AI For Psychology Students

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

  • History of machine translation

    History of machine translation

    Machine translation is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one natural language to another. In the 1950s, machine translation became a reality in research, although references to the subject can be found as early as the 17th century. The Georgetown experiment, which involved successful fully automatic translation of more than sixty Russian sentences into English in 1954, was one of the earliest recorded projects. Researchers of the Georgetown experiment asserted their belief that machine translation would be a solved problem within a few years. In the Soviet Union, similar experiments were performed shortly after. Consequently, the success of the experiment ushered in an era of significant funding for machine translation research in the United States. The achieved progress was much slower than expected; in 1966, the ALPAC report found that ten years of research had not fulfilled the expectations of the Georgetown experiment and resulted in dramatically reduced funding. Interest grew in statistical models for machine translation, which became more common and also less expensive in the 1980s as available computational power increased. Although there exists no autonomous system of "fully automatic high quality translation of unrestricted text," there are many programs now available that are capable of providing useful output within strict constraints. Several of these programs are available online, such as Google Translate and the SYSTRAN system that powers AltaVista's BabelFish (which was replaced by Microsoft Bing translator in May 2012). == The beginning == The origins of machine translation can be traced back to the work of Al-Kindi, a 9th-century Arabic cryptographer who developed techniques for systemic language translation, including cryptanalysis, frequency analysis, and probability and statistics, which are used in modern machine translation. The idea of machine translation later appeared in the 17th century. In 1629, René Descartes proposed a universal language, with equivalent ideas in different tongues sharing one symbol. In the mid-1930s the first patents for "translating machines" were applied for by Georges Artsrouni, for an automatic bilingual dictionary using punched tape. Russian Peter Troyanskii submitted a more detailed proposal that included both the bilingual dictionary and a method for dealing with grammatical roles between languages, based on the grammatical system of Esperanto. This system was separated into three stages: stage one consisted of a native-speaking editor in the source language to organize the words into their logical forms and to exercise the syntactic functions; stage two required the machine to "translate" these forms into the target language; and stage three required a native-speaking editor in the target language to normalize this output. Troyanskii's proposal remained unknown until the late 1950s, by which time computers were well-known and utilized. == The early years == The first set of proposals for computer based machine translation was presented in 1949 by Warren Weaver, a researcher at the Rockefeller Foundation, "Translation memorandum". These proposals were based on information theory, successes in code breaking during the Second World War, and theories about the universal principles underlying natural language. A few years after Weaver submitted his proposals, research began in earnest at many universities in the United States. On 7 January 1954 the Georgetown–IBM experiment was held in New York at the head office of IBM. This was the first public demonstration of a machine translation system. The demonstration was widely reported in the newspapers and garnered public interest. The system itself, however, was no more than a "toy" system. It had only 250 words and translated 49 carefully selected Russian sentences into English – mainly in the field of chemistry. Nevertheless, it encouraged the idea that machine translation was imminent and stimulated the financing of the research, not only in the US but worldwide. Early systems used large bilingual dictionaries and hand-coded rules for fixing the word order in the final output which was eventually considered too restrictive in linguistic developments at the time. For example, generative linguistics and transformational grammar were exploited to improve the quality of translations. During this period operational systems were installed. The United States Air Force used a system produced by IBM and Washington University in St. Louis, while the Atomic Energy Commission and Euratom, in Italy, used a system developed at Georgetown University. While the quality of the output was poor it met many of the customers' needs, particularly in terms of speed. At the end of the 1950s, Yehoshua Bar-Hillel was asked by the US government to look into machine translation, to assess the possibility of fully automatic high-quality translation by machines. Bar-Hillel described the problem of semantic ambiguity or double-meaning, as illustrated in the following sentence: Little John was looking for his toy box. Finally he found it. The box was in the pen. The word pen may have two meanings: the first meaning, something used to write in ink with; the second meaning, a container of some kind. To a human, the meaning is obvious, but Bar-Hillel claimed that without a "universal encyclopedia" a machine would never be able to deal with this problem. At the time, this type of semantic ambiguity could only be solved by writing source texts for machine translation in a controlled language that uses a vocabulary in which each word has exactly one meaning. == The 1960s, the ALPAC report and the seventies == Research in the 1960s in both the Soviet Union and the United States concentrated mainly on the Russian–English language pair. The objects of translation were chiefly scientific and technical documents, such as articles from scientific journals. The rough translations produced were sufficient to get a basic understanding of the articles. If an article discussed a subject deemed to be confidential, it was sent to a human translator for a complete translation; if not, it was discarded. A great blow came to machine-translation research in 1966 with the publication of the ALPAC report. The report was commissioned by the US government and delivered by ALPAC, the Automatic Language Processing Advisory Committee, a group of seven scientists convened by the US government in 1964. The US government was concerned that there was a lack of progress being made despite significant expenditure. The report concluded that machine translation was more expensive, less accurate and slower than human translation, and that despite the expenditures, machine translation was not likely to reach the quality of a human translator in the near future. The report recommended, however, that tools be developed to aid translators – automatic dictionaries, for example – and that some research in computational linguistics should continue to be supported. The publication of the report had a profound impact on research into machine translation in the United States, and to a lesser extent the Soviet Union and United Kingdom. Research, at least in the US, was almost completely abandoned for over a decade. In Canada, France and Germany, however, research continued. In the US the main exceptions were the founders of SYSTRAN (Peter Toma) and Logos (Bernard Scott), who established their companies in 1968 and 1970 respectively and served the US Department of Defense. In 1970, the SYSTRAN system was installed for the United States Air Force, and subsequently by the Commission of the European Communities in 1976. The METEO System, developed at the Université de Montréal, was installed in Canada in 1977 to translate weather forecasts from English to French, and was translating close to 80,000 words per day or 30 million words per year until it was replaced by a competitor's system on 30 September 2001. While research in the 1960s concentrated on limited language pairs and input, demand in the 1970s was for low-cost systems that could translate a range of technical and commercial documents. This demand was spurred by the increase of globalisation and the demand for translation in Canada, Europe, and Japan. == The 1980s and early 1990s == By the 1980s, both the diversity and the number of installed systems for machine translation had increased. A number of systems relying on mainframe technology were in use, such as SYSTRAN, Logos, Ariane-G5, and Metal. As a result of the improved availability of microcomputers, there was a market for lower-end machine translation systems. Many companies took advantage of this in Europe, Japan, and the USA. Systems were also brought onto the market in China, Eastern Europe, Korea, and the Soviet Union. During the 1980s there was a lot of activity in MT in Japan especially. With the fifth-generation co

