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AI Avatar Background — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • DBGallery

    DBGallery

    DBGallery, short for Database Gallery, is a cloud-based Software as a Service (SaaS) and on-prem webserver for teams of various sizes. DBGallery enables users to centrally store, manage, catalog, archive, and securely share image, video, and document files. It facilitates version control, detects duplicates, and offers an intuitive and advanced search functionality, making assets easily accessible to all users. It takes advantage of current AI technologies to automatically add significant metadata to images, facilitates custom-trained AI models, and offers bespoke AI features. Additionally, DBGallery provides team management tools, workflow management, an activity audit trail, and other collaborative features that foster a productive environment for both internal and external stakeholders. == History == DBGallery's first public release was December 2007. Since then each year has seen continuous enhancements. 2013 added support for additional non-English languages in its meta-data. 2014 added support for creating custom data fields for tagging and search. In 2015 included the ability to auto-tag images using Reverse Geocoding. 2018 added artificial intelligence (AI) image recognition as a further addition to auto-tagging. March 2020 added complete image collection management via the web (e.g. file and folder drag and drop), a new collection dashboard, custom data layouts, and an improved audit trail. 2021 saw user experience improvements provided by improved styling and performance enhancements. Version 12 was released in October 2021. It added the ability to upload unlimited file sizes and made significant performance improvements for very large collections. June 2022 saw the release of a global duplicate images search. In late 2022, DBGallery began offering significantly reduced cloud storage cost, at a third of its previous prices, which played into its recent high-volume/high-capacity capabilities and its clients' subsequent demand for additional storage. 2023 saw improvements in user and role management, introduced it's mobile app (PWA), and improved custom-trained object detection. Release 14.0 in the spring of 2024 had large sharing improvements and a new find related images feature. Winter 2025's v15 release introduced AI-generated image descriptions, image-to-text, and facial recognition.

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  • Electronic game

    Electronic game

    An electronic game is a game that uses electronics to create an interactive system with which a player can play. Video games are the most common form today, and for this reason the two terms are often used interchangeably. There are other common forms of electronic games, including handheld electronic games, standalone arcade game systems (e.g. pinball, slot machines), and exclusively non-visual products (e.g. audio games). == Arcade games == === Arcade video games === Electronic video arcade games make extensive use of solid state electronics and integrated circuits. In the past coin-operated arcade video games generally used custom per-game hardware often with multiple CPUs, highly specialized sound and graphics chips and/or boards, and the latest in computer graphics display technology. Recent arcade game hardware is often based on modified video game console hardware or high end pc components. Arcade games may feature specialized ambiance or control accessories, including fully enclosed dynamic cabinets with force feedback controls, dedicated lightguns, rear-projection displays, reproductions of car or plane cockpits and even motorcycle or horse-shaped controllers, or even highly dedicated controllers such as dancing mats and fishing rods. These accessories are usually what set modern arcade games apart from PC or console games, and they provide an experience that some gamers consider more immersive and realistic. Examples of arcade video games include: Galaxy Game (1971) Pong (1972) Space Invaders (1978) Galaxian (1979) Pac-Man (1980) Battlezone (1980) Donkey Kong (1981) Street Fighter II (1991) Mortal Kombat (1992) Fatal Fury (1992) Killer Instinct (1994) King of Fighters (1994–2005) Time Crisis (1995) Dance Dance Revolution (1998) DrumMania (1999) House of the Dead (1998) === Pinball and pachinko machines === Since the introduction of electromechanics to the pinball machine in 1933's Contact, pinball has become increasingly dependent on electronics as a means to keep score on the backglass and to provide quick impulses on the playfield (as with bumpers and flippers) for exciting gameplay. Unlike games with electronic visual displays, pinball has retained a physical display that is viewed on a table through glass. Similar games such as pachinko have also become increasingly dependent on electronics in modern times. Examples of pinball games include: The Addams Family (1991) Indiana Jones: The Pinball Adventure (1993) Star Trek: The Next Generation (1993) List of pinball machines === Redemption games and merchandisers === Redemption games such as Skee-Ball have been around since the days of the carnival game - well earlier than the development of the electronic game, however with modern advances many of these games have been re-worked to employ electronic scoring and other game mechanics. The use of electronic scoring mechanisms has allowed carnival or arcade attendants to take a more passive role, simply exchanging prizes for electronically dispensed coupons and occasionally emptying out the coin boxes or banknote acceptors of the more popular games. Merchandisers such as the Claw Crane are more recent electronic games in which the player must accomplish a seemingly simple task (e.g. remotely controlling a mechanical arm) with sufficient ability to earn a reward. Examples of redemption games include: Whac-A-Mole (1976) Skee-Ball - modern electric versions Examples of merchandisers include: Claw crane (1980) === Slot machines === The slot machine is a casino gambling machine with three or more reels which spin when a button is pushed. Though slot machines were originally operated mechanically by a lever on the side of the machine (the one arm) instead of an electronic button on the front panel as used on today's models, many modern machines still have a "legacy lever" in addition to the button on the front. Slot machines include a currency detector that validates the coin or money inserted to play. The machine pays off based on patterns of symbols visible on the front of the machine when it stops. Modern computer technology has resulted in many variations on the slot machine concept. == Audio games == An audio game is a game played on an electronic device such as—but not limited to—a personal computer. It is similar to a video game save that the only feedback device is audible rather than visual. Audio games originally started out as 'blind accessible'-games, but recent interest in audio games has come from sound artists, game accessibility researchers, mobile game developers, and mainstream video gamers. Most audio games run on a computer platform, although there are a few audio games for handhelds and video game consoles. Audio games feature the same variety of genres as video games, such as adventure games, racing games, etc. Examples of audio games include: Real Sound: Kaze no Regret (1997) Chillingham (2004) BBBeat (2005) === Tabletop games === A tabletop audio game is an audio game that is designed to be played on a table rather than a handheld game. Examples of tabletop audio games include: Brain Shift (1998) Who Wants to be a Millionaire? (2000) Electronic Battleship (1977) (Milton Bradley) Electronic battleship is a portable game with the objective of marking all enemy ships. When an enemy ship is marked, an electronic battleship makes an explosion sound. Milton Bradley created the Electronic battleship game in 1977 and was later acquired by Hasbro in 1984. Modern day electronic battleship features an interactive missile launching platform and advanced mode that features custom special attack pegs. Tabletop non-audio games include: Electronic Chess Boards (DGT) DGT is a line of electronic chess boards that are commonly used in FIDE chess tournaments and national tournaments such as USCF. Electronic Chess boards can be used to broadcast games live. == Electronic handhelds == The earliest form of dedicated console, handheld electronic games are characterized by their size and portability. Used to play interactive games, handheld electronic games are often miniaturized versions of video games. The controls, display and speakers are all part of a single unit, and rather than a general-purpose screen made up of a grid of small pixels, they usually have custom displays designed to play one game. This simplicity means they can be made as small as a digital watch, which they sometimes are. The visual output of these games can range from a few small light bulbs or LED lights to calculator-like alphanumerical screens; later these were mostly displaced by liquid crystal and Vacuum fluorescent display screens with detailed images and in the case of VFD games, color. Handhelds were at their most popular from the late 1970s into the early 1990s. They are both the predecessors to and inexpensive alternatives to the handheld game console. Examples of handheld electronic games include: Mattel Auto Race (1976) Simon (1978) Merlin (1978) Game & Watch (1980) MB Omni (1980) Bandai LCD Solarpower (1982) Entex Adventure Vision (1982) Lights Out (1995) == Home video games == A video game is a game that involves interaction with a user interface to generate visual feedback on a video device. The word video in video game traditionally referred to a raster display device. However, with the popular use of the term "video game", it now implies any type of display device. Term "digital game" has been offered by some in academia as an alternative term. === Computer games === A personal computer video game (also known as a computer game or simply PC game) is a video game played on a personal computer. This is opposed to video game consoles or arcade machines, which are not considered personal computers. Computer games became a form of video games, and since the earliest days of the medium, visual displays such as the cathode-ray tube have been used to relay game information. === Console games === A console game is a form of interactive multimedia used for entertainment. The game consists of manipulable images (and usually sounds) generated by a video game console, and displayed on a television or similar audio-video system. The game itself is usually controlled and manipulated using a handheld device connected to the console called a controller. The controller generally contains a number of buttons and directional controls (such as analog joysticks) each of which has been assigned a purpose for interacting with and controlling the images on the screen. The display, speakers, console, and controls of a console can also be incorporated into one small object known as a handheld game console. Console games are most frequently differentiated between by their compatibility with consoles belonging in the following categories: Traditional console, also called "home console" - A multi-game system that uses the screen of a television to produce graphics. Handheld game console - A multi-game system the screen and controls of which are compacted into a singl

