AI For Mba Students

AI For Mba Students — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

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  Apache ORC

  Apache ORC (Optimized Row Columnar) is a free and open-source column-oriented data storage format. It is similar to the other columnar-storage file formats available in the Hadoop ecosystem such as RCFile and Parquet. It is used by most of the data processing frameworks Apache Spark, Apache Hive, Apache Flink, and Apache Hadoop. In February 2013, the Optimized Row Columnar (ORC) file format was announced by Hortonworks in collaboration with Facebook. A calendar month later, the Apache Parquet format was announced, developed by Cloudera and Twitter. Apache ORC format is widely supported including Amazon Web Services' Glue,Google Cloud Platform's BigQuery, and Pandas (software). == History ==

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  Comet (programming)

  Comet is a web application model in which a long-held HTTPS request allows a web server to push data to a browser, without the browser explicitly requesting it. Comet is an umbrella term, encompassing multiple techniques for achieving this interaction. All these methods rely on features included by default in browsers, such as JavaScript, rather than on non-default plugins. The Comet approach differs from the original model of the web, in which a browser requests a complete web page at a time. The use of Comet techniques in web development predates the use of the word Comet as a neologism for the collective techniques. Comet is known by several other names, including Ajax Push, Reverse Ajax, Two-way-web, HTTP Streaming, and HTTP server push among others. The term Comet is not an acronym, but was coined by Alex Russell in his 2006 blog post. In recent years, the standardisation and widespread support of WebSocket and Server-sent events has rendered the Comet model obsolete. == History == === Early Java applets === The ability to embed Java applets into browsers (starting with Netscape Navigator 2.0 in March 1996) made two-way sustained communications possible, using a raw TCP socket to communicate between the browser and the server. This socket can remain open as long as the browser is at the document hosting the applet. Event notifications can be sent in any format – text or binary – and decoded by the applet. === The first browser-to-browser communication framework === The very first application using browser-to-browser communications was Tango Interactive, implemented in 1996–98 at the Northeast Parallel Architectures Center (NPAC) at Syracuse University using DARPA funding. TANGO architecture has been patented by Syracuse University. TANGO framework has been extensively used as a distance education tool. The framework has been commercialized by CollabWorx and used in a dozen or so Command&Control and Training applications in the United States Department of Defense. === First Comet applications === The first set of Comet implementations dates back to 2000, with the Pushlets, Lightstreamer, and KnowNow projects. Pushlets, a framework created by Just van den Broecke, was one of the first open source implementations. Pushlets were based on server-side Java servlets, and a client-side JavaScript library. Bang Networks – a Silicon Valley start-up backed by Netscape co-founder Marc Andreessen – had a lavishly financed attempt to create a real-time push standard for the entire web. In April 2001, Chip Morningstar began developing a Java-based (J2SE) web server which used two HTTP sockets to keep open two communications channels between the custom HTTP server he designed and a client designed by Douglas Crockford; a functioning demo system existed as of June 2001. The server and client used a messaging format that the founders of State Software, Inc. assented to coin as JSON following Crockford's suggestion. The entire system, the client libraries, the messaging format known as JSON and the server, became the State Application Framework, parts of which were sold and used by Sun Microsystems, Amazon.com, EDS and Volkswagen. In March 2006, software engineer Alex Russell coined the term Comet in a post on his personal blog. The new term was a play on Ajax (Ajax and Comet both being common household cleaners in the USA). In 2006, some applications exposed those techniques to a wider audience: Meebo’s multi-protocol web-based chat application enabled users to connect to AOL, Yahoo, and Microsoft chat platforms through the browser; Google added web-based chat to Gmail; JotSpot, a startup since acquired by Google, built Comet-based real-time collaborative document editing. New Comet variants were created, such as the Java-based ICEfaces JSF framework (although they prefer the term "Ajax Push"). Others that had previously used Java-applet based transports switched instead to pure-JavaScript implementations. == Implementations == Comet applications attempt to eliminate the limitations of the page-by-page web model and traditional polling by offering two-way sustained interaction, using a persistent or long-lasting HTTP connection between the server and the client. Since browsers and proxies are not designed with server events in mind, several techniques to achieve this have been developed, each with different benefits and drawbacks. The biggest hurdle is the HTTP 1.1 specification, which states "this specification... encourages clients to be conservative when opening multiple connections". Therefore, holding one connection open for real-time events has a negative impact on browser usability: the browser may be blocked from sending a new request while waiting for the results of a previous request, e.g., a series of images. This can be worked around by creating a distinct hostname for real-time information, which is an alias for the same physical server. This strategy is an application of domain sharding. Specific methods of implementing Comet fall into two major categories: streaming and long polling. === Streaming === An application using streaming Comet opens a single persistent connection from the client browser to the server for all Comet events. These events are incrementally handled and interpreted on the client side every time the server sends a new event, with neither side closing the connection. Specific techniques for accomplishing streaming Comet include the following: ==== Hidden iframe ==== A basic technique for dynamic web application is to use a hidden iframe HTML element (an inline frame, which allows a website to embed one HTML document inside another). This invisible iframe is sent as a chunked block, which implicitly declares it as infinitely long (sometimes called "forever frame"). As events occur, the iframe is gradually filled with script tags, containing JavaScript to be executed in the browser. Because browsers render HTML pages incrementally, each script tag is executed as it is received. Some browsers require a specific minimum document size before parsing and execution is started, which can be obtained by initially sending 1–2 kB of padding spaces. One benefit of the iframes method is that it works in every common browser. Two downsides of this technique are the lack of a reliable error handling method, and the impossibility of tracking the state of the request calling process. ==== XMLHttpRequest ==== The XMLHttpRequest (XHR) object, a tool used by Ajax applications for browser–server communication, can also be pressed into service for server–browser Comet messaging by generating a custom data format for an XHR response, and parsing out each event using browser-side JavaScript; relying only on the browser firing the onreadystatechange callback each time it receives new data. === Ajax with long polling === None of the above streaming transports work across all modern browsers without negative side-effects. This forces Comet developers to implement several complex streaming transports, switching between them depending on the browser. Consequently, many Comet applications use long polling, which is easier to implement on the browser side, and works, at minimum, in every browser that supports XHR. As the name suggests, long polling requires the client to poll the server for an event (or set of events). The browser makes an Ajax-style request to the server, which is kept open until the server has new data to send to the browser, which is sent to the browser in a complete response. The browser initiates a new long polling request in order to obtain subsequent events. IETF RFC 6202 "Known Issues and Best Practices for the Use of Long Polling and Streaming in Bidirectional HTTP" compares long polling and HTTP streaming. Specific technologies for accomplishing long-polling include the following: ==== XMLHttpRequest long polling ==== For the most part, XMLHttpRequest long polling works like any standard use of XHR. The browser makes an asynchronous request of the server, which may wait for data to be available before responding. The response can contain encoded data (typically XML or JSON) or Javascript to be executed by the client. At the end of the processing of the response, the browser creates and sends another XHR, to await the next event. Thus the browser always keeps a request outstanding with the server, to be answered as each event occurs. ==== Script tag long polling ==== While any Comet transport can be made to work across subdomains, none of the above transports can be used across different second-level domains (SLDs), due to browser security policies designed to prevent cross-site scripting attacks. That is, if the main web page is served from one SLD, and the Comet server is located at another SLD (which does not have cross-origin resource sharing enabled), Comet events cannot be used to modify the HTML and DOM of the main page, using those transports. This problem can be sidestepped by creating a proxy server in