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  • Problematic social media use

    Problematic social media use

    Excessive use of social media can lead to problems including impaired functioning and a reduction in overall wellbeing, for both users and those around them. Such usage is associated with a risk of mental health problems, sleep problems, academic struggles, and daytime fatigue. Psychological or behavioural dependence on social media platforms can result in significant negative functions in peoples daily lives. The risk of problems is also related to the type of platform of social media or online community being used. People of different ages and genders may be affected in different ways by problematic social media use. == Signs and symptoms == Signs of social media addiction or excessive use of social media include many behaviours similar to substance use disorders, including mood modification, salience, tolerance, stress withdrawal symptoms, psychological distress, anxiety and depression, conflict, and relapse, and low self esteem. People with problematic social media habits are at risk of being addicted and may require more time on social media as time passes. Frequent social media use may also be associated with self-reported symptoms of attention deficit hyperactivity disorder. Social anxiety (or fear of missing out) is another potential symptom. Social anxiety is defined as having intense anxiety or fear of being judged, negatively evaluated, or rejected in a social or performance situation. The fear of missing out can contribute to excessive usage due to frequent checking the media constantly throughout the day to check in and see what others are doing instead of doing other activities. Common signs include displacement, or replacing meaningful other activities with social media, and loneliness. == Causes and mechanisms == There are many theories for the mechanism or cause behind a person having problematic social media use. The transition from normal to problematic social media use occurs when a person relies on it to relieve stress, loneliness, depression, or provide continuous rewards. Cognitive-behavioral model – People increase their use of social media when they are in unfamiliar environments or awkward situations; Social skill model – People pull out their phones and use social media when they prefer virtual communication as opposed to face-to-face interactions because they lack self-presentation skills; Socio-cognitive model – This person uses social media because they love the feeling of people liking and commenting on their photos and tagging them in pictures. They are attracted to the positive outcomes they receive on social media. There are parallels to the gambling industry inherent to the design of various social media sites, with "'ludic loops' or repeated cycles of uncertainty, anticipation and feedback" potentially contributing to problematic social media use. Another factor directly facilitating the development of addiction to social media is the implicit attitude toward the IT artifact. Social media use may also stimulate the reward pathway in the brain. There is also a theory that social media addiction fulfills a basic evolutionary drives in the wake of mass urbanization worldwide. The basic psychological needs of "secure, predictable community life that evolved over millions of years" remain unchanged, leading some to find online communities to cope with the new individualized way of life in some modern societies. The "Evolutionary Mismatch" hypothesis holds that modern digital platforms amplify social competition and comparison in ways our ancestors never faced, possibly triggering maladaptive patterns such as anxiety, depression, or compulsive use. Similarly, some scholars compare social media to "junk food": The approach taken to develop social media platforms may contribute to problematic social media use. The ability to scroll and stream content endlessly and how app developers distort time by affecting the 'flow' of content when scrolling, potentially resulting in the Zeigarnik effect (the human brain will continue to pursue an unfinished task until a satisfying closure. Autoplay modes, the personalized nature of the content results in emotional attachment (the user values this above its actual value, which is referred to as the endowment effect), and the exposure effect (repeated exposure to a distinct stimulus by the user can condition the user into an enhanced or improved attitude toward it). The interactive nature of the platforms, including the ability to "like" content has also been linked. Even though social media can satisfy personal communication needs, those who use it at higher rates are shown to have higher levels of psychological distress. == Diagnosis == While there is no official diagnostic term or measurement, problematic social media use is conceptualized as a non-substance-related disorder, resulting in preoccupation and compulsion to engage excessively in social media platforms despite negative consequences. No diagnosis exists for problematic social media use in either the ICD-11 or DSM-5. Excessive use of an activity, like social media, does not directly equate with addiction. There are other factors that could lead to someone's social media addiction including personality traits and pre-existing tendencies. While the extent of social media use and addiction are positively correlated, it is erroneous to employ use (the degree to which one makes use of the site's features, the effort exerted during use sessions, access frequency, etc.) as a proxy for addiction. Indicators of a potential dependence on social media include: Mood swings: a person uses social media to regulate his or her mood, or as a means of escaping real world conflicts. Relevance: social media starts to dominate a person's thoughts at the expense of other activities. Salience: social media becomes the most important part of someone's life. Tolerance: a person increases their time spent on social media to experience previously associated feelings they had while using social media. Withdrawal: when a person can not access social media their sleeping or eating habits change or signs of depression or anxiety can become present. Conflicts in real life: when social media is used excessively, it can affect real-life relationships with family and friends. Relapse: the tendency for previously affected individuals to revert to previous patterns of excessive social media use. There have been several scales developed and validated that help to understand the issues regarding problematic social media use. There is not one single scale that is being used by all researchers. == Treatment == Screen time recommendations for children and families have been developed by the American Academy of Pediatrics. Possible therapeutic interventions published include: Self-help interventions, including application-specific timers; Cognitive behavioural therapy; and Organisational and schooling support. Medications have not been shown to be effective in randomized, controlled trials for the related conditions of Internet addiction disorder or gaming disorder. == Prevention == Prevention approaches include screen time monitoring apps and other tech-based approaches to improve efficiency and decrease screen time and tools to help with addiction to online platform products. Parents' methods for monitoring, regulating, and understanding their children's social media use are referred to as parental mediation. Parental mediation strategies include active, restrictive, and co-using methods. Active mediation involves direct parent-child conversations that are intended to educate children on social media norms and safety, as well as the variety and purposes of online content. Restrictive mediation entails the implementation of rules, expectations, and limitations regarding children's social media use and interactions. Co-use is when parents jointly use social media alongside their children, and is most effective when parents are actively participating (like asking questions, making inquisitive/supportive comments) versus being passive about it. Active mediation is the most common strategy used by parents, though the key to success for any mediation strategy is consistency/reliability. When parents reinforce rules inconsistently, have no mediation strategy, or use highly restrictive strategies for monitoring their children's social media use, there is an observable increase in children's aggressive behaviours. When parents openly express that they are supportive of their child's autonomy and provide clear, consistent rules for media use, problematic usage and aggression decreases. Knowing that consistent, autonomy-supportive mediation has more positive outcomes than inconsistent, controlling mediation, parents can consciously foster more direct, involved, and genuine dialogue with their children. This can help prevent or reduce problematic social media use in children and teenagers. == Outcomes == === Adolescents and teens === Increased social medi

