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Stop Motion Studio is a stop motion animation software developed by Cateater LLC. It is available as both an app for iOS and Android and as a software for Windows and Mac. Two versions of the software exist, the standard Stop Motion Studio for free, and the paid Stop Motion Studio Pro, which contains extra, more advanced features. The software is commonly used in brickfilming.
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Fan loyalty is the loyalty felt and expressed by a fan towards the object of their fanaticism. Fan loyalty is often used in the context of sports and the support of a specific team or institution. Fan loyalties can range from a passive support to radical allegiance and expressions of loyalty can take shape in many forms and be displayed across varying platforms. Fan loyalty can be threatened by team actions. The loyalties of sports fans in particular have been studied by psychologists, who have determined several factors that help to create such loyalties. == Underpinning psychology == Given the extensive costs involved in managing and operating a professional team sport, it is beneficial for sports marketers to be conscious of the elements that establish a strong brand and the effect they have on fan loyalty, so they can best cater to their current fans while acquiring new ones. This is because fans and spectators are considered key stakeholders of professional sports organisations. Fans directly and indirectly influence the production of operating revenue through purchasing merchandise, buying game tickets and improving the value that can be obtained from television broadcasting deals and sponsorship. Therefore, fans are a key factor to consider in determining the economic success of a sports club. Deep psychological connections with new teams can be built with individuals before a team has even played a match revealing insights can develop quickly in the mind of consumers without direct encounters or experiences e.g. watching a team compete. Brand management approaches are helping sport organisations to expand the sport experience, appeal to new fans and enable long term business to consumer relationships through multi faceted connection such as social media. To affect consumers’ loyalty with a team, they must develop a compelling, positive and distinctive brand in order to stand out amongst competitor and vie for fan support. Loyalty programmes positively shape fan attachment and behaviour as it connects teams and their fans, aside from a club's season ticketholder database. It not only provides marketers with essential information about consumers and their thinking, but also acts as a channel to promote attendance and an opportunity to add value to their game day experience. Bauer et al. concludes that non product related attributes such as contextual factors (other fans, the club history and tradition, logo, club colours and the stadium atmosphere) hold a higher place in fan experience than product related attributes such as the team's winning record. Therefore, to increase fan loyalty (customer retention) Bauer et al. suggests sports marketers focus on targeting non product related benefits and brand attributes. As a result of fostering this loyalty, sports organisations can afford to charge prices at premium. Fan loyalty also leads to dependable ratings in broadcast media which means broadcasters can also charge premiums for advertising time in team broadcasts with loyal followings. A flow on effect from fan loyalty is the ability to create additional revenue streams outside of the core product such as merchandise shops and food venues that are close to the location of the game if the team chooses to own and operate ventures or share licensing agreements. Fan loyalty, particularly with respect to team sports, is different from brand loyalty, in as much as if a consumer bought a product that was of lower quality than expected, he or she will usually abandon allegiance to the brand. However, fan loyalty continues even if the team that the fan supports continues to perform poorly year after year. Author Mark Conrad uses the Chicago Cubs as an example of a team with a loyal fan following, where fans spend their money in support of a poorly performing team that (until 2016) had not won a pennant since 1945 or a World Series since 1908. They attribute it to the following factors: Entertainment Value The entertainment value that a fan derives from spectating motivates him/her to remain a loyal fan. Entertainment value of team sports is also valuable to communities in general. Authenticity This is described by Passikoff as "the acceptance of the game as real and meaningful". Fan Bonding Fan bonding is where a fan bonds with the players, identifying with them as individuals, and bonds with the team. Team History and Tradition Shank gives the Cincinnati Reds, all-professional baseball's oldest team, as an example of a team where a long team history and tradition is a motivator for fans in the Cincinnati area. Group Affiliation Fans receive personal validation of their support for a team from being surrounded by a group of fans who also support the same team. Fair Weather Fans Fans that engage when a team is good, and lose interest when a team is bad. Bandwagon Fans Fans who support the winning team, instead of supporting the same team year after year. Diehard Fans Fans who follow their team no matter if they are winning or losing. == Factors influencing fan loyalty == === Community === Fan loyalty attachment is strengthened through communal ties that connect fans around a team, forming a community that results in regular fan interaction. This interaction is particularly important as fans may not develop solely an intra-psychic team identity but predominantly display behavioural loyalty through the group consumption of indirect sport experiences instead, such as wearing the team colours, singing, cheering, flags and interaction between the sport's team's fans (e.g. laughing, talking) Through indirect sport experiences, the stadium atmosphere can be heightened and as a result, the frequency of fan attendance can increase. Furthermore, by wearing team apparel, fans can visually identify with one another resulting an increased likelihood of opportunities to engage with others socially through this point of connection. For example, a study on NASCAR fans found that their personal identity was connected to the brand itself as they felt connected to the larger community of NASCAR revealing an emotional connection to the brand. This indicates that their fan loyalty will result in the notion that fans are naturally more resistant to the promotional efforts of competing brands (e.g. lower-price offers) as their emotional commitment to NASCAR is greatly embedded in their sense of identity. When they associate themselves with the sponsors because of the sponsor's relation to the brand, they are solidifying their relationship with NASCAR and are therefore reinforcing their identity. Consequently, their fan loyalty translates into brand loyalty so long as the sponsor remains attached to the subject of their fanaticism, NASCAR, meaning they are less price sensitive and more willing to pay premium prices for sponsor's products or services. Another aspect of consumer behaviour regarding fan loyalty is the existence of consumption communities where members feel a sense of unity when they participate in the group consumption of brand sponsors’ goods and services further strengthening their ties to a brand and its sponsors. However, a strategy sports marketers use to appeal to a wider range of fan identities is to sponsor more than one club in sports such as soccer. This is so they are careful not to come across as a singularly affiliated club brand, where the opinion or perceptions of opposing teams’ fans would be one of disfavour towards them. === Brand association === Any benefit or characteristic connected to a brand as perceived by a consumer is called a brand association. These hold significance over the thoughts and opinions a consumer holds about a brand and can therefore influence one's loyalty. These associations provide a reference point to gauge the salience of a brand which is the perceived favourability associated with it. Brand salience is vital because it ultimately effects the likelihood of brand selection and loyalty leading to steadier spectator numbers, and an increase in attention from the media such as advertisers and sponsors. However, loyalty is a developmental process. According to Bee & Havitz (2010), spectators who are highly involved in the participation of a sport and exhibit psychological commitment, possess the capability to display high levels of behavioural loyalty as they develop into committed fans. On the other hand, neutral or negative feelings towards a team are found to foster indifference or cause an individual to disidentify with a team altogether. A model of ‘escalating commitment’, put forward by Funk and James (2001), demonstrates an individual's movement from ‘awareness’ of team to a subsequent ‘allegiance’ but came to the conclusion that more research was required to find out the key influences that lead one to the highest state of commitment. However, brand association development is fostered under brand management within a sports organisation. It is important for sports management research to identify t