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  Creepy treehouse

  Creepy treehouse is a social media term, or internet slang, referring to websites or technologies that are used for educational purposes but regarded by students as an invasion of privacy. == History == The term was first described in 2008 by Utah Valley University instructional-design services director Jared Stein as "institutionally controlled technology/tool that emulates or mimics pre-existing [sic] technologies or tools that may already be in use by the learners, or by learners' peer groups." This was when social media such as Facebook was starting to become mainstream and professors would try and get students to interact with them on the site for educational purposes. Some professors would require their students to use Facebook or Twitter as part of class assignments. == Usage == The term was first described as "technological innovations by faculty members that make students’ skin crawl." The term also refers to online accounts and websites that users tend to avoid, especially young people who avoid visiting the pages of educators and other adults. Author Martin Weller defines creepy treehouse as a digital space where authority figures are viewed as invading younger people's privacy. One such example is a professor giving his students an option to use a popular video game to learn about history instead of writing an essay. Students in that class chose to write the essay instead as the method was previously unmentioned and it was not an unnatural method of interaction. Another example given was Blackboard Sync, a feature that was used to connect the school website Blackboard with students' Facebook accounts. == Solutions == University of Regina professor Alec Couros suggests that instead of "forcing" student participation with their own digital platforms, professors should use methods like online forums. Jason Jones of chronicle.com suggested letting students create social media groups for the class themselves and explaining why using technologies is required and important.