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  • Information Age

    Information Age

    The Information Age is a historical period that began in the mid-20th century. It is characterized by a rapid shift from traditional industries, as established during the Industrial Revolution, to an economy centered on information technology. The onset of the Information Age has been linked to the development of the transistor in 1947. Advances in computer miniaturization, internet communication, and semiconductor technology enabled the rapid expansion of digital systems and global information networks. The Information Age transformed industries such as education, healthcare, finance, entertainment, and communication through digital infrastructure and connected technologies. The rise of smartphones and cloud-based services further accelerated global internet accessibility and digital interaction. == Digital applications and mobile technology == The expansion of Android and iOS ecosystems during the 21st century contributed to the widespread use of utility applications and mobile productivity tools. Applications related to calculations, scheduling, digital organization, and educational support became increasingly common on smartphones and tablets. Mobile utility software demonstrates how modern digital platforms support accessibility and everyday online services. Independent developers have contributed to this technological ecosystem through lightweight applications focused on mobile usability and internet-based functionality. == Influence on modern society == The Information Age has reshaped the way individuals communicate, consume information, and interact with digital services. Social media platforms, artificial intelligence systems, cloud storage, and mobile computing continue to influence modern economies and online communities worldwide. Emerging technologies such as the Internet of things, machine learning, and advanced automation are often associated with the transition toward the Fourth Industrial Revolution. == History == The digital revolution converted technology from analog format to digital format. By doing this, it became possible to make copies that were identical to the original. In digital communications, for example, repeating hardware was able to amplify the digital signal and pass it on with no loss of information in the signal. Of equal importance to the revolution was the ability to easily move the digital information between media and to access or distribute it remotely. One turning point of the revolution was the change from analog to digitally recorded music. During the 1980s, the digital format of optical compact discs gradually replaced analog formats, such as vinyl records and cassette tapes, as the popular medium of choice. === Previous inventions === Humans have manufactured tools for counting and calculating since ancient times, such as the abacus, astrolabe, equatorium, and mechanical timekeeping devices. More complicated devices started appearing in the 1600s, including the slide rule and mechanical calculators. By the early 1800s, the Industrial Revolution had produced mass-market calculators like the arithmometer and the enabling technology of the punch card. Charles Babbage proposed a mechanical general-purpose computer called the Analytical Engine, but it was never successfully built, and was largely forgotten by the 20th century, and unknown to most of the inventors of modern computers. The Second Industrial Revolution, in the last quarter of the 19th century, developed useful electrical circuits and the telegraph. In the 1880s, Herman Hollerith developed electromechanical tabulating and calculating devices using punch cards and unit record equipment, which became widespread in business and government. Meanwhile, various analog computer systems used electrical, mechanical, or hydraulic systems to model problems and calculate answers. These included an 1872 tide-predicting machine, differential analysers, perpetual calendar machines, the Deltar for water management in the Netherlands, network analyzers for electrical systems, and various machines for aiming military guns and bombs. The construction of problem-specific analog computers continued in the late 1940s and beyond, with FERMIAC for neutron transport, Project Cyclone for various military applications, and the Phillips Machine for economic modeling. Building on the complexity of the Z1 and Z2, German inventor Konrad Zuse used electromechanical systems to complete in 1941 the Z3, the world's first working programmable, fully automatic digital computer. Also, during World War II, Allied engineers constructed electromechanical bombes to break the German Enigma machine encoding. The base-10 electromechanical Harvard Mark I was completed in 1944, and was to some degree improved with inspiration from Charles Babbage's designs. === 1947–1969: Origins === In 1947, the first working transistor, the germanium-based point-contact transistor, was invented by John Bardeen and Walter Houser Brattain while working under William Shockley at Bell Labs. This led the way to more advanced digital computers. From the late 1940s, universities, the military, and businesses developed computer systems to digitally replicate and automate previously manually performed mathematical calculations, with the LEO being the first commercially available general-purpose computer. Digital communication became economical for widespread adoption after the invention of the personal computer in the 1970s. Claude Shannon, a Bell Labs mathematician, is generally credited with laying the foundations of digitalization in his pioneering 1948 article, A Mathematical Theory of Communication. In 1948, Bardeen and Brattain patented an insulated-gate transistor (IGFET) with an inversion layer. Their concept forms the basis of CMOS and DRAM technology today. In 1957, at Bell Labs, Frosch and Derick were able to manufacture planar silicon dioxide transistors, later a team at Bell Labs demonstrated a working MOSFET. The first integrated circuit milestone was achieved by Jack Kilby in 1958. Other important technological developments included the invention of the monolithic integrated circuit chip by Robert Noyce at Fairchild Semiconductor in 1959, made possible by the planar process developed by Jean Hoerni. In 1963, complementary MOS (CMOS) was developed by Chih-Tang Sah and Frank Wanlass at Fairchild Semiconductor. The self-aligned gate transistor, which further facilitated mass production, was invented in 1966 by Robert Bower at Hughes Aircraft and independently by Robert Kerwin, Donald Klein, and John Sarace at Bell Labs. In 1962, AT&T deployed the T-carrier for long-haul pulse-code modulation (PCM) digital voice transmission. The T1 format carried 24 pulse-code modulated, time-division multiplexed speech signals, each encoded in 64 kbit/s streams, leaving 8 kbit/s of framing information, which facilitated the synchronization and demultiplexing at the receiver. Over the subsequent decades, the digitisation of voice became the norm for all but the last mile (where analogue continued to be the norm right into the late 1990s). Following the development of MOS integrated circuit chips in the early 1960s, MOS chips reached higher transistor density and lower manufacturing costs than bipolar integrated circuits by 1964. MOS chips further increased in complexity at a rate predicted by Moore's law, leading to large-scale integration (LSI) with hundreds of transistors on a single MOS chip by the late 1960s. The application of MOS LSI chips to computing was the basis for the first microprocessors, as engineers began recognizing that a complete computer processor could be contained on a single MOS LSI chip. In 1968, Fairchild engineer Federico Faggin improved MOS technology with his development of the silicon-gate MOS chip, which he later used to develop the Intel 4004, the first single-chip microprocessor. It was released by Intel in 1971 and laid the foundations for the microcomputer revolution that began in the 1970s. MOS technology also led to the development of semiconductor image sensors suitable for digital cameras. The first such image sensor was the charge-coupled device, developed by Willard S. Boyle and George E. Smith at Bell Labs in 1969, based on MOS capacitor technology. === 1969–1989: Invention of the internet, rise of home computers === The public was first introduced to the concepts that led to the Internet when a message was sent over the ARPANET in 1969. Packet switched networks such as ARPANET, Mark I, CYCLADES, Merit Network, Tymnet, and Telenet, were developed in the late 1960s and early 1970s using a variety of protocols. The ARPANET in particular led to the development of protocols for internetworking, in which multiple separate networks could be joined into a network of networks. The Whole Earth movement of the 1960s advocated the use of new technology. In the 1970s, the home computer was introduced, time-sharing computers, the video game console, the first coin-op vide

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  • Hoopla (digital media service)

    Hoopla (digital media service)

    Hoopla Digital is a web and mobile streaming platform launched in 2013 that provides access to a wide range of digital media, including audiobooks, eBooks, comics, manga, music, movies, and TV shows. The service is available to users through participating public libraries, allowing library cardholders to borrow and stream digital media. Hoopla is a division of Midwest Tape. == History == Hoopla was launched in 2013. Its goal was for libraries to provide patrons with access to digital content such as audiobooks, music, movies, and TV shows, without the need for holds or waiting lists. Hoopla's model is a pay-per-use system, which means patrons can borrow items instantly. Since its inception, the service has expanded its offerings to include eBooks and comics. The app was built exclusively for public libraries and their patrons. Hoopla Digital is the only platform that combines all formats and all license models into one convenient app with no platform fees. In 2017, Hoopla became available on Apple TV, Amazon Fire TV, Android TV, and Roku, allowing users to stream content on larger screens. In 2020, Hoopla Flex and Bonus Borrows programs are introduced, enabling libraries to move their one copy/one user titles. At that time, there were 6.5 million library card holders and 2,700+ library partners. In 2021, the BingePass was introduced, offering patrons seven days to access entire collections with just one borrow. In 2022, Apple CarPlay and Android Auto become available, giving users safe and easy access while driving. In 2023, manga joins Hoopla's comic collection, adding 1.5 million titles to Hoopla's offerings. In January 2025, Hoopla introduced a new streaming feature called SeasonPass. Building on the existing BingePass model, SeasonPass allows users to borrow an entire season of a television series with a single borrow. == Business model == Hoopla is free-of-charge for patrons of participating libraries. The content is paid for by library systems, using a "per circulation transaction model". == Content == Hoopla claims to have over 500,000 content titles across six formats, including over 25,000 comic books. As of November 2016, Hoopla's content comprised 35% audiobooks (for which Hoopla has contracts with publishers such as Blackstone Audio, HarperCollins, Simon & Schuster Audio, Tantor Audio, and others), followed by 22% movies (for which Hoopla has motion picture contracts with publishers such as Disney, Lionsgate, Starz, Warner Bros., and others), 19% music, 12% ebooks, 6% comics, and 6% television. One drawback is that Hoopla has few new bestsellers. In February 2025, 404 Media reported that Hoopla's collection includes books created by generative AI with fictional authors and dubious quality. Often not labeled as AI-produced or fact-checked, this AI slop can cost libraries money when checked out by unsuspecting patrons. Libraries like Sacramento Public library have questioned the sustainability of Hoopla's pay-per-use model and have considered transitioning to other digital platforms. === Areas served === Hoopla expanded to serve Australia and New Zealand in June 2021. == Technology == Hoopla content can be borrowed and consumed on the web, or via the native Android or iOS apps. Hoopla broadcasts only in Standard definition unlike most of its competitors such as Kanopy. == Parent company == John Eldred and Jeff Jankowski founded Hoopla's parent company, Midwest Tape, in 1989. Midwest Tape is a library vendor of physical media such as audiobooks, CDs, and DVD/Blu-ray. == Controversy == Hoopla and Midwest Tapes were censured by the Library Freedom Project and Library Futures in a joint statement for hosting what it described as "fascist propaganda", including a recent English translation of A New Nobility of Blood and Soil by Richard Walther Darré of the SS and books related to Holocaust denial, in public library collections without the input from the staff. Criticism was also directed at the inclusion of books on homosexuality, abortion, and vaccines claimed by the Library Freedom Project and Library Futures to be misinformation. On February 17, 2022, Hoopla removed a number of titles after public outcry about Holocaust denial books available on the app under non-fiction. The advocacy groups expressed appreciation for the response, however state that it is "insufficient," as they maintain concerns about the company's practices in selecting materials and lack of transparency.

