises at least one of the relocating steps. 19. The computer-readable storage medium of claim 15, wherein the format transition comprises continuously and correspondingly resizing the displayed graphical items as a display area of the row is continuously resized while displaying M graphical items in a fixed format and then as the display area continues being resized displaying N graphical items in a fixed format, with M and N being different non-consecutive positive integers. 20. The computer-readable storage medium of claim 15, wherein the method comprises transitioning between a fixed format and a horizontal scroll format in conjunction with moving the displayed graphical items between the first hardware screen of the first computing device and a second hardware screen of a second computing device. | 2,100 |
6,086 | 6,086 | 12,186,173 | 2,152 | A computer implemented system and method includes obtaining a query referring to rows in a relational database. A sparse index of the database that has a set of rows that is a subset of the rows referred to in the query is obtained. Rows referred to in the query that are not in the sparse index are then obtained and a union of such rows and the rows of the sparse index is performed to obtain a complete row set for processing the query. | 1. A computer implemented method comprising:
obtaining a query referring to rows in a relational database; obtaining a sparse index of the database that has a set of rows that is a subset of the rows referred to in the query; obtaining the rows referred to in the query that are not in the sparse index; and performing a union of such rows and the rows of the sparse index to obtain a complete row set for processing the query. 2. The method of claim 1 and further comprising processing the query against the complete row set. 3. The method of claim 1 wherein obtaining a sparse index comprises defining base tables with a partitioned primary index. 4. The method of claim 3 wherein new incoming data is stored in most recent partitions. 5. The method of claim 3 wherein the base tables are defined with data definition language statements comprising:
CREATE SET TABLE orders
(
o_orderkey INTEGER NOT NULL,
o_orderdate DATE FORMAT ‘yyyy-mm-dd’ NOT NULL,
o_amount integer)
PRIMARY INDEX ( o_orderkey )
PARTITION BY RANGE_N(o_orderdate BETWEEN DATE ‘xxx’
AND DATE ‘yyy’ EACH INTERVAL ‘zzz’ QQQ )
wherein xxx and yyy are dates, and zzz is a number of time periods QQQ. 6. The method of claim 1 and further comprising leveraging an aggregate join index (AJI) with aggregates at a same or lower level than in a query. 7. The method of claim 1 wherein rows referred to in the query that are not in the sparse index are obtained from a base table. 8. The method of claim 7 and further comprising rewriting the received query utilizing the sparse index, rows from the base table and union of the sparse index and rows from the base table. 9. The method of claim 8 and further comprising a sum following the union to deal with overlapping rows returned from the sparse index and rows from the base table. 10. A computer implemented method comprising:
obtaining a query referring to rows in a relational database; rewriting the query to select rows from a sparse index, obtain rows that are not in the sparse index and perform a union of such rows and the rows of the sparse index to obtain a complete row set for processing the query. 11. The method of claim 10 wherein the sparse index is defined from base tables with a partitioned primary index. 12. The method of claim 11 wherein the base tables are defined with data definition language statements comprising:
CREATE SET TABLE orders
(
o_orderkey INTEGER NOT NULL,
o_orderdate DATE FORMAT ‘yyyy-mm-dd’ NOT NULL,
o_amount integer)
PRIMARY INDEX ( o_orderkey )
PARTITION BY RANGE_N(o_orderdate BETWEEN DATE ‘xxx’
AND DATE ‘yyy’ EACH INTERVAL ‘zzz’ QQQ )
wherein xxx and yyy are dates, and zzz is a number of time periods QQQ. 13. The method of claim 10 and wherein the query is rewritten to leverage an aggregate join index (AJI) with aggregates at a same or lower level than in the query. 14. The method of claim 10 wherein rows referred to in the query that are not in the sparse index are obtained from a base table. 15. A computer readable medium having instructions for execution by a computer to perform a method comprising:
obtaining a query referring to rows in a relational database; obtaining a sparse index of the database that has a set of rows that is a subset of the rows referred to in the query; obtaining the rows referred to in the query that are not in the sparse index; and performing a union of such rows and the rows of the sparse index to obtain a complete row set for processing the query. 16. The computer readable medium of claim 15 wherein the method further comprises performing a sum following the union to deal with overlapping rows returned from the sparse index and rows from the base table. 17. A system comprising:
one or more processing units; one or more data storage units coupled to the one or more processors; one or more optimizers executing on the one or more processing units that are configured to:
obtain a query referring to rows in a relational database;
obtain a sparse index of the database that has a set of rows that is a subset of the rows referred to in the query;
obtain the rows referred to in the query that are not in the sparse index; and
perform a union of such rows and the rows of the sparse index to obtain a complete row set for processing the query. 18. The system of claim 17 wherein the one or more processors process the query against the complete row set. 19. The system of claim 17 wherein an aggregate join index (AJI) with aggregates at a same or lower level than in a query is leveraged. 20. The system of claim 17 wherein the query optimizer rewrites the received query utilizing the sparse index, rows from the base table and union of the sparse index and rows from the base table. | A computer implemented system and method includes obtaining a query referring to rows in a relational database. A sparse index of the database that has a set of rows that is a subset of the rows referred to in the query is obtained. Rows referred to in the query that are not in the sparse index are then obtained and a union of such rows and the rows of the sparse index is performed to obtain a complete row set for processing the query.1. A computer implemented method comprising:
obtaining a query referring to rows in a relational database; obtaining a sparse index of the database that has a set of rows that is a subset of the rows referred to in the query; obtaining the rows referred to in the query that are not in the sparse index; and performing a union of such rows and the rows of the sparse index to obtain a complete row set for processing the query. 2. The method of claim 1 and further comprising processing the query against the complete row set. 3. The method of claim 1 wherein obtaining a sparse index comprises defining base tables with a partitioned primary index. 4. The method of claim 3 wherein new incoming data is stored in most recent partitions. 5. The method of claim 3 wherein the base tables are defined with data definition language statements comprising:
CREATE SET TABLE orders
(
o_orderkey INTEGER NOT NULL,
o_orderdate DATE FORMAT ‘yyyy-mm-dd’ NOT NULL,
o_amount integer)
PRIMARY INDEX ( o_orderkey )
PARTITION BY RANGE_N(o_orderdate BETWEEN DATE ‘xxx’
AND DATE ‘yyy’ EACH INTERVAL ‘zzz’ QQQ )
wherein xxx and yyy are dates, and zzz is a number of time periods QQQ. 6. The method of claim 1 and further comprising leveraging an aggregate join index (AJI) with aggregates at a same or lower level than in a query. 7. The method of claim 1 wherein rows referred to in the query that are not in the sparse index are obtained from a base table. 8. The method of claim 7 and further comprising rewriting the received query utilizing the sparse index, rows from the base table and union of the sparse index and rows from the base table. 9. The method of claim 8 and further comprising a sum following the union to deal with overlapping rows returned from the sparse index and rows from the base table. 10. A computer implemented method comprising:
obtaining a query referring to rows in a relational database; rewriting the query to select rows from a sparse index, obtain rows that are not in the sparse index and perform a union of such rows and the rows of the sparse index to obtain a complete row set for processing the query. 11. The method of claim 10 wherein the sparse index is defined from base tables with a partitioned primary index. 12. The method of claim 11 wherein the base tables are defined with data definition language statements comprising:
CREATE SET TABLE orders
(
o_orderkey INTEGER NOT NULL,
o_orderdate DATE FORMAT ‘yyyy-mm-dd’ NOT NULL,
o_amount integer)
PRIMARY INDEX ( o_orderkey )
PARTITION BY RANGE_N(o_orderdate BETWEEN DATE ‘xxx’
AND DATE ‘yyy’ EACH INTERVAL ‘zzz’ QQQ )
wherein xxx and yyy are dates, and zzz is a number of time periods QQQ. 13. The method of claim 10 and wherein the query is rewritten to leverage an aggregate join index (AJI) with aggregates at a same or lower level than in the query. 14. The method of claim 10 wherein rows referred to in the query that are not in the sparse index are obtained from a base table. 15. A computer readable medium having instructions for execution by a computer to perform a method comprising:
obtaining a query referring to rows in a relational database; obtaining a sparse index of the database that has a set of rows that is a subset of the rows referred to in the query; obtaining the rows referred to in the query that are not in the sparse index; and performing a union of such rows and the rows of the sparse index to obtain a complete row set for processing the query. 16. The computer readable medium of claim 15 wherein the method further comprises performing a sum following the union to deal with overlapping rows returned from the sparse index and rows from the base table. 17. A system comprising:
one or more processing units; one or more data storage units coupled to the one or more processors; one or more optimizers executing on the one or more processing units that are configured to:
obtain a query referring to rows in a relational database;
obtain a sparse index of the database that has a set of rows that is a subset of the rows referred to in the query;
obtain the rows referred to in the query that are not in the sparse index; and
perform a union of such rows and the rows of the sparse index to obtain a complete row set for processing the query. 18. The system of claim 17 wherein the one or more processors process the query against the complete row set. 19. The system of claim 17 wherein an aggregate join index (AJI) with aggregates at a same or lower level than in a query is leveraged. 20. The system of claim 17 wherein the query optimizer rewrites the received query utilizing the sparse index, rows from the base table and union of the sparse index and rows from the base table. | 2,100 |
6,087 | 6,087 | 15,630,322 | 2,192 | In a system of developing a screen by reusing a componentized element, the component can be developed while achieving consistency and harmony with an appearance of an entire screen. According to an embodiment, the system has: a component development controller that receives a request for development of a reusable component; a component development model that acquires information containing a source code of the component; and a component development view that displays a predetermined background image on a developer terminal and a component development region for displaying an appearance of the component which is a development target so as to overlap on the background image. When the source code of the component which is the development target is edited, the component which is the development target is displayed based on the source code in the component development region to provide the appearance defined by a template compatible with the device type. | 1. A development support system that supports screen development of a Web application that receives a request from a client terminal and that returns a processing result screen compatible with a device type of the client terminal, the development support system comprising:
a template that is formed of a combination of one or more screen parts and that defines an appearance of each of the screen parts when being displayed on a screen for each of the device types; a component development controller that receives, through a developer terminal, a request for development of a component reusable to the screen development of the Web application; a component development model that acquires information containing a source code of the component based on an instruction from the component development controller; and a component development view that displays, on the developer terminal, a predetermined background image compatible with the device type specified by the developer terminal based on the instruction from the component development controller, and that displays, on the developer terminal, a component development region for displaying the appearance of the component which is a development target so as to overlap on the background image, wherein, when the source code of the component which is the development target is edited, the component which is the development target is displayed based on the source code in the component development region so as to provide the appearance defined by the template compatible with the device type specified by the developer terminal. 2. The development support system according to claim 1,
wherein a size and/or a position of the component development region can be changed by an instruction of a developer. | In a system of developing a screen by reusing a componentized element, the component can be developed while achieving consistency and harmony with an appearance of an entire screen. According to an embodiment, the system has: a component development controller that receives a request for development of a reusable component; a component development model that acquires information containing a source code of the component; and a component development view that displays a predetermined background image on a developer terminal and a component development region for displaying an appearance of the component which is a development target so as to overlap on the background image. When the source code of the component which is the development target is edited, the component which is the development target is displayed based on the source code in the component development region to provide the appearance defined by a template compatible with the device type.1. A development support system that supports screen development of a Web application that receives a request from a client terminal and that returns a processing result screen compatible with a device type of the client terminal, the development support system comprising:
a template that is formed of a combination of one or more screen parts and that defines an appearance of each of the screen parts when being displayed on a screen for each of the device types; a component development controller that receives, through a developer terminal, a request for development of a component reusable to the screen development of the Web application; a component development model that acquires information containing a source code of the component based on an instruction from the component development controller; and a component development view that displays, on the developer terminal, a predetermined background image compatible with the device type specified by the developer terminal based on the instruction from the component development controller, and that displays, on the developer terminal, a component development region for displaying the appearance of the component which is a development target so as to overlap on the background image, wherein, when the source code of the component which is the development target is edited, the component which is the development target is displayed based on the source code in the component development region so as to provide the appearance defined by the template compatible with the device type specified by the developer terminal. 2. The development support system according to claim 1,
wherein a size and/or a position of the component development region can be changed by an instruction of a developer. | 2,100 |
6,088 | 6,088 | 14,847,088 | 2,153 | A system receives a query and an information space is queried based on the query. Results of the query of the information space are received and each of the results is associated with a respective time period. Each of a plurality of pictograms representing one or more results that are associated with the respective time period is determined The plurality of pictograms are displayed in a linear progression and in chronological order with respect to one another based on their respective time periods. | 1. A method comprising:
receiving a query; querying an information space based on the query; receiving results of the query of the information space; associating each of the results with one of a plurality of groups with each group of the plurality of groups representing a respective time period; determining an pictogram representing each group of the plurality of groups; and displaying the plurality of pictograms in a linear progression and in chronological order with respect to one another. 2. The method of claim 1, further comprising:
determining a most common phrase or term within each group of the plurality of groups; and labeling each pictogram with the most common phrase or term associated with the group represented by the pictogram, wherein the linear progression is a horizontal progression with respect to a display screen. 3. The method of claim 1, further comprising:
receiving an indication of a cursor co-located with one of the plurality of pictograms; and in response to the indication, displaying information associated with the group that is represented by the one of the plurality of pictograms. 4. The method of claim 1, wherein the results comprise a plurality of snippets, each snippet of the plurality of snippets associated with a uniform resource locator (“URL”), the method further comprising:
receiving an indication of a user selection of one of the plurality of pictograms; and
in response to the indication, displaying the plurality of snippets and respective URLs associated with the group that is represented by the one of the plurality of pictograms. 5. The method of the claim 1, wherein a size of a first of the plurality of pictograms is based on a relevance of the results associated with the group that is represented by the first of the plurality of pictograms and a size of a second of the plurality of pictograms is based on a relevance of the results associated with the group that is represented by the second of the plurality of pictograms, wherein the first size is different from the second size. 6. The method of the claim 1, wherein a first of the plurality of pictograms is visually enhanced is based on an amount of the results associated with the group that is represented by the first of the plurality of pictograms. 7. The method of claim 1, further comprising:
displaying a chronological indicator linking a first pictogram of the plurality of pictograms with a second pictogram of the plurality of pictograms. 8. The method of claim 1, further comprising:
displaying a causal indicator linking a first pictogram of the plurality of pictograms with a second pictogram of the plurality of pictograms. 9. A system comprising:
a processor; and a non-transitory computer-readable medium storing program code, the program code executable by a computer system to cause the computer system to: receive a query; query an information space based on the query; receive results of the query of the information space; associate each of the results with a respective time period; associate each of the results with one or more of a plurality of categories; and for each category of the plurality of categories, determine a plurality of pictograms, each of the plurality of pictograms representing one or more results that are associated with the category and with a respective time period, and display the plurality of pictograms determined for each category in a linear progression and in chronological order with respect to one another based on their respective time periods. 10. The system of claim 9, wherein the linear progression is a horizontal progression with respect to a display screen. 11. The system of claim 9, further comprising program code executable by a computer system to cause the computer system to:
receive an indication of a cursor co-located with one of the plurality of pictograms; and in response to the indication, display information associated with the group that is represented by the one of the plurality of pictograms. 12. The system of claim 9, wherein the results comprise a plurality of snippets, each snippet of the plurality of snippets associated with a uniform resource locator (“URL”) and further comprising program code executable by a computer system to cause the computer system to:
receive an indication of a user selection of one of the plurality of pictograms; and
in response to the indication, display the plurality of snippets and respective URLs being represented by the one of the plurality of pictograms. 13. The system of the claim 9, wherein a size of a first of the plurality of pictograms is based on a relevance of the results being represented by the first of the plurality of pictograms and a size of a second of the plurality of pictograms is based on a relevance of the results being represented by the second of the plurality of pictograms, wherein the first size is different from the second size. 14. The system of the claim 9, wherein a first of the plurality of pictograms is visually enhanced is based on an amount of the results associated with the group that is represented by the first of the plurality of pictograms. 15. The system of claim 9, further comprising program code executable by a computer system to cause the computer system to:
display a chronological indicator linking a first pictogram of the plurality of pictograms with a second pictogram of the plurality of pictograms. 16. The system of claim 9, further comprising program code executable by a computer system to cause the computer system to:
display a causal indicator linking a first pictogram of the plurality of pictograms with a second pictogram of the plurality of pictograms. 17. A non-transitory computer-readable medium storing program code, the program code executable by a computer system to cause the computer system to:
receive a query; query an information space based on the query; receive results of the query of the information space; associate each of the results with a respective time period; associate each of the results with one or more of a plurality of categories; and for each category of the plurality of categories, determine a plurality of pictograms, each of the plurality of pictograms representing one or more results that are associated with the category and with a respective time period, and display the plurality of pictograms determined for each category in a horizontal linear progression and in chronological order with respect to one another based on their respective time periods. 18. The medium of the claim 17, wherein a size of a first of the plurality of pictograms is based on a relevance of the results being represented by the first of the plurality of pictograms and a size of a second of the plurality of pictograms is based on a relevance of the results being represented by the second of the plurality of pictograms, wherein the first size is different from the second size. 19. The medium of the claim 17, wherein a first of the plurality of pictograms is visually enhanced is based on an amount of the results associated with the group that is represented by the first of the plurality of pictograms. 20. The system of claim 9, further comprising program code executable by a computer system to cause the computer system to:
display a chronological indicator linking a first pictogram of the plurality of pictograms with a second pictogram of the plurality of pictograms; and display a causal indicator linking the second pictogram of the plurality of pictograms with a third pictogram of the plurality of pictograms. | A system receives a query and an information space is queried based on the query. Results of the query of the information space are received and each of the results is associated with a respective time period. Each of a plurality of pictograms representing one or more results that are associated with the respective time period is determined The plurality of pictograms are displayed in a linear progression and in chronological order with respect to one another based on their respective time periods.1. A method comprising:
receiving a query; querying an information space based on the query; receiving results of the query of the information space; associating each of the results with one of a plurality of groups with each group of the plurality of groups representing a respective time period; determining an pictogram representing each group of the plurality of groups; and displaying the plurality of pictograms in a linear progression and in chronological order with respect to one another. 2. The method of claim 1, further comprising:
determining a most common phrase or term within each group of the plurality of groups; and labeling each pictogram with the most common phrase or term associated with the group represented by the pictogram, wherein the linear progression is a horizontal progression with respect to a display screen. 3. The method of claim 1, further comprising:
receiving an indication of a cursor co-located with one of the plurality of pictograms; and in response to the indication, displaying information associated with the group that is represented by the one of the plurality of pictograms. 4. The method of claim 1, wherein the results comprise a plurality of snippets, each snippet of the plurality of snippets associated with a uniform resource locator (“URL”), the method further comprising:
receiving an indication of a user selection of one of the plurality of pictograms; and
in response to the indication, displaying the plurality of snippets and respective URLs associated with the group that is represented by the one of the plurality of pictograms. 5. The method of the claim 1, wherein a size of a first of the plurality of pictograms is based on a relevance of the results associated with the group that is represented by the first of the plurality of pictograms and a size of a second of the plurality of pictograms is based on a relevance of the results associated with the group that is represented by the second of the plurality of pictograms, wherein the first size is different from the second size. 6. The method of the claim 1, wherein a first of the plurality of pictograms is visually enhanced is based on an amount of the results associated with the group that is represented by the first of the plurality of pictograms. 7. The method of claim 1, further comprising:
displaying a chronological indicator linking a first pictogram of the plurality of pictograms with a second pictogram of the plurality of pictograms. 8. The method of claim 1, further comprising:
displaying a causal indicator linking a first pictogram of the plurality of pictograms with a second pictogram of the plurality of pictograms. 9. A system comprising:
a processor; and a non-transitory computer-readable medium storing program code, the program code executable by a computer system to cause the computer system to: receive a query; query an information space based on the query; receive results of the query of the information space; associate each of the results with a respective time period; associate each of the results with one or more of a plurality of categories; and for each category of the plurality of categories, determine a plurality of pictograms, each of the plurality of pictograms representing one or more results that are associated with the category and with a respective time period, and display the plurality of pictograms determined for each category in a linear progression and in chronological order with respect to one another based on their respective time periods. 10. The system of claim 9, wherein the linear progression is a horizontal progression with respect to a display screen. 11. The system of claim 9, further comprising program code executable by a computer system to cause the computer system to:
receive an indication of a cursor co-located with one of the plurality of pictograms; and in response to the indication, display information associated with the group that is represented by the one of the plurality of pictograms. 12. The system of claim 9, wherein the results comprise a plurality of snippets, each snippet of the plurality of snippets associated with a uniform resource locator (“URL”) and further comprising program code executable by a computer system to cause the computer system to:
receive an indication of a user selection of one of the plurality of pictograms; and
in response to the indication, display the plurality of snippets and respective URLs being represented by the one of the plurality of pictograms. 13. The system of the claim 9, wherein a size of a first of the plurality of pictograms is based on a relevance of the results being represented by the first of the plurality of pictograms and a size of a second of the plurality of pictograms is based on a relevance of the results being represented by the second of the plurality of pictograms, wherein the first size is different from the second size. 14. The system of the claim 9, wherein a first of the plurality of pictograms is visually enhanced is based on an amount of the results associated with the group that is represented by the first of the plurality of pictograms. 15. The system of claim 9, further comprising program code executable by a computer system to cause the computer system to:
display a chronological indicator linking a first pictogram of the plurality of pictograms with a second pictogram of the plurality of pictograms. 16. The system of claim 9, further comprising program code executable by a computer system to cause the computer system to:
display a causal indicator linking a first pictogram of the plurality of pictograms with a second pictogram of the plurality of pictograms. 17. A non-transitory computer-readable medium storing program code, the program code executable by a computer system to cause the computer system to:
receive a query; query an information space based on the query; receive results of the query of the information space; associate each of the results with a respective time period; associate each of the results with one or more of a plurality of categories; and for each category of the plurality of categories, determine a plurality of pictograms, each of the plurality of pictograms representing one or more results that are associated with the category and with a respective time period, and display the plurality of pictograms determined for each category in a horizontal linear progression and in chronological order with respect to one another based on their respective time periods. 18. The medium of the claim 17, wherein a size of a first of the plurality of pictograms is based on a relevance of the results being represented by the first of the plurality of pictograms and a size of a second of the plurality of pictograms is based on a relevance of the results being represented by the second of the plurality of pictograms, wherein the first size is different from the second size. 19. The medium of the claim 17, wherein a first of the plurality of pictograms is visually enhanced is based on an amount of the results associated with the group that is represented by the first of the plurality of pictograms. 20. The system of claim 9, further comprising program code executable by a computer system to cause the computer system to:
display a chronological indicator linking a first pictogram of the plurality of pictograms with a second pictogram of the plurality of pictograms; and display a causal indicator linking the second pictogram of the plurality of pictograms with a third pictogram of the plurality of pictograms. | 2,100 |
6,089 | 6,089 | 13,004,980 | 2,169 | A computer implemented method of finding commonalities among search terms within an electronic database, comprises the steps of: receiving at least two search terms from a user; performing an individual computerized search within the electronic database for each of the at least two search terms; generating a plurality of individual results for each of the at least two search terms; identifying at least one commonality mutually shared by at least two of the plurality of individual results; and presenting the at least one commonality. The at least one commonality can comprise a plurality of commonalities which can be ranked based on the number of search terms with which the commonality is associated, where the commonality associated with the greatest number of search terms is ranked highest. The ranking can be further based on frequency of the commonality across all individual results, link distance or other standard measures of commonality. | 1. A computer implemented method of finding commonalities among search terms within an electronic database, comprising the steps of:
receiving, via a computing device, at least two search terms from a user; performing, via the computing device, an individual computerized search within the electronic database for each of the at least two search terms; generating, via the computing device, a plurality of individual results for each of the at least two search terms; identifying, via the computing device, at least one commonality mutually shared by at least two of the plurality of individual results; and presenting, via the computing device, to the user the at least one commonality. 2. The computer implemented method of claim 1, further comprising the step of removing, via the computing device, all individual results from the plurality of individual results lacking the at least one commonality. 3. The computer implemented method of claim 1, wherein the electronic database comprises a closed database. 4. The computer implemented method of claim 3, wherein the closed database includes a local database, an email server, a corporate directory, a closed social network, a research database, or an intranet. 5. The computer implemented method of claim 1, wherein the electronic database comprises an open database. 6. The computer implemented method of claim 5, wherein the open database includes the Internet or an open social network. 7. The computer implemented method of claim 1, wherein the electronic database comprises both an open database and a closed database. 8. The computer implemented method of claim 1, further comprising the step of excluding, via the computing device, all non-informative commonalities from the at least one commonality. 9. The computer implemented method of claim 1, wherein the at least one commonality comprises a plurality of commonalities. 10. The computer implemented method of claim 9, further comprising the step of ranking, via the computing device, the plurality of commonalities. 11. The computer implemented method of claim 10, wherein the step of ranking the plurality of commonalities is based on the number of search terms with which the commonality is associated, where the commonality associated with the greatest number of search terms is ranked highest. 12. The computer implemented method of claim 11, wherein the step of ranking the plurality of commonalities is further based on a frequency of the commonality across all individual results, where the commonality repeated with the greatest frequency is ranked highest. 13. The computer implemented method of claim 12, wherein the step of ranking the plurality of commonalities is further based on a link distance, where the commonality with the smallest link distance is ranked highest. 14. The computer implemented method of claim 1, wherein the step of presenting the at least one commonality to the user comprises displaying each of the at least two search terms as column headers. 15. The computer implemented method of claim 14, wherein the step of presenting the at least one commonality to the user further comprises displaying each of the at least one commonality as row headers. 16. The computer implemented method of claim 15, wherein the step of presenting the at least one commonality to the user further comprises displaying each of the plurality of individual results below its corresponding column header and adjacent to its corresponding row header. 17. The computer implemented method of claim 1, further comprising the step of receiving an additional search term from a user after a first predetermined keyboard shortcut. 18. The computer implemented method of claim 17, wherein the first predetermined keyboard shortcut comprises a double space. 19. The computer implemented method of claim 18, further comprising the step of removing the additional search term after a second predetermined keyboard shortcut. 20. The computer implemented method of claim 19, wherein the second predetermined keyboard shortcut comprises a double backspace. 21. The computer implemented method of claim 9, wherein the database comprises the Internet and wherein the plurality of individual results for each of the at least two search terms comprise hidden descriptive identifiers. 22. The computer implemented method of claim 21, wherein the hidden descriptive identifiers comprise metatext. 23. The computer implemented method of claim 22, further comprising the step of ranking, via the computing device, the plurality of commonalities from the individual results based on the metatext, where the metatext repeated with the greatest frequency is ranked highest. 24. The computer implemented method of claim 1, wherein the presenting step further comprises providing information associated with the at least one commonality including an accessible web address. 25. The computer implemented method of claim 1, wherein the presenting step further comprises providing graphical representations of commonalities. 26. The computer implemented method of claim 1, wherein at least one of the at least two search terms is a predefined group. 27. The computer implemented method of claim 9, further comprising the step of removing, via the computing device, a particular commonality from the plurality of commonalities, the removed commonality corresponding to a user-defined restriction term. 28. The computer implemented method of claim 10, further comprising the step of re-sorting the ranking of the plurality of commonalities based upon a manual re-sorting of the rankings by the user. 29. The computer implemented method of claim 28, wherein the user can manually re-sort the rankings by dragging a particular commonality higher or lower in ranking. 30. The computer implemented method of claim 9, further comprising the step of manually removing a particular commonality from the plurality of commonalities. 31. The computer implemented method of claim 30, further comprising the step of receiving, via the computing device, a subsequent input from the user for a future commonality search. 32. The computer implemented method of claim 1, further comprising the step of providing a sponsored advertisement or product placement associated with the at least one commonality or a group of commonalities. 33. The computer implemented method of claim 32, wherein the sponsored advertisement or product placement is determined by the highest bidder. 34. A computer-readable medium having computer-readable instructions stored thereon which, which executed by a computer, cause the computer to perform a method of finding commonalities among search terms within an electronic database, comprising the steps of:
receiving, through the computer, at least two search terms from a user; performing, through the computer, an individual computerized search within an electronic database for each of the at least two search terms; generating, through the computer, a plurality of individual results for each of the at least two search terms; identifying, through the computer, at least one commonality mutually shared by at least two of the plurality of individual results; and presenting, through the computer, to the user the at least one commonality. 35. The computer-readable medium of claim 34, wherein the at least one commonality comprises a plurality of commonalities. 36. The computer-readable medium of claim 35, further comprising the step of ranking the plurality of commonalities. 37. The computer-readable medium of claim 36, wherein the step of ranking the plurality of commonalities is based on the number of search terms with which the commonality is associated, where the commonality associated with the greatest number of search terms is ranked highest. 38. The computer-readable medium of claim 37, wherein the step of ranking the plurality of commonalities is further based on a frequency of the commonality across all individual results, where the commonality repeated with the greatest frequency is ranked highest. 39. The computer-readable medium of claim 38, wherein the step of ranking the plurality of commonalities is further based on a link distance, where the commonality with the smallest link distance is ranked highest. 40. The computer-readable medium of claim 39, further comprising the step of removing a particular commonality from the plurality of commonalities, the removed commonality corresponding to a user-defined restriction term. 41. A computing device configured to perform operations comprising:
receiving, through the computing device, at least two search terms from a user; performing, through the computing device, an individual computerized search within an electronic database for each of the at least two search terms; generating, through the computing device, a plurality of individual results for each of the at least two search terms; identifying, through the computing device, a plurality of commonalities mutually shared by at least two of the plurality of individual results; and presenting, through the computing device, to the user the at least one commonality. 42. The computing device of claim 41, further comprising ranking, through the computing device, the plurality of commonalities wherein the ranking the plurality of commonalities is based on the number of search terms with which the commonality is associated, where the commonality associated with the greatest number of search terms is ranked highest. 43. The computing device of claim 42, wherein the ranking the plurality of commonalities is further based on a frequency of the commonality across all individual results, where the commonality repeated with the greatest frequency is ranked highest. 44. The computing device of claim 43, wherein the ranking the plurality of commonalities is further based on a link distance, where the commonality with the smallest link distance is ranked highest. 45. The computing device of claim 44, further comprising removing, through the computing device, a particular commonality from the plurality of commonalities wherein the removed commonality corresponds to a user-defined restriction term. | A computer implemented method of finding commonalities among search terms within an electronic database, comprises the steps of: receiving at least two search terms from a user; performing an individual computerized search within the electronic database for each of the at least two search terms; generating a plurality of individual results for each of the at least two search terms; identifying at least one commonality mutually shared by at least two of the plurality of individual results; and presenting the at least one commonality. The at least one commonality can comprise a plurality of commonalities which can be ranked based on the number of search terms with which the commonality is associated, where the commonality associated with the greatest number of search terms is ranked highest. The ranking can be further based on frequency of the commonality across all individual results, link distance or other standard measures of commonality.1. A computer implemented method of finding commonalities among search terms within an electronic database, comprising the steps of:
receiving, via a computing device, at least two search terms from a user; performing, via the computing device, an individual computerized search within the electronic database for each of the at least two search terms; generating, via the computing device, a plurality of individual results for each of the at least two search terms; identifying, via the computing device, at least one commonality mutually shared by at least two of the plurality of individual results; and presenting, via the computing device, to the user the at least one commonality. 2. The computer implemented method of claim 1, further comprising the step of removing, via the computing device, all individual results from the plurality of individual results lacking the at least one commonality. 3. The computer implemented method of claim 1, wherein the electronic database comprises a closed database. 4. The computer implemented method of claim 3, wherein the closed database includes a local database, an email server, a corporate directory, a closed social network, a research database, or an intranet. 5. The computer implemented method of claim 1, wherein the electronic database comprises an open database. 6. The computer implemented method of claim 5, wherein the open database includes the Internet or an open social network. 7. The computer implemented method of claim 1, wherein the electronic database comprises both an open database and a closed database. 8. The computer implemented method of claim 1, further comprising the step of excluding, via the computing device, all non-informative commonalities from the at least one commonality. 9. The computer implemented method of claim 1, wherein the at least one commonality comprises a plurality of commonalities. 10. The computer implemented method of claim 9, further comprising the step of ranking, via the computing device, the plurality of commonalities. 11. The computer implemented method of claim 10, wherein the step of ranking the plurality of commonalities is based on the number of search terms with which the commonality is associated, where the commonality associated with the greatest number of search terms is ranked highest. 12. The computer implemented method of claim 11, wherein the step of ranking the plurality of commonalities is further based on a frequency of the commonality across all individual results, where the commonality repeated with the greatest frequency is ranked highest. 13. The computer implemented method of claim 12, wherein the step of ranking the plurality of commonalities is further based on a link distance, where the commonality with the smallest link distance is ranked highest. 14. The computer implemented method of claim 1, wherein the step of presenting the at least one commonality to the user comprises displaying each of the at least two search terms as column headers. 15. The computer implemented method of claim 14, wherein the step of presenting the at least one commonality to the user further comprises displaying each of the at least one commonality as row headers. 16. The computer implemented method of claim 15, wherein the step of presenting the at least one commonality to the user further comprises displaying each of the plurality of individual results below its corresponding column header and adjacent to its corresponding row header. 17. The computer implemented method of claim 1, further comprising the step of receiving an additional search term from a user after a first predetermined keyboard shortcut. 18. The computer implemented method of claim 17, wherein the first predetermined keyboard shortcut comprises a double space. 19. The computer implemented method of claim 18, further comprising the step of removing the additional search term after a second predetermined keyboard shortcut. 20. The computer implemented method of claim 19, wherein the second predetermined keyboard shortcut comprises a double backspace. 21. The computer implemented method of claim 9, wherein the database comprises the Internet and wherein the plurality of individual results for each of the at least two search terms comprise hidden descriptive identifiers. 22. The computer implemented method of claim 21, wherein the hidden descriptive identifiers comprise metatext. 23. The computer implemented method of claim 22, further comprising the step of ranking, via the computing device, the plurality of commonalities from the individual results based on the metatext, where the metatext repeated with the greatest frequency is ranked highest. 24. The computer implemented method of claim 1, wherein the presenting step further comprises providing information associated with the at least one commonality including an accessible web address. 25. The computer implemented method of claim 1, wherein the presenting step further comprises providing graphical representations of commonalities. 26. The computer implemented method of claim 1, wherein at least one of the at least two search terms is a predefined group. 27. The computer implemented method of claim 9, further comprising the step of removing, via the computing device, a particular commonality from the plurality of commonalities, the removed commonality corresponding to a user-defined restriction term. 28. The computer implemented method of claim 10, further comprising the step of re-sorting the ranking of the plurality of commonalities based upon a manual re-sorting of the rankings by the user. 29. The computer implemented method of claim 28, wherein the user can manually re-sort the rankings by dragging a particular commonality higher or lower in ranking. 30. The computer implemented method of claim 9, further comprising the step of manually removing a particular commonality from the plurality of commonalities. 31. The computer implemented method of claim 30, further comprising the step of receiving, via the computing device, a subsequent input from the user for a future commonality search. 32. The computer implemented method of claim 1, further comprising the step of providing a sponsored advertisement or product placement associated with the at least one commonality or a group of commonalities. 33. The computer implemented method of claim 32, wherein the sponsored advertisement or product placement is determined by the highest bidder. 34. A computer-readable medium having computer-readable instructions stored thereon which, which executed by a computer, cause the computer to perform a method of finding commonalities among search terms within an electronic database, comprising the steps of:
receiving, through the computer, at least two search terms from a user; performing, through the computer, an individual computerized search within an electronic database for each of the at least two search terms; generating, through the computer, a plurality of individual results for each of the at least two search terms; identifying, through the computer, at least one commonality mutually shared by at least two of the plurality of individual results; and presenting, through the computer, to the user the at least one commonality. 35. The computer-readable medium of claim 34, wherein the at least one commonality comprises a plurality of commonalities. 36. The computer-readable medium of claim 35, further comprising the step of ranking the plurality of commonalities. 37. The computer-readable medium of claim 36, wherein the step of ranking the plurality of commonalities is based on the number of search terms with which the commonality is associated, where the commonality associated with the greatest number of search terms is ranked highest. 38. The computer-readable medium of claim 37, wherein the step of ranking the plurality of commonalities is further based on a frequency of the commonality across all individual results, where the commonality repeated with the greatest frequency is ranked highest. 39. The computer-readable medium of claim 38, wherein the step of ranking the plurality of commonalities is further based on a link distance, where the commonality with the smallest link distance is ranked highest. 40. The computer-readable medium of claim 39, further comprising the step of removing a particular commonality from the plurality of commonalities, the removed commonality corresponding to a user-defined restriction term. 41. A computing device configured to perform operations comprising:
receiving, through the computing device, at least two search terms from a user; performing, through the computing device, an individual computerized search within an electronic database for each of the at least two search terms; generating, through the computing device, a plurality of individual results for each of the at least two search terms; identifying, through the computing device, a plurality of commonalities mutually shared by at least two of the plurality of individual results; and presenting, through the computing device, to the user the at least one commonality. 42. The computing device of claim 41, further comprising ranking, through the computing device, the plurality of commonalities wherein the ranking the plurality of commonalities is based on the number of search terms with which the commonality is associated, where the commonality associated with the greatest number of search terms is ranked highest. 43. The computing device of claim 42, wherein the ranking the plurality of commonalities is further based on a frequency of the commonality across all individual results, where the commonality repeated with the greatest frequency is ranked highest. 44. The computing device of claim 43, wherein the ranking the plurality of commonalities is further based on a link distance, where the commonality with the smallest link distance is ranked highest. 45. The computing device of claim 44, further comprising removing, through the computing device, a particular commonality from the plurality of commonalities wherein the removed commonality corresponds to a user-defined restriction term. | 2,100 |
