AI Data Jobs

AI Data Jobs — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Feng Office Community Edition

    Feng Office Community Edition

    Feng Office Community Edition (formerly OpenGoo) is an open-source collaboration platform developed and supported by Feng Office and the OpenGoo community. It is a fully featured online office suite with a similar set of features as other online office suites, like Google Workspace, Microsoft 365, Zimbra, LibreOffice Online and Zoho Office Suite. The application can be downloaded and installed on a server. Feng Office could also be categorized as collaborative software and as personal information manager software. == Features == Feng Office Community Edition main features include project management, document management, contact management, e-mail and time management. Text documents and presentations can be created and edited online. Files can be uploaded, organized and shared, independent of file formats. Organization of the information in Feng Office Community Edition is done using workspaces and tags. The application presents the information stored using different interfaces such as lists, dashboards and calendar views. == Licensing == Feng Office Community Edition is distributed under the GNU Affero General Public License, version 3 only. == Technology used == Feng Office uses PHP, JavaScript, AJAX (ExtJS) and MySQL technology. Several open source projects served as a basis for development. ActiveCollab's last open sourced release was used as the initial code base. It includes CKEditor for online document editing. == System requirements == The server could run on any operating system. The system needs the following packages: Apache HTTP Server 2.0+ PHP 5.0+ MySQL 4.1+ (InnoDB support recommended) On the client side, the user is only required to use a modern Web browser. == History == OpenGoo started as a degree project at the faculty of Engineering of the University of the Republic, Uruguay. The project was presented and championed by Software Engineer Conrado Viña. Software Engineers Marcos Saiz and Ignacio de Soto developed the first prototype as their thesis. Professors Eduardo Fernández and Tomas Laurenzo served as tutors. Conrado, Ignacio and Marcos founded the OpenGoo community and remain active members and core developers. The thesis was approved with the highest score. In 2008, Viña joined the Uruguayan software development company Moove It. Currently there is a second project for OpenGoo at the same university being developed by students Fernando Rodríguez, Ignacio Vázquez and Juan Pedro del Campo. Their project aims to build an open source Web-based spreadsheet. In December 2009 the OpenGoo name was changed to Feng Office Community Edition.

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  • Trazzler

    Trazzler

    Trazzler is a travel destination app that specializes in unique and local destinations. The initial concept was developed by Adam Rugel and Biz Stone in 2006 at Twitter's original offices under the name "71 miles". More than 10,000 writers and photographers have contributed and more than $350,000 in freelance contracts have been issued as a result of Trazzeler's weekly writing and photography contests. Investors in the company include SV Angel, AOL Founder Steve Case, and the Twitter founders, Evan Williams, Jack Dorsey, and Biz Stone. The company's partners are the City of Chicago, Hawaii Tourism Authority, Fairmont Hotels & Resorts, Salon.com, and Air New Zealand. Trazzler is designed for use on the iOS, Android, and Facebook.

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  • Public computer

    Public computer

    A public computer (or public access computer) is any of various computers available in public areas. Some places where public computers may be available are libraries, schools, or dedicated facilities run by government. Public computers share similar hardware and software components to personal computers, however, the role and function of a public access computer is entirely different. A public access computer is used by many different untrusted individuals throughout the course of the day. The computer must be locked down and secure against both intentional and unintentional abuse. Users typically do not have authority to install software or change settings. A personal computer, in contrast, is typically used by a single responsible user, who can customize the machine's behavior to their preferences. Public access computers are often provided with tools such as a PC reservation system to regulate access. The world's first public access computer center was the Marin Computer Center in California, co-founded by David and Annie Fox in 1977. == Kiosks == A kiosk is a special type of public computer using software and hardware modifications to provide services only about the place the kiosk is in. For example, a movie ticket kiosk can be found at a movie theater. These kiosks are usually in a secure browser with zero access to the desktop. Many of these kiosks may run Linux, however, ATMs, a kiosk designed for depositing money, often run Windows XP. == Public computers in the United States == === Library computers === In the United States and Canada, almost all public libraries have computers available for the use of patrons, though some libraries will impose a time limit on users to ensure others will get a turn and keep the library less busy. Users are often allowed to print documents that they have created using these computers, though sometimes for a small fee. ==== Privacy ==== Privacy is an important part of the public library institution, since the libraries entitle the public to intellectual freedom. Use of any computer or network may create records of users' activities that can jeopardize their privacy. It is possible for a patron to jeopardize their privacy if they do not delete cache, clear cookies, or documents from the public computer. In order for a member of the public to remain private on a computer, the American Library Association (ALA) has guidelines. These give patrons an idea of the right way to keep using public library computers. In their provision of services to library users, librarians have an ethical responsibility, expressed in the ALA Code of Ethics, to preserve users' right to privacy. A librarian is also responsible for giving users an understanding of private patron use and access. Libraries must ensure that users have the following rights when browsing on public computers: the computer automatically will clear a users history; libraries should display privacy screens so users do not see another patron's screen; updating software for effective safety measures; restoration data software to clear documents that users may have left on their computers and to combat possible malware; security practices; and making users aware of any possible monitoring of their browsing activities. Users can also view the Library Privacy Checklist for Public Access Computers and Networks to better understand what libraries strive for when protecting privacy. === School computers === The U.S. government has given money to many school boards to purchase computers for educational applications. Schools may have multiple computer labs, which contain these computers for students to use. There is usually Internet access on these machines, but some schools will put up a blocking service to limit the websites that students are able to access to only include educational resources, such as Google. In addition to controlling the content students are viewing, putting up these blocks can also help to keep the computers safe by preventing students from downloading malware and other threats. However, the effectiveness of such content filtering systems is questionable since it can easily be circumvented by using proxy websites, Virtual Private Networks, and for some weak security systems, merely knowing the IP address of the intended website is enough to bypass the filter. School computers often have advanced operating system security to prevent tech-savvy students from inflicting damage (i.e. the Windows Registry Editor and Task Manager, etc.) are disabled on Microsoft Windows machines. Schools with very advanced tech services may also install a locked down BIOS/firmware or make kernel-level changes to the operating system, precluding the possibility of unauthorized activity.