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  Algorithmic curation

  Algorithm curation is the selection of online media by technologies such as recommender systems and personalized search. Curation entails the selective sharing of online content and recommendations based on inferred interests. Curation algorithms implement different filter approaches, such as collaborative filtering and content-based filtering. Examples include search engine and social media products such as the Twitter feed, Facebook's News Feed, and Google Personalized Search. == History == === Early algorithmic curation === Online platforms use newsfeed algorithms to determine what content to present to each user. The volume of content published on social media platforms created a need for automated filtering, as manual review of all available content by users is not feasible. These systems function as a form of gatekeeper, shaping which new material users are exposed to and influencing knowledge, attention, and political exposure. ==== Information overload ==== Early ranking algorithms addressed information overload by surfacing the most recent or most popular posts. Later systems shifted toward ranking content based on predicted engagement, aiming to increase the time users spend on a platform. Research has found that these engagement-oriented systems can increase the spread of misinformation and contribute to political polarization as a side effect of optimising for user interaction. ==== How algorithm changes users' feeds over time ==== Algorithmic curation has been found to increase source diversity in some respects while simultaneously reducing the number of external links presented to users, which limits exposure to off-platform content. Research using agent-based modelling has examined how user behaviour, information quality, and algorithmic design interact with one another over time. === Emergence of AI === Platforms increasingly shifted from rule-based ranking systems toward machine-learning and AI-driven approaches, which allow feeds to be personalised at a larger scale and with greater responsiveness to user behaviour. For example, X (formerly Twitter) moved away from a chronological feed toward an AI-powered ranking system that personalises content for each user. These systems are capable of making ranking decisions across volumes of content and user interactions that would not be practical to handle manually. == Approach == === Filter types === ==== Collaborative filtering ==== Collaborative filtering (CF) methods create recommendations based on a person's usage patterns. CF predicts a person's preference for an item by matching their interests with those of users who have similar interests. This process allows for the sharing of ratings between users with similar profiles. CF is based on patterns of human behaviour rather than machine analysis of content itself. Users of CF systems rate items they have interacted with, and these ratings form a profile of interests. The CF system then matches that user with others who have similar profiles, and uses their ratings to generate recommendations. Collaborative filtering can be applied across various content types including text, images, music, and financial products, and can account for complex attributes such as taste and quality that are difficult to represent explicitly. ==== Content-based filtering ==== Content-based filtering (CBF) builds a user profile to represent the types of items a user has engaged with, based on keywords and attributes used to describe those items. Recommendations are generated by presenting items similar to those the user has previously engaged with or is currently viewing. The CBF method creates a profile for each item based on discrete attributes and features, and then constructs a content-based user profile using a weighted vector of those features derived from items the user has rated, purchased, or interacted with. The weights represent the relative importance of each feature, and can be computed using techniques such as Bayesian classifiers, cluster analysis, decision trees, and artificial neural networks, with the goal of estimating the probability that a user will engage with a suggested item. One application of content-based filtering is Pandora Radio, where users provide an artist, genre, or composer to generate a station, and the system surfaces music with similar attributes. == Technology == === Recommender system === Recommender systems rank and suggest content to users based on a combination of implicit and explicit user input. Implicit signals include time spent viewing or engaging with a specific item. Explicit signals include actions such as liking posts, saving store pages, reading news articles, or sharing content. === Personalized search === Personalized search aims to retrieve results most relevant to the user by incorporating contextual factors beyond the explicit query, such as past queries, browsing history, and inferred interests. Social media platforms such as X (formerly Twitter) and Bluesky generate recommendations based on similar users and the content those users interact with. Personalized search may also allow users to explicitly filter results by blocking content containing certain phrases or hashtags. For first-time users without prior history, personalized search may draw on content-based filtering to establish an initial context. Similar processes are used by search engines and retail platforms to tailor results and product recommendations to individual users. == AI contribution == Artificial intelligence contributes to algorithmic curation through machine-learning models capable of processing large volumes of data. Techniques such as deep learning and reinforcement learning allow curation algorithms to model user preferences with greater granularity alongside established filtering approaches. This enables platforms to adjust content rankings rapidly in response to user behaviour. In social media and streaming contexts, AI-driven systems arrange feeds according to predicted relevance, with the outputs shaped by patterns present in the training data. == Social media and potential impact == === Echo chambers === Social media algorithms, such as those used by X (formerly Twitter), recommend content that the system predicts a user will engage with positively. Content from accounts with differing perspectives is less likely to be surfaced, which may reduce source and topic diversity and contribute to the formation of echo chambers. For example, Facebook's news feed is designed to surface content aligned with users' prior engagement, which may reinforce existing views. This dynamic may contribute to filter bubbles, in which users are seldom exposed to content outside their existing interests. Users may further narrow their feeds by actively blocking certain content or accounts. === Over-representation === A pattern observed across social media platforms is the concentration of algorithmic visibility among a small subset of users. Content from the most active users, those with the largest followings, or those generating the most engagement tends to be surfaced more frequently, meaning a small number of accounts can account for a disproportionate share of what appears in other users' feeds.

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  JAX (software)

  JAX is a Python library for accelerator-oriented array computation and program transformation, designed for high-performance numerical computing and large-scale machine learning. It is developed by Google with contributions from Nvidia and other community contributors. It is described as bringing together a modified version of the automatic differentiation system autograd and OpenXLA's XLA (Accelerated Linear Algebra). It is designed to follow the structure and workflow of NumPy as closely as possible and works with various existing frameworks such as TensorFlow and PyTorch. The primary features of JAX are: Providing a unified NumPy-like interface to computations that run on CPU, GPU, or TPU, in local or distributed settings. Built-in Just-In-Time (JIT) compilation via OpenXLA, an open-source machine learning compiler ecosystem. Efficient evaluation of gradients via its automatic differentiation transformations. Automatic vectorization to efficiently map functions over arrays representing batches of inputs. == Libraries using Jax == Flax Equinox Optax

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  1tik

  1tik, pronounced Antik (Arabic: أنتيك; lit. "Everything is going well") is a fully Algerian instant messaging, social media and mobile payment app. designed, developed and built locally by the Algerian start-up, INTAJ Digital, with backing from the state-owned company ATM Mobilis (who's the company's main sponsor). It is described as Algeria's first super-app that is entirely designed and built by local developers. == Etymology == The name "1tik" (Arabic: أنتيك) is drawn from the popular Algerian vernacular (Antik), the neologism, which appeared several years ago, means "everything is going well" or "it's all good". == History == 1tik was officially launched and announced the 20th December 2025 by INTAJ Digital's founder Youcef Toulaib and a team of 50 employees, making it the first ever Algerian instant messaging, social media and mobile payment app, rivaling with the growing influence of Yassir in Algeria. it grew in popularity after the presidency of Algeria and several other state-owned companies, medias, and ministries opened official accounts on the app.