6,090 | 6,090 | 14,044,697 | 2,174 | A simplified menu screen for a handheld mobile wireless device with a display/touch screen that provides for and displays an initial menu, a simplified menu in lieu of an original menu screen, on the display screen when the device is first activated, the simplified menu displays only up to five menu selection choices and thereby simplifies the initial menu screen and minimizes the complexity of the initial screen and a desired menu selection there from. A part of the simplified menu screen is used for live feed minimizing the number of steps required to access display of data relevant to a user. | 1. A handheld mobile wireless device comprising:
a. a mobile wireless device with a display/touch screen; b. a menu function resident in the memory of the device and operating in a CPU of the device displays as an initial menu, a simplified menu screen in lieu of an original menu screen, on the display screen when the device is first activated, the simplified menu displays only up to five menu selection choices, thereby simplifying a complexity of the original menu screen and a desired menu selection there from. 2. The device as in claim 1, further comprising:
the menu function maintains data in the memory of the device related to and that support a selection of only the up to five menu choices that is based on either a highest average number of selections of these specific menu choices in a general population or a highest average number of selections of these specific menu choices by a device user. 3. The device as in claim 1, further comprising:
the menu function uses a part of the display screen, not used for displaying menu icons, for display of changing/live content to include one or more of a date/time, weather, live event video, live news feed, and live stock data. 4. The device as in claim 1, further comprising:
a. the up to five menu icons that are displayed are arranged in two groups of menu icons, one group with three menu icons and another group with two menu icons; b. the two groups of menu icons are displayed either in a vertical orientation or in a horizontal orientation on the display screen of the device. 5. The device as in claim 1, further comprising:
a swipe touch on any part of the display screen toggles the display between the simplified menu and the original menu of choices. 6. A method for a simplified menu screen for a handheld mobile wireless device comprising the steps of:
a. enabling use a mobile wireless device with a display/touch screen and having a menu function resident in the device; b. displaying, by the menu function, an initial menu, a simplified menu, in lieu of an original menu screen on the display screen when the device is first activated, the simplified menu displaying only up to five menu selection choices, thereby simplifying the initial menu screen and minimizing the complexity of the initial menu screen and a desired menu selection there from. 7. The method for the simplified menu screen as in claim 6, further comprising the steps of:
maintaining by the menu function, data in a memory of the device related to and that support a selection of only the up to five menu choices that is based on either a highest average number of selections of these specific menu choices in a general population or a highest average number of selections of these specific menu choices by a device user. 8. The method for the simplified menu screen as in claim 6, further comprising the steps of:
displaying by the menu function on a part of the display screen, not used for display of menu icons, displays with changing/live content to include one or more of a date/time, weather, live event video, live news feed, and live stock data. 9. The method for the menu screen as in claim 6, further comprising the steps of:
a. displaying the up to five menu icons arranged in two groups of, a group of three icons and a group of two menu icons; b. displaying the two groups of menu icons, in either a vertical orientation or in a horizontal orientation. 10. The method for the simplified menu screen as in claim 6, further comprising the steps of:
toggling the display between the simplified menu and the original menu of choices on a swipe-touch on any part of the display screen. 11. A display screen for a handheld mobile wireless device with a display/touch feature comprising:
a. a menu function resident in the device that displays on the device on the device being unlocked, an initial menu, a simplified menu in lieu of an original menu screen, on the display screen when the device is first activated, the simplified menu displays only up to five menu selection choices; b. the menu function uses a part of the display screen space as a live feed display space for displaying a changing/live content to include one or more of a date/time, weather, live event video, live news feed, and live stock data. 12. The display screen as in claim 11, comprising:
a swipe touch on any part of the display screen toggles the display between the initial menu screen and an original menu of choices screen. 13. The display screen as in claim 11, comprising:
the live feed/data that is displayed on the part of the display screen has been pre-identified for a device user. 14. The display screen as in claim 11, comprising:
substantially half of the display screen space is used for the display of the live feed/data that is displayed on the part of the display screen has been pre-identified for a device user. 15. The display screen as in claim 11, comprising:
the live feed display space is partitioned into multiple spaces that enable more than one live feed to be displayed at the same time in the live feed display space. 16. A handheld mobile wireless device with a display screen and a touch screen, comprising:
a. a menu function operating in the device as part of a device operating system in a hardware processor of the device, after the device is powered on, displays an initial menu display screen, the initial menu display provides for the display of at least two different display spaces, a display space A and a display space B; b. the display space A displays a limited number of menu icons and the display space B displays a changing and live digital content, whether the content is pre-stored in the device itself or received live in the device from a wireless network. 17. The device as in claim 16, comprising:
the spaces A and B each occupy substantially half of the display screen. 18. The device as in claim 16, comprising:
the space A displays a maximum number of menu icons not to exceed six in number. 19. The device as in claim 16, comprising:
the space B displays a plurality of live feeds not to exceed three in number. 20. The device as in claim 16, further comprising:
a swipe touch on any part of the display screen toggles the display between the initial menu screen and an original menu of choices screen. | A simplified menu screen for a handheld mobile wireless device with a display/touch screen that provides for and displays an initial menu, a simplified menu in lieu of an original menu screen, on the display screen when the device is first activated, the simplified menu displays only up to five menu selection choices and thereby simplifies the initial menu screen and minimizes the complexity of the initial screen and a desired menu selection there from. A part of the simplified menu screen is used for live feed minimizing the number of steps required to access display of data relevant to a user.1. A handheld mobile wireless device comprising:
a. a mobile wireless device with a display/touch screen; b. a menu function resident in the memory of the device and operating in a CPU of the device displays as an initial menu, a simplified menu screen in lieu of an original menu screen, on the display screen when the device is first activated, the simplified menu displays only up to five menu selection choices, thereby simplifying a complexity of the original menu screen and a desired menu selection there from. 2. The device as in claim 1, further comprising:
the menu function maintains data in the memory of the device related to and that support a selection of only the up to five menu choices that is based on either a highest average number of selections of these specific menu choices in a general population or a highest average number of selections of these specific menu choices by a device user. 3. The device as in claim 1, further comprising:
the menu function uses a part of the display screen, not used for displaying menu icons, for display of changing/live content to include one or more of a date/time, weather, live event video, live news feed, and live stock data. 4. The device as in claim 1, further comprising:
a. the up to five menu icons that are displayed are arranged in two groups of menu icons, one group with three menu icons and another group with two menu icons; b. the two groups of menu icons are displayed either in a vertical orientation or in a horizontal orientation on the display screen of the device. 5. The device as in claim 1, further comprising:
a swipe touch on any part of the display screen toggles the display between the simplified menu and the original menu of choices. 6. A method for a simplified menu screen for a handheld mobile wireless device comprising the steps of:
a. enabling use a mobile wireless device with a display/touch screen and having a menu function resident in the device; b. displaying, by the menu function, an initial menu, a simplified menu, in lieu of an original menu screen on the display screen when the device is first activated, the simplified menu displaying only up to five menu selection choices, thereby simplifying the initial menu screen and minimizing the complexity of the initial menu screen and a desired menu selection there from. 7. The method for the simplified menu screen as in claim 6, further comprising the steps of:
maintaining by the menu function, data in a memory of the device related to and that support a selection of only the up to five menu choices that is based on either a highest average number of selections of these specific menu choices in a general population or a highest average number of selections of these specific menu choices by a device user. 8. The method for the simplified menu screen as in claim 6, further comprising the steps of:
displaying by the menu function on a part of the display screen, not used for display of menu icons, displays with changing/live content to include one or more of a date/time, weather, live event video, live news feed, and live stock data. 9. The method for the menu screen as in claim 6, further comprising the steps of:
a. displaying the up to five menu icons arranged in two groups of, a group of three icons and a group of two menu icons; b. displaying the two groups of menu icons, in either a vertical orientation or in a horizontal orientation. 10. The method for the simplified menu screen as in claim 6, further comprising the steps of:
toggling the display between the simplified menu and the original menu of choices on a swipe-touch on any part of the display screen. 11. A display screen for a handheld mobile wireless device with a display/touch feature comprising:
a. a menu function resident in the device that displays on the device on the device being unlocked, an initial menu, a simplified menu in lieu of an original menu screen, on the display screen when the device is first activated, the simplified menu displays only up to five menu selection choices; b. the menu function uses a part of the display screen space as a live feed display space for displaying a changing/live content to include one or more of a date/time, weather, live event video, live news feed, and live stock data. 12. The display screen as in claim 11, comprising:
a swipe touch on any part of the display screen toggles the display between the initial menu screen and an original menu of choices screen. 13. The display screen as in claim 11, comprising:
the live feed/data that is displayed on the part of the display screen has been pre-identified for a device user. 14. The display screen as in claim 11, comprising:
substantially half of the display screen space is used for the display of the live feed/data that is displayed on the part of the display screen has been pre-identified for a device user. 15. The display screen as in claim 11, comprising:
the live feed display space is partitioned into multiple spaces that enable more than one live feed to be displayed at the same time in the live feed display space. 16. A handheld mobile wireless device with a display screen and a touch screen, comprising:
a. a menu function operating in the device as part of a device operating system in a hardware processor of the device, after the device is powered on, displays an initial menu display screen, the initial menu display provides for the display of at least two different display spaces, a display space A and a display space B; b. the display space A displays a limited number of menu icons and the display space B displays a changing and live digital content, whether the content is pre-stored in the device itself or received live in the device from a wireless network. 17. The device as in claim 16, comprising:
the spaces A and B each occupy substantially half of the display screen. 18. The device as in claim 16, comprising:
the space A displays a maximum number of menu icons not to exceed six in number. 19. The device as in claim 16, comprising:
the space B displays a plurality of live feeds not to exceed three in number. 20. The device as in claim 16, further comprising:
a swipe touch on any part of the display screen toggles the display between the initial menu screen and an original menu of choices screen. | 2,100 |
6,091 | 6,091 | 14,977,487 | 2,162 | A synchronization protocol is provided that can be used to resolve synchronization errors encountered while trying to synchronize versions of data objects between a client device and a remote computing system. The protocol includes a client device, in an offline processing mode, handling user interface (“UI”) manipulation actions on one or more UI elements of one or more UI screens. The handling of the UI manipulation actions modifies or creates a local version of a data object stored on the client device. The UI manipulation actions are stored by the client device and sent to the remote computing system. The client device receives a synchronization error notification from the remote computing system. After receiving the notification, the client device displays, in one of the UI screens, the local version of the data object and one or more indications of a synchronization error. | 1. One or more non-transitory computer-readable media comprising computer-executable instructions for causing a client device to perform operations comprising:
in an offline processing mode, handling a plurality of user interface (“UI”) manipulation actions on one or more UI elements of one or more UI screens, wherein the handling the plurality of UI manipulation actions modifies or creates a local version of a data object stored on the client device, and wherein the client device is not connected to a remote computing system in the offline processing mode; in the offline processing mode, storing the plurality of UI manipulation actions; in a synchronization stage, sending the stored plurality of UI manipulation actions to the remote computing system; receiving a synchronization error notification from the remote computing system, the synchronization error notification indicating a synchronization error associated with the UI manipulation actions; and after receiving the synchronization error notification, displaying, in one of the one or more UI screens, the local version of the data object and one or more indications of the synchronization error. 2. The one or more non-transitory computer-readable media of claim 1, wherein the plurality of UI manipulation actions indicate actuation, selection, or other manipulation of the one or more UI elements as rendered with a UI engine at the client device, the one or more UI elements being specified with UI metadata stored on the client device. 3. The one or more non-transitory computer-readable media of claim 1, wherein the operations further comprise:
handling one or more additional UI manipulation actions, wherein the handling the one or more additional UI manipulation actions modifies the local version of the data object stored on the client device to address the synchronization error notification. 4. The one or more non-transitory computer-readable media of claim 2, wherein the operations further comprise sending the one or more additional UI manipulation actions to the remote computing system. 5. The one or more non-transitory computer-readable media of claim 1, wherein the displaying comprises highlighting a data field to indicate the synchronization error. 6. The one or more non-transitory computer-readable media of claim 1, wherein the one or more indications include a synchronization error message identifying the synchronization error. 7. The one or more non-transitory computer-readable media of claim 1, wherein the one or more indications include a synchronization error message suggesting action to resolve the synchronization error. 8. The one or more non-transitory computer-readable media of claim 1, wherein the operations further comprise displaying a synchronization summary screen, the synchronization summary screen including information related to the synchronization error. 9. The one or more non-transitory computer-readable media of claim 8, wherein the synchronization summary screen includes a user selectable icon for resolving the synchronization error, the displaying of the UI screen that presents the local version of the data object occurring upon user selection of the icon. 10. The one or more non-transitory computer-readable media of claim 1, wherein a given one of the actions modifies metadata of a data object instance, and the synchronization error indicates an error condition with the modified metadata. 11. The one or more non-transitory computer-readable media of claim 1, wherein the plurality of UI manipulation actions are stored in an order in which they occurred or are stored with information sufficient to reconstitute the order. 12. In a remote computing system, a method comprising:
receiving a plurality of recorded user interface (“UI”) manipulation actions from a client device, the recorded UI manipulation actions implementing a modification or creation of a local version of a data object stored on the client device in an offline processing mode, wherein the client device is not connected to the remote computing system in the offline processing mode; replaying the plurality of recorded UI manipulation actions, wherein the replaying the plurality of recorded UI manipulation actions modifies or creates a remote version of the data object, the remote version of the data object being for storage on the remote computing system; determining a synchronization error associated with the UI manipulation actions; and sending a synchronization error notification to the client device. 13. The method of claim 12, wherein the plurality of recorded UI manipulation actions indicate actuation, selection, or other manipulation of one or more UI elements rendered with a UI engine at the client device, the one or more UI elements being specified with UI metadata stored on the client device and also on the remote computing system. 14. The method of claim 12, further comprising:
receiving one or more additional UI manipulation actions from the client device; and executing the one or more additional UI manipulation actions to modify the remote version of the data object. 15. The method of claim 12, further comprising sending data regarding the local version of the data object to the client device, wherein the data comprises a data field associated with the synchronization error. 16. The method of claim 12, wherein the synchronization error notification comprises a description of the synchronization error to be displayed in a UI screen of the client device. 17. The method of claim 12, wherein the recorded UI manipulation actions are stored in an order in which they occurred at the client device and the replaying handles the UI manipulation actions in the same order in which they occurred at the client device. 18. A computing system that implements a synchronization service, the computing system comprising:
memory storing a plurality of user interface (“UI”) manipulation actions received during synchronization with a client device, the UI manipulation actions implementing a modification or creation of a local version of a data object stored on the client device in an offline processing mode, wherein the client device is not connected to the computing system in the offline processing mode; and a processor configured to:
execute instructions that implement synchronization, the synchronization replaying the stored UI manipulation actions, wherein the replaying the stored UI manipulation actions modifies or creates a remote version of the data object, the remote version of the data object being for storage on the computing system;
determine a synchronization error associated with the UI manipulation actions;
produce synchronization error notification to be sent to the client device; and
cause the client device to display the local version of the data object and one or more indications of the synchronization error. 19. The computing system of claim 18, wherein the processor is further configured to receive one or more additional UI manipulation actions and execute the one or more additional UI manipulation actions to modify the remote version of the data object. 20. The computing system of claim 18, wherein the stored UI manipulation actions are replayed in an order in which they occurred at the client device. | A synchronization protocol is provided that can be used to resolve synchronization errors encountered while trying to synchronize versions of data objects between a client device and a remote computing system. The protocol includes a client device, in an offline processing mode, handling user interface (“UI”) manipulation actions on one or more UI elements of one or more UI screens. The handling of the UI manipulation actions modifies or creates a local version of a data object stored on the client device. The UI manipulation actions are stored by the client device and sent to the remote computing system. The client device receives a synchronization error notification from the remote computing system. After receiving the notification, the client device displays, in one of the UI screens, the local version of the data object and one or more indications of a synchronization error.1. One or more non-transitory computer-readable media comprising computer-executable instructions for causing a client device to perform operations comprising:
in an offline processing mode, handling a plurality of user interface (“UI”) manipulation actions on one or more UI elements of one or more UI screens, wherein the handling the plurality of UI manipulation actions modifies or creates a local version of a data object stored on the client device, and wherein the client device is not connected to a remote computing system in the offline processing mode; in the offline processing mode, storing the plurality of UI manipulation actions; in a synchronization stage, sending the stored plurality of UI manipulation actions to the remote computing system; receiving a synchronization error notification from the remote computing system, the synchronization error notification indicating a synchronization error associated with the UI manipulation actions; and after receiving the synchronization error notification, displaying, in one of the one or more UI screens, the local version of the data object and one or more indications of the synchronization error. 2. The one or more non-transitory computer-readable media of claim 1, wherein the plurality of UI manipulation actions indicate actuation, selection, or other manipulation of the one or more UI elements as rendered with a UI engine at the client device, the one or more UI elements being specified with UI metadata stored on the client device. 3. The one or more non-transitory computer-readable media of claim 1, wherein the operations further comprise:
handling one or more additional UI manipulation actions, wherein the handling the one or more additional UI manipulation actions modifies the local version of the data object stored on the client device to address the synchronization error notification. 4. The one or more non-transitory computer-readable media of claim 2, wherein the operations further comprise sending the one or more additional UI manipulation actions to the remote computing system. 5. The one or more non-transitory computer-readable media of claim 1, wherein the displaying comprises highlighting a data field to indicate the synchronization error. 6. The one or more non-transitory computer-readable media of claim 1, wherein the one or more indications include a synchronization error message identifying the synchronization error. 7. The one or more non-transitory computer-readable media of claim 1, wherein the one or more indications include a synchronization error message suggesting action to resolve the synchronization error. 8. The one or more non-transitory computer-readable media of claim 1, wherein the operations further comprise displaying a synchronization summary screen, the synchronization summary screen including information related to the synchronization error. 9. The one or more non-transitory computer-readable media of claim 8, wherein the synchronization summary screen includes a user selectable icon for resolving the synchronization error, the displaying of the UI screen that presents the local version of the data object occurring upon user selection of the icon. 10. The one or more non-transitory computer-readable media of claim 1, wherein a given one of the actions modifies metadata of a data object instance, and the synchronization error indicates an error condition with the modified metadata. 11. The one or more non-transitory computer-readable media of claim 1, wherein the plurality of UI manipulation actions are stored in an order in which they occurred or are stored with information sufficient to reconstitute the order. 12. In a remote computing system, a method comprising:
receiving a plurality of recorded user interface (“UI”) manipulation actions from a client device, the recorded UI manipulation actions implementing a modification or creation of a local version of a data object stored on the client device in an offline processing mode, wherein the client device is not connected to the remote computing system in the offline processing mode; replaying the plurality of recorded UI manipulation actions, wherein the replaying the plurality of recorded UI manipulation actions modifies or creates a remote version of the data object, the remote version of the data object being for storage on the remote computing system; determining a synchronization error associated with the UI manipulation actions; and sending a synchronization error notification to the client device. 13. The method of claim 12, wherein the plurality of recorded UI manipulation actions indicate actuation, selection, or other manipulation of one or more UI elements rendered with a UI engine at the client device, the one or more UI elements being specified with UI metadata stored on the client device and also on the remote computing system. 14. The method of claim 12, further comprising:
receiving one or more additional UI manipulation actions from the client device; and executing the one or more additional UI manipulation actions to modify the remote version of the data object. 15. The method of claim 12, further comprising sending data regarding the local version of the data object to the client device, wherein the data comprises a data field associated with the synchronization error. 16. The method of claim 12, wherein the synchronization error notification comprises a description of the synchronization error to be displayed in a UI screen of the client device. 17. The method of claim 12, wherein the recorded UI manipulation actions are stored in an order in which they occurred at the client device and the replaying handles the UI manipulation actions in the same order in which they occurred at the client device. 18. A computing system that implements a synchronization service, the computing system comprising:
memory storing a plurality of user interface (“UI”) manipulation actions received during synchronization with a client device, the UI manipulation actions implementing a modification or creation of a local version of a data object stored on the client device in an offline processing mode, wherein the client device is not connected to the computing system in the offline processing mode; and a processor configured to:
execute instructions that implement synchronization, the synchronization replaying the stored UI manipulation actions, wherein the replaying the stored UI manipulation actions modifies or creates a remote version of the data object, the remote version of the data object being for storage on the computing system;
determine a synchronization error associated with the UI manipulation actions;
produce synchronization error notification to be sent to the client device; and
cause the client device to display the local version of the data object and one or more indications of the synchronization error. 19. The computing system of claim 18, wherein the processor is further configured to receive one or more additional UI manipulation actions and execute the one or more additional UI manipulation actions to modify the remote version of the data object. 20. The computing system of claim 18, wherein the stored UI manipulation actions are replayed in an order in which they occurred at the client device. | 2,100 |
6,092 | 6,092 | 14,486,259 | 2,152 | Enclosed herein are systems, methods, and software to facilitate incremental graph view maintenance in a data system. In one example, a method of operating a graph maintenance module to implement graph view maintenance on a graph view based on a relational database includes identifying a modification to the relational database. The method further includes, identifying a graph modification for the graph view based on the modification to the relational database, and implementing the graph modification in the graph view. | 1. A method of operating a graph maintenance module to implement graph view maintenance on a graph view, the method comprising:
identifying a modification to a relational database; identifying a graph modification for the graph view based on the modification to the relational database; and implementing the graph modification in the graph view. 2. The method of claim 1 wherein identifying the modification in the relational database comprises identifying an addition to the relational database. 3. The method of claim 2 wherein identifying the graph modification for the graph view based on the modification in the relational database comprises identifying at least one additional node or edge for the graph view based on the addition to the relational database. 4. The method of claim 3 wherein implementing the graph modification in the graph view comprises adding the at least one additional node or edge to the graph view. 5. The method of claim 1 wherein identifying the modification in the relational database comprises identifying a deletion to the relational database. 6. The method of claim 5 wherein identifying the graph modification for the graph view based on the modification in the relational database comprises identifying at least one node or edge for deletion in the graph view based on the deletion to the relational database. 7. The method of claim 6 wherein implementing the graph modification in the graph view comprises removing the at least one node or edge in the graph view. 8. The method of claim 1 wherein the graph view comprises one or more nodes and edges based on the relational database. 9. A computer apparatus to implement incremental graph view maintenance on a graph view, the computer apparatus comprising:
processing instructions that direct a computing system, when executed by the computing system, to:
identify a modification to a relational database;
identify a graph modification for the graph view based on the modification to the relational database; and
implement the graph modification in the graph view; and
one or more non-transitory computer readable media that store the processing instructions. 10. The computer apparatus of claim 9 wherein the processing instructions to identify the modification in the relational database direct the computing system to identify an addition to the relational database. 11. The computer apparatus of claim 10 wherein the processing instructions to identify the graph modification for the graph view based on the modification in the relational database direct the computing system to identify at least one additional node or edge for the graph view based on the addition to the relational database. 12. The computer apparatus of claim 11 wherein the processing instructions to implement the graph modification in the graph view direct the computing system to add the at least one additional node or edge to the graph view. 13. The computer apparatus of claim 9 wherein the processing instructions to identify the modification in the relational database direct the computing system to identify a deletion to the relational database. 14. The computer apparatus of claim 13 wherein the processing instructions to identify the graph modification for the graph view based on the modification in the relational database direct the computing system to identify at least one node or edge for deletion in the graph view based on the deletion in the relational database. 15. The computer apparatus of claim 14 wherein the processing instructions to implement the graph view modification in the graph view direct the computing system to remove the at least one node or edge in the graph view. 16. The computer apparatus of claim 9 wherein the graph view comprises one or more nodes and edges based on the relational database. 17. A data system comprising:
a relational database configured to store data and relationship information concerning the data; a graph database configured to store one or more graph views related to the relational database; and a graph maintenance module configured to:
identify a modification to the relational database;
identify a graph modification for at least one graph view in the graph database based on the modification to the relational database; and
implement the graph modification in the at least one graph view. 18. The data system of claim 17 wherein the modification to the relational database comprises an addition to the relational database. 19. The data system of claim 17 wherein the modification to the relational database comprises a deletion to the relational database. 20. The data system of claim 17 wherein the graph maintenance module configured to identify the modification to the relational database is configured to periodically identify a relational modification to the relational database. | Enclosed herein are systems, methods, and software to facilitate incremental graph view maintenance in a data system. In one example, a method of operating a graph maintenance module to implement graph view maintenance on a graph view based on a relational database includes identifying a modification to the relational database. The method further includes, identifying a graph modification for the graph view based on the modification to the relational database, and implementing the graph modification in the graph view.1. A method of operating a graph maintenance module to implement graph view maintenance on a graph view, the method comprising:
identifying a modification to a relational database; identifying a graph modification for the graph view based on the modification to the relational database; and implementing the graph modification in the graph view. 2. The method of claim 1 wherein identifying the modification in the relational database comprises identifying an addition to the relational database. 3. The method of claim 2 wherein identifying the graph modification for the graph view based on the modification in the relational database comprises identifying at least one additional node or edge for the graph view based on the addition to the relational database. 4. The method of claim 3 wherein implementing the graph modification in the graph view comprises adding the at least one additional node or edge to the graph view. 5. The method of claim 1 wherein identifying the modification in the relational database comprises identifying a deletion to the relational database. 6. The method of claim 5 wherein identifying the graph modification for the graph view based on the modification in the relational database comprises identifying at least one node or edge for deletion in the graph view based on the deletion to the relational database. 7. The method of claim 6 wherein implementing the graph modification in the graph view comprises removing the at least one node or edge in the graph view. 8. The method of claim 1 wherein the graph view comprises one or more nodes and edges based on the relational database. 9. A computer apparatus to implement incremental graph view maintenance on a graph view, the computer apparatus comprising:
processing instructions that direct a computing system, when executed by the computing system, to:
identify a modification to a relational database;
identify a graph modification for the graph view based on the modification to the relational database; and
implement the graph modification in the graph view; and
one or more non-transitory computer readable media that store the processing instructions. 10. The computer apparatus of claim 9 wherein the processing instructions to identify the modification in the relational database direct the computing system to identify an addition to the relational database. 11. The computer apparatus of claim 10 wherein the processing instructions to identify the graph modification for the graph view based on the modification in the relational database direct the computing system to identify at least one additional node or edge for the graph view based on the addition to the relational database. 12. The computer apparatus of claim 11 wherein the processing instructions to implement the graph modification in the graph view direct the computing system to add the at least one additional node or edge to the graph view. 13. The computer apparatus of claim 9 wherein the processing instructions to identify the modification in the relational database direct the computing system to identify a deletion to the relational database. 14. The computer apparatus of claim 13 wherein the processing instructions to identify the graph modification for the graph view based on the modification in the relational database direct the computing system to identify at least one node or edge for deletion in the graph view based on the deletion in the relational database. 15. The computer apparatus of claim 14 wherein the processing instructions to implement the graph view modification in the graph view direct the computing system to remove the at least one node or edge in the graph view. 16. The computer apparatus of claim 9 wherein the graph view comprises one or more nodes and edges based on the relational database. 17. A data system comprising:
a relational database configured to store data and relationship information concerning the data; a graph database configured to store one or more graph views related to the relational database; and a graph maintenance module configured to:
identify a modification to the relational database;
identify a graph modification for at least one graph view in the graph database based on the modification to the relational database; and
implement the graph modification in the at least one graph view. 18. The data system of claim 17 wherein the modification to the relational database comprises an addition to the relational database. 19. The data system of claim 17 wherein the modification to the relational database comprises a deletion to the relational database. 20. The data system of claim 17 wherein the graph maintenance module configured to identify the modification to the relational database is configured to periodically identify a relational modification to the relational database. | 2,100 |
6,093 | 6,093 | 13,082,544 | 2,117 | Operating a computer system includes determining, for each of a plurality of electronic units in a computer system, at least one upcoming process being assigned to a specific electronic unit. An anticipated workload for the specific electronic unit is identified based upon the at least one upcoming process. At least one control signal is generated based upon a plurality of anticipated workloads for the plurality of electronic units. A flow of cooling fluid to each of a plurality of cooling units in the computer system is controlled based upon the at least one control signal. Each of the plurality of cooling units are respectively associated with an electronic unit of the plurality of electronic units. | 1. A method for operating a computer system, comprising:
determining, for each of a plurality of electronic units in a computer system, at least one upcoming process being assigned to a specific electronic unit; identifying an anticipated workload for the specific electronic unit based upon the at least one upcoming process; generating at least one control signal based upon a plurality of anticipated workloads for the plurality of electronic units; and controlling, based upon the at least one control signal, a flow of cooling fluid to each of a plurality of cooling units in the computer system, wherein each of the plurality of cooling units are respectively associated with an electronic unit of the plurality of electronic units. 2. The method of claim 1, wherein
each of the plurality of cooling units is configured to receive a stream of the cooling fluid, an input port of each of the plurality of cooling units is hydraulically coupled with an upstream positioned common inlet portion, and an output port of each of the plurality of cooling units is hydraulically coupled with a downstream positioned common outlet portion. 3. The method of claim 2, further comprising
determining an output temperature value of the cooling fluid at the common outlet portion; and redistributing, based on the determined output temperature value, a plurality of upcoming processes to predetermined ones of the plurality of electronic units. 4. The method of claim 3, further comprising
comparing the determined output temperature value to a predetermined temperature threshold value, wherein the plurality of upcoming processes are redistributed to the predetermined ones of the plurality of electronic units to result in workloads, for each of the predetermined ones of the plurality of electronic units, being above a predetermined workload threshold value; and setting remaining electronic units from the plurality of electronic units into a predetermined low-power mode. 5. The method of claim 1, further comprising
observing process memory access to at least one memory unit within the computer system, wherein the access is caused by a particular process assigned to one of the plurality of electronic units; and controlling the flow of the cooling fluid to a cooling unit respectively associated with the one of the plurality of electronic units while the one of the plurality of electronic units is performing the process memory access 6. A method for operating a computer system, comprising
obtaining, for each of a plurality of electronic units in a computer system, an anticipated workload; generating at least one control signal based upon a plurality of anticipated workloads for the plurality of electronic units; and controlling, based upon the at least one control signal, a flow of cooling fluid to each of a plurality of cooling units in the computer system, wherein each of the plurality of cooling units are respectively associated with an electronic unit of the plurality of electronic units. 7. The method of claim 6, wherein
each of the plurality of cooling units is configured to receive a stream of the cooling fluid, an input port of each of the plurality of cooling units is hydraulically coupled with an upstream positioned common inlet portion, and an output port of each of the plurality of cooling units is hydraulically coupled with a downstream positioned common outlet portion. 8. The method of claim 7, further comprising
determining an output temperature value of the cooling fluid at the common outlet portion; and redistributing, based on the determined output temperature value, a plurality of upcoming processes to predetermined ones of the plurality of electronic units. 9. The method of claim 7, wherein
the at least one control signal is generated based on a predetermined output temperature range representing a target temperature range of the cooling fluid at the common outlet portion. 10. The method of claim 6, further comprising
generating at least one process signal, wherein the at least one process signal generates upcoming processes assigned to the electronic units, and the plurality of anticipated workload loads for the plurality of electronics units are identified based upon the at least one process signal. 11. A computer system, comprising
a plurality of electronic units; a plurality of cooling units, each of the plurality of cooling units respectively associated with one of the plurality of electronic units; a downstream positioned common outlet portion; an upstream positioned common inlet portion; and a controller, wherein each of the plurality of cooling units is configured to receive a stream of cooling fluid and includes
an input port hydraulically coupled with the upstream positioned common inlet portion, and
an output port hydraulically coupled with the downstream positioned common outlet portion,
the controller is configured to
determine, for each of the plurality of electronic units, at least one upcoming process being assigned to a specific electronic unit;
identify an anticipated workload for the specific electronic unit based upon the at least one upcoming process;
generate at least one control signal based upon a plurality of anticipated workloads for the plurality of electronic units; and
control, based upon the at least one control signal, a flow of the cooling fluid to each of the plurality of cooling units. 12. The computer system of claim 11, wherein
the controller is further configured to
determine an output temperature value of the cooling fluid at the common outlet portion; and
redistribute, based on the determined output temperature value, a plurality of upcoming processes to predetermined ones of the plurality of electronic units. 13. The computer system of claim 11, wherein
the controller is further configured to
observe process memory access to at least one memory unit within the computer system, wherein the access is caused by a particular process assigned to one of the plurality of electronic units; and
control the flow of the cooling fluid to a cooling unit respectively associated with the one of the plurality of electronic units while the one of the plurality of electronic units is performing the process memory access 14. A computer system, comprising
a plurality of electronic units; a plurality of cooling units, each of the plurality of cooling units respectively associated with one of the plurality of electronic units; a downstream positioned common outlet portion; an upstream positioned common inlet portion; and a controller, wherein each of the plurality of cooling units is configured to receive a stream of cooling fluid and includes
an input port hydraulically coupled with the upstream positioned common inlet portion, and
an output port hydraulically coupled with the downstream positioned common outlet portion,
the controller is configured to
determine, for each of the plurality of electronic units, at least one upcoming process being assigned to a specific electronic unit;
identify an anticipated workload for the specific electronic unit based upon the at least one upcoming process;
generate at least one control signal based upon a plurality of anticipated workloads for the plurality of electronic units; and
control, based upon the at least one control signal, a flow of the cooling fluid to each of the plurality of cooling units. 15. The computer system of claim 14, wherein
the controller is further configured to
determine an output temperature value of the cooling fluid at the common outlet portion; and
redistribute, based on the determined output temperature value, a plurality of upcoming processes to predetermined ones of the plurality of electronic units. 16. The computer system of claim 14, wherein
the controller is further configured to generate at least one process signal, the at least one process signal generates upcoming processes assigned to the electronic units, and the plurality of anticipated workload loads for the plurality of electronics units are identified based upon the at least one process signal. 17. A computer program product comprising a computer usable storage medium having stored therein computer usable program code for operating a computer hardware system, the computer usable program code, which when executed by the computer hardware system, causes the computer hardware system to perform:
determining, for each of a plurality of electronic units in the computer hardware system, at least one upcoming process being assigned to a specific electronic unit; identifying an anticipated workload for the specific electronic unit based upon the at least one upcoming process; generating at least one control signal based upon a plurality of anticipated workloads for the plurality of electronic units; and controlling, based upon the at least one control signal, a flow of cooling fluid to each of a plurality of cooling units in the computer system, wherein each of the plurality of cooling units are respectively associated with an electronic unit of the plurality of electronic units. 18. The computer program product of claim 17, wherein
each of the plurality of cooling units is configured to receive a stream of the cooling fluid, an input port of each of the plurality of cooling units is hydraulically coupled with an upstream positioned common inlet portion, and an output port of each of the plurality of cooling units is hydraulically coupled with a downstream positioned common outlet portion. 19. The computer program product of claim 18, wherein
the computer usable program code further causes the computer hardware system to perform:
determining an output temperature value of the cooling fluid at the common outlet portion; and
redistributing, based on the determined output temperature value, a plurality of upcoming processes to predetermined ones of the plurality of electronic units. | Operating a computer system includes determining, for each of a plurality of electronic units in a computer system, at least one upcoming process being assigned to a specific electronic unit. An anticipated workload for the specific electronic unit is identified based upon the at least one upcoming process. At least one control signal is generated based upon a plurality of anticipated workloads for the plurality of electronic units. A flow of cooling fluid to each of a plurality of cooling units in the computer system is controlled based upon the at least one control signal. Each of the plurality of cooling units are respectively associated with an electronic unit of the plurality of electronic units.1. A method for operating a computer system, comprising:
determining, for each of a plurality of electronic units in a computer system, at least one upcoming process being assigned to a specific electronic unit; identifying an anticipated workload for the specific electronic unit based upon the at least one upcoming process; generating at least one control signal based upon a plurality of anticipated workloads for the plurality of electronic units; and controlling, based upon the at least one control signal, a flow of cooling fluid to each of a plurality of cooling units in the computer system, wherein each of the plurality of cooling units are respectively associated with an electronic unit of the plurality of electronic units. 2. The method of claim 1, wherein
each of the plurality of cooling units is configured to receive a stream of the cooling fluid, an input port of each of the plurality of cooling units is hydraulically coupled with an upstream positioned common inlet portion, and an output port of each of the plurality of cooling units is hydraulically coupled with a downstream positioned common outlet portion. 3. The method of claim 2, further comprising
determining an output temperature value of the cooling fluid at the common outlet portion; and redistributing, based on the determined output temperature value, a plurality of upcoming processes to predetermined ones of the plurality of electronic units. 4. The method of claim 3, further comprising
comparing the determined output temperature value to a predetermined temperature threshold value, wherein the plurality of upcoming processes are redistributed to the predetermined ones of the plurality of electronic units to result in workloads, for each of the predetermined ones of the plurality of electronic units, being above a predetermined workload threshold value; and setting remaining electronic units from the plurality of electronic units into a predetermined low-power mode. 5. The method of claim 1, further comprising
observing process memory access to at least one memory unit within the computer system, wherein the access is caused by a particular process assigned to one of the plurality of electronic units; and controlling the flow of the cooling fluid to a cooling unit respectively associated with the one of the plurality of electronic units while the one of the plurality of electronic units is performing the process memory access 6. A method for operating a computer system, comprising