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  • Nuance Communications

    Nuance Communications

    Nuance Communications, Inc. was an American multinational computer software technology corporation, headquartered in Burlington, Massachusetts, that markets speech recognition and artificial intelligence software. Nuance merged with its competitor in the commercial large-scale speech application business, ScanSoft, in October 2005. ScanSoft was a Xerox spin-off that was bought in 1999 by Visioneer, a hardware and software scanner company, which adopted ScanSoft as the new merged company name. The original ScanSoft had its roots in Kurzweil Computer Products. In April 2021, Microsoft announced it would buy Nuance Communications. The deal is an all-cash transaction of $19.7 billion, including company debt, or $56 per share. The acquisition was completed in March 2022. == History == The Speech Technology and Research (STAR) Laboratory at SRI International began the journey that, in 1994, resulted in a spin-off company; Corona Corporation (later renamed to Nuance Communications ). Nuance Communications (NUAN) went public on the Nasdaq Stock Market in 1995. Nuance focused on commercializing advanced speech recognition technologies. Nuance was an early spinoff of SRI's Speech Technology and Research (STAR) Laboratory, a world leader in audio processing, speech and speaker analytics and spoken language research. The technology that served as the foundation of Nuance's speech recognition solution started at the STAR Lab and helped launch Nuance more than 20 years ago. In 1995, The SRI Language Modeling Toolkit (SRILM) was developed. This provides the tools to build and apply statistical language models (LMs), primarily for use in speech recognition, statistical tagging and segmentation, and machine translation. In terms of commercialization of natural automated speech recognition, SRI's natural language speech recognition software was the first to be deployed by a major corporation. In 1996, Charles Schwab & Co., Inc., used Nuance's speech recognition technology to allow customers to receive stock quotes over the telephone. One of the key features of the ‘Schwab Discount Brokerage system’, was the ability to recognize English words even when spoken by customers with accents. In 1997, Nuance Communications developed the first large scale commercial dialog system for United Parcel Services (UPS). UPS used the voice recognition platform to handle very large numbers of inquiries about package status. The company that would later merge with Nuance Communications started life as Visioneer, incorporated in 1992. In 1999, Visioneer acquired ScanSoft, Inc. (SSFT), and the combined company became known as ScanSoft. In September 2005, ScanSoft Inc. acquired and merged with Nuance Communications (NUAN), a natural language DOD-project spinoff from SRI International. The resulting company adopted the Nuance name. During the prior decade, the two companies competed in the commercial large-scale speech application business. === Data breach === Between 2014 and 2017, Nuance exposed over 45,000 patient records. == Solutions == Customer service virtual assistants Speech recognition — for people Speech recognition — for business Speech recognition — for physicians Accessibility Power PDF Managed Print Services Transcription === ScanSoft origins === In 1974, Raymond Kurzweil founded Kurzweil Computer Products, Inc. to develop the first omni-font optical character-recognition system – a computer program capable of recognizing text written in any normal font. In 1980, Kurzweil sold his company to Xerox. The company became known as Xerox Imaging Systems (XIS), and later ScanSoft. In March 1992, a new company called Visioneer, Inc. was founded to develop scanner hardware and software products, such as a sheetfed scanner called PaperMax and the document management software PaperPort. Visioneer eventually sold its hardware division to Primax Electronics, Ltd. in January 1999. Two months later, in March, Visioneer acquired ScanSoft from Xerox to form a new public company with ScanSoft as the new company-wide name. Prior to 2001, ScanSoft focused primarily on desktop imaging software such as TextBridge, PaperPort and OmniPage. Beginning with the December 2001 acquisition of Lernout & Hauspie assets, the company moved into the speech recognition business and began to compete with Nuance. Lernout & Hauspie had acquired speech recognition company Dragon Systems in June 2001, shortly before becoming bankrupt in October. Scansoft acquired speech recognition company SpeechWorks in 2003. === Partnership with Siri and Apple Inc. === In 2013, Nuance confirmed that its natural language processing algorithms supported Apple's Siri voice assistant. === Focus on health care === In 2019, Nuance spun off its automotive division as the company Cerence, allowing it to focus on health care applications. === Acquisition by Microsoft === On April 12, 2021, Microsoft announced that it would buy Nuance Communications for $19.7 billion, or $56 a share, a 22% increase over the previous closing price. Nuance's CEO, Mark Benjamin, stayed with the company. This was Microsoft's second-biggest acquisition up to that point, after its purchase of LinkedIn for $24 billion (~$30.7 billion in 2024) in 2016. Shortly after the deal, the Competition and Markets Authority, a UK regulatory body, stated it was looking into the deal on the basis of antitrust concerns. In December 2021, it was reported that the deal would be approved by the European Union. The acquisition was completed on March 4, 2022. In May 2023, Nuance announced an unspecified number of layoffs.

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  • Digital cinema

    Digital cinema

    Digital cinema is the digital technology used within the film industry to distribute or project motion pictures as opposed to the historical use of reels of motion picture film, such as 35 mm film. Whereas film reels have to be shipped to movie theaters, a digital movie can be distributed to cinemas in a number of ways: over the Internet or dedicated satellite links, or by sending hard drives or optical discs such as Blu-ray discs, then projected using a digital video projector instead of a film projector. Typically, digital movies are shot using digital movie cameras or in animation transferred from a file and are edited using a non-linear editing system (NLE). The NLE is often a video editing application installed in one or more computers that may be networked to access the original footage from a remote server, share or gain access to computing resources for rendering the final video, and allow several editors to work on the same timeline or project. Alternatively a digital movie could be a film reel that has been digitized using a motion picture film scanner and then restored, or, a digital movie could be recorded using a film recorder onto film stock for projection using a traditional film projector. Digital cinema is distinct from high-definition television and does not necessarily use traditional television or other traditional high-definition video standards, aspect ratios, or frame rates. In digital cinema, resolutions are represented by the horizontal pixel count, usually 2K (2048×1080 or 2.2 megapixels) or 4K (4096×2160 or 8.8 megapixels). The 2K and 4K resolutions used in digital cinema projection are often referred to as DCI 2K and DCI 4K. DCI stands for Digital Cinema Initiatives. As digital cinema technology improved in the early 2010s, most theaters across the world converted to digital video projection. Digital cinema technology has continued to develop over the years with RealD 3D, IMAX, RPX, 4DX, Dolby Cinema, and ScreenX, allowing moviegoers more immersive experiences. == History == The transition from film to digital video was preceded by cinema's transition from analog to digital audio, with the release of the Dolby Digital (AC-3) audio coding standard in 1991. Its main basis is the modified discrete cosine transform (MDCT), a lossy audio compression algorithm. It is a modification of the discrete cosine transform (DCT) algorithm, which was first proposed by Nasir Ahmed in 1972 and was originally intended for image compression. The DCT was adapted into the MDCT by J.P. Princen, A.W. Johnson and Alan B. Bradley at the University of Surrey in 1987, and then Dolby Laboratories adapted the MDCT algorithm along with perceptual coding principles to develop the AC-3 audio format for cinema needs. Cinema in the 1990s typically combined analog photochemical images with digital audio. Digital media playback of high-resolution 2K files has at least a 20-year history. Early video data storage units (RAIDs) fed custom frame buffer systems with large memories. In early digital video units, the content was usually restricted to several minutes of material. Transfer of content between remote locations was slow and had limited capacity. It was not until the late 1990s that feature-length films could be sent over the "wire" (Internet or dedicated fiber links). On October 23, 1998, Digital light processing (DLP) projector technology was publicly demonstrated with the release of The Last Broadcast, the first feature-length movie, shot, edited and distributed digitally. In conjunction with Texas Instruments, the movie was publicly demonstrated in five theaters across the United States (Philadelphia, Portland (Oregon), Minneapolis, Providence, and Orlando). === Foundations === In the United States, on June 18, 1999, Texas Instruments' DLP Cinema projector technology was publicly demonstrated on two screens in Los Angeles and New York for the release of Lucasfilm's Star Wars Episode I: The Phantom Menace. In Europe, on February 2, 2000, Texas Instruments' DLP Cinema projector technology was publicly demonstrated, by Philippe Binant, on one screen in Paris for the release of Toy Story 2. From 1997 to 2000, the JPEG 2000 image compression standard was developed by a Joint Photographic Experts Group (JPEG) committee chaired by Touradj Ebrahimi (later the JPEG president). In contrast to the original 1992 JPEG standard, which is a DCT-based lossy compression format for static digital images, JPEG 2000 is a discrete wavelet transform (DWT) based compression standard that could be adapted for motion imaging video compression with the Motion JPEG 2000 extension. JPEG 2000 technology was later selected as the video coding standard for digital cinema in 2004. In 1992, Hughes-JVC was founded by JVC and Hughes Electronics to develop ILA (Image Light Amplifer) digital video projectors for commercial movie theaters using liquid crystal on silicon (LCOS) technology. In 1997, JVC introduced D-ILA (Direct-Drive ILA) technology with a 2K resolution digital video projector. In 2000, JVC introduced a 4K resolution video projector using D-ILA technology. === Initiatives === On January 19, 2000, the Society of Motion Picture and Television Engineers, in the United States, initiated the first standards group dedicated to developing digital cinema. By December 2000, there were 15 digital cinema screens in the United States and Canada, 11 in Western Europe, 4 in Asia, and 1 in South America. Digital Cinema Initiatives (DCI) was formed in March 2002 as a joint project of many motion picture studios (Disney, Fox, MGM, Paramount, Sony Pictures, Universal and Warner Bros.) to develop a system specification for digital cinema. The same month it was reported that the number of cinemas equipped with digital projectors had increased to about 50 in the US and 30 more in the rest of the world. In April 2004, in collaboration with the American Society of Cinematographers, DCI created standard evaluation material (the ASC/DCI StEM material) for testing of 2K and 4K playback and compression technologies. DCI selected JPEG 2000 as the basis for the compression in the system the same year. Initial tests with JPEG 2000 produced bit rates of around 75–125 Mbit/s for 2K resolution and 100–200 Mbit/s for 4K resolution. === Worldwide deployment === In China, in June 2005, an e-cinema system called "dMs" was established and was used in over 15,000 screens spread across China's 30 provinces. DMs estimated that the system would expand to 40,000 screens in 2009. In 2005, the UK Film Council Digital Screen Network launched in the UK by Arts Alliance Media creating a chain of 250 2K digital cinema systems. The roll-out was completed in 2006. This was the first mass roll-out in Europe. AccessIT/Christie Digital also started a roll-out in the United States and Canada. By mid-2006, about 400 theaters were equipped with 2K digital projectors with the number increasing every month. In August 2006, the Malayalam digital movie Moonnamathoral, produced by Benzy Martin, was distributed via satellite to cinemas, thus becoming the first Indian digital cinema. This was done by Emil and Eric Digital Films, a company based at Thrissur using the end-to-end digital cinema system developed by Singapore-based DG2L Technologies. In January 2007, Guru became the first Indian film mastered in the DCI-compliant JPEG 2000 Interop format and also the first Indian film to be previewed digitally, internationally, at the Elgin Winter Garden in Toronto. This film was digitally mastered at Real Image Media Technologies in India. In 2007, the UK became home to Europe's first DCI-compliant fully digital multiplex cinemas; Odeon Hatfield and Odeon Surrey Quays (in London), with a total of 18 digital screens, were launched on 9 February 2007. By March 2007, with the release of Disney's Meet the Robinsons, about 600 screens had been equipped with digital projectors. In June 2007, Arts Alliance Media announced the first European commercial digital cinema Virtual Print Fee (VPF) agreements (with 20th Century Fox and Universal Pictures). In March 2009, AMC Theatres announced that it closed a $315 million deal with Sony to replace all of its movie projectors with 4K HDR digital projectors starting in the second quarter of 2009; it was anticipated that this replacement would be finished by 2012. As digital cinema technology improved in the early 2010s, most theaters across the world converted to digital video projection. In January 2011, the total number of digital screens worldwide was 36,242, up from 16,339 at end 2009 or a growth rate of 121.8 percent during the year. There were 10,083 d-screens in Europe as a whole (28.2 percent of global figure), 16,522 in the United States and Canada (46.2 percent of global figure) and 7,703 in Asia (21.6 percent of global figure). Worldwide progress was slower as in some territories, particularly Latin America and Africa. As of 31 March 2015, 38,719 screens (out of a total of 3