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  Redshift (theory)

  Redshift is a techno-economic theory suggesting hypersegmentation of information technology markets based on whether individual computing needs are over or under-served by Moore's law, which predicts the doubling of computing transistors (and therefore roughly computing power) every two years. The theory, proposed and named by New Enterprise Associates partner and former Sun Microsystems CTO Greg Papadopoulos, categorized a series of high growth markets (redshifting) while predicting slower GDP-driven growth in traditional computing markets (blueshifting). Papadopoulos predicted the result will be a fundamental redesign of components comprising computing systems. == Hypergrowth market segments (redshifting) == According to the Redshift theory, applications "redshift" when they grow dramatically faster than Moore's Law allows, growing quickly in their absolute number of systems. In these markets, customers are running out of datacenter real-estate, power and cooling infrastructure. According to Dell Senior Vice President Brad Anderson, “Businesses requiring hyperscale computing environments – where infrastructure deployments are measured by up to millions of servers, storage and networking equipment – are changing the way they approach IT.” While various Redshift proponents offer minor alterations on the original presentation, “Redshifting” generally includes: === ΣBW (Sum-of-Bandwidth) === These are companies that drive heavy Internet traffic. This includes popular web-portals like Google, Yahoo, AOL and MSN. It also includes telecoms, multimedia, television over IP, online games like World of Warcraft and others. This segment has been enabled by widespread availability of high-bandwidth Internet connections to consumers through a DSL or cable modem. A simple way to understand this market is that for every byte of content served to a PC, mobile phone or other device over a network, there must exist computing systems to send it over the network. === High performance computing (HPC) === These are companies that do complex simulations that involve (for example) weather, stock markets or drug-design simulations. This is a generally elastic market because businesses frequently spend every "available" dollar budgeted for IT. A common anecdote claims that cutting the cost of computing by half causes customers in this segment to buy at least twice as much, because each marginal IT dollar spent contributes to business advantage. === prise (or "Star-prise") === These are companies that aggregate traditional computing applications and offer them as services, typically in the form of Software as a Service (SaaS). For example, companies that deploy CRM are over-served by Moore's Law, but companies that aggregate CRM functions and offer them as a service, such as Salesforce.com, grow faster than Moore's Law. === The eBay crisis === A prime example of redshift was a crisis at eBay. In 1999 eBay suffered a database crisis when a single Oracle Database running on the fastest Sun machine available (these tracking Moore's law in this period) was not enough to cope with eBay's growth. The solution was to massively parallelise their system architecture. == Traditional computing markets (blueshifting) == Redshift theory suggests that traditional computing markets, such as those serving enterprise resource planning or customer relationship management applications, have reached relative saturation in industrialized nations. Thereafter, proponents argued further market growth will closely follow gross domestic product growth, which typically remains under 10% for most countries annually. Given that Moore's Law continues to predict accurately the rate of computing transistor growth, which roughly translates into computing power doubling every two years, the Redshift theory suggests that traditional computing markets will ultimately contract as a percentage of computing expenditures over time. Functionally, this means “Blueshifting” customers can satisfy computing requirement growth by swapping in faster processors without increasing the absolute number of computing systems. == Consequences and industry commentary == Papadopoulos argued that while traditional computing markets remain the dominant source of revenue through the late 2000s, a shift to hypergrowth markets will inevitably occur. When that shift occurs, he argued computing (but not computers) will become a utility, and differentiation in the IT market will be based upon a company's ability to deliver computing at massive scale, efficiently and with predictable service levels, much like electricity at that time. If computing is to be delivered as a utility, Nicholas Carr suggested Papadopoulos' vision compares with Microsoft researcher Jim Hamilton, who both agree that computing is most efficiently generated in shipping containers. Industry analysts are also beginning to quantify Redshifting and Blueshifting markets. According to International Data Corporation vice president Matthew Eastwood, "IDC believes that the IT market is in a period of hyper segmentation... This a class of customers that is Moore's law driven and as price performance gains continue, IDC believes that these organizations will accelerate their consumption of IT infrastructure.” == History and nomenclature == Key portions of Papadopoulos' theory were first presented by Sun Microsystems CEO Jonathan Schwartz in late 2006. Papadopoulos later gave a full presentation on Redshift to Sun's annual Analyst Summit in February 2007. The term Redshift refers to what happens when electromagnetic radiation, usually visible light, moves away from an observer. Papadopoulos chose this term to reflect growth markets because redshift helped cosmologists explain the expansion of the universe. Papadopoulos originally depicted traditional IT markets as green to represent their revenue base, but later changed them to “blueshift,” which occurs when a light source moves toward an observer, similar to what would happen during a contraction of the universe.

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  Electronics (journal)

  Electronics is a peer-reviewed, scientific journal that covers the study of electronics, including the design, development, and application of electronic devices, systems, and circuits. The journal is published by MDPI and was established in 2012. The editor-in-chief is Flavio Canavero 'Politecnico di Torino). The journal covers a wide range of topics related to electronics, including: electronic devices, electronic materials, electronic circuits, electronic systems, communication electronics, power electronics, and biomedical electronics. The journal also includes articles on the application of electronics in various fields, such as consumer electronics, industrial electronics, automotive electronics, and military electronics. The journal publishes original research articles, review articles, and short communications. == Abstracting and indexing == EBSCO databases ProQuest databases Scopus According to the Journal Citation Reports, the journal has a 2021 impact factor of 2.690.