obtaining, for each of a plurality of electronic units in a computer system, an anticipated workload; generating at least one control signal based upon a plurality of anticipated workloads for the plurality of electronic units; and controlling, based upon the at least one control signal, a flow of cooling fluid to each of a plurality of cooling units in the computer system, wherein each of the plurality of cooling units are respectively associated with an electronic unit of the plurality of electronic units. 7. The method of claim 6, wherein
each of the plurality of cooling units is configured to receive a stream of the cooling fluid, an input port of each of the plurality of cooling units is hydraulically coupled with an upstream positioned common inlet portion, and an output port of each of the plurality of cooling units is hydraulically coupled with a downstream positioned common outlet portion. 8. The method of claim 7, further comprising
determining an output temperature value of the cooling fluid at the common outlet portion; and redistributing, based on the determined output temperature value, a plurality of upcoming processes to predetermined ones of the plurality of electronic units. 9. The method of claim 7, wherein
the at least one control signal is generated based on a predetermined output temperature range representing a target temperature range of the cooling fluid at the common outlet portion. 10. The method of claim 6, further comprising
generating at least one process signal, wherein the at least one process signal generates upcoming processes assigned to the electronic units, and the plurality of anticipated workload loads for the plurality of electronics units are identified based upon the at least one process signal. 11. A computer system, comprising
a plurality of electronic units; a plurality of cooling units, each of the plurality of cooling units respectively associated with one of the plurality of electronic units; a downstream positioned common outlet portion; an upstream positioned common inlet portion; and a controller, wherein each of the plurality of cooling units is configured to receive a stream of cooling fluid and includes
an input port hydraulically coupled with the upstream positioned common inlet portion, and
an output port hydraulically coupled with the downstream positioned common outlet portion,
the controller is configured to
determine, for each of the plurality of electronic units, at least one upcoming process being assigned to a specific electronic unit;
identify an anticipated workload for the specific electronic unit based upon the at least one upcoming process;
generate at least one control signal based upon a plurality of anticipated workloads for the plurality of electronic units; and
control, based upon the at least one control signal, a flow of the cooling fluid to each of the plurality of cooling units. 12. The computer system of claim 11, wherein
the controller is further configured to
determine an output temperature value of the cooling fluid at the common outlet portion; and
redistribute, based on the determined output temperature value, a plurality of upcoming processes to predetermined ones of the plurality of electronic units. 13. The computer system of claim 11, wherein
the controller is further configured to
observe process memory access to at least one memory unit within the computer system, wherein the access is caused by a particular process assigned to one of the plurality of electronic units; and
control the flow of the cooling fluid to a cooling unit respectively associated with the one of the plurality of electronic units while the one of the plurality of electronic units is performing the process memory access 14. A computer system, comprising
a plurality of electronic units; a plurality of cooling units, each of the plurality of cooling units respectively associated with one of the plurality of electronic units; a downstream positioned common outlet portion; an upstream positioned common inlet portion; and a controller, wherein each of the plurality of cooling units is configured to receive a stream of cooling fluid and includes
an input port hydraulically coupled with the upstream positioned common inlet portion, and
an output port hydraulically coupled with the downstream positioned common outlet portion,
the controller is configured to
determine, for each of the plurality of electronic units, at least one upcoming process being assigned to a specific electronic unit;
identify an anticipated workload for the specific electronic unit based upon the at least one upcoming process;
generate at least one control signal based upon a plurality of anticipated workloads for the plurality of electronic units; and
control, based upon the at least one control signal, a flow of the cooling fluid to each of the plurality of cooling units. 15. The computer system of claim 14, wherein
the controller is further configured to
determine an output temperature value of the cooling fluid at the common outlet portion; and
redistribute, based on the determined output temperature value, a plurality of upcoming processes to predetermined ones of the plurality of electronic units. 16. The computer system of claim 14, wherein
the controller is further configured to generate at least one process signal, the at least one process signal generates upcoming processes assigned to the electronic units, and the plurality of anticipated workload loads for the plurality of electronics units are identified based upon the at least one process signal. 17. A computer program product comprising a computer usable storage medium having stored therein computer usable program code for operating a computer hardware system, the computer usable program code, which when executed by the computer hardware system, causes the computer hardware system to perform:
determining, for each of a plurality of electronic units in the computer hardware system, at least one upcoming process being assigned to a specific electronic unit; identifying an anticipated workload for the specific electronic unit based upon the at least one upcoming process; generating at least one control signal based upon a plurality of anticipated workloads for the plurality of electronic units; and controlling, based upon the at least one control signal, a flow of cooling fluid to each of a plurality of cooling units in the computer system, wherein each of the plurality of cooling units are respectively associated with an electronic unit of the plurality of electronic units. 18. The computer program product of claim 17, wherein
each of the plurality of cooling units is configured to receive a stream of the cooling fluid, an input port of each of the plurality of cooling units is hydraulically coupled with an upstream positioned common inlet portion, and an output port of each of the plurality of cooling units is hydraulically coupled with a downstream positioned common outlet portion. 19. The computer program product of claim 18, wherein
the computer usable program code further causes the computer hardware system to perform:
determining an output temperature value of the cooling fluid at the common outlet portion; and
redistributing, based on the determined output temperature value, a plurality of upcoming processes to predetermined ones of the plurality of electronic units. | 2,100 |
6,094 | 6,094 | 13,855,210 | 2,176 | Example configurations herein include a media player that initiates playback of content (e.g., play back of a movie in a web browser). Based on input from a respective user, the media player receives selections of playback commands (e.g., play, pause, stop, rewind, fast forward, etc.) applied to the content being played back by the media player. Based on the selections, the media player creates a log report. The log report records the selections of the playback commands applied to the content and indicates, for example, a corresponding time when the playback commands were applied. According to one configuration, the media player initiates distribution of the log report to notify a publisher associated with the content which playback commands were selected during playback of the content on the media player. | 1. A method comprising:
receiving a first log report from a first media player, wherein the first log report comprises a first unique value associated with a publisher and the first media player, and wherein the first log report includes one or more playback commands applied to a first piece of content at the first media player; storing the first log report in a repository; receiving a second log report from a second media player, wherein the second log report comprises a second unique value associated with the publisher and the second media player, and wherein the second log report includes one or more playback commands applied to a second piece of content at the second media player; storing the second log report in the repository along with the first log report; and receiving a query to search the repository for playback information. 2. The method according to claim 1, wherein the query includes a request for information associated with playback of specific content. 3. The method according to claim 1, wherein the first log report does not include information that reveals an identity of the first media player and the second log report does not include information that reveals an identity of the second media player. 4. The method according to claim 1, wherein the one or more playback commands includes at least one of play, stop, pause, fast forward, and rewind. 5. The method according to claim 1, wherein the first log report and the second log report include feed events including at least one of subscribe, unsubscribe, check for update notification, check for update, complete, download start, download paused, download resumed, and download completed. 6. The method according to claim 1, wherein the query is received from the publisher. 7. A non-transitory computer-readable medium embodying program code executable by a processing device, the non-transitory computer-readable medium comprising program code for, the method comprising:
receiving a first log report from a first media player, wherein the first log report comprises a first unique value associated with a publisher and the first media player, and wherein the first log report includes one or more playback commands applied to a first piece of content at the first media player; storing the first log report in a repository; receiving a second log report from a second media player, wherein the second log report comprises a second unique value associated with the publisher and the second media player, and wherein the second log report includes one or more playback commands applied to a second piece of content at the second media player; storing the second log report in the repository along with the first log report; and receiving a query to search the repository for playback information. 8. The non-transitory computer-readable medium according to claim 7, wherein the query includes a request for information associated with playback of specific content. 9. The non-transitory computer-readable medium according to claim 7, wherein the first log report does not include information that reveals an identity of the first media player and the second log report does not include information that reveals an identity of the second media player. 10. The non-transitory computer-readable medium according to claim 7, wherein the one or more playback commands includes at least one of play, stop, pause, fast forward, and rewind. 11. The non-transitory computer-readable medium according to claim 7, wherein the first log report and the second log report include feed events including at least one of subscribe, unsubscribe, check for update notification, check for update, complete, download start, download paused, download resumed, and download completed. 12. The non-transitory computer-readable medium according to claim 7, wherein the query is received from the publisher. 13. A system comprising:
a digital storage device; and a processor coupled with the digital storage device, the processor configured to: receive a first log report from a first media player, wherein the first log report comprises a first unique value associated with a publisher and the first media player, and wherein the first log report includes one or more playback commands applied to a first piece of content at the first media player; store the first log report in the digital storage device; receive a second log report from a second media player, wherein the second log report comprises a second unique value associated with the publisher and the second media player, and wherein the second log report includes one or more playback commands applied to a second piece of content at the second media player; store the second log report in the storage device along with the first log report; and receive a query to search the storage device for playback information 14. The system according to claim 13, wherein the query includes a request for information associated with playback of specific content. 15. The system according to claim 13, wherein the first log report does not include information that reveals an identity of the first media player and the second log report does not include information that reveals an identity of the second media player. 16. The system according to claim 13, wherein the one or more playback commands includes at least one of play, stop, pause, fast forward, and rewind. 17. The system according to claim 13, wherein the first log report and the second log report include feed events including at least one of subscribe, unsubscribe, check for update notification, check for update, complete, download start, download paused, download resumed, and download completed. 18. The system according to claim 13, wherein the query is received from the publisher. | Example configurations herein include a media player that initiates playback of content (e.g., play back of a movie in a web browser). Based on input from a respective user, the media player receives selections of playback commands (e.g., play, pause, stop, rewind, fast forward, etc.) applied to the content being played back by the media player. Based on the selections, the media player creates a log report. The log report records the selections of the playback commands applied to the content and indicates, for example, a corresponding time when the playback commands were applied. According to one configuration, the media player initiates distribution of the log report to notify a publisher associated with the content which playback commands were selected during playback of the content on the media player.1. A method comprising:
receiving a first log report from a first media player, wherein the first log report comprises a first unique value associated with a publisher and the first media player, and wherein the first log report includes one or more playback commands applied to a first piece of content at the first media player; storing the first log report in a repository; receiving a second log report from a second media player, wherein the second log report comprises a second unique value associated with the publisher and the second media player, and wherein the second log report includes one or more playback commands applied to a second piece of content at the second media player; storing the second log report in the repository along with the first log report; and receiving a query to search the repository for playback information. 2. The method according to claim 1, wherein the query includes a request for information associated with playback of specific content. 3. The method according to claim 1, wherein the first log report does not include information that reveals an identity of the first media player and the second log report does not include information that reveals an identity of the second media player. 4. The method according to claim 1, wherein the one or more playback commands includes at least one of play, stop, pause, fast forward, and rewind. 5. The method according to claim 1, wherein the first log report and the second log report include feed events including at least one of subscribe, unsubscribe, check for update notification, check for update, complete, download start, download paused, download resumed, and download completed. 6. The method according to claim 1, wherein the query is received from the publisher. 7. A non-transitory computer-readable medium embodying program code executable by a processing device, the non-transitory computer-readable medium comprising program code for, the method comprising:
receiving a first log report from a first media player, wherein the first log report comprises a first unique value associated with a publisher and the first media player, and wherein the first log report includes one or more playback commands applied to a first piece of content at the first media player; storing the first log report in a repository; receiving a second log report from a second media player, wherein the second log report comprises a second unique value associated with the publisher and the second media player, and wherein the second log report includes one or more playback commands applied to a second piece of content at the second media player; storing the second log report in the repository along with the first log report; and receiving a query to search the repository for playback information. 8. The non-transitory computer-readable medium according to claim 7, wherein the query includes a request for information associated with playback of specific content. 9. The non-transitory computer-readable medium according to claim 7, wherein the first log report does not include information that reveals an identity of the first media player and the second log report does not include information that reveals an identity of the second media player. 10. The non-transitory computer-readable medium according to claim 7, wherein the one or more playback commands includes at least one of play, stop, pause, fast forward, and rewind. 11. The non-transitory computer-readable medium according to claim 7, wherein the first log report and the second log report include feed events including at least one of subscribe, unsubscribe, check for update notification, check for update, complete, download start, download paused, download resumed, and download completed. 12. The non-transitory computer-readable medium according to claim 7, wherein the query is received from the publisher. 13. A system comprising:
a digital storage device; and a processor coupled with the digital storage device, the processor configured to: receive a first log report from a first media player, wherein the first log report comprises a first unique value associated with a publisher and the first media player, and wherein the first log report includes one or more playback commands applied to a first piece of content at the first media player; store the first log report in the digital storage device; receive a second log report from a second media player, wherein the second log report comprises a second unique value associated with the publisher and the second media player, and wherein the second log report includes one or more playback commands applied to a second piece of content at the second media player; store the second log report in the storage device along with the first log report; and receive a query to search the storage device for playback information 14. The system according to claim 13, wherein the query includes a request for information associated with playback of specific content. 15. The system according to claim 13, wherein the first log report does not include information that reveals an identity of the first media player and the second log report does not include information that reveals an identity of the second media player. 16. The system according to claim 13, wherein the one or more playback commands includes at least one of play, stop, pause, fast forward, and rewind. 17. The system according to claim 13, wherein the first log report and the second log report include feed events including at least one of subscribe, unsubscribe, check for update notification, check for update, complete, download start, download paused, download resumed, and download completed. 18. The system according to claim 13, wherein the query is received from the publisher. | 2,100 |
6,095 | 6,095 | 15,990,964 | 2,154 | A method, a system, and an article are provided for managing a file cache for a client application. An example computer-implemented method can include: storing a plurality of files in a memory on a client device for a client application; identifying a first portion of the files in the memory as having been used during a previous run of the client application; receiving, from at least one server, one or more lists of files to be used during a current run of the client application; identifying a second portion of the files in the memory as not being included in at least one of the first portion and the one or more lists of files from the at least one server; and removing, from the memory, at least a subset of the second portion of the files during the current run of the client application. | 1. A computer-implemented method, comprising:
storing a plurality of files in a memory on a client device for a client application; identifying a first portion of the files in the memory as having been used during a previous run of the client application; receiving, from at least one server, one or more lists of files to be used during a current run of the client application; identifying a second portion of the files in the memory as not being included in at least one of the first portion and the one or more lists of files from the at least one server; and removing, from the memory, at least a subset of the second portion of the files during the current run of the client application. 2. The method of claim 1, wherein the plurality of files is stored in at least one cache folder, and wherein each cache folder in the at least one cache folder corresponds to a respective server in the at least one server. 3. The method of claim 1, wherein identifying the first portion comprises:
retrieving, from the memory, a history file that lists the files used during the previous run. 4. The method of claim 3, further comprising:
updating the history file to list the files used during the current run of the client application. 5. The method of claim 4, further comprising:
using the updated history file to identify the first portion of the files during a subsequent run of the client application. 6. The method of claim 1, wherein the second portion comprises files that were not used during the previous run and will not be used during the current run. 7. The method of claim 1, wherein removing from the memory comprises:
deleting files from the memory up to a predetermined maximum number of files, wherein the maximum number is less than or equal to a number of files included in the second portion. 8. The method of claim 1, further comprising:
obtaining each file identified in the one or more lists of files for use during the current run of the client application. 9. The method of claim 8, wherein obtaining each file comprises determining if the file is stored in the memory. 10. The method of claim 9, wherein obtaining each file comprises one of:
retrieving the file from the memory if the file is stored in the memory; and downloading the file from the at least one server if the file is not stored in the memory. 11. A system, comprising:
one or more computer processors programmed to perform operations comprising:
storing a plurality of files in a memory on a client device for a client application;
identifying a first portion of the files in the memory as having been used during a previous run of the client application;
receiving, from at least one server, one or more lists of files to be used during a current run of the client application;
identifying a second portion of the files in the memory as not being included in at least one of the first portion and the one or more lists of files from the at least one server; and
removing, from the memory, at least a subset of the second portion of the files during the current run of the client application. 12. The system of claim 11, wherein the plurality of files is stored in at least one cache folder, and wherein each cache folder in the at least one cache folder corresponds to a respective server in the at least one server. 13. The system of claim 11, wherein identifying the first portion comprises:
retrieving, from the memory, a history file that lists the files used during the previous run. 14. The system of claim 13, the operations further comprising:
updating the history file to list the files used during the current run of the client application. 15. The system of claim 11, wherein the second portion comprises files that were not used during the previous run and will not be used during the current run. 16. The system of claim 11, wherein removing from the memory comprises:
deleting files from the memory up to a predetermined maximum number of files, wherein the maximum number is less than or equal to a number of files included in the second portion. 17. The system of claim 11, the operations further comprising:
obtaining each file identified in the one or more lists of files for use during the current run of the client application. 18. The system of claim 17, wherein obtaining each file comprises determining if the file is stored in the memory. 19. The system of claim 18, wherein obtaining each file comprises one of:
retrieving the file from the memory if the file is stored in the memory; and downloading the file from the at least one server if the file is not stored in the memory. 20. An article, comprising:
a non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more computer processors, cause the computer processors to perform operations comprising:
storing a plurality of files in a memory on a client device for a client application;
identifying a first portion of the files in the memory as having been used during a previous run of the client application;
receiving, from at least one server, one or more lists of files to be used during a current run of the client application;
identifying a second portion of the files in the memory as not being included in at least one of the first portion and the one or more lists of files from the at least one server; and
removing, from the memory, at least a subset of the second portion of the files during the current run of the client application. | A method, a system, and an article are provided for managing a file cache for a client application. An example computer-implemented method can include: storing a plurality of files in a memory on a client device for a client application; identifying a first portion of the files in the memory as having been used during a previous run of the client application; receiving, from at least one server, one or more lists of files to be used during a current run of the client application; identifying a second portion of the files in the memory as not being included in at least one of the first portion and the one or more lists of files from the at least one server; and removing, from the memory, at least a subset of the second portion of the files during the current run of the client application.1. A computer-implemented method, comprising:
storing a plurality of files in a memory on a client device for a client application; identifying a first portion of the files in the memory as having been used during a previous run of the client application; receiving, from at least one server, one or more lists of files to be used during a current run of the client application; identifying a second portion of the files in the memory as not being included in at least one of the first portion and the one or more lists of files from the at least one server; and removing, from the memory, at least a subset of the second portion of the files during the current run of the client application. 2. The method of claim 1, wherein the plurality of files is stored in at least one cache folder, and wherein each cache folder in the at least one cache folder corresponds to a respective server in the at least one server. 3. The method of claim 1, wherein identifying the first portion comprises:
retrieving, from the memory, a history file that lists the files used during the previous run. 4. The method of claim 3, further comprising:
updating the history file to list the files used during the current run of the client application. 5. The method of claim 4, further comprising:
using the updated history file to identify the first portion of the files during a subsequent run of the client application. 6. The method of claim 1, wherein the second portion comprises files that were not used during the previous run and will not be used during the current run. 7. The method of claim 1, wherein removing from the memory comprises:
deleting files from the memory up to a predetermined maximum number of files, wherein the maximum number is less than or equal to a number of files included in the second portion. 8. The method of claim 1, further comprising:
obtaining each file identified in the one or more lists of files for use during the current run of the client application. 9. The method of claim 8, wherein obtaining each file comprises determining if the file is stored in the memory. 10. The method of claim 9, wherein obtaining each file comprises one of:
retrieving the file from the memory if the file is stored in the memory; and downloading the file from the at least one server if the file is not stored in the memory. 11. A system, comprising:
one or more computer processors programmed to perform operations comprising:
storing a plurality of files in a memory on a client device for a client application;
identifying a first portion of the files in the memory as having been used during a previous run of the client application;
receiving, from at least one server, one or more lists of files to be used during a current run of the client application;
identifying a second portion of the files in the memory as not being included in at least one of the first portion and the one or more lists of files from the at least one server; and
removing, from the memory, at least a subset of the second portion of the files during the current run of the client application. 12. The system of claim 11, wherein the plurality of files is stored in at least one cache folder, and wherein each cache folder in the at least one cache folder corresponds to a respective server in the at least one server. 13. The system of claim 11, wherein identifying the first portion comprises:
retrieving, from the memory, a history file that lists the files used during the previous run. 14. The system of claim 13, the operations further comprising:
updating the history file to list the files used during the current run of the client application. 15. The system of claim 11, wherein the second portion comprises files that were not used during the previous run and will not be used during the current run. 16. The system of claim 11, wherein removing from the memory comprises:
deleting files from the memory up to a predetermined maximum number of files, wherein the maximum number is less than or equal to a number of files included in the second portion. 17. The system of claim 11, the operations further comprising:
obtaining each file identified in the one or more lists of files for use during the current run of the client application. 18. The system of claim 17, wherein obtaining each file comprises determining if the file is stored in the memory. 19. The system of claim 18, wherein obtaining each file comprises one of:
retrieving the file from the memory if the file is stored in the memory; and downloading the file from the at least one server if the file is not stored in the memory. 20. An article, comprising:
a non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more computer processors, cause the computer processors to perform operations comprising:
storing a plurality of files in a memory on a client device for a client application;
identifying a first portion of the files in the memory as having been used during a previous run of the client application;
receiving, from at least one server, one or more lists of files to be used during a current run of the client application;
identifying a second portion of the files in the memory as not being included in at least one of the first portion and the one or more lists of files from the at least one server; and
removing, from the memory, at least a subset of the second portion of the files during the current run of the client application. | 2,100 |
6,096 | 6,096 | 14,614,344 | 2,119 | A computer may display on a graphical user interface (GUI) a component library including a set of components relating to a compressed air system. The GUI may have a modeling interface for configuring a virtual model using the set of components. The computer may simulate the virtual model to determine one or more optimizations to the compressed air system. The computer may also determine the cost of implementing the compressor system optimization. | 1. A method, comprising:
receiving, with a computer, a set of library data relating to a compressed air system from a database at a first server; displaying, with a first graphical user interface (GUI) on the computer, a visual representation of each of the set of library data in a first portion of the GUI, a settings interface in a second portion of the GUI, and a modeling interface in a third portion of the GUI; receiving, through the GUI, a user initiated request to add at least a portion of the set library data to the second portion of the GUI to form a model of a compressed air system; receiving a demand profile from a user; receiving, through the GUI, a user initiated request to simulate the model; simulating the model of the system to generate simulation data; determining one or more optimization gaps based on the simulation data and the demand profile; determining a recommendation based on the one or more optimization gap; transmitting the recommendation to a second server; receiving a sales quote for one or more products from the second server based on the recommendation; displaying, with a second GUI on the computer, the simulation data, the sales quote, and the recommendation. 2. The method of claim 1, wherein the set of library data includes at least one of a component library and a template library. 3. The method of claim 2, wherein the component library comprises a set of components relating to a compressed air system, wherein the set of components includes at least one of a compressor, a dryer, a filter, a regulator, a pipe, a pipe fitting, a point-of-use tool, a hose, a valve, a drain, an air receiver, a separator, a lubricator, a cooler, a safety device, a treatment component, and a customizable component. 4. The method of claim 3, wherein each component in the set of components includes one or more settings, and wherein the one or more settings includes at least one of a compressor pressure set point, a dryer dew point, a flow demand, a humidity, a temperature, an energy consumption, a pressure, a flow, a relative humidity, a temperature, and a component specific setting. 5. The method of claim 2, wherein the template library comprises a set of templates relating to a compressed air system, wherein the set of templates includes at least one of a component combination template, a compressor room layout template, a factory floor layout template, and a header network template. 6. The method of claim 1, wherein the visual representation includes at least one of an icon, a button, a textual representation, and a graphical representation. 7. The method of claim 1, wherein the simulation data includes at least one of a transient pressure, a dynamic pressure, a flow, a moisture content, an energy consumption, and a financial reference. 8. The method of claim 7, wherein the financial reference includes at least one of a bill of materials (BOM), a budget, a return on investment (ROI), and a total cost of ownership (TCO). 9. The method of claim 1, further comprising transmitting the sales quote and the recommendation to another computing device via email. 10. The method of claim 1, further comprising:
transmitting at least one of the model and the simulation to be saved on the first server. 11. A system, comprising:
a first computing device configured with non-transitory computer executable instructions to receive and maintain a first database that includes library data relating to a compressed air system; a second computing device configured with non-transitory computer executable instructions to receive at least a portion of the library data from the first computing device, display the library data in a graphical user interface (GUI), receive input through the GUI from a user to create a demand profile and generate a model of a system from the library data, simulate the model of the system to generate simulation data, determine one or more optimizations based on the simulation data and the demand profile, determine a recommendation based on the optimizations, receive a sales quote for one or more products, and display the simulation data, the sales quote, and the recommendation; and a third computing device configured with non-transitory computer executable instructions to receive the recommendation, generate the sales quote based on the recommendation and transmit the sales quote to the second computing device. 12. The system of claim 11, wherein the first computing device is a first server and the third computing device is a second server, and wherein the first server and the second server are part of one server. 13. The system of claim 11, wherein the first computing device is a first server and the third computing device is a second server, and wherein the first server and the second server are separate servers. 14. The system of claim 11, wherein the first computing device is further configured to receive and maintain at least one of a real-time data and a historical data. 15. The system of claim 14, wherein the second computing device is further configured to receive and display, through the GUI, at least one of the real-time data and the historical data, and wherein the one or more optimizations are further determined based on at least one of the real-time data and the historical data. 16. The system of claim 11, wherein the third computing device further includes a second database to store at least one of the component library, the model, and the simulation data. 17. A computing device, comprising:
a processor and a memory including non-transitory computer executable instructions that when executed by the processor cause the computing device to:
receive a component library relating to an HVAC system and generate a model of a customer system based on the component library, the component library including a set of components relating to the HVAC system;
simulate the model of the customer system to generate simulation data;
determine an optimization based on the simulation data and a demand profile;
determine a recommendation based on the optimization and receive a sales quote for a product; and
generate and display a GUI with the component library in a first portion of the GUI, the model of the customer system based on the component library in a second portion of the GUI, and the demand profile and one or more settings of the each of the set of components in the component library in a third portion of the GUI. 18. The computing device of claim 17, wherein the computing device is further structured to generate and display a second GUI with the simulation data, the recommendation, and the sales quote. 19. The computing device of claim 17, wherein the computing device is further structured to transmit the sales quote and the recommendation to another computing device via email. 20. The computing device of claim 19, further comprising:
a database to store at least one of the component library, the model, and the simulation data. 21. The computing device of claim 17, wherein the optimization is based on real-time data and historical data. | A computer may display on a graphical user interface (GUI) a component library including a set of components relating to a compressed air system. The GUI may have a modeling interface for configuring a virtual model using the set of components. The computer may simulate the virtual model to determine one or more optimizations to the compressed air system. The computer may also determine the cost of implementing the compressor system optimization.1. A method, comprising:
receiving, with a computer, a set of library data relating to a compressed air system from a database at a first server; displaying, with a first graphical user interface (GUI) on the computer, a visual representation of each of the set of library data in a first portion of the GUI, a settings interface in a second portion of the GUI, and a modeling interface in a third portion of the GUI; receiving, through the GUI, a user initiated request to add at least a portion of the set library data to the second portion of the GUI to form a model of a compressed air system; receiving a demand profile from a user; receiving, through the GUI, a user initiated request to simulate the model; simulating the model of the system to generate simulation data; determining one or more optimization gaps based on the simulation data and the demand profile; determining a recommendation based on the one or more optimization gap; transmitting the recommendation to a second server; receiving a sales quote for one or more products from the second server based on the recommendation; displaying, with a second GUI on the computer, the simulation data, the sales quote, and the recommendation. 2. The method of claim 1, wherein the set of library data includes at least one of a component library and a template library. 3. The method of claim 2, wherein the component library comprises a set of components relating to a compressed air system, wherein the set of components includes at least one of a compressor, a dryer, a filter, a regulator, a pipe, a pipe fitting, a point-of-use tool, a hose, a valve, a drain, an air receiver, a separator, a lubricator, a cooler, a safety device, a treatment component, and a customizable component. 4. The method of claim 3, wherein each component in the set of components includes one or more settings, and wherein the one or more settings includes at least one of a compressor pressure set point, a dryer dew point, a flow demand, a humidity, a temperature, an energy consumption, a pressure, a flow, a relative humidity, a temperature, and a component specific setting. 5. The method of claim 2, wherein the template library comprises a set of templates relating to a compressed air system, wherein the set of templates includes at least one of a component combination template, a compressor room layout template, a factory floor layout template, and a header network template. 6. The method of claim 1, wherein the visual representation includes at least one of an icon, a button, a textual representation, and a graphical representation. 7. The method of claim 1, wherein the simulation data includes at least one of a transient pressure, a dynamic pressure, a flow, a moisture content, an energy consumption, and a financial reference. 8. The method of claim 7, wherein the financial reference includes at least one of a bill of materials (BOM), a budget, a return on investment (ROI), and a total cost of ownership (TCO). 9. The method of claim 1, further comprising transmitting the sales quote and the recommendation to another computing device via email. 10. The method of claim 1, further comprising:
transmitting at least one of the model and the simulation to be saved on the first server. 11. A system, comprising:
a first computing device configured with non-transitory computer executable instructions to receive and maintain a first database that includes library data relating to a compressed air system; a second computing device configured with non-transitory computer executable instructions to receive at least a portion of the library data from the first computing device, display the library data in a graphical user interface (GUI), receive input through the GUI from a user to create a demand profile and generate a model of a system from the library data, simulate the model of the system to generate simulation data, determine one or more optimizations based on the simulation data and the demand profile, determine a recommendation based on the optimizations, receive a sales quote for one or more products, and display the simulation data, the sales quote, and the recommendation; and a third computing device configured with non-transitory computer executable instructions to receive the recommendation, generate the sales quote based on the recommendation and transmit the sales quote to the second computing device. 12. The system of claim 11, wherein the first computing device is a first server and the third computing device is a second server, and wherein the first server and the second server are part of one server. 13. The system of claim 11, wherein the first computing device is a first server and the third computing device is a second server, and wherein the first server and the second server are separate servers. 14. The system of claim 11, wherein the first computing device is further configured to receive and maintain at least one of a real-time data and a historical data. 15. The system of claim 14, wherein the second computing device is further configured to receive and display, through the GUI, at least one of the real-time data and the historical data, and wherein the one or more optimizations are further determined based on at least one of the real-time data and the historical data. 16. The system of claim 11, wherein the third computing device further includes a second database to store at least one of the component library, the model, and the simulation data. 17. A computing device, comprising:
a processor and a memory including non-transitory computer executable instructions that when executed by the processor cause the computing device to:
receive a component library relating to an HVAC system and generate a model of a customer system based on the component library, the component library including a set of components relating to the HVAC system;
simulate the model of the customer system to generate simulation data;
determine an optimization based on the simulation data and a demand profile;
determine a recommendation based on the optimization and receive a sales quote for a product; and
generate and display a GUI with the component library in a first portion of the GUI, the model of the customer system based on the component library in a second portion of the GUI, and the demand profile and one or more settings of the each of the set of components in the component library in a third portion of the GUI. 18. The computing device of claim 17, wherein the computing device is further structured to generate and display a second GUI with the simulation data, the recommendation, and the sales quote. 19. The computing device of claim 17, wherein the computing device is further structured to transmit the sales quote and the recommendation to another computing device via email. 20. The computing device of claim 19, further comprising:
a database to store at least one of the component library, the model, and the simulation data. 21. The computing device of claim 17, wherein the optimization is based on real-time data and historical data. | 2,100 |
6,097 | 6,097 | 14,721,630 | 2,128 | This disclosure relates to service discovery using a dynamically configurable Bloom filter. According to some embodiments, various parameters of the Bloom filter may be determined by a first wireless device. The parameters may include a number of services advertised using the Bloom filter, a false positive rate of the Bloom filter, a set of hash functions used with the Bloom filter, and/or a size of the Bloom filter. The Bloom filter may be generated according to the determined parameters. The Bloom filter, along with some or all of the parameters of the Bloom filter, may be transmitted by the first wireless device. A second wireless device may use the Bloom filter as part of a service discovery process to determine whether or not a desired service is available via the first wireless device. | 1. A wireless device, comprising:
a radio; and a processing element operatively coupled to the radio; wherein the radio and the processing element are configured to:
select a plurality of parameter values for a probabilistic data structure;
generate the probabilistic data structure using the selected plurality of parameter values, wherein the probabilistic data structure provides a service hint map for at least one service available via the wireless device; and
wirelessly transmit the probabilistic data structure. 2. The wireless device of claim 1,
wherein the probabilistic data structure comprises a Bloom filter. 3. The wireless device of claim 1, wherein the plurality of parameter values comprise one or more of:
a number of services advertised using the probabilistic data structure; a false positive rate of services advertised using the probabilistic data structure; a set of hash functions used with the probabilistic data structure; or a size of the probabilistic data structure. 4. The wireless device of claim 1, wherein the radio and the processing element are further configured to:
wirelessly transmit an indication of one or more of the plurality of parameter values for the probabilistic data structure. 5. The wireless device of claim 1, wherein the radio and the processing element are further configured to:
wirelessly transmit information directly advertising one or more services available via the wireless device in addition to advertising services available via the wireless device using the probabilistic data structure. 6. The wireless device of claim 1, wherein the probabilistic data structure is wirelessly transmitted as part of a Wi-Fi beacon. 7. A method for discovering services advertised by a first wireless device, comprising:
by a second wireless device: receiving information regarding services available via the first wireless device, wherein the information comprises a Bloom filter and one or more parameters of the Bloom filter; and determining whether the Bloom filter indicates that at least a first service is or is not available via the first wireless device. 8. The method of claim 7, the method further comprising:
determining a false-positive probability of the Bloom filter; and if the Bloom filter indicates that the first service is available and the false-positive probability of the Bloom filter is below a false-positive threshold, sending a generic advertisement service (GAS) query to the first wireless device regarding the first service. 9. The method of claim 8, the method further comprising, if the Bloom filter indicates that the first service is available and the false-positive probability of the Bloom filter is above a false-positive threshold:
sending a probe request to the first wireless device regarding the first service; receiving a probe response indicating whether the first service is available via the first wireless device; and if the first service is available via the first wireless device, sending a generic advertisement service (GAS) query to the first wireless device regarding the first service. 10. The method of claim 7,
wherein the information regarding services available via the first wireless device further comprises information directly indicating availability of one or more services via the first wireless device. 11. The method of claim 7,
wherein the one or more parameters comprise a number of services advertised using the Bloom filter and a set of hash functions used with the Bloom filter. 12. The method of claim 11, the method further comprising:
calculating a false positive rate of the Bloom filter based on a number of hash functions used with the Bloom filter. 13. The method of claim 12, the method further comprising:
calculating a length of the Bloom filter based on the false positive rate of the Bloom filter and the number of services advertised using the Bloom filter. 14. The method of claim 7,
wherein the information is received in a Wi-Fi beacon. 15. A second wireless device, comprising:
a radio; and a processing element operatively coupled to the radio; wherein the radio and the processing element are configured to:
receive information regarding services available via a first wireless device, wherein the information comprises a probabilistic data structure and an indication of one or more parameters of the probabilistic data structure; and
determine whether the probabilistic data structure provides a positive or negative indication of the availability via the first wireless device of each of one or more services. 16. The second wireless device of claim 15, wherein the radio and the processing element are further configured to:
determine that a first service is not available via the first wireless device if the probabilistic data structure provides a negative indication of the availability via the first wireless device of the first service. 17. The second wireless device of claim 15, wherein the radio and the processing element are further configured to:
determine a false-positive probability of the probabilistic data structure based at least in part on the one or more parameters of the probabilistic data structure. 18. The second wireless device of claim 15, wherein the radio and the processing element are further configured to:
calculate one or more additional parameters of the probabilistic data structure based at least in part on the indicated one or more parameters of the probabilistic data structure. 19. The second wireless device of claim 15,
wherein the information regarding services available via the first wireless device further comprises information directly indicating availability of one or more services via the first wireless device. 20. The second wireless device of claim 15,