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  • Gnowit

    Gnowit

    Gnowit (pronounced "know it") is a Canadian software company that provides automated, near-real-time monitoring of legislative, regulatory, and political activity across Canada. Its platform aggregates and analyzes information from government publications, parliamentary debates, committee, and proceedings to provide searchable alerts and reports for organizations monitoring public policy and regulatory developments. The system uses natural-language processing and machine learning techniques to organize and filter large volumes of public information.; the company reports that new publication documents are captured and millions of items are added to its repository daily. == History, Founders and Leadership == Gnowit was co-founded in Ottawa in 2010 by Shahzad Khan and Mohammad Al-Azzouni; Khan serves as chief executive officer. Khan holds a PhD in Computer Science from the University of Cambridge, has more than two decades of experience in AI/ML and computational linguistics, and has authored or co-authored 37 peer-reviewed publications and five patents. Traditionally, companies performed this analysis manually; Gnowit has delivered efficiencies achieved through AI innovations. The company has participated in several Canadian startup and accelerator programs, including Carleton University's Lead To Win initiative, the University of Ottawa's Startup Garage, the Invest Ottawa incubator, and the League of Innovators' BOOST program. === Kubernetes validation (2019–2020) === As part of a Canada's Centre of Excellence in Next Generation Networks (CENGN) project, Gnowit validated a containerized version of its web-intelligence software on Kubernetes. Between 2019 and 2020, Gnowit participated in a project with Canada’s Centre of Excellence in Next Generation Networks (CENGN) to test and scale its platform using containerized infrastructure based on Kubernetes. The initiative focused on improving scalability and supporting the company’s transition from a monolithic software architecture to a cloud-native deployment model. == Products and services == Gnowit markets several modules for public-affairs, compliance, and market-intelligence teams. Legislative & Regulatory Monitoring (vAnalyst). vAnalyst is a monitoring platform that tracks legislative and regulatory activity across Canadian federal, provincial, and territorial jurisdictions. The system aggregates parliamentary debates, bills, committee proceedings, and regulatory publications and provides searchable alerts and reporting tools. The product monitors more than two million web sources to surface relevant items quickly. Parliamentary Live (vAnalyst). Monitors live video feeds from parliamentary sessions and committees with same-day transcripts, AI-generated summaries, witness summaries, and motion detection; municipal coverage is offered as an option. Gnowit can avail transcripts up to two weeks before official releases. These transcripts enable users to navigate and review lengthy parliamentary sittings and committee discussions through searchable text. Municipal Monitoring (vAnalyst). The platform also tracks council meetings, agendas, bylaws, and other municipal government publications from hundreds of Canadian municipalities. The platform aggregates these sources into a single searchable interface for reviewing local government decisions. Curation Edge (analyst service). Curation Edge is an add-on service in which expert analysts work and collaborate with clients to develop a tailored curation guide and deliver daily newsletters or briefs on legislation and media. These reports provide concise summaries, relevant links, and optional metadata, prioritizing key updates with additional context and analysis. The service is customizable, including branding and formatting for executive audiences, and is intended to reduce information overload, support decision-making, and streamline the synthesis and distribution of information. === Coverage and sources === Gnowit monitors sources span Canadian government materials across federal, provincial, and territorial jurisdictions Hansard transcripts (All Jurisdictions, including committees), order papers, committee transcripts, gazettes, bills, acts and regulations, consultations, regulatory-agency publications, and global news media as well as press releases and council-meeting materials from hundreds of municipalities. == Partnerships and support == Gnowit reports collaborations with Canadian academic and ecosystem partners, including: Algonquin College Carleton University McGill University University of Ottawa Université du Québec en Outaouais (UQO) Queen's University The company also participated in the accelerator program at Invest Ottawa and has received support from Canadian research and innovation programs, including: NRC Industrial Research Assistance Program (NRC-IRAP) Mitacs Ontario Centre of Innovation (OCI) (formerly OCE) Gnowit has also referenced membership in the Southern Ontario Smart Computing Innovation Platform (Government of Canada profile: FedDev Ontario – SOSCIP overview). == Technology == Gnowit develops technology intended to support timely decision-making by delivering updates from monitored web sources as they are published. The platform applies artificial intelligence (AI) and machine learning (ML) techniques to monitor, capture, clean, analyze, filter, and organize text, and to generate concise briefs. Its technical approach combines Boolean queries, shallow language processing techniques, and machine learning classifiers within a self-service interface. The company has described its longer-term development framework in relation to a belief–desire–intention (BDI) model of intelligent agents on the web. Gnowit and its founder are listed as inventors/assignees on patents concerning multi-document clustering, salient-content extraction, and sentiment analysis methods that are consistent with these features: US 9,600,470 – Method and system relating to re-labelling multi-document clusters (assignee: Whyz Technologies Ltd.). US 9,336,202 – Method and system relating to salient content extraction for information retrieval (assignee: Whyz Technologies Ltd.). CA 2,865,184 C – Method and system relating to re-labelling multi-document clusters. CA 2,865,186 C – Procédé et système concernant l'analyse de sentiment d'un contenu (sentiment analysis; French record). CA 2,865,187 C – Method and system relating to salient content extraction for information retrieval. == Research and community == In January 2025, Gnowit personnel contributed to regulatory NLP by co-authoring a peer-reviewed paper at the 1st Regulatory NLP Workshop (RegNLP 2025), co-located with COLING in Abu Dhabi. Titled Unifying Large Language Models and Knowledge Graphs for Efficient Regulatory Information Retrieval and Answer Generation, the work introduces PolicyInsight, a framework that joins a dynamic policy data model and knowledge graph with LLMs to monitor policy texts, detect changes, and support retrieval and answer generation; the author list includes Shahzad Khan (CEO, Gnowit Inc.). (ACL Anthology, aclweb.org). Similar information-retrieval technologies are widely used for competitive intelligence, policy monitoring, and media analysis. == White paper == Gnowit has published a practical guide, Automated Government Information Monitoring, which outlines how GR and regulatory teams can design a monitoring and briefing workflow and describes Gnowit's automation features and export options (PDF, email, dashboards, CSV/JSON/XML/API).