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  Key frame

  In animation and filmmaking, a key frame (or keyframe) is a drawing or shot that defines the starting and ending points of a smooth transition. These are called frames because their position in time is measured in frames on a strip of film or on a digital video editing timeline. A sequence of key frames defines which movement the viewer will see, whereas the position of the key frames on the film, video, or animation defines the timing of the movement. Because only two or three key frames over the span of a second do not create the illusion of movement, the remaining frames are filled with "inbetweens". == Use of key frames as a means to change parameters == In software packages that support animation, especially 3D graphics, there are many parameters that can be changed for any one object. One example of such an object is a light. In 3D graphics, lights function similarly to real-world lights. They cause illumination, cast shadows, and create specular highlights. Lights have many parameters, including light intensity, beam size, light color, and the texture cast by the light. Supposing that an animator wants the beam size to change smoothly from one value to another within a predefined period of time, that could be achieved by using key frames. At the start of the animation, a beam size value is set. Another value is set for the end of the animation. Thus, the software program automatically interpolates the two values, creating a smooth transition. == Video editing == In non-linear digital video editing, as well as in video compositing software, a key frame is a frame used to indicate the beginning or end of a change made to a parameter. For example, a key frame could be set to indicate the point at which audio will have faded up or down to a certain level. == Video compression == In video compression, a key frame, also known as an intra-frame, is a frame in which a complete image is stored in the data stream. In video compression, only changes that occur from one frame to the next are stored in the data stream, in order to greatly reduce the amount of information that must be stored. This technique capitalizes on the fact that most video sources (such as a typical movie) have only small changes in the image from one frame to the next. Whenever a drastic change to the image occurs, such as when switching from one camera shot to another or at a scene change, a key frame must be created. The entire image for the frame must be output when the visual difference between the two frames is so great that representing the new image incrementally from the previous frame would require more data than recreating the whole image. Because video compression only stores incremental changes between frames (except for key frames), it is not possible to fast-forward or rewind to any arbitrary spot in the video stream. That is because the data for a given frame only represents how that frame was different from the preceding one. For that reason, it is beneficial to include key frames at arbitrary intervals while encoding video. For example, a key frame may be output once for each 10 seconds of video, even though the video image does not change enough visually to warrant the automatic creation of the key frame. That would allow seeking within the video stream at a minimum of 10-second intervals. The downside is that the resulting video stream will be larger in disk size because many key frames are added when they are not necessary for the frame's visual representation. This drawback, however, does not produce significant compression loss when the bitrate is already set at a high value for better quality (as in the DVD MPEG-2 format).

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  Web worker

  A web worker, as defined by the World Wide Web Consortium (W3C) and the Web Hypertext Application Technology Working Group (WHATWG), is a JavaScript script executed from an HTML page that runs in the background, independently of scripts that may also have been executed from the same HTML page. Web workers are often able to utilize multi-core CPUs more effectively. The W3C and WHATWG envision web workers as long-running scripts that are not interrupted by scripts that respond to clicks or other user interactions. Keeping such workers from being interrupted by user activities should allow Web pages to remain responsive at the same time as they are running long tasks in the background. The web worker specification is part of the HTML Living Standard. == Overview == As envisioned by WHATWG, web workers are relatively heavy-weight and are not intended to be used in large numbers. They are expected to be long-lived, with a high start-up performance cost, and a high per-instance memory cost. Web workers run outside the context of an HTML document's scripts. Consequently, while they do not have access to the DOM, they can facilitate concurrent execution of JavaScript programs. == Features == Web workers interact with the main document via message passing. The following code creates a Worker that will execute the JavaScript in the given file. To send a message to the worker, the postMessage method of the worker object is used as shown below. The onmessage property uses an event handler to retrieve information from a worker. Once a worker is terminated, it goes out of scope and the variable referencing it becomes undefined; at this point a new worker has to be created if needed. == Example == The simplest use of web workers is for performing a computationally expensive task without interrupting the user interface. In this example, the main document spawns a web worker to compute prime numbers, and progressively displays the most recently found prime number. The main page is as follows: The Worker() constructor call creates a web worker and returns a worker object representing that web worker, which is used to communicate with the web worker. That object's onmessage event handler allows the code to receive messages from the web worker. The Web Worker itself is as follows: To send a message back to the page, the postMessage() method is used to post a message when a prime is found. == Support == If the browser supports web workers, a Worker property will be available on the global window object. The Worker property will be undefined if the browser does not support it. The following example code checks for web worker support on a browser Web workers are currently supported by Chrome, Opera, Edge, Internet Explorer (version 10), Mozilla Firefox, and Safari. Mobile Safari for iOS has supported web workers since iOS 5. The Android browser first supported web workers in Android 2.1, but support was removed in Android versions 2.2–4.3 before being restored in Android 4.4.