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  • Coupling (electronics)

    Coupling (electronics)

    In electronics, electric power and telecommunication, coupling is the transfer of electrical energy from one circuit to another, or between parts of a circuit. Coupling can be deliberate as part of the function of the circuit, or it may be undesirable, for instance due to coupling to stray fields. For example, energy is transferred from a power source to an electrical load by means of conductive coupling, which may be either resistive or direct coupling. An AC potential may be transferred from one circuit segment to another having a DC potential by use of a capacitor. Electrical energy may be transferred from one circuit segment to another segment with different impedance by use of a transformer; this is known as impedance matching. These are examples of electrostatic and electrodynamic inductive coupling. == Types == Electrical conduction: Direct coupling, also called conductive coupling and galvanic coupling Resistive conduction Atmospheric plasma channel coupling Electromagnetic induction: Electrodynamic induction — commonly called inductive coupling, also magnetic coupling Capacitive coupling Evanescent wave coupling Electromagnetic radiation: Radio waves — Wireless telecommunications. Electromagnetic interference (EMI) — Sometimes called radio frequency interference (RFI), is unwanted coupling. Electromagnetic compatibility (EMC) requires techniques to avoid such unwanted coupling, such as electromagnetic shielding. Microwave power transmission Other kinds of energy coupling: Acoustic coupler

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  • Communications system

    Communications system

    A communications system is a collection of individual telecommunications networks systems, relay stations, tributary stations, and terminal equipment usually capable of interconnection and interoperation to form an integrated whole. Communication systems allow the transfer of information from one place to another or from one device to another through a specified channel or medium. The components of a communications system serve a common purpose, are technically compatible, use common procedures, respond to controls, and operate in union. In the structure of a communication system, the transmitter first converts the data received from the source into a light signal and transmits it through the medium to the destination of the receiver. The receiver connected at the receiving end converts it to digital data, maintaining certain protocols e.g. FTP, ISP assigned protocols etc. Telecommunications is a method of communication (e.g., for sports broadcasting, mass media, journalism, etc.). Communication is the act of conveying intended meanings from one entity or group to another through the use of mutually understood signs and semiotic rules. == Types == === By media === An optical communication system is any form of communications system that uses light as the transmission medium. Equipment consists of a transmitter, which encodes a message into an optical signal, a communication channel, which carries the signal to its destination, and a receiver, which reproduces the message from the received optical signal. Fiber-optic communication systems transmit information from one place to another by sending light through an optical fiber. The light forms a carrier signal that is modulated to carry information. A radio communication system is composed of several communications subsystems that give exterior communications capabilities. A radio communication system comprises a transmitting conductor in which electrical oscillations or currents are produced and which is arranged to cause such currents or oscillations to be propagated through the free space medium from one point to another remote therefrom and a receiving conductor at such distant point adapted to be excited by the oscillations or currents propagated from the transmitter. Power-line communication systems operate by impressing a modulated carrier signal on power wires. Different types of power-line communications use different frequency bands, depending on the signal transmission characteristics of the power wiring used. Since the power wiring system was originally intended for transmission of AC power, the power wire circuits have only a limited ability to carry higher frequencies. The propagation problem is a limiting factor for each type of power line communications. === By technology === A duplex communication system is a system composed of two connected parties or devices which can communicate with one another in both directions. The term duplex is used when describing communication between two parties or devices. Duplex systems are employed in nearly all communications networks, either to allow for a communication "two-way street" between two connected parties or to provide a "reverse path" for the monitoring and remote adjustment of equipment in the field. An antenna is basically a small length of a conductor that is used to radiate or receive electromagnetic waves. It acts as a conversion device. At the transmitting end it converts high frequency current into electromagnetic waves. At the receiving end it transforms electromagnetic waves into electrical signals that is fed into the input of the receiver. several types of antenna are used in communication. Examples of communications subsystems include the Defense Communications System (DCS). === Examples: by technology === Telephone Mobile phone Tablet computer Television Telegraph Edison Telegraph TV cable Computer === By application area === The term transmission system is used in the telecommunications industry to emphasize the intermediate media, protocols, and equipment in the circuit, rather than particular end-user applications. A tactical communications system is a communications system that (a) is used within, or in direct support of tactical forces (b) is designed to meet the requirements of changing tactical situations and varying environmental conditions, (c) provides securable communications, such as voice, data, and video, among mobile users to facilitate command and control within, and in support of, tactical forces, and (d) usually requires extremely short installation times, usually on the order of hours, in order to meet the requirements of frequent relocation. An Emergency communication system is any system (typically computer based) that is organized for the primary purpose of supporting the two way communication of emergency messages between both individuals and groups of individuals. These systems are commonly designed to integrate the cross-communication of messages between are variety of communication technologies. An Automatic call distributor (ACD) is a communication system that automatically queues, assigns and connects callers to handlers. This is used often in customer service (such as for product or service complaints), ordering by telephone (such as in a ticket office), or coordination services (such as in air traffic control). A Voice Communication Control System (VCCS) is essentially an ACD with characteristics that make it more adapted to use in critical situations (no waiting for dial tone, or lengthy recorded announcements, radio and telephone lines equally easily connected to, individual lines immediately accessible etc..) == Key components == =