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  • Geometric primitive

    Geometric primitive

    In vector computer graphics, CAD systems, and geographic information systems, a geometric primitive (or prim) is the simplest (i.e. 'atomic' or irreducible) geometric shape that the system can handle (draw, store). Sometimes the subroutines that draw the corresponding objects are called "geometric primitives" as well. The most "primitive" primitives are point and straight line segments, which were all that early vector graphics systems had. In constructive solid geometry, primitives are simple geometric shapes such as a cube, cylinder, sphere, cone, pyramid, torus. Modern 2D computer graphics systems may operate with primitives which are curves (segments of straight lines, circles and more complicated curves), as well as shapes (boxes, arbitrary polygons, circles). A common set of two-dimensional primitives includes lines, points, and polygons, although some people prefer to consider triangles primitives, because every polygon can be constructed from triangles (polygon triangulation). All other graphic elements are built up from these primitives. In three dimensions, triangles or polygons positioned in three-dimensional space can be used as primitives to model more complex 3D forms. In some cases, curves (such as Bézier curves, circles, etc.) may be considered primitives; in other cases, curves are complex forms created from many straight, primitive shapes. == Common primitives == The set of geometric primitives is based on the dimension of the region being represented: Point (0-dimensional), a single location with no height, width, or depth. Line or curve (1-dimensional), having length but no width, although a linear feature may curve through a higher-dimensional space. Planar surface or curved surface (2-dimensional), having length and width. Volumetric region or solid (3-dimensional), having length, width, and depth. In GIS, the terrain surface is often spoken of colloquially as "2 1/2 dimensional," because only the upper surface needs to be represented. Thus, elevation can be conceptualized as a scalar field property or function of two-dimensional space, affording it a number of data modeling efficiencies over true 3-dimensional objects. A shape of any of these dimensions greater than zero consists of an infinite number of distinct points. Because digital systems are finite, only a sample set of the points in a shape can be stored. Thus, vector data structures typically represent geometric primitives using a strategic sample, organized in structures that facilitate the software interpolating the remainder of the shape at the time of analysis or display, using the algorithms of Computational geometry. A Point is a single coordinate in a Cartesian coordinate system. Some data models allow for Multipoint features consisting of several disconnected points. A Polygonal chain or Polyline is an ordered list of points (termed vertices in this context). The software is expected to interpolate the intervening shape of the line between adjacent points in the list as a parametric curve, most commonly a straight line, but other types of curves are frequently available, including circular arcs, cubic splines, and Bézier curves. Some of these curves require additional points to be defined that are not on the line itself, but are used for parametric control. A Polygon is a polyline that closes at its endpoints, representing the boundary of a two-dimensional region. The software is expected to use this boundary to partition 2-dimensional space into an interior and exterior. Some data models allow for a single feature to consist of multiple polylines, which could collectively connect to form a single closed boundary, could represent a set of disjoint regions (e.g., the state of Hawaii), or could represent a region with holes (e.g., a lake with an island). A Parametric shape is a standardized two-dimensional or three-dimensional shape defined by a minimal set of parameters, such as an ellipse defined by two points at its foci, or three points at its center, vertex, and co-vertex. A Polyhedron or Polygon mesh is a set of polygon faces in three-dimensional space that are connected at their edges to completely enclose a volumetric region. In some applications, closure may not be required or may be implied, such as modeling terrain. The software is expected to use this surface to partition 3-dimensional space into an interior and exterior. A triangle mesh is a subtype of polyhedron in which all faces must be triangles, the only polygon that will always be planar, including the Triangulated irregular network (TIN) commonly used in GIS. A parametric mesh represents a three-dimensional surface by a connected set of parametric functions, similar to a spline or Bézier curve in two dimensions. The most common structure is the Non-uniform rational B-spline (NURBS), supported by most CAD and animation software. == Application in GIS == A wide variety of vector data structures and formats have been developed during the history of Geographic information systems, but they share a fundamental basis of storing a core set of geometric primitives to represent the location and extent of geographic phenomena. Locations of points are almost always measured within a standard Earth-based coordinate system, whether the spherical Geographic coordinate system (latitude/longitude), or a planar coordinate system, such as the Universal Transverse Mercator. They also share the need to store a set of attributes of each geographic feature alongside its shape; traditionally, this has been accomplished using the data models, data formats, and even software of relational databases. Early vector formats, such as POLYVRT, the ARC/INFO Coverage, and the Esri shapefile support a basic set of geometric primitives: points, polylines, and polygons, only in two dimensional space and the latter two with only straight line interpolation. TIN data structures for representing terrain surfaces as triangle meshes were also added. Since the mid 1990s, new formats have been developed that extend the range of available primitives, generally standardized by the Open Geospatial Consortium's Simple Features specification. Common geometric primitive extensions include: three-dimensional coordinates for points, lines, and polygons; a fourth "dimension" to represent a measured attribute or time; curved segments in lines and polygons; text annotation as a form of geometry; and polygon meshes for three-dimensional objects. Frequently, a representation of the shape of a real-world phenomenon may have a different (usually lower) dimension than the phenomenon being represented. For example, a city (a two-dimensional region) may be represented as a point, or a road (a three-dimensional volume of material) may be represented as a line. This dimensional generalization correlates with tendencies in spatial cognition. For example, asking the distance between two cities presumes a conceptual model of the cities as points, while giving directions involving travel "up," "down," or "along" a road imply a one-dimensional conceptual model. This is frequently done for purposes of data efficiency, visual simplicity, or cognitive efficiency, and is acceptable if the distinction between the representation and the represented is understood, but can cause confusion if information users assume that the digital shape is a perfect representation of reality (i.e., believing that roads really are lines). == In 3D modelling == In CAD software or 3D modelling, the interface may present the user with the ability to create primitives which may be further modified by edits. For example, in the practice of box modelling the user will start with a cuboid, then use extrusion and other operations to create the model. In this use the primitive is just a convenient starting point, rather than the fundamental unit of modelling. A 3D package may also include a list of extended primitives which are more complex shapes that come with the package. For example, a teapot is listed as a primitive in 3D Studio Max. == In graphics hardware == Various graphics accelerators exist with hardware acceleration for rendering specific primitives such as lines or triangles, frequently with texture mapping and shaders. Modern 3D accelerators typically accept sequences of triangles as triangle strips.