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  Robert Abel and Associates

  Robert Abel and Associates (RA&A) was an American pioneering animation production company specializing in television commercials made with computer graphics. Founded by Robert Abel and Con Pederson in 1971, RA&A was especially known for their art direction and won many Clio Awards. Abel and his team created some of the most advanced and impressive computer-animated works of their time, including full ray-traced renders and fluid character animation at a time when such things were largely unknown. A variety of high-profile television advertisements, graphics sequences for motion pictures (including The Andromeda Strain and Tron), and work on laserdisc video games such as Cube Quest, put Abel and his team on the map in the early 1980s. The company was also originally commissioned to create the visual effects for Star Trek: The Motion Picture, but were subsequently taken off the project for mishandling funds. The company was also notable on its work for The Jacksons' 1981 music video "Can You Feel It." RA&A was on the southwest corner of Highland Avenue and Romaine in the heart of Hollywood, California. RA&A closed in 1987 following an ill-fated merger with now-defunct Omnibus Computer Graphics, Inc., a company which had been based in Toronto. Many people who worked at RA&A went on to other ground-breaking projects, including the founding of Wavefront Technologies, Rhythm & Hues and other studios. Many RA&A people went on to win Academy Awards.

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  Asymmetric follow

  An asymmetric follow social network is one which allows many people to follow an individual or account without having to follow them back. It is also known as asynchronous follow or sometimes asymmetric friendship. Asymmetric follow is a common pattern on Twitter, where someone may have thousands of followers, but themselves follow few (or no) accounts. In September 2010 Facebook started experimenting with a similar feature, which Facebook calls "Subscribe To."

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  Vulnerability Discovery Model

  A Vulnerability Discovery Model (VDM) uses discovery event data with software reliability models for predicting the same. A thorough presentation of VDM techniques is available in. Numerous model implementations are available in the MCMCBayes open source repository. Several VDM examples include: Alhazmi-Malaiya: Time based model (Alhazmi-Malaiya Logistic (AML) model) Alhazmi-Malaiya: Effort based model Rescorla: Quadratic Model and Exponential Model Anderson: Thermodynamic Model Kim: Weibull Model Linear Model Hump-Shaped Model Independent and Dependent Model Vulnerability Discovery Modeling using Bayesian model averaging Multivariate Vulnerability Discovery Models

