source stringlengths 32 199 | text stringlengths 26 3k |
|---|---|
https://en.wikipedia.org/wiki/Binding | Binding may refer to:
Computing
Binding, associating a network socket with a local port number and IP address
Data binding, the technique of connecting two data elements together
UI data binding, linking an user interface element to an element of a domain model, such as a database field
XML data binding, representing XML document data using objects and classes
Key binding, or keyboard shortcut, mapping key combinations to software functionality
Language binding, a library providing a functional interface to second library in a different programming language
Name binding, the association of code or data with an identifier in a programming language
Late binding, name binding which is resolved at run-time rather than in pre-execution time
Science
Binding problem, a term for several problems in cognitive science and philosophy
Neural binding, synchronous activity of neurons and neuronal ensembles
Molecular binding, an attractive interaction between two molecules
Binding (linguistics), the distribution of pronouns etc. to identify syntactic relationships
People
Carly Binding (born 1978), New Zealand pop singer-songwriter
Karl Binding (1841–1920), German jurist
Lee Binding (born 1975), graphic designer
Lothar Binding (born 1950), German politician
Rudolf G. Binding (1867–1938), German writer and supporter of Adolf Hitler
Textiles
Binding (knitting), a type of gather also known as a pullover stitch
Binding (sewing), a finish to a seam or hem
Binding knot, a knot used to keep objects together
Binding off, in knitting, a family of techniques for ending a column of stitches
Other uses
Binding and loosing, in the New Testament, both forbidding and permitting an action
Binding Brauerei, a brewery in Frankfurt, Germany
Binding precedent, a legal decision that must be applied or followed
Binding (woodworking), an inlaid edging, often used to reduce fluctuations in the wood's humidity
Bookbinding, the protective cover of a book and the art of its construction
Coil binding or spiral binding, is a commonly used book binding style for documents
Comb binding, cerlox or surelox binding, a method of binding pages into a book
Breast binding or chest binding, a wrapping to form a bra-like structure
Foot binding, a Chinese custom practiced on young girls from the 10th to early 20th centuries
Legally binding, enforceable by law
Ski binding, an attachment which anchors a ski boot to the ski
Snowboard binding, a device for connecting a foot to a snowboard
The Binding (2016 film), an American psychological thriller film
The Binding (2020 film), an Italian film
See also
Binding protein, a protein whose principal function is to associate with or carry another molecule
Binding neuron, a 1998 abstract mathematical model of the electrical activity of a neuron
Binding domain, a protein domain in a binding protein
Binding constant, an equilibrium constant associated with the reaction of receptor and ligand molecules
Binding energy, th |
https://en.wikipedia.org/wiki/Shor%27s%20algorithm | Shor's algorithm is a quantum algorithm for finding the prime factors of an integer. It was developed in 1994 by the American mathematician Peter Shor. It is one of the few known quantum algorithms with compelling potential applications and strong evidence of superpolynomial speedup compared to best known classical (that is, non-quantum) algorithms. On the other hand, factoring numbers of practical significance requires far more qubits than available in the near future. Another concern is that noise in quantum circuits may undermine results, requiring additional qubits for quantum error correction.
Shor proposed multiple similar algorithms solving the factoring problem, the discrete logarithm problem, and the period finding problem. "Shor's algorithm" usually refers to his algorithm solving factoring, but may also refer to each of the three. The discrete logarithm algorithm and the factoring algorithm are instances of the period finding algorithm, and all three are instances of the hidden subgroup problem.
On a quantum computer, to factor an integer , Shor's algorithm runs in polynomial time, meaning the time taken is polynomial in , the size of the integer given as input. Specifically, it takes quantum gates of order using fast multiplication, or even utilizing the asymptotically fastest multiplication algorithm currently known due to Harvey and Van Der Hoven, thus demonstrating that the integer factorization problem can be efficiently solved on a quantum computer and is consequently in the complexity class BQP. This is significantly faster than the most efficient known classical factoring algorithm, the general number field sieve, which works in sub-exponential time: .
Feasibility and impact
If a quantum computer with a sufficient number of qubits could operate without succumbing to quantum noise and other quantum-decoherence phenomena, then Shor's algorithm could be used to break public-key cryptography schemes, such as
The RSA scheme
The Finite Field Diffie-Hellman key exchange
The Elliptic Curve Diffie-Hellman key exchange
RSA is based on the assumption that factoring large integers is computationally intractable. As far as is known, this assumption is valid for classical (non-quantum) computers; no classical algorithm is known that can factor integers in polynomial time. However, Shor's algorithm shows that factoring integers is efficient on an ideal quantum computer, so it may be feasible to defeat RSA by constructing a large quantum computer. It was also a powerful motivator for the design and construction of quantum computers, and for the study of new quantum-computer algorithms. It has also facilitated research on new cryptosystems that are secure from quantum computers, collectively called post-quantum cryptography.
Physical implementation
Given the high error rates of contemporary quantum computers and too few qubits to use quantum error correction, laboratory demonstrations obtain correct results only in a fraction of a |
https://en.wikipedia.org/wiki/Java%20Naming%20and%20Directory%20Interface | The Java Naming and Directory Interface (JNDI) is a Java API for a directory service that allows Java software clients to discover and look up data and resources (in the form of Java objects) via a name. Like all Java APIs that interface with host systems, JNDI is independent of the underlying implementation. Additionally, it specifies a service provider interface (SPI) that allows directory service implementations to be plugged into the framework. The information looked up via JNDI may be supplied by a server, a flat file, or a database; the choice is up to the implementation used.
Typical uses of JNDI include:
connecting a Java application to an external directory service (such as an address database or an LDAP server)
allowing a Java Servlet to look up configuration information provided by the hosting web container
Background
The Java RMI and Java EE APIs use the JNDI API to look up objects in a network.
The API provides:
a mechanism to bind an object to a name
a directory-lookup interface that allows general queries
an event interface that allows clients to determine when directory entries have been modified
LDAP extensions to support the additional capabilities of an LDAP service
The SPI portion allows support for practically any kind of naming or directory service, including:
LDAP
DNS
NIS
CORBA name service
file system
Sun Microsystems first released the JNDI specification on March 10, 1997. , the current version is JNDI 1.2.
Basic lookup
JNDI (Java Naming and Directory Interface) organizes its names into a hierarchy. A name can be any string such as "com.example.ejb.MyBean". A name can also be an object that implements the Name interface; however, a string is the most common way to name an object. A name is bound to an object in the directory by storing either the object or a reference to the object in the directory service identified by the name.
The JNDI API defines a context that specifies where to look for an object. The initial context is typically used as a starting point.
In the simplest case, an initial context must be created using the specific implementation and extra parameters required by the implementation. The initial context will be used to look up a name. The initial context is analogous to the root or top of a directory tree for a file system. Below is an example of creating an initial context:
Hashtable contextArgs = new Hashtable<String, String>();
// First you must specify the context factory.
// This is how you choose between jboss implementation
// vs. an implementation from Sun or other vendors.
contextArgs.put( Context.INITIAL_CONTEXT_FACTORY, "com.jndiprovider.TheirContextFactory" );
// The next argument is the URL specifying where the data store is:
contextArgs.put( Context.PROVIDER_URL, "jndiprovider-database" );
// (You may also have to provide security credentials)
// Next you create the initial context
Context myCurrentContext = new InitialContext(contextArgs);
A context is then us |
https://en.wikipedia.org/wiki/Speech%20synthesis | Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware products. A text-to-speech (TTS) system converts normal language text into speech; other systems render symbolic linguistic representations like phonetic transcriptions into speech. The reverse process is speech recognition.
Synthesized speech can be created by concatenating pieces of recorded speech that are stored in a database. Systems differ in the size of the stored speech units; a system that stores phones or diphones provides the largest output range, but may lack clarity. For specific usage domains, the storage of entire words or sentences allows for high-quality output. Alternatively, a synthesizer can incorporate a model of the vocal tract and other human voice characteristics to create a completely "synthetic" voice output.
The quality of a speech synthesizer is judged by its similarity to the human voice and by its ability to be understood clearly. An intelligible text-to-speech program allows people with visual impairments or reading disabilities to listen to written words on a home computer. Many computer operating systems have included speech synthesizers since the early 1990s.
A text-to-speech system (or "engine") is composed of two parts: a front-end and a back-end. The front-end has two major tasks. First, it converts raw text containing symbols like numbers and abbreviations into the equivalent of written-out words. This process is often called text normalization, pre-processing, or tokenization. The front-end then assigns phonetic transcriptions to each word, and divides and marks the text into prosodic units, like phrases, clauses, and sentences. The process of assigning phonetic transcriptions to words is called text-to-phoneme or grapheme-to-phoneme conversion. Phonetic transcriptions and prosody information together make up the symbolic linguistic representation that is output by the front-end. The back-end—often referred to as the synthesizer—then converts the symbolic linguistic representation into sound. In certain systems, this part includes the computation of the target prosody (pitch contour, phoneme durations), which is then imposed on the output speech.
History
Long before the invention of electronic signal processing, some people tried to build machines to emulate human speech. Some early legends of the existence of "Brazen Heads" involved Pope Silvester II (d. 1003 AD), Albertus Magnus (1198–1280), and Roger Bacon (1214–1294).
In 1779 the German-Danish scientist Christian Gottlieb Kratzenstein won the first prize in a competition announced by the Russian Imperial Academy of Sciences and Arts for models he built of the human vocal tract that could produce the five long vowel sounds (in International Phonetic Alphabet notation: , , , and ). There followed the bellows-operated "acoustic-mechanical speech machine" of Wolfgang von |
https://en.wikipedia.org/wiki/Jakarta%20Messaging | The Jakarta Messaging API (formerly Java Message Service or JMS API) is a Java application programming interface (API) for message-oriented middleware. It provides generic messaging models, able to handle the producer–consumer problem, that can be used to facilitate the sending and receiving of messages between software systems. Jakarta Messaging is a part of Jakarta EE and was originally defined by a specification developed at Sun Microsystems before being guided by the Java Community Process.
General idea of messaging
Messaging is a form of loosely coupled distributed communication, where in this context the term 'communication' can be understood as an exchange of messages between software components. Message-oriented technologies attempt to relax tightly coupled communication (such as TCP network sockets, CORBA or RMI) by the introduction of an intermediary component. This approach allows software components to communicate with each other indirectly. Benefits of this include message senders not needing to have precise knowledge of their receivers.
The advantages of messaging include the ability to integrate heterogeneous platforms, reduce system bottlenecks, increase scalability, and respond more quickly to change.
Version history
JMS 1.0
JMS 1.0.1 (October 5, 1998)
JMS 1.0.1a (October 30, 1998)
JMS 1.0.2 (December 17, 1999)
JMS 1.0.2a (December 23, 1999)
JMS 1.0.2b (August 27, 2001)
JMS 1.1 (April 12, 2002)
JMS 2.0 (May 21, 2013)
JMS 2.0a (March 16, 2015)
JMS 2.0 is currently maintained under the Java Community Process as JSR 343.
JMS 3.0 is under early development as part of Jakarta EE.
Elements
The following are JMS elements:
JMS provider
An implementation of the JMS interface for message-oriented middleware (MOM). Providers are implemented as either a Java JMS implementation or an adapter to a non-Java MOM.
JMS client
An application or process that produces and/or receives messages.
JMS producer/publisher
A JMS client that creates and sends messages.
JMS consumer/subscriber
A JMS client that receives messages.
JMS message
An object that contains the data being transferred between JMS clients.
JMS queue
A staging area that contains messages that have been sent and are waiting to be read (by only one consumer). As the name queue suggests, the messages are delivered in the order sent. A JMS queue guarantees that each message is processed only once.
JMS topic
A distribution mechanism for publishing messages that are delivered to multiple subscribers.
Models
The JMS API supports two distinct models:
Point-to-point
Publish-and-subscribe
Point-to-point model
Under the point-to-point messaging system, messages are routed to individual consumers who maintain queues of incoming messages. This messaging type is built on the concept of message queues, senders, and receivers. Each message is addressed to a specific queue, and the receiving clients extract messages from the queues established to hold their messag |
https://en.wikipedia.org/wiki/Java%20Platform%2C%20Micro%20Edition | Java Platform, Micro Edition or Java ME is a computing platform for development and deployment of portable code for embedded and mobile devices (micro-controllers, sensors, gateways, mobile phones, personal digital assistants, TV set-top boxes, printers). Java ME was formerly known as Java 2 Platform, Micro Edition or J2ME. As of December 22, 2006, the Java ME source code is licensed under the GNU General Public License, and is released under the project name phoneME.
The platform uses the object-oriented Java programming language. It is part of the Java software-platform family. Java ME was designed by Sun Microsystems, acquired by Oracle Corporation in 2010; the platform replaced a similar technology, PersonalJava. Originally developed under the Java Community Process as JSR 68, the different flavors of Java ME have evolved in separate JSRs. Oracle provides a reference implementation of the specification, but has tended not to provide free binary implementations of its Java ME runtime environment for mobile devices, rather relying on third parties to provide their own. As of 2008, all Java ME platforms are currently restricted to JRE 1.3 features and use that version of the class file format (internally known as version 47.0). Should Oracle ever declare a new round of Java ME configuration versions that support the later class file formats and language features, such as those corresponding to JRE 1.5 or 1.6 (notably, generics), it will entail extra work on the part of all platform vendors to update their JREs.
Java ME devices implement a profile. The most common of these are the Mobile Information Device Profile aimed at mobile devices, such as cell phones, and the Personal Profile aimed at consumer products and embedded devices like set-top boxes and PDAs. Profiles are subsets of configurations, of which there are currently two: the Connected Limited Device Configuration (CLDC) and the Connected Device Configuration (CDC).
There are more than 2.1 billion Java ME enabled mobile phones and PDAs. It was popular in sub-$200 devices such as Nokia's Series 40. It was also used on the Bada operating system and on Symbian OS along with native software. Users of Windows CE, Windows Mobile, Maemo, MeeGo and Android can download Java ME for their respective environments ("proof-of-concept" for Android).
Connected Limited Device Configuration
The Connected Limited Device Configuration (CLDC) contains a strict subset of the Java-class libraries, and is the minimum amount needed for a Java virtual machine to operate. CLDC is basically used for classifying myriad devices into a fixed configuration.
A configuration provides the most basic set of libraries and virtual-machine features that must be present in each implementation of a J2ME environment. When coupled with one or more profiles, the Connected Limited Device Configuration gives developers a solid Java platform for creating applications for consumer and embedded devices.
The configuration is de |
https://en.wikipedia.org/wiki/Java%20Platform%2C%20Standard%20Edition | Java Platform, Standard Edition (Java SE) is a computing platform for development and deployment of portable code for desktop and server environments. Java SE was formerly known as Java 2 Platform, Standard Edition (J2SE).
The platform uses Java programming language and is part of the Java software-platform family. Java SE defines a range of general-purpose APIs—such as Java APIs for the Java Class Library—and also includes the Java Language Specification and the Java Virtual Machine Specification. OpenJDK is the official reference implementation since version 7.
Nomenclature, standards and specifications
The platform was known as Java 2 Platform, Standard Edition or J2SE from version 1.2, until the name was changed to Java Platform, Standard Edition or Java SE in version 1.5. The "SE" is used to distinguish the base platform from the Enterprise Edition (Java EE) and Micro Edition (Java ME) platforms. The "2" was originally intended to emphasize the major changes introduced in version 1.2, but was removed in version 1.6. The naming convention has been changed several times over the Java version history. Starting with J2SE 1.4 (Merlin), Java SE has been developed under the Java Community Process, which produces descriptions of proposed and final specifications for the Java platform called Java Specification Requests (JSR). JSR 59 was the umbrella specification for J2SE 1.4 and JSR 176 specified J2SE 5.0 (Tiger). Java SE 6 (Mustang) was released under JSR 270.
Java Platform, Enterprise Edition (Java EE) is a related specification that includes all the classes in Java SE, plus a number that are more useful to programs that run on servers as opposed to workstations.
Java Platform, Micro Edition (Java ME) is a related specification intended to provide a certified collection of Java APIs for the development of software for small, resource-constrained devices such as cell phones, PDAs and set-top boxes.
The Java Runtime Environment (JRE) and Java Development Kit (JDK) are the actual files downloaded and installed on a computer to run or develop Java programs, respectively.
General purpose packages
java.lang
The Java package contains fundamental classes and interfaces closely tied to the language and runtime system. This includes the root classes that form the class hierarchy, types tied to the language definition, basic exceptions, math functions, threading, security functions, as well as some information on the underlying native system. This package contains 22 of 32 Error classes provided in JDK 6.
The main classes and interfaces in java.lang are:
– the class that is the root of every class hierarchy.
– the base class for enumeration classes (as of J2SE 5.0).
– the class that is the root of the Java reflection system.
– the class that is the base class of the exception class hierarchy.
, , and – the base classes for each exception type.
– the class that allows operations on threads.
– the class for strings and string literals |
https://en.wikipedia.org/wiki/Ninety%E2%80%93ninety%20rule | In computer programming and software engineering, the ninety-ninety rule is a humorous aphorism that states:
This adds up to 180%, making a wry allusion to the notoriety of software development projects significantly over-running their schedules (see software development effort estimation). The anecdote expresses both the rough allocation of time to easy and hard portions of a programming undertaking, and the cause of the lateness of many projects in their failure to anticipate their difficult, often unpredictable, complexities. In short, it often takes both more time and more coding than expected to complete a project.
The rule is attributed to Tom Cargill of Bell Labs, and was made popular by Jon Bentley's September 1985 "Programming Pearls" column in Communications of the ACM, in which it was titled the "Rule of Credibility".
In some agile software projects, this rule also surfaces when a task is portrayed as "relatively done." This indicates a common scenario where planned work is completed but cannot be signed off, pending a single final activity which may not occur for a substantial amount of time.
See also
– the 80/20 rule
References
Adages
Computer humor
Software project management
Programming principles |
https://en.wikipedia.org/wiki/JSP | JSP may refer to:
Computing
Jackson structured programming
JavaServer Pages, server-side Java
Java stored procedure (SQL/JRT)
Organisations
The Japanese School in Perth
Jewish Settlement Police, an organization established in Mandatory Palestine in 1936
JSP Records, a record label
Politics
Japan Socialist Party, a political party existed from 1945 to 1996 in Japan
Jai Samaikyandhra Party, a political party in India
Jana Sena Party, a political party in India
Other uses
Japanese Surrendered Personnel
Jacketed, soft point, a soft-point bullet
Jesup station (Amtrak station code), a train station in Georgia, US
Joint Schools Project, a 1960s "New Maths" project for schools in West Africa and later in the British Caribbean
Joint Service Publication, a UK MoD document
The Joseph Smith Papers, the published volumes of all of Joseph Smith's writings
Joseph Smith Papyri, Egyptian papyrus fragments |
https://en.wikipedia.org/wiki/Comparison%20of%20Java%20and%20C%2B%2B | Java and C++ are two prominent object-oriented programming languages. By many language popularity metrics, the two languages have dominated object-oriented and high-performance software development for much of the 21st century, and are often directly compared and contrasted. Java's syntax was based on C/C++.
Design aims
The differences between the programming languages C++ and Java can be traced to their heritage, as they have different design goals.
C++ was designed for systems and applications programming (i.e. infrastructure programming), extending the procedural programming language C, which was designed for efficient execution. To C, C++ added support for object-oriented programming, exception handling, lifetime-based resource management (RAII), generic programming, template metaprogramming, and the C++ Standard Library which includes generic containers and algorithms (the Standard Template Library or STL), and many other general purpose facilities.
Java is a general-purpose, concurrent, class-based, object-oriented programming language that is designed to minimize implementation dependencies. It relies on a Java virtual machine to be secure and highly portable. It is bundled with an extensive library designed to provide abstraction of the underlying platform. Java is a statically typed object-oriented language that uses a syntax similar to (but incompatible with) C++. It includes a documentation system called Javadoc.
The different goals in the development of C++ and Java resulted in different principles and design trade-offs between the languages. The differences are as follows:
Language features
Syntax
Java syntax has a context-free grammar that can be parsed by a simple LALR parser. Parsing C++ is more complicated. For example, Foo<1>(3); is a sequence of comparisons if Foo is a variable, but creates an object if Foo is the name of a class template.
C++ allows namespace-level constants, variables, and functions. In Java, such entities must belong to some given type, and therefore must be defined inside a type definition, either a class or an interface.
In C++, objects are values, while in Java they are not. C++ uses value semantics by default, while Java always uses reference semantics. To opt for reference semantics in C++, either a pointer or a reference can be used.
In C++, it is possible to declare a pointer or reference to a const object in order to prevent client code from modifying it. Functions and methods can also guarantee that they will not modify the object pointed to by a pointer by using the "const" keyword. This enforces const-correctness.
In Java, the final keyword is similar to the const keyword in C++, but its usage is more limited. For the most part, const-correctness must rely on the semantics of the class' interface, i.e., it is not strongly enforced, except for public data members that are labeled final.
C++ supports goto statements, which may lead to spaghetti code programming. With the exception o |
https://en.wikipedia.org/wiki/Endianness | In computing, endianness is the order or sequence of bytes of a word of digital data in computer memory or data communication which is identified by describing the impact of the "first" bytes, meaning at the smallest address or sent first. Endianness is primarily expressed as big-endian (BE) or little-endian (LE). A big-endian system stores the most significant byte of a word at the smallest memory address and the least significant byte at the largest. A little-endian system, in contrast, stores the least-significant byte at the smallest address. Bi-endianness is a feature supported by numerous computer architectures that feature switchable endianness in data fetches and stores or for instruction fetches. Other orderings are generically called middle-endian or mixed-endian.
Endianness may also be used to describe the order in which the bits are transmitted over a communication channel, e.g., big-endian in a communications channel transmits the most significant bits first. Bit-endianness is seldom used in other contexts.
Etymology
Danny Cohen introduced the terms big-endian and little-endian into computer science for data ordering in an Internet Experiment Note published in 1980.
The adjective endian has its origin in the writings of 18th century Anglo-Irish writer Jonathan Swift. In the 1726 novel Gulliver's Travels, he portrays the conflict between sects of Lilliputians divided into those breaking the shell of a boiled egg from the big end or from the little end. As a boy, the grandfather of the emperor whom Gulliver met had cut his finger while opening an egg from the big end. The boy's father and emperor at the time published an imperial edict commanding all his subjects to break their eggs from the small end. The people resented the change, sparking six rebellions of "Big-Endians." Swift did not use the term Little-Endians in the work. Cohen makes the connection to Gulliver's Travels explicit in the appendix to his 1980 note.
The names and have sometimes been used for the same concept.
Overview
Computers store information in various-sized groups of binary bits. Each group is assigned a number, called its address, that the computer uses to access that data. On most modern computers, the smallest data group with an address is eight bits long and is called a byte. Larger groups comprise two or more bytes, for example, a 32-bit word contains four bytes. There are two possible ways a computer could number the individual bytes in a larger group, starting at either end. Both types of endianness are in widespread use in digital electronic engineering. The initial choice of endianness of a new design is often arbitrary, but later technology revisions and updates perpetuate the existing endianness to maintain backward compatibility.
Internally, any given computer will work equally well regardless of what endianness it uses since its hardware will consistently use the same endianness to both store and load its data. For this reason, program |
https://en.wikipedia.org/wiki/Interleaf | Interleaf, Inc., was a company that created computer software products for the technical publishing creation and distribution process. Founded in 1981, its initial product was the first commercial document processor that integrated text and graphics editing, producing WYSIWYG ("what you see is what you get") output at near-typeset quality. It also had early products in the document management, electronic publishing, and Web publishing spaces. Interleaf's "Active Documents" functionality, integrated into its text and graphics editing products in the early 1990s, was the first to give document creators programmatic access (via LISP) to virtually all of the document's elements, structures, and software capabilities.
Broadvision acquired Interleaf in January 2000. The latest version of the publishing software (i.e. TPS) is called QuickSilver.
Interleaf's headquarters was in Cambridge, Massachusetts, US, and later moved to Waltham, Massachusetts.
History
Interleaf was founded by David Boucher and Harry George in 1981. Boucher served as chief executive officer from 1981 until 1992; George served as chief financial officer. Earlier, both were among the founders of Kurzweil Computer Products. Other early personnel came from NBI and Wang Labs. The company initially produced "turnkey" systems, that is, combinations of hardware and software integrated by the company. It initially ran on workstations from Sun Microsystems and Apollo Computers, but later ported its software to workstations made by Digital Equipment Corporation, HP, IBM and SGI, and later still, to the Apple Macintosh II and the IBM Personal Computer.
Interleaf released its first product in 1985. Inspired by the Xerox Star and Apple Lisa, TPS (Technical Publishing Software) uniquely enabled authors to write their text and create technical graphics on a computer screen that showed what the page would look like when formatted and printed on a laser printer. This capability was so unusual in 1985 that the company's name referred to the "interleaving" of text and graphics. TPS was also noted for its ability to handle the sorts of long documents corporate technical publishing departments routinely created.
Interleaf had its initial public offering (IPO) in June 1986, raising $24.6 million.
In 1990, Interleaf moved from Cambridge, to Waltham.
The company was bought by Broadvision in 2000, which renamed its authoring products "Quicksilver". The availability of Quicksilver 3.0 was announced in March 2007. The availability of QuickSilver 3.5 was announced in May 2010. QuickSilver 3.7 was released in July 2014.
Conversion
There remain engineering companies and defense contractors that have their archives in the Interleaf/Quicksilver format, however in the 2000's it became increasingly difficult and expensive to maintain documents in that format, thus, established users of Quicksilver and the original Interleaf often seek to convert their documents to another format, usually Microsoft Word b |
https://en.wikipedia.org/wiki/Hemichordate | Hemichordata is a phylum which consists of triploblastic, enterocoelomate, and bilaterally symmetrical marine deuterostome animals, generally considered the sister group of the echinoderms. They appear in the Lower or Middle Cambrian and include two main classes: Enteropneusta (acorn worms), and Pterobranchia. A third class, Planctosphaeroidea, is known only from the larva of a single species, Planctosphaera pelagica. The class Graptolithina, formerly considered extinct, is now placed within the pterobranchs, represented by a single living genus Rhabdopleura.
Acorn worms are solitary worm-shaped organisms. They generally live in burrows (the earliest secreted tubes) and are deposit feeders, but some species are pharyngeal filter feeders, while the family Torquaratoridae are free living detritivores. Many are well known for their production and accumulation of various halogenated phenols and pyrroles. Pterobranchs are filter-feeders, mostly colonial, living in a collagenous tubular structure called a coenecium.
Anatomy
The body plan of hemichordates is characterized by a muscular organization. The anteroposterior axis is divided into three parts: the anterior prosome, the intermediate mesosome, and the posterior metasome.
The body of acorn worms is worm-shaped and divided into an anterior proboscis, an intermediate collar, and a posterior trunk. The proboscis is a muscular and ciliated organ used in locomotion and in the collection and transport of food particles. The mouth is located between the proboscis and the collar. The trunk is the longest part of the animal. It contains the pharynx, which is perforated with gill slits (or pharyngeal slits), the oesophagus, a long intestine, and a terminal anus. It also contains the gonads. A post-anal tail is present in juvenile member of the acorn worm family Harrimaniidae.
The prosome of pterobranchs is specialized into a muscular and ciliated cephalic shield used in locomotion and in secreting the coenecium. The mesosome extends into one pair (in the genus Rhabdopleura) or several pairs (in the genus Cephalodiscus) of tentaculated arms used in filter feeding. The metasome, or trunk, contains a looped digestive tract, gonads, and extends into a contractile stalk that connects individuals to the other members of the colony, produced by asexual budding. In the genus Cephalodiscus, asexually produced individuals stay attached to the contractile stalk of the parent individual until completing their development. In the genus Rhabdopleura, zooids are permanently connected to the rest of the colony via a common stolon system.