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  • Neuro-symbolic AI

    Neuro-symbolic AI

    Neuro-symbolic AI is a subfield of artificial intelligence that integrates neural methods (e.g., neural networks and deep learning) with symbolic methods (e.g., formal logic, knowledge representation, and automated reasoning). The goal is to combine the strengths of both approaches, resulting in AI systems that can be trained from raw data and demonstrate robustness against outliers or errors in the base data, while preserving explainability, explicit use of expert knowledge, and explicit cognitive reasoning. As argued by Leslie Valiant and others, the effective construction of rich computational cognitive models demands the combination of symbolic reasoning and efficient machine learning. Gary Marcus argued, "We cannot construct rich cognitive models in an adequate, automated way without the triumvirate of hybrid architecture, rich prior knowledge, and sophisticated techniques for reasoning." Further, "To build a robust, knowledge-driven approach to AI we must have the machinery of symbol manipulation in our toolkit. Too much of useful knowledge is abstract to make do without tools that represent and manipulate abstraction, and to date, the only known machinery that can manipulate such abstract knowledge reliably is the apparatus of symbol manipulation." Angelo Dalli, Henry Kautz, Francesca Rossi, and Bart Selman also argued for such a synthesis. Their arguments attempt to address the two kinds of thinking, as discussed in Daniel Kahneman's book Thinking, Fast and Slow. It describes cognition as encompassing two components: System 1 is fast, reflexive, intuitive, and unconscious. System 2 is slower, step-by-step, and explicit. System 1 is used for pattern recognition. System 2 handles planning, deduction, and deliberative thinking. In this view, deep learning best handles the first kind of cognition, while symbolic reasoning best handles the second kind. Both are necessary for the development of a robust and reliable AI system capable of learning, reasoning, and interacting with humans to accept advice and answer questions. Since the 1990s, dual-process models with explicit references to the two contrasting systems have been the focus of research in both the fields of AI and cognitive science by numerous researchers. In 2025, the adoption of neurosymbolic AI, an approach that integrates neural networks with symbolic reasoning, increased in response to the need to address hallucination issues in large language models. For example, Amazon implemented Neurosymbolic AI in its Vulcan warehouse robots and Rufus shopping assistant to enhance accuracy and decision-making. == Approaches == Approaches for integration are diverse. Henry Kautz's taxonomy of neuro-symbolic architectures follows, along with some examples: Symbolic Neural symbolic is the current approach of many neural models in natural language processing, where words or subword tokens are the ultimate input and output of large language models. Examples include BERT, RoBERTa, and GPT-3. Symbolic[Neural] is exemplified by AlphaGo, where symbolic techniques are used to invoke neural techniques. In this case, the symbolic approach is Monte Carlo tree search and the neural techniques learn how to evaluate game positions. Neural | Symbolic uses a neural architecture to interpret perceptual data as symbols and relationships that are reasoned about symbolically. Neural-Concept Learner is an example. Neural: Symbolic → Neural relies on symbolic reasoning to generate or label training data that is subsequently learned by a deep learning model, e.g., to train a neural model for symbolic computation by using a Macsyma-like symbolic mathematics system to create or label examples. NeuralSymbolic uses a neural net that is generated from symbolic rules. An example is the Neural Theorem Prover, which constructs a neural network from an AND-OR proof tree generated from knowledge base rules and terms. Logic Tensor Networks also fall into this category. Neural[Symbolic] according to Kautz, this approach embeds true symbolic reasoning inside a neural network. These are tightly-coupled neural-symbolic systems, in which the logical inference rules are internal to the neural network. This way, the neural network internally computes the inference from the premises and learns to reason based on logical inference systems. Early work on connectionist modal and temporal logics by Garcez, Lamb, and Gabbay is aligned with this approach. These categories are not exhaustive, as they do not consider multi-agent systems. In 2005, Bader and Hitzler presented a more fine-grained categorization that took into account, e.g., whether the use of symbols included logic and, if so, whether the logic was propositional or first-order logic. The 2005 categorization and Kautz's taxonomy above are compared and contrasted in a 2021 article. Sepp Hochreiter argued that Graph Neural Networks "...are the predominant models of neural-symbolic computing" since "[t]hey describe the properties of molecules, simulate social networks, or predict future states in physical and engineering applications with particle-particle interactions." == Artificial general intelligence == Gary Marcus argues that "...hybrid architectures that combine learning and symbol manipulation are necessary for robust intelligence, but not sufficient", and that there are ...four cognitive prerequisites for building robust artificial intelligence: hybrid architectures that combine large-scale learning with the representational and computational powers of symbol manipulation, large-scale knowledge bases—likely leveraging innate frameworks—that incorporate symbolic knowledge along with other forms of knowledge, reasoning mechanisms capable of leveraging those knowledge bases in tractable ways, and rich cognitive models that work together with those mechanisms and knowledge bases. This echoes earlier calls for hybrid models as early as the 1990s. == History == Garcez and Lamb described research in this area as ongoing, at least since the 1990s. During that period, the terms symbolic and sub-symbolic AI were popular. A series of workshops on neuro-symbolic AI has been held annually since 2005 Neuro-Symbolic Artificial Intelligence. In the early 1990s, an initial set of workshops on this topic were organized. == Research == Key research questions remain, such as: What is the best way to integrate neural and symbolic architectures? How should symbolic structures be represented within neural networks and extracted from them? How should common-sense knowledge be learned and reasoned about? How can abstract knowledge that is hard to encode logically be handled? == Implementations == Implementations of neuro-symbolic approaches include: AllegroGraph: an integrated Knowledge Graph based platform for neuro-symbolic application development. Scallop: a language based on Datalog that supports differentiable logical and relational reasoning. Scallop can be integrated in Python and with a PyTorch learning module. Logic Tensor Networks: encode logical formulas as neural networks and simultaneously learn term encodings, term weights, and formula weights. DeepProbLog: combines neural networks with the probabilistic reasoning of ProbLog. Abductive Learning: integrates machine learning and logical reasoning in a balanced-loop via abductive reasoning, enabling them to work together in a mutually beneficial way. SymbolicAI: a compositional differentiable programming library.

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  • Hardware compatibility list

    Hardware compatibility list

    A hardware compatibility list (HCL) is a list of computer hardware (typically including many types of peripheral devices) that is compatible with a particular operating system or device management software. The list contains both whole computer systems and specific hardware elements including motherboards, sound cards, and video cards. In today's world, there is a vast amount of computer hardware in circulation, and many operating systems too. A hardware compatibility list is a database of hardware models and their compatibility with a certain operating system. HCLs can be centrally controlled (one person or team keeps the list of hardware maintained) or user-driven (users submit reviews on hardware they have used). There are many HCLs. Usually, each operating system will have an official HCL on its website.