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  Deplatforming

  Deplatforming, also known as no-platforming, is a boycott on an individual or group by removing the platforms used to share their information or ideas. The term is commonly associated with social media. == History == === Deplatforming of invited speakers === In the United States, the banning of speakers on university campuses dates back to the 1940s. This was carried out by the policies of the universities themselves. The University of California had a policy known as the Speaker Ban, codified in university regulations under President Robert Gordon Sproul, that mostly, but not exclusively, targeted communists. One rule stated that "the University assumed the right to prevent exploitation of its prestige by unqualified persons or by those who would use it as a platform for propaganda." This rule was used in 1951 to block Max Shachtman, a socialist, from speaking at the University of California at Berkeley. In 1947, former U.S. Vice President Henry A. Wallace was banned from speaking at UCLA because of his views on U.S. Cold War policy, and in 1961, Malcolm X was prohibited from speaking at Berkeley as a religious leader. Controversial speakers invited to appear on college campuses have faced deplatforming attempts to disinvite them or to otherwise prevent them from speaking. The British National Union of Students established its No Platform policy as early as 1973. In the mid-1980s, visits by South African ambassador Glenn Babb to Canadian college campuses faced opposition from students opposed to apartheid. In the United States, recent examples include the March 2017 disruption by protestors of a public speech at Middlebury College by political scientist Charles Murray. In February 2018, students at the University of Central Oklahoma rescinded a speaking invitation to creationist Ken Ham, after pressure from an LGBT student group. In March 2018, a "small group of protesters" at Lewis & Clark Law School attempted to stop a speech by visiting lecturer Christina Hoff Sommers. In the 2019 film No Safe Spaces, Adam Carolla and Dennis Prager documented their own disinvitation along with others. As of February 2020, the Foundation for Individual Rights in Education, a speech advocacy group, documented 469 disinvitation or disruption attempts at American campuses since 2000, including both "unsuccessful disinvitation attempts" and "successful disinvitations"; the group defines the latter category as including three subcategories: formal disinvitation by the sponsor of the speaking engagement; the speaker's withdrawal "in the face of disinvitation demands"; and "heckler's vetoes" (situations when "students or faculty persistently disrupt or entirely prevent the speakers' ability to speak"). === Deplatforming in social media === Beginning in 2015, Reddit banned several communities on the site ("subreddits") for violating the site's anti-harassment policy. A 2017 study published in the journal Proceedings of the ACM on Human-Computer Interaction, examining "the causal effects of the ban on both participating users and affected communities," found that "the ban served a number of useful purposes for Reddit" and that "Users participating in the banned subreddits either left the site or (for those who remained) dramatically reduced their hate speech usage. Communities that inherited the displaced activity of these users did not suffer from an increase in hate speech." In June 2020 and January 2021, Reddit also issued bans to pro-Trump communities over violations of the website's content and harassment policies. On May 2, 2019, Facebook and the Facebook-owned platform Instagram announced a ban of "dangerous individuals and organizations" including Nation of Islam leader Louis Farrakhan, Milo Yiannopoulos, Alex Jones and his organization InfoWars, Paul Joseph Watson, Laura Loomer, and Paul Nehlen. In the wake of the 2021 storming of the US Capitol, Twitter banned then-president Donald Trump, as well as 70,000 other accounts linked to the event and the far-right movement QAnon. Some studies have found that the deplatforming of extremists reduced their audience, although other research has found that some content creators became more toxic following deplatforming and migration to alt-tech platform. ==== Twitter ==== On November 18, 2022, Elon Musk, as newly appointed CEO of Twitter, reopened previously banned Twitter accounts of high-profile users, including Kathy Griffin, Jordan Peterson, and The Babylon Bee as part of the new Twitter policy. As Musk exclaimed, "New Twitter policy is freedom of speech, but not freedom of reach". ==== Alex Jones ==== On August 6, 2018, Facebook, Apple, YouTube and Spotify removed all content by Jones and InfoWars for policy violations. YouTube removed channels associated with InfoWars, including The Alex Jones Channel. On Facebook, four pages associated with InfoWars and Alex Jones were removed over repeated policy violations. Apple removed all podcasts associated with Jones from iTunes. On August 13, 2018, Vimeo removed all of Jones's videos because of "prohibitions on discriminatory and hateful content". Facebook cited instances of dehumanizing immigrants, Muslims and transgender people, as well as glorification of violence, as examples of hate speech. After InfoWars was banned from Facebook, Jones used another of his websites, NewsWars, to circumvent the ban. Jones's accounts were also removed from Pinterest, Mailchimp and LinkedIn. As of early August 2018, Jones retained active accounts on Instagram, Google+ and Twitter. In September, Jones was permanently banned from Twitter and Periscope after berating CNN reporter Oliver Darcy. On September 7, 2018, the InfoWars app was removed from the Apple App Store for "objectionable content". He was banned from using PayPal for business transactions, having violated the company's policies by expressing "hate or discriminatory intolerance against certain communities and religions." After Elon Musk's purchase of Twitter several previously banned accounts were reinstated including Donald Trump, Andrew Tate and Ye resulting in questioning if Alex Jones will be unbanned as well. However Musk denied that Alex Jones will be unbanned criticizing Jones as a person that "would use the deaths of children for gain, politics or fame". InfoWars remained available on Roku devices in January 2019, a year after the channel's removal from multiple streaming services. Roku indicated that they do not "curate or censor based on viewpoint," and that it had policies against content that is "unlawful, incited illegal activities, or violates third-party rights," but that InfoWars was not in violation of these policies. Following a social media backlash, Roku removed InfoWars and stated "After the InfoWars channel became available, we heard from concerned parties and have determined that the channel should be removed from our platform." In March 2019, YouTube terminated the Resistance News channel due to its reuploading of live streams from InfoWars. On May 1, 2019, Jones was barred from using both Facebook and Instagram. Jones briefly moved to Dlive, but was suspended in April 2019 for violating community guidelines. In March 2020, the InfoWars app was removed from the Google Play store due to claims of Jones disseminating COVID-19 misinformation. A Google spokesperson stated that "combating misinformation on the Play Store is a top priority for the team" and apps that violate Play policy by "distributing misleading or harmful information" are removed from the store. ==== Donald Trump ==== On January 6, 2021, in a joint session of the United States Congress, the counting of the votes of the Electoral College was interrupted by a breach of the United States Capitol chambers. The rioters were supporters of President Donald Trump who hoped to delay and overturn the President's loss in the 2020 election. The event resulted in five deaths and at least 400 people being charged with crimes. The certification of the electoral votes was only completed in the early morning hours of January 7, 2021. In the wake of several Tweets by President Trump on January 7, 2021 Facebook, Instagram, YouTube, Reddit, and Twitter all deplatformed Trump to some extent. Twitter deactivated his personal account, which the company said could possibly be used to promote further violence. Trump subsequently tweeted similar messages from the President's official US Government account @POTUS, which resulted in him being permanently banned on January 8. Twitter then announced that Trump's ban from their platform would be permanent. Trump planned to rejoin on social media through the use of a new platform by May or June 2021, according to Jason Miller on a Fox News broadcast. The same week Musk announced Twitter's new freedom of speech policy, he tweeted a poll to ask whether to bring back Trump into the platform. The poll ended with 51.8% in favor of unbanning Trump's account. Twitter has since reinstated Trump's Twitter accou