They have a diverticulum of the foregut called a stomochord, previously thought to be related to the chordate notochord, but this is most likely the result of convergent evolution rather than a homology. A hollow neural tube exists among some species (at least in early life), probably a primitive trait that they share with the common ancestor of chordata and the rest of the deuteros |
https://en.wikipedia.org/wiki/Java%20remote%20method%20invocation | In computing, the Java Remote Method Invocation (Java RMI) is a Java API that performs remote method invocation, the object-oriented equivalent of remote procedure calls (RPC), with support for direct transfer of serialized Java classes and distributed garbage-collection.
The original implementation depends on Java Virtual Machine (JVM) class-representation mechanisms and it thus only supports making calls from one JVM to another. The protocol underlying this Java-only implementation is known as Java Remote Method Protocol (JRMP). In order to support code running in a non-JVM context, programmers later developed a CORBA version.
Usage of the term RMI may denote solely the programming interface or may signify both the API and JRMP, IIOP, or another implementation, whereas the term RMI-IIOP (read: RMI over IIOP) specifically denotes the RMI interface delegating most of the functionality to the supporting CORBA implementation.
The basic idea of Java RMI, the distributed garbage-collection (DGC) protocol, and much of the architecture underlying the original Sun implementation, come from the "network objects" feature of Modula-3.
Generalized code
The programmers of the original RMI API generalized the code somewhat to support different implementations, such as a HTTP transport. Additionally, the ability to pass arguments "by value" was added to CORBA in order to be compatible with the RMI interface. Still, the RMI-IIOP and JRMP implementations do not have fully identical interfaces.
RMI functionality comes in the package , while most of Sun's implementation is located in the sun.rmi package. Note that with Java versions before Java 5.0 developers had to compile RMI stubs in a separate compilation step using rmic. Version 5.0 of Java and beyond no longer require this step.
Jini version
Jini offers a more advanced version of RMI in Java. It functions similarly but provides more advanced security, object discovery capabilities, and other mechanisms for distributed object applications.
Example
The following classes implement a simple client-server program using RMI that displays a message.
RmiServerIntf interface defines the interface that is used by the client and implemented by the server.
import java.rmi.Remote;
import java.rmi.RemoteException;
public interface RmiServerIntf extends Remote {
String getMessage() throws RemoteException;
}
RmiServer class listens to RMI requests and implements the interface which is used by the client to invoke remote methods.
import java.rmi.Naming;
import java.rmi.RemoteException;
import java.rmi.server.UnicastRemoteObject;
import java.rmi.registry.*;
public class RmiServer extends UnicastRemoteObject implements RmiServerIntf {
public static final String MESSAGE = "Hello World";
public RmiServer() throws RemoteException {
super(0); // required to avoid the 'rmic' step, see below
}
public String getMessage() {
return MESSAGE;
}
public static void main(String |
https://en.wikipedia.org/wiki/List%20of%20free%20and%20open-source%20software%20packages | This is a list of free and open-source software packages, computer software licensed under free software licenses and open-source licenses. Software that fits the Free Software Definition may be more appropriately called free software; the GNU project in particular objects to their works being referred to as open-source. For more information about the philosophical background for open-source software, see free software movement and Open Source Initiative. However, nearly all software meeting the Free Software Definition also meets the Open Source Definition and vice versa. A small fraction of the software that meets either definition is listed here. Some of the open-source applications are also the basis of commercial products, shown in the List of commercial open-source applications and services.
Artificial intelligence
General AI
OpenCog – A project that aims to build an artificial general intelligence (AGI) framework. OpenCog Prime is a specific set of interacting components designed to give rise to human-equivalent artificial general intelligence.
Computer vision
AForge.NET – computer vision, artificial intelligence and robotics library for the .NET framework
OpenCV – computer vision library in C++
Machine learning
See List of open-source machine learning software
See Data Mining below
See R programming language – packages of statistical learning and analysis tools
Planning
TREX – Reactive planning
Robotics
Robot Operating System (ROS)
Webots – Robot Simulator
YARP – Yet Another Robot Platform
Assistive technology
Speech (synthesis and recognition)
CMU Sphinx – Speech recognition software from Carnegie Mellon University
Emacspeak – Audio desktop
ESpeak – Compact software speech synthesizer for English and other languages
Festival Speech Synthesis System – General multilingual speech synthesis
Modular Audio Recognition Framework – Voice, audio, speech NLP processing
NonVisual Desktop Access – (NVDA) Screen reader, for Windows
Text2Speech – Lightweight, easy-to-use Text-To-Speech (TTS) Software
Other assistive technology
Dasher – Unique text input software
Gnopernicus – AT suite for GNOME 2
Virtual Magnifying Glass – A multi-platform screen magnification tool
CAD
FreeCAD – Parametric 3D CAD modeler with a focus on mechanical engineering, BIM, and product design.
LibreCAD – 2D CAD software using AutoCAD-like interface and file format.
SolveSpace - 2D and 3D CAD, constraint-based parametric modeler with simple mechanical simulation abilities.
BRL-CAD - a constructive solid geometry (CSG) solid modeling computer-aided design (CAD) system.
OpenSCAD – A scripting based 3D CAD software.
Open Cascade Technology (OCCT) - a CAD kernel for 3D CAD, CAM, CAE, etc.
Finite Element Analysis (FEA)
Gmsh - A three-dimensional finite element mesh generator with built-in pre- and post-processing facilities.
Electronic design automation (EDA)
Fritzing - a CAD software for the design of electronics hardware to build more permanent cir |
https://en.wikipedia.org/wiki/List%20of%20mail%20server%20software | This is a list of mail server software: mail transfer agents, mail delivery agents, and other computer software which provide e-mail.
Product statistics
All such figures are necessarily estimates because data about mail server share is difficult to obtain; there are few reliable primary sources—and no agreed methodologies for its collection.
Surveys probing Internet-exposed systems typically attempt to identify systems via their banner, or other identifying features; and report Postfix and exim as overwhelming leaders in March 2021, with greater than 92% share between them. While such methods are effective at identifying mail server share for receiving systems, most large-scale sending environments are not listening for traffic on the public internet and will not be counted using such methodologies.
SMTP
POP/IMAP
Mail filtering
Mail server packages
Mail-in-a-Box
iRedmail
Modoboa
Mailcow
Poste.io
docker-mailserver
Mailu
See also
Comparison of mail servers
Message transfer agent
References
Message transfer agents
Mail servers |
https://en.wikipedia.org/wiki/Metropolitan%20area%20network | A metropolitan area network (MAN) is a computer network that interconnects users with computer resources in a geographic region of the size of a metropolitan area. The term MAN is applied to the interconnection of local area networks (LANs) in a city into a single larger network which may then also offer efficient connection to a wide area network. The term is also used to describe the interconnection of several LANs in a metropolitan area through the use of point-to-point connections between them.
History
By 1999, local area networks (LANs) were well established and providing data communication in buildings and offices. For the interconnection of LANs within a city, businesses relied primarily on the public switched telephone network. But while the telephone network was able to support the packet-based exchange of data that the various LAN protocols implemented, the bandwidth of the telephone network was already under heavy demand from circuit-switched voice, and the telephone exchanges were ill-designed to cope with the traffic spikes that LANs tended to produce.
To interconnect local area networks more effectively, it was suggested that office buildings are connected using the single-mode optical fiber lines, which were by that time widely used in long-haul telephone trunks. Such dark fibre links were in some cases already installed on customer premises and telephone companies started to offer their dark fibre within their subscriber packages. Fibre optic metropolitan area networks were operated by telephone companies as private networks for their customers and did not necessarily have full integration with the public wide area network (WAN) through gateways.
Besides the larger companies that connected their offices across metropolitan areas, universities and research institutions also adopted dark fibre as their metropolitan area network backbone. In West Berlin the BERCOM project built up a multifunctional broadband communications system to connect the mainframe computers that publicly funded universities and research institutions in the city housed. The BERCOM MAN project could progress at speed because the Deutsche Bundespost had already installed hundreds of miles of fibre optic cable in West Berlin. Like other metropolitan dark fibre networks at the time, the dark fibre network in West Berlin had a star topology with a hub somewhere in the city centre. The backbone of the dedicated BERCOM MAN for universities and research institutions was an optical fibre double ring that used a high-speed slotted ring protocol developed by the GMD Research Centre for Innovative Computer Systems and Telephony. The BERCOM MAN backbone could thus support two times 280 Mbit/s data transfer.
The productive use of dense wavelength-division multiplexing (DWDM) provided another impetus for the development of metropolitan area networks in the 2000s. Long haul DWDM, with ranges from 0 to 3000+ km, had been developed so that companies that stored large amount |
https://en.wikipedia.org/wiki/X.25 | X.25 is an ITU-T standard protocol suite for packet-switched data communication in wide area networks (WAN). It was originally defined by the International Telegraph and Telephone Consultative Committee (CCITT, now ITU-T) in a series of drafts and finalized in a publication known as The Orange Book in 1976.
X.25 was preceded by the Arpanet Host and IMP protocols (1970-72) and developed concurrently with the Transmission Control Protocol (1974-1976). This makes it one of the oldest packet-switching communication protocols available; it was developed several years before the OSI Reference Model (1984). The protocol suite is designed as three conceptual layers, which correspond closely to the lower three layers of the seven-layer OSI model. It also supports functionality not found in the OSI network layer.
Networks using X.25 were popular during the late 1970s and 1980s with telecommunications companies and in financial transaction systems such as automated teller machines. An X.25 WAN consists of packet-switching exchange (PSE) nodes as the networking hardware, and leased lines, plain old telephone service connections, or ISDN connections as physical links. However, most users have moved to Internet Protocol (IP) systems instead. X.25 was used up to 2015 (e.g. by the credit card payment industry) and is still used by aviation, purchasable from telecoms companies. X.25 was also available in niche applications such as Retronet that allow vintage computers to use the Internet.
History
The CCITT (later ITU-T) Study Group VII began developing a standard for packet-switched data communication in the mid-1970s based upon a number of emerging data network projects. Participants in the design of X.25 included engineers from Canada, France, Japan, the UK, and the USA representing a mix of national PTTs (France, Japan, UK) and private operators (Canada, USA). In particular, the work of Rémi Després, contributed significantly to the standard. A few minor changes, which complemented the proposed specification, were accommodated to enable Larry Roberts to join the agreement. Various updates and additions were worked into the standard, eventually recorded in the ITU series of technical books describing the telecommunication systems. These books were published every fourth year with different-colored covers. The X.25 specification is part of the larger set of X-Series.
Publicly accessible X.25 networks, commonly called public data networks, were set up in many countries during the late 1970s and 1980s to lower the cost of accessing various online services. Examples include Iberpac, TRANSPAC, Compuserve, Tymnet, Telenet, Euronet, PSS, Datapac, Datanet 1 and AUSTPAC as well as the International Packet Switched Service. Their combined network had large global coverage during the 1980s and into the 1990s.
Beginning in the early 1990s, in North America, use of X.25 networks (predominated by Telenet and Tymnet) started to be replaced by Frame Relay services of |
https://en.wikipedia.org/wiki/Packet%20switching | In telecommunications, packet switching is a method of grouping data into packets that are transmitted over a digital network. Packets are made of a header and a payload. Data in the header is used by networking hardware to direct the packet to its destination, where the payload is extracted and used by an operating system, application software, or higher layer protocols. Packet switching is the primary basis for data communications in computer networks worldwide.
During the early 1960s, Polish-American engineer Paul Baran developed a concept he called "distributed adaptive message block switching", with the goal of providing a fault-tolerant, efficient routing method for telecommunication messages as part of a research program at the RAND Corporation, funded by the United States Department of Defense. His ideas contradicted then-established principles of pre-allocation of network bandwidth, exemplified by the development of telecommunications in the Bell System. The new concept found little resonance among network implementers until the independent work of British computer scientist Donald Davies at the National Physical Laboratory in 1965. Davies coined the modern term packet switching and inspired numerous packet switching networks in the decade following, including the incorporation of the concept into the design of the ARPANET in the United States and the CYCLADES network in France. The ARPANET and CYCLADES were the primary precursor networks of the modern Internet.
Concept
A simple definition of packet switching is:
Packet switching allows delivery of variable bit rate data streams, realized as sequences of packets, over a computer network which allocates transmission resources as needed using statistical multiplexing or dynamic bandwidth allocation techniques. As they traverse networking hardware, such as switches and routers, packets are received, buffered, queued, and retransmitted (stored and forwarded), resulting in variable latency and throughput depending on the link capacity and the traffic load on the network. Packets are normally forwarded by intermediate network nodes asynchronously using first-in, first-out buffering, but may be forwarded according to some scheduling discipline for fair queuing, traffic shaping, or for differentiated or guaranteed quality of service, such as weighted fair queuing or leaky bucket. Packet-based communication may be implemented with or without intermediate forwarding nodes (switches and routers). In case of a shared physical medium (such as radio or 10BASE5), the packets may be delivered according to a multiple access scheme.
Packet switching contrasts with another principal networking paradigm, circuit switching, a method which pre-allocates dedicated network bandwidth specifically for each communication session, each having a constant bit rate and latency between nodes. In cases of billable services, such as cellular communication services, circuit switching is characterized by a fee per un |
https://en.wikipedia.org/wiki/IPsec | In computing, Internet Protocol Security (IPsec) is a secure network protocol suite that authenticates and encrypts packets of data to provide secure encrypted communication between two computers over an Internet Protocol network. It is used in virtual private networks (VPNs).
IPsec includes protocols for establishing mutual authentication between agents at the beginning of a session and negotiation of cryptographic keys to use during the session. IPsec can protect data flows between a pair of hosts (host-to-host), between a pair of security gateways (network-to-network), or between a security gateway and a host (network-to-host).
IPsec uses cryptographic security services to protect communications over Internet Protocol (IP) networks. It supports network-level peer authentication, data origin authentication, data integrity, data confidentiality (encryption), and replay protection (protection from replay attacks).
The initial IPv4 suite was developed with few security provisions. As a part of the IPv4 enhancement, IPsec is a layer 3 OSI model or internet layer end-to-end security scheme. In contrast, while some other Internet security systems in widespread use operate above the network layer, such as Transport Layer Security (TLS) that operates above the transport layer and Secure Shell (SSH) that operates at the application layer, IPsec can automatically secure applications at the internet layer.
History
Starting in the early 1970s, the Advanced Research Projects Agency sponsored a series of experimental ARPANET encryption devices, at first for native ARPANET packet encryption and subsequently for TCP/IP packet encryption; some of these were certified and fielded. From 1986 to 1991, the NSA sponsored the development of security protocols for the Internet under its Secure Data Network Systems (SDNS) program. This brought together various vendors including Motorola who produced a network encryption device in 1988. The work was openly published from about 1988 by NIST and, of these, Security Protocol at Layer 3 (SP3) would eventually morph into the ISO standard Network Layer Security Protocol (NLSP).
In 1992, the US Naval Research Laboratory (NRL) was funded by DARPA CSTO to implement IPv6 and to research and implement IP encryption in 4.4 BSD, supporting both SPARC and x86 CPU architectures. DARPA made its implementation freely available via MIT. Under NRL's DARPA-funded research effort, NRL developed the IETF standards-track specifications (RFC 1825 through RFC 1827) for IPsec. NRL's IPsec implementation was described in their paper in the 1996 USENIX Conference Proceedings. NRL's open-source IPsec implementation was made available online by MIT and became the basis for most initial commercial implementations.
The Internet Engineering Task Force (IETF) formed the IP Security Working Group in 1992 to standardize openly specified security extensions to IP, called IPsec. In 1995, the working group organized a few of the workshops with memb |
https://en.wikipedia.org/wiki/Open%20Shortest%20Path%20First | Open Shortest Path First (OSPF) is a routing protocol for Internet Protocol (IP) networks. It uses a link state routing (LSR) algorithm and falls into the group of interior gateway protocols (IGPs), operating within a single autonomous system (AS).
OSPF gathers link state information from available routers and constructs a topology map of the network. The topology is presented as a routing table to the internet layer for routing packets by their destination IP address. OSPF supports Internet Protocol version 4 (IPv4) and Internet Protocol version 6 (IPv6) networks and is widely used in large enterprise networks. IS-IS, another LSR-based protocol, is more common in large service provider networks.
Originally designed in the 1980s, OSPF version 2 is defined in RFC 2328 (1998). The updates for IPv6 are specified as OSPF version 3 in RFC 5340 (2008). OSPF supports the Classless Inter-Domain Routing (CIDR) addressing model.
Concepts
OSPF is an interior gateway protocol (IGP) for routing Internet Protocol (IP) packets within a single routing domain, such as an autonomous system. It gathers link state information from available routers and constructs a topology map of the network. The topology is presented as a routing table to the internet layer which routes packets based solely on their destination IP address.
OSPF detects changes in the topology, such as link failures, and converges on a new loop-free routing structure within seconds. It computes the shortest-path tree for each route using a method based on Dijkstra's algorithm. The OSPF routing policies for constructing a route table are governed by link metrics associated with each routing interface. Cost factors may be the distance of a router (round-trip time), data throughput of a link, or link availability and reliability, expressed as simple unitless numbers. This provides a dynamic process of traffic load balancing between routes of equal cost.
OSPF divides the network into routing areas to simplify administration and optimize traffic and resource utilization. Areas are identified by 32-bit numbers, expressed either simply in decimal, or often in the same octet-based dot-decimal notation used for IPv4 addresses. By convention, area 0 (zero), or 0.0.0.0, represents the core or backbone area of an OSPF network. While the identifications of other areas may be chosen at will, administrators often select the IP address of a main router in an area as the area identifier. Each additional area must have a connection to the OSPF backbone area. Such connections are maintained by an interconnecting router, known as an area border router (ABR). An ABR maintains separate link-state databases for each area it serves and maintains summarized routes for all areas in the network.
OSPF runs over IPv4 and IPv6, but does not use a transport protocol such as UDP or TCP. It encapsulates its data directly in IP packets with protocol number 89. This is in contrast to other routing protocols, such as the Routi |
https://en.wikipedia.org/wiki/Trams%20in%20Melbourne | Trams are a major form of public transport in Melbourne, the capital city of the state of Victoria, Australia. As of May 2017, the Melbourne tramway network consists of of double track, 493 trams, 24 routes, and 1,763 tram stops. The system is the largest operational urban tram network in the world. Trams are the second most used form of public transport in overall boardings in Melbourne after the commuter railway network, with a total of 206 million passenger trips in 2017–18.
Trams have operated continuously in Melbourne since 1885 (the horse tram line in Fairfield opened in 1884, but was at best an irregular service). Since then they have become a distinctive part of Melbourne's character and feature in tourism and travel advertising. Melbourne's cable tram system opened in 1885, and expanded to one of the largest in the world, with of double track. The first electric tram line opened in 1889, but closed only a few years later in 1896. In 1906 electric tram systems were opened in St Kilda and Essendon, marking the start of continuous operation of Melbourne's electric trams.
Victoria's public transport system was reorganised in 1983 and saw the Melbourne & Metropolitan Tramways Board absorbed into the Metropolitan Transit Authority, which was in turn absorbed by the Public Transport Corporation in 1989. The network has been operated under contract since the commencement of franchising, following the privatisation of the Public Transport Corporation in 1999. The current private operator contracted to run Melbourne's tram system is Keolis Downer, trading as Yarra Trams.
Ticketing, public information and patronage promotion are undertaken by Victoria's public transport body, Public Transport Victoria. The multi-modal integrated ticketing system, myki, currently operates across the tram network.
At some Melbourne intersections (most within the CBD), motor vehicles turning right are required to perform a hook turn, a manoeuvre designed to give trams priority. To further improve tram speeds on congested Melbourne streets, trams also have priority in road usage, with specially fitted traffic lights and exclusive lanes being provided either at all times or in peak times, as well as other measures.
History
Horse trams
Melbourne's first tram was a horse tram from Fairfield railway station to a real estate development in Thornbury; it opened on 20 December 1884, and was closed by 1890. Seven horse tramlines operated in Melbourne, three were built by the Melbourne Tramway & Omnibus Company (MTOC), while the other four were built by different private companies.
The MTOC's three lines fed their cable tram system: Victoria Bridge cable tram terminus to Kew (Boroondara Cemetery), opened in 1887 and closed in 1915 after its sale to Kew Council for conversion to a Prahran & Malvern Tramways Trust electric line; Hawthorn Bridge cable tram terminus to Auburn Road, via Burwood Road, Power Street and Riversdale Road, opened in 1890 and closed on 31 January |
https://en.wikipedia.org/wiki/Email%20client | An email client, email reader or, more formally, message user agent (MUA) or mail user agent is a computer program used to access and manage a user's email.
A web application which provides message management, composition, and reception functions may act as a web email client, and a piece of computer hardware or software whose primary or most visible role is to work as an email client may also use the term.
Retrieving messages from a mailbox
Like most client programs, an email client is only active when a user runs it. The common arrangement is for an email user (the client) to make an arrangement with a remote Mail Transfer Agent
(MTA) server for the receipt and storage of the client's emails. The MTA, using a suitable mail delivery agent (MDA), adds email messages to a client's storage as they arrive. The remote mail storage is referred to as the user's mailbox. The default setting on many Unix systems is for the mail server to store formatted messages in mbox, within the user's home directory. Of course, users of the system can log-in and run a mail client on the same computer that hosts their mailboxes; in which case, the server is not actually remote, other than in a generic sense.
Emails are stored in the user's mailbox on the remote server until the user's email client requests them to be downloaded to the user's computer, or can otherwise access the user's mailbox on the possibly remote server. The email client can be set up to connect to multiple mailboxes at the same time and to request the download of emails either automatically, such as at pre-set intervals, or the request can be manually initiated by the user.
A user's mailbox can be accessed in two dedicated ways. The Post Office Protocol (POP) allows the user to download messages one at a time and only deletes them from the server after they have been successfully saved on local storage. It is possible to leave messages on the server to permit another client to access them. However, there is no provision for flagging a specific message as seen, answered, or forwarded, thus POP is not convenient for users who access the same mail from different machines.
Alternatively, the Internet Message Access Protocol (IMAP) allows users to keep messages on the server, flagging them as appropriate. IMAP provides folders and sub-folders, which can be shared among different users with possibly different access rights. Typically, the Sent, Drafts, and Trash folders are created by default. IMAP features an idle extension for real-time updates, providing faster notification than polling, where long-lasting connections are feasible. See also the remote messages section below.
The JSON Meta Application Protocol (JMAP) is implemented using JSON APIs over HTTP and has been developed as an alternative to IMAP/SMTP.
In addition, the mailbox storage can be accessed directly by programs running on the server or via shared disks. Direct access can be more efficient but is less portable as it depends |
https://en.wikipedia.org/wiki/Ross%20Perot | Henry Ross Perot Sr. ( ; June 27, 1930 – July 9, 2019) was an American business magnate, politician, and philanthropist. He was the founder and chief executive officer of Electronic Data Systems and Perot Systems. He ran an independent campaign in the 1992 U.S. presidential election and a third-party campaign in the 1996 U.S. presidential election as the nominee of the Reform Party, which was formed by grassroots supporters of Perot's 1992 campaign. Although he failed to carry a single state in either election, both campaigns were among the strongest presidential showings by a third party or independent candidate in U.S. history.
Born and raised in Texarkana, Texas, Perot became a salesman for IBM after serving in the United States Navy. In 1962, he founded Electronic Data Systems, a data processing service company. In 1984, General Motors bought a controlling interest in the company for $2.4 billion ($ billion in ). Perot established Perot Systems in 1988 and was an angel investor for NeXT, a computer company founded by Steve Jobs after he left Apple. Perot also became heavily involved in the Vietnam War POW/MIA issue, arguing that hundreds of American servicemen were left behind in Southeast Asia after the Vietnam War. During the presidency of George H. W. Bush, Perot became increasingly active in politics and strongly opposed the Gulf War and ratification of the North American Free Trade Agreement.
In 1992, Perot announced his intention to run for president and advocated a balanced budget, an end to the outsourcing of jobs, and the enactment of electronic direct democracy. A June 1992 Gallup poll showed Perot leading a three-way race against President Bush and presumptive Democratic nominee Bill Clinton. Perot withdrew from the race in July, but re-entered the race in early October after he qualified for all 50 state ballots. He chose Admiral James Stockdale as his running mate and appeared in the 1992 debates with Bush and Clinton. In the election, Perot did not win any electoral votes, but won over 19.7 million votes for an 18.9% share of the popular vote. He won support from across the ideological and partisan spectrum, but performed best among self-described moderates. Perot ran for president again in 1996, establishing the Reform Party as a vehicle for his campaign. He won 8.4 percent of the popular vote against President Clinton and Republican nominee Bob Dole.
Perot did not seek public office again after 1996. He endorsed Republican George W. Bush over Reform nominee Pat Buchanan in the 2000 election and supported Republican Mitt Romney in 2008 and 2012. In 2009, Dell acquired Perot Systems for $3.9 billion ($ billion in ). According to Forbes, Perot was the 167th richest person in the United States as of 2016.
Early life, education, and military career
Ross Perot was born in Texarkana, Texas, the son of Lula May (née Ray) and Gabriel Ross Perot, a commodity broker specializing in cotton contracts. His patrilineal line traces back |
https://en.wikipedia.org/wiki/United%20States%20Naval%20Observatory | The United States Naval Observatory (USNO) is a scientific and military facility that produces geopositioning, navigation and timekeeping data for the United States Navy and the United States Department of Defense. Established in 1830 as the Depot of Charts and Instruments, it is one of the oldest scientific agencies in the United States, and remains the country's leading authority for astronomical and timing data for all purposes.
The observatory is located in Northwest Washington, D.C. at the northwestern end of Embassy Row. It is among the few pre-20th century astronomical observatories located in an urban area; initially located in Foggy Bottom near the city's center, it was relocated to its Northwest DC location in 1893 to escape light pollution.
The USNO has conducted significant scientific studies throughout its history, including measuring the speed of light, observing solar eclipses, and discovering the moons of Mars. Its achievements including providing data for the first radio time signals, constructing some of the earliest and most accurate telescopes of their kind, and helping develop universal time. The Naval Observatory performs radio VLBI-based positions of quasars for astrometry and geodesy with numerous global collaborators (IERS), in order to produce Earth orientation parameters and to realize the celestial reference system (ICRF).
Aside from its scientific mission, the Naval Observatory campus hosts the official residence of the vice president of the United States.
History
Early presidential astronomical interest
President John Quincy Adams, who in 1825 signed the bill for the creation of a national observatory just before leaving presidential office, had intended for it to be called the National Observatory.
The names "National Observatory" and "Naval Observatory" were both used for 10 years, until the Secretary of the Navy officially adopted the latter.
Adams had made protracted efforts to bring astronomy to a national level. He spent many nights at the observatory, watching and charting the stars, which had always been one of his interests.
Establishment as an optical equipment depot
Established by order of the United States Secretary of the Navy John Branch on 6 December 1830 as the Depot of Charts and Instruments, the Observatory rose from humble beginnings: Placed under the command of Lieutenant Louis M. Goldsborough, with an annual budget of $330; its primary function was the restoration, repair, and rating of navigational instruments.