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  • Digital heritage

    Digital heritage

    The Charter on the Preservation of Digital Heritage of UNESCO defines digital heritage as embracing "cultural, educational, scientific and administrative resources, as well as technical, legal, medical and other kinds of information created digitally, or converted into digital form from existing analogue resources". Digital heritage also includes the use of digital media in the service of understanding and preserving cultural or natural heritage. The digitization of both cultural heritage and Natural heritage serves to enable the permanent access of current and future generations to culturally important objects ranging from literature and paintings to flora, fauna, or habitats. It is also used in the preservation and access of objects with enduring or significant historical, scientific, or cultural value including buildings, archeological sites, and natural phenomena. The main idea is the transformation of a material object into a virtual copy. It should not be confused with digital humanities, which uses digitizing technology to specifically help with research. There have been several debates concerning the efficiency of the process of digitizing heritage. Some of the drawbacks refer to the deterioration and technological obsolescence due to the lack of funding for archival materials and underdeveloped policies that would regulate such a process. Another main social debate has taken place around the restricted accessibility due to the digital divide that exists around the world. Nevertheless, new technologies enable easy, instant and cross boarder access to the digitized work. Many of these technologies include spatial and surveying technology to gain aerial or 3D images. Digital heritage is also used to monitor cultural heritage sites over years to help with preservation, maintenance, and sustainable tourism. It aims to observe any changes, diseases, or deterioration that may occur on objects. == Cultural and natural heritage == Digital Heritage that is not born-digital can be divided into two separate groups—digital cultural heritage and digital natural heritage. Digital cultural heritage is the maintenance or preservation of cultural objects through digitization. These are objects, in some cases entire cities, that are considered of cultural importance. These objects are sometimes able to be digitized or physically represented in minute detail. Digital cultural heritage also includes intangible heritage. These are things such as "oral traditions, customs, value systems, skills, traditional dances, diets, performances" and other unique features of a culture. Intangible heritage is particularly vulnerable to destruction due to urbanization. There are several projects and programs which concentrate on digital cultural heritage. One such project is Mapping Gothic France, which aims to document and preserve cathedrals across France using images, VR tours, laser scans, and panoramas. This allows for scientific and historical study and preservation of the cathedrals and also provides detailed access to the sites for anyone in the world. The aim of projects like these is to help with the preservation and restoration of cultural objects. After the fire at Notre-Dame de Paris in 2019, digital scans are a major component in the ongoing restoration. Digital natural heritage pertains to objects of natural heritage that are considered of cultural, scientific, or aesthetic importance. Digital heritage in this instance is used not only to grant access to these objects, but to monitor any changes over time, such as with plant or animal habitats. Geographic information systems are a form of technology that is used primarily in the study of natural heritage. Western Australia has one such digital heritage project where they have created a digital repository of native plants important to both the region and the Aboriginal people. This is in order to protect and preserve the important biological heritage of Western Australia. == Educational impact == The digitization of these heritage objects has impacts around the world and across many disciplines. The increase of digital items means that people, especially the youth, are able to learn about new objects and cultures online through various media. They provide viewers with a more in-depth experience with an item or place, instead of just an image. The media is also able to be curated to age- or educational-level appropriateness, making learning easier. Some of the technology used in education, especially in museums, includes mobile apps, virtual reality, social media, and video games. Cultural heritage institutions are using this technology to try to expand access, increase appreciation for these items, and to gain new viewpoints on their collections. Digital heritage also helps scientists, archeologists, or other historians and specialists collect data on these objects, providing more information on the objects and the past. Digital Heritage is still currently being studied and improved by several sectors invested in cultural and intellectual preservation. It is particularly of interest to museums, governments, and academic institutions. Research by these groups are creating new concepts, methodologies, and techniques for the implementation of digital heritage to protect this type of cultural and natural heritage. As new technologies are created, museums and other heritage institutions are provided with more ways of disseminating their information and engaging with the public. A lack of resources within certain groups may still hinder everyone from accessing digital heritage. == Technologies used == The digitization of cultural heritage is attained through several means. Some of the main technology used is spatial and surveying technology. Space archaeological technology - Observations from space satellites are non-intrusive and can be integrated with other technologies on the ground. It is used to photograph vast areas of earth and help with research. Remnants of ancient civilizations or other human objects are also able to be spotted via satellite imaging. Unmanned aerial vehicles - UAV, such as drones, are commonly used in digitization of cultural heritage objects. The Great Wall of China is one such site that has been digitized and analyzed through unmanned aerial vehicle investigation. The resulting images, 3-D scans, maps, and other data are used to evaluate and maintain the Great Wall. Laser Scanning - Laser scanning is used to scan an area and recreate spatially accurate depictions, such as a 3D model. Virtual and Augmented Reality - VR is used primarily for education but does have uses for reconstruction and research. It is used to provide users with an immersive experience, as though they are actually at the site. Geographic Information systems - GIS are used primarily to study objects and sites over time. It is also important in studying the socioeconomic status of the past. 3D Modeling - 3D modeling has become more widely used due to an increase in technology that works specifically with heritage sites. It is often used in tandem with GIS to reconstruct objects for restoration, documentation, preservation, and educational purposes. Data is collected using satellite or other aerial imaging and ground-based imaging. There is some concern about the accuracy and authenticity of these types of digital reconstructions and their effects on the sites themselves. A major barrier to digital heritage is the amount of resources it takes to undertake such projects, such as money, time, and technology. Money and the lack of qualified personnel are two that are considered the most obstructive. This is especially an issue in less developed areas or within underfunded groups such as minorities. == Virtual heritage == A particular branch of digital heritage, known as "virtual heritage", is formed by the use of information technology with the aim of recreating the experience of existing cultural heritage, as in (approximations of) virtual reality. It is hard to differentiate this branch from the core contribution of digital heritage which is storing the heritage data digitally. Parsinejad et al. developed two techniques for Digital Twinning of the architectural assets and representation of the physical assets virtually in the museum context. Two techniques are hand recording and digital recording and both have challenges in adoption and implementation of Digital Twin as a revolutionary concept. == Digital heritage stewardship == Digital heritage stewardship is a form of digital curation which is modeled after collaborative curation. Digital heritage stewardship means stepping away from typical curatorial practices (e.g. discovering, arranging, and sharing information, material, and/or content) in favor of practices which allow its stakeholders the opportunity to contribute historical, political, and social context and culture. The collaborative practice encourages the creation, engagement, and maintena