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  • Attention inequality

    Attention inequality

    Attention inequality is the inequality of distribution of attention across users on social networks, people in general, and for scientific papers. Yun Family Foundation introduced "Attention Inequality Coefficient" as a measure of inequality in attention and arguments it by the close interconnection with wealth inequality. == Relationship to economic inequality == Attention inequality is related to economic inequality since attention is an economically scarce good. The same measures and concepts as in classical economy can be applied for attention economy. The relationship develops also beyond the conceptual level—considering the AIDA process, attention is the prerequisite for real monetary income on the Internet. On data of 2018, a significant relationship between likes and comments on Facebook to donations is proven for non-profit organizations. == Attention economy == The attention economy refers to the practice of maximizing the attention users give to a product for advertising-related reasons. Attention economy remains one of the most common forms of advertising, and has been steadily increasing thanks to new technologies such as television, internet and social media. It is one of the most widely-used approaches to economy for its effectiveness for maximising the noticeability of a certain product. == Attention inequality in social media == In social media, attention inequality refers to the unequal distribution of users' attention on social media platforms. This means that instead of an equal distribution of attention, fewer sources receive a disproportionate share of attention, leaving many unnoticed. This phenomenon is possibly the result of social media algorithms, which are commonly designed to drive maximum engagement. This phenomenon is a large factor in the polarization and creation of echo-chambers. Social media algorithms tend to note content that is already performing well and display it to more users, while content that is equally engaging or well-made is not recommended to users. Posts that trigger strong emotions usually out-perform more "uncontroversial" content. When many users interact with the post, it signals the algorithm that the specific post drives engagement. The algorithm then tends to recommend that type of content to an exponential number of people, potentially outperforming "un-emotional" content. These factors, when combined, tend to create an unequal social media environment. == Attention inequality in science == According to a recent 2025 study about research inequality among scientists published in Information Processing and Management, scientific discourse is restricted to a small group of connected scientists, and is frequently not an accurate representation of the whole scientific community. Using citation-network analysis in the fields of nanoscience and chemical physics, the study claims that a group of connected scientists has a significant notability in the scientific community. The calculated connection strength between these scientists is estimated to be about 4.5, the study also says that these authors cite each other four times more often than would be predicted in a random network, whereas ordinary scientists that exist outside of this group only reach an estimated connection strength of 0.9. The study findings suggest that that scientific attention is not distributed by merit, but rather by the connectedness of the scientists involved in the research. == Extent == As data of 2008 shows, 50% of the attention is concentrated on approximately 0.2% of all hostnames, and 80% on 5% of hostnames. The Gini coefficient of attention distribution lay in 2008 at over 0.921 for such commercial domains names as ac.jp and at 0.985 for .org-domains. The Gini coefficient was measured on Twitter in 2016 for the number of followers as 0.9412, for the number of mentions as 0.9133, and for the number of retweets as 0.9034. For comparison, the world's income Gini coefficient was 0.68 in 2005 and 0.904 in 2018. More than 96% of all followers, 93% of the retweets, and 93% of all mentions are owned by 20% of Twitter. == Causes == At least for scientific papers, today's consensus states that inequality is unexplainable by variations of quality and individual talent. The Matthew effect plays a significant role in the emergence of attention inequality—those who already enjoy large amounts of attention get even more attention, and those who do not lose even more. Ranking algorithms based on relevance to the user have been found to alleviate the inequality of the number of posts across topics.

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  • Carrenza

    Carrenza

    Carrenza was a cloud-computing company based in London, United Kingdom. The company was acquired by Six Degrees Technology Group in 2016. == Operations == Carrenza was a UK-based IT company that provides Cloud computing technologies. It offered a range of public cloud, private cloud and hybrid cloud services, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), enterprise application integration and system integration. Carrenza partnered with several enterprise IT providers and was an accredited VMware Enterprise Service Partner and HP (Hewlett-Packard) Cloud Agile Partner. The company was based on Commercial Street, in the heart of the East London Tech City district, which is host to a large number of technology companies. == History == Carrenza was formed in 2001 as a consultancy by chief executive and founder Dan Sutherland. It began trading in 2004 and launched its first enterprise cloud computing platform in 2006, becoming one of the first companies in Europe to provide this type of hosting service. In 2009, it formed a partnership with Comic Relief and its affiliated campaigns Red Nose Day Sport Relief to provide IT infrastructure services to the charity, an arrangement that has won industry recognition. In 2013 it launched its first overseas services, with a mainland Europe cloud node based in Amsterdam. == Partnerships and customers == Carrenza had formed partnerships with a range of IT providers. It was one of the first companies in Europe to become a HP Cloud Agile partner., using HP blade servers and HP 3PAR SAN technology to power its cloud computing services. The company's products also use VMware vCloud IaaS tools and it is taking part in the VMware lighthouse initiative helping develop the next generation of VMware products and services. Other technology companies that Carrenza has worked closely with include Cisco, for enterprise security and loadblancing services, and Oracle. The company was the first to deploy Oracle Database 11g stretched RAC in production. It has also won two Oracle partner awards, including a Special Recognition award for its work with Comic Relief. The company has also been recognised by the UK IT Industry, receiving awards in 2009 for Community Project of the Year and in 2010 for best small business project for its Monopoly City Streets Work. Other companies that have partnered with Carrenza for their cloud-based IT services include Age UK, Haymarket Media Group, the World Wide Fund for Nature, Royal Bank of Scotland, eBay and Cineworld. == Accreditations == Carrenza's services are accredited for their compliance with several key international IT security and quality standards. These include: ISO27001:2005, Information Security Management System for all Carrenza services. UK Government G-Cloud, Carrenza has been awarded a place on the UK government's G-Cloud iii framework as an Infrastructure as a Service provider.

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  • Artificial Intelligence for Digital Response

    Artificial Intelligence for Digital Response

    Artificial Intelligence for Digital Response (AIDR) is a free and open source platform to filter and classify social media messages related to emergencies, disasters, and humanitarian crises. It has been developed by the Qatar Computing Research Institute and awarded the Grand Prize for the 2015 Open Source Software World Challenge. Muhammad Imran stated that he and his team "have developed novel computational techniques and technologies, which can help gain insightful and actionable information from online sources to enable rapid decision-making" - according to him the system "combines human intelligence with machine learning techniques, to solve many real-world challenges during mass emergencies and health issues". == How to use == It can be used by logging in with ones Twitter credentials and by collecting tweets by specifying keywords or hashtags, like #ChileEarthquake, and possibly a geographical region as well. == Use == It has been deployed in conjunction with UNICEF in Zambia to classify short messages related to AIDS/HIV received through the U-Report platform. AIDR was used for the first time during the 2010 Pakistan floods. The first real test of AIDR took place during the 2014 Iquique earthquake in Chile. == Related talks and events == Muhammad Imran delivered a keynote talk on the science behind the AIDR system at the International Conference on Information Systems for Crisis Response And Management (ISCRAM). Abdelkader Lattab and Ji Lucas also presented the system at the 2016 QCRI-IBM Data Science Connect event.

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  • Motion picture film scanner