wherein the probabilistic data structure comprises a Bloom filter. | This disclosure relates to service discovery using a dynamically configurable Bloom filter. According to some embodiments, various parameters of the Bloom filter may be determined by a first wireless device. The parameters may include a number of services advertised using the Bloom filter, a false positive rate of the Bloom filter, a set of hash functions used with the Bloom filter, and/or a size of the Bloom filter. The Bloom filter may be generated according to the determined parameters. The Bloom filter, along with some or all of the parameters of the Bloom filter, may be transmitted by the first wireless device. A second wireless device may use the Bloom filter as part of a service discovery process to determine whether or not a desired service is available via the first wireless device.1. A wireless device, comprising:
a radio; and a processing element operatively coupled to the radio; wherein the radio and the processing element are configured to:
select a plurality of parameter values for a probabilistic data structure;
generate the probabilistic data structure using the selected plurality of parameter values, wherein the probabilistic data structure provides a service hint map for at least one service available via the wireless device; and
wirelessly transmit the probabilistic data structure. 2. The wireless device of claim 1,
wherein the probabilistic data structure comprises a Bloom filter. 3. The wireless device of claim 1, wherein the plurality of parameter values comprise one or more of:
a number of services advertised using the probabilistic data structure; a false positive rate of services advertised using the probabilistic data structure; a set of hash functions used with the probabilistic data structure; or a size of the probabilistic data structure. 4. The wireless device of claim 1, wherein the radio and the processing element are further configured to:
wirelessly transmit an indication of one or more of the plurality of parameter values for the probabilistic data structure. 5. The wireless device of claim 1, wherein the radio and the processing element are further configured to:
wirelessly transmit information directly advertising one or more services available via the wireless device in addition to advertising services available via the wireless device using the probabilistic data structure. 6. The wireless device of claim 1, wherein the probabilistic data structure is wirelessly transmitted as part of a Wi-Fi beacon. 7. A method for discovering services advertised by a first wireless device, comprising:
by a second wireless device: receiving information regarding services available via the first wireless device, wherein the information comprises a Bloom filter and one or more parameters of the Bloom filter; and determining whether the Bloom filter indicates that at least a first service is or is not available via the first wireless device. 8. The method of claim 7, the method further comprising:
determining a false-positive probability of the Bloom filter; and if the Bloom filter indicates that the first service is available and the false-positive probability of the Bloom filter is below a false-positive threshold, sending a generic advertisement service (GAS) query to the first wireless device regarding the first service. 9. The method of claim 8, the method further comprising, if the Bloom filter indicates that the first service is available and the false-positive probability of the Bloom filter is above a false-positive threshold:
sending a probe request to the first wireless device regarding the first service; receiving a probe response indicating whether the first service is available via the first wireless device; and if the first service is available via the first wireless device, sending a generic advertisement service (GAS) query to the first wireless device regarding the first service. 10. The method of claim 7,
wherein the information regarding services available via the first wireless device further comprises information directly indicating availability of one or more services via the first wireless device. 11. The method of claim 7,
wherein the one or more parameters comprise a number of services advertised using the Bloom filter and a set of hash functions used with the Bloom filter. 12. The method of claim 11, the method further comprising:
calculating a false positive rate of the Bloom filter based on a number of hash functions used with the Bloom filter. 13. The method of claim 12, the method further comprising:
calculating a length of the Bloom filter based on the false positive rate of the Bloom filter and the number of services advertised using the Bloom filter. 14. The method of claim 7,
wherein the information is received in a Wi-Fi beacon. 15. A second wireless device, comprising:
a radio; and a processing element operatively coupled to the radio; wherein the radio and the processing element are configured to:
receive information regarding services available via a first wireless device, wherein the information comprises a probabilistic data structure and an indication of one or more parameters of the probabilistic data structure; and
determine whether the probabilistic data structure provides a positive or negative indication of the availability via the first wireless device of each of one or more services. 16. The second wireless device of claim 15, wherein the radio and the processing element are further configured to:
determine that a first service is not available via the first wireless device if the probabilistic data structure provides a negative indication of the availability via the first wireless device of the first service. 17. The second wireless device of claim 15, wherein the radio and the processing element are further configured to:
determine a false-positive probability of the probabilistic data structure based at least in part on the one or more parameters of the probabilistic data structure. 18. The second wireless device of claim 15, wherein the radio and the processing element are further configured to:
calculate one or more additional parameters of the probabilistic data structure based at least in part on the indicated one or more parameters of the probabilistic data structure. 19. The second wireless device of claim 15,
wherein the information regarding services available via the first wireless device further comprises information directly indicating availability of one or more services via the first wireless device. 20. The second wireless device of claim 15,
wherein the probabilistic data structure comprises a Bloom filter. | 2,100 |
6,098 | 6,098 | 15,258,287 | 2,125 | A method, system and a computer program product are provided for verifying ground truth data by iteratively clustering machine-annotated training set examples with validation set examples to identify and display one or more prioritized review candidate training set examples grouped with validation set examples meeting a predetermined misclassification criteria in order to solicit verification or correction feedback from a human subject matter expert for inclusion in an accepted training set. | 1. A method of verifying ground truth data, the method comprising:
receiving, by an information handling system, comprising a processor and a memory, ground truth data comprising a human-curated training set and validation set; performing, by the information handling system, annotation operations on the training set and validation set using an annotator to generate a machine-annotated training set and validation set; assigning, by the information handling system, examples from the machine-annotated training set and validation set to one or more clusters using a cluster model; analyzing, by the information handling system, the one or more clusters to identify one or more training set examples grouped with validation set examples meeting predetermined misclassification criteria; and displaying, by the information handling system, the identified one or more training set examples as prioritized review candidates to solicit verification or correction feedback from a human subject matter expert for inclusion in an accepted training set. 2. The method of claim 1, where the annotator comprises a dictionary annotator, rule-based annotator, or a machine learning annotator. 3. The method of claim 1, where assigning examples from the machine-annotated training set and validation set to one or more clusters comprises:
generating a vector representation for each of example from the machine-annotated training set and validation set; and applying a rule-based probabilistic algorithm to the vector representations of the machine-annotated training set and validation set examples to identify the one or more clusters. 4. The method of claim 1, where the cluster model comprises a neural network language model. 5. The method of claim 1, where the predetermined misclassification criteria is that the validation set examples are not annotated by a human annotator. 6. The method of claim 1, where the predetermined misclassification criteria is that the validation set examples are not annotated by a human annotator or a machine annotator. 7. The method of claim 1, further comprising verifying or correcting all prioritized review candidates in a cluster as a single group based on verification or correction feedback from the human subject matter expert. 8. The method of claim 1, further comprising training final annotator with the accepted training set. 9. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on an information handling system, causes the system to verify ground truth data by:
receiving a human-curated training set and validation set; performing annotation operations on the training set and validation set using an annotator to generate a machine-annotated training set and validation set; assigning examples from the machine-annotated training set and validation set to one or more clusters using a cluster model; analyzing the one or more clusters to identify one or more training set examples grouped with validation set examples meeting predetermined misclassification criteria; and displaying the identified one or more training set examples as prioritized review candidates to solicit verification or correction feedback from a human subject matter expert for inclusion in an accepted training set. 10. The computer program product of claim 9, wherein the computer readable program, when executed on the system, causes the system to perform annotation operations using a dictionary annotator, rule-based annotator, or a machine learning annotator. 11. The computer program product of claim 9, wherein the computer readable program, when executed on the system, causes the system to assign examples from the machine-annotated training set and validation set to one or more clusters by:
generating a vector representation for each of example from the machine-annotated training set and validation set using a neural network language model; and applying a rule-based probabilistic algorithm to the vector representations of the machine-annotated training set and validation set examples to identify the one or more clusters using the cluster model. 12. The computer program product of claim 9, where at least one of the predetermined misclassification criteria is that the validation set examples are not annotated by a human annotator. 13. The computer program product of claim 9, where at least one of the predetermined misclassification criteria is that the validation set examples are not annotated by a human annotator or a machine annotator. 14. The computer program product of claim 9, further comprising computer readable program, when executed on the system, causes the system to verify or correct all prioritized review candidates in a cluster as a single group based on verification or correction feedback from the human subject matter expert. 15. The computer program product of claim 9, further comprising computer readable program, when executed on the system, causes the system to verify or correct prioritized review candidates in a cluster one at a time based on verification or correction feedback from the human subject matter expert. 16. An information handling system comprising:
one or more processors; a memory coupled to at least one of the processors; and a set of instructions stored in the memory and executed by at least one of the processors to verify ground truth data, wherein the set of instructions are executable to perform actions of: receiving, by the system, a human-curated training set and validation set; performing, by the system, annotation operations on the training set and validation set using an annotator to generate a machine-annotated training set and validation set; assigning, by the system, examples from the machine-annotated training set and validation set to one or more clusters using a cluster model; analyzing, by the system, the one or more clusters to identify one or more training set examples grouped with validation set examples meeting predetermined misclassification criteria; and displaying, by the system, the identified one or more training set examples as prioritized review candidates to solicit verification or correction feedback from a human subject matter expert for inclusion in an accepted training set. 17. The information handling system of claim 16, wherein performing annotation operations comprises using a dictionary annotator, rule-based annotator, or a machine learning annotator. 18. The information handling system of claim 16, wherein assigning examples from the machine-annotated training set and validation set to one or more clusters comprises:
generating, by the system, a vector representation for each of example from the machine-annotated training set and validation set using a neural network language model; and applying, by the system, a rule-based probabilistic algorithm to the vector representations of the machine-annotated training set and validation set examples to identify the one or more clusters using the cluster model. 19. The information handling system of claim 16, where at least one of the predetermined misclassification criteria is that the validation set examples are not annotated by a human annotator. 20. The information handling system of claim 16, where at least one of the predetermined misclassification criteria is that the validation set examples are not annotated by a human annotator or a machine annotator. 21. The information handling system of claim 16, further comprising verifying or correcting all prioritized review candidates in a cluster as a single group based on verification or correction feedback from the human subject matter expert. 22. The information handling system of claim 16, further comprising verifying or correcting prioritized review candidates in a cluster one at a time based on verification or correction feedback from the human subject matter expert. | A method, system and a computer program product are provided for verifying ground truth data by iteratively clustering machine-annotated training set examples with validation set examples to identify and display one or more prioritized review candidate training set examples grouped with validation set examples meeting a predetermined misclassification criteria in order to solicit verification or correction feedback from a human subject matter expert for inclusion in an accepted training set.1. A method of verifying ground truth data, the method comprising:
receiving, by an information handling system, comprising a processor and a memory, ground truth data comprising a human-curated training set and validation set; performing, by the information handling system, annotation operations on the training set and validation set using an annotator to generate a machine-annotated training set and validation set; assigning, by the information handling system, examples from the machine-annotated training set and validation set to one or more clusters using a cluster model; analyzing, by the information handling system, the one or more clusters to identify one or more training set examples grouped with validation set examples meeting predetermined misclassification criteria; and displaying, by the information handling system, the identified one or more training set examples as prioritized review candidates to solicit verification or correction feedback from a human subject matter expert for inclusion in an accepted training set. 2. The method of claim 1, where the annotator comprises a dictionary annotator, rule-based annotator, or a machine learning annotator. 3. The method of claim 1, where assigning examples from the machine-annotated training set and validation set to one or more clusters comprises:
generating a vector representation for each of example from the machine-annotated training set and validation set; and applying a rule-based probabilistic algorithm to the vector representations of the machine-annotated training set and validation set examples to identify the one or more clusters. 4. The method of claim 1, where the cluster model comprises a neural network language model. 5. The method of claim 1, where the predetermined misclassification criteria is that the validation set examples are not annotated by a human annotator. 6. The method of claim 1, where the predetermined misclassification criteria is that the validation set examples are not annotated by a human annotator or a machine annotator. 7. The method of claim 1, further comprising verifying or correcting all prioritized review candidates in a cluster as a single group based on verification or correction feedback from the human subject matter expert. 8. The method of claim 1, further comprising training final annotator with the accepted training set. 9. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on an information handling system, causes the system to verify ground truth data by:
receiving a human-curated training set and validation set; performing annotation operations on the training set and validation set using an annotator to generate a machine-annotated training set and validation set; assigning examples from the machine-annotated training set and validation set to one or more clusters using a cluster model; analyzing the one or more clusters to identify one or more training set examples grouped with validation set examples meeting predetermined misclassification criteria; and displaying the identified one or more training set examples as prioritized review candidates to solicit verification or correction feedback from a human subject matter expert for inclusion in an accepted training set. 10. The computer program product of claim 9, wherein the computer readable program, when executed on the system, causes the system to perform annotation operations using a dictionary annotator, rule-based annotator, or a machine learning annotator. 11. The computer program product of claim 9, wherein the computer readable program, when executed on the system, causes the system to assign examples from the machine-annotated training set and validation set to one or more clusters by:
generating a vector representation for each of example from the machine-annotated training set and validation set using a neural network language model; and applying a rule-based probabilistic algorithm to the vector representations of the machine-annotated training set and validation set examples to identify the one or more clusters using the cluster model. 12. The computer program product of claim 9, where at least one of the predetermined misclassification criteria is that the validation set examples are not annotated by a human annotator. 13. The computer program product of claim 9, where at least one of the predetermined misclassification criteria is that the validation set examples are not annotated by a human annotator or a machine annotator. 14. The computer program product of claim 9, further comprising computer readable program, when executed on the system, causes the system to verify or correct all prioritized review candidates in a cluster as a single group based on verification or correction feedback from the human subject matter expert. 15. The computer program product of claim 9, further comprising computer readable program, when executed on the system, causes the system to verify or correct prioritized review candidates in a cluster one at a time based on verification or correction feedback from the human subject matter expert. 16. An information handling system comprising:
one or more processors; a memory coupled to at least one of the processors; and a set of instructions stored in the memory and executed by at least one of the processors to verify ground truth data, wherein the set of instructions are executable to perform actions of: receiving, by the system, a human-curated training set and validation set; performing, by the system, annotation operations on the training set and validation set using an annotator to generate a machine-annotated training set and validation set; assigning, by the system, examples from the machine-annotated training set and validation set to one or more clusters using a cluster model; analyzing, by the system, the one or more clusters to identify one or more training set examples grouped with validation set examples meeting predetermined misclassification criteria; and displaying, by the system, the identified one or more training set examples as prioritized review candidates to solicit verification or correction feedback from a human subject matter expert for inclusion in an accepted training set. 17. The information handling system of claim 16, wherein performing annotation operations comprises using a dictionary annotator, rule-based annotator, or a machine learning annotator. 18. The information handling system of claim 16, wherein assigning examples from the machine-annotated training set and validation set to one or more clusters comprises:
generating, by the system, a vector representation for each of example from the machine-annotated training set and validation set using a neural network language model; and applying, by the system, a rule-based probabilistic algorithm to the vector representations of the machine-annotated training set and validation set examples to identify the one or more clusters using the cluster model. 19. The information handling system of claim 16, where at least one of the predetermined misclassification criteria is that the validation set examples are not annotated by a human annotator. 20. The information handling system of claim 16, where at least one of the predetermined misclassification criteria is that the validation set examples are not annotated by a human annotator or a machine annotator. 21. The information handling system of claim 16, further comprising verifying or correcting all prioritized review candidates in a cluster as a single group based on verification or correction feedback from the human subject matter expert. 22. The information handling system of claim 16, further comprising verifying or correcting prioritized review candidates in a cluster one at a time based on verification or correction feedback from the human subject matter expert. | 2,100 |
6,099 | 6,099 | 15,828,133 | 2,114 | Automated computational methods and systems to classify and troubleshoot problems in information technology (“IT”) systems or services provided by a distributed computing system are described. Each IT system of the distribution computing system or IT service provided by the distributed computing system has an associated key performance indicator (“KPI”) used to monitor performance of the IT system or service. When real-time KPI data violates a KPI threshold, a real-time event-type distribution is computed from event messages generated by event sources associated with the IT system or service following the threshold violation. The real-time event-type distribution is compared with historical event-type distributions recorded for the KPI data in order to identify the problem and execute remedial action to resolve the problem. | 1. An automated method stored in one or more data-storage devices and executed using one or more processors of a management server computer of a distributed computing system to classify and troubleshoot problems in information technology (“IT”) systems or services, the method comprising:
generating an alert when real-time key performance indicator (“KPI”) data used to monitor an IT system or service violates a KPI threshold, the KPI threshold violation indicates a problem in the IT system or service;
determining a real-time event-type distribution from event messages generated by event sources associated with the IT system or service;
comparing the real-time event-type distribution with historical event-type distributions recorded in a historical record of KPI aberrations in previously recorded KPI data of the IT system or service to identify a problem type of a historical event-type distribution closest to the real-time event-type distribution; and
when a problem type is identified, determining remedial action associated with the problem type that when executed remedies the problem identified by the problem type. 2. The method of claim 1 further comprises:
determining start times of each KPI threshold violation in the previously recorded KPI data;
identifying event messages generated by the event sources in time windows that begin at the start times;
determining a historical event-type distribution for the event messages in each of the time windows; and
recording a problem type and remedial action for each historical event-type distribution in the historical record of KPI aberrations. 3. The method of claim 2 further comprises:
averaging two or more historical event-type distributions with a same problem type in the historical record of KPI aberrations; and
replacing the two or more historical event-type distributions in the historical record of KPI aberrations with the problem type and remedial action and the average of the two or more historical event-type distributions. 4. The method of claim 2 further comprises:
computing a distance between each pair of historical event-type distributions with a same problem type in the historical record of KPI aberrations;
determining an average distance of each historical event-type distribution to the other historical event-type distributions with the same problem type;
determining a minimum average distance of the average distances; and
replacing the historical event-type distributions with the same problem type in the historical record of KPI aberrations with the problem type and remedial action of the historical event-type distributions with minimum average distance to the other historical event-type distributions. 5. The method of claim 1 wherein determining the real-time event-type distribution comprises:
determining a start time of the threshold violation in the real-time KPI data;
identifying event messages generated by the event sources in a time window that begins at the start time; and
computing the real-time event-type distribution from the event messages in the time window. 6. The method of claim 1 wherein comparing the real-time event-type distribution with the historical event-type distributions comprises:
computing a distance between the real-time event-type distribution and each historical event-type distribution recorded in the historical record of KPI aberrations;
rank ordering the distances from smallest distance to largest distance;
when the smallest distance is less than an event-type distance threshold,
identifying a problem type of the historical event-type distribution with the smallest distance to the real-time event-type distribution, and