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  • IDN Times

    IDN Times

    IDN Times is a digital multi-platform media outlet that provides news and entertainment for Millennials and Gen Z in Indonesia. IDN Times is one of IDN’s business units under the Digital Media pillar, founded by Winston Utomo and William Utomo on June 8, 2014. Currently, senior journalist Uni Zulfiani Lubis serves as the Editor-in-Chief of IDN Times. == History == IDN Times was initially known as Indonesian Times, a blog featuring articles written by Winston Utomo while he was working at Google Singapore. As interest and readership grew, Indonesian Times evolved into IDN Times, a digital multi-platform media company focused on delivering relevant content for Indonesia’s younger generations. == Bureau == IDN Times has a representative bureau that has spread over 12 provinces in Indonesia: == Events == === Indonesia Millennial and Gen Z Summit === The Indonesia Millennial and Gen-Z Summit (IMGS) is an annual event organized by IDN. This event aims to empower Indonesia’s younger generations through discussions and interdisciplinary collaborations. IMGS features inspirational figures, professionals, and leaders from various fields who share insights and drive positive change. The event hosts dozens of discussion sessions in collaboration with eight prominent communities. Topics covered include politics, economics, technology, and pop culture. === Indonesia Writers Festival === The Indonesia Writers Festival is an independent writing festival organized by IDN Times. The event seeks to empower Indonesians through writing by inviting experts and literacy activists from various backgrounds. == Duniaku.com == Duniaku.com is a multi-platform digital media part of IDN Times which presents content about geek culture ranging from video games, anime, comics, films, technology and gadgets. Duniaku.com was officially launched on September 6, 2019 by the Minister of Communication and Informatics Rudiantara together with CEO of IDN Media Winston Utomo and IDN Times and Editor-in-Chief of Duniaku.com Uni Lubis. == Awards == 2019 IDN won WAN-IFRA Asia Digital Media Awards 2019 as the Best Digital Project to Engage Younger and/or Millennial Audiences for IDN Times’ #MillennialsMemilih program 2020 IDN Times (IDN Times Community) won WAN-IFRA Asia Digital Media Awards 2019 in The Best in Audience Engagement category. 2021 IDN Times journalists won awards at the Subroto Award, Ministry of Energy and Mineral Resources (ESDM) on 28 September 2021. 2024 IDN Times won WAN-IFRA event at both the Asia and Global levels in Best Use of AI in Revenue Strategy. === #Interconnected22 by Pulitzer Center === One of the IDN Times journalists, Dhana Kencana, was the speaker at the #Interconnected22 conference held from June 9 to June 10, 2022, in Washington DC, United States of America. Dhana Kencana is also a grant recipient Pulitzer Center through the Rainforest Journalism Fund (RJF) program, a funding program for journalists that makes a number of coverage of the rainforest.

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  • System requirements specification

    System requirements specification

    A System Requirements Specification (SysRS) (abbreviated SysRS to be distinct from a software requirements specification (SRS)) is a structured collection of information that embodies the requirements of a system. A business analyst (BA), sometimes titled system analyst, is responsible for analyzing the business needs of their clients and stakeholders to help identify business problems and propose solutions. Within the systems development life cycle domain, the BA typically performs a liaison function between the business side of an enterprise and the information technology department or external service providers.

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  • Robert Abel and Associates