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UCSD Pascal is a Pascal programming language system that runs on the UCSD p-System, a portable, highly machine-independent operating system. UCSD Pascal was first released in 1977. It was developed at the University of California, San Diego (UCSD). == The p-System == In 1977, the University of California, San Diego (UCSD) Institute for Information Systems developed UCSD Pascal to provide students with a common environment that could run on any of the then available microcomputers as well as campus DEC PDP-11 minicomputers. The operating system became known as UCSD p-System. There were three operating systems that IBM offered for its original IBM PC: the UCSD p-System, CP/M-86, and IBM PC DOS. Vendor SofTech Microsystems emphasized p-System's application portability, with virtual machines for 20 CPUs as of the IBM PC's release. It predicted that users would be able to use applications they purchased on future computers running p-System; advertisements called it "the Universal Operating System". PC Magazine denounced UCSD p-System on the IBM PC, stating in a review of Context MBA, written in the language, that it "simply does not produce good code". The p-System did not sell very well for the IBM PC, because of a lack of applications and because it was more expensive than the other choices. Previously, IBM had offered the UCSD p-System as an option for IBM Displaywriter, an 8086-based dedicated word processing machine. (The Displaywriter's native operating system had been developed completely internally and was not opened for end-user programming.) Notable extensions to standard Pascal include separately compilable Units and a String type. Some intrinsics were provided to accelerate string processing (e.g. scanning in an array for a particular search pattern); other language extensions were provided to allow the UCSD p-System to be self-compiling and self-hosted. UCSD Pascal was based on a p-code machine architecture. Its contribution to these early virtual machines was to extend p-code away from its roots as a compiler intermediate language into a full execution environment. The UCSD Pascal p-Machine was optimized for the new small microcomputers with addressing restricted to 16-bit (only 64 KB of memory). James Gosling cites UCSD Pascal as a key influence (along with the Smalltalk virtual machine) on the design of the Java virtual machine. UCSD p-System achieved machine independence by defining a virtual machine, called the p-Machine (or pseudo-machine, which many users began to call the "Pascal-machine" like the OS—although UCSD documentation always used "pseudo-machine") with its own instruction set called p-code (or pseudo-code). Urs Ammann, a student of Niklaus Wirth, originally presented a p-code in his PhD thesis, from which the UCSD implementation was derived, the Zurich Pascal-P implementation. The UCSD implementation changed the Zurich implementation to be "byte oriented". The UCSD p-code was optimized for execution of the Pascal programming language. Each hardware platform then only needed a p-code interpreter program written for it to port the entire p-System and all the tools to run on it. Later versions also included additional languages that compiled to the p-code base. For example, Apple Computer offered a Fortran Compiler (written by Silicon Valley Software, Sunnyvale California) producing p-code that ran on the Apple version of the p-system. Later, TeleSoft (also located in San Diego) offered an early Ada development environment that used p-code and was therefore able to run on a number of hardware platforms including the Motorola 68000, the System/370, and the Pascal MicroEngine. UCSD p-System shares some concepts with the later Java platform. Both use a virtual machine to hide operating system and hardware differences, and both use programs written to that virtual machine to provide cross-platform support. Likewise both systems allow the virtual machine to be used either as the complete operating system of the target computer or to run in a "box" under another operating system. The UCSD Pascal compiler was distributed as part of a portable operating system, the p-System. == History == UCSD p-System began around 1974 as the idea of UCSD's Kenneth Bowles, who believed that the number of new computing platforms coming out at the time would make it difficult for new programming languages to gain acceptance. He based UCSD Pascal on the Pascal-P2 release of the portable compiler from Zurich. He was particularly interested in Pascal as a language to teach programming. UCSD introduced two features that were important improvements on the original Pascal: variable length strings, and "units" of independently compiled code (an idea included into the then-evolving Ada (programming language)). Niklaus Wirth credits the p-System, and UCSD Pascal in particular, with popularizing Pascal. It was not until the release of Turbo Pascal that UCSD's version started to slip from first place among Pascal users. The Pascal dialect of UCSD Pascal came from the subset of Pascal implemented in Pascal-P2, which was not designed to be a full implementation of the language, but rather "the minimum subset that would self-compile", to fit its function as a bootstrap kit for Pascal compilers. UCSD added strings from BASIC, and several other implementation dependent features. Although UCSD Pascal later obtained many of the other features of the full Pascal language, the Pascal-P2 subset persisted in other dialects, notably Borland Pascal, which copied much of the UCSD dialect. == Versions == There were four versions of UCSD p-code engine, each with several revisions of the p-System and UCSD Pascal. A revision of the p-code engine (i.e., the p-Machine) meant a change to the p-code language, and therefore compiled code is not portable between different p-Machine versions. Each revision was represented with a leading Roman Numeral, while operating system revisions were enumerated as the "dot" number following the p-code Roman Numeral. For example, II.3 represented the third revision of the p-System running on the second revision of the p-Machine. === Version I === Original version, never officially distributed outside of the University of California, San Diego. However, the Pascal sources for both Versions I.3 and I.5 were freely exchanged between interested users. Specifically, the patch revision I.5a was known to be one of the most stable. === Version II === Widely distributed, available on many early microcomputers. Numerous versions included Apple II ultimately Apple Pascal, DEC PDP-11, Intel 8080, Zilog Z80, and MOS 6502 based machines, Motorola 68000 and the IBM PC (Version II on the PC was restricted to one 64K code segment and one 64K stack/heap data segment; Version IV removed the code segment limit but cost a lot more). Project members from this era include Dr Kenneth L Bowles, Mark Allen, Richard Gleaves, Richard Kaufmann, Pete Lawrence, Joel McCormack, Mark Overgaard, Keith Shillington, Roger Sumner, and John Van Zandt. === Version III === Custom version written for Western Digital to run on their Pascal MicroEngine microcomputer. Included support for parallel processes for the first time. === Version IV === Commercial version, developed and sold by SofTech. Based on Version II; did not include changes from Version III. Did not sell well due to combination of their pricing structure, performance problems due to p-code interpreter, and competition with native operating systems (on top of which it often ran). After SofTech dropped the product, it was picked up by Pecan Systems, a relatively small company formed of p-System users and fans. Sales revived somewhat, due mostly to Pecan's reasonable pricing structure, but the p-System and UCSD Pascal gradually lost the market to native operating systems and compilers. Available for the TI-99/4A equipped with p-code card, Commodore CBM 8096, Sage II/IV, HP 9000, and BBC Micro with 6502 second processor. == Further use == The Corvus Systems computer used UCSD Pascal for all its user software. The "innovative concept" of the Constellation OS was to run Pascal (interpretively or compiled) and include all common software in the manual, so users could modify as needed.
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Customizable, Ubiquitous Real Time Communication over the Web is an API definition being drafted by Bernard Aboba at Microsoft. It is a competing standard to WebRTC, which drafted by a World Wide Web Consortium working group since May 2011. As of 2024, CU-RTC-WEB is still in the drafting phase, with ongoing discussions and contributions from various stakeholders in the tech community. Bernard Aboba, who serves as a co-chair of the W3C WebRTC Working Group, is actively involved in both CU-RTC-WEB and WebRTC, indicating a commitment to advancing real-time communication standards across platforms.