Federal observatory
It was established as a national observatory in 1842 by federal law and a Congressional appropriation of $25,000. Lt. J.M. Gilliss was put in charge of "obtaining the instruments needed and books." Lt. Gilliss visited the principal observatories of Europe with the mission to purchase telescopes and other scientific devices, and books.
The observatory's primary mission was to care for the United States Navy's marine chronometers, charts, and other navigatio |
https://en.wikipedia.org/wiki/Gnuplot | gnuplot is a command-line and GUI program that can generate two- and three-dimensional plots of functions, data, and data fits. The program runs on all major computers and operating systems (Linux, Unix, Microsoft Windows, macOS, FreeDOS, and many others).
Originally released in 1986, its listed authors are Thomas Williams, Colin Kelley, Russell Lang, Dave Kotz, John Campbell, Gershon Elber, Alexander Woo "and many others." Despite its name, this software is not part of the GNU Project.
Features
gnuplot can produce output directly on screen, or in many formats of graphics files, including Portable Network Graphics (PNG), Encapsulated PostScript (EPS), Scalable Vector Graphics (SVG), JPEG and many others. It is also capable of producing LaTeX code that can be included directly in LaTeX documents, making use of LaTeX's fonts and powerful formula notation abilities. The program can be used both interactively and in batch mode using scripts.
gnuplot can read data in multiple formats, including ability to read data on the fly generated by other programs (piping), create multiple plots on one image, do 2D, 3D, contour plots, parametric equations, supports various linear and non-linear coordinate systems, projections, geographic and time data reading and presentation, box plots of various forms, histograms, labels, and other custom elements on the plot, including shapes, text and images, that can be set manually, computed by script or automatically from input data.
gnuplot also provides scripting capabilities, looping, functions, text processing, variables, macros, arbitrary pre-processing of input data (usually across columns), as well ability to perform non-linear multi-dimensional multi-set weighted data fitting (see Curve fitting and Levenberg–Marquardt algorithm).
The gnuplot core code is programmed in C. Modular subsystems for output via Qt, wxWidgets, and LaTeX/TikZ/ConTeXt are written in C++ and Lua.
The code below creates the graph to the right.
set title "Some Math Functions"
set xrange [-10:10]
set yrange [-2:2]
set zeroaxis
plot (x/4)**2, sin(x), 1/x
The name of this program was originally chosen to avoid conflicts with a program called "newplot", and was originally a compromise between "llamaplot" and "nplot".
Support of Epidemic daily and weekly formats in Version 5.4.2 is a result of pandemic coronavirus data needs.
Distribution terms
Despite gnuplot's name, it is not named after, part of or related to the GNU Project, nor does it use the GNU General Public License. It was named as part of a compromise by the original authors, punning on gnu (the animal) and newplot (a planned name that was discarded due to already being used).
Official source code to gnuplot is freely redistributable, but modified versions thereof are not. The gnuplot license allows instead distribution of patches against official releases, optionally accompanied by officially released source code. Binaries may be distributed along with the unmodified source |
https://en.wikipedia.org/wiki/Control-flow%20graph | In computer science, a control-flow graph (CFG) is a representation, using graph notation, of all paths that might be traversed through a program during its execution. The control-flow graph was discovered by Frances E. Allen, who noted that Reese T. Prosser used boolean connectivity matrices for flow analysis before.
The CFG is essential to many compiler optimizations and static-analysis tools.
Definition
In a control-flow graph each node in the graph represents a basic block, i.e. a straight-line piece of code without any jumps or jump targets; jump targets start a block, and jumps end a block. Directed edges are used to represent jumps in the control flow. There are, in most presentations, two specially designated blocks: the entry block, through which control enters into the flow graph, and the exit block, through which all control flow leaves.
Because of its construction procedure, in a CFG, every edge A→B has the property that:
outdegree(A) > 1 or indegree(B) > 1 (or both).
The CFG can thus be obtained, at least conceptually, by starting from the program's (full) flow graph—i.e. the graph in which every node represents an individual instruction—and performing an edge contraction for every edge that falsifies the predicate above, i.e. contracting every edge whose source has a single exit and whose destination has a single entry. This contraction-based algorithm is of no practical importance, except as a visualization aid for understanding the CFG construction, because the CFG can be more efficiently constructed directly from the program by scanning it for basic blocks.
Example
Consider the following fragment of code:
0: (A) t0 = read_num
1: (A) if t0 mod 2 == 0
2: (B) print t0 + " is even."
3: (B) goto 5
4: (C) print t0 + " is odd."
5: (D) end program
In the above, we have 4 basic blocks: A from 0 to 1, B from 2 to 3, C at 4 and D at 5. In particular, in this case, A is the "entry block", D the "exit block" and lines 4 and 5 are jump targets. A graph for this fragment has edges from A to B, A to C, B to D and C to D.
Reachability
Reachability is a graph property useful in optimization.
If a subgraph is not connected from the subgraph containing the entry block, that subgraph is unreachable during any execution, and so is unreachable code; under normal conditions it can be safely removed.
If the exit block is unreachable from the entry block, an infinite loop may exist. Not all infinite loops are detectable, see Halting problem. A halting order may also exist there.
Unreachable code and infinite loops are possible even if the programmer does not explicitly code them: optimizations like constant propagation and constant folding followed by jump threading can collapse multiple basic blocks into one, cause edges to be removed from a CFG, etc., thus possibly disconnecting parts of the graph.
Domination relationship
A block M dominates a block N if every path from the entry that reaches block N has to pass through block M. The e |
https://en.wikipedia.org/wiki/Linear%20programming | Linear programming (LP), also called linear optimization, is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships. Linear programming is a special case of mathematical programming (also known as mathematical optimization).
More formally, linear programming is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints. Its feasible region is a convex polytope, which is a set defined as the intersection of finitely many half spaces, each of which is defined by a linear inequality. Its objective function is a real-valued affine (linear) function defined on this polyhedron. A linear programming algorithm finds a point in the polytope where this function has the largest (or smallest) value if such a point exists.
Linear programs are problems that can be expressed in standard form as
Here the components of are the variables to be determined, and are given vectors, and is a given matrix. The function whose value is to be maximized ( in this case) is called the objective function. The constraints and specify a convex polytope over which the objective function is to be optimized.
Linear programming can be applied to various fields of study. It is widely used in mathematics and, to a lesser extent, in business, economics, and some engineering problems. Industries that use linear programming models include transportation, energy, telecommunications, and manufacturing. It has proven useful in modeling diverse types of problems in planning, routing, scheduling, assignment, and design.
History
The problem of solving a system of linear inequalities dates back at least as far as Fourier, who in 1827 published a method for solving them, and after whom the method of Fourier–Motzkin elimination is named.
In 1939 a linear programming formulation of a problem that is equivalent to the general linear programming problem was given by the Soviet mathematician and economist Leonid Kantorovich, who also proposed a method for solving it. It is a way he developed, during World War II, to plan expenditures and returns in order to reduce costs of the army and to increase losses imposed on the enemy. Kantorovich's work was initially neglected in the USSR. About the same time as Kantorovich, the Dutch-American economist T. C. Koopmans formulated classical economic problems as linear programs. Kantorovich and Koopmans later shared the 1975 Nobel prize in economics. In 1941, Frank Lauren Hitchcock also formulated transportation problems as linear programs and gave a solution very similar to the later simplex method. Hitchcock had died in 1957, and the Nobel prize is not awarded posthumously.
From 1946 to 1947 George B. Dantzig independently developed general linear programming formulation to use for planning problems in the US Air Force. In 1947, Dantzig also invented the simplex method that, f |
https://en.wikipedia.org/wiki/Network%20packet | In telecommunications and computer networking, a network packet is a formatted unit of data carried by a packet-switched network. A packet consists of control information and user data; the latter is also known as the payload. Control information provides data for delivering the payload (e.g., source and destination network addresses, error detection codes, or sequencing information). Typically, control information is found in packet headers and trailers.
In packet switching, the bandwidth of the transmission medium is shared between multiple communication sessions, in contrast to circuit switching, in which circuits are preallocated for the duration of one session and data is typically transmitted as a continuous bit stream.
Terminology
In the seven-layer OSI model of computer networking, packet strictly refers to a protocol data unit at layer 3, the network layer. A data unit at layer 2, the data link layer, is a frame. In layer 4, the transport layer, the data units are segments and datagrams. Thus, in the example of TCP/IP communication over Ethernet, a TCP segment is carried in one or more IP packets, which are each carried in one or more Ethernet frames.
Architecture
The basis of the packet concept is the postal letter: the header is like the envelope, the payload is the entire content inside the envelope, and the footer would be your signature at the bottom.
Network design can achieve two major results by using packets: error detection and multiple host addressing.
Framing
Communications protocols use various conventions for distinguishing the elements of a packet and for formatting the user data. For example, in Point-to-Point Protocol, the packet is formatted in 8-bit bytes, and special characters are used to delimit elements. Other protocols, like Ethernet, establish the start of the header and data elements by their location relative to the start of the packet. Some protocols format the information at a bit level instead of a byte level.
Contents
A packet may contain any of the following components:
Addresses
The routing of network packets requires two network addresses, the source address of the sending host, and the destination address of the receiving host.
Error detection and correction
Error detection and correction is performed at various layers in the protocol stack. Network packets may contain a checksum, parity bits or cyclic redundancy checks to detect errors that occur during transmission.
At the transmitter, the calculation is performed before the packet is sent. When received at the destination, the checksum is recalculated, and compared with the one in the packet. If discrepancies are found, the packet may be corrected or discarded. Any packet loss due to these discards is dealt with by the network protocol.
In some cases, modifications of the network packet may be necessary while routing, in which cases checksums are recalculated.
Hop limit
Under fault conditions, packets can end up traversing a closed cir |
https://en.wikipedia.org/wiki/Java%20XML | The Java programming language XML APIs developed by Sun Microsystems consist of the following separate computer-programming APIs:
Java API for XML Processing, or JAXP
Java API for XML Messaging, or JAXM
Jakarta XML RPC, or JAX-RPC — formerly Java API for XML Based RPC deprecated for Java API for XML Web Services
Jakarta XML Registries, or JAXR — formerly Java API for XML Registries
Jakarta XML Web Services, or JAX-WS — formerly Java API for XML Web Services
Jakarta RESTful Web Services, or JAX-RS — formerly Java API for RESTful Web Services
Java API for XQuery, or XQJ
Jakarta XML Binding, or JAXB — formerly Java Architecture for XML Binding (this was its official Sun name, even though it is an API, see )
Streaming XML processing, or StAX (compatible with JDK 1.4 and above, included in JDK 1.6)
Only the Java API for XML Processing (JAXP) is a required API in Enterprise Java Beans Specification 1.3.
A number of different open-source software packages implement these APIs:
Xerces — One of the original and most popular SAX and DOM parsers
Xalan — XSLT/XPath implementation, included in JDK 1.4 and above as the default transformer (XSLT 1.0)
Saxon — alternative highly specification-compliant XSLT/XPath/XQuery processor (supports both XSLT 1.0 and 2.0)
Woodstox — An open-source StAX and SAX (as of version 3.2) implementation
External links
StelsXML JDBC driver - JDBC driver for XML files.
Woodstox - Woodstox home page.
How To Schema Check Xml Via JAXB - Rob Austin
Java EE and web framework tutorials - Learning xml in java.
XML |
https://en.wikipedia.org/wiki/More | More may refer to:
Computing
MORE (application), outline software for Mac OS
more (command), a shell command
MORE protocol, a routing protocol
Missouri Research and Education Network
Music
Albums
More! (album), by Booka Shade, 2010
More (soundtrack), by Pink Floyd with music from the 1969 film
More... (Trace Adkins album), or the title song, 1999
More (Mary Alessi album), 2005
More (Beyoncé EP), 2014
More (Michael Bublé EP), 2005
More (Clarke-Boland Big Band album), 1968
More (Double Dagger album), 2009
More... (Montell Jordan album), 1996
More (Crystal Lewis album), 2001
More (Giuseppi Logan album), 1966
More (No Mercy album), 1998
More (No Trend album), 2001
More (Jeremy Riddle album), or the title song, 2017
More (Symphony Number One album), 2016
More (Tamia album), or the title song, 2004
More (Vitamin C album), 2001
More, by Mylon LeFevre, 1983
More, by Resin Dogs, 2007
Songs
"More" (Alex Alstone and Tom Glazer song), popularized by Perry Como, 1956
"More" (Alison Moyet song), 2003
"More" (J-Hope song), 2022
"More" (K/DA song), 2020
"More" (Matthew West song), 2003
"More" (Peaches song), 2009
"More" (The Sisters of Mercy song), 1990
"More" (Trace Adkins song), 2000
"More" (Usher song), 2010
"More" (Theme from Mondo Cane), from the 1963 film Mondo Cane
"More", by 5 Seconds of Summer from Youngblood, 2018
"More", by the Black Eyed Peas, performed on the Black Blue & You Tour, 2007
"More", by Doctor and the Medics from I Keep Thinking It's Tuesday, 1987
"More", by Grupa More, featuring Meri Cetinić, 1973
"More", by Halsey from Manic, 2020
"More", by Ice Prince from Fire of Zamani, 2012
"More", by Junkie XL from More More, 2007
"More", by Madonna from I'm Breathless, 1990
"More", by Nebula from Atomic Ritual, 2003
"More", by Selena Gomez & the Scene from Kiss & Tell, 2009
Bands
More (British band), a 1980s heavy metal band
More, a 1980s Yugoslav band featuring Doris Dragović
Places
More, Shropshire, a location in the United Kingdom
Möre, one of the original small lands of historical province Småland in southern Sweden
Radio, film, and television
More (1969 film), a film directed by Barbet Schroeder
More (1998 film), a short film by Mark Osborne
More (2017 film), a Turkish drama film
More FM, a New Zealand radio network
More Radio, an FM station in Swindon, North Wiltshire, UK
"More", an episode of The Good Doctor
Other uses
more, an English comparative determiner
More (surname), a family name, including a list of people with the surname
More!, a British women's fashion magazine
More (magazine), an American women's lifestyle magazine
More (cigarette), a cigarette brand marketed to women
More (store), a chain of supermarkets in India
Morè (clan), a Maratha clan of India
More (interjection), used in many Balkan languages
Mòoré language or Moré, a language spoken primarily in Burkina Faso by the Mossi
morebus, a bus brand operating around Bournemouth and Poole (England, UK)
Mayo |
https://en.wikipedia.org/wiki/Autonomous%20system | Autonomous system may refer to:
Autonomous system (Internet), a collection of IP networks and routers under the control of one entity
Autonomous system (mathematics), a system of ordinary differential equations which does not depend on the independent variable
Autonomous robot, robots which can perform desired tasks in unstructured environments without continuous human guidance
Autonomous underwater vehicle, a system that travels underwater without requiring input from an operator. |
https://en.wikipedia.org/wiki/C64%20%28disambiguation%29 | The Commodore 64, commonly known as just C64, is a home computer introduced by Commodore International.
C64 or C-64 may also refer to :
C64 (field gun), a late 19th-century field gun by Krupp
C-64 (Michigan county highway), a road in the United States
C-64 Norseman, an aircraft
Ruy Lopez's chess opening number in the Encyclopedia of Chess Openings
Renal cell carcinoma's code in the International Classification of Diseases 10th edition |
https://en.wikipedia.org/wiki/Java%20API%20for%20XML%20Processing | In computing, the Java API for XML Processing, or JAXP ( ), one of the Java XML Application programming interfaces, provides the capability of validating and parsing XML documents. It has three basic parsing interfaces:
the Document Object Model parsing interface or DOM interface
the Simple API for XML parsing interface or SAX interface
the Streaming API for XML or StAX interface (part of JDK 6; separate jar available for JDK 5)
In addition to the parsing interfaces, the API provides an XSLT interface to provide data and structural transformations on an XML document.
JAXP was developed under the Java Community Process as JSR 5 (JAXP 1.0), JSR 63 (JAXP 1.1 and 1.2), and JSR 206 (JAXP 1.3).
JAXP version 1.4.4 was released on September 3, 2010. JAXP 1.3 was declared end-of-life on February 12, 2008.
DOM interface
The DOM interface parses an entire XML document and constructs a complete in-memory representation of the document using the classes and modeling the concepts found in the Document Object Model Level 2 Core Specification.
The DOM parser is called a , as it builds an in-memory Document representation. The is created by the . The creates an instance - a tree structure containing nodes in the XML Document. Each tree node in the structure implements the interface. Among the many different types of tree nodes, each representing the type of data found in an XML document, the most important include:
element nodes that may have attributes
text nodes representing the text found between the start and end tags of a document element.
SAX interface
The creates the SAX parser, called the . Unlike the DOM parser, the SAX parser does not create an in-memory representation of the XML document and so runs faster and uses less memory. Instead, the SAX parser informs clients of the XML document structure by invoking callbacks, that is, by invoking methods on an instance provided to the parser. This way of accessing document is called Streaming XML.
The DefaultHandler class implements the , the , the , and the interfaces. Most clients will be interested in methods defined in the ContentHandler interface that are called when the SAX parser encounters the corresponding elements in the XML document. The most important methods in this interface are:
and methods that are called at the start and end of a XML document.
startElement() and endElement() methods that are called at the start and end of a document element.
characters() method that is called with the text data contents contained between the start and end tags of an XML document element.
Clients provide a subclass of the DefaultHandler that overrides these methods and processes the data. This may involve storing the data into a database or writing it out to a stream.
During parsing, the parser may need to access external documents. It is possible to store a local cache for frequently used documents using an XML Catalog.
This was introduced with Java 1.3 in May 2000.
StAX i |
https://en.wikipedia.org/wiki/Windows%20Media%20Player | Windows Media Player (WMP) is the first media player and media library application that Microsoft developed to play audio and video on personal computers. It has been a component of the Microsoft Windows operating system, including Windows 9x, Windows NT, Pocket PC, and Windows Mobile. Microsoft also released editions of Windows Media Player for classic Mac OS, , and Solaris, but has since discontinued them. Since 2022, it has been branded with the Legacy suffix to distinguish it from the new UWP-based Media Player introduced in Windows 11.
In addition to being a media player, the software has the ability to rip audio file from and copy to compact discs, burn recordable discs in Audio CD format or as data discs with playlists such as an MP3 CD, synchronize content with a digital audio player (MP3 player) or other mobile devices, play and stream media over the local network, and enable users to purchase or rent music from a number of online music stores. The default file formats are Windows Media Video (WMV), Windows Media Audio (WMA), and Advanced Systems Format (ASF), and its own XML based playlist format called Windows Playlist (WPL). The player is also able to utilize a digital rights management service in the form of Windows Media DRM.
Windows Media Player is a unique component, in that since 1999, each version of Windows came with two or more versions of it side-by-side. For example Media Player versions 5.1, 6.4, and 8 were all included in Windows XP. These versions of Windows also included several other media playback apps, namely ActiveMovie Control, CD Player, DVD Player, Windows Media Center, and Microsoft Movies & TV.
Windows Media Player 11 is the last out-of-band version of Media Player. It was made available for Windows XP and is included in Windows Vista and Windows Server 2008. Version 12 was released in 2009 along with Windows 7 and has not been made available for previous versions of Windows nor has it been updated ever since. Windows 8 bundled Windows Media Player 12 along two other media player apps, namely Xbox Video and Xbox Music. The latter was renamed Groove Music in Windows 10, and then finally Media Player in Windows 11, which has since been backported to Windows 10.
History
The first version of Windows Media Player appeared in 1991, when Windows 3.0 with Multimedia Extensions was released. Originally called Media Player, this component was included with "Multimedia PC"-compatible machines but not available for retail sale. It was capable of playing .mmm animation files, and could be extended to support other formats. It used MCI to handle media files. Being a component of Windows, Media Player shows the same version number as that of the version Windows with which it was included.
Microsoft continually produced new programs to play media files. In November of the following year, Video for Windows was introduced with the ability to play digital video files in an AVI container format, with codec support for RLE and |
https://en.wikipedia.org/wiki/Interstate%20Highway%20System | The Dwight D. Eisenhower National System of Interstate and Defense Highways, commonly known as the Interstate Highway System, the Eisenhower Interstate System, or simply the Interstate, is a network of controlled-access highways that forms part of the National Highway System in the United States. The system extends throughout the contiguous United States and has routes in Hawaii, Alaska, and Puerto Rico.
In the 20th century, the United States Congress began funding roadways through the Federal Aid Road Act of 1916, and started an effort to construct a national road grid with the passage of the Federal Aid Highway Act of 1921. In 1926, the United States Numbered Highway System was established, creating the first national road numbering system for cross-country travel. The roads were state-funded and maintained, and there were few national standards for road design. United States Numbered Highways ranged from two-lane country roads to multi-lane freeways. After Dwight D. Eisenhower became president in 1953, his administration developed a proposal for an interstate highway system, eventually resulting in the enactment of the Federal-Aid Highway Act of 1956.
Unlike the earlier United States Numbered Highway System, the Interstates were designed to be an all-freeway system, with nationally unified standards for construction and signage. While some older freeways were adopted into the system, most of the routes were completely new construction, greatly expanding the freeway network in the United States. Particularly in densely populated urban areas, these new freeways were often controversial as their building necessitated the destruction of many older, well-established neighborhoods; as a result of the many freeway revolts during the 1960s and 1970s, several planned Interstates were abandoned or re-routed to avoid urban cores.
Construction of the original Interstate Highway System was proclaimed complete in 1992, despite deviations from the original 1956 plan and several stretches that did not fully conform with federal standards. The construction of the Interstate Highway System cost approximately $114 billion (equivalent to $ in ). The system has continued to expand and grow as additional federal funding has provided for new routes to be added, and many future Interstate Highways are currently either being planned or under construction.
Though much of their construction was funded by the federal government, Interstate Highways are owned by the state in which they were built. With few exceptions, all Interstates must meet specific standards, such as having controlled access, physical barriers or median strips between lanes of oncoming traffic, breakdown lanes, avoiding at-grade intersections, no traffic lights and complying with federal traffic sign specifications. Interstate Highways use a numbering scheme in which primary Interstates are assigned one- or two-digit numbers, and shorter routes which branch off of longer ones are assigned three-di |
https://en.wikipedia.org/wiki/United%20States%20Numbered%20Highway%20System | The United States Numbered Highway System (often called U.S. Routes or U.S. Highways) is an integrated network of roads and highways numbered within a nationwide grid in the contiguous United States. As the designation and numbering of these highways were coordinated among the states, they are sometimes called Federal Highways, but the roadways were built and have always been maintained by state or local governments since their initial designation in 1926.
The route numbers and locations are coordinated by the American Association of State Highway and Transportation Officials (AASHTO). The only federal involvement in AASHTO is a nonvoting seat for the United States Department of Transportation. Generally, most north-to-south highways are odd-numbered, with the lowest numbers in the east and the highest in the west, while east-to-west highways are typically even-numbered, with the lowest numbers in the north, and the highest in the south, though the grid guidelines are not rigidly followed, and many exceptions exist. Major north–south routes generally have numbers ending in "1", while major east–west routes usually have numbers ending in "0". Three-digit numbered highways are generally spur routes of parent highways; for example, U.S. Route 264 (US 264) is a spur off US 64. Some divided routes, such as US 19E and US 19W, exist to provide two alignments for one route. Special routes, which can be labeled as alternate, bypass or business, depending on the intended use, provide a parallel routing to the mainline U.S. Highway.
Before the U.S. Routes were designated, auto trails designated by auto trail associations were the main means of marking roads through the United States. These were private organizations, and the system of road marking at the time was haphazard and not uniform. In 1925, the Joint Board on Interstate Highways, recommended by the American Association of State Highway Officials (AASHO), worked to form a national numbering system to rationalize the roads. After several meetings, a final report was approved by the U.S. Department of Agriculture in November 1925. After getting feedback from the states, they made several modifications; the U.S. Highway System was approved on November 11, 1926.
Expansion of the U.S. Highway System continued until 1956, when the Interstate Highway System was laid out and began construction under the administration of President Dwight D. Eisenhower. After the national implementation of the Interstate Highway System, many U.S. Routes that had been bypassed or overlaid with Interstate Highways were decommissioned and removed from the system. In some places, the U.S. Routes remain alongside the Interstates and serve as a means for interstate travelers to access local services and as secondary feeder roads or as important major arteries in their own right. In other places, where there are no nearby Interstate Highways, the U.S. Routes often remain as the most well-developed roads for long-distance trave |
https://en.wikipedia.org/wiki/ATRAC | Adaptive Transform Acoustic Coding (ATRAC) is a family of proprietary audio compression algorithms developed by Sony. MiniDisc was the first commercial product to incorporate ATRAC, in 1992. ATRAC allowed a relatively small disc like MiniDisc to have the same running time as CD while storing audio information with minimal perceptible loss in quality. Improvements to the codec in the form of ATRAC3, ATRAC3plus, and ATRAC Advanced Lossless followed in 1999, 2002, and 2006 respectively.
Files in ATRAC3 format originally had the extension, however in most cases the files would be stored in an OpenMG Audio container using the extension . Previously, files that were encrypted with OpenMG had the extension, which was replaced by starting in SonicStage v2.1. Encryption is no longer compulsory as of v3.2.
Other MiniDisc manufacturers such as Sharp and Panasonic also implemented their own versions of the ATRAC codec.
History
ATRAC was developed for Sony's MiniDisc format. ATRAC was updated with version 2, then version 3, version 4, version 4.5, and Type R and Type S.
The first major update was ATRAC3 (not to be confused with version 3 of original ATRAC) in 1999. ATRAC3 was used on MiniDisc as well as the Network Walkman and Vaio Music Clip. ATRAC3plus launched in 2003 for Hi-MD, but was also compatible with some PlayStation, VAIO and Xplod devices.
On 31 March 2008 Sony all but dropped the ATRAC-related codecs in the United States and Europe, and in their SonicStage powered Connect Music Store (Sony's equivalent of iTunes and iTunes Music Store). This was partly due to low adoption of the format, with a source claiming that 90% of European Walkman users did not use ATRAC. Walkman digital players outside Japan no longer worked with ATRAC after September 2007.
Until October 1, 2012, ATRAC was the only codec available to download music from mora until they transitioned to a DRM free model and began offering FLAC files the next year.
ATRAC9 was designed for PlayStation audio and debuted with the PlayStation Vita.
Bitrate quality
ATRAC's 292 kbit/s bitrate used on the original MiniDiscs was designed to be near to CD audio quality. Years later ATRAC was improved over earlier versions at similar bitrates. For comparison, CDs are encoded at 1411.2 kbit/s, and lossless encoders can encode most CDs below 1000 kbit/s, with further bitrate reduction for easier-to-encode content such as voice.
Performance
ATRAC algorithms were developed in close cooperation with LSI integrated circuit development engineers within Sony in order to deliver a product that could encode at high speeds and with minimal power consumption. This contrasts with other codecs developed on computers without regard for the constraints of portable hardware. This is reflected in the design of the ATRAC codecs, which emphasize processing smaller groups of samples at a time to save memory at the cost of compression efficiency and additional multiplies. These trade-offs are logical for DS |
https://en.wikipedia.org/wiki/MiniDisc | MiniDisc (MD) is an erasable magneto-optical disc-based data storage format offering a capacity of 60, 74, and later, 80 minutes of digitized audio.
Sony announced the MiniDisc in September 1992 and released it in November of that year for sale in Japan and in December in Europe, North America, and other countries. The music format was based on ATRAC audio data compression, Sony's own proprietary compression code. Its successor, Hi-MD, would later introduce the option of linear PCM digital recording to meet audio quality comparable to that of a compact disc. MiniDiscs were very popular in Japan and found moderate success in Europe. Although it was designed to succeed the cassette tape, it did not manage to supplant it globally.