    Robert Abel and Associates

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

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  • Flat-panel display

    Flat-panel display

    A flat-panel display (FPD) is an electronic display used to display visual content such as text or images. It is present in consumer, medical, transportation, and industrial equipment. Flat-panel displays are thin, lightweight, provide better linearity and are capable of higher resolution and contrast than typical consumer-grade TVs from earlier eras. They are usually less than 10 centimetres (3.9 in) thick. While the highest resolution for consumer-grade CRT televisions is 1080i, many interactive flat panels in the 2020s are capable of 1080p and 4K resolution. In the 2010s, portable consumer electronics such as laptops, mobile phones, and portable cameras have used flat-panel displays since they consume less power and are lightweight. As of 2016, flat-panel displays have almost completely replaced CRT displays. Most 2010s-era flat-panel displays use LCD or light-emitting diode (LED) technologies, sometimes combined. Most LCD screens are back-lit with color filters used to display colors. In many cases, flat-panel displays are combined with touch screen technology, which allows the user to interact with the display in a natural manner. For example, modern smartphone displays often use OLED panels, with capacitive touch screens. Flat-panel displays can be divided into two display device categories: volatile and static. The former requires that pixels be periodically electronically refreshed to retain their state (e.g. liquid-crystal displays (LCD)), and can only show an image when it has power. On the other hand, static flat-panel displays rely on materials whose color states are bistable, such as displays that make use of e-ink technology, and as such retain content even when power is removed. == History == The first engineering proposal for a flat-panel TV was by General Electric in 1954 as a result of its work on radar monitors. The publication of their findings gave all the basics of future flat-panel TVs and monitors. But GE did not continue with the R&D required and never built a working flat panel at that time. The first production flat-panel display was the Aiken tube, developed in the early 1950s and produced in limited numbers in 1958. This saw some use in military systems as a heads up display and as an oscilloscope monitor, but conventional technologies overtook its development. Attempts to commercialize the system for home television use ran into continued problems and the system was never released commercially. Dennis Gabor, better known as the inventor of holography, patented a flat-screen CRT in 1958. This was substantially similar to Aiken's concept, and led to a years-long patent battle. By the time the lawsuits were complete, with Aiken's patent applying in the US and Gabor's in the UK, the commercial aspects had long lapsed, and the two became friends. Around this time, Clive Sinclair came across Gabor's work and began an ultimately unsuccessful decade-long effort to commercialize it. The Philco Predicta featured a relatively flat (for its day) cathode-ray tube setup and would be the first commercially released "flat panel" upon its launch in 1958; the Predicta was a commercial failure. The plasma display panel was invented in 1964 at the University of Illinois, according to The History of Plasma Display Panels. === Liquid-crystal displays (LC displays, or LCDs) === The MOSFET (metal–oxide–semiconductor field-effect transistor, or MOS transistor) was invented by Mohamed M. Atalla and Dawon Kahng at Bell Labs in 1959, and presented in 1960. Building on their work, Paul K. Weimer at RCA developed the thin-film transistor (TFT) in 1962. It was a type of MOSFET distinct from the standard bulk MOSFET. The idea of a TFT-based LCD was conceived by Bernard J. Lechner of RCA Laboratories in 1968. B.J. Lechner, F.J. Marlowe, E.O. Nester and J. Tults demonstrated the concept in 1968 with a dynamic scattering LCD that used standard discrete MOSFETs. The first active-matrix addressed electroluminescent display was made using TFTs by T. Peter Brody's Thin-Film Devices department at Westinghouse Electric Corporation in 1968. In 1973, Brody, J. A. Asars and G. D. Dixon at Westinghouse Research Laboratories demonstrated the first thin-film-transistor liquid-crystal display. Brody and Fang-Chen Luo demonstrated the first flat active-matrix liquid-crystal display (AM LCD) using TFTs in 1974. By 1982, pocket LCD TVs based on LCD technology were developed in Japan. The 2.1-inch Epson ET-10 Epson Elf was the first color LCD pocket TV, released in 1984. In 1988, a Sharp research team led by engineer T. Nagayasu demonstrated a 14-inch full-color LCD, which convinced the electronics industry that LCD would eventually replace CRTs as the standard television display technology. As of 2013, all modern high-resolution and high-quality electronic visual display devices use TFT-based active-matrix displays. === LED displays === The first usable LED display was developed by Hewlett-Packard (HP) and introduced in 1968. It was the result of research and development (R&D) on practical LED technology between 1962 and 1968, by a research team under Howard C. Borden, Gerald P. Pighini, and Mohamed M. Atalla, at HP Associates and HP Labs. In February 1969, they introduced the HP Model 5082-7000 Numeric Indicator. It was the first alphanumeric LED display, and was a revolution in digital display technology, replacing the Nixie tube for numeric displays and becoming the basis for later LED displays. In 1977, James P Mitchell prototyped and later demonstrated what was perhaps the earliest monochromatic flat-panel LED television display. Ching W. Tang and Steven Van Slyke at Eastman Kodak built the first practical organic LED (OLED) device in 1987. In 2003, Hynix produced an organic EL driver capable of lighting in 4,096 colors. In 2004, the Sony Qualia 005 was the first LED-backlit LCD. The Sony XEL-1, released in 2007, was the first OLED television. == Common types == === Liquid-crystal display (LCD) === Field-effect LCDs are lightweight, compact, portable, cheap, more reliable, and easier on the eyes than CRT screens. LCD screens use a thin layer of liquid crystal, a liquid that exhibits crystalline properties. It is sandwiched between two glass plates carrying transparent electrodes. Two polarizing films are placed at each side of the LCD. By generating a controlled electric field between electrodes, various segments or pixels of the liquid crystal can be activated, causing changes in their polarizing properties. These polarizing properties depend on the alignment of the liquid-crystal layer and the specific field-effect used, being either twisted nematic (TN), in-plane switching (IPS) or vertical alignment (VA). Color is produced by applying appropriate color filters (red, green and blue) to the individual subpixels. LC displays are used in various electronics like watches, calculators, mobile phones, TVs, computer monitors and laptops screens etc. === LED-LCD === Most earlier large LCD screens were back-lit using a number of CCFL (cold-cathode fluorescent lamps). However, small pocket size devices almost always used LEDs as their illumination source. With the improvement of LEDs, almost all new displays are now equipped with LED backlight technology. The image is still generated by the LCD layer. === Plasma panel === A plasma display consists of two glass plates separated by a thin gap filled with a gas such as neon. Each of these plates has several parallel electrodes running across it. The electrodes on the two plates are at right angles to each other. A voltage applied between the two electrodes one on each plate causes a small segment of gas at the two electrodes to glow. The glow of gas segments is maintained by a lower voltage that is continuously applied to all electrodes. By 2010, consumer plasma displays had been discontinued by numerous manufacturers. === Electroluminescent panel === In an electroluminescent display, the image is created by applying electrical signals to the plates which make the phosphor glow. === Organic light-emitting diode === An OLED (organic light-emitting diode) is a light-emitting diode (LED) in which the emissive electroluminescent layer is a film of organic compound which emits light in response to an electric current. This layer of organic semiconductor is situated between two electrodes; typically, at least one of these electrodes is transparent. OLEDs are used to create digital displays in devices such as television screens, computer monitors, portable systems such as mobile phones, handheld game consoles and PDAs. === Quantum-dot light-emitting diode === QLED or quantum dot LED is a flat panel display technology introduced by Samsung under this trademark. Other television set manufacturers such as Sony have used the same technology to enhance the backlighting of LCD TVs already in 2013. Quantum dots create their own unique light when illuminated by a light source of shorter wavelength such as blue LEDs. Th