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  • Nanosemantics

    Nanosemantics

    Nanosemantics Lab is a Russian IT company specializing in natural language processing (NLP), computer vision (CV), speech technologies (ASR/TTS) and creation of interactive dialog interfaces, particularly chatbots and virtual assistants, based on artificial intelligence (AI). The company uses neural network platforms, including its own-made platform PuzzleLib which works on Russian-made microprocessor architecture Elbrus and Russia-based Astra Linux operating system. The company was founded in 2005 by Igor Ashmanov and Natalya Kaspersky. == Profile == The company was one of the first on Russian market to develop dialog interfaces for different branches of businesses, as well as to support community of AI developers. The company's most demanded product, as for beginning of the 2020s, is the automated "online advisers", functioning as chat bots, made for helping customers with usage of commercial products. In 2009 the company released an online service called iii.ru, where visitors were able to create their own AI-based virtual personalities entitles "infs" (for free). A visitor was able to train its own "inf" and let them chat to other "live" visitors as well with other "infs". More than 2.3 million of "infs" were created and trained by visitors over several years. Nanosemantics Lab maintains its own linguistic programming language for AI development called Dialog Language (DL). Popular social networks and instant messaging services may be used as base platforms. Nanosemantics' AI bots support different types of businesses: banks and financial services, telecommunications, retail, travel and automobile industry, home appliances production, etc. Among its solutions, Nanosemantics lists projects for various companies and institutions, among them VTB, Beeline, MTS, Sberbank, Higher School of Economics, Webmoney, Gazpromneft, Rostelecom, Ford Motors, Ministry of Health of the Russian Federation and others. The company uses the term "inf" for naming its numerous types of chat bots. The term was coined by co-founder Igor Ashmanov, head of Ashmanov & Partners. A 2014 scholarly research at Higher School of Economics, called "Basics of Business Informatics", states that such "infs", when used at business, may lower load on employees, collect statistics useful for understanding market demand and also may increase customer loyalty by providing fast and informative answers due to usage of large databases. The same research describes Nanosemantics' project for Russian branch of Ford Motors company, when AI capabilities were used for promoting the car model Ford Kuga. The research pointed out that within 2 months since beginning, the promo-website conducted 47774 talks of visitors with the specialized "inf", which indicated several hundred thousand of questions and the longest chat lasted for 3 hours 10 minutes. One-year promo campaign showed that 28.6% of people who made pre-orders talked to an "inf". In 2016 Nanosemantics launched a SaaS platform aimed at creating customized virtual assistants by users. The company's flagship product is considered to be Dialog Operating System (DialogOS), a professional corporate platform for creating intellectual voice and textual bots. It has its own linguistic programming language for creation of flexible scenarios and ready-studied neural natural language processing modules that are able to understand human interlocutors. In 2021 the company presented technology called NLab Speech ASR which contains a set of neural-networking algorithms for processing audio signals and analysis of texts that were trained and calibrated using speech-based big data marked up manually. The technology allows speed of processing of data up to "6 real-time factor" and precision values in noisy audio data may exceed 82%. In March 2022 the technology was included in Russia's Joint Registry for Russian Programs for Computers and Databases. As well, another technology was included: NLab Speech TTS, which is text-to-speech system that produces synthesized speech from printed text. == Joint projects == Nanosemantics participates in Ashmanov & Partners' projects related to AI. Since 2014, it helps in development of hardware "personal assistant" called Lexy, a solution similar to Amazon Alexa and the analogues. In August 2019 it was announced that Nanosemantics is going to participate in creation of open operating system for creating automated voice assistants. The project was called SOVA (Smart Open Virtual Assistant) and received investment of 300 million roubles (~$4,6 million) from Russian state-maintained National Technological Initiative. The company maintains long-term partnerships with Skolkovo Innovation Center (resident of IT cluster), branch association "Neuronet" and Yandex. Together with USA-based startup Remedy Logic, Nanosemantics has developed a medical diagnostic system for finding, using AI, spinal pathologies in tomography images of human bodies. Among them: central, foraminal and lateral lumbar stenosis, hernias, arthrosis. The system offers options of treatment. Since August 2021 the company is the resident of Technology Valley of Moscow State University. Also in 2021, Nanosemantics became a member of Committee on Artificial Intelligence within the Russian Association of Software Developers "Native Soft". The company states as one of its missions support of initiatives aimed at preservation and development of the Russian language. In May 2021, together with Pushkin Institute, the company created a chat bot called Phil, that explains to Russian people meaning of different Russian neologisms, and offers synonyms for them. Bot's vocabulary contains more than 500 neologisms, as well the bot can give advice on jargonisms and other types of specific words. Also in 2021, Nanosemanics Lab has signed the first-ever Russian "Codex of ethics of artificial intelligence". It establishes guidelines for ethical behavior of businesses that implement AI-based solutions. === IT contests === The company regularly organizes All-Russian Turing Test competitions for IT developers. Some of these events are co-organized with Microsoft. During the competitions, judges randomly choose virtual interlocutor and have a short conversation with them. They have to determine if a human or a machine is talking to them. An interlocutor may be either a bot or its human creator or operator. The results are measured in per cent of judges that were successfully convinced by a machine that it was a human. In 2021 Nanosemantics took part in federal project "Artificial Intelligence" by National Technological Initiative. In December 2021 the company together with state enterprise "Resource Center of Universal Design and Rehabilitation Technologies" (RCUD-RT) held an all-Russian hackathon aimed at development of AI solutions for medicine. During 3 days, participants created several training programs for patients with speech disorders. In April 2022, another hackathon by Nanosemantics was held together with MIREA – Russian Technological University. Students were participating and trying to generate algorithms for voice deepfakes. 17 teams contested in creation of software that generated artificial voice of a certain person. == Recognition == Since its foundation, Nanosemantics Lab has received a number of recognitions and awards. Among them are several professional ROTOR awards for the website iii.ru (created in 2009). The website gives the general public the means to create and train virtual assistants, which can then be used on a website or integrated into social networks. In 2013, a virtual assistant called Dana, created for Beeline Kazakhstan, was awarded with professional prize "Crystal Headset" in nomination "the best applying of technology". In 2015, the RBTH international media service included Nanosemantics in its list of "Top 50 Startups" in Russia. In 2016, the company received Russian state-maintained award called Runet Prize in two nominations: "State and Society" and "Technology and Innovation". In 2021, in Velikiy Novgorod, Nanosemantics team has won a hackathon aimed at finding means of discovering corruption schemes in Russian laws. In February 2022 the company won another contest by National Technological Initiative, called "Prochtenie", aimed at creation of AI systems for checking schoolchildren's school essays. The Nanosemantics team was awarded 20 million rubles for "overcoming technological barrier" in contest dedicated to English language, and 12 million for 1st place in special nomination "Structure" in Russian-language essay contest.