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Pixorial was a cloud-based consumer photo sharing, video sharing and video editing platform. The company was formed in 2007 in Centennial, Colorado as a media conversion service. In 2013, Pixorial was chosen as one of two video storage companies to partner with the launch of Google Drive. Pixorial allowed users to edit and share videos on social channels by connecting through their Pixorial account. The company closed on July 18, 2014, and its assets were acquired by LifeLogger Technologies Corp in November 2015. == History == The company was founded in 2007 and launched in 2009 by former Netscape employee Andres Espineira. Changing its focus to video editing software in 2009, Pixorial began developing an app that would be launched for iOS and Android devices in 2011. Later developments in the app in 2012 would also included real time filters, which were later removed. With the launch of Google Drive in 2012, Pixorial was chosen as an integrated video partner. This integration with Google Drive allowed users to access videos stored in Google Drive within the web app of Pixorial. After the Google Drive launch, Pixorial developed a crowdsourced, location-based video sharing app, Krowds. The app was cited in July 2012 by PC Magazine as one of "The 8 Best Apps for Making and Sharing Videos on Your iPhone". In late July, Pixorial replaced its original mobile app with the MyPlayer HD app that optimized HD video viewing for large screen viewing including tablets and smart televisions. Pixorial's services terminated on July 18, 2014. == Products == === Krowds App === Pixorial's app was launched in April 2013 for iOS, and in May for Android, as a tool to aggregate event videos through location based collections. The app was launched to generally positive reviews. === Movie Creator === Launched July 12, 2012 Pixorial's Movie Creator allowed users to edit movies in a simple story-telling platform Movie Creator's features include transitions, text boxes, access to free music tracks, credits, and social media sharing capabilities. The Pixorial platform allowed users to view, share, and edit videos without modifying the original. Movie Creator integrated pictures and video to create user movies. == Awards == 2012 Apex Award from the Colorado Technology Association, for Best Technology Project of the Year 2010 Computerworld Laureate for Media, Arts and Entertainment
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VibeOS is an operating system built from scratch entirely by generative artificial intelligence, using code produced through prompts to Claude (vibe coding). It is capable of running on QEMU and was successfully tested on a Raspberry Pi Zero. It has been released under the MIT license. == Features == === Core === Custom kernel with cooperative multitasking (preemptive backup) FAT32 filesystem with long filename support Memory allocator, process scheduler, interrupt handling GIC-400 (QEMU) and BCM2836/BCM2835 (Pi) interrupt controllers Configurable boot (splash screen, boot target) === GUI === Desktop environment with draggable windows Menu bar, dock, window minimize/maximize/close Mouse and keyboard input Modern macOS-inspired aesthetic === Networking === Full TCP/IP stack (Ethernet, ARP, IP, ICMP, UDP, TCP) DNS resolver HTTP client TLS 1.2 with HTTPS support === Apps === Web browser with HTML/CSS rendering Terminal emulator with readline-style shell Text editor (vim clone) with syntax highlighting File manager with drag-and-drop Music player (MP3/WAV) Calculator, system monitor VibeCode IDE Doom port === Development === TCC (Tiny C Compiler) - compile C programs directly on VibeOS MicroPython interpreter with full kernel API bindings 60+ userspace programs (coreutils, games, GUI apps) === Hardware === Runs on Raspberry Pi Zero 2W USB keyboard and mouse via DWC2 driver SD card via EMMC driver 1920×1080 framebuffer == Further projects == There are other independent projects under the VibeOS name, including an independent development by Ben, also developed using vibe coding, aimed at creating a Unix-like operating system for educational purposes. Another project is Vib-OS, an operating system also built using vibe coding, capable of booting on a Raspberry Pi. It offers a desktop environment with a customizable wallpaper, a file manager, and a web browser currently in an early stage of development, a functional Doom port, among other features that are not very polished given the state of development.
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DiscoVision is the name of several things related to the video LaserDisc format. It was the original name of the "Reflective Optical Videodisc System" format later known as "LaserVision" or LaserDisc. == Description == MCA DiscoVision, Inc. was a division of entertainment giant MCA (Music Corporation of America), established in 1969 to develop and sell an optical videodisc system. MCA released discs pressed in Carson and Costa Mesa, California on the DiscoVision label from the format's Atlanta, Georgia launch in 1978 to 1982 and the release of the film The Four Seasons. DiscoVision titles included films from Universal Pictures, Paramount Pictures, Warner Bros. Pictures, and Disney content. Agreements were made with Columbia Pictures and United Artists, though no discs were released on the DiscoVision label from either studio. Most of these companies later established their own labels for the format, the first being Paramount with a dozen movies released on the Paramount Home Video label in the summer of 1981. The successor to MCA DiscoVision, DiscoVision Associates (DVA), was the result of a partnership between IBM and MCA. It was hoped that the merger would provide the basis for improvement of the quality of DiscoVision pressings, but no appreciable improvement ever took hold. In 1981, responsibility for the laser videodisc was sold to Pioneer Electronic Corporation, after MCA Discovision had previously started a partnership in 1977 with Pioneer, Universal Pioneer, to produce the Pioneer PR-7820 player (the first industrial model of DiscoVision player from 1978), as well as establishing disc pressing plants in Japan. As part of the partnership, Pioneer, in association with MCA, had a disc replication facility in Kofu, Japan that produced discs. Some of the last DiscoVision label discs were manufactured by Pioneer in Japan. In the same year, MCA discontinued their DiscoVision branding, due to the sale of the technology to Pioneer (who then rebranded the format as LaserDisc) and in turn rebranded their laserdisc releases, now fabricated by Pioneer, under the MCA Videodisc banner; this was changed to the "MCA Home Video" name for both its VHS and videodisc releases. Some of DiscoVision's technical staff went on to form MCA Video Games, in an effort to produce video game cartridges. DiscoVision Associates later evolved into a patent holding company which manages and licenses intellectual property related to LaserDisc, Compact Disc, and optical disc technologies, as well as other non-disc related fields. In 1989, Pioneer acquired DiscoVision Associates where it continues to license its technologies independently. As the portfolio of patent expired, the presence of DiscoVision became less visible. However, it established the success of a patent holding company, which other companies are stimulated to generate royalty income from their own patent portfolio.
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Feature detection (also feature testing) is a technique used in web development for handling differences between runtime environments (typically web browsers or user agents), by programmatically testing for clues that the environment may or may not offer certain functionality. This information is then used to make the application adapt in some way to suit the environment: to make use of certain APIs, or tailor for a better user experience. Its proponents claim it is more reliable and future-proof than other techniques like user agent sniffing and browser-specific CSS hacks. == Techniques == A feature test can take many forms. It is essentially any snippet of code which gives some level of confidence that a required feature is indeed supported. However, in contrast to other techniques, feature detection usually focuses on performing actions which directly relate to the feature to be detected, rather than heuristics. === JavaScript === JavaScript feature detection can inspect the DOM and the local JavaScript environment to test whether browser features or APIs are supported. The simplest technique is to check for the existence of a relevant object or property. For example, the Geolocation API (used for accessing the device's knowledge of its geographical location, possibly obtained from a GPS navigation device) exposes a geolocation property on the navigator object in the DOM; the presence of which implies the Geolocation API is supported: if ('geolocation' in navigator) { // Geolocation API is supported } For a higher level of confidence, some feature tests will attempt to invoke the feature then look for clues that it behaved properly. For example, a test for support for cookies might attempt to set a value as a cookie and then verify it can be read back. === CSS === In CSS, the at-rule @supports introduced in 2015 allows to test if a given feature is supported. For instance the following code activates the declarations only if the user agent supports display: flex: == Undetectables == Some browser features are considered undetectable, because no clues are known to give sufficient confidence that a feature is supported. These are often because of limited information available to the JavaScript environment in the browser; generally features must be exposed via the DOM in some way in order to be detectable using JavaScript. When undetectables are encountered, it is common to turn to user agent sniffing as an alternative mechanism, or to employ defensive coding to minimise the impact if the feature turns out not to be supported. The Modernizr project maintains a record of known undetectables on their wiki.