assigning the problem type to the real-time event-type distribution; and
when the smallest distance is greater than the distance threshold, generating an alert indicating that a problem type cannot be assigned to the real-time event-type distribution. 7. The method of claim 1 wherein comparing the real-time event-type distribution with the historical event-type distributions comprises:
computing a distance between the real-time event-type distribution and each historical event-type distribution recorded in the historical record of KPI aberrations;
rank ordering the distances from smallest distance to largest distance;
determining k-nearest neighbor historical event-type distributions to the real-time event-type distribution, the k-nearest neighbor historical event-type distributions having the k-smallest distances to the real-time even-type distribution; and
assigning a problem type of a largest number of historical event-type distributions of the k-nearest neighbor historical event-type distributions to the real-time event-type distribution. 8. The method of claim 1 wherein determining the remedial action to remedy the problem based on the problem type comprises identifying the remedial action associated with the problem type in the historical record of KPI aberrations, the remedial action including instructions that when executed remedy the problem. 9. A system to classify and troubleshoot problems in information technology systems and services, the system comprising:
one or more processors; one or more data-storage devices; and machine-readable instructions stored in the one or more data-storage devices that when executed using the one or more processors controls the system to carry out
generating an alert when real-time key performance indicator (“KPI”) data used to monitor an IT system or service violates a KPI threshold, the KPI threshold violation indicates a problem in the IT system or service;
determining a real-time event-type distribution from event messages generated by event sources associated with the IT system or service;
comparing the real-time event-type distribution with historical event-type distributions recorded in a historical record of KPI aberrations in previously recorded KPI data of the IT system or service to identify a problem type of a historical event-type distribution closest to the real-time event-type distribution; and
when a problem type is identified, determining remedial action associated with the problem type that when executed remedies the problem identified by the problem type. 10. The system of claim 9 further comprises:
determining start times of each KPI threshold violation in the previously recorded KPI data;
identifying event messages generated by the event sources in time windows that begin at the start times;
determining a historical event-type distribution for the event messages in each of the time windows; and
recording a problem type and remedial action for each historical event-type distribution in the historical record of KPI aberrations. 11. The system of claim 10 further comprises:
averaging two or more historical event-type distributions with a same problem type in the historical record of KPI aberrations; and
replacing the two or more historical event-type distributions in the historical record of KPI aberrations with the problem type and remedial action and the average of the two or more historical event-type distributions. 12. The system of claim 10 further comprises:
computing a distance between each pair of historical event-type distributions with a same problem type in the historical record of KPI aberrations;
determining an average distance of each historical event-type distribution to the other historical event-type distributions with the same problem type;
determining a minimum average distance of the average distances; and
replacing the historical event-type distributions with the same problem type in the historical record of KPI aberrations with the problem type and remedial action of the historical event-type distributions with minimum average distance to the other historical event-type distributions. 13. The system of claim 9 wherein determining the real-time event-type distribution comprises:
determining a start time of the threshold violation in the real-time KPI data;
identifying event messages generated by the event sources in a time window that begins at the start time; and
computing the real-time event-type distribution from the event messages in the time window. 14. The system of claim 9 wherein comparing the real-time event-type distribution with the historical event-type distributions comprises:
computing a distance between the real-time event-type distribution and each historical event-type distribution recorded in the historical record of KPI aberrations;
rank ordering the distances from smallest distance to largest distance;
when the smallest distance is less than an event-type distance threshold,
identifying a problem type of the historical event-type distribution with the smallest distance to the real-time event-type distribution, and
assigning the problem type to the real-time event-type distribution; and
when the smallest distance is greater than the distance threshold, generating an alert indicating that a problem type cannot be assigned to the real-time event-type distribution. 15. The system of claim 9 wherein comparing the real-time event-type distribution with the historical event-type distributions comprises:
computing a distance between the real-time event-type distribution and each historical event-type distribution recorded in the historical record of KPI aberrations;
rank ordering the distances from smallest distance to largest distance;
determining k-nearest neighbor historical event-type distributions to the real-time event-type distribution, the k-nearest neighbor historical event-type distributions having the k-smallest distances to the real-time even-type distribution; and
assigning a problem type of a largest number of historical event-type distributions of the k-nearest neighbor historical event-type distributions to the real-time event-type distribution. 16. The system of claim 9 wherein determining the remedial action to remedy the problem based on the problem type comprises identifying the remedial action associated with the problem type in the historical record of KPI aberrations, the remedial action including instructions that when executed remedy the problem. 17. A non-transitory computer-readable medium encoded with machine-readable instructions that implement a method carried out by one or more processors of a computer system to perform the operations of
generating an alert when real-time key performance indicator (“KPI”) data used to monitor an IT system or service violates a KPI threshold, the KPI threshold violation indicates a problem in the IT system or service; determining a real-time event-type distribution from event messages generated by event sources associated with the IT system or service; comparing the real-time event-type distribution with historical event-type distributions recorded in a historical record of KPI aberrations in previously recorded KPI data of the IT system or service to identify a problem type of a historical event-type distribution closest to the real-time event-type distribution; and when a problem type is identified, determining remedial action associated with the problem type that when executed remedies the problem identified by the problem type. 18. The medium of claim 1 further comprises:
determining start times of each KPI threshold violation in the previously recorded KPI data;
identifying event messages generated by the event sources in time windows that begin at the start times;
determining a historical event-type distribution for the event messages in each of the time windows; and
recording a problem type and remedial action for each historical event-type distribution in the historical record of KPI aberrations. 19. The medium of claim 18 further comprises:
averaging two or more historical event-type distributions with a same problem type in the historical record of KPI aberrations; and
replacing the two or more historical event-type distributions in the historical record of KPI aberrations with the problem type and remedial action and the average of the two or more historical event-type distributions. 20. The medium of claim 18 further comprises:
computing a distance between each pair of historical event-type distributions with a same problem type in the historical record of KPI aberrations;
determining an average distance of each historical event-type distribution to the other historical event-type distributions with the same problem type;
determining a minimum average distance of the average distances; and
replacing the historical event-type distributions with the same problem type in the historical record of KPI aberrations with the problem type and remedial action of the historical event-type distributions with minimum average distance to the other historical event-type distributions. 21. The medium of claim 17 wherein determining the real-time event-type distribution comprises:
determining a start time of the threshold violation in the real-time KPI data;
identifying event messages generated by the event sources in a time window that begins at the start time; and
computing the real-time event-type distribution from the event messages in the time window. 22. The medium of claim 17 wherein comparing the real-time event-type distribution with the historical event-type distributions comprises:
computing a distance between the real-time event-type distribution and each historical event-type distribution recorded in the historical record of KPI aberrations;
rank ordering the distances from smallest distance to largest distance;
when the smallest distance is less than an event-type distance threshold,
identifying a problem type of the historical event-type distribution with the smallest distance to the real-time event-type distribution, and
assigning the problem type to the real-time event-type distribution; and
when the smallest distance is greater than the distance threshold, generating an alert indicating that a problem type cannot be assigned to the real-time event-type distribution. 23. The medium of claim 17 wherein comparing the real-time event-type distribution with the historical event-type distributions comprises:
computing a distance between the real-time event-type distribution and each historical event-type distribution recorded in the historical record of KPI aberrations;
rank ordering the distances from smallest distance to largest distance;
determining k-nearest neighbor historical event-type distributions to the real-time event-type distribution, the k-nearest neighbor historical event-type distributions having the k-smallest distances to the real-time even-type distribution; and
assigning a problem type of a largest number of historical event-type distributions of the k-nearest neighbor historical event-type distributions to the real-time event-type distribution. 24. The medium of claim 17 wherein determining the remedial action to remedy the problem based on the problem type comprises identifying the remedial action associated with the problem type in the historical record of KPI aberrations, the remedial action including instructions that when executed remedy the problem. | Automated computational methods and systems to classify and troubleshoot problems in information technology (“IT”) systems or services provided by a distributed computing system are described. Each IT system of the distribution computing system or IT service provided by the distributed computing system has an associated key performance indicator (“KPI”) used to monitor performance of the IT system or service. When real-time KPI data violates a KPI threshold, a real-time event-type distribution is computed from event messages generated by event sources associated with the IT system or service following the threshold violation. The real-time event-type distribution is compared with historical event-type distributions recorded for the KPI data in order to identify the problem and execute remedial action to resolve the problem.1. An automated method stored in one or more data-storage devices and executed using one or more processors of a management server computer of a distributed computing system to classify and troubleshoot problems in information technology (“IT”) systems or services, the method comprising:
generating an alert when real-time key performance indicator (“KPI”) data used to monitor an IT system or service violates a KPI threshold, the KPI threshold violation indicates a problem in the IT system or service;
determining a real-time event-type distribution from event messages generated by event sources associated with the IT system or service;
comparing the real-time event-type distribution with historical event-type distributions recorded in a historical record of KPI aberrations in previously recorded KPI data of the IT system or service to identify a problem type of a historical event-type distribution closest to the real-time event-type distribution; and
when a problem type is identified, determining remedial action associated with the problem type that when executed remedies the problem identified by the problem type. 2. The method of claim 1 further comprises:
determining start times of each KPI threshold violation in the previously recorded KPI data;
identifying event messages generated by the event sources in time windows that begin at the start times;
determining a historical event-type distribution for the event messages in each of the time windows; and
recording a problem type and remedial action for each historical event-type distribution in the historical record of KPI aberrations. 3. The method of claim 2 further comprises:
averaging two or more historical event-type distributions with a same problem type in the historical record of KPI aberrations; and
replacing the two or more historical event-type distributions in the historical record of KPI aberrations with the problem type and remedial action and the average of the two or more historical event-type distributions. 4. The method of claim 2 further comprises:
computing a distance between each pair of historical event-type distributions with a same problem type in the historical record of KPI aberrations;
determining an average distance of each historical event-type distribution to the other historical event-type distributions with the same problem type;
determining a minimum average distance of the average distances; and
replacing the historical event-type distributions with the same problem type in the historical record of KPI aberrations with the problem type and remedial action of the historical event-type distributions with minimum average distance to the other historical event-type distributions. 5. The method of claim 1 wherein determining the real-time event-type distribution comprises:
determining a start time of the threshold violation in the real-time KPI data;
identifying event messages generated by the event sources in a time window that begins at the start time; and
computing the real-time event-type distribution from the event messages in the time window. 6. The method of claim 1 wherein comparing the real-time event-type distribution with the historical event-type distributions comprises:
computing a distance between the real-time event-type distribution and each historical event-type distribution recorded in the historical record of KPI aberrations;
rank ordering the distances from smallest distance to largest distance;
when the smallest distance is less than an event-type distance threshold,
identifying a problem type of the historical event-type distribution with the smallest distance to the real-time event-type distribution, and
assigning the problem type to the real-time event-type distribution; and
when the smallest distance is greater than the distance threshold, generating an alert indicating that a problem type cannot be assigned to the real-time event-type distribution. 7. The method of claim 1 wherein comparing the real-time event-type distribution with the historical event-type distributions comprises:
computing a distance between the real-time event-type distribution and each historical event-type distribution recorded in the historical record of KPI aberrations;
rank ordering the distances from smallest distance to largest distance;
determining k-nearest neighbor historical event-type distributions to the real-time event-type distribution, the k-nearest neighbor historical event-type distributions having the k-smallest distances to the real-time even-type distribution; and
assigning a problem type of a largest number of historical event-type distributions of the k-nearest neighbor historical event-type distributions to the real-time event-type distribution. 8. The method of claim 1 wherein determining the remedial action to remedy the problem based on the problem type comprises identifying the remedial action associated with the problem type in the historical record of KPI aberrations, the remedial action including instructions that when executed remedy the problem. 9. A system to classify and troubleshoot problems in information technology systems and services, the system comprising:
one or more processors; one or more data-storage devices; and machine-readable instructions stored in the one or more data-storage devices that when executed using the one or more processors controls the system to carry out
generating an alert when real-time key performance indicator (“KPI”) data used to monitor an IT system or service violates a KPI threshold, the KPI threshold violation indicates a problem in the IT system or service;
determining a real-time event-type distribution from event messages generated by event sources associated with the IT system or service;
comparing the real-time event-type distribution with historical event-type distributions recorded in a historical record of KPI aberrations in previously recorded KPI data of the IT system or service to identify a problem type of a historical event-type distribution closest to the real-time event-type distribution; and
when a problem type is identified, determining remedial action associated with the problem type that when executed remedies the problem identified by the problem type. 10. The system of claim 9 further comprises:
determining start times of each KPI threshold violation in the previously recorded KPI data;
identifying event messages generated by the event sources in time windows that begin at the start times;
determining a historical event-type distribution for the event messages in each of the time windows; and
recording a problem type and remedial action for each historical event-type distribution in the historical record of KPI aberrations. 11. The system of claim 10 further comprises:
averaging two or more historical event-type distributions with a same problem type in the historical record of KPI aberrations; and
replacing the two or more historical event-type distributions in the historical record of KPI aberrations with the problem type and remedial action and the average of the two or more historical event-type distributions. 12. The system of claim 10 further comprises:
computing a distance between each pair of historical event-type distributions with a same problem type in the historical record of KPI aberrations;
determining an average distance of each historical event-type distribution to the other historical event-type distributions with the same problem type;
determining a minimum average distance of the average distances; and
replacing the historical event-type distributions with the same problem type in the historical record of KPI aberrations with the problem type and remedial action of the historical event-type distributions with minimum average distance to the other historical event-type distributions. 13. The system of claim 9 wherein determining the real-time event-type distribution comprises:
determining a start time of the threshold violation in the real-time KPI data;
identifying event messages generated by the event sources in a time window that begins at the start time; and
computing the real-time event-type distribution from the event messages in the time window. 14. The system of claim 9 wherein comparing the real-time event-type distribution with the historical event-type distributions comprises:
computing a distance between the real-time event-type distribution and each historical event-type distribution recorded in the historical record of KPI aberrations;
rank ordering the distances from smallest distance to largest distance;
when the smallest distance is less than an event-type distance threshold,
identifying a problem type of the historical event-type distribution with the smallest distance to the real-time event-type distribution, and
assigning the problem type to the real-time event-type distribution; and
when the smallest distance is greater than the distance threshold, generating an alert indicating that a problem type cannot be assigned to the real-time event-type distribution. 15. The system of claim 9 wherein comparing the real-time event-type distribution with the historical event-type distributions comprises:
computing a distance between the real-time event-type distribution and each historical event-type distribution recorded in the historical record of KPI aberrations;
rank ordering the distances from smallest distance to largest distance;
determining k-nearest neighbor historical event-type distributions to the real-time event-type distribution, the k-nearest neighbor historical event-type distributions having the k-smallest distances to the real-time even-type distribution; and
assigning a problem type of a largest number of historical event-type distributions of the k-nearest neighbor historical event-type distributions to the real-time event-type distribution. 16. The system of claim 9 wherein determining the remedial action to remedy the problem based on the problem type comprises identifying the remedial action associated with the problem type in the historical record of KPI aberrations, the remedial action including instructions that when executed remedy the problem. 17. A non-transitory computer-readable medium encoded with machine-readable instructions that implement a method carried out by one or more processors of a computer system to perform the operations of
generating an alert when real-time key performance indicator (“KPI”) data used to monitor an IT system or service violates a KPI threshold, the KPI threshold violation indicates a problem in the IT system or service; determining a real-time event-type distribution from event messages generated by event sources associated with the IT system or service; comparing the real-time event-type distribution with historical event-type distributions recorded in a historical record of KPI aberrations in previously recorded KPI data of the IT system or service to identify a problem type of a historical event-type distribution closest to the real-time event-type distribution; and when a problem type is identified, determining remedial action associated with the problem type that when executed remedies the problem identified by the problem type. 18. The medium of claim 1 further comprises:
determining start times of each KPI threshold violation in the previously recorded KPI data;
identifying event messages generated by the event sources in time windows that begin at the start times;
determining a historical event-type distribution for the event messages in each of the time windows; and
recording a problem type and remedial action for each historical event-type distribution in the historical record of KPI aberrations. 19. The medium of claim 18 further comprises:
averaging two or more historical event-type distributions with a same problem type in the historical record of KPI aberrations; and
replacing the two or more historical event-type distributions in the historical record of KPI aberrations with the problem type and remedial action and the average of the two or more historical event-type distributions. 20. The medium of claim 18 further comprises:
computing a distance between each pair of historical event-type distributions with a same problem type in the historical record of KPI aberrations;
determining an average distance of each historical event-type distribution to the other historical event-type distributions with the same problem type;
determining a minimum average distance of the average distances; and
replacing the historical event-type distributions with the same problem type in the historical record of KPI aberrations with the problem type and remedial action of the historical event-type distributions with minimum average distance to the other historical event-type distributions. 21. The medium of claim 17 wherein determining the real-time event-type distribution comprises:
determining a start time of the threshold violation in the real-time KPI data;
identifying event messages generated by the event sources in a time window that begins at the start time; and
computing the real-time event-type distribution from the event messages in the time window. 22. The medium of claim 17 wherein comparing the real-time event-type distribution with the historical event-type distributions comprises:
computing a distance between the real-time event-type distribution and each historical event-type distribution recorded in the historical record of KPI aberrations;
rank ordering the distances from smallest distance to largest distance;
when the smallest distance is less than an event-type distance threshold,
identifying a problem type of the historical event-type distribution with the smallest distance to the real-time event-type distribution, and
assigning the problem type to the real-time event-type distribution; and
when the smallest distance is greater than the distance threshold, generating an alert indicating that a problem type cannot be assigned to the real-time event-type distribution. 23. The medium of claim 17 wherein comparing the real-time event-type distribution with the historical event-type distributions comprises:
computing a distance between the real-time event-type distribution and each historical event-type distribution recorded in the historical record of KPI aberrations;
rank ordering the distances from smallest distance to largest distance;
determining k-nearest neighbor historical event-type distributions to the real-time event-type distribution, the k-nearest neighbor historical event-type distributions having the k-smallest distances to the real-time even-type distribution; and
assigning a problem type of a largest number of historical event-type distributions of the k-nearest neighbor historical event-type distributions to the real-time event-type distribution. 24. The medium of claim 17 wherein determining the remedial action to remedy the problem based on the problem type comprises identifying the remedial action associated with the problem type in the historical record of KPI aberrations, the remedial action including instructions that when executed remedy the problem. | 2,100 |
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