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  • Ware report

    Ware report

    Security Controls for Computer Systems, commonly called the Ware report, is a 1970 text by Willis Ware that was foundational in the field of computer security. == Development == A defense contractor in St. Louis, Missouri, had bought an IBM mainframe computer, which it was using for classified work on a fighter aircraft. To provide additional income, the contractor asked the Department of Defense (DoD) for permission to sell computer time on the mainframe to local businesses via remote terminals, while the classified work continued. At the time, the DoD did not have a policy to cover this. The DoD's Advanced Research Projects Agency (DARPA) asked Ware - a RAND employee - to chair a committee to examine and report on the feasibility of security controls for computer systems. The committee's report was a classified document given in January 1970 to the Defense Science Board (DSB), which had taken over the project from ARPA. After declassification, the report was published by RAND in October 1979. == Influence == The IEEE Computer Society said the report was widely circulated, and the IEEE Annals of the History of Computing said that it, together with Ware's 1967 Spring Joint Computer Conference session, marked the start of the field of computer security. The report influenced security certification standards and processes, especially in the banking and defense industries, where the report was instrumental in creating the Orange Book.

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  • Materialized view

    Materialized view

    In computing, a materialized view is a database object that contains the results of a query. For example, it may be a local copy of data located remotely, or may be a subset of the rows and/or columns of a table or join result, or may be a summary using an aggregate function. The process of setting up a materialized view is sometimes called materialization. This is a form of caching the results of a query, similar to memoization of the value of a function in functional languages, and it is sometimes described as a form of precomputation. As with other forms of precomputation, database users typically use materialized views for performance reasons, i.e. as a form of optimization. Materialized views that store data based on remote tables were also known as snapshots (deprecated Oracle terminology). In any database management system following the relational model, a view is a virtual table representing the result of a database query. Whenever a query or an update addresses an ordinary view's virtual table, the DBMS converts these into queries or updates against the underlying base tables. A materialized view takes a different approach: the query result is cached as a concrete ("materialized") table (rather than a view as such) that may be updated from the original base tables from time to time. This enables much more efficient access, at the cost of extra storage and of some data being potentially out-of-date. Materialized views find use especially in data warehousing scenarios, where frequent queries of the actual base tables can be expensive. In a materialized view, indexes can be built on any column. In contrast, in a normal view, it's typically only possible to exploit indexes on columns that come directly from (or have a mapping to) indexed columns in the base tables; often this functionality is not offered at all. == Implementations == === Oracle === Materialized views were implemented first by the Oracle Database: the Query rewrite feature was added from version 8i. Example syntax to create a materialized view in Oracle: === PostgreSQL === In PostgreSQL, version 9.3 and newer natively support materialized views. In version 9.3, a materialized view is not auto-refreshed, and is populated only at time of creation (unless WITH NO DATA is used). It may be refreshed later manually using REFRESH MATERIALIZED VIEW. In version 9.4, the refresh may be concurrent with selects on the materialized view if CONCURRENTLY is used. Example syntax to create a materialized view in PostgreSQL: === SQL Server === Microsoft SQL Server differs from other RDBMS by the way of implementing materialized view via a concept known as "Indexed Views". The main difference is that such views do not require a refresh because they are in fact always synchronized to the original data of the tables that compound the view. To achieve this, it is necessary that the lines of origin and destination are "deterministic" in their mapping, which limits the types of possible queries to do this. This mechanism has been realised since the 2000 version of SQL Server. Example syntax to create a materialized view in SQL Server: === Stream processing frameworks === Apache Kafka (since v0.10.2), Apache Spark (since v2.0), Apache Flink, Kinetica DB, Materialize, RisingWave, and Epsio all support materialized views on streams of data. === Others === Materialized views are also supported in Sybase SQL Anywhere. In IBM Db2, they are called "materialized query tables". ClickHouse supports materialized views that automatically refresh on merges. MySQL doesn't support materialized views natively, but workarounds can be implemented by using triggers or stored procedures or by using the open-source application Flexviews. Materialized views can be implemented in Amazon DynamoDB using data modification events captured by DynamoDB Streams. Google announced in 8 April 2020 the availability of materialized views for BigQuery as a beta release.

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  • Hooked (app)

    Hooked (app)

    Hooked is a mobile application where users can write or read chat fiction, short pieces of fiction told in the format of text messages between fictional characters. The app was released in September 2015 and was developed by Telepathic Inc. == Features == Hooked is a freemium smartphone app that allows users to write or read short stories made up of text messages between characters. CEO Prerna Gupta described the app as "books for the Snapchat generation" or "Twitter for fiction." As of March 2019, the app had more than 40 million active users. The stories are written by a mix of professional authors and crowd-sourced participants. The most popular genres are suspense and horror. The stories usually lack literary elements like character arcs, are simply written and are intended to be suspenseful or addicting. Each piece of fiction on the app is approximately 1,000 to 1,300 words long and can be read in about five minutes. Some longer stories are told in "chapters" and a 32,000-word thriller called Dark Matter was released in 2018. The app provides a certain number of text messages for free, then delays the next text message by 15 minutes unless the user pays for a subscription. Prior to 2020, the app offered a three-day free trial and then required users to pay. According to Gupta, the app was intended to get the younger generation to read more without getting distracted. Most users of the app are between 13 and 24 years-old. == History == The Hooked app was first released in September 2015. Initially, Hooked featured about 200 stories that were written by professional authors selected by the app developers. The following year, Telepathic Inc. released Hooked 2.0, which allowed users of the app to create and share their own short stories. By mid-2016, the app had 700 stories written by professional authors and 9,000 stories written by users. Hooked had 1.8 million downloads by 2016 and 20 million download as of 2017, which generated $6.5 million in revenue. The response to Hooked prompted others to create similar text-message based short story apps, like Yarn and Tap. Sensor Tower reported that the Hooked app received 2.22 million downloads during the period from October 2016 to March 2017. Starting in 2020, longer stories divided into chapters debuted on the app. In March, the company launched Hooked TV, an app to showcase video pilots based on a number of scripts themed around the app's content. Out of 50 pilots, those that were most popular among users of the app and social media were expanded into original series as Hooked TV evolved into a streaming platform in the second half of 2021. == Background == The idea for Hooked was conceived when Gupta was working on writing a book of her own. Prerna Gupta and her husband Parag Chordia tested short stories with 15,000 people and found that readers were five times more likely to read a story to its end if the story was presented in a text message format. They created Telepathic Inc., which developed Hooked. According to Celebrity Secret when they first started out, the stories were basically as if two people were texting each other and some sort of drama unfolds. Some of their most popular initial stories were actually horror stories, where a mom gets a text from her daughter and something creepy is happening to her. Over time, they started to turn those into podcasts, which then led to making their own movies and TV shows. As of 2017, the Telepathic has raised $6 million in funding to develop and support the Hooked app. From the main website itself the Hooked investors include Sound Ventures, The Chernin Group, WME/Endeavor, MACRO, Greg Silverman, Steph Curry, Kevin Durant, LeBron James, Mariah Carey, Jamie Foxx, Joe Montana, Aasif Mandvi, Max Martin, Anjula Acharia, Savan Kotecha, Cyan Banister, Eric Ries, A Capital, SV Angel, Cowboy Ventures, Founders Fund and Greylock, among many others.