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  Digital history

  Digital history is the use of digital media to further historical analysis, presentation, and research. It is a branch of the digital humanities and an extension of quantitative history, cliometrics, and computing. Digital history is commonly known as digital public history, concerned primarily with engaging online audiences with historical content, or digital research methods, that further academic research. Digital history outputs include: digital archives, online presentations, data and information visualizations, interactive maps, timelines, audio files, and virtual worlds. These outputs are designed to enhance accessibility to users, facilitating engagement with historical content. Recent digital history projects focus on creativity, collaboration, and technical innovation, text mining, corpus linguistics, network analysis, 3D modeling, and big data analysis. By utilizing these resources, the user can rapidly develop new analyses that can link to, extend, and bring to life existing histories. == History == Rooted in earlier social science history work, particularly around the history of enslavement in the United States, early digital history in the 1960s and 70s focused on using computers to conduct quantitative analyses, primarily of demographic and social history data - censuses, election returns, city directories, and other tabular or countable data. - with the aim of producing defensible research findings These early computers could be programmed to conduct statistical analyses of these records, creating tallies, or seeking trends across records. This research into historical demography was rooted in the rise of social history as a field of historical interest. The historians involved in this work sought to quantify past societies, to come to new conclusions about communities and population. Computers proved capable tools for that type of work. By the late 1970s younger historians turned to cultural studies, most of these studies involved online databases that were checked by Professionals in Great Britain about once a year. The outpouring of quantitative studies by established scholars continued. Since then, quantitative history and cliometrics have been used primarily by historically minded economists and political scientists. In the late 1980s quantifiers founded the Association for History and Computing. This movement provided some of the impetus for the rise of digital history in the 1990s. The more recent roots of digital history were in software rather than online networks. In 1982, the Library of Congress embarked on its Optical Disk Pilot Project, which placed text and images from its collection on to laserdiscs and CD-ROMs. The library started offering online exhibits in 1992 when it launched Selected Civil War Photographs. In 1993, Roy Rosenzweig, along with Steve Brier and Josh Brown, produced their award-winning CD-ROM Who Built America? From the Centennial Exposition of 1876 to the Great War of 1914, designed for Apple, Inc. that integrated images, text, film and sound clips, displayed in a visual interface that supported a text narrative. Among the earliest online digital history projects were The Heritage Project of the University of Kansas, and medieval historian Dr. Lynn Nelson's World History Index and History Central Catalogue. Another was The Valley of the Shadow, conceived in 1991 by current University of Richmond professor of humanities and president emeritus, Edward L. Ayers, who was then at the University of Virginia. The Institute for Advanced Technology in the Humanities (IATH) at the University of Virginia adopted the Valley Project and partnered with IBM to collect and transcribe historical sources into digital files. The project collected data related to Augusta County in Virginia and Franklin County in Pennsylvania during the American Civil War. In 1996, William G. Thomas III joined Ayers on the Valley Project. Together, they produced an online article entitled "The Differences Slavery Made: A Close Analysis of Two American Communities," which also appeared in The American Historical Review in 2003. A CD-ROM also accompanied the Valley Project, published by W. W. Norton and Company in 2000. Rosenzweig, who died October 11, 2007, founded the Center for History and New Media (CHNM) at George Mason University in 1994. Today, CHNM boasts several digital tools available to historians, such as Zotero, Omeka or Tropy. In 1997, Ayers and Thomas used the term "digital history" when they proposed and founded the Virginia Center for Digital History (VCDH) at the University of Virginia, the earliest center devoted exclusively to history. Several other institutions promoting digital history include the Center for Humane Arts, Letters, and Social Sciences Online (MATRIX) at Michigan State University, Maryland's Institute for Technology in the Humanities, and the Center for Digital Research in the Humanities at the University of Nebraska. In 2004, Emory University launched Southern Spaces, a "peer-reviewed Internet journal and scholarly forum" examining the history of the South. == Applications == There are many potential benefits to the use of digital history when combined with traditional historical methods. Some of these applications include: Combining traditional historical methods and new research methods in order to come to new conclusions. Using different tools to extract and analyse larger amounts of data that would not be manageable otherwise. Create models and maps of data extracted to create a visualisation of the data. Data extracted and analysed can be placed alongside existing historiography to increase combined historical knowledge. By adding new research methods to existing historical method, historians can benefit greatly from the ability to work with larger amounts of data and develop new interpretations from this. == Notable Projects == The collaborative nature of most digital history endeavors has meant that the discipline has developed primarily at institutions with the resources to sponsor content research and technical innovation. Two of the first centers, George Mason University's Center for History and New Media and the Virginia Center for Digital History at the University of Virginia have been among the leaders in the development of digital history projects and the education of digital historians. Some of the noteworthy projects emerging from these pioneering centers are The Geography of Slavery, The Texas Slavery Project, and The Countryside Transformed at VCDH and Liberty, Equality, Fraternity: Exploring the French Revolution and The Lost Museum at the CHNM. In each of these projects, mediated archives holding multiple types of sources are combined with digital tools to analyze and illuminate an historical question to a varying degree; this integration of content and tools with analysis is one of the hallmarks of digital history—projects move beyond archives or collections and into scholarly analysis and the use of digital tools to develop that analysis. The differences between the ways projects incorporate these integrations are a measure of the development of the field and point to the ongoing debates over what digital history can and should be. While many of the projects at VCDH, CHNM, and other university's centers have been geared towards academics and post-secondary education, the University of Victoria (British Columbia), in conjunction with the Université de Sherbrooke and the Ontario Institute for Studies in Education at the University of Toronto, has created as series of projects for all ages, "Great Unsolved Mysteries in Canadian History." Laden with instructional aids, this site asks teachers to introduce students to historical research methods to help them develop analytical skills and a sense of the complexities of their national history. Issues of race, religion, and gender are addressed in carefully constructed modules that cover incidents in Canadian history from Viking exploration through the 1920s. One of the original co-creators of the project, John Lutz has also developed Victoria's Victoria with the University of Victoria and Malaspina University-College. In addition to Ayers, Thomas, Lutz, and Rosenzweig, numerous other individual scholars work with digital history techniques and have made and/or continue to make important contributions to the field. Robert Darnton's 2000 article, "An Early Information Society: News and the Media in Eighteenth-Century Paris" was supplemented with electronic resources and is an early model of the discussions around digital history and its future in the humanities. One of the first major digital projects to be reviewed by the American Historical Review (AHR) was Philip Ethington's "Los Angeles and the Problem of Urban Historical Knowledge"—a multimedia exploration of changes to Los Angeles' physical profile over the course of several decades. In this essay, he also expresses his beliefs that historians have major power in

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