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In machine learning, a neural scaling law is an empirical scaling law that describes how neural network performance changes as key factors are scaled up or down. These factors typically include the number of parameters, training dataset size, and training cost. Some models also exhibit performance gains by scaling inference through increased test-time compute (TTC), extending neural scaling laws beyond training to the deployment phase. == Introduction == In general, a deep learning model can be characterized by four parameters: model size, training dataset size, training cost, and the post-training error rate (e.g., the test set error rate). Each of these variables can be defined as a real number, usually written as N , D , C , L {\displaystyle N,D,C,L} (respectively: parameter count, dataset size, computing cost, and loss). A neural scaling law is a theoretical or empirical statistical law between these parameters. There are also other parameters with other scaling laws. === Size of the model === In most cases, the model's size is simply the number of parameters. However, one complication arises with the use of sparse models, such as mixture-of-expert models. With sparse models, during inference, only a fraction of their parameters are used. In comparison, most other kinds of neural networks, such as transformer models, always use all their parameters during inference. === Size of the training dataset === The size of the training dataset is usually quantified by the number of data points within it. Larger training datasets are typically preferred, as they provide a richer and more diverse source of information from which the model can learn. This can lead to improved generalization performance when the model is applied to new, unseen data. However, increasing the size of the training dataset also increases the computational resources and time required for model training. With the "pretrain, then finetune" method used for most large language models, there are two kinds of training dataset: the pretraining dataset and the finetuning dataset. Their sizes have different effects on model performance. Generally, the finetuning dataset is less than 1% the size of pretraining dataset. In some cases, a small amount of high quality data suffices for finetuning, and more data does not necessarily improve performance. Many scaling laws, due to their inherent diminishing returns nature, value data based on a submodular set function which was shown in a paper on this topic. === Cost of training === Training cost is typically measured in terms of time (how long it takes to train the model) and computational resources (how much processing power and memory are required). It is important to note that the cost of training can be significantly reduced with efficient training algorithms, optimized software libraries, and parallel computing on specialized hardware such as GPUs or TPUs. The cost of training a neural network model is a function of several factors, including model size, training dataset size, the training algorithm complexity, and the computational resources available. In particular, doubling the training dataset size does not necessarily double the cost of training, because one may train the model for several times over the same dataset (each being an "epoch"). === Performance === The performance of a neural network model is evaluated based on its ability to accurately predict the output given some input data. Common metrics for evaluating model performance include: Negative log-likelihood per token (logarithm of perplexity) for language modeling; Accuracy, precision, recall, and F1 score for classification tasks; Mean squared error (MSE) or mean absolute error (MAE) for regression tasks; Elo rating in a competition against other models, such as gameplay or preference by a human judge. Performance can be improved by using more data, larger models, different training algorithms, regularizing the model to prevent overfitting, and early stopping using a validation set. When the performance is a number bounded within the range of [ 0 , 1 ] {\displaystyle [0,1]} , such as accuracy, precision, etc., it often scales as a sigmoid function of cost, as seen in the figures. == Examples == === (Hestness, Narang, et al, 2017) === The 2017 paper is a common reference point for neural scaling laws fitted by statistical analysis on experimental data. Previous works before the 2000s, as cited in the paper, were either theoretical or orders of magnitude smaller in scale. Whereas previous works generally found the scaling exponent to scale like L ∝ D − α {\displaystyle L\propto D^{-\alpha }} , with α ∈ { 0.5 , 1 , 2 } {\displaystyle \alpha \in \{0.5,1,2\}} , the paper found that α ∈ [ 0.07 , 0.35 ] {\displaystyle \alpha \in [0.07,0.35]} . Of the factors they varied, only task can change the exponent α {\displaystyle \alpha } . Changing the architecture optimizers, regularizers, and loss functions, would only change the proportionality factor, not the exponent. For example, for the same task, one architecture might have L = 1000 D − 0.3 {\displaystyle L=1000D^{-0.3}} while another might have L = 500 D − 0.3 {\displaystyle L=500D^{-0.3}} . They also found that for a given architecture, the number of parameters necessary to reach lowest levels of loss, given a fixed dataset size, grows like N ∝ D β {\displaystyle N\propto D^{\beta }} for another exponent β {\displaystyle \beta } . They studied machine translation with LSTM ( α ∼ 0.13 {\displaystyle \alpha \sim 0.13} ), generative language modelling with LSTM ( α ∈ [ 0.06 , 0.09 ] , β ≈ 0.7 {\displaystyle \alpha \in [0.06,0.09],\beta \approx 0.7} ), ImageNet classification with ResNet ( α ∈ [ 0.3 , 0.5 ] , β ≈ 0.6 {\displaystyle \alpha \in [0.3,0.5],\beta \approx 0.6} ), and speech recognition with two hybrid (LSTMs complemented by either CNNs or an attention decoder) architectures ( α ≈ 0.3 {\displaystyle \alpha \approx 0.3} ). === (Henighan, Kaplan, et al, 2020) === A 2020 analysis studied statistical relations between C , N , D , L {\displaystyle C,N,D,L} over a wide range of values and found similar scaling laws, over the range of N ∈ [ 10 3 , 10 9 ] {\displaystyle N\in [10^{3},10^{9}]} , C ∈ [ 10 12 , 10 21 ] {\displaystyle C\in [10^{12},10^{21}]} , and over multiple modalities (text, video, image, text to image, etc.). In particular, the scaling laws it found are (Table 1 of ): For each modality, they fixed one of the two C , N {\displaystyle C,N} , and varying the other one ( D {\displaystyle D} is varied along using D = C / 6 N {\displaystyle D=C/6N} ), the achievable test loss satisfies L = L 0 + ( x 0 x ) α {\displaystyle L=L_{0}+\left({\frac {x_{0}}{x}}\right)^{\alpha }} where x {\displaystyle x} is the varied variable, and L 0 , x 0 , α {\displaystyle L_{0},x_{0},\alpha } are parameters to be found by statistical fitting. The parameter α {\displaystyle \alpha } is the most important one. When N {\displaystyle N} is the varied variable, α {\displaystyle \alpha } ranges from 0.037 {\displaystyle 0.037} to 0.24 {\displaystyle 0.24} depending on the model modality. This corresponds to the α = 0.34 {\displaystyle \alpha =0.34} from the Chinchilla