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  • Stencil buffer

    Stencil buffer

    A stencil buffer is an extra data buffer, in addition to the color buffer and Z-buffer, found on modern graphics hardware. The buffer is per pixel and works on integer values, usually with a depth of one byte per pixel. The Z-buffer and stencil buffer often share the same area in the RAM of the graphics hardware. In the simplest case, the stencil buffer is used to limit the area of rendering (stenciling). More advanced usage of the stencil buffer makes use of the strong connection between the Z-buffer and the stencil buffer in the rendering pipeline. For example, stencil values can be automatically increased/decreased for every pixel that fails or passes the depth test. The simple combination of depth test and stencil modifiers make a vast number of effects possible (such as stencil shadow volumes, Two-Sided Stencil, compositing, decaling, dissolves, fades, swipes, silhouettes, outline drawing, or highlighting of intersections between complex primitives) though they often require several rendering passes and, therefore, can put a heavy load on the graphics hardware. The most typical application is still to add shadows to 3D applications. It is also used for planar reflections. Other rendering techniques, such as portal rendering, use the stencil buffer in other ways; for example, it can be used to find the area of the screen obscured by a portal and re-render those pixels correctly. The stencil buffer and its modifiers can be accessed in computer graphics by using APIs like OpenGL, Direct3D, Vulkan or Metal. == Architecture == The stencil buffer typically shares the same memory space as the Z-buffer, and typically the ratio is 24 bits for Z-buffer + 8 bits for stencil buffer or, in the past, 15 bits for Z-buffer + 1 bit for stencil buffer. Another variant is 4 + 24, where 28 of the 32 bits are used and 4 ignored. Stencil and Z-buffers are part of the frame buffer, coupled to the color buffer. The first chip available to a wider market was 3Dlabs' Permedia II, which supported a one-bit stencil buffer. The bits allocated to the stencil buffer can be used to represent numerical values in the range [0, 2n-1], and also as a Boolean matrix (n is the number of allocated bits), each of which may be used to control the particular part of the scene. Any combination of these two ways of using the available memory is also possible. == Stencil test == Stencil test or stenciling is among the operations on the pixels/fragments (Per-pixel operations), located after the alpha test, and before the depth test. The stencil test ensures undesired pixels do not reach the depth test. This saves processing time for the scene. Similarly, the alpha test can prevent corresponding pixels to reach the stencil test. The test itself is carried out over the stencil buffer to some value in it, or altered or used it, and carried out through the so-called stencil function and stencil operations. The stencil function is a function by which the stencil value of a certain pixel is compared to a given reference value. If this comparison is logically true, the stencil test passes. Otherwise not. In doing so, the possible reaction caused by the result of comparing three different state-depth and stencil buffer: Stencil test is not passed Stencil test is passed but not the depth test Both tests are passed (or stencil test is passed, and the depth is not enabled) For each of these cases, different operations can be set over the examined pixel. In the OpenGL stencil functions, the reference value and mask, respectively, define the function glStencilFunc. In Direct3D each of these components is adjusted individually using methods SetRenderState devices currently in control. This method expects two parameters, the first of which is a condition that is set and the other its value. In the order that was used above, these conditions are called D3DRS_STENCILFUNC, D3DRS_STENCILREF, and D3DRS_STENCILMASK. Stencil operations in OpenGL adjust glStencilOp function that expects three values. In Direct3D, again, each state sets a specific method SetRenderState. The three states that can be assigned to surgery are called D3DRS_STENCILFAIL, D3DRENDERSTATE_STENCILZFAIL, and D3DRENDERSTATE_STENCILPASS. == Z-fighting == Due to the lack of precision in the Z-buffer, coplanar polygons that are short-range, or overlapping, can be portrayed as a single plane with a multitude of irregular cross-sections. These sections can vary depending on the camera position and other parameters and are rapidly changing. This is called Z-fighting. There exist multiple solutions to this issue: - Bring the far plane closer to restrict the scene's depth, thus increasing the accuracy of the Z-buffer, or reducing the distance at which objects are visible in the scene. - Increase the number of bits allocated to the Z-buffer, which is possible at the expense of memory for the stencil buffer. - Move polygons farther apart from one another, which restricts the possibilities for the artist to create an elaborate scene. All of these approaches to the problem can only reduce the likelihood that the polygons will experience Z-fighting, and do not guarantee a definitive solution in the general case. A solution that includes the stencil buffer is based on the knowledge of which polygon should be in front of the others. The silhouette of the front polygon is drawn into the stencil buffer. After that, the rest of the scene can be rendered only where the silhouette is negative, and so will not clash with the front polygon. == Shadow volume == Shadow volume is a technique used in 3D computer graphics to add shadows to a rendered scene. They were first proposed by Frank Crow in 1977 as the geometry describing the 3D shape of the region occluded from a light source. A shadow volume divides the virtual world in two: areas that are in shadow and areas that are not. The stencil buffer implementation of shadow volumes is generally considered among the most practical general-purpose real-time shadowing techniques for use on modern 3D graphics hardware. It has been popularised by the video game Doom 3, and a particular variation of the technique used in this game has become known as Carmack's Reverse. == Reflections == Reflection of a scene is drawn as the scene itself transformed and reflected relative to the "mirror" plane, which requires multiple render passes and using of stencil buffer to restrict areas where the current render pass works: Draw the scene excluding mirror areas – for each mirror lock the Z-buffer and color buffer Render visible part of the mirror Depth test is set up so that each pixel is passed to enter the maximum value and always passes for each mirror: Depth test is set so that it passes only if the distance of a pixel is less than the current (default behavior) The matrix transformation is changed to reflect the scene relative to the mirror plane Unlock the Z-buffer and color buffer Draw the scene, but only the part of it that lies between the mirror plane and the camera. In other words, a mirror plane is also a clipping plane Again locks color buffer, depth test is set so that it always passes, reset stencil for the next mirror. == Planar Shadows == While drawing a plane of shadows, there are two dominant problems: The first concerns the problem of deep struggle in case the flat geometry is not awarded on the part covered with the shadow of shadows and outside. See the section that relates to this. Another problem relates to the extent of the shadows outside the area where the plane there. Another problem, which may or may not appear, depending on the technique, the design of more polygons in one part of the shadow, resulting in darker and lighter parts of the same shade. All three problems can be solved geometrically, but because of the possibility that hardware acceleration is directly used, it is a far more elegant implementation using the stencil buffer: 1. Enable lights and the lights 2. Draw a scene without any polygon that should be projected shadows 3. Draw all polygons which should be projected shadows, but without lights. In doing so, the stencil buffer, the pixel of each polygon to be assigned to a specific value for the ground to which they belong. The distance between these values should be at least two, because for each plane to be used two values for two states: in the shadows and bright. 4. Disable any global illumination (to ensure that the next steps will affect only individual selected light) For each plane: For each light: 1. Edit a stencil buffer and only the pixels that carry a specific value for the selected level. Increase the value of all the pixels that are projected objects between the date of a given level and bright. 2. Allow only selected light for him to draw level at which part of her specific value was not changed. == Spatial shadows == Stencil buffer implementation of spatial drawing shadows is any shadow of a geometric body that its volume includes part of the scene that is