By March 2011 Sony had sold 22 million MD players, but halted further development. Sony ceased manufacturing and sold the last of the players by March 2013.
Market history
In 1983, just a year after the introduction of the compact disc, Kees Schouhamer Immink and Joseph Braat presented the first experiments with erasable magneto-optical compact discs during the 73rd AES Convention in Eindhoven. It took almost 10 years, however, before their idea was commercialized.
Sony's MiniDisc was one of two rival digital systems introduced in 1992 that were intended to replace the Philips Compact Cassette analog audio tape system: the other was the Digital Compact Cassette (DCC), created by Philips and Matsushita (now Panasonic). Sony had originally intended the Digital Audio Tape (DAT) to be the dominant home digital audio recording format, replacing the analog cassette. Because of technical delays, the DAT was not launched until 1989, and by then the U.S. dollar had fallen so far against the yen that the introductory DAT machine Sony had intended to market for about $400 in the late 1980s then had to retail for $800 or even $1,000 to break even, putting it out of reach of most users.
Relegating DAT to professional use, Sony set to work to come up with a simpler, more economical digital home format. By the time Sony came up with the MiniDisc in late 1992, Philips had introduced a competing system, DCC, on a magnetic tape cassette. This created marketing confusion very similar to the videocassette format war of the late 1970s and early 1980s. Sony licensed MD technology to other manufacturers, with JVC, Sharp, Pioneer, Panasonic and others producing their own MD products. However, non-Sony machines were not widely available in North America, and companies such as Technics and Radio Shack tended to promote DCC instead.
Despite having a loyal customer base largely of musicians and audio enthusiasts, the MiniDisc met with only limited success in the United States. It was very popular in Japan and parts of Asia, and relatively so in Europe during the 1990s and into the 2000s, but did not enjoy comparable sales success in other markets. Since then, recordable CDs, flash memory and HDD and solid-state-based digital audio players such |
https://en.wikipedia.org/wiki/DSP | DSP may refer to:
Computing
Digital signal processing, the mathematical manipulation of an information signal
Digital signal processor, a microprocessor designed for digital signal processing
Dynamic Reconfiguration port
Yamaha DSP-1, a proprietary digital signal processor
Demand-side platform, a system to facilitate the buying of online advertising
Education
Developmental social-pragmatic model, a developmental intervention for autistic spectrum disorders
Direct support professional, a specialist in education of the mentally disabled
Deutsche Schule Prag, a German international school in Prague, Czech Republic
Deutsche Schule Paris, now the Internationale Deutsche Schule Paris, a German international school in France
Deutsche Schule Pretoria, a German international school in Pretoria, South Africa
Military and police
Deputy Superintendent of Police, also known acronym as DySP Also known as DySP
Defense Standardization Program, in the U.S. military
Defense Support Program, operators of the U.S. Air Force's early-warning satellites
Delaware State Police
Disruptive solutions process in the U.S. Air National Guard
Special Presidential Division, a Zairean military unit
Music
Dark Sky Paradise, an album by Big Sean
Devi Sri Prasad (born 1979), south Indian film composer, lyricist, singer, and performer
Deathlike Silence Productions, a record label in Norway
DSP Media, a Korean entertainment company
Organizations
Politics
Democratic Left Party (Turkey) (Demokratik Sol Parti)
Democratic Socialist Party (Japan)
Democratic Socialist Party (Prabodh Chandra), India
Democratic Socialist Perspective (formerly Democratic Socialist Party), Australia
German State Party (Deutsche Staatspartei), a political party of the Weimar Republic period
German Socialist Party (Deutschsozialistische Partei), a far-right party founded after World War I
Other
Delta Sigma Phi, a social fraternity
Delta Sigma Pi, a co-ed business fraternity
Science and technology
Disodium phosphate
Dairy Science Park, a scientific organization in Peshawar, Pakistan
Desmoplakin, a human gene
Dynamin Superfamily Protein, a protein superfamily
Diarrhetic shellfish poisoning
Dual-specificity phosphatase
Downstream processing
Other
DSP (film), a 2022 Indian Tamil-language film
Decessit sine prole, in genealogy, a person who died without having children
Detroit-style pizza
Dyson Sphere Program, a 2021 science fiction PC video game
Designated Suppliers Program, an anti-sweatshop standard used in some US universities
Deutscher Spiele Preis, a board games award in Germany
Durgapur Steel Plant, in India
Devante Smith-Pelly (born 1992), hockey player
Delivery Service Partners, who deliver packages for Amazon (company)
Drone Service Provider |
https://en.wikipedia.org/wiki/MD%20Data | MD Data is a magneto-optical medium succeeding MiniDisc. Sony wanted it to replace floppy disks, but instead came the Zip drive, CD writers, and memory sticks and cards.
Overview
The technology has 140 MB of data storage, but it is slow and expensive. It is in products such as a still camera, a document scanner, and in late 1990s 4- and 8-track multitrack recording decks. Meant as a step up from the popular 4-track cassette-based studios, these recorders enjoyed a brief prominence before they were replaced by relatively affordable and far more flexible direct-to-hard drive recording on Windows and Macintosh based computers. The format lacks an affordable computer drive. Some examples of products that used the format are a few multitrack "portastudio"-style audio recorders such as Sony's MDM-X4 and Tascam's 564.
MD Data2
In 1997, Sony introduced the MD Data2 format at 650 MB. The only product that used the format was Sony's DCM-M1 camcorder (capable of still images and MPEG-2 video).
Hi-MD
Since 2004, Hi-MD allows 340MB or 1GB of any type of data to be stored on a Hi-MD formatted MiniDisc, succeeding MD Data and MD Data2.
Gallery
See also
MiniDisc
Hi-MD
References
External links
MiniDisc Data Product table
Optical computer storage
Computer-related introductions in 1993
Sony products |
https://en.wikipedia.org/wiki/DocBook | DocBook is a semantic markup language for technical documentation. It was originally intended for writing technical documents related to computer hardware and software, but it can be used for any other sort of documentation.
As a semantic language, DocBook enables its users to create document content in a presentation-neutral form that captures the logical structure of the content; that content can then be published in a variety of formats, including HTML, XHTML, EPUB, PDF, man pages, WebHelp and HTML Help, without requiring users to make any changes to the source. In other words, when a document is written in DocBook format it becomes easily portable into other formats, rather than needing to be rewritten.
Design
DocBook is an XML language. In its current version (5.x), DocBook's language is formally defined by a RELAX NG schema with integrated Schematron rules. (There are also W3C XML Schema+Schematron and Document Type Definition (DTD) versions of the schema available, but these are considered non-standard.)
As a semantic language, DocBook documents do not describe what their contents "look like", but rather the meaning of those contents. For example, rather than explaining how the abstract for an article might be visually formatted, DocBook simply says that a particular section is an abstract. It is up to an external processing tool or application to decide where on a page the abstract should go and what it should look like or whether or not it should be included in the final output at all.
DocBook provides a vast number of semantic element tags. They are divided into three broad categories, namely structural, block-level, and inline.
Structural tags specify broad characteristics of their contents. The book element, for example, specifies that its child elements represent the parts of a book. This includes a title, chapters, glossaries, appendices, and so on. DocBook's structural tags include, but are not limited to:
set: Titled collection of one or more books or articles, can be nested with other sets
book: Titled collection of chapters, articles, and/or parts, with optional glossaries, appendices, etc.
part: Titled collection of one or more chapters—can be nested with other parts, and may have special introductory text
article: Titled, unnumbered collection of block-level elements
chapter: Titled, numbered collection of block-level elements—chapters don't require explicit numbers, a chapter number is the number of previous chapter elements in the XML document plus 1
appendix: Contains text that represents an appendix
dedication: Text represents the dedication of the contained structural element
Structural elements can contain other structural elements. Structural elements are the only permitted top-level elements in a DocBook document.
Block-level tags are elements like paragraph, lists, etc. Not all these elements can directly contain text. Sequential block-level elements render one "after" another. After, in this case, can |
https://en.wikipedia.org/wiki/Friends%20of%20the%20Earth | Friends of the Earth International (FoEI) is an international network of grassroots environmental organizations in 73 countries. About half of the member groups call themselves "Friends of the Earth" in their own languages; the others use other names. The organization was founded in 1969 in San Francisco by David Brower, Donald Aitken and Gary Soucie after Brower's split with the Sierra Club because of the latter's positive approach to nuclear energy. The founding donation of $500,000 (in 2019 USD) was provided by Robert Orville Anderson, the owner of Atlantic Richfield oil company. It became an international network of organizations in 1971 with a meeting of representatives from four countries: U.S., Sweden, the UK and France.
FoEI currently has a secretariat (based in Amsterdam, Netherlands) which provides support for the network and its agreed major campaigns. The executive committee of elected representatives from national groups sets policy and oversees the work of the secretariat. In 2016, Uruguayan activist Karin Nansen was elected to serve as chair of the organization. Sri Lankan activist Hemantha Withanage has served as chair of FoEI since 2021.
Campaign issues
Friends of the Earth International is an international membership organisation, with members spread across the world. Its advocacy programs focus on environmental, economic and social issues, highlighting their political and human rights contexts.
As per its website, the current campaign priorities of Friends of the Earth International are: economic justice and resisting neoliberalism; forests and biodiversity; food sovereignty; and climate justice and energy. The campaign priorities of FOEI are set at its bi-annual general meeting. Additionally, FOEI also plans campaigns in other fields, such as waste and overcomsumption, international financial institutions, ecological debt, mining and extractive industries, and nuclear power. FOEI also supports campaigns from the regions or member groups, such as the one on the consumption and intensive production of meat (Meat Atlas) by Friends of the Earth Europe.
FOEI claims that it has been successful as it has eliminated billions in taxpayer subsidies to corporate polluters, reformed the World Bank to address environmental and human rights concerns, pushed the debate on global warming to pressure the U.S. and U.K. to attempt the best legislation possible, stopped more than 150 destructive dams and water projects worldwide, pressed and won landmark regulations of strip mines and oil tankers and banned international whaling. Its critics claim that the organization tries only to obtain media attention (as by releasing the song "Love Song to the Earth"), but does not stay with locals to actually solve complicated problems, and that it prevents development in developing countries. They have also been critical of its policy to accept high levels of funding from companies and charities related to oil and gas.
One of Friends of the Earth's m |
https://en.wikipedia.org/wiki/Xerox%20Network%20Systems | Xerox Network Systems (XNS) is a computer networking protocol suite developed by Xerox within the Xerox Network Systems Architecture. It provided general purpose network communications, internetwork routing and packet delivery, and higher level functions such as a reliable stream, and remote procedure calls. XNS predated and influenced the development of the Open Systems Interconnection (OSI) networking model, and was very influential in local area networking designs during the 1980s.
XNS was developed by the Xerox Systems Development Department in the early 1980s, who were charged with bringing Xerox PARC's research to market. XNS was based on the earlier (and equally influential) PARC Universal Packet (PUP) suite from the late 1970s. Some of the protocols in the XNS suite were lightly modified versions of the ones in the Pup suite. XNS added the concept of a network number, allowing larger networks to be constructed from multiple smaller ones, with routers controlling the flow of information between the networks.
The protocol suite specifications for XNS were placed in the public domain in 1977. This helped XNS become the canonical local area networking protocol, copied to various degrees by practically all networking systems in use into the 1990s. XNS was used unchanged by 3Com's 3+Share and Ungermann-Bass's Net/One. It was also used, with modifications, as the basis for Novell NetWare, and Banyan VINES. XNS was used as the basis for the AppleNet system, but this was never commercialized; a number of XNS's solutions to common problems were used in AppleNet's replacement, AppleTalk.
Description
Overall design
In comparison to the OSI model's 7 layers, XNS is a five-layer system, like the later Internet protocol suite.
The Physical and Data Link layers of the OSI model correspond to the Physical layer (layer 0) in XNS, which was designed to use the transport mechanism of the underlying hardware and did not separate the data link. Specifically, XNS's Physical layer is really the Ethernet local area network system, also being developed by Xerox at the same time, and a number of its design decisions reflect that fact. The system was designed to allow Ethernet to be replaced by some other system, but that was not defined by the protocol (nor had to be).
The primary part of XNS is its definition of the Internal Transport layer (layer 1), which corresponds to OSI's Network layer, and it is here that the primary internetworking protocol, IDP, is defined. XNS combined the OSI's Session and Transport layers into the single Interprocess Communications layer (layer 2). Layer 3 was Resource Control, similar to the OSI's Presentation.
Finally, on top of both models, is the Application layer, although these layers were not defined in the XNS standard.
Basic internetwork protocol
The main internetwork layer protocol is the Internet Datagram Protocol (IDP). IDP is a close descendant of Pup's internetwork protocol, and roughly corresponds to the Internet |
https://en.wikipedia.org/wiki/Hungarian%20notation | Hungarian notation is an identifier naming convention in computer programming in which the name of a variable or function indicates its intention or kind, or in some dialects, its type. The original Hungarian notation uses only intention or kind in its naming convention and is sometimes called Apps Hungarian as it became popular in the Microsoft Apps division in the development of Microsoft Office applications. When the Microsoft Windows division adopted the naming convention, they based it on the actual data type, and this convention became widely spread through the Windows API; this is sometimes called Systems Hungarian notation.
Hungarian notation was designed to be language-independent, and found its first major use with the BCPL programming language. Because BCPL has no data types other than the machine word, nothing in the language itself helps a programmer remember variables' types. Hungarian notation aims to remedy this by providing the programmer with explicit knowledge of each variable's data type.
In Hungarian notation, a variable name starts with a group of lower-case letters which are mnemonics for the type or purpose of that variable, followed by whatever name the programmer has chosen; this last part is sometimes distinguished as the given name. The first character of the given name can be capitalized to separate it from the type indicators (see also CamelCase). Otherwise the case of this character denotes scope.
History
The original Hungarian notation was invented by Charles Simonyi, a programmer who worked at Xerox PARC circa 1972–1981, and who later became Chief Architect at Microsoft. The name of the notation is a reference to Simonyi's nation of origin, and also, according to Andy Hertzfeld, because it made programs "look like they were written in some inscrutable foreign language". Hungarian people's names are "reversed" compared to most other European names; the family name precedes the given name. For example, the anglicized name "Charles Simonyi" in Hungarian was originally "Simonyi Károly". In the same way, the type name precedes the "given name" in Hungarian notation. The similar Smalltalk "type last" naming style (e.g. aPoint and lastPoint) was common at Xerox PARC during Simonyi's tenure there.
Simonyi's paper on the notation referred to prefixes used to indicate the "type" of information being stored. His proposal was largely concerned with decorating identifier names based upon the semantic information of what they store (in other words, the variable's purpose). Simonyi's notation came to be called Apps Hungarian, since the convention was used in the applications division of Microsoft. Systems Hungarian developed later in the Microsoft Windows development team. Apps Hungarian is not entirely distinct from what became known as Systems Hungarian, as some of Simonyi's suggested prefixes contain little or no semantic information (see below for examples).
Systems Hungarian vs. Apps Hungarian
Where Systems notation an |
https://en.wikipedia.org/wiki/Capi | Capi or CAPI may refer to:
Computing
Common Application Programmer's Interface, LispWorks Common Lisp GUI toolkit
Common ISDN Application Programming Interface, Common ISDN API
Computer-assisted personal interviewing, a surveying technique that uses a computer based questionnaire
Microsoft Cryptographic Application Programming Interface, an interface to a library of functions software developers can call upon for security and cryptography services
Coherent Accelerator Processor Interface, a bus technology introduced in IBM's POWER8.
People
Capi (footballer, born 1977), Jesús Capitán Prado, Spanish football midfielder
Capi (footballer, born 1979), Jesús Tablado Feito, Spanish football forward
Capi (footballer, born 1981), Manuel Borja Calvar Simón, Spanish football defender
Other uses
Cash Assistance Program for Immigrants, a service for immigrants in the US not eligible for Supplemental Security Income (SSI)
Capi, daily newspaper from Nagaland, India
See also
Cappi
Kapi (disambiguation) |
https://en.wikipedia.org/wiki/TLS | TLS may refer to:
Computing
Transport Layer Security, a cryptographic protocol for secure computer network communication
Thread level speculation, an optimisation on multiprocessor CPUs
Thread-local storage, a mechanism for allocating variables in computer science
Transparent LAN Service, a transparent data link connecting remote Ethernet networks
Media
Theaterlexikon der Schweiz, an encyclopedia about theatre in Switzerland
The Times Literary Supplement, a British weekly literary review
Town Life Stuff, one of The Sims 3 Stuff packs
Organisations
Telstra (ASX code), an Australian telecommunications and media company
Trans Link Systems B.V., a company delivering the OV-chipkaart system to public-transport operators in the Netherlands.
Transmitter Location Systems, a US satellite radio interference geolocation company
Education
The Lindsey School, a secondary school in Cleethorpes, North East Lincolnshire, England
Tallinn Law School, in Estonia
Torrey Life Science, a biology organization of the University of Connecticut, US
Trinity Law School, in Santa Ana, California, US
Trinity Lutheran School (disambiguation), several schools in the US
Tulane University Law School, in New Orleans, Louisiana, US
Science, medicine and technology
Thüringer Landessternwarte Tautenburg, the Karl Schwarzschild Observatory, in Tautenburg, Thuringia, Germany
Terrestrial laser scanning, a 3D laser scanning method
Total least squares, a statistical analysis
Translesion synthesis, a form of DNA repair
Transponder landing system, an airplane landing system
Tumor lysis syndrome, a group of metabolic complications that can occur after treatment of cancer
Tunable laser spectrometer, an instrument in the Mars rover suite Sample Analysis at Mars
Two-level system, a quantum system
Transport
Thorpe-le-Soken railway station, Tendring, England (National Rail station code)
Toulouse–Blagnac Airport (IATA code)
Other uses
East Timor (IOC code) |
https://en.wikipedia.org/wiki/Indymedia | The Independent Media Center, better known as Indymedia, is an open publishing network of activist journalist collectives that report on political and social issues. Following beginnings during the 1999 Carnival Against Capital and 1999 Seattle WTO protests, Indymedia became closely associated with the global justice movement. The Indymedia network extended internationally in the early 2000s with volunteer-run centers that shared software and a common format with a newswire and columns. Police raided several centers and seized computer equipment. The centers declined in the 2010s with the waning of the global justice movement.
Content and distribution
Indymedia is a website for citizen journalism that promotes activism and counters mainstream media news and commentary perspectives. Indymedia originated from protests against the concentrated ownership and perceived biases in corporate media reporting. The first Indymedia node, attached to the Seattle anti-corporate globalization protests, was seen by activists as an alternative news source to that of the corporate media, which they accused of only showing violence and confrontation, and portraying all protesters negatively. Indymedia initially covered protests between 1999 and 2001. As protests began to wane, Indymedia covered global social justice movements, such as opposition to the war in Iraq. Indymedia was purported to be the first network on-the-scene in reporting the 2008 Greek riots and the resistance towards the 2009 Honduran coup. The network also has a focus in covering the social justice campaigns of students, Indigenous people, immigrants, and peace activists. A slogan was "Don't Hate the Media, Become the Media!"
Active, the software used as the basis for the first Indymedia center websites, was written by activists in Sydney. It went live in January 1999 and featured open publishing, calendars, events and contacts. Indymedia also ran a global radio project which aggregated audio RSS feeds from around the world.
History
The origins of Indymedia can be traced to the global justice protest Carnival Against Capital, which took place in over forty countries on June 18, 1999. In late November 1999, the first dedicated Indymedia project was ready to cover the 1999 Seattle WTO protests. The first post was made on November 24. It read:
When the protests began, a hundred videographers were on the streets filming, joined by photographers and journalists, all working as volunteers.
After Seattle, local, autonomous collectives formed. Local sociopolitical context determined each individual center's focus. However, it was a core theme that centers would have both an open publishing structure to which anyone could contribute and an open archive. Centers tended to be set up in response to meetings of groups such as the World Bank or G8, to world forum events, or to party conventions, such as Democrat or Republican meetings in the US. By 2002, there were 90 Indymedia websites, mainly in the |
https://en.wikipedia.org/wiki/Warren%20Sturgis%20McCulloch | Warren Sturgis McCulloch (November 16, 1898 – September 24, 1969) was an American neurophysiologist and cybernetician, known for his work on the foundation for certain brain theories and his contribution to the cybernetics movement. Along with Walter Pitts, McCulloch created computational models based on mathematical algorithms called threshold logic which split the inquiry into two distinct approaches, one approach focused on biological processes in the brain and the other focused on the application of neural networks to artificial intelligence.
Biography
Warren Sturgis McCulloch was born in Orange, New Jersey, in 1898. His brother was a chemical engineer and Warren was originally planning to join the Christian ministry. As a teenager he was associated with the theologians Henry Sloane Coffin, Harry Emerson Fosdick, Herman Karl Wilhelm Kumm and Julian F. Hecker. He was also mentored by the Quaker, Rufus Jones. He attended Haverford College and studied philosophy and psychology at Yale University, where he received a Bachelor of Arts degree in 1921. He continued to study psychology at Columbia and received a Master of Arts degree in 1923. Receiving his MD in 1927 from the Columbia University College of Physicians and Surgeons in New York, he undertook an internship at Bellevue Hospital, New York. Then he worked under Eilhard von Domarus at the Rockland State Hospital for the Insane. He returned to academia in 1934. He worked at the Laboratory for Neurophysiology at Yale University from 1934 to 1941.
In 1941 he moved to Chicago and joined the Department of Psychiatry at the University of Illinois at Chicago, where he was a professor of psychiatry, as well as the director of the Illinois Neuropsychiatric Institute until 1951. From 1952 he worked at the Massachusetts Institute of Technology in Cambridge, Massachusetts with Norbert Wiener. He was a founding member of the American Society for Cybernetics and its second president during 1967–1968. He was a mentor to the British operations research pioneer Stafford Beer.
McCulloch had a range of interests and talents. In addition to his scientific contributions he wrote poetry (sonnets), and he designed and engineered buildings and a dam at his farm in Old Lyme, Connecticut.
McCulloch married Ruth Metzger, known as 'Rook', in 1924 and they had three children. He died in Cambridge in 1969.
Work
He is remembered for his work with Joannes Gregorius Dusser de Barenne from Yale and later with Walter Pitts from the University of Chicago. He provided the foundation for certain brain theories in a number of classic papers, including "A Logical Calculus of the Ideas Immanent in Nervous Activity" (1943) and "How We Know Universals: The Perception of Auditory and Visual Forms" (1947), both published in the Bulletin of Mathematical Biophysics. The former is "widely credited with being a seminal contribution to neural network theory, the theory of automata, the theory of computation, and cybernetics".
M |
https://en.wikipedia.org/wiki/Raster%20graphics%20editor | A raster graphics editor (also called bitmap graphics editor) is a computer program that allows users to create and edit images interactively on the computer screen and save them in one of many raster graphics file formats (also known as bitmap images) such as JPEG, PNG, and GIF.
Comparison to vector graphic editors
Vector graphics editors are often contrasted with raster graphics editors, yet their capabilities complement each other. The technical difference between vector and raster editors stem from the difference between vector and raster images. Vector graphics are created mathematically, using geometric formulas. Each element is created and manipulated numerically; essentially using Cartesian coordinates for the placement of key points, and then a mathematical algorithm to connect the dots and define the colors.
Raster images include digital photos. A raster image is made up of rows and columns of dots, called pixels, and is generally more photo-realistic. This is the standard form for digital cameras; whether it be a .raw file or .jpg file, the concept is the same. The image is represented pixel by pixel, like a microscopic jigsaw puzzle.
Vector editors tend to be better suited for graphic design, page layout, typography, logos, sharp-edged artistic illustrations, e.g., cartoons, clip art, complex geometric patterns, technical illustrations, diagramming and flowcharting.
Advanced raster editors, like GIMP and Adobe Photoshop, use vector methods (mathematics) for general layout and elements such as text, but are equipped to deal with raster images down to the pixel and often have special capabilities in doing so, such as brightness/contrast, and even adding "lighting" to a raster image or photograph.
Common features
Select a region for editing
Draw lines with simulated brushes of different color, size, shape and pressure
Fill a region with a single color, gradient of colors, or a texture
Select a color using different color models, e.g., RGB, HSV, or by using a color dropper
Edit and convert between various color models.
Add typed letters in various font styles
Remove imperfections from photo images
Composite editing using layers
Apply filters for effects including sharpening and blurring
Convert between various image file formats
See also
Comparison of raster graphics editors
Vector graphics editor
Texture mapping
Text editor
3D modeling
External links |
https://en.wikipedia.org/wiki/Vector%20graphics%20editor | A vector graphic editor is a computer program that allows users to compose and edit vector graphic images interactively on a computer and save them in one of many popular vector graphic formats, such as EPS, PDF, WMF, SVG, or VML.
Vector editors versus bitmap editors
Vector editors are often contrasted with bitmap editors, and their capabilities complement each other. Vector editors are often better for page layout, typography, logos, sharp-edged artistic illustrations (e.g. cartoons, clip art, complex geometric patterns), technical illustrations, diagramming and flowcharting. Bitmap editors are more suitable for retouching, photo processing, photorealistic illustrations, collage, and illustrations drawn by hand with a pen tablet. Recent versions of bitmap editors such as GIMP and Adobe Photoshop support vector tools (e.g. editable paths), and vector editors have adopted raster effects that were once limited to bitmap editors (e.g. blurring).
Specialized features
Some vector editors support animation, while others (e.g. Adobe Flash, Animatron or Synfig Studio) are specifically geared towards producing animated graphics. Generally, vector graphics are more suitable for animation, though there are raster-based animation tools as well.
Vector editors are closely related to desktop publishing software such as Adobe InDesign or Scribus, which also usually include some vector drawing tools (usually less powerful than those in standalone vector editors).
Special vector editors are used for computer-aided drafting. These are not suitable for artistic or decorative graphics, but are rich in tools and object libraries used to ensure precision and standards compliance of drawings and blueprints.
Finally, 3D computer graphics software such as Maya, Blender or Autodesk 3ds Max can also be thought of as an extension of the traditional 2D vector editors, as they share some common concepts and tools.
See also
Comparison of vector graphics editors
Raster graphics editor
Image editing
Graphics
MetaPost
External links
Bitmap and Vector Graphics Explained
Edit SVG Images Online
App Vector Graphics |
https://en.wikipedia.org/wiki/Likelihood%20function | The likelihood function (often simply called the likelihood) is the joint probability (or probability density) of observed data viewed as a function of the parameters of a statistical model.
In maximum likelihood estimation, the arg max (over the parameter ) of the likelihood function serves as a point estimate for , while the Fisher information (often approximated by the likelihood's Hessian matrix) indicates the estimate's precision. Meanwhile in Bayesian statistics, parameter estimates are derived from the converse of the likelihood, the so-called posterior probability, which is calculated via Bayes' rule.
Definition
The likelihood function, parameterized by a (possibly multivariate) parameter , is usually defined differently for discrete and continuous probability distributions (a more general definition is discussed below). Given a probability density or mass function
where is a realization of the random variable , the likelihood function is
often written
In other words, when is viewed as a function of with fixed, it is a probability density function, and when viewed as a function of with fixed, it is a likelihood function. In the frequentist paradigm, the notation is often avoided and instead or are used to indicate that is regarded as a fixed unknown quantity rather than as a random variable being conditioned on.
The likelihood function does not specify the probability that is the truth, given the observed sample . Such an interpretation is a common error, with potentially disastrous consequences (see prosecutor's fallacy).