scaling paper. When C {\displaystyle C} is the varied variable, α {\displaystyle \alpha } ranges from 0.048 {\displaystyle 0.048} to 0.19 {\displaystyle 0.19} depending on the model modality. This corresponds to the β = 0.28 {\displaystyle \beta =0.28} from the Chinchilla scaling paper. Given fixed computing budget, optimal model parameter count is consistently around N o p t ( C ) = ( C 5 × 10 − 12 petaFLOP-day ) 0.7 = 9.0 × 10 − 7 C 0.7 {\displaystyle N_{opt}(C)=\left({\frac {C}{5\times 10^{-12}{\text{petaFLOP-day}}}}\right)^{0.7}=9.0\times 10^{-7}C^{0.7}} The parameter 9.0 × 10 − 7 {\displaystyle 9.0\times 10^{-7}} varies by a factor of up to 10 for different modalities. The exponent parameter 0.7 {\displaystyle 0.7} varies from 0.64 {\displaystyle 0.64} to 0.75 {\displaystyle 0.75} for different modalities. This exponent corresponds to the ≈ 0.5 {\displaystyle \approx 0.5} from the Chinchilla scaling paper. It's "strongly suggested" (but not statistically checked) that D o p t ( C ) ∝ N o p t ( C ) 0.4 ∝ C 0.28 {\displaystyle D_{opt}(C)\propto N_{opt}(C)^{0.4}\propto C^{0.28}} . This exponent corresponds to the ≈ 0.5 {\displaystyle \approx 0.5} from the Chinchilla scaling paper. The scaling law of L = L 0 + ( C 0 / C ) 0.048 {\displaystyle L=L_{0}+(C_{0}/C)^{0.048}} was confirmed during the training of GPT-3 (Figure 3.1 ). === Chinchilla scaling (Hoffmann, et al, 2022) === One particular scaling law ("Chinchilla scaling") states that, for a large language model (LLM) autoregressively trained for one epoch, with a cosine learning rate schedule, we have: { C = C 0 N D L = A N α + B D β + L 0 {\displaystyle {\begin{cases}C=C_{0}ND\\L={\frac {A}{N^{\alpha }}}+{\frac {B}{D^{\beta }}}+L_{0}\end{cases}}} where the variables are C {\displaystyle C} is the cost o
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Hardware-based encryption is the use of computer hardware to assist software, or sometimes replace software, in the process of data encryption. Typically, this is implemented as part of the processor's instruction set. For example, the AES encryption algorithm (a modern cipher) can be implemented using the AES instruction set on the ubiquitous x86 architecture. Such instructions also exist on the ARM architecture. However, more unusual systems exist where the cryptography module is separate from the central processor, instead being implemented as a coprocessor, in particular a secure cryptoprocessor or cryptographic accelerator, of which an example is the IBM 4758, or its successor, the IBM 4764. Hardware implementations can be faster and less prone to exploitation than traditional software implementations, and furthermore can be protected against tampering. == History == Prior to the use of computer hardware, cryptography could be performed through various mechanical or electro-mechanical means. An early example is the Scytale used by the Spartans. The Enigma machine was an electro-mechanical system cipher machine notably used by the Germans in World War II. After World War II, purely electronic systems were developed. In 1987 the ABYSS (A Basic Yorktown Security System) project was initiated. The aim of this project was to protect against software piracy. However, the application of computers to cryptography in general dates back to the 1940s and Bletchley Park, where the Colossus computer was used to break the encryption used by German High Command during World War II. The use of computers to encrypt, however, came later. In particular, until the development of the integrated circuit, of which the first was produced in 1960, computers were impractical for encryption, since, in comparison to the portable form factor of the Enigma machine, computers of the era took the space of an entire building. It was only with the development of the microcomputer that computer encryption became feasible, outside of niche applications. The development of the World Wide Web lead to the need for consumers to have access to encryption, as online shopping became prevalent. The key concerns for consumers were security and speed. This led to the eventual inclusion of the key algorithms into processors as a way of both increasing speed and security. == Implementations == === In the instruction set === ==== x86 ==== The X86 architecture, as a CISC (Complex Instruction Set Computer) Architecture, typically implements complex algorithms in hardware. Cryptographic algorithms are no exception. The x86 architecture implements significant components of the AES (Advanced Encryption Standard) algorithm, which can be used by the NSA for Top Secret information. The architecture also includes support for the SHA Hashing Algorithms through the Intel SHA extensions. Whereas AES is a cipher, which is useful for encrypting documents, hashing is used for verification, such as of passwords (see PBKDF2). ==== ARM ==== ARM processors can optionally support Security Extensions. Although ARM is a RISC (Reduced Instruction Set Computer) architecture, there are several optional extensions specified by ARM Holdings. === As a coprocessor === IBM 4758 – The predecessor to the IBM 4764. This includes its own specialised processor, memory and a Random Number Generator. IBM 4764 and IBM 4765, identical except for the connection used. The former uses PCI-X, while the latter uses PCI-e. Both are peripheral devices that plug into the motherboard. === Proliferation === Advanced Micro Devices (AMD) processors are also x86 devices, and have supported the AES instructions since the 2011 Bulldozer processor iteration. Due to the existence of encryption instructions on modern processors provided by both Intel and AMD, the instructions are present on most modern computers. They also exist on many tablets and smartphones due to their implementation in ARM processors. == Advantages == Implementing cryptography in hardware means that part of the processor is dedicated to the task. This can lead to a large increase in speed. In particular, modern processor architectures that support pipelining can often perform other instructions concurrently with the execution of the encryption instruction. Furthermore, hardware can have methods of protecting data from software. Consequently, even if the operating system is compromised, the data may still be secure (see Software Guard Extensions). == Disadvantages == If, however, the hardware implementation is compromised, major issues arise. Malicious software can retrieve the data from the (supposedly) secure hardware – a large class of method used is the timing attack. This is far more problematic to solve than a software bug, even within the operating system. Microsoft regularly deals with security issues through Windows Update. Similarly, regular security updates are released for Mac OS X and Linux, as well as mobile operating systems like iOS, Android, and Windows Phone. However, hardware is a different issue. Sometimes, the issue will be fixable through updates to the processor's microcode (a low level type of software). However, other issues may only be resolvable through replacing the hardware, or a workaround in the operating system which mitigates the performance benefit of the hardware implementation, such as in the Spectre exploit.