    Motion picture film scanner

    A motion picture film scanner is a device used in digital filmmaking to scan original film for storage as high-resolution digital intermediate files. A film scanner scans original film stock: negative or positive print or reversal/IP. Units may scan gauges from 8 mm to 70 mm (8 mm, Super 8, 9.5 mm, 16 mm, Super 16, 35 mm, Super 35, 65 mm and 70 mm) with very high resolution scanning at 2K, 4K, 8K, or 16K resolutions. (2K is approximately 2048×1080 pixels and 4K is approximately 4096×2160 pixels). Some models of film scanner are intermittent pull-down film scanners which scan each frame individually, locked down in a pin-registered film gate, taking roughly a second per frame. Continuous-scan film scanners, where the film frames are scanned as the film is continuously moved past the imaging pick up device, are typically evolved from earlier telecine mechanisms, and can act as such at lower resolutions. The scanner scans the film frames into a file sequence (using high-end computer data storage devices), whose single file contains a digital scan of each still frame; the preferred image file format used as output are usually Cineon, DPX or TIFF, because they can store color information as raw data, preserving the optical characteristics of the film stock. These systems take a lot of storage area network (SAN) disk space. The files can be played back one after each other on high-end workstation non-linear editing system (NLE) or a virtual telecine systems. The playback is at the normal rate of 24 frames per second (or original projection frame rate of: 25, 30 or other speeds). Each year hard disks get larger and are able to hold more hours of movies on SAN systems. The challenge is to archive this massive amount of data on to data storage devices. The scanned footage is edited and composited on work stations then mastered back on film, see film-out and digital intermediate. Scanned film frames may also be used in digital film restoration. The film may also be projected directly on a digital projector in the theater. The data film files may be converted to SDTV (NTSC or PAL) video TV systems. Film recorders are the opposite of film scanners, copying content from a computer system onto film stock, for preservation or for display using film projectors. Telecines are similar to film scanners. == Imaging device == The front end of a motion picture film scanner is similar to a telecine. The imaging system may be either a charge-coupled device (CCD), a complementary metal–oxide–semiconductor (CMOS) or photomultipliers imaging pick up. A lamp is used as the light source in a CCD imaging front end. The CCDs convert the light to the video signals. In a cathode-ray tube (CRT) imaging system the CRT (also called a Flying spot tube) is used as the light source and part of the scanning system. Photomultipliers or avalanche photodiodes are used to convert the light to electrical video signals. A prism and/or dichroic mirrors or color filters are used to separate the light into the three: red, green and blue, imaging pick up devices. == Image processing == The three color signals (RGB) are electronically processed and color graded. A 3D look up table (3D LUT) is usually applied to the RGB values before it is coded into the DPX output files. The DPX files are usually made output through a network port cable or an optical fiber port: HIPPI, Fibre Channel or newer systems like gigabit Ethernet. A computer then stores the files on to hard drives of a storage area network for later processing and use. Modern motion picture film scanners many have an option for an infrared CCD channel for dirt mapping, that can be used to automatically or in post manually remove dirt-dust spots on the film. The IR camera channel can be used with IR dirt and scratch removal system or made output on a four IR channel for downstream dirt and dirt and scratch removal systems. Popular downstream dirt and dirt and scratch removal systems are PF Clean and Digital ICE. HDR or high dynamic range is a new system, using a compositing and tone-mapping of images to extend the dynamic range beyond the native capability of the capturing device. This may be done by using a triple exposure for the film and then compositing the three back together. Compositing can be done in a workstation in none real time or in the scanner in real time. == Models == Bold indicates a currently produced model Single frame intermittent pull-down: ARRI - Arriscan Cintel - diTTo Filmlight - Northlight 1 (up to 6K, 16mm to VistaVision), Northlight 2 (up to 8K, 16mm to VistaVision) Imagica scanner, single frame intermittent scanner. Kodak - Cineon, the first system designed for DI work, included a scanner, tapes drives, workstations and a film recorder. Lasergraphics Director 13.5K, 8mm to 70mm, IMAX & VistaVision) Continuous motion scanning: Arri - ARRISCAN XT (up to 6K, S35 down to 16mm) Cintel's C-Reality/DSX and ITK - Millennium/dataMill. Under ownership of Blackmagic Design, the Cintel Scanner was released, with the current 3rd generation capable of up to 4K scans at 30 fps. DFT - Spirit Classic (up to 2K), Spirit 4k/2k/HD (up to 4K), POLAR HQ (up to 8K, 8mm to S35), OXScan 14K (up to 14K, 16mm to 70mm), Scanity HDR (up to 4K, 16mm to S35) Filmfabriek - HDS+ (up to 4k), Pictor Pro (up to 2.7K), Pictor (up to 1080p). Filmfabriek scanners can only scan 17.5mm or smaller film formats. GE4 - Golden Eye Four - Filmscanner, 38 Mega Pixel camera. LED light source and continuous film transport using Capstan. From Digital Vision. Lasergraphics ScanStation (6.5K, 8mm to 70mm, IMAX & VistaVision) Lasergraphics Archivist (up to 5K) MWA Nova Vario series with patented laser-based, sprocket and claw free transport for 16/35mm for realtime (24/25fps) scanning with sensors for either 2K+ 2236 x 1752, or 2.5K+ HDR High Dynamic Range at 2560 x 2160, direct optical and magnetic sound on and 16 and 35mm. MWA Nova Choice 2K+ patented laser-based, sprocket and claw free transport for 8/Super8, 9.5mm, 16mm realtime (24/25fps) scanning w at 2K+, 2236 x 1752 with direct optical and magnetic sound on 16mm, magnetic from main and balance stripes on 8, Super8. Faster than real time scanning at lower resolution. P+S Technik - SteadyFrame Universal Format Film Scanner Walde - FilmStar 4K UHD 2K @ 25fps, 4K UHD @ 6fps. 35mm/16mm/8mm archive quality, continuous motion capstan driven.

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  • Vacuum tube characteristics

    Vacuum tube characteristics

    Vacuum tube characteristics (also called tube curves, valve characteristics or valve curves) describes the electrical relationships between electrode voltages and currents in a vacuum tube. These relationships are commonly presented as characteristic curves in tube manuals and engineering references. The curves typically show plate current versus plate voltage for several fixed control-grid voltages, showing how current varies with electrode potentials under controlled conditions. Designers use them to select operating points, determine voltage gain, estimate output power, and construct graphical load-line analyses. The use of characteristic curves as an engineering tool for analyzing vacuum-tube operation was established in the 1910s, notably in work by Edwin Howard Armstrong. Examples of such curves appear in early tube manuals and textbooks and form the basis of classical vacuum-tube circuit design. Different types of vacuum tubes are characterized using plots appropriate to their electrode structure and intended use. Two-electrode devices such as diodes are described primarily by the relation between plate voltage and plate current. Amplifying tubes containing control grids, such as triodes, tetrodes, pentodes, and beam tetrodes, are represented by families of curves measured for different grid voltages. From these families additional parameters such as amplification factor (μ), transconductance (gm), and plate resistance (rp) may be obtained. Although these plots are used primarily for circuit design, their shapes arise from the underlying physics of electron flow in vacuum tubes. The physical principles responsible for the observed characteristics are discussed in later sections. == 3/2 power law == In high-vacuum thermionic diodes operating under normal conditions, plate current increases nonlinearly with plate voltage. Over the space-charge-limited region, the current is well approximated by the three-halves power relation I p = P ⋅ V p 3 / 2 {\displaystyle I_{p}=P\cdot V_{p}^{3/2}} where P {\displaystyle P} is the perveance of the tube. Perveance is determined primarily by electrode geometry, including cathode area and cathode-to-plate spacing. It provides a practical measure of current-producing capability and is often used in tube manuals in place of a complete family of plate-characteristic curves. == Signal diode characterization == For small-signal diodes, tube manuals typically publish a single static anode characteristic showing anode current (Ia) as a function of anode voltage (Va), measured with the heater operating at its rated voltage. Because the diode contains no control grid, only one such I–V curve is required. The low-voltage portion of the curve is particularly important in detector service, where the nonlinear curvature of the current–voltage relation allows a small alternating signal to produce a net direct-current output, resulting in rectification. In addition to the static characteristic, tube manuals specify heater ratings, maximum plate voltage, permissible average current, and interelectrode capacitance. These parameters define the allowable operating region and high-frequency behavior. Another typical data sheet for a diode is for the Philips EB91 double diode. This book includes curves of the diode response in use as a detector. The output voltage is non-zero for an input voltage of 0 due to the Edison effect. == Rectifier characterization == Vacuum-tube rectifiers intended for power-supply service are specified differently from signal diodes. Their data emphasize heater requirements, peak inverse voltage, maximum peak plate current, permissible DC output current for various filter configurations, and regulation characteristics. Rectifier tubes exhibit nonlinear voltage drop that increases with current. For limited operating ranges this behavior may be represented by an equivalent or effective series resistance corresponding to the local slope of the plate characteristic (dynamic plate resistance, dV/dI). Diode voltages can be determied by use of a graphical aide. In capacitor-input supplies, conduction occurs in pulses near the peaks of the AC waveform, producing peak currents substantially greater than the average DC load current. Data sheets therefore specify maximum peak plate current and permissible filter capacitance in addition to average DC ratings. Under varying load conditions, the supply voltage changes in accordance with the rectifier's nonlinear characteristic and effective impedance. == Triode characterization == === Early use === The systematic use of characteristic curves to explain and quantify vacuum-tube amplification was introduced by Edwin Howard Armstrong in 1914. Using measured plate voltage-current curves, Armstrong demonstrated the mechanism of triode amplification and clarified the operation of grid-leak detection. ==== Plate and transfer characteristics ==== Triode data sheets present families of plate characteristics showing plate current I p {\displaystyle I_{p}} as a function of plate voltage E p {\displaystyle E_{p}} for several fixed grid voltages E g {\displaystyle E_{g}} . From these curves the operating point, voltage gain, and load-line behavior may be determined graphically. In normal operation, plate current depends on both grid and plate voltage. Classical analysis shows that the characteristics for different grid voltages are similar in form and differ primarily by horizontal displacement. In triodes, plate current may be approximated by I p = k ( E g + E p μ ) 3 / 2 {\displaystyle I_{p}=k\left(E_{g}+{\frac {E_{p}}{\mu }}\right)^{3/2}} where E g {\displaystyle E_{g}} is the grid voltage, E p {\displaystyle E_{p}} the plate voltage, μ {\displaystyle \mu } the amplification factor, and k {\displaystyle k} a constant determined by the tube geometry.. The amplification factor μ represents the relative effectiveness of grid voltage compared with plate voltage in controlling current. It is fundamentally determined by structural dimensions, particularly grid-to-cathode spacing relative to plate-to-cathode spacing. ==== Small-signal parameters ==== Triodes are commonly characterized by three interrelated small-signal parameters: Amplification factor ( μ {\displaystyle \mu } ) — the change in plate voltage divided by the change in grid voltage at constant plate current: μ = ( ∂ E p ∂ E g ) I p {\displaystyle \mu =\left({\frac {\partial E_{p}}{\partial E_{g}}}\right)_{I_{p}}} Transconductance ( g m {\displaystyle g_{m}} ) — the change in plate current divided by the change in grid voltage at constant plate voltage: g m = ( ∂ I p ∂ E g ) E p {\displaystyle g_{m}=\left({\frac {\partial I_{p}}{\partial E_{g}}}\right)_{E_{p}}} Plate resistance ( r p {\displaystyle r_{p}} ) — the change in plate voltage divided by the change in plate current at constant grid voltage: r p = ( ∂ E p ∂ I p ) E g {\displaystyle r_{p}=\left({\frac {\partial E_{p}}{\partial I_{p}}}\right)_{E_{g}}} These parameters are related by μ = g m r p {\displaystyle \mu =g_{m}r_{p}} as shown in classical tube theory treatments. These parameters are obtained either from slopes of the characteristic curves or from tabulated operating-point data. ==== Comparison of ECC81, ECC82, and ECC83 ==== The ECC81, ECC82, and ECC83 (also known respectively as 12AT7, 12AU7, and 12AX7) are closely related dual triodes widely used in small-signal amplifier stages. Although similar in construction and envelope size, they differ significantly in electrical parameters due to differences in electrode spacing and grid structure. (Data representative of manufacturer specifications.) The ECC83 exhibits high μ {\displaystyle \mu } and high plate resistance, producing large voltage gain but relatively low current drive capability. The ECC82 has lower μ {\displaystyle \mu } and lower plate resistance, allowing greater current delivery and reduced voltage gain. The ECC81 occupies an intermediate position with comparatively high transconductance and moderate amplification factor. These differences arise primarily from variations in grid pitch, cathode area, and electrode spacing, which determine perveance and amplification factor. Although the external envelope is similar, the internal geometry governs the characteristic curves and small-signal parameters. == Tetrode (screen-grid) characterization == The screen-grid tube (tetrode) was developed primarily to reduce the electrostatic coupling between plate and control grid that limited gain and stability in radio-frequency triode amplifiers. In triodes, the grid–plate capacitance provides feedback from plate to grid, restricting obtainable gain and often requiring neutralization circuits such as those used in neutrodyne receivers. By inserting a positively biased screen grid between control grid and plate, this capacitive coupling is greatly reduced, permitting higher stable gain at radio frequencies. The screen grid, also known as the shield grid or grid 2 (to distinguish it from t