Discrete probability distribution
Let be a discrete random variable with probability mass function depending on a parameter . Then the function
considered as a function of , is the likelihood function, given the outcome of the random variable . Sometimes the probability of "the value of for the parameter value " is written as or . The likelihood is the probability that a particular outcome is observed when the true value of the parameter is , equivalent to the probability mass on ; it is not a probability density over the parameter . The likelihood, , should not be confused with , which is the posterior probability of given the data .
Given no event (no data), the likelihood is 1; any non-trivial event will have a lower likelihood.
Example
Consider a simple statistical model of a coin flip: a single parameter that expresses the "fairness" of the coin. The parameter is the probability that a coin lands heads up ("H") when tossed. can take on any value within the range 0.0 to 1.0. For a perfectly fair coin, .
Imagine flipping a fair coin twice, and observing two heads in two tosses ("HH"). Assuming that each successive coin flip is i.i.d., then the probability of observing HH is
Equivalently, the likelihood at given that "HH" was observed is 0.25:
This is not the same as saying that , a conclusion which could only be reached via Bayes' theorem given knowledge about the marginal p |
https://en.wikipedia.org/wiki/Framestore | Framestore Limited(The) is a British animation and visual effects studio based in Chancery Lane in London. Formed in 1986, it acquired and subsequently merged with the Computer Film Company in 1997. Framestore specialises in effects for film, television, video games, and other media. It is the largest production house within Europe, employing roughly 2500 staff — 1000 in London, and 1500 across offices in Chicago, New York, Los Angeles, Montreal, Vancouver, Mumbai and Beijing.
History
Foundation
Framestore was founded in 1986 by husband and (then) wife William Sargent and Sharon Reed, together with three friends. Tim Webber joined Framestore in 1988 and led the company's push into digital film and television, developing Framestore's virtual camera and motion rig systems. In 1992, Mike Milne started the CGI department, adding computer-generated animation to the company's range of facilities.
Merger with CFC
In 1997, Framestore acquired the Computer Film Company, which was one of the UK's first digital film special effects companies, developing technology for digital film scanning, compositing, and output. CFC was founded in London in 1984 by Mike Boudry, Wolfgang Lempp (now CTO at Filmlight) and Neil Harris (Lightworks). CFC's first film was The Fruit Machine, in 1988, which utilised early morphing techniques.
In 2004, Framestore opened their first satellite office in New York City, to focus on advertising. This was followed by another office in Iceland in 2008, which has since been closed and has reopened as a local VFX company, RVX. In 2013 Framestore opened an office in Montreal, followed by another in Los Angeles the same year. In 2014, it launched a production arm.
Early projects for the company include the delivery of its first feature animation project The Tale of Despereaux with Universal; the completion of Europe's first digital intermediate for the film Chicken Run in 2000; contribution of scenes for the 2009 film Avatar, and the completion as a production project of four British feature films which opened in theatres between during 2009 and 2010.
Acquisition by CIH
In November 2016, Framestore agreed to let the Shanghai-based Cultural Investment Holdings Co acquire 75% of it for £112.50 million. The company worked on projects such as Fantastic Beasts and Where to Find Them, Beauty and the Beast, and Paddington 2. In April 2017, Framestore opened a third US location, in Chicago, Illinois.
The company also worked on the 2017 film Darkest Hour directed by Joe Wright, working out of the Montreal facility of Framestore to create historically accurate backdrops for 85 shots in the film, including battle scenes.
The team created around 300 shots for the 2017 film Blade Runner 2049, with Framestore winning a special visual effects award at the 2018 British Academy Film Awards. They have also worked on Black Mirror, creating props such as the 60s-style spaceship in the premiere of the fourth season.
Reception
Framestore has been award |
https://en.wikipedia.org/wiki/Cad%20%28disambiguation%29 | CAD is a commonly used acronym for computer-aided design.
CAD or Cad may also refer to:
Biology and medicine
CAD (gene), an enzyme-encoding gene
Caspase-activated DNase, a protein encoded by the DFFB gene in humans
Coronary artery disease, a group of cardiovascular diseases
Cold agglutinin disease, an autoimmune disease that makes the suffering predisposed to autoimmune hemolytic anemia
Computer-aided diagnosis, software for assisting physicians in the interpretation of medical images
Chemistry
Charged aerosol detector, used to measure the amount of chemicals in a sample
Collisionally activated dissociation, a technique in mass spectrometry
Economics
Canadian dollar, by currency code CAD
Capital Adequacy Directives CAD1 and CAD2, EU directives on capital requirements
Science and technology
Cold-air damming, a meteorological phenomenon
Computer-aided dispatch, software used to dispatch and track vehicles or personnel
Control-alt-delete
Transportation
CAD (TransMilenio), a mass-transit station in Bogotá, Colombia
Center axle disconnect, a type of automotive drivetrain
Civil Aviation Department (Hong Kong), also called CAD
CAD, the IATA code for Wexford County Airport in Michigan, United States
CAD, the station code for Cadoxton railway station in Wales
Other uses
Cad (character), a man who is aware of gentlemanly codes, but does not live up to them
Cad Coles (1886–1942), American baseball player
Cad (river), a river in Romania
Cad Bane, a character in the Star Wars franchise
Cad Brook, a tributary of the River Isle in Britain
Central Ammunition Depot (disambiguation), several depots nicknamed "CAD"
Chicago Assyrian Dictionary, a project to compile a dictionary of the Akkadian language
Cylindrical algebraic decomposition, a notion and an algorithm in computer algebra and real algebraic geometry
cad, the ISO 639 code for the Caddo language of the Caddo Nation of Oklahoma
CAD, abbreviation for the American Ctrl+Alt+Del (webcomic)
Civil Affairs Division, of the US Army
cad., caddesi in Turkish
See also
CADS (disambiguation)
CADD (disambiguation)
CAAD, abbreviation for Computer-aided architectural design |
https://en.wikipedia.org/wiki/CP/M | CP/M, originally standing for Control Program/Monitor and later Control Program for Microcomputers, is a mass-market operating system created in 1974 for Intel 8080/85-based microcomputers by Gary Kildall of Digital Research, Inc. Initially confined to single-tasking on 8-bit processors and no more than 64 kilobytes of memory, later versions of CP/M added multi-user variations and were migrated to 16-bit processors.
The combination of CP/M and S-100 bus computers became an early standard in the microcomputer industry. This computer platform was widely used in business through the late 1970s and into the mid-1980s. CP/M increased the market size for both hardware and software by greatly reducing the amount of programming required to install an application on a new manufacturer's computer. An important driver of software innovation was the advent of (comparatively) low-cost microcomputers running CP/M, as independent programmers and hackers bought them and shared their creations in user groups. CP/M was eventually displaced by DOS following the 1981 introduction of the IBM PC.
History
Early history
Gary Kildall originally developed CP/M during 1974, as an operating system to run on an Intel Intellec-8 development system, equipped with a Shugart Associates 8-inch floppy-disk drive interfaced via a custom floppy-disk controller. It was written in Kildall's own PL/M (Programming Language for Microcomputers). Various aspects of CP/M were influenced by the TOPS-10 operating system of the DECsystem-10 mainframe computer, which Kildall had used as a development environment. An early outside licensee of CP/M was Gnat Computers, an early microcomputer developer out of San Diego, California. In 1977, the company was granted the license to use CP/M 1.0 for any micro they desired for $90. Within the year, demand for CP/M was so high that Digital Research was able to increase the license to tens of thousands of dollars.
Under Kildall's direction, the development of CP/M 2.0 was mostly carried out by John Pierce in 1978. Kathryn Strutynski, a friend of Kildall from Naval Postgraduate School (NPS), became the fourth employee of Digital Research Inc. in early 1979. She started by debugging CP/M 2.0, and later became influential as key developer for CP/M 2.2 and CP/M Plus. Other early developers of the CP/M base included Robert "Bob" Silberstein and David "Dave" K. Brown.
CP/M originally stood for "Control Program/Monitor", a name which implies a resident monitor—a primitive precursor to the operating system. However, during the conversion of CP/M to a commercial product, trademark registration documents filed in November 1977 gave the product's name as "Control Program for Microcomputers". The CP/M name follows a prevailing naming scheme of the time, as in Kildall's PL/M language, and Prime Computer's PL/P (Programming Language for Prime), both suggesting IBM's PL/I; and IBM's CP/CMS operating system, which Kildall had used when working at the NPS. This ren |
https://en.wikipedia.org/wiki/8-bit%20computing | In computer architecture, 8-bit integers or other data units are those that are 8 bits wide (1 octet). Also, 8-bit central processing unit (CPU) and arithmetic logic unit (ALU) architectures are those that are based on registers or data buses of that size. Memory addresses (and thus address buses) for 8-bit CPUs are generally larger than 8-bit, usually 16-bit. 8-bit microcomputers are microcomputers that use 8-bit microprocessors.
The term '8-bit' is also applied to the character sets that could be used on computers with 8-bit bytes, the best known being various forms of extended ASCII, including the ISO/IEC 8859 series of national character sets especially Latin 1 for English and Western European languages.
The IBM System/360 introduced byte-addressable memory with 8-bit bytes, as opposed to bit-addressable or decimal digit-addressable or word-addressable memory, although its general-purpose registers were 32 bits wide, and addresses were contained in the lower 24 bits of those addresses. Different models of System/360 had different internal data path widths; the IBM System/360 Model 30 (1965) implemented the 32-bit System/360 architecture, but had an 8-bit native path width, and performed 32-bit arithmetic 8 bits at a time.
The first widely adopted 8-bit microprocessor was the Intel 8080, being used in many hobbyist computers of the late 1970s and early 1980s, often running the CP/M operating system; it had 8-bit data words and 16-bit addresses. The Zilog Z80 (compatible with the 8080) and the Motorola 6800 were also used in similar computers. The Z80 and the MOS Technology 6502 8-bit CPUs were widely used in home computers and second- and third-generation game consoles of the 1970s and 1980s. Many 8-bit CPUs or microcontrollers are the basis of today's ubiquitous embedded systems.
Historical context
8-bit microprocessors were the first widely used microprocessors in the computing industry, marking a major shift from mainframes and minicomputers to smaller, more affordable systems. The introduction of 8-bit processors in the 1970s enabled the production of personal computers, leading to the popularization of computing and setting the foundation for the modern computing landscape.
Details
An 8-bit register can store 28 different values. The range of integer values that can be stored in 8 bits depends on the integer representation used. With the two most common representations, the range is 0 through 255 (28 − 1) for representation as an (unsigned) binary number, and −128 (−1 × 27) through 127 (27 − 1) for representation as two's complement.
8-bit CPUs use an 8-bit data bus and can therefore access 8 bits of data in a single machine instruction. The address bus is typically a double octet (16 bits) wide, due to practical and economical considerations. This implies a direct address space of 64 KB (65,536 bytes) on most 8-bit processors.
Most home computers from the 8-bit era fully exploited the address space, such as the BBC Micro (Model |
https://en.wikipedia.org/wiki/Process%20%28computing%29 | In computing, a process is the instance of a computer program that is being executed by one or many threads. There are many different process models, some of which are light weight, but almost all processes (even entire virtual machines) are rooted in an operating system (OS) process which comprises the program code, assigned system resources, physical and logical access permissions, and data structures to initiate, control and coordinate execution activity. Depending on the OS, a process may be made up of multiple threads of execution that execute instructions concurrently.
While a computer program is a passive collection of instructions typically stored in a file on disk, a process is the execution of those instructions after being loaded from the disk into memory. Several processes may be associated with the same program; for example, opening up several instances of the same program often results in more than one process being executed.
Multitasking is a method to allow multiple processes to share processors (CPUs) and other system resources. Each CPU (core) executes a single process at a time. However, multitasking allows each processor to switch between tasks that are being executed without having to wait for each task to finish (preemption). Depending on the operating system implementation, switches could be performed when tasks initiate and wait for completion of input/output operations, when a task voluntarily yields the CPU, on hardware interrupts, and when the operating system scheduler decides that a process has expired its fair share of CPU time (e.g, by the Completely Fair Scheduler of the Linux kernel).
A common form of multitasking is provided by CPU's time-sharing that is a method for interleaving the execution of users' processes and threads, and even of independent kernel tasks – although the latter feature is feasible only in preemptive kernels such as Linux. Preemption has an important side effect for interactive processes that are given higher priority with respect to CPU bound processes, therefore users are immediately assigned computing resources at the simple pressing of a key or when moving a mouse. Furthermore, applications like video and music reproduction are given some kind of real-time priority, preempting any other lower priority process. In time-sharing systems, context switches are performed rapidly, which makes it seem like multiple processes are being executed simultaneously on the same processor. This seemingly-simultaneous execution of multiple processes is called concurrency.
For security and reliability, most modern operating systems prevent direct communication between independent processes, providing strictly mediated and controlled inter-process communication.
Representation
In general, a computer system process consists of (or is said to own) the following resources:
An image of the executable machine code associated with a program.
Memory (typically some region of virtual memory); which includes |
https://en.wikipedia.org/wiki/User%20interface | In the industrial design field of human–computer interaction, a user interface (UI) is the space where interactions between humans and machines occur. The goal of this interaction is to allow effective operation and control of the machine from the human end, while the machine simultaneously feeds back information that aids the operators' decision-making process. Examples of this broad concept of user interfaces include the interactive aspects of computer operating systems, hand tools, heavy machinery operator controls and process controls. The design considerations applicable when creating user interfaces are related to, or involve such disciplines as, ergonomics and psychology.
Generally, the goal of user interface design is to produce a user interface that makes it easy, efficient, and enjoyable (user-friendly) to operate a machine in the way which produces the desired result (i.e. maximum usability). This generally means that the operator needs to provide minimal input to achieve the desired output, and also that the machine minimizes undesired outputs to the user.
User interfaces are composed of one or more layers, including a human-machine interface (HMI) that typically interfaces machines with physical input hardware (such as keyboards, mice, or game pads) and output hardware (such as computer monitors, speakers, and printers). A device that implements an HMI is called a human interface device (HID). User interfaces that dispense with the physical movement of body parts as an intermediary step between the brain and the machine use no input or output devices except electrodes alone; they are called brain–computer interfaces (BCIs) or brain–machine interfaces (BMIs).
Other terms for human–machine interfaces are man–machine interface (MMI) and, when the machine in question is a computer, human–computer interface. Additional UI layers may interact with one or more human senses, including: tactile UI (touch), visual UI (sight), auditory UI (sound), olfactory UI (smell), equilibria UI (balance), and gustatory UI (taste).
Composite user interfaces (CUIs) are UIs that interact with two or more senses. The most common CUI is a graphical user interface (GUI), which is composed of a tactile UI and a visual UI capable of displaying graphics. When sound is added to a GUI, it becomes a multimedia user interface (MUI). There are three broad categories of CUI: standard, virtual and augmented. Standard CUI use standard human interface devices like keyboards, mice, and computer monitors. When the CUI blocks out the real world to create a virtual reality, the CUI is virtual and uses a virtual reality interface. When the CUI does not block out the real world and creates augmented reality, the CUI is augmented and uses an augmented reality interface. When a UI interacts with all human senses, it is called a qualia interface, named after the theory of qualia. CUI may also be classified by how many senses they interact with as either an X-sense virtual realit |
https://en.wikipedia.org/wiki/Infinite%20loop | In computer programming, an infinite loop (or endless loop) is a sequence of instructions that, as written, will continue endlessly, unless an external intervention occurs ("pull the plug"). It may be intentional.
Overview
This differs from "a type of computer program that runs the same instructions continuously until it is either stopped or interrupted". Consider the following pseudocode:
how_many = 0
while is_there_more_data() do
how_many = how_many + 1
end
display "the number of items counted = " how_many
The same instructions were run continuously until it was stopped or interrupted . . . by the FALSE returned at some point by the function is_there_more_data.
By contrast, the following loop will not end by itself:
birds = 1
fish = 2
while birds + fish > 1 do
birds = 3 - birds
fish = 3 - fish
end
birds will alternate being 1 or 2, while fish will alternate being 2 or 1. The loop will not stop unless an external intervention occurs ("pull the plug").
Details
An infinite loop is a sequence of instructions in a computer program which loops endlessly, either due to the loop having no terminating condition, having one that can never be met, or one that causes the loop to start over. In older operating systems with cooperative multitasking, infinite loops normally caused the entire system to become unresponsive. With the now-prevalent preemptive multitasking model, infinite loops usually cause the program to consume all available processor time, but can usually be terminated by the user. Busy wait loops are also sometimes called "infinite loops". Infinite loops are one possible cause for a computer "freezing"; others include thrashing, deadlock, and access violations.
Intended vs unintended looping
Looping is repeating a set of instructions until a specific condition is met. An infinite loop occurs when the condition will never be met, due to some inherent characteristic of the loop.
Intentional looping
There are a few situations when this is desired behavior. For example, the games on cartridge-based game consoles typically have no exit condition in their main loop, as there is no operating system for the program to exit to; the loop runs until the console is powered off.
Modern interactive computers require that the computer constantly be monitoring for user input or device activity, so at some fundamental level there is an infinite processing idle loop that must continue until the device is turned off or reset. In the Apollo Guidance Computer, for example, this outer loop was contained in the Exec program, and if the computer had absolutely no other work to do it would loop run a dummy job that would simply turn off the "computer activity" indicator light.
Modern computers also typically do not halt the processor or motherboard circuit-driving clocks when they crash. Instead they fall back to an error condition displaying messages to the operator (such as the blue screen of death), and enter an infinite loop waiting for the u |
https://en.wikipedia.org/wiki/Thread%20%28computing%29 | In computer science, a thread of execution is the smallest sequence of programmed instructions that can be managed independently by a scheduler, which is typically a part of the operating system. In many cases, a thread is a component of a process.
The multiple threads of a given process may be executed concurrently (via multithreading capabilities), sharing resources such as memory, while different processes do not share these resources. In particular, the threads of a process share its executable code and the values of its dynamically allocated variables and non-thread-local global variables at any given time.
The implementation of threads and processes differs between operating systems. In Modern Operating Systems, Tanenbaum shows that many distinct models of process organization are possible.
History
Threads made an early appearance under the name of "tasks" in OS/360 Multiprogramming with a Variable Number of Tasks (MVT) in 1967. Saltzer (1966) credits Victor A. Vyssotsky with the term "thread".
The use of threads in software applications became more common in the early 2000s as CPUs began to utilize multiple cores. Applications wishing to take advantage of multiple cores for performance advantages were required to employ concurrency to utilize the multiple cores.
Related concepts
Scheduling can be done at the kernel level or user level, and multitasking can be done preemptively or cooperatively. This yields a variety of related concepts.
Processes
At the kernel level, a process contains one or more kernel threads, which share the process's resources, such as memory and file handles – a process is a unit of resources, while a thread is a unit of scheduling and execution. Kernel scheduling is typically uniformly done preemptively or, less commonly, cooperatively. At the user level a process such as a runtime system can itself schedule multiple threads of execution. If these do not share data, as in Erlang, they are usually analogously called processes, while if they share data they are usually called (user) threads, particularly if preemptively scheduled. Cooperatively scheduled user threads are known as fibers; different processes may schedule user threads differently. User threads may be executed by kernel threads in various ways (one-to-one, many-to-one, many-to-many). The term "light-weight process" variously refers to user threads or to kernel mechanisms for scheduling user threads onto kernel threads.
A process is a "heavyweight" unit of kernel scheduling, as creating, destroying, and switching processes is relatively expensive. Processes own resources allocated by the operating system. Resources include memory (for both code and data), file handles, sockets, device handles, windows, and a process control block. Processes are isolated by process isolation, and do not share address spaces or file resources except through explicit methods such as inheriting file handles or shared memory segments, or mapping the same file in |
https://en.wikipedia.org/wiki/Hash%20collision | In computer science, a hash collision or hash clash is when two pieces of data in a hash table share the same hash value. The hash value in this case is derived from a hash function which takes a data input and returns a fixed length of bits.
Although hash algorithms have been created with the intent of being collision resistant, they can still sometimes map different data to the same hash (by virtue of the pigeonhole principle). Malicious users can take advantage of this to mimic, access, or alter data.
Due to the possible negative applications of hash collisions in data management and computer security (in particular, cryptographic hash functions), collision avoidance has become an important topic in computer security.
Background
Hash collisions can be unavoidable depending on the number of objects in a set and whether or not the bit string they are mapped to is long enough in length. When there is a set of n objects, if n is greater than |R|, which in this case R is the range of the hash value, the probability that there will be a hash collision is 1, meaning it is guaranteed to occur.
Another reason hash collisions are likely at some point in time stems from the idea of the birthday paradox in mathematics. This problem looks at the probability of a set of two randomly chosen people having the same birthday out of n number of people. This idea has led to what has been called the birthday attack. The premise of this attack is that it is difficult to find a birthday that specifically matches your birthday or a specific birthday, but the probability of finding a set of any two people with matching birthdays increases the probability greatly. Bad actors can use this approach to make it simpler for them to find hash values that collide with any other hash value – rather than searching for a specific value.
The impact of collisions depends on the application. When hash functions and fingerprints are used to identify similar data, such as homologous DNA sequences or similar audio files, the functions are designed so as to maximize the probability of collision between distinct but similar data, using techniques like locality-sensitive hashing. Checksums, on the other hand, are designed to minimize the probability of collisions between similar inputs, without regard for collisions between very different inputs. Instances where bad actors attempt to create or find hash collisions are known as collision attacks.
In practice, security-related applications use cryptographic hash algorithms, which are designed to be long enough for random matches to be unlikely, fast enough that they can be used anywhere, and safe enough that it would be extremely hard to find collisions.
Probability of occurrence
Hash collisions can occur by chance and can be intentionally created for many hash algorithms. The probability of a hash collision thus depends on the size of the algorithm, the distribution of hash values, and whether or not it is both mathematically k |
https://en.wikipedia.org/wiki/Control%20flow | In computer science, control flow (or flow of control) is the order in which individual statements, instructions or function calls of an imperative program are executed or evaluated. The emphasis on explicit control flow distinguishes an imperative programming language from a declarative programming language.
Within an imperative programming language, a control flow statement is a statement that results in a choice being made as to which of two or more paths to follow. For non-strict functional languages, functions and language constructs exist to achieve the same result, but they are usually not termed control flow statements.
A set of statements is in turn generally structured as a block, which in addition to grouping, also defines a lexical scope.
Interrupts and signals are low-level mechanisms that can alter the flow of control in a way similar to a subroutine, but usually occur as a response to some external stimulus or event (that can occur asynchronously), rather than execution of an in-line control flow statement.
At the level of machine language or assembly language, control flow instructions usually work by altering the program counter. For some central processing units (CPUs), the only control flow instructions available are conditional or unconditional branch instructions, also termed jumps.
Categories
The kinds of control flow statements supported by different languages vary, but can be categorized by their effect:
Continuation at a different statement (unconditional branch or jump)
Executing a set of statements only if some condition is met (choice - i.e., conditional branch)
Executing a set of statements zero or more times, until some condition is met (i.e., loop - the same as conditional branch)
Executing a set of distant statements, after which the flow of control usually returns (subroutines, coroutines, and continuations)
Stopping the program, preventing any further execution (unconditional halt)
Primitives
Labels
A label is an explicit name or number assigned to a fixed position within the source code, and which may be referenced by control flow statements appearing elsewhere in the source code. A label marks a position within source code and has no other effect.
Line numbers are an alternative to a named label used in some languages (such as BASIC). They are whole numbers placed at the start of each line of text in the source code. Languages which use these often impose the constraint that the line numbers must increase in value in each following line, but may not require that they be consecutive. For example, in BASIC:
10 LET X = 3
20 PRINT X
In other languages such as C and Ada, a label is an identifier, usually appearing at the start of a line and immediately followed by a colon. For example, in C:
Success: printf("The operation was successful.\n");
The language ALGOL 60 allowed both whole numbers and identifiers as labels (both linked by colons to the following statement), but few if any other AL |
https://en.wikipedia.org/wiki/Pseudorandom%20number%20generator | A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG), is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by an initial value, called the PRNG's seed (which may include truly random values). Although sequences that are closer to truly random can be generated using hardware random number generators, pseudorandom number generators are important in practice for their speed in number generation and their reproducibility.
PRNGs are central in applications such as simulations (e.g. for the Monte Carlo method), electronic games (e.g. for procedural generation), and cryptography. Cryptographic applications require the output not to be predictable from earlier outputs, and more elaborate algorithms, which do not inherit the linearity of simpler PRNGs, are needed.
Good statistical properties are a central requirement for the output of a PRNG. In general, careful mathematical analysis is required to have any confidence that a PRNG generates numbers that are sufficiently close to random to suit the intended use. John von Neumann cautioned about the misinterpretation of a PRNG as a truly random generator, joking that "Anyone who considers arithmetical methods of producing random digits is, of course, in a state of sin."
Potential issues
In practice, the output from many common PRNGs exhibit artifacts that cause them to fail statistical pattern-detection tests. These include:
Shorter-than-expected periods for some seed states (such seed states may be called "weak" in this context);
Lack of uniformity of distribution for large quantities of generated numbers;
Correlation of successive values;
Poor dimensional distribution of the output sequence;
Distances between where certain values occur are distributed differently from those in a random sequence distribution.
Defects exhibited by flawed PRNGs range from unnoticeable (and unknown) to very obvious. An example was the RANDU random number algorithm used for decades on mainframe computers. It was seriously flawed, but its inadequacy went undetected for a very long time.
In many fields, research work prior to the 21st century that relied on random selection or on Monte Carlo simulations, or in other ways relied on PRNGs, were much less reliable than ideal as a result of using poor-quality PRNGs. Even today, caution is sometimes required, as illustrated by the following warning in the International Encyclopedia of Statistical Science (2010).
As an illustration, consider the widely used programming language Java. Up until 2020, Java still relied on a linear congruential generator (LCG) for its PRNG, which is of low quality (see further below). Java support was upgraded with Java 17.
One well-known PRNG to avoid major problems and still run fairly quickly is the Mersenne Twister (discussed below), wh |
https://en.wikipedia.org/wiki/Linear%20congruential%20generator | A linear congruential generator (LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear equation. The method represents one of the oldest and best-known pseudorandom number generator algorithms. The theory behind them is relatively easy to understand, and they are easily implemented and fast, especially on computer hardware which can provide modular arithmetic by storage-bit truncation.
The generator is defined by the recurrence relation:
where is the sequence of pseudo-random values, and
— the "modulus"
— the "multiplier"
— the "increment"
— the "seed" or "start value"
are integer constants that specify the generator. If c = 0, the generator is often called a multiplicative congruential generator (MCG), or Lehmer RNG. If c ≠ 0, the method is called a mixed congruential generator.
When c ≠ 0, a mathematician would call the recurrence an affine transformation, not a linear one, but the misnomer is well-established in computer science.
History
The Lehmer generator was published in 1951 and the Linear congruential generator was published in 1958 by W. E. Thomson and A. Rotenberg.
Period length
A benefit of LCGs is that an appropriate choice of parameters results in a period which is both known and long. Although not the only criterion, too short a period is a fatal flaw in a pseudorandom number generator.
While LCGs are capable of producing pseudorandom numbers which can pass formal tests for randomness, the quality of the output is extremely sensitive to the choice of the parameters m and a. For example, a = 1 and c = 1 produces a simple modulo-m counter, which has a long period, but is obviously non-random.
Historically, poor choices for a have led to ineffective implementations of LCGs. A particularly illustrative example of this is RANDU, which was widely used in the early 1970s and led to many results which are currently being questioned because of the use of this poor LCG.