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A digital backlot or virtual backlot is a motion-picture set that is neither a genuine location nor a constructed studio; the shooting takes place entirely on a stage with a blank background (often a greenscreen) that will later on project an artificial environment put in during post-production. Digital backlots are mainly used for genres such as science fiction, where building a real set would be too expensive or outright impossible. == Notable films == Among the first films to introduce the technique was Mini Moni the Movie by Shinji Higuchi in 2002, predated by Rest In Peace by Stolpskott Film (2000). Others include: === Released === Rest in Peace (Sweden, 2000) – Shot entirely with green-screen. Some sections fully CGI. Casshern (Japan, 2004) – Shot on celluloid. A few practical set pieces used. Able Edwards (United States, 2004) – Shot digitally on Canon XL1 cameras. Immortal (France, 2004) – Shot on celluloid. Also showed CGI characters interacting with live actors. Sky Captain and the World of Tomorrow (United States, 2004) – Shot digitally on Sony CineAlta cameras. Sin City (United States, 2005) – Shot digitally on CineAlta cameras. Three practical sets used. MirrorMask (United States/United Kingdom, 2005) – Shot on celluloid. 80% of film uses digital backlot. Some practical set pieces used. The Cabinet of Dr. Caligari (United States, 2005) – Shot digitally. 300 (United States, 2007) – Shot on celluloid. Two practical sets used. Speed Racer (United States, 2008) – Directed by the Wachowskis. Three practical sets used. The Spirit (United States, 2008) – Director Frank Miller shot the film with the same techniques he and Robert Rodriguez used on Sin City. Avatar (United States, 2009) – Directed by James Cameron. Two practical sets used. Goemon (Japan, 2009) – The second film from Casshern helmer Kazuaki Kiriya. Alice in Wonderland (United States, 2010) – Directed by Tim Burton. Practical sets used. Sin City: A Dame to Kill For (United States 2014) – Co-directed by Robert Rodriguez and Frank Miller. Sequel to Sin City. === Upcoming === Tribes of October
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A hashtag is a metadata tag operator that is prefaced by the hash symbol, #. On social media, hashtags are used on microblogging and photo-sharing services–especially Twitter and Tumblr–as a form of user-generated tagging that enables cross-referencing of content by topic or theme. For example, a search within Instagram for the hashtag #flowers returns all posts that have been tagged with that term. After the initial hash symbol, a hashtag may include letters, numerals or other punctuation. The use of hashtags was first proposed by American blogger and product consultant Chris Messina in a 2007 tweet. Messina made no attempt to patent the use because he felt that "they were born of the internet, and owned by no one". Hashtags became entrenched in the culture of Twitter and soon emerged across Instagram, Facebook, and YouTube. In June 2014, hashtag was added to the Oxford English Dictionary as "a word or phrase with the symbol # in front of it, used on social media websites and apps so that you can search for all messages with the same subject". == Origin and acceptance == The number sign or hash symbol, #, has long been used in information technology to highlight specific pieces of text. In 1970, the number sign was used to denote immediate address mode in the assembly language of the PDP-11 when placed next to a symbol or a number, and around 1973, '#' was introduced in the C programming language to indicate special keywords that the C preprocessor had to process first. The pound sign was adopted for use within IRC (Internet Relay Chat) networks around 1988 to label groups and topics. Channels or topics that are available across an entire IRC network are prefixed with a hash symbol # (as opposed to those local to a server, which uses an ampersand '&'). The use of the pound sign in IRC inspired Chris Messina to propose a similar system on Twitter to tag topics of interest on the microblogging network. He proposed the usage of hashtags on Twitter: How do you feel about using # (pound) for groups. As in #barcamp [msg]? According to Messina, he suggested use of the hashtag to make it easy for lay users without specialized knowledge of search protocols to find specific relevant content. Therefore, the hashtag "was created organically by Twitter users as a way to categorize messages". The first published use of the term "hash tag" was in a blog post "Hash Tags = Twitter Groupings" by Stowe Boyd, on August 26, 2007, according to lexicographer Ben Zimmer, chair of the American Dialect Society's New Words Committee. Messina's suggestion to use the hashtag was not immediately adopted by Twitter, but the convention gained popular acceptance when hashtags were used in tweets relating to the 2007 San Diego forest fires in Southern California. The hashtag gained international acceptance during the 2009–2010 Iranian election protests; Twitter users used both English- and Persian-language hashtags in communications during the events. Hashtags have since played critical roles in recent social movements such as #jesuischarlie, #BLM, and #MeToo. Beginning July 2, 2009, Twitter began to hyperlink all hashtags in tweets to Twitter search results for the hashtagged word (and for the standard spelling of commonly misspelled words). In 2010, Twitter introduced "Trending Topics" on the Twitter front page, displaying hashtags that are rapidly becoming popular, and the significance of trending hashtags has become so great that the company makes significant efforts to foil attempts to spam the trending list. During the 2010 World Cup, Twitter explicitly encouraged the use of hashtags with the temporary deployment of "hashflags", which replaced hashtags of three-letter country codes with their respective national flags. Other platforms such as YouTube and Gawker Media followed in officially supporting hashtags, and real-time search aggregators such as Google Real-Time Search began supporting hashtags. == Format == A hashtag must begin with a hash (#) character followed by other characters, and is terminated by a space or the end of the line. Some platforms may require the # to be preceded with a space. Most or all platforms that support hashtags permit the inclusion of letters (without diacritics), numerals, and underscores. Other characters may be supported on a platform-by-platform basis. Some characters, such as "&", are generally not supported as they may already serve other search functions. Hashtags are not case sensitive (a search for "#hashtag" will match "#HashTag" as well), but the use of embedded capitals (i.e., CamelCase) increases legibility and improves accessibility. Languages that do not use word dividers handle hashtags differently. In China, microblogs Sina Weibo and Tencent Weibo use a double-hashtag-delimited #HashName# format, since the lack of spacing between Chinese characters necessitates a closing tag. Twitter uses a different syntax for Chinese characters and orthographies with similar spacing conventions: the hashtag contains unspaced characters, separated from preceding and following text by spaces (e.g., '我 #爱 你' instead of '我#爱你') or by zero-width non-joiner characters before and after the hashtagged element, to retain a linguistically natural appearance (displaying as unspaced '我#爱你', but with invisible non-joiners delimiting the hashtag). === Etiquette and regulation === Some communities may limit, officially or unofficially, the number of hashtags permitted on a single post. Misuse of hashtags can lead to account suspensions. Twitter warns that adding hashtags to unrelated tweets, or repeated use of the same hashtag without adding to a conversation can filter an account from search results, or suspend the account. Individual platforms may deactivate certain hashtags either for being too generic to be useful, such as #photography on Instagram, or due to their use to facilitate illegal activities. === Alternate formats === In 2009, StockTwits began using ticker symbols preceded by the dollar sign (e.g., $XRX). In July 2012, Twitter began supporting the tag convention and dubbed it the "cashtag". The convention has extended to national currencies, and Cash App has implemented the cashtag to mark usernames. == Function == Hashtags are particularly useful in unmoderated forums that lack a formal ontological organization. Hashtags help users find content similar interest. Hashtags are neither registered nor controlled by any one user or group of users. They do not contain any set definitions, meaning that a single hashtag can be used for any number of purposes, and that the accepted meaning of a hashtag can change with time. Hashtags intended for discussion of a particular event tend to use an obscure wording to avoid being caught up with generic conversations on similar subjects, such as a cake festival using #cakefestival rather than simply #cake. However, this can also make it difficult for topics to become "trending topics" because people often use different spelling or words to refer to the same topic. For topics to trend, there must be a consensus, whether silent or stated, that the hashtag refers to that specific topic. Hashtags may be used informally to express context around a given message, with no intent to categorize the message for later searching, sharing, or other reasons. Hashtags may thus