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  • Gradient vector flow

    Gradient vector flow

    Gradient vector flow (GVF), a computer vision framework introduced by Chenyang Xu and Jerry L. Prince, is the vector field that is produced by a process that smooths and diffuses an input vector field. It is usually used to create a vector field from images that points to object edges from a distance. It is widely used in image analysis and computer vision applications for object tracking, shape recognition, segmentation, and edge detection. In particular, it is commonly used in conjunction with active contour model. == Background == Finding objects or homogeneous regions in images is a process known as image segmentation. In many applications, the locations of object edges can be estimated using local operators that yield a new image called an edge map. The edge map can then be used to guide a deformable model, sometimes called an active contour or a snake, so that it passes through the edge map in a smooth way, therefore defining the object itself. A common way to encourage a deformable model to move toward the edge map is to take the spatial gradient of the edge map, yielding a vector field. Since the edge map has its highest intensities directly on the edge and drops to zero away from the edge, these gradient vectors provide directions for the active contour to move. When the gradient vectors are zero, the active contour will not move, and this is the correct behavior when the contour rests on the peak of the edge map itself. However, because the edge itself is defined by local operators, these gradient vectors will also be zero far away from the edge and therefore the active contour will not move toward the edge when initialized far away from the edge. Gradient vector flow (GVF) is the process that spatially extends the edge map gradient vectors, yielding a new vector field that contains information about the location of object edges throughout the entire image domain. GVF is defined as a diffusion process operating on the components of the input vector field. It is designed to balance the fidelity of the original vector field, so it is not changed too much, with a regularization that is intended to produce a smooth field on its output. Although GVF was designed originally for the purpose of segmenting objects using active contours attracted to edges, it has been since adapted and used for many alternative purposes. Some newer purposes including defining a continuous medial axis representation, regularizing image anisotropic diffusion algorithms, finding the centers of ribbon-like objects, constructing graphs for optimal surface segmentations, creating a shape prior, and much more. == Theory == The theory of GVF was originally described by Xu and Prince. Let f ( x , y ) {\displaystyle \textstyle f(x,y)} be an edge map defined on the image domain. For uniformity of results, it is important to restrict the edge map intensities to lie between 0 and 1, and by convention f ( x , y ) {\displaystyle \textstyle f(x,y)} takes on larger values (close to 1) on the object edges. The gradient vector flow (GVF) field is given by the vector field v ( x , y ) = [ u ( x , y ) , v ( x , y ) ] {\displaystyle \textstyle \mathbf {v} (x,y)=[u(x,y),v(x,y)]} that minimizes the energy functional In this equation, subscripts denote partial derivatives and the gradient of the edge map is given by the vector field ∇ f = ( f x , f y ) {\displaystyle \textstyle \nabla f=(f_{x},f_{y})} . Figure 1 shows an edge map, the gradient of the (slightly blurred) edge map, and the GVF field generated by minimizing E {\displaystyle \textstyle {\mathcal {E}}} . Equation 1 is a variational formulation that has both a data term and a regularization term. The first term in the integrand is the data term. It encourages the solution v {\displaystyle \textstyle \mathbf {v} } to closely agree with the gradients of the edge map since that will make v − ∇ f {\displaystyle \textstyle \mathbf {v} -\nabla f} small. However, this only needs to happen when the edge map gradients are large since v − ∇ f {\displaystyle \textstyle \mathbf {v} -\nabla f} is multiplied by the square of the length of these gradients. The second term in the integrand is a regularization term. It encourages the spatial variations in the components of the solution to be small by penalizing the sum of all the partial derivatives of v {\displaystyle \textstyle \mathbf {v} } . As is customary in these types of variational formulations, there is a regularization parameter μ > 0 {\displaystyle \textstyle \mu >0} that must be specified by the user in order to trade off the influence of each of the two terms. If μ {\displaystyle \textstyle \mu } is large, for example, then the resulting field will be very smooth and may not agree as well with the underlying edge gradients. Theoretical Solution. Finding v ( x , y ) {\displaystyle \textstyle \mathbf {v} (x,y)} to minimize Equation 1 requires the use of calculus of variations since v ( x , y ) {\displaystyle \textstyle \mathbf {v} (x,y)} is a function, not a variable. Accordingly, the Euler equations, which provide the necessary conditions for v {\displaystyle \textstyle \mathbf {v} } to be a solution can be found by calculus of variations, yielding where ∇ 2 {\displaystyle \textstyle \nabla ^{2}} is the Laplacian operator. It is instructive to examine the form of the equations in (2). Each is a partial differential equation that the components u {\displaystyle u} and v {\displaystyle v} of v {\displaystyle \mathbf {v} } must satisfy. If the magnitude of the edge gradient is small, then the solution of each equation is guided entirely by Laplace's equation, for example ∇ 2 u = 0 {\displaystyle \textstyle \nabla ^{2}u=0} , which will produce a smooth scalar field entirely dependent on its boundary conditions. The boundary conditions are effectively provided by the locations in the image where the magnitude of the edge gradient is large, where the solution is driven to agree more with the edge gradients. Computational Solutions. There are two fundamental ways to compute GVF. First, the energy function E {\displaystyle {\mathcal {E}}} itself (1) can be directly discretized and minimized, for example, by gradient descent. Second, the partial differential equations in (2) can be discretized and solved iteratively. The original GVF paper used an iterative approach, while later papers introduced considerably faster implementations such as an octree-based method, a multi-grid method, and an augmented Lagrangian method. In addition, very fast GPU implementations have been developed in Extensions and Advances. GVF is easily extended to higher dimensions. The energy function is readily written in a vector form as which can be solved by gradient descent or by finding and solving its Euler equation. Figure 2 shows an illustration of a three-dimensional GVF field on the edge map of a simple object (see ). The data and regularization terms in the integrand of the GVF functional can also be modified. A modification described in , called generalized gradient vector flow (GGVF) defines two scalar functions and reformulates the energy as While the choices g ( ∇ f | ) = μ {\displaystyle \textstyle g(\nabla f|)=\mu } and h ( | ∇ f | ) = | ∇ f | 2 {\displaystyle \textstyle h(|\nabla f|)=|\nabla f|^{2}} reduce GGVF to GVF, the alternative choices g ( | ∇ f | ) = exp ⁡ { − | ∇ f | / K } {\displaystyle \textstyle g(|\nabla f|)=\exp\{-|\nabla f|/K\}} and h ( ∇ f | ) = 1 − g ( | ∇ f | ) {\displaystyle \textstyle h(\nabla f|)=1-g(|\nabla f|)} , for K {\displaystyle K} a user-selected constant, can improve the tradeoff between the data term and its regularization in some applications. The GVF formulation has been further extended to vector-valued images in where a weighted structure tensor of a vector-valued image is used. A learning based probabilistic weighted GVF extension was proposed in to further improve the segmentation for images with severely cluttered textures or high levels of noise. The variational formulation of GVF has also been modified in motion GVF (MGVF) to incorporate object motion in an image sequence. Whereas the diffusion of GVF vectors from a conventional edge map acts in an isotropic manner, the formulation of MGVF incorporates the expected object motion between image frames. An alternative to GVF called vector field convolution (VFC) provides many of the advantages of GVF, has superior noise robustness, and can be computed very fast. The VFC field v V F C {\displaystyle \textstyle \mathbf {v} _{\mathrm {VFC} }} is defined as the convolution of the edge map f {\displaystyle f} with a vector field kernel k {\displaystyle \mathbf {k} } where The vector field kernel k {\displaystyle \textstyle \mathbf {k} } has vectors that always point toward the origin but their magnitudes, determined in detail by the function m {\displaystyle m} , decrease to zero with increasing distance from the origin. The beauty of VFC is that it can be computed very rapidly using a fast Fourier tra

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  • Group (online social networking)

    Group (online social networking)