There are three common families of parameter choice:
m prime, c = 0
This is the original Lehmer RNG construction. The period is m−1 if the multiplier a is chosen to be a primitive element of the integers modulo m. The initial state must be chosen between 1 and m−1.
One disadvantage of a prime modulus is that the modular reduction requires a double-width product and an explicit reduction step. Often a prime just less than a power of 2 is used (the Mersenne primes 231−1 and 261−1 are popular), so that the reduction modulo m = 2e − d can be computed as (ax mod 2e) + d . This must be followed by a conditional subtraction of m if the result is too large, but the number of subtractions is limited to ad/m, which can be easily limited to one if d is small.
If a double-width product is unavailable, and the multiplier is chosen carefully, Schrage's method may be used. To do this, factor m = qa+r, i.e. and . Then compute ax mod m = . Since x mod q < q ≤ m/a, the first term is strictly less tha |
https://en.wikipedia.org/wiki/Telephony%20Application%20Programming%20Interface | The Telephony Application Programming Interface (TAPI) is a Microsoft Windows API, which provides computer telephony integration and enables PCs running Microsoft Windows to use telephone services. Different versions of TAPI are available on different versions of Windows. TAPI allows applications to control telephony functions between a computer and telephone network for data, fax, and voice calls. It includes basic functions, such as dialing, answering, and hanging up a call. It also supports supplementary functions, such as hold, transfer, conference, and call park found in PBX, ISDN, and other telephone systems.
TAPI is used primarily to control either modems or, more recently, to control business telephone system (PBX) handsets. When controlling a PBX handset, the driver is provided by the manufacturer of the telephone system. Some manufacturers provide drivers that allow the control of multiple handsets. This is traditionally called "third-party control". Other manufacturers provide drivers that allow the control of a single handset. This is called "first-party control". Third-party drivers are designed to allow applications to see and/or control multiple extensions at the same time. Some telephone systems only permit one third-party connection at a time. First-party drivers are designed to allow applications to monitor and/or control one extension at a time. Telephone systems naturally permit many of these connections simultaneously. Modem connections are by nature first-party.
TAPI can also be used to control voice-enabled telephony devices, including voice modems and dedicated hardware such as Dialogic cards.
History
TAPI was introduced in 1993 as the result of joint development by Microsoft and Intel. The first publicly available version of TAPI was version 1.3, which was released as a patch on top of Microsoft Windows 3.1. Version 1.3 drivers were 16-bit only. Version 1.3 is no longer supported, although some MSDN development library CDs still contain the files and patches.
With Microsoft Windows 95, TAPI was integrated into the operating system. The first version on Windows 95 was TAPI 1.4. TAPI 1.4 had support for 32-bit applications.
The TAPI standard supports both connections from individual computers and LAN connections serving any number of computers.
TAPI 2.0 was introduced with Windows NT 4.0. Version 2.0 was the first version on the Windows NT platform. It made a significant step forward by supporting ACD and PBX-specific functionality.
In 1997, Microsoft released TAPI version 2.1. This version of TAPI was available as a downloadable update and was the first version to be supported on both the Microsoft Windows 95 and Windows NT/2000 platforms.
TAPI 3.0 was released in 1999 together with Windows 2000. This version enables IP telephony (VoIP) by providing simple and generic methods for making connections between two (using H.323) or more (using IP multicast) computers and now also offers the ability to access any medi |
https://en.wikipedia.org/wiki/Thread%20safety | Thread safety is a computer programming concept applicable to multi-threaded code. Thread-safe code only manipulates shared data structures in a manner that ensures that all threads behave properly and fulfill their design specifications without unintended interaction. There are various strategies for making thread-safe data structures.
A program may execute code in several threads simultaneously in a shared address space where each of those threads has access to virtually all of the memory of every other thread. Thread safety is a property that allows code to run in multithreaded environments by re-establishing some of the correspondences between the actual flow of control and the text of the program, by means of synchronization.
Levels of thread safety
Software libraries can provide certain thread-safety guarantees. For example, concurrent reads might be guaranteed to be thread-safe, but concurrent writes might not be. Whether a program using such a library is thread-safe depends on whether it uses the library in a manner consistent with those guarantees.
Different vendors use slightly different terminology for thread-safety:
Thread safe: Implementation is guaranteed to be free of race conditions when accessed by multiple threads simultaneously.
Conditionally safe: Different threads can access different objects simultaneously, and access to shared data is protected from race conditions.
Not thread safe: Data structures should not be accessed simultaneously by different threads.
Thread safety guarantees usually also include design steps to prevent or limit the risk of different forms of deadlocks, as well as optimizations to maximize concurrent performance. However, deadlock-free guarantees cannot always be given, since deadlocks can be caused by callbacks and violation of architectural layering independent of the library itself.
Implementation approaches
Below we discuss two classes of approaches for avoiding race conditions to achieve thread-safety.
The first class of approaches focuses on avoiding shared state and includes:
Re-entrancy Writing code in such a way that it can be partially executed by a thread, executed by the same thread, or simultaneously executed by another thread and still correctly complete the original execution. This requires the saving of state information in variables local to each execution, usually on a stack, instead of in static or global variables or other non-local state. All non-local states must be accessed through atomic operations and the data-structures must also be reentrant.
Thread-local storage Variables are localized so that each thread has its own private copy. These variables retain their values across subroutine and other code boundaries and are thread-safe since they are local to each thread, even though the code which accesses them might be executed simultaneously by another thread.
Immutable objects The state of an object cannot be changed after construction. This implies both that only re |
https://en.wikipedia.org/wiki/Borland%20Turbo%20C | Turbo C is a discontinued integrated development environment (IDE) and compiler for the C programming language from Borland. First introduced in 1987, it was noted for its integrated development environment, small size, fast compile speed, comprehensive manuals and low price.
In May 1990, Borland replaced Turbo C with Turbo C++. In 2006, Borland reintroduced the Turbo moniker.
Early history
In the early 1980s, Borland enjoyed considerable success with their Turbo Pascal product and it became a popular choice when developing applications for the PC. Borland followed up that success by releasing Turbo Basic, Turbo Prolog, and in 1987, Turbo C. Turbo C has similar properties to Turbo Pascal: an integrated development environment, a fast compiler (though not near the speed of Turbo Pascal), a good editor, and a competitive price.
While Turbo Pascal was successful with hobbyists and schools as well as professional programmers, Turbo C competed with other professional programming tools, such as Microsoft C, Lattice C, and Watcom C.
Version history
Version 1.0 (May 13, 1987) offered the first integrated development environment for C on IBM PCs. Like many Borland products of the time, the software was bought from another company (in this case Wizard C by Bob Jervis), and branded with the "Turbo" name. It ran in of memory. It allowed inline assembly with full access to C symbolic names and structures, supported all memory models, and offered optimizations for speed, size, constant folding, and jump elimination.
Version 1.5 (January 1988) was an incremental improvement over version 1.0. It included more sample programs, improved manuals and bug fixes. It was shipped on five 360 KB diskettes of uncompressed files, and came with sample C programs, including a stripped down spreadsheet called mcalc. This version introduced the <conio.h> header file (which provided fast, PC-specific console I/O routines).
Version 2.0 (late 1988) featured the first "blue screen" version, which would be typical of all future Borland releases for MS-DOS. It was also available bundled with Turbo Assembler and Turbo Debugger. Turbo C 2.0 was also released (in Germany only) for the Atari ST; the program was not maintained by Borland, but sold and renamed PureC. This version introduced the <graphics.h> header file, which provided the Borland Graphics Interface already included in Turbo Pascal.
With the release of Turbo C++ 1.0 (in 1990), the two products were folded into one and the name "Turbo C" was discontinued. The C++ compiler was developed under contract by a company in San Diego, and was one of the first "true" compilers for C++ (until then, it was common to use pre-compilers that generated C code, ref. Cfront).
Freeware release
In 2006, Borland's successor, Embarcadero Technologies, re-released Turbo C and the MS-DOS versions of the Turbo C++ compilers as freeware.
Reception
BYTE in 1989 listed Turbo C and Turbo Pascal as among the "Distinction" winners of the BYT |
https://en.wikipedia.org/wiki/Undocumented%20feature | An undocumented feature is an unintended or undocumented hardware operation, for example an undocumented instruction, or software feature found in computer hardware and software that is considered beneficial or useful. Sometimes the documentation is omitted through oversight, but undocumented features are sometimes not intended for use by end users, but left available for use by the vendor for software support and development. Also, some unintended operation of hardware or software that ends up being of utility to users is simply a bug, flaw or quirk.
Since the suppliers of the software usually consider the software documentation to constitute a contract for the behavior of the software, undocumented features are generally left unsupported and may be removed or changed at will and without notice to the users.
Undocumented or unsupported features are sometimes also called "not manufacturer supported" (NOMAS), a term coined by PPC Journal in the early 1980s.
Some user-reported defects are viewed by software developers as working as expected, leading to the catchphrase "it's not a bug, it's a feature" (INABIAF) and its variations.
Hardware
Undocumented instructions, known as illegal opcodes, on the MOS Technology 6502 and its variants are sometimes used by programmers. These were removed in the WDC 65C02.
Video game and demoscene programmers for the Amiga have taken advantage of the unintended operation of its coprocessors to produce new effects or optimizations.
In 2019, researchers discovered that a manufacturer debugging mode, known as VISA, had an undocumented feature on Intel Platform Controller Hubs (PCHs), chipsets included on most Intel-based motherboards, which makes the mode accessible with a normal motherboard. Since the chipset has direct memory access this is problematic for security reasons.
Software
Undocumented features (for example, the ability to change the switch character in MS-DOS, usually to a hyphen) can be included for compatibility purposes (in this case with Unix utilities) or for future-expansion reasons. However; if the software provider changes their software strategy to better align with the business, the absence of documentation makes it easier to justify the feature's removal.
New versions of software might omit mention of old (possibly superseded) features in documentation but keep them implemented for users who've grown accustomed to them.
In some cases, software bugs are referred to by developers either jokingly or conveniently as undocumented features. This usage may have been popularised in some of Microsoft's responses to bug reports for its first Word for Windows product, but doesn't originate there. The oldest surviving reference on Usenet dates to 5 March 1984. Between 1969 and 1972, Sandy Mathes, a systems programmer for PDP-8 software at Digital Equipment Corporation (DEC) in Maynard, MA, used the terms "bug" and "feature" in her reporting of test results to distinguish between undocumented action |
https://en.wikipedia.org/wiki/Visual%20DialogScript | Visual DialogScript (VDS) is an interpreted programming language for Microsoft Windows, using dialog and graphic elements to create programs. VDS is similar to other programming languages such as Visual Basic, C++, or Delphi, as they use Windows API.
Language
Unlike other programming languages, the syntax of VDS is very simple. Each command occupies one line and has a plain English name that clearly describes its purpose. Variables are typeless and can hold many kinds of information, for example, numbers or text. Functions are clearly distinguishable with names that start with '@', just like a spreadsheet.
The DialogScript language has a simple syntax, not unlike the MS-DOS batch language. It is designed for ease of use and efficiency when being interpreted by the run-time engine. There are 10 system variables, %0 to %9, which initially have the script file name in %0 and command line parameters in %1 through %9, just as in a batch file. There are also a further 26 user variables, from %A to %Z. The contents of all variables (including system ones) can be changed once the script is running. There are now also 4032 global variables. These variables begin with %%, a letter, then alphanumerics plus underscores (e.g., %%my_variable_1.) There is no limit on the length of these user-defined variable names.
Syntax examples
Comments:
# This is a single line comment
REM This is a single line comment
Simple Information Message Box:
info "This is the information text"
Simple Warning Message Box:
warn "This is the warning text"
Create a custom dialog box:
dialog create,<name>,<top pixel position>,<left pixel position>,<width in pixels>,<height in pixels>
Write to the Windows Registry:
registry write,<root key>,<key>,<subkey>,<data>
Display an input prompt dialog box, storing the result in the variable %A:
%A = @input("Please enter a value:")
History
Visual DialogScript was created by Julian Moss (1953 – October 24, 2014) of JM-Tech/Tech-Pro Ltd. In 1998, after version 3.0, Emmanuel Daunizeau of S.A.D.E. sarl, took over the ownership and development of VDS, modifying and improving its syntax. Currently, VDS is marketed by the British company Commercial Research Ltd. and is still the property of Emmanuel Daunizeau who; continues to develop it.
Several versions of VDS have been released over time:
Visual DialogScript 2.0
Visual DialogScript 2.5
Visual DialogScript 3.0
Visual DialogScript 3.5
Visual DialogScript 4
Visual DialogScript 4.5
Visual DialogScript 5
Visual DialogScript 5.01
Visual DialogScript 5.02
Visual DialogScript 6
Currently available versions
There are several versions available for download:
Personal Visual DialogScript (PVDS) 4: This freeware version is intended for students and home PC users. The package includes a short tutorial and full online help, which includes many example scripts. The software is not licensable for commercial use. This version is incapable of producing compiled executable files; however, compilin |
https://en.wikipedia.org/wiki/Social%20capital | Social capital is "the networks of relationships among people who live and work in a particular society, enabling that society to function effectively". It involves the effective functioning of social groups through interpersonal relationships, a shared sense of identity, a shared understanding, shared norms, shared values, trust, cooperation, and reciprocity. Social capital is a measure of the value of resources, both tangible (e.g., public spaces, private property) and intangible (e.g., actors, human capital, people), and the impact that ideal creators have on the resources involved in each relationship, and on larger groups. Some have described it as a form of capital that produces public goods for a common purpose, although this does not align with how it has been measured.
Social capital has been used to explain the improved performance of diverse groups, the growth of entrepreneurial firms, superior managerial performance, enhanced supply chain relations, the value derived from strategic alliances, and the evolution of communities.
History
While it has been suggested that the term social capital was in intermittent use from about 1890, before becoming widely used in the late 1990s, the earliest credited use is by Lyda Hanifan in 1916 (see 20th century below).
The debate of community versus modernization of society and individualism has been the most discussed topic among the founders of sociology: such theorists as Tönnies (1887), Durkheim (1893), Simmel (1905), Weber (1946) were convinced that industrialisation and urbanization were transforming social relationships in an irreversible way. They observed a breakdown of traditional bonds and the progressive development of anomie and alienation in society.
18th–19th century
The power of community governance has been stressed by many philosophers from antiquity to the 18th century, from Aristotle to Thomas Aquinas, and Edmund Burke. This vision was strongly criticised at the end of the 18th century, with the development of the idea of Homo Economicus and subsequently with rational choice theory. Such a set of theories became dominant in the last centuries, but many thinkers questioned the complicated relationship between modern society and the importance of old institutions, in particular family and traditional communities.
The concept that underlies social capital has a much longer history; thinkers exploring the relation between associational life and democracy were using similar concepts regularly by the 19th century, drawing on the work of earlier writers such as James Madison (The Federalist Papers) and Alexis de Tocqueville (Democracy in America) to integrate concepts of social cohesion and connectedness into the pluralist tradition in American political science. John Dewey may have made the first direct mainstream use of social capital in The School and Society in 1899, though he did not offer a definition.
In the first half of the 19th century, de Tocqueville had observations a |
https://en.wikipedia.org/wiki/Dijkstra%27s%20algorithm | Dijkstra's algorithm ( ) is an algorithm for finding the shortest paths between nodes in a weighted graph, which may represent, for example, road networks. It was conceived by computer scientist Edsger W. Dijkstra in 1956 and published three years later.
The algorithm exists in many variants. Dijkstra's original algorithm found the shortest path between two given nodes, but a more common variant fixes a single node as the "source" node and finds shortest paths from the source to all other nodes in the graph, producing a shortest-path tree.
For a given source node in the graph, the algorithm finds the shortest path between that node and every other. It can also be used for finding the shortest paths from a single node to a single destination node by stopping the algorithm once the shortest path to the destination node has been determined. For example, if the nodes of the graph represent cities and costs of edge paths represent driving distances between pairs of cities connected by a direct road (for simplicity, ignore red lights, stop signs, toll roads and other obstructions), then Dijkstra's algorithm can be used to find the shortest route between one city and all other cities. A widely used application of shortest path algorithms is network routing protocols, most notably IS-IS (Intermediate System to Intermediate System) and OSPF (Open Shortest Path First). It is also employed as a subroutine in other algorithms such as Johnson's.
The Dijkstra algorithm uses labels that are positive integers or real numbers, which are totally ordered. It can be generalized to use any labels that are partially ordered, provided the subsequent labels (a subsequent label is produced when traversing an edge) are monotonically non-decreasing. This generalization is called the generic Dijkstra shortest-path algorithm.
Dijkstra's algorithm uses a data structure for storing and querying partial solutions sorted by distance from the start. Dijkstra's original algorithm does not use a min-priority queue and runs in time (where is the number of nodes). The idea of this algorithm is also given in . propose using a Fibonacci heap min-priority queue to optimize the running time complexity to . This is asymptotically the fastest known single-source shortest-path algorithm for arbitrary directed graphs with unbounded non-negative weights. However, specialized cases (such as bounded/integer weights, directed acyclic graphs etc.) can indeed be improved further as detailed in Specialized variants. Additionally, if preprocessing is allowed algorithms such as contraction hierarchies can be up to seven orders of magnitude faster.
In some fields, artificial intelligence in particular, Dijkstra's algorithm or a variant of it is known as uniform cost search and formulated as an instance of the more general idea of best-first search.
History
Dijkstra thought about the shortest path problem when working at the Mathematical Center in Amsterdam in 1956 as a programmer to demon |
https://en.wikipedia.org/wiki/National%20Center%20for%20Supercomputing%20Applications | The National Center for Supercomputing Applications (NCSA) is a state-federal partnership to develop and deploy national-scale computer infrastructure that advances research, science and engineering based in the United States. NCSA operates as a unit of the University of Illinois Urbana-Champaign,
and provides high-performance computing resources to researchers across the country. Support for NCSA comes from the National Science Foundation,
the state of Illinois, the University of Illinois, business and industry partners, and other federal agencies.
NCSA provides leading-edge computing, data storage, and visualization resources. NCSA computational and data environment implements a multi-architecture hardware strategy, deploying both clusters and shared memory systems to support high-end users and communities on the architectures best-suited to their requirements. Nearly 1,360 scientists, engineers and students used the computing and data systems at NCSA to support research in more than 830 projects.
NCSA is led by Bill Gropp.
History
NCSA is one of the five original centers in the National Science Foundation's Supercomputer Centers Program. The idea for NCSA and the four other supercomputer centers arose from the frustration of its founder, Larry Smarr, who wrote an influential paper, "The Supercomputer Famine in American Universities", in 1982, after having to travel to Europe in summertime to access supercomputers and conduct his research.
So i wrote a proposal to address the future needs of scientific research. Seven other University of Illinois professors joined as co-principal investigators, and many others provided descriptions of what could be accomplished if the proposal were accepted. Known as the Black Proposal (after the color of its cover), it was submitted to the NSF in 1983. It met the NSF's mandate and its contents immediately generated excitement. However, the NSF had no organization in place to support it, and the proposal itself did not contain a clearly defined home for its implementation.
The NSF established an Office of Scientific Computing in 1984 and, with strong congressional support, it announced a national competition that would fund a set of supercomputer centers like the one described in the Black Proposal.
The result was that four supercomputer centers would be chartered (Cornell, Illinois, Princeton, and San Diego), with a fifth (Pittsburgh) added later.
The Black Proposal was approved in 1985 and marked the foundation of NCSA, with $42,751,000 in funding from 1 January 1985 through 31 December 1989. This was also noteworthy in that the NSF's action of approving an unsolicited proposal was unprecedented. NCSA opened its doors in January 1986.
In 2007, NCSA was awarded a grant from the National Science Foundation to build "Blue Waters", a supercomputer capable of performing quadrillions of calculations per second, a level of performance known as petascale.
Black Proposal
The 'Black Proposal' was a sho |
https://en.wikipedia.org/wiki/Dark%20Angel%20%28American%20TV%20series%29 | Dark Angel is an American science fiction drama television series that premiered on the Fox network on October 3, 2000. Created by James Cameron and Charles H. Eglee, it stars Jessica Alba in her breakthrough role. Set in 2019, the series chronicles the life of Max Guevara (Alba), a runaway genetically enhanced supersoldier who escapes from a covert military facility as a child. In a dystopian near-future Seattle, she tries to lead a normal life while eluding capture by government agents and searching for her brothers and sisters scattered in the aftermath of their escape. Dark Angel was the only show produced by the company Cameron/Eglee Productions, and was filmed in Vancouver at Lions Gate Studios.
The high-budget pilot episode marked Cameron's television debut and was heavily promoted by Fox, reaching 17.4 million viewers. The first season, which was shown on Tuesday nights in the United States, received mainly positive reviews and won several awards, including the People's Choice Award for Favorite New TV Drama, and averaged 10.4 million viewers per episode. Alba's portrayal of Max also received mostly positive reviews and several awards. For the second season, the show was moved to the less desirable air time of Friday night and received some criticism for new plot elements. It suffered from a drop in ratings, averaging 6 million viewers per episode, and was canceled.
A series of novels continued the storyline, and a video game adaptation was also released. Dark Angel is considered to have gothic and female empowerment themes; Max followed a long line of strong female characters in Cameron's work, including Sarah Connor and Ellen Ripley. Cameron was also influenced by the manga Battle Angel Alita. Dark Angel is considered to be part of a wave of shows in the late 1990s and early 2000s that feature strong female characters, alongside Buffy the Vampire Slayer, Xena: Warrior Princess, Alias, and La Femme Nikita.
Plot
Season one
In February 2009, a genetically enhanced nine-year-old female supersoldier designated as X5-452 (Geneva Locke) escapes along with eleven others from a secret U.S. government institution code-named Manticore, where they were born, raised, and trained to be soldiers and assassins. On June 1, 2009, months after the twelve X5s' escape, terrorists detonate an electromagnetic pulse weapon in the atmosphere over the U.S., which destroys the vast majority of computer and communication systems, throwing the country into chaos.
Ten years later in 2019, the now 19-year-old X5-452 (Jessica Alba), who calls herself Max Guevara, struggles to search for her Manticore brothers and sisters. In the recovering United States, which is now barely more than a developing country, she tries to live a relatively normal life and evade capture by Manticore, which wishes to recover its lost asset. Logan Cale (Michael Weatherly), an underground cyber-journalist with the alias Eyes Only, attempts to recruit her to help fight corruption in the |
https://en.wikipedia.org/wiki/Psion%20Organiser | Psion Organiser was the brand name of a range of pocket computers developed by the British company Psion in the 1980s. The Organiser I (launched in 1984) and Organiser II (launched in 1986) had a characteristic hard plastic sliding cover protecting a 6×6 keypad instead of a computer keyboard, with letters arranged alphabetically.
The Organiser II competed with the Filofax and can be considered the first usable electronic organizer or personal digital assistant (PDA) in that it combined an electronic diary and searchable address database in a small, portable device.
Production of consumer hand-held devices by Psion has now ceased; the company, after corporate changes, now concentrates on hardware and software for industrial and commercial data-collection applications.
On an episode of The Gadget Show, first aired 30 March 2009, the Psion was pitted against the BlackBerry for a place on the show's Hall of Fame. Whilst the Psion was highly praised as a device that pioneered portable computing, host Jon Bentley ultimately gave the accolade to the BlackBerry.
As of autumn 2017 several software features and hardware devices are still being developed and are available including a JavaScript Emulator, Parallel Interface, USB Commslink, 32 kilobyte (KB) and 256 KB RAMpaks, and 512 KB FlashPak.
Organiser I
Launched in 1984, the Psion Organiser was the "world's first practical pocket computer". Based on an 8-bit Hitachi 6301-family processor, running at 0.9 MHz, with 4 KB of read-only memory (ROM) and 2 KB of static RAM and has a one-row monochrome liquid crystal display (LCD) screen. The size with the case closed is 142 × 78 × 29.3 mm, and the mass is 225 grams.
A Byte reviewer described the Organiser's software as a "clever design ... for fast and foolproof use". He approved of the consistent user interface across applications and reported that without documentation he was able to learn how to do everything except program in 15 minutes. The machine provided a simple flat-file database, calculator and clock, and had no operating system (OS). The Organiser I supported removable storage write once read many (write-once) devices, which used erasable programmable read-only memory EPROM storage. The device can host two of these, named Datapaks (stylized as DATAPAK, or simply PAK), to which it can write data, but which must be removed from the device and erased by exposure to ultraviolet light before they can be re-used. As Psion had patented the use of EPROMS as a storage device, it was impossible for other device makers to copy this unusual approach to mobile storage.
Software supplied on Datapak included a crude programming language named POPL, in which end-users could write their own programs. Software Datapaks titled Science, Maths and Finance contained the POPL programming language editor, interpreter and runtime system and extended the built-in calculator by adding named functions. These Datapaks also contained different sets of application softw |
https://en.wikipedia.org/wiki/Psion%20%28company%29 | Psion PLC was a designer and manufacturer of mobile handheld computers for commercial and industrial uses. The company was headquartered in London, England, with major operations in Mississauga, Ontario, Canada, and other company offices in Europe, the United States, Asia, Latin America, and the Middle East. It was a public company listed on the London Stock Exchange () and was once a constituent of the FTSE 100 Index.
Psion's operational business was formed in September 2000 from a merger of Psion and Canadian-based Teklogix Inc., and was a global provider of solutions for mobile computing and wireless data collection. The Group's products and services included rugged mobile hardware, secure software and wireless networks, professional services, and support programs. Psion worked with its clients in the area of burgeoning technologies, including imaging, voice recognition, and radio-frequency identification (RFID). They had operations worldwide in 14 countries, and customers in more than 80 countries.
Formed in 1980, Psion first achieved success as a consumer hardware company that developed the Psion Organiser and a wide range of more sophisticated clamshell personal digital assistants (PDAs). Psion either closed or disposed of all its prior operations and then focused on rugged mobile computing systems. It withdrew from the consumer device market in 2001. Motorola Solutions announced in June 2012 that it had agreed to acquire Psion for $200 million.
History
Beginnings (1980–1984)
Psion was established in 1980 as a software house with a close relationship with Sinclair Research. The company developed games and other software for the ZX81 and ZX Spectrum home computers, released under the Sinclair/Psion brand. Psion's games for the ZX Spectrum included Chess, Chequered Flag, Flight Simulation and the Horace series. Psion Chess was later ported to other platforms, including the early Macintosh in 1984.
Early software releases for the ZX Spectrum included titles such as VU-Calc, VU-File and VU-3D along with dozens of other titles.
The company name is an acronym standing for "Potter Scientific Instruments", after the company's founder, David Potter. The acronym PSI was already in use elsewhere in the world so "ON" was added to make the name PSION unique, according to David Potter this was explained as his ambition was so strong that it was Potter Scientific Instruments - Or Nothing. David Potter remained managing director until 1999 and was chairman of the company until late 2009.
In early 1983, Sinclair approached Psion regarding the development of a suite of office applications for the forthcoming Sinclair QL personal computer. Psion were already working on a project in this area and the QL was launched in 1984, bundled with Quill, Archive, Abacus and Easel; respectively a word processor, database, spreadsheet, and business graphics application. These were later ported to DOS and were made available for the IBM PC and ACT Sirius and Apri |
https://en.wikipedia.org/wiki/Case%20sensitivity | In computers, case sensitivity defines whether uppercase and lowercase letters are treated as distinct (case-sensitive) or equivalent (case-insensitive). For instance, when users interested in learning about dogs search an e-book, "dog" and "Dog" are of the same significance to them. Thus, they request a case-insensitive search. But when they search an online encyclopedia for information about the United Nations, for example, or something with no ambiguity regarding capitalization and ambiguity between two or more terms cut down by capitalization, they may prefer a case-sensitive search.