serve as a reflexive meta-commentary. This can help express contextual cues or offer more depth to the information or message that appears with the hashtag. "My arms are getting darker by the minute. #toomuchfaketan". AnoHashtags can also be used to express personal feelings and emotions. ther function of the hashtag can be used to express personal feelings and emotions. For example, with "It's Monday!! #excited #sarcasm" in which the adjectives are directly indicating the emotions of the speaker. Verbal use of the word hashtag is sometimes used in informal conversations. Use may be humorous, such as "I'm hashtag confused!" By August 2012, use of a hand gesture, sometimes called the "finger hashtag", in which the index and middle finger both hands are extended and arranged perpendicularly to form the hash, was documented. === Co-optation by other industries === Companies, businesses, and advocacy organizations have taken advantage of hashtag-based discussions for promotion of their products, services or campaigns. In the early 2010s, some television broadcasters began to employ hashtags related to programs in digital on-screen graphics, to encourage viewers to participate in a backchannel of discussion via social media prior to, during, or after the program. Television commercials have sometimes contained hashtags for similar purposes. The increased usage of hashtags as brand promotion devices has been compared to the promotion of branded "keywords" by AOL in the late 1990s and early 2000s, as such keywords were also promoted at the end of television commercials and series episodes. Organized real-world events have used hashta
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In databases, and transaction processing (transaction management), snapshot isolation is a guarantee that all reads made in a transaction will see a consistent snapshot of the database (in practice it reads the last committed values that existed at the time it started), and the transaction itself will successfully commit only if no updates it has made conflict with any concurrent updates made since that snapshot. Snapshot isolation has been adopted by several major database management systems, such as InterBase, Firebird, Oracle, MySQL, PostgreSQL, SQL Anywhere, MongoDB and Microsoft SQL Server (2005 and later). The main reason for its adoption is that it allows better performance than serializability, yet still avoids most of the concurrency anomalies that serializability avoids (but not all). In practice snapshot isolation is implemented within multiversion concurrency control (MVCC), where generational values of each data item (versions) are maintained: MVCC is a common way to increase concurrency and performance by generating a new version of a database object each time the object is written, and allowing transactions' read operations of several last relevant versions (of each object). Snapshot isolation has been used to criticize the ANSI SQL-92 standard's definition of isolation levels, as it exhibits none of the "anomalies" that the SQL standard prohibited, yet is not serializable (the anomaly-free isolation level defined by ANSI). In spite of its distinction from serializability, snapshot isolation is sometimes referred to as serializable by Oracle. == Definition == A transaction executing under snapshot isolation appears to operate on a personal snapshot of the database, taken at the start of the transaction. When the transaction concludes, it will successfully commit only if the values updated by the transaction have not been changed externally since the snapshot was taken. Such a write–write conflict will cause the transaction to abort. In a write skew anomaly, two transactions (T1 and T2) concurrently read an overlapping data set (e.g. values V1 and V2), concurrently make disjoint updates (e.g. T1 updates V1, T2 updates V2), and finally concurrently commit, neither having seen the update performed by the other. Were the system serializable, such an anomaly would be impossible, as either T1 or T2 would have to occur "first", and be visible to the other. In contrast, snapshot isolation permits write skew anomalies. As a concrete example, imagine V1 and V2 are two balances held by a single person, Phil. The bank will allow either V1 or V2 to run a deficit, provided the total held in both is never negative (i.e. V1 + V2 ≥ 0). Both balances are currently $100. Phil initiates two transactions concurrently, T1 withdrawing $200 from V1, and T2 withdrawing $200 from V2. If the database guaranteed serializable transactions, the simplest way of coding T1 is to deduct $200 from V1, and then verify that V1 + V2 ≥ 0 still holds, aborting if not. T2 similarly deducts $200 from V2 and then verifies V1 + V2 ≥ 0. Since the transactions must serialize, either T1 happens first, leaving V1 = −$100, V2 = $100, and preventing T2 from succeeding (since V1 + (V2 − $200) is now −$200), or T2 happens first and similarly prevents T1 from committing. If the database is under snapshot isolation(MVCC), however, T1 and T2 operate on private snapshots of the database: each deducts $200 from an account, and then verifies that the new total is zero, using the other account value that held when the snapshot was taken. Since neither update conflicts, both commit successfully, leaving V1 = V2 = −$100, and V1 + V2 = −$200. Some systems built using multiversion concurrency control (MVCC) may support (only) snapshot isolation to allow transactions to proceed without worrying about concurrent operations, and more importantly without needing to re-verify all read operations when the transaction finally commits. This is convenient because MVCC maintains a series of recent history consistent states. The only information that must be stored during the transaction is a list of updates made, which can be scanned for conflicts fairly easily before being committed. However, MVCC systems (such as MarkLogic) will use locks to serialize writes together with MVCC to obtain some of the performance gains and still support the stronger "serializability" level of isolation. == Workarounds == Potential inconsistency problems arising from write skew anomalies can be fixed by adding (otherwise unnecessary) updates to the transactions in order to enforce the serializability property. Materialize the conflict Add a special conflict table, which both transactions update in order to create a direct write–write conflict. Promotion Have one transaction "update" a read-only location (replacing a value with the same value) in order to create a direct write–write conflict (or use an equivalent promotion, e.g. Oracle's SELECT FOR UPDATE). In the example above, we can materialize the conflict by adding a new table which makes the hidden constraint explicit, mapping each person to their total balance. Phil would start off with a total balance of $200, and each transaction would attempt to subtract $200 from this, creating a write–write conflict that would prevent the two from succeeding concurrently. However, this approach violates the normal form. Alternatively, we can promote one of the transaction's reads to a write. For instance, T2 could set V1 = V1, creating an artificial write–write conflict with T1 and, again, preventing the two from succeeding concurrently. This solution may not always be possible. In general, therefore, snapshot isolation puts some of the problem of maintaining non-trivial constraints onto the user, who may not appreciate either the potential pitfalls or the possible solutions. The upside to this transfer is better performance. == Terminology == Snapshot isolation is called "serializable" mode in Oracle and PostgreSQL versions prior to 9.1, which may cause confusion with the "real serializability" mode. There are arguments both for and against this decision; what is clear is that users must be aware of the distinction to avoid possible undesired anomalous behavior in their database system logic. == History == Snapshot isolation arose from work on multiversion concurrency control databases, where multiple versions of the database are maintained concurrently to allow readers to execute without colliding with writers. Such a system allows a natural definition and implementation of such an isolation level. InterBase, later owned by Borland, was acknowledged to provide SI rather than full serializability in version 4, and likely permitted write-skew anomalies since its first release in 1985. Unfortunately, the ANSI SQL-92 standard was written with a lock-based database in mind, and hence is rather vague when applied to MVCC systems. Berenson et al. wrote a paper in 1995 critiquing the SQL standard, and cited snapshot isolation as an example of an isolation level that did not exhibit the standard anomalies described in the ANSI SQL-92 standard, yet still had anomalous behaviour when compared with serializable transactions. In 2008, Cahill et al. showed that write-skew anomalies could be prevented by detecting and aborting "dangerous" triplets of concurrent transactions. This implementation of serializability is well-suited to multiversion concurrency control databases, and has been adopted in PostgreSQL 9.1, where it is known as Serializable Snapshot Isolation (SSI). When used consistently, this eliminates the need for the above workarounds. The downside over snapshot isolation is an increase in aborted transactions. This can perform better or worse than snapshot isolation with the above workarounds, depending on workload.