    A group (often termed as a community, e-group or club) is a feature in many social networking services which allows users to create, post, comment to and read from their own interest- and niche-specific forums, often within the realm of virtual communities. Groups, which may allow for open or closed access, invitation and/or joining by other users outside the group, are formed to provide mini-networks within the larger, more diverse social network service. Much like electronic mailing lists, they are also owned and maintained by owners, moderators, or managers, who can edit posts to discussion threads and regulate member behavior within the group. However, unlike traditional Internet forums and mailing lists, groups in social networking services allow owners and moderators alike to share account credentials between groups without having to log in to every group. == History == The rise of the World Wide Web resulted in an expansion of the varieties of methods for communication on the Internet, much of which was limited in the 1980s to discussion in newsgroups, BBS and chat rooms. While the initial rise of web-based mass communication took place in the form of early Internet forums in the mid-1990s, a few services such as MSN Groups, Yahoo! Groups and eGroups pioneered the combination of web-based mailing list archives with user profiles; by 2000, such services doubled as full-fledged mailing lists and Internet forums, allowing users to create an extremely large variety of discussion and networking mediums with comparatively sparse thresholds of complexity. Further features included chat rooms (often Java-based), image and video galleries, and group calendars. The second spurt of bullecalbel networking, one which was less dependent upon mailing list-related features and more upon Internet forum features, began in the early- to mid-2000s in the form of such services as LiveJournal, Friendster, MySpace and Facebook. These services continued the evolution of the web-based e-group as a discussion and organization medium. In the late 2000s, services such as Yammer and Micromobs further advanced e-group communication by taking advantage of microblog-style activity streams. == In virtual worlds == In Second Life, groups are centered less around discussion forums (as such, an asynchronous conferencing feature is not built into the Second Life network as of 2009) and common interest, and are more centered on maintenance of a particular geographic location inside the network. Such groups are often created by the owners of areas such as buildings, plots of land or whole islands in order to cater to the most frequent visitors and patrons of the regions. With the limited asynchronous messaging capability of Second Life, groups are also a means of mass-emailing announcements pertinent to the group, but are not completely capable of hosting discussion or deliberation of such announcement messages. == The importance of online social networking groups == Before people expanded their social life to the internet, they had small circles. These included the networks gained from rural areas or villages, such as family, friends and neighbors, and community groups such as churches. These networks represented a social safety net to support individuals. Since we have moved a huge part of our social life to the internet, online social networking groups have become a way to maintain a structure in social life. Online networking is made up by clusters of people, bounding themselves together on the World Wide Web. To be able to sort out the many different clusters we belong to we use online groups to helps us arrange and make sense of all our contacts. This sense-making is rooted within us, we sort and put people into compartments or sort by categories to make sense and try to understand our relationships to the people around us. Online social networking groups therefore enables us to do the same thing online. Online social networks have a huge impact on people’s lives. Since the social network revolution has offered people with more loose ties and diversity in their relationships, it creates both stress and opportunities. Furthermore, the Internet revolution has transformed the contact point from a household to the individual. In addition, people are in constant communication with each other due to the mobile revolution. All in all, the mentioned revolutions created a new social operating system: "networked individualism". The way that people currently connect, communicate and exchange information can be described as a form of operating system because of the similarities between the structure of computer systems and the networked individualism that has taken form in society. These structures consist of unwritten rules, norms, constraints and opportunities which are apparent for those who are part of a specific network. == Concerns == There is some research claiming that fake news is infiltrating online social networking. A recent study claimed that people exposed to fake news generally revert to their original opinion even after finding out the information they were given was false.

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  • Quality of experience

    Quality of experience

    Quality of experience (QoE) is a measure of the delight or annoyance of a customer's experiences with a service (e.g., web browsing, phone call, TV broadcast). QoE focuses on the entire service experience; it is a holistic concept, similar to the field of user experience, but with its roots in telecommunication. QoE is an emerging multidisciplinary field based on social psychology, cognitive science, economics, and engineering science, focused on understanding overall human quality requirements. == Definition and concepts == In 2013, within the context of the COST Action QUALINET, QoE has been defined as:The degree of delight or annoyance of the user of an application or service. It results from the fulfillment of his or her expectations with respect to the utility and / or enjoyment of the application or service in the light of the user’s personality and current state.This definition has been adopted in 2016 by the International Telecommunication Union in Recommendation ITU-T P.10/G.100. Before, various definitions of QoE had existed in the domain, with the above-mentioned definition now finding wide acceptance in the community. QoE has historically emerged from Quality of Service (QoS), which attempts to objectively measure service parameters (such as packet loss rates or average throughput). QoS measurement is most of the time not related to a customer, but to the media or network itself. QoE however is a purely subjective measure from the user's perspective of the overall quality of the service provided, by capturing people's aesthetic and hedonic needs. QoE looks at a vendor's or purveyor's offering from the standpoint of the customer or end user, and asks, "What mix of goods, services, and support, do you think will provide you with the perception that the total product is providing you with the experience you desired and/or expected?" It then asks, "Is this what the vendor/purveyor has actually provided?" If not, "What changes need to be made to enhance your total experience?" In short, QoE provides an assessment of human expectations, feelings, perceptions, cognition and satisfaction with respect to a particular product, service or application. QoE is a blueprint of all human subjective and objective quality needs and experiences arising from the interaction of a person with technology and with business entities in a particular context. Although QoE is perceived as subjective, it is an important measure that counts for customers of a service. Being able to measure it in a controlled manner helps operators understand what may be wrong with their services and how to improve them. == QoE factors == QoE aims at taking into consideration every factor that contributes to a user's perceived quality of a system or service. This includes system, human and contextual factors. The following so-called "influence factors" have been identified and classified by Reiter et al.: Human Influence Factors Low-level processing (visual and auditory acuity, gender, age, mood, …) Higher-level processing (cognitive processes, socio-cultural and economic background, expectations, needs and goals, other personality traits…) System Influence Factors Content-related Media-related (encoding, resolution, sample rate, …) Network-related (bandwidth, delay, jitter, …) Device-related (screen resolution, display size, …) Context Influence Factors Physical context (location and space) Temporal context (time of day, frequency of use, …) Social context (inter-personal relations during experience) Economic context Task context (multitasking, interruptions, task type) Technical and information context (relationship between systems) Studies in the field of QoE have typically focused on system factors, primarily due to its origin in the QoS and network engineering domains. Through the use of dedicated test laboratories, the context is often sought to be kept constant. == QoE versus User Experience == QoE is strongly related to but different from the field of User Experience (UX), which also focuses on users' experiences with services. Historically, QoE has emerged from telecommunication research, while UX has its roots in Human–Computer Interaction. Both fields can be considered multi-disciplinary. In contrast to UX, the goal of improving QoE for users was more strongly motivated by economic needs. Wechsung and De Moor identify the following key differences between the fields: == QoE measurement == As a measure of the end-to-end performance at the service level from the user's perspective, QoE is an important metric for the design of systems and engineering processes. This is particularly relevant for video services because – due to their high traffic demands –, bad network performance may highly affect the user's experience. So, when designing systems, the expected output, i.e. the expected QoE, is often taken into account – also as a system output metric and optimization goal. To measure this level of QoE, human ratings can be used. The mean opinion score (MOS) is a widely used measure for assessing the quality of media signals. It is a limited form of QoE measurement, relating to a specific media type, in a controlled environment and without explicitly taking into account user expectations. The MOS as an indicator of experienced quality has been used for audio and speech communication, as well as for the assessment of quality of Internet video, television and other multimedia signals, and web browsing. Due to inherent limitations in measuring QoE in a single scalar value, the usefulness of the MOS is often debated. Subjective quality evaluation requires a lot of human resources, establishing it as a time-consuming process. Objective evaluation methods can provide quality results faster, but require dedicated computing resources. Since such instrumental video quality algorithms are often developed based on a limited set of subjective data, their QoE prediction accuracy may be low when compared to human ratings. QoE metrics are often measured at the end devices and can conceptually be seen as the remaining quality after the distortion introduced during the preparation of the content and the delivery through the network, until it reaches the decoder at the end device. There are several elements in the media preparation and delivery chain, and some of them may introduce distortion. This causes degradation of the content, and several elements in this chain can be considered as "QoE-relevant" for the offered services. The causes of degradation are applicable for any multimedia service, that is, not exclusive to video or speech. Typical degradations occur at the encoding system (compression degradation), transport network, access network (e.g., packet loss or packet delay), home network (e.g. WiFi performance) and end device (e.g. decoding performance). == QoE management == Several QoE-centric network management and bandwidth management solutions have been proposed, which aim to improve the QoE delivered to the end-users. When managing a network, QoE fairness may be taken into account in order to keep the users sufficiently satisfied (i.e., high QoE) in a fair manner. From a QoE perspective, network resources and multimedia services should be managed in order to guarantee specific QoE levels instead of classical QoS parameters, which are unable to reflect the actual delivered QoE. A pure QoE-centric management is challenged by the nature of the Internet itself, as the Internet protocols and architecture were not originally designed to support today's complex and high demanding multimedia services. As an example for an implementation of QoE management, network nodes can become QoE-aware by estimating the status of the multimedia service as perceived by the end-users. This information can then be used to improve the delivery of the multimedia service over the network and proactively improve the users' QoE. This can be achieved, for example, via traffic shaping. QoE management gives the service provider and network operator the capability to minimize storage and network resources by allocating only the resources that are sufficient to maintain a specific level of user satisfaction. As it may involve limiting resources for some users or services in order to increase the overall network performance and QoE, the practice of QoE management requires that net neutrality regulations are considered.

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