Areas of significance
Case sensitivity may differ depending on the situation:
Searching: Users expect information retrieval systems to be able to have correct case sensitivity depending on the nature of an operation. Users looking for the word "dog" in an online journal probably do not wish to differentiate between "dog" or "Dog", as this is a writing distinction; the word should be matched whether it appears at the beginning of a sentence or not. On the other hand, users looking for information about a brand name, trademark, human name, or city name may be interested in performing a case-sensitive operation to filter out irrelevant results. For example, somebody searching for the name "Jade" would not want to find references to the mineral called "jade". On the English Wikipedia for example a search for friendly fire returns the military article but Friendly Fire (capitalized "Fire") returns the disambiguation page.
Usernames: Authentication systems usually treat usernames as case-insensitive to make them easier to remember, reducing typing complexity, and eliminate the possibility of both mistakes and fraud when two usernames are identical in every aspect except the case of one of their letters. However, these systems are not case-blind. They preserve the case of the characters in the name so that users may choose an aesthetically pleasing username combination.
Passwords: Authentication systems usually treat passwords as case-sensitive. This enables the users to increase the complexity of their passwords.
File names: Traditionally, Unix-like operating systems treat file names case-sensitively while Microsoft Windows is case-insensitive but, for most file systems, case-preserving. For more details, see below.
Variable names: Some programming languages are case-sensitive for their variable names while others are not. For more details, see below.
URLs: The path, query, fragment, and authority sections of a URL may or may not be case-sensitive, depending on the receiving web server. The scheme and host parts, however, are strictly lowercase.
In programming languages
Some programming languages are case-sensitive for their identifiers (C, C++, Java, C#, Verilog, Ruby, Python and Swift). Others are case-insensitive (i.e., not case-sensitive), such as ABAP, Ada, most BASICs (an exception being BBC BASIC), Fortran, SQL (for the syntax, and for some vendor imple |
https://en.wikipedia.org/wiki/Simpson%27s%20paradox | Simpson's paradox is a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined. This result is often encountered in social-science and medical-science statistics, and is particularly problematic when frequency data are unduly given causal interpretations. The paradox can be resolved when confounding variables and causal relations are appropriately addressed in the statistical modeling (e.g., through cluster analysis).
Simpson's paradox has been used to illustrate the kind of misleading results that the misuse of statistics can generate.
Edward H. Simpson first described this phenomenon in a technical paper in 1951, but the statisticians Karl Pearson (in 1899) and Udny Yule (in 1903) had mentioned similar effects earlier. The name Simpson's paradox was introduced by Colin R. Blyth in 1972. It is also referred to as Simpson's reversal, the Yule–Simpson effect, the amalgamation paradox, or the reversal paradox.
Mathematician Jordan Ellenberg argues that Simpson's paradox is misnamed as "there's no contradiction involved, just two different ways to think about the same data" and suggests that its lesson "isn't really to tell us which viewpoint to take but to insist that we keep both the parts and the whole in mind at once."
Examples
UC Berkeley gender bias
One of the best-known examples of Simpson's paradox comes from a study of gender bias among graduate school admissions to University of California, Berkeley. The admission figures for the fall of 1973 showed that men applying were more likely than women to be admitted, and the difference was so large that it was unlikely to be due to chance.
However, when taking into account the information about departments being applied to, the different rejection percentages reveal the different difficulty of getting into the department, and at the same time it showed that women tended to apply to more competitive departments with lower rates of admission, even among qualified applicants (such as in the English department), whereas men tended to apply to less competitive departments with higher rates of admission (such as in the engineering department). The pooled and corrected data showed a "small but statistically significant bias in favor of women".
The data from the six largest departments are listed below:
The entire data showed total of 4 out of 85 departments to be significantly biased against women, while 6 to be significantly biased against men (not all present in the 'six largest departments' table above). Notably, the numbers of biased departments were not the basis for the conclusion, but rather it was the gender admissions pooled across all departments, while weighing by each department's rejection rate across all of its applicants.
Kidney stone treatment
Another example comes from a real-life medical study comparing the success rates of two treatments for kidney stones. The table below shows the suc |
https://en.wikipedia.org/wiki/Robert%20Tarjan | Robert Endre Tarjan (born April 30, 1948) is an American computer scientist and mathematician. He is the discoverer of several graph algorithms, including Tarjan's strongly connected components algorithm, and co-inventor of both splay trees and Fibonacci heaps. Tarjan is currently the James S. McDonnell Distinguished University Professor of Computer Science at Princeton University.
Personal life and education
He was born in Pomona, California. His father, raised in Hungary, was a child psychiatrist, specializing in mental retardation, and ran a state hospital. As a child, Tarjan read a lot of science fiction, and wanted to be an astronomer. He became interested in mathematics after reading Martin Gardner's mathematical games column in Scientific American. He became seriously interested in math in the eighth grade, thanks to a "very stimulating" teacher.
While he was in high school, Tarjan got a job, where he worked with IBM punch card collators. He first worked with real computers while studying astronomy at the Summer Science Program in 1964.
Tarjan obtained a Bachelor's degree in mathematics from the California Institute of Technology in 1969. At Stanford University, he received his master's degree in computer science in 1971 and a Ph.D. in computer science (with a minor in mathematics) in 1972. At Stanford, he was supervised by Robert Floyd and Donald Knuth, both highly prominent computer scientists, and his Ph.D. dissertation was An Efficient Planarity Algorithm. Tarjan selected computer science as his area of interest because he believed that computer science was a way of doing mathematics that could have a practical impact.
Tarjan now lives in Princeton, NJ, and Silicon Valley. He is married to Nayla Rizk.
He has three daughters: Alice Tarjan, Sophie Zawacki, and Maxine Tarjan.
Computer science career
Tarjan has been teaching at Princeton University since 1985. He has also held academic positions at Cornell University (1972–73), University of California, Berkeley (1973–1975), Stanford University (1974–1980), and New York University (1981–1985). He has also been a fellow of the NEC Research Institute (1989–1997). In April 2013 he joined Microsoft Research Silicon Valley in addition to the position at Princeton. In October 2014 he rejoined Intertrust Technologies as chief scientist.
Tarjan has worked at AT&T Bell Labs (1980–1989), Intertrust Technologies (1997–2001, 2014–present), Compaq (2002) and Hewlett Packard (2006–2013).
Algorithms and data structures
Tarjan is known for his pioneering work on graph theory algorithms and data structures. Some of his well-known algorithms include Tarjan's off-line least common ancestors algorithm, and Tarjan's strongly connected components algorithm, and he was one of five co-authors of the median of medians linear-time selection algorithm. The Hopcroft–Tarjan planarity testing algorithm was the first linear-time algorithm for planarity testing.
Tarjan has also developed important data struc |
https://en.wikipedia.org/wiki/ITV%20Digital | ITV Digital was a British digital terrestrial television broadcaster which launched a pay-TV service on the world's first digital terrestrial television network. Its main shareholders were Carlton Communications plc and Granada plc, owners of multiple licences of the ITV network. Starting as ONdigital in 1998, the service was rebranded as ITV Digital in July 2001.
Low audience figures, piracy issues and an ultimately unaffordable multi-million pound deal with the Football League led to the broadcaster suffering large losses, and it entered administration in March 2002. Pay television services ceased permanently on 1 May of that year, but carriage of the remaining free-to-air channels such as BBC One and Channel 4 continued. In October, ITV Digital’s former terrestrial multiplexes were taken over by Crown Castle and the BBC to create the Freeview free-to-air service.
History
On 31 January 1997, Carlton Television, Granada Television and satellite company British Sky Broadcasting (BSkyB) together created British Digital Broadcasting (BDB) as a joint venture, and applied to operate three digital terrestrial television (DTT) licences. They faced competition from a rival, Digital Television Network (DTN), a company created by cable operator CableTel (later known as NTL). On 25 June 1997, BDB won the auction and the Independent Television Commission (ITC) awarded the sole broadcast licence for DTT to the consortium. Then on 20 December 1997, the ITC awarded three pay-TV digital multiplex licences to BDB.
That same year, however, the ITC forced BSkyB out of the consortium on competition grounds; this effectively placed Sky in direct competition with the new service as Sky would also launch its digital satellite service in 1998, although Sky was still required to provide key channels such as Sky Movies and Sky Sports to BDB. With Sky as part of the consortium, British Digital Broadcasting would have paid discounted rates to carry Sky's television channels. Instead, with its positioning as a competitor, Sky charged the full market rates for the channels, at an extra cost of around £60million a year to BDB. On 28 July 1998, BDB announced the service would be called ONdigital, and claimed it would be the biggest television brand launch in history. The company would be based in Marco Polo House (since demolished) in Battersea, south London, which was previously the home of BSkyB's earlier rival, British Satellite Broadcasting (BSB).
Six multiplexes were set up, with three of them allocated to the existing analogue broadcasters. The other three multiplexes were auctioned off. ONdigital was given one year from the award of the licence to launch the first DTT service. In addition to launching audio and video services, it also led the specification of an industry-wide advanced interactive engine, based on MHEG-5. This was an open standard that was used by all broadcasters on DTT.
The launch
ONdigital was officially launched on 15 November 1998 amid a larg |
https://en.wikipedia.org/wiki/Planner%20%28programming%20language%29 | Planner (often seen in publications as "PLANNER" although it is not an acronym) is a programming language designed by Carl Hewitt at MIT, and first published in 1969. First, subsets such as Micro-Planner and Pico-Planner were implemented, and then essentially the whole language was implemented as Popler by Julian Davies at the University of Edinburgh in the POP-2 programming language. Derivations such as QA4, Conniver, QLISP and Ether (see scientific community metaphor) were important tools in artificial intelligence research in the 1970s, which influenced commercial developments such as Knowledge Engineering Environment (KEE) and Automated Reasoning Tool (ART).
Procedural approach versus logical approach
The two major paradigms for constructing semantic software systems were procedural and logical. The procedural paradigm was epitomized by
Lisp which featured recursive procedures that operated on list structures.
The logical paradigm was epitomized by uniform proof procedure resolution-based derivation (proof) finders. According to the logical paradigm it was “cheating” to incorporate procedural knowledge.
Procedural embedding of knowledge
Planner was invented for the purposes of the procedural embedding of knowledge and was a rejection of the resolution uniform proof procedure paradigm, which
Converted everything to clausal form. Converting all information to clausal form is problematic because it hides the underlying structure of the information.
Then used resolution to attempt to obtain a proof by contradiction by adding the clausal form of the negation of the theorem to be proved. Using only resolution as the rule of inference is problematical because it hides the underlying structure of proofs. Also, using proof by contradiction is problematical because the axiomatizations of all practical domains of knowledge are inconsistent in practice.
Planner was a kind of hybrid between the procedural and logical paradigms because it combined programmability with logical reasoning. Planner featured a procedural interpretation of logical sentences where an implication of the form can be procedurally interpreted in the following ways using pattern-directed invocation:
Forward chaining (antecedently):
Backward chaining (consequently)
In this respect, the development of Planner was influenced by natural deductive logical systems (especially the one by Frederic Fitch [1952]).
Micro-planner implementation
A subset called Micro-Planner was implemented by Gerry Sussman, Eugene Charniak and Terry Winograd and was used in Winograd's natural-language understanding program SHRDLU, Eugene Charniak's story understanding work, Thorne McCarty's work on legal reasoning, and some other projects. This generated a great deal of excitement in the field of AI. It also generated controversy because it proposed an alternative to the logic approach that had been one of the mainstay paradigms for AI.
At SRI International, Jeff Rulifson, Jan Derksen, and Rich |
https://en.wikipedia.org/wiki/Oracle%20Solaris | Solaris is a proprietary Unix operating system originally developed by Sun Microsystems. After the Sun acquisition by Oracle in 2010, it was renamed Oracle Solaris.
Solaris superseded the company's earlier SunOS in 1993, and became known for its scalability, especially on SPARC systems, and for originating many innovative features such as DTrace, ZFS and Time Slider.
Solaris supports SPARC and x86-64 workstations and servers from Oracle and other vendors. Solaris was registered as compliant with the Single UNIX Specification until 29 April 2019.
Historically, Solaris was developed as proprietary software. In June 2005, Sun Microsystems released most of the codebase under the CDDL license, and founded the OpenSolaris open-source project. With OpenSolaris, Sun wanted to build a developer and user community around the software. After the acquisition of Sun Microsystems in January 2010, Oracle decided to discontinue the OpenSolaris distribution and the development model. In August 2010, Oracle discontinued providing public updates to the source code of the Solaris kernel, effectively turning Solaris 11 back into a closed source proprietary operating system. Following that, OpenSolaris was forked as Illumos and is alive through several illumos distributions. In September 2017, Oracle laid off most of the Solaris teams.
In 2011, the Solaris 11 kernel source code leaked. Through the Oracle Technology Network (OTN), industry partners can gain access to the in-development Solaris source code. Solaris is developed under a proprietary development model, and only the source for open-source components of Solaris 11 is available for download from Oracle.
History
In 1987, AT&T Corporation and Sun announced that they were collaborating on a project to merge the most popular Unix variants on the market at that time: Berkeley Software Distribution, UNIX System V, and Xenix. This became Unix System V Release 4 (SVR4).
On September 4, 1991, Sun announced that it would replace its existing BSD-derived Unix, SunOS 4, with one based on SVR4. This was identified internally as SunOS 5, but a new marketing name was introduced at the same time: Solaris 2. The justification for this new overbrand was that it encompassed not only SunOS, but also the OpenWindows graphical user interface and Open Network Computing (ONC) functionality.
Although SunOS 4.1.x micro releases were retroactively named Solaris 1 by Sun, the Solaris name is used almost exclusively to refer only to the releases based on SVR4-derived SunOS 5.0 and later.
For releases based on SunOS 5, the SunOS minor version is included in the Solaris release number. For example, Solaris 2.4 incorporates SunOS 5.4. After Solaris 2.6, the 2. was dropped from the release name, so Solaris 7 incorporates SunOS 5.7, and the latest release SunOS 5.11 forms the core of Solaris 11.4.
Although SunSoft stated in its initial Solaris 2 press release their intent to eventually support both SPARC and x86 systems, the first t |
https://en.wikipedia.org/wiki/Lua%20%28programming%20language%29 | Lua ( ; from meaning moon) is a lightweight, high-level, multi-paradigm programming language designed primarily for embedded use in applications. Lua is cross-platform, since the interpreter of compiled bytecode is written in ANSI C, and Lua has a relatively simple C API to embed it into applications.
Lua originated in 1993 as a language for extending software applications to meet the increasing demand for customization at the time. It provided the basic facilities of most procedural programming languages, but more complicated or domain-specific features were not included; rather, it included mechanisms for extending the language, allowing programmers to implement such features. As Lua was intended to be a general embeddable extension language, the designers of Lua focused on improving its speed, portability, extensibility, and ease-of-use in development.
History
Lua was created in 1993 by Roberto Ierusalimschy, Luiz Henrique de Figueiredo, and Waldemar Celes, members of the Computer Graphics Technology Group (Tecgraf) at the Pontifical Catholic University of Rio de Janeiro, in Brazil.
From 1977 until 1992, Brazil had a policy of strong trade barriers (called a market reserve) for computer hardware and software. In that atmosphere, Tecgraf's clients could not afford, either politically or financially, to buy customized software from abroad. Those reasons led Tecgraf to implement the basic tools it needed from scratch.
Lua's predecessors were the data-description/configuration languages SOL (Simple Object Language) and DEL (data-entry language). They had been independently developed at Tecgraf in 1992–1993 to add some flexibility into two different projects (both were interactive graphical programs for engineering applications at Petrobras company). There was a lack of any flow-control structures in SOL and DEL, and Petrobras felt a growing need to add full programming power to them.
In The Evolution of Lua, the language's authors wrote:
Lua 1.0 was designed in such a way that its object constructors, being then slightly different from the current light and flexible style, incorporated the data-description syntax of SOL (hence the name Lua: Sol meaning "Sun" in Portuguese, and Lua meaning "Moon"). Lua syntax for control structures was mostly borrowed from Modula (if, while, repeat/until), but also had taken influence from CLU (multiple assignments and multiple returns from function calls, as a simpler alternative to reference parameters or explicit pointers), C++ ("neat idea of allowing a local variable to be declared only where we need it"), SNOBOL and AWK (associative arrays). In an article published in Dr. Dobb's Journal, Lua's creators also state that LISP and Scheme with their single, ubiquitous data-structure mechanism (the list) were a major influence on their decision to develop the table as the primary data structure of Lua.
Lua semantics have been increasingly influenced by Scheme over time, especially with the introduction of |
https://en.wikipedia.org/wiki/Fox%20Broadcasting%20Company | The Fox Broadcasting Company, commonly known simply as Fox and stylized in all caps, is an American commercial broadcast television network owned by the Fox Entertainment division of Fox Corporation. Headquartered at 1211 Avenue of the Americas, New York City, Fox has master control operations and additional offices at the Fox Network Center in Los Angeles and the Fox Media Center in Tempe. Launched as a competitor to the Big Three television networks (ABC, CBS, and NBC) on October 9, 1986, the network went on to become the most successful attempt at a fourth television network. It was the highest-rated free-to-air network in the 18–49 demographic from 2004 to 2012 and 2020 to 2021, and was the most-watched American television network in total viewership during the 2007–08 season.
Fox and its affiliated companies operate many entertainment channels in international markets, but these do not necessarily air the same programming as the U.S. network. Most viewers in Canada have access to at least one U.S.-based Fox affiliate, either over the air or through a pay television provider, although Fox's National Football League broadcasts and most of its prime time programming are subject to simultaneous substitution regulations for pay television providers imposed by the Canadian Radio-television and Telecommunications Commission (CRTC) to protect rights held by domestically based networks.
Fox is named after the film studio that was originally called 20th Century Fox (the network's corporate sibling prior to that studio's acquisition by The Walt Disney Company), and (indirectly) after the producer William Fox, who had founded one of the film studio's predecessors, Fox Film, before it was merged with another company in 1935. Fox is a member of the North American Broadcasters Association and the National Association of Broadcasters.
History
Origins
20th Century Fox (now 20th Century Studios) had been involved in television production as early as the 1950s, producing several syndicated programs. Following the demise of the DuMont Television Network in August 1956, after it became mired in severe financial problems, the NTA Film Network was launched as a new "fourth network". 20th Century Fox would also produce original content for the NTA network. The film network effort would fail after a few years, but 20th Century Fox continued to dabble in television through its production arm, TCF Television Productions, producing series (such as Perry Mason, Batman and M*A*S*H) for the three major broadcast television networks (ABC, NBC, and CBS).
1980s: Establishment of the network
Foundations
The Fox network's foundations were laid in March 1985 through News Corporation's $255 million purchase of a 50% interest in TCF Holdings, the parent company of the 20th Century Fox film studio. In May 1985, News Corporation, a media company owned by Australian publishing magnate Rupert Murdoch that had mainly served as a newspaper publisher at the time of the TCF Holding |
https://en.wikipedia.org/wiki/Telemetry | Telemetry is the in situ collection of measurements or other data at remote points and their automatic transmission to receiving equipment (telecommunication) for monitoring. The word is derived from the Greek roots tele, 'remote', and metron, 'measure'. Systems that need external instructions and data to operate require the counterpart of telemetry: telecommand.
Although the term commonly refers to wireless data transfer mechanisms (e.g., using radio, ultrasonic, or infrared systems), it also encompasses data transferred over other media such as a telephone or computer network, optical link or other wired communications like power line carriers. Many modern telemetry systems take advantage of the low cost and ubiquity of GSM networks by using SMS to receive and transmit telemetry data.
A telemeter is a physical device used in telemetry. It consists of a sensor, a transmission path, and a display, recording, or control device. Electronic devices are widely used in telemetry and can be wireless or hard-wired, analog or digital. Other technologies are also possible, such as mechanical, hydraulic and optical.
Telemetry may be commutated to allow the transmission of multiple data streams in a fixed frame.
History
The beginning of industrial telemetry lies in the steam age, although the sensor was not called telemeter at that time. Examples are James Watt's (1736-1819) additions to his steam engines for monitoring from a (near) distance such as the mercury pressure gauge and the fly-ball governor.
Although the original telemeter referred to a ranging device (the rangefinding telemeter), by the late 19th century the same term had been in wide use by electrical engineers applying it refer to electrically operated devices measuring many other quantities besides distance (for instance, in the patent of an "Electric Telemeter Transmitter"). General telemeters included such sensors as the thermocouple (from the work of Thomas Johann Seebeck), the resistance thermometer (by William Siemens based on the work of Humphry Davy), and the electrical strain gauge (based on Lord Kelvin's discovery that conductors under mechanical strain change their resistance) and output devices such as Samuel Morse's telegraph sounder and the relay. In 1889 this led an author in the Institution of Civil Engineers proceedings to suggest that the term for the rangefinder telemeter might be replaced with tacheometer.
In the 1930s use of electrical telemeters grew rapidly. The electrical strain gauge was widely used in rocket and aviation research and the radiosonde was invented for meteorological measurements. The advent of World War II gave an impetus to industrial development and henceforth many of these telemeters became commercially viable.
Carrying on from rocket research, radio telemetry was used routinely as space exploration got underway. Spacecraft are in a place where a physical connection is not possible, leaving radio or other electromagnetic waves (such as infra |
https://en.wikipedia.org/wiki/Image%20compression | Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.
Lossy and lossless image compression
Image compression may be lossy or lossless. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics. Lossy compression methods, especially when used at low bit rates, introduce compression artifacts. Lossy methods are especially suitable for natural images such as photographs in applications where minor (sometimes imperceptible) loss of fidelity is acceptable to achieve a substantial reduction in bit rate. Lossy compression that produces negligible differences may be called visually lossless.
Methods for lossy compression:
Transform coding – This is the most commonly used method.
Discrete Cosine Transform (DCT) – The most widely used form of lossy compression. It is a type of Fourier-related transform, and was originally developed by Nasir Ahmed, T. Natarajan and K. R. Rao in 1974. The DCT is sometimes referred to as "DCT-II" in the context of a family of discrete cosine transforms (see discrete cosine transform). It is generally the most efficient form of image compression.
DCT is used in JPEG, the most popular lossy format, and the more recent HEIF.
The more recently developed wavelet transform is also used extensively, followed by quantization and entropy coding.
Color quantization - Reducing the color space to a few "representative" colors in the image. The selected colors are specified in the color palette in the header of the compressed image. Each pixel just references the index of a color in the color palette. This method can be combined with dithering to avoid posterization.
Whole-image palette, typically 256 colors, used in GIF and PNG file formats.
block palette, typically 2 or 4 colors for each block of 4x4 pixels, used in BTC, CCC, S2TC, and S3TC.
Chroma subsampling. This takes advantage of the fact that the human eye perceives spatial changes of brightness more sharply than those of color, by averaging or dropping some of the chrominance information in the image.
Fractal compression.
More recently, methods based on Machine Learning were applied, using Multilayer perceptrons, Convolutional neural networks and Generative adversarial networks. Implementations are available in OpenCV, TensorFlow, MATLAB's Image Processing Toolbox (IPT), and the High-Fidelity Generative Image Compression (HiFiC) open source project.
Methods for lossless compression:
Run-length encoding – used in default method in PCX and as one of possible in BMP, TGA, TIFF
Area image compression
Predictive coding – used in DPCM
Entropy encoding – the two most common entropy encoding techniques are arithmetic co |
https://en.wikipedia.org/wiki/Telecommunications%20network | A telecommunications network is a group of nodes interconnected by telecommunications links that are used to exchange messages between the nodes. The links may use a variety of technologies based on the methodologies of circuit switching, message switching, or packet switching, to pass messages and signals.
Multiple nodes may cooperate to pass the message from an originating node to the destination node, via multiple network hops. For this routing function, each node in the network is assigned a network address for identification and locating it on the network. The collection of addresses in the network is called the address space of the network.
Examples of telecommunications networks include computer networks, the Internet, the public switched telephone network (PSTN), the global Telex network, the aeronautical ACARS network, and the wireless radio networks of cell phone telecommunication providers.
Network structure
In general, every telecommunications network conceptually consists of three parts, or planes (so-called because they can be thought of as being and often are, separate overlay networks):
The data plane (also user plane, bearer plane, or forwarding plane) carries the network's users' traffic, the actual payload.
The control plane carries control information (also known as signaling).
The management plane carries the operations, administration and management traffic required for network management. The management plane is sometimes considered a part of the control plane.
Data networks
Data networks are used extensively throughout the world for communication between individuals and organizations. Data networks can be connected to allow users seamless access to resources that are hosted outside of the particular provider they are connected to. The Internet is the best example of the internetworking of many data networks from different organizations.
Terminals attached to IP networks like the Internet are addressed using IP addresses. Protocols of the Internet protocol suite (TCP/IP) provide the control and routing of messages across the and IP data network. There are many different network structures that IP can be used across to efficiently route messages, for example:
Wide area networks (WAN)
Metropolitan area networks (MAN)
Local area networks (LAN)
There are three features that differentiate MANs from LANs or WANs:
The area of the network size is between LANs and WANs. The MAN will have a physical area between 5 and 50 km in diameter.
MANs do not generally belong to a single organization. The equipment that interconnects the network, the links, and the MAN itself are often owned by an association or a network provider that provides or leases the service to others.
A MAN is a means for sharing resources at high speeds within the network. It often provides connections to WAN networks for access to resources outside the scope of the MAN.
Data center networks also rely highly on TCP/IP for communication across machin |
https://en.wikipedia.org/wiki/Embedded%20system | An embedded system is a computer system—a combination of a computer processor, computer memory, and input/output peripheral devices—that has a dedicated function within a larger mechanical or electronic system. It is embedded as part of a complete device often including electrical or electronic hardware and mechanical parts.
Because an embedded system typically controls physical operations of the machine that it is embedded within, it often has real-time computing constraints. Embedded systems control many devices in common use. , it was estimated that ninety-eight percent of all microprocessors manufactured were used in embedded systems.
Modern embedded systems are often based on microcontrollers (i.e. microprocessors with integrated memory and peripheral interfaces), but ordinary microprocessors (using external chips for memory and peripheral interface circuits) are also common, especially in more complex systems. In either case, the processor(s) used may be types ranging from general purpose to those specialized in a certain class of computations, or even custom designed for the application at hand. A common standard class of dedicated processors is the digital signal processor (DSP).
Since the embedded system is dedicated to specific tasks, design engineers can optimize it to reduce the size and cost of the product and increase its reliability and performance. Some embedded systems are mass-produced, benefiting from economies of scale.
Embedded systems range in size from portable personal devices such as digital watches and MP3 players to bigger machines like home appliances, industrial assembly lines, robots, transport vehicles, traffic light controllers, and medical imaging systems. Often they constitute subsystems of other machines like avionics in aircraft and astrionics in spacecraft. Large installations like factories, pipelines and electrical grids rely on multiple embedded systems networked together. Generalized through software customization, embedded systems such as programmable logic controllers frequently comprise their functional units.
Embedded systems range from those low in complexity, with a single microcontroller chip, to very high with multiple units, peripherals and networks, which may reside in equipment racks or across large geographical areas connected via long-distance communications lines.