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Vue.js (commonly referred to as Vue; pronounced "view") is an open-source model–view–viewmodel front end JavaScript framework for building user interfaces and single-page applications. It was created by Evan You and is maintained by him and the rest of the active core team members. == Overview == Vue.js features an incrementally adaptable architecture that focuses on declarative rendering and component composition. The core library is focused on the view layer only. Advanced features required for complex applications such as routing, state management and build tooling are offered via officially maintained supporting libraries and packages. Vue.js allows for extending HTML with HTML attributes called directives. The directives offer functionality to HTML applications, and come as either built-in or user defined directives. == History == Vue was created by Evan You after working for Google using AngularJS in several projects. He later summed up his thought process: "I figured, what if I could just extract the part that I really liked about Angular and build something really lightweight." The first source code commit to the project was dated July 2013, at which time it was originally named "Seed". Vue was first publicly announced the following February, in 2014. Version names are often derived from manga and anime series, with the first letters arranged in alphabetical order. === Versions === When a new major is released i.e. v3.y.z, the last minor i.e. 2.x.y will become a LTS release for 18 months (bug fixes and security patches) and for the following 18 months will be in maintenance mode (security patches only). Vue 3 was officially released in September 2020. According to the State of Vue.js Report 2025, 96% of surveyed developers reported having used Vue 3.x. However, 35% also indicated that they used Vue 2.7.x in the past year, reflecting continued reliance on Vue 2 despite its end of support. The report also noted that more than a quarter of respondents encountered challenges when migrating from Vue 2 to Vue 3. === State management evolution === 2015 - Vuex introduced as official state management solution 2021 - Pinia development begins as Vuex 5 experiment 2022 - Pinia becomes officially recommended for new projects 2023 - Vue team announces Vuex maintenance mode transition According to the State of Vue.js Report 2025, the Vue's core team recommendation is reflected in developer adoption–over 80% of surveyed developers reported using Pinia while Vuex still had 38.4% usage, indicating ongoing reliance on the older library. == Features == === Components === Vue components extend basic HTML elements to encapsulate reusable code. At a high level, components are custom elements to which the Vue's compiler attaches behavior. In Vue, a component is essentially a Vue instance with pre-defined options. The code snippet below contains an example of a Vue component. The component presents a button and prints the number of times the button is clicked: === Templates === Vue uses an HTML-based template syntax that allows binding the rendered DOM to the underlying Vue instance's data. All Vue templates are valid HTML that can be parsed by specification-compliant browsers and HTML parsers. Vue compiles the templates into virtual DOM render functions. A virtual Document Object Model (or "DOM") allows Vue to render components in its memory before updating the browser. Combined with the reactivity system, Vue can calculate the minimal number of components to re-render and apply the minimal amount of DOM manipulations when the app state changes. Vue users can use template syntax or choose to directly write render functions using hyperscript either through function calls or JSX. Render functions allow applications to be built from software components. === Reactivity === Vue features a reactivity system that uses plain JavaScript objects and optimized re-rendering. Each component keeps track of its reactive dependencies during its render, so the system knows precisely when to re-render, and which components to re-render. === Transitions === Vue provides a variety of ways to apply transition effects when items are inserted, updated, or removed from the DOM. This includes tools to: Automatically apply classes for CSS transitions and animations Integrate third-party CSS animation libraries, such as Animate.css Use JavaScript to directly manipulate the DOM during transition hooks Integrate third-party JavaScript animation libraries, such as Velocity.js When an element wrapped in a transition component is inserted or removed, this is what happens: Vue will automatically sniff whether the target element has CSS transitions or animations applied. If it does, CSS transition classes will be added/removed at appropriate timings. If the transition component provided JavaScript hooks, these hooks will be called at appropriate timings. If no CSS transitions/animations are detected and no JavaScript hooks are provided, the DOM operations for insertion and/or removal will be executed immediately on next frame. === Routing === A traditional disadvantage of single-page applications (SPAs) is the inability to share links to the exact "sub" page within a specific web page. Because SPAs serve their users only one URL-based response from the server (it typically serves index.html or index.vue), bookmarking certain screens or sharing links to specific sections is normally difficult if not impossible. To solve this problem, many client-side routers delimit their dynamic URLs with a "hashbang" (#!), e.g. page.com/#!/. However, with HTML5 most modern browsers support routing without hashbangs. Vue provides an interface to change what is displayed on the page based on the current URL path – regardless of how it was changed (whether by emailed link, refresh, or in-page links). Additionally, using a front-end router allows for the intentional transition of the browser path when certain browser events (i.e. clicks) occur on buttons or links. Vue itself doesn't come with front-end hashed routing. But the open-source "vue-router" package provides an API to update the application's URL, supports the back button (navigating history), and email password resets or email verification links with authentication URL parameters. It supports mapping nested routes to nested components and offers fine-grained transition control. With Vue, developers are already composing applications with small building blocks building larger components. With vue-router added to the mix, components must merely be mapped to the routes they belong to, and parent/root routes must indicate where children should render. The code above: Sets a front-end route at websitename.com/user/
A radio code is any code that is commonly used over a telecommunication system such as Morse code, brevity codes and procedure words. == Brevity code == Brevity codes are designed to convey complex information with a few words or codes. Specific brevity codes include: ACP-131 Aeronautical Code signals ARRL Numbered Radiogram Multiservice tactical brevity code Ten-code Phillips Code NOTAM Code === Operating signals === Brevity codes that are specifically designed for use between communications operators and to support communication operations are referred to as "operating signals". These include: Prosigns for Morse code 92 Code, Western Union telegraph brevity codes Q code, initially developed for commercial radiotelegraph communication, later adopted by other radio services, especially amateur radio. Used since circa 1909. QN Signals, published by the ARRL and used by Amateur radio operators to assist in the transmission of ARRL Radiograms in the National Traffic System. R and S brevity codes, published by the British Post Office in 1908 for coastal wireless stations and ships, superseded in 1912 by Q codes X code, used by European military services as a wireless telegraphy code in the 1930s and 1940s Z code, also used in the early days of radiotelegraph communication. == Other == Morse code is commonly used in amateur radio. Morse code abbreviations are a type of brevity code. Procedure words used in radiotelephony procedure, are a type of radio code. Spelling alphabets, including the ICAO spelling alphabet, are commonly used in communication over radios and telephones. == Other meanings == Many car audio systems (car radios) have a so-called 'radio code' number which needs to be entered after a power disconnection. This was introduced as a measure to deter theft of these devices. If the code is entered correctly, the radio is activated for use. Entering the code incorrectly several times in a row will cause a temporary or permanent lockout. Some car radios have another check which operates in conjunction with car electronics. If the VIN or another vehicle ID matches the previously stored one, the radio is activated. If the radio cannot verify the vehicle, it is considered to be moved into another vehicle. The radio will then request for the code number or simply refuse to operate and display an error message such as "CANCHECK" or "SECURE".
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