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  • NHS COVID-19

    NHS COVID-19

    NHS COVID-19 was a voluntary contact tracing app for monitoring the spread of the COVID-19 pandemic in England and Wales, in use from 24 September 2020 until 27 April 2023. It was available for Android and iOS smartphones, and could be used by anyone aged 16 or over. Two versions of the app were created. The first was commissioned by NHSX and developed by the Pivotal division of American software company VMware. A pilot deployment began in May 2020, but on 18 June development of the app was abandoned in favour of a second design using the Apple/Google Exposure Notification system. Scotland and Northern Ireland had separate contact tracing apps. A 2023 study estimated that in its first year of use, the app's contact tracing function prevented an estimated 1 million cases, and 9,600 deaths. == Description == The app allowed users to: See the alert level of their local authority area (in Wales) or information about restrictions (in England); to enable this, the user must enter the first half of their postcode "Check in" at places displaying an NHS QR code poster (no longer required by legislation after 26 January 2022, removed from the app the next month) Be notified when they have been in close contact with someone who has tested positive for the virus Be notified when local health protection teams determine that people with the virus had attended a business or other venue around the same time as the user Check their symptoms, and book a coronavirus test if necessary If asked to self-isolate, receive information and a daily "countdown". At first, "close contact" was defined as being within 2 metres for 15 minutes, or within 4 metres for a longer time. These time durations were reduced from 29 October 2020, to as little as three minutes when the other person is at their most infectious, i.e. soon after they begin showing symptoms. === Implementation === The Android app was coded in Kotlin, and the iOS app in Swift. The backend used Java and is deployed to Amazon Web Services using Terraform. The code of the app and back-end is open-source and available on GitHub. == Context == The app was part of the UK's test and trace programme which was chaired by Dido Harding; from 12 May 2020 Tom Riordan, chief executive of Leeds City Council, led the tracing effort. == First phase and cancellation == === Description === In March 2020, NHSX commissioned a contact tracing app to monitor the spread in the United Kingdom of the coronavirus disease 2019 (COVID-19) in the 2020 pandemic, developed by the Pivotal division of American software company VMware. The app used a centralised approach, in contrast to the Google / Apple contact tracing project. NHSX consulted ethicists and GCHQ's National Cyber Security Centre (NCSC) about the privacy aspects. The app recorded the make and model of the phone and asked the user for their postcode area. It generated a unique installation identification number and also a daily identification number. It then used Bluetooth Low Energy (BLE) to record the daily identification number of other users nearby. If a user was unwell, they could tell the app about symptoms which are characteristic of COVID-19, such as a fever and cough. These details were then passed to a central NHS server. This would assess the information and notify other users that have been in contact, giving them appropriate advice such as physical distancing. The NHS would also arrange for a swab test of the unwell user and the outcome would determine further notifications to contacts: if the test confirmed infection with COVID-19, the contacts would be asked to isolate. By June 2020, £11.8 million had been spent on the app; in 2020–21, £35 million was spent on the app. === Deployment === The first public trial of the app began on the Isle of Wight on 5 May 2020 and by 11 May it had been downloaded 55,000 times. When the first national contact tracing schemes were launched – Test, Trace, Protect in Wales on 13 May, then on 28 May NHS Test and Trace in England, and Test and Protect in Scotland – the app was not ready to be included. Replying to a question at the government's daily briefing on 8 June, Hancock was unable to give a date for rollout of the app in England, saying it would be brought in "when it's right to do so". On 17 June, Lord Bethell, junior minister for Innovation at the Department of Health and Social Care, said "we're seeking to get something going before the winter ... it isn't a priority for us at the moment". On 18 June, Health Secretary Matt Hancock announced development would switch to the Apple/Google system after admitting that Apple's restrictions on usage of Bluetooth prevented the app from working effectively. At the same press briefing Dido Harding, leader of the UK's test and trace programme, said "What we've done in really rigorously testing both our own Covid-19 app and the Google-Apple version is demonstrate that none of them are working sufficiently well enough to be actually reliable to determine whether any of us should self-isolate for two weeks [and] that's true across the world". === Concerns === The first, ultimately rejected, version of the app was subject to privacy concerns, the government backtracking on initial statements that the data collected from the app would not be shared outside the NHS. Matthew Gould, CEO of NHSX, the government department responsible for the app, said the data would be accessible to other organisations, but did not disclose which. Data collected would not necessarily be anonymised and would be held in a centralised repository. Over 150 of the UK's security and privacy experts warned the app's data could be used by 'a bad actor (state, private sector, or hacker)' to spy on citizens. Fears were discussed by the House of Commons' Human Rights Select Committee about plans for the app to record user location data. Parliament's Joint Committee on Human Rights said this version of the app should not be released without proper privacy protections. The second version of the app, released nationwide, addressed these concerns by employing a decentralised framework, the Apple/Google Exposure Notification system. Under this system, users remain pseudonymous: a person diagnosed with COVID-19 does not know which people are informed about an encounter, and contacted persons do not receive any information about the person diagnosed with COVID-19. The functionality of the app was also questioned in late April and early May 2020, as the software's use of Bluetooth required the app to be constantly running, meaning users could not use other apps or lock their device if the app was to function properly. The developers of the app were said to have found a way of working around this restriction. === Related contracts === Faculty – a company linked to Cambridge Analytica – provided research and modelling to NHSX in support of the response to the pandemic. Palantir, also linked to Cambridge Analytica, provided their data management platform. These contracts began in February and March respectively. == Second phase == As outlined on cancellation of the first app on 18 June 2020, the Department of Health and Social Care published on 30 July a brief description of the "next phase" app. Users would be able to scan a QR code at venues they visit, and later be notified if they had visited a place which was the source of a number of infections; the app would also assist with identifying symptoms and ordering a test. By using the Exposure Notification system from Apple and Google, personal data would be decentralised. Zuhlke Engineering Ltd, the UK branch of Swiss-based Zühlke Group, used 70 staff to complete the development of the app in 12 weeks. Zuhlke Engineering was awarded "Development Team of the Year" title at UK IT Industry awards in November 2021 for development of NHS COVID-19 application. === Timeline === Testing of the app by NHS volunteer responders, and selected residents of the Isle of Wight and the London Borough of Newham, began around 13 August. The app was made available to the public (aged 16 or over) in England and Wales on 24 September. An updated app released on 29 October, in part from collaboration with the Alan Turing Institute, improved the accuracy of measurements of the distance between the user's phone and other phones. At the same time, the duration threshold for determining exposure was reduced; this was expected to lead to an increase in the number of users told to self-isolate. An update to the app in April 2021, timed to coincide with easing of restrictions on hospitality businesses, was blocked by Apple and Google. It was intended that users who tested positive would be asked to share their history of visited venues, to assist in warning others, but this would have contravened assurances by Apple and Google that location data from devices would not be shared. === Statistics and effectiveness === The app was downloaded six million times on the first day it was generally availa