History
Background
The origins of the microprocessor and the microcontroller can be traced back to the MOS integrated circuit, which is an integrated circuit chip fabricated from MOSFETs (metal–oxide–semiconductor field-effect transistors) and was developed in the early 1960s. By 1964, MOS chips had reached higher transistor density and lower manufacturing costs than bipolar chips. MOS chips further increased in complexity at a rate predicted by Moore's law, leading to large-scale integration (LSI) with hundreds of transistors on a single MOS chip by the late 1960s. The application of MOS LSI chips to computing was the bas |
https://en.wikipedia.org/wiki/Turing%20tarpit | A Turing tarpit (or Turing tar-pit) is any programming language or computer interface that allows for flexibility in function but is difficult to learn and use because it offers little or no support for common tasks. The phrase was coined in 1982 by Alan Perlis in the Epigrams on Programming:
In any Turing complete language, it is possible to write any computer program, so in a very rigorous sense nearly all programming languages are equally capable. However, having that theoretical ability is not the same as usefulness in practice. Turing tarpits are characterized by having a simple abstract machine that requires the user to deal with many details in the solution of a problem. At the extreme opposite are interfaces that can perform very complex tasks with little human intervention but become obsolete if requirements change slightly.
Some esoteric programming languages, such as Brainfuck or Malbolge, are specifically referred to as "Turing tarpits" because they deliberately implement the minimum functionality necessary to be classified as Turing complete languages. Using such languages is a form of mathematical recreation: programmers can work out how to achieve basic programming constructs in an extremely difficult but mathematically Turing-equivalent language.
See also
Greenspun's tenth rule
Write-only language
Zawinski's law of software envelopment
References
Further reading
G. Fischer, A.C. Lemke, "Constrained Design Processes: Steps Toward Convivial Computing", Technical Report CU-CS-369-87, Colorado University, USA.
E.L. Hutchins, J.D. Hollan, D.A. Norman, . Also found in
Esolangs, Turing Tarpit.
Alan Turing
Recreational mathematics
Theory of computation
Software engineering folklore |
https://en.wikipedia.org/wiki/Grep | grep is a command-line utility for searching plain-text data sets for lines that match a regular expression. Its name comes from the ed command g/re/p (global / regular expression search / and print), which has the same effect. grep was originally developed for the Unix operating system, but later available for all Unix-like systems and some others such as OS-9.
History
Before it was named, grep was a private utility written by Ken Thompson to search files for certain patterns. Doug McIlroy, unaware of its existence, asked Thompson to write such a program. Responding that he would think about such a utility overnight, Thompson actually corrected bugs and made improvements for about an hour on his own program called s (short for "search"). The next day he presented the program to McIlroy, who said it was exactly what he wanted. Thompson's account may explain the belief that grep was written overnight.
Thompson wrote the first version in PDP-11 assembly language to help Lee E. McMahon analyze the text of The Federalist Papers to determine authorship of the individual papers. The ed text editor (also authored by Thompson) had regular expression support but could not be used to search through such a large amount of text, as it loaded the entire file into memory to enable random access editing, so Thompson excerpted that regexp code into a standalone tool which would instead process arbitrarily long files sequentially without buffering too much into memory. He chose the name because in ed, the command g/re/p would print all lines featuring a specified pattern match. grep was first included in Version 4 Unix. Stating that it is "generally cited as the prototypical software tool", McIlroy credited grep with "irrevocably ingraining" Thompson's tools philosophy in Unix.
Implementations
A variety of grep implementations are available in many operating systems and software development environments. Early variants included egrep and fgrep, introduced in Version 7 Unix. The "egrep" variant supports an extended regular expression syntax added by Alfred Aho after Ken Thompson's original regular expression implementation. The "fgrep" variant searches for any of a list of fixed strings using the Aho–Corasick string matching algorithm. Binaries of these variants exist in modern systems, usually linking to grep or calling grep as a shell script with the appropriate flag added, e.g. exec grep -E "$@". egrep and fgrep, while commonly deployed on POSIX systems, to the point the POSIX specification mentions their widespread existence, are actually not part of POSIX.
Other commands contain the word "grep" to indicate they are search tools, typically ones that rely on regular expression matches. The pgrep utility, for instance, displays the processes whose names match a given regular expression.
In the Perl programming language, grep is the name of the built-in function that finds elements in a list that satisfy a certain property. This higher-order function is typi |
https://en.wikipedia.org/wiki/Entropy%20coding | In information theory, an entropy coding (or entropy encoding) is any lossless data compression method that attempts to approach the lower bound declared by Shannon's source coding theorem, which states that any lossless data compression method must have expected code length greater or equal to the entropy of the source.
More precisely, the source coding theorem states that for any source distribution, the expected code length satisfies , where is the number of symbols in a code word, is the coding function, is the number of symbols used to make output codes and is the probability of the source symbol. An entropy coding attempts to approach this lower bound.
Two of the most common entropy coding techniques are Huffman coding and arithmetic coding.
If the approximate entropy characteristics of a data stream are known in advance (especially for signal compression), a simpler static code may be useful.
These static codes include universal codes (such as Elias gamma coding or Fibonacci coding) and Golomb codes (such as unary coding or Rice coding).
Since 2014, data compressors have started using the asymmetric numeral systems family of entropy coding techniques, which allows combination of the compression ratio of arithmetic coding with a processing cost similar to Huffman coding.
Entropy as a measure of similarity
Besides using entropy coding as a way to compress digital data, an entropy encoder can also be used to measure the amount of similarity between streams of data and already existing classes of data. This is done by generating an entropy coder/compressor for each class of data; unknown data is then classified by feeding the uncompressed data to each compressor and seeing which compressor yields the highest compression. The coder with the best compression is probably the coder trained on the data that was most similar to the unknown data.
See also
Arithmetic coding
Asymmetric numeral systems (ANS)
Context-adaptive binary arithmetic coding (CABAC)
Huffman coding
Range coding
References
External links
Information Theory, Inference, and Learning Algorithms, by David MacKay (2003), gives an introduction to Shannon theory and data compression, including the Huffman coding and arithmetic coding.
Source Coding, by T. Wiegand and H. Schwarz (2011).
Entropy coding
Entropy and information |
https://en.wikipedia.org/wiki/Artificial%20Intelligence%20Markup%20Language | Artificial Intelligence Markup Language (AIML) is an XML dialect for creating natural language software agents.
History
The XML dialect called AIML was developed by Richard Wallace and a worldwide free software community between 1995 and 2002. AIML formed the basis for what was initially a highly extended Eliza called "A.L.I.C.E." ("Artificial Linguistic Internet Computer Entity"), which won the annual Loebner Prize Competition in Artificial Intelligence three times, and was also the Chatterbox Challenge Champion in 2004.
Because the A.L.I.C.E. AIML set was released under the GNU GPL, and because most AIML interpreters are offered under a free or open source license, many "Alicebot clones" have been created based upon the original implementation of the program and its AIML knowledge base. Free AIML sets in several languages have been developed and made available by the user community. There are AIML interpreters available in Java, Ruby, Python, C++, C#, Pascal, and other languages (see below ).
A semi-formal specification and a W3C XML Schema for AIML are available.
Since early 2013, The A.L.I.C.E foundation has been working on a draft specification for AIML 2.0.
Elements of AIML
AIML contains several elements. The most important of these are described in further detail below.
Categories
Categories in AIML form the fundamental unit of knowledge. A category consists of at least two further elements: the pattern and template elements. Here is a simple category:
<category>
<pattern>WHAT IS YOUR NAME</pattern>
<template>My name is Michael N.S Evanious.</template>
</category>
When this category is loaded, an AIML bot will respond to the input "What is your name" with the response "My name is Michael N.S Evanious."
Patterns
A pattern is a string of characters intended to match one or more user inputs. A literal pattern like
WHAT IS YOUR NAME
will match only one input, ignoring case: "what is your name". But patterns may also contain wildcards, which match one or more words. A pattern like
WHAT IS YOUR *
will match an infinite number of inputs, including "what is your name", "what is your shoe size", "what is your purpose in life", etc.
The AIML pattern syntax is a very simple pattern language, substantially less complex than regular expressions and as such less than level 3 in the Chomsky hierarchy.
To compensate for the simple pattern matching capabilities, AIML interpreters can provide preprocessing functions to expand abbreviations, remove misspellings, etc.
The AIML syntax itself is at least as complex as finite state machines and as such at least of level 3 in the Chomsky hierarchy. This is because a state correlates to one topic. To implement that behavior, the topic should have a "*" Pattern to make sure, that the state is not left accidentally. A state transit is implemented with the Tag. This way, the bot will be able to "remember" the topic talked about or even user privileges, which are gained during the chat.
Temp |
https://en.wikipedia.org/wiki/Parallax%20scrolling | Parallax scrolling is a technique in computer graphics where background images move past the camera more slowly than foreground images, creating an illusion of depth in a 2D scene of distance. The technique grew out of the multiplane camera technique used in traditional animation since the 1930s.
Parallax scrolling was popularized in 2D computer graphics with its introduction to video games in the early 1980s. Some parallax scrolling was used in the arcade video game Jump Bug (1981). It used a limited form of parallax scrolling with the main scene scrolling while the starry night sky is fixed and clouds move slowly, adding depth to the scenery. The following year, Moon Patrol (1982) implemented a full form of parallax scrolling, with three separate background layers scrolling at different speeds, simulating the distance between them. Moon Patrol is often credited with popularizing parallax scrolling. Jungle King (1982), later called Jungle Hunt, also had parallax scrolling, and was released a month after Moon Patrol in June 1982.
Methods
There are four main methods of parallax scrolling used in titles for arcade system board, video game console and personal computer systems.
Layer method
Some display systems support multiple background layers that can be scrolled independently in horizontal and vertical directions and composited on one another, simulating a multiplane camera. On such a display system, a game can produce parallax by simply changing each layer's position by a different amount in the same direction. Layers that move more quickly are perceived to be closer to the virtual camera. Layers can be placed in front of the playfield—the layer containing the objects with which the player interacts—for various reasons such as to provide increased dimension, obscure some of the action of the game, or distract the player.
Sprite method
Programmers may also make pseudo-layers of sprites—individually controllable moving objects drawn by hardware on top of or behind the layers—if they are available on the display system. For instance Star Force, an overhead-view vertically scrolling shooter for NES, used this for its starfield, and Final Fight for the Super NES used this technique for the layer immediately in front of the main playfield.
The Amiga computer has sprites which can have any height and can be set horizontal with the copper co-processor, which makes them ideal for this purpose.
Risky Woods on the Amiga uses sprites multiplexed with the copper to create an entire fullscreen parallax background layer as an alternative to the system's dual playfield mode.
Repeating pattern/animation method
Scrolling displays built up of individual tiles can be made to 'float' over a repeating background layer by animating the individual tiles' bitmaps in order to portray the parallax effect. Color cycling can be used to animate tiles quickly on the whole screen. This software effect gives the illusion of another (hardware) layer. Many games use |
https://en.wikipedia.org/wiki/Identity%20map%20pattern | In the design of DBMS, the identity map pattern is a database access design pattern used to improve performance by providing a context-specific, in-memory cache to prevent duplicate retrieval of the same object data from the database.
If the requested data has already been loaded from the database, the identity map returns the same instance of the already instantiated object, but if it has not been loaded yet, it loads it and stores the new object in the map. In this way, it follows a similar principle to lazy loading.
There are 4 types of identity maps
Explicit
Generic
Session
Class
See also
Active record
Identity function
Map (mathematics)
Lazy loading
References
Architectural pattern (computer science)
Software design patterns |
https://en.wikipedia.org/wiki/Cepstrum | In Fourier analysis, the cepstrum (; plural cepstra, adjective cepstral) is the result of computing the inverse Fourier transform (IFT) of the logarithm of the estimated signal spectrum. The method is a tool for investigating periodic structures in frequency spectra. The power cepstrum has applications in the analysis of human speech.
The term cepstrum was derived by reversing the first four letters of spectrum. Operations on cepstra are labelled quefrency analysis (or quefrency alanysis), liftering, or cepstral analysis. It may be pronounced in the two ways given, the second having the advantage of avoiding confusion with kepstrum.
Origin
The concept of the cepstrum was introduced in 1963 by B. P. Bogert, M. J. Healy, and J. W. Tukey. It serves as a tool to investigate periodic structures in frequency spectra. Such effects are related to noticeable echos or reflections in the signal, or to the occurrence of harmonic frequencies (partials, overtones). Mathematically it deals with the problem of deconvolution of signals in the frequency space.
References to the Bogert paper, in a bibliography, are often edited incorrectly. The terms "quefrency", "alanysis", "cepstrum" and "saphe" were invented by the authors by rearranging the letters in frequency, analysis, spectrum, and phase. The invented terms are defined in analogy to the older terms.
General definition
The cepstrum is the result of following sequence of mathematical operations:
transformation of a signal from the time domain to the frequency domain
computation of the logarithm of the spectral amplitude
transformation to frequency domain, where the final independent variable, the quefrency, has a time scale.
Types
The cepstrum is used in many variants. Most important are:
power cepstrum: The logarithm is taken from the "power spectrum"
complex cepstrum: The logarithm is taken from the spectrum, which is calculated via Fourier analysis
The following abbreviations are used in the formulas to explain the cepstrum:
Power cepstrum
The "cepstrum" was originally defined as power cepstrum by the following relationship:
The power cepstrum has main applications in analysis of sound and vibration signals. It is a complementary tool to spectral analysis.
Sometimes it is also defined as:
Due to this formula, the cepstrum is also sometimes called the spectrum of a spectrum. It can be shown that both formulas are consistent with each other as the frequency spectral distribution remains the same, the only difference being a scaling factor which can be applied afterwards. Some articles prefer the second formula.
Other notations are possible due to the fact that the log of the power spectrum is equal to the log of the spectrum if a scaling factor 2 is applied:
and therefore:
which provides a relationship to the real cepstrum (see below).
Further, it shall be noted, that the final squaring operation in the formula for the power spectrum is sometimes called unnecessary and therefore sometimes |
https://en.wikipedia.org/wiki/Colocation%20centre | A colocation center (also spelled co-location, or shortened to colo) or "carrier hotel", is a type of data centre where equipment, space, and bandwidth are available for rental to retail customers. Colocation facilities provide space, power, cooling, and physical security for the server, storage, and networking equipment of other firms and also connect them to a variety of telecommunications and network service providers with a minimum of cost and complexity.
Configuration
Many colocation providers sell to a wide range of customers, ranging from large enterprises to small companies. Typically, the customer owns the information technology (IT) equipment and the facility provides power and cooling. Customers retain control over the design and usage of their equipment, but daily management of the data center and facility are overseen by the multi-tenant colocation provider.
Cabinets – A cabinet is a locking unit that holds a server rack. In a multi-tenant data center, servers within cabinets share raised-floor space with other tenants, in addition to sharing power and cooling infrastructure.
Cages – A cage is dedicated server space within a traditional raised-floor data center; it is surrounded by mesh walls and entered through a locking door. Cages share power and cooling infrastructure with other data center tenants.
Suites – A suite is a dedicated, private server space within a traditional raised-floor data center; it is fully enclosed by solid partitions and entered through a locking door. Suites may share power and cooling infrastructure with other data center tenants, or have these resources provided on a dedicated basis.
Modules – data center modules are purpose-engineered modules and components to offer scalable data center capacity. They typically use standardized components, which make them easily added, integrated or retrofitted into existing data centers, and cheaper and easier to build. In a colocation environment, the data center module is a data center within a data center, with its own steel walls and security protocol, and its own cooling and power infrastructure. "A number of colocation companies have praised the modular approach to data centers to better match customer demand with physical build outs, and allow customers to buy a data center as a service, paying only for what they consume."
Building features
Buildings with data centres inside them are often easy to recognize by the amount of cooling equipment located outside or on the roof.
Colocation facilities have many other special characteristics:
Fire protection systems, including passive and active elements, as well as implementation of fire prevention programmes in operations. Smoke detectors are usually installed to provide early warning of a developing fire by detecting particles generated by smouldering components prior to the development of flame. This allows investigation, interruption of power, and manual fire suppression using hand held fire extinguishers b |
https://en.wikipedia.org/wiki/Telephone%20company | A telephone company is a kind of communications service provider (CSP), more precisely a telecommunications service provider (TSP), that provides telecommunications services such as telephony and data communications access. Many telephone companies were at one time government agencies or privately owned but state-regulated monopolies. The government agencies are often referred to, primarily in Europe, as PTTs (postal, telegraph and telephone services).
Telephone companies are common carriers, and in the United States are also called local exchange carriers. With the advent of mobile telephony, telephone companies now include wireless carriers, or mobile network operators.
Most telephone companies now also function as internet service providers (ISPs), and the distinction between a telephone company and an ISP may disappear completely over time, as the current trend for supplier convergence in the industry continues.
In the past, most TSPs were government owned and operated in most countries, due to the nature of capital expenditure involved in it. But today there are many private players in most regions of the world, and even most of the government owned companies have been privatized.
History
In 1913, the Kingsbury Commitment allowed more than 20,000 independent telephone companies in the United States to use the long distance trunks of Bell Telephone Company.
Popular culture
Comedian Lily Tomlin frequently satirized the telephone industry (and the country's then-dominant Bell System in particular) with a skit playing the telephone operator Ernestine. Ernestine, who became one of Tomlin's trademark characters, was perhaps most famous for the following line: "We don't care; we don't have to. We're the phone company."
In the satirical 1967 film The President's Analyst, The Phone Company (TPC) is depicted as plotting to enslave humanity by replacing landlines with brain-implanted mobile phones.
In the 1988 video game Zak McKracken and the Alien Mindbenders, The Phone Company (TPC) was used by the Caponian aliens to secretly reduce the intelligence of humans.
See also
Bell Telephone Company, forerunner of AT&T in the U.S.
Internet telephony service provider
Competitive local exchange carrier (in Canada and the U.S.)
Communications service provider
History of the telephone
Incumbent local exchange carrier (of the Bell System)
Individual communication services and tariffs
List of telephone operating companies
List of mobile network operators
Mobile network operator
Plain old telephone service (POTS)
Public switched telephone network
Telecommunications Industry Association (for the development of U.S. telecom standards)
Regional Bell Operating Company (in the U.S.)
Service provider
References and notes
Notes
Citations
Bibliography
Huurdeman, Anton A. The Worldwide History Of Telecommunications, Wiley-IEEE, 2003, ,
External links
Village Telco – site about microtelcos
Business Telecoms Company – site about business broa |
https://en.wikipedia.org/wiki/Peering | In computer networking, peering is a voluntary interconnection of administratively separate Internet networks for the purpose of exchanging traffic between the "down-stream" users of each network. Peering is settlement-free, also known as "bill-and-keep" or "sender keeps all", meaning that neither party pays the other in association with the exchange of traffic; instead, each derives and retains revenue from its own customers.
An agreement by two or more networks to peer is instantiated by a physical interconnection of the networks, an exchange of routing information through the Border Gateway Protocol (BGP) routing protocol, tacit agreement to norms of conduct and, in some extraordinarily rare cases (0.07%), a formalized contractual document.
In 0.02% of cases the word "peering" is used to describe situations where there is some settlement involved. Because these outliers can be viewed as creating ambiguity, the phrase "settlement-free peering" is sometimes used to explicitly denote normal cost-free peering.
History
The first Internet exchange point was the Commercial Internet eXchange (CIX), formed by Alternet/UUNET (now Verizon Business), PSI, and CERFNET to exchange traffic without regard for whether the traffic complied with the acceptable use policy (AUP) of the NSFNet or ANS' interconnection policy. The CIX infrastructure consisted of a single router, managed by PSI, and was initially located in Santa Clara, California. Paying CIX members were allowed to attach to the router directly or via leased lines. After some time, the router was also attached to the Pacific Bell SMDS cloud. The router was later moved to the Palo Alto Internet Exchange, or PAIX, which was developed and operated by Digital Equipment Corporation (DEC). Because the CIX operated at OSI layer 3, rather than OSI layer 2, and because it was not neutral, in the sense that it was operated by one of its participants rather than by all of them collectively, and it conducted lobbying activities supported by some of its participants and not by others, it would not today be considered an Internet exchange point. Nonetheless, it was the first thing to bear that name.
The first exchange point to resemble modern, neutral, Ethernet-based exchanges was the Metropolitan Area Ethernet, or MAE, in Tysons Corner, Virginia. When the United States government de-funded the NSFNET backbone, Internet exchange points were needed to replace its function, and initial governmental funding was used to aid the preexisting MAE and bootstrap three other exchanges, which they dubbed NAPs, or "Network Access Points," in accordance with the terminology of the National Information Infrastructure document. All four are now defunct or no longer functioning as Internet exchange points:
MAE-East – Located in Tysons Corner, Virginia, and later relocated to Ashburn, Virginia
Chicago NAP – Operated by Ameritech and located in Chicago, Illinois
New York NAP – Operated by Sprint and located in Pennsauken, New |
https://en.wikipedia.org/wiki/Package%20manager | A package manager or package-management system is a collection of software tools that automates the process of installing, upgrading, configuring, and removing computer programs for a computer in a consistent manner.
A package manager deals with packages, distributions of software and data in archive files. Packages contain metadata, such as the software's name, description of its purpose, version number, vendor, checksum (preferably a cryptographic hash function), and a list of dependencies necessary for the software to run properly. Upon installation, metadata is stored in a local package database. Package managers typically maintain a database of software dependencies and version information to prevent software mismatches and missing prerequisites. They work closely with software repositories, binary repository managers, and app stores.
Package managers are designed to eliminate the need for manual installs and updates. This can be particularly useful for large enterprises whose operating systems typically consist of hundreds or even tens of thousands of distinct software packages.
History
An early package manager was SMIT (and its backend installp) from IBM AIX. SMIT was introduced with AIX 3.0 in 1989.
Early package managers, from around 1994, had no automatic dependency resolution but could already drastically simplify the process of adding and removing software from a running system.
By around 1995, beginning with CPAN, package managers began doing the work of downloading packages from a repository, automatically resolving its dependencies and installing them as needed, making it much easier to install, uninstall and update software from a system.
Functions
A software package is an archive file containing a computer program as well as necessary metadata for its deployment. The computer program can be in source code that has to be compiled and built first. Package metadata include package description, package version, and dependencies (other packages that need to be installed beforehand).
Package managers are charged with the task of finding, installing, maintaining or uninstalling software packages upon the user's command. Typical functions of a package management system include:
Working with file archivers to extract package archives
Ensuring the integrity and authenticity of the package by verifying their checksums and digital certificates, respectively
Looking up, downloading, installing, or updating existing software from a software repository or app store
Grouping packages by function to reduce user confusion
Managing dependencies to ensure a package is installed with all packages it requires, thus avoiding "dependency hell"
Challenges with shared libraries
Computer systems that rely on dynamic library linking, instead of static library linking, share executable libraries of machine instructions across packages and applications. In these systems, conflicting relationships between different packages requiring different versio |
https://en.wikipedia.org/wiki/London%20Internet%20Exchange | The London Internet Exchange ("LINX") is a mutually governed Internet exchange point (IXP) that provides peering services and public policy representation to network operators (over 950 different ASNs). It was founded in 1994 in London. LINX operates IXPs in London, Manchester, Scotland and Wales in the United Kingdom and Northern Virginia in the United States.
LINX was founded in 1994 by a group of ISPs and educational networks and is a founding member of Euro-IX, a Europe-wide alliance of Internet Exchanges. It is one of the largest neutral IXPs in Europe in terms of average throughput.
LINX is a non-profit organization (a company limited by a guarantee). Networks join LINX as members and sign a memorandum of understanding. Members collectively 'own' the company, and all members have a single vote at AGMs and EGMs in matters relating to finances, constitution, and what activities LINX may carry out. Members also periodically elect the LINX non-executive board of directors. Members meet at regular LINX meetings to discuss technical, corporate governance, and regulatory matters. LINX has a mandate to not actively compete with its members.
History
In November 1994, using a donated piece of equipment no bigger than a video recorder and without any written contracts, five UK-based Internet service providers (ISPs) linked their networks to exchange data and avoid paying high transatlantic bandwidth costs.
LINX effectively began when two ISPs (PIPEX and UK Net) linked their networks via a 64-kilobit serial link to save the cost and time delay involved in routing data across the Atlantic to US Internet exchanges.
When Demon Internet, UKERNA – the UK academic network – and other ISPs showed interest in establishing similar serial links, Keith Mitchell, then chief technical officer of PIPEX, initiated a meeting with BT to discuss the creation of a London-based Internet exchange.
PIPEX provided the LINX founders with a Cisco Catalyst 1200 switch with eight 10-megabit ports. Rack space was leased at a then virtually empty data centre operated by Telehouse International Corporation of Europe Ltd at Coriander Avenue in London's Dockland.
Switching the first data through the Telehouse hub was accomplished by primarily technical specialists who were unconcerned about the formalities of legal contracts. However, while PIPEX continued to provide administrative and technical oversight, the need for a formal constitution was eventually recognized.
The solution was to form a company limited by guarantee. Lawyers produced a draft memorandum and constitution which was extensively modified by members. The company was formed in 1995, and a board of five non-executive directors was elected, with Keith Mitchell as the initial chairman.
Not for profit organization
From the beginning, it was agreed that LINX would be a non-profit organization run for the benefit of members and governed collectively through regular member meetings, a practice which continues to th |
https://en.wikipedia.org/wiki/Painter%27s%20algorithm | The painter’s algorithm (also depth-sort algorithm and priority fill) is an algorithm for visible surface determination in 3D computer graphics that works on a polygon-by-polygon basis rather than a pixel-by-pixel, row by row, or area by area basis of other Hidden-Surface Removal algorithms. The painter’s algorithm creates images by sorting the polygons within the image by their depth and placing each polygon in order from the farthest to the closest object.
The painter's algorithm was initially proposed as a basic method to address the Hidden-surface determination problem by Martin Newell, Richard Newell, and Tom Sancha in 1972, while all three were working at CADCentre. The name "painter's algorithm" refers to the technique employed by many painters where they begin by painting distant parts of a scene before parts that are nearer, thereby covering some areas of distant parts. Similarly, the painter's algorithm sorts all the polygons in a scene by their depth and then paints them in this order, farthest to closest. It will paint over the parts that are normally not visible — thus solving the visibility problem — at the cost of having painted invisible areas of distant objects. The ordering used by the algorithm is called a depth order' and does not have to respect the numerical distances to the parts of the scene: the essential property of this ordering is, rather, that if one object obscures part of another, then the first object is painted after the object that it obscures. Thus, a valid ordering can be described as a topological ordering of a directed acyclic graph representing occlusions between objects.
Algorithm
Conceptually Painter's Algorithm works as follows:
Sort each polygon by depth
Place each polygon from the farthest polygon to the closest polygon
Pseudocode
sort polygons by depth for each polygon p:
for each pixel that p covers:
paint p.color on pixel Time complexity
The painter's algorithm's time-complexity is heavily dependent on the sorting algorithm used to order the polygons. Assuming the use of the most optimal sorting algorithm, painter's algorithm has a worst-case complexity of O(n log n + m*n), where n is the number of polygons and m is the number of pixels to be filled.
Space complexity
The painter's algorithm's worst-case space-complexity is O(n+m), where n is the number of polygons and m'' is the number of pixels to be filled.
Advantages
There are two primary technical requisites that favor the use of the painter’s algorithm.
Basic graphical structure
The painter's algorithm is not as complex in structure as its other depth sorting algorithm counterparts. Components such as the depth-based rendering order, as employed by the painter’s algorithm, are one of the simplest ways to designate the order of graphical production. This simplicity makes it useful in basic computer graphics output scenarios where an unsophisticated render will need to be made with little struggle.
Memory effi |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.