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  • Image-based modeling and rendering

    Image-based modeling and rendering

    In computer graphics and computer vision, image-based modeling and rendering (IBMR) methods rely on a set of two-dimensional images of a scene to generate a three-dimensional model and then render some novel views of this scene. The traditional approach of computer graphics has been used to create a geometric model in 3D and try to reproject it onto a two-dimensional image. Computer vision, conversely, is mostly focused on detecting, grouping, and extracting features (edges, faces, etc.) present in a given picture and then trying to interpret them as three-dimensional clues. Image-based modeling and rendering allows the use of multiple two-dimensional images in order to generate directly novel two-dimensional images, skipping the manual modeling stage. == Light modeling == Instead of considering only the physical model of a solid, IBMR methods usually focus more on light modeling. The fundamental concept behind IBMR is the plenoptic illumination function which is a parametrisation of the light field. The plenoptic function describes the light rays contained in a given volume. It can be represented with seven dimensions: a ray is defined by its position ( x , y , z ) {\displaystyle (x,y,z)} , its orientation ( θ , ϕ ) {\displaystyle (\theta ,\phi )} , its wavelength ( λ ) {\displaystyle (\lambda )} and its time ( t ) {\displaystyle (t)} : P ( x , y , z , θ , ϕ , λ , t ) {\displaystyle P(x,y,z,\theta ,\phi ,\lambda ,t)} . IBMR methods try to approximate the plenoptic function to render a novel set of two-dimensional images from another. Given the high dimensionality of this function, practical methods place constraints on the parameters in order to reduce this number (typically to 2 to 4). == IBMR methods and algorithms == View morphing generates a transition between images Panoramic imaging renders panoramas using image mosaics of individual still images Lumigraph relies on a dense sampling of a scene Space carving generates a 3D model based on a photo-consistency check

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  • Kdb+

    Kdb+

    kdb+ is a column-based relational time series database (TSDB) with in-memory (IMDB) abilities, developed and marketed by KX Systems. The database is commonly used in high-frequency trading (HFT) to store, analyze, process, and retrieve large data sets at high speed. kdb+ has the ability to handle billions of records and analyzes data within a database. The database is available in 32-bit and 64-bit versions for several operating systems. Financial institutions use kdb+ to analyze time series data such as stock or commodity exchange data. The database has also been used for other time-sensitive data applications including commodity markets such as energy trading, telecommunications, sensor data, log data, machine and computer network usage monitoring along with real time analytics in Formula One racing. == Overview == kdb+ is a high-performance column-store database that was designed to process and store large amounts of data. Commonly accessed data is pushed into random-access memory (RAM), which is faster to access than data in disk storage. Created with financial institutions in mind, the database was developed as a central repository to store time series data that supports real-time analysis of billions of records. kdb+ has the ability to analyze data over time and responds to queries similar to Structured Query Language (SQL). Columnar databases return answers to some queries in a more efficient way than row-based database management systems. kdb+ dictionaries, tables and nanosecond time stamps are native data types and are used to store time series data. At the core of kdb+ is the built-in programming language, q, a concise, expressive query array language, and dialect of the language APL. Q can manipulate streaming, real-time, and historical data. kdb+ uses q to aggregate and analyze data, perform statistical functions, and join data sets and supports SQL queries The vector language q was built for speed and expressiveness and eliminates most need for looping structures. kdb+ includes interfaces in C, C++, Java, C#, and Python. == History == In 1998, KX released kdb, a database built on the language K written by Arthur Whitney. In 2003, kdb+ was released as a 64-bit version of kdb. In 2004, the kdb+ tick market database framework was released along with kdb+ taq, a loader for the New York Stock Exchange (NYSE) taq data. kdb+ was created by Arthur Whitney, building on his prior work with array languages. In April 2007, KX announced that it was releasing a version of kdb+ for Mac OS X. Then, kdb+ was also available on the operating systems Linux, Windows, and Solaris. In September 2012, version 3.0 was released. It was optimized for Intel's upgraded processors with support for WebSockets, and universally unique identifiers (UUIDs, termed globally unique identifiers (GUID)s in Microsoft software). Intel's Advanced Vector Extensions (AVX) and Streaming SIMD Extensions 4 (SSE4) 4.2 on the Sandy Bridge processors of the time allowed for enhanced support of the kdb+ system. In June 2013, version 3.1 was released, with benchmarks up to 8 times faster than older versions. In March 2020, version 4.0 was released. New features included Multithreaded primitives, Intel Optane DC persistent memory support and Data at Rest Encryption.

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  • Fabric Connect

    Fabric Connect

    Fabric Connect, in computer networking usage, is the name used by Extreme Networks to market an extended implementation of the IEEE 802.1aq and IEEE 802.1ah-2008 standards. The Fabric Connect technology was originally developed by the Enterprise Solutions R&D department within Nortel Networks. In 2009, Avaya, Inc acquired Nortel Networks Enterprise Business Solutions; this transaction included the Fabric Connect intellectual property together with all of the Ethernet Switching platforms that supported it. Subsequently, the Fabric Connect technology became part of the Extreme Networks portfolio by virtue of their 2017 purchase of the Avaya Networking business and assets. It was during the Avaya era that this technology was promoted as the lead element of the Virtual Enterprise Network Architecture (VENA). == Technologies == === Fabric Connect === Fabric Connect's provides network-wide, end-to-end, multi-layer virtualization. A network virtualization capability, based on an enhanced implementation of the IEEE 802.1aq Shortest Path Bridging (SPB) standard, Fabric Connect offers the ability to create a simplified network that can dynamically virtualize elements to efficiently provision and utilize resources, thus reducing the strain on the network and personnel. Extreme Networks base the Fabric Connect technology on the SPB standard, including support for RFC 6329, and have integrated IP Routing and IP Multicast support; this unified technology allows for the replacement of multiple conventional protocols such as Spanning Tree, RIP and/or OSPF, ECMP, and PIM. === Fabric Attach === An adjunct to the Fabric Connect technology, Fabric Attach allows network operators to extend network virtualization directly into conventional wiring closets (using existing non-Fabric Ethernet switches) and automate the provisioning of devices to their appropriate virtual network. This is particularly relevant for the mass of unattended network end-point that are now appearing, such as IP Phones, Wireless Access Points, and IP Cameras. Fabric Attach standardized protocols such as 802.1AB LLDP to exchange credentials and obtain provisioning information that allows "Client" Switches to be automatically re-configured on the fly with parameters that let Traffic Flows Map through to Fabric Connect Edge Switches (aka "Backbone Edge Bridge" in SPB definition) functioning as a Fabric Attach "Server" Switch. This method is described by an IETF "Internet Draft", pending further standardization activity. Fabric Attach is typically used to automate Wiring Closet connectivity, but has the potential to be extensible for use in the Data Center, with Virtual Machines being able to dynamically request VLAN/VSN (Virtual Service Network) assignment based upon application requirements. == Hardware products == === Virtual Services Platform 9000 Series === A range of modular chassis-based products, featuring a carrier-grade Linux operation system, and designed for high-performance deployment scenarios that need to scale to multiple terabits of switching capacity and support 10 and 40 gigabit Ethernet connections, and is designed eventually to support 100 gigabit Ethernet. === Virtual Services Platform 8000 Series === A compact form-factor platform delivering high-density 10/40 gigabit Ethernet connectivity, and targeted at mid-market through to mid-size enterprise core switch applications. === Virtual Services Platform 7000 Series === A range of high-end 10 gigabit Ethernet stackable switches that extend fabric-based networking to the data center top-of-rack. They support 40 gigabit Ethernet via the MDA Slot. === Virtual Services Platform 4000 Series === A range of high-end gigabit Ethernet stackable switches that extend Fabric-based networking to branch and metro locations. === Ethernet Routing Switch 5000 Series === A range of high-end gigabit Ethernet stackable switches that provides enterprise-class desktop features, including PoE, and offers 10 Gbit/s uplink connections. Each Switch supports up to 144 Gbit/s of virtual backplane capacity, delivering up to 1.152 Tbit/s for a system of eight, creating a virtual backplane through a stacking configuration. === Ethernet Routing Switch 4000 Series === A range of gigabit Ethernet stackable switches that provide enterprise-class desktop features, including PoE/PoE+, and offer 1/10 Gbit/s uplink connections. Each switch supports up to 48 Gbit/s of virtual backplane capacity, delivering up to 384 Gbit/s for a system of 8, creating a virtual backplane through a stacking configuration. === Ethernet Routing Switch 3500 Series === These entry-level gigabit Ethernet stackable switches provide enterprise-class desktop features, including PoE/PoE+, and 1 Gbit/s uplink connections.

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  • Puck App

    Puck App

    Puck App is a mobile application that allows hockey players to quickly find and rent a hockey goalie. Founded in 2015 in Toronto, the application primarily operates throughout Canada. It is available on Apple's App Store and Google Play. == History == Puck App was founded in 2016 by Niki Sawni. Users can rate the goalies, message with available goalies, and coordinate skill levels. In 2017, Puck App expanded to Western Canada and has over 1,000 goalies registered. In 2018, Puck App charged approximately $40 CDN to rent a goalie with more than 2 hours notice. Previously, Puck App was a competitor to a similar application called GoalieUp. As of 2024, both companies have agreed to a merger deal.

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  • Key frame

    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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