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  • Cultural technology

    Cultural technology

    Cultural technology (Korean: 문화기술; Hanja: 文化技術; RR: munhwagisul) is a system used by South Korean talent agencies to promote K-pop culture throughout the world as part of the Korean Wave. The system was developed by Lee Soo-man, founder of talent agency and record company SM Entertainment. == History == === Coinage === During a speech at the Stanford Graduate School of Business in 2011, Lee said he coined the term "cultural technology" as a system about fourteen years prior, when S.M. Entertainment decided to promote its K-pop artists to all of Asia. In the late 1990s, Lee and his colleagues created a manual on cultural technology, which specified the steps needed to popularize K-pop artists outside South Korea. "The manual, which all S.M. employees are instructed to learn, explains when to bring in foreign composers, producers, and choreographers; what chord progressions to use in what country; the precise color of eyeshadow a performer should wear in a particular country; the exact hand gestures he or she should make; and the camera angles to be used in the videos (a three-hundred-and-sixty-degree group shot to open the video, followed by a montage of individual closeups)," according to The New Yorker. The term "cultural technology," apart from Lee's systemized definition, can be traced back to the lectures of Michael White, an Australian social worker, educator, and therapeutic theorist and his works Narrative Means to Therapeutic Ends (1990) and Maps of Narrative Practice (2007). Its usage may also date further back to French philosopher Michel Foucault (1977). South Korean computer scientist Kwangyun Wohn said he coined the term "culture technology" in 1994. Cultural technology has also been one of six technology initiatives of the South Korean government since 2001. In regards to cultural technology, the Korean Wave is considered one of the most successful outcomes of government support of exporting Korean entertainment products. === The Four Core Stages === The cultural technology system originally employed by SM Entertainment since the 1990s existed in four stages: Casting, Training, Producing, and Marketing/Managing. Each of these four stages were curated to help spread the Hallyu wave through the development of its artists, and are present in the strategies of many other South Korean talent agencies when creating, debuting, and marketing groups. ==== Casting ==== While the majority of K-pop idols are from South Korea, some are from Japan, China, or Thailand. Many of Korea's entertainment companies, such as SM's Global Auditions, Bighit's Hit It auditions, and YG's Next Generation, host worldwide auditions. Scouting and streetcasting are also common, with members like BTS's Jin recruited for their looks or other surface reasons. Sometimes, casting agents go to dance schools to recruit the top dancers to be trained further at the entertainment company. ==== Training ==== Idols train extensively before debut. They receive training in dance, vocal activities, presentation, and other areas that will benefit them in the industry. Oftentimes, this training will last for years at a time, and trainees are in the proverbial dungeon. Before debut, idols and groups attempt to gain fans through pre-debut activities. SM Entertainment has a system in place called SM Rookies, which is a pre-debut team that hosts concerts and releases videos that strengthen the fanbase of the group even before their first single is released. Other forms of pre-debut activities include featuring in other, more seasoned idols' videos—like Nu'est in Orange Caramel or Exo in Girls' Generation-TTS Twinkle or BTS in Jo Kwon. One particular method of pre-debut training is coupled with casting in production shows, like Sixteen and Produce 101, in which members for a final group are selected and trained. ==== Producing ==== The production of music is integral in culture technology. For cultural technology, production of music helps create differentiated content to set trends in the K-pop world—trends that vary from music to also costume, choreography, and music videos. SM in particular focuses heavily on the expansion globally. Some companies also outsource production to more internationally famed parties, like Cube Entertainment's partnership with Skrillex for 4minute's Act. 7. ==== Marketing/Managing ==== In the marketing and management stage, talent agencies seek to broaden their reach. Often, idols have potential for being actors and actresses in dramas, or perhaps hosts/permanent members of variety shows like Kim Hee-chul in Knowing Bros. This so-called omnidirectional marketing lineup ranges over lifestyle and seeks to reach many aspects of living, like music, TV, drama, entertainment, sports, and fashion. This is also where older groups find new life, like Super Junior. Companies are not complacent but experiment constantly to develop the best marketing for the best management system. Marketing also aspires to branch out to international audiences, sometimes via the implementation of variety shows. Despite being primarily in Korean, these variety shows are accessible to all due to the simplistic, easily understood nature of shows—game-oriented shows like Run BTS! or consistently subbed shows like Weekly Idol are popular in showing the fun-loving side of idols. == Evolution into New Culture Technology == In February 2016, SM hosted a press conference discussing the future of SM and its cultural technology. Lee Soo-man announced the implementation of New Culture Technology, an SM-specific system. While SM's cultural technology in the past relied on local, Korean artists like Rain and BoA, the updated model tries to embed more and more foreign singers from strategic markets into larger girl or boy bands. These imported singers are then used to promote their acts back in their respective home countries. New Culture Technology is five projects—SM Station, EDM, Digital Platforms, Rookies Entertainment, and MCN—and one experimental group, NCT. It is a convergence and expansion of SM's four core culture technologies developed and deals heavily with interaction and the desire to innovate through communication. === SM Station === SM announced their intention of creating a new song every week for 52 weeks. Through this constant output of music, they intend to stray away from conventional forms of music and show active movement in digital music market and physical album market through freely and continuously releasing music. Additionally, this SM Station will feature collaborations between artists, producers, composers, and company brands outside the SM label. The name of SM Station is both derived from the radio station and the metaphorical train station. === NCT === Neo Culture Technology (NCT) introduced the idea of "Interactive". SM company tried to connect the targeting market, customers and artist, in order to lead the K-pop culture. NCT (Neo Culture Technology) is the new artist group formed by SM that embodies the concepts of cultural technology. With the seemingly limitless combinations and groups, SM aspires to make the whole world a stage for NCT. Since 2023, there are six NCT groups, who debuted on the digital song sales: NCT U, NCT 127, NCT Dream, WayV, NCT DoJaeJung, and NCT Wish. As of October 2023, the group consists of 25 members: Johnny, Taeyong, Yuta, Kun, Doyoung, Ten, Jaehyun, Winwin, Jungwoo, Mark, Xiaojun, Hendery, Renjun, Jeno, Haechan, Jaemin, Yangyang, Chenle, Jisung, Sion, Riku, Yushi, Daeyoung, Ryo, and Sakuya. ScreaM Records ScreaM Records has been released by SM Entertainment as an EDM label since 2016 for "SM TOWN: New Culture Technology". ScreaM Records is made for "performances made to be enjoyed". It collaborates with inside and outside Korean well-known EDM DJs. ScreaM Records has first launched collaborated song "Wave" E-Mart's home electronics store, Electro Mart. "Our goal is to provide opportunities to producers who have yet to be discovered and produce world famous DJs from the Asian scene." a ScreaM Records representative said. == Three stages of globalization == According to Lee, there are three stages necessary to popularize Korean culture outside South Korea: exporting the product, collaborating with international companies to expand the product's presence abroad, and finally creating a joint venture with international companies. As part of their joint ventures with international companies, South Korean talent agencies may hire foreign composers, producers, and choreographers to ensure K-pop songs feel "local" to foreign countries.

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  • Kolmogorov–Arnold Networks

    Kolmogorov–Arnold Networks

    Kolmogorov–Arnold Networks (KANs) are a type of artificial neural network architecture inspired by the Kolmogorov–Arnold representation theorem, also known as the superposition theorem. Unlike traditional multilayer perceptrons (MLPs), which rely on fixed activation functions and linear weights, KANs replace each weight with a learnable univariate function, often represented using splines. == History == KANs (Kolmogorov–Arnold Networks) were proposed by Liu et al. (2024) as a generalization of the Kolmogorov–Arnold representation theorem (KART), aiming to outperform MLPs in small-scale AI and scientific tasks. Before KANs, numerous studies explored KART's connections to neural networks or used it as a basis for designing new network architectures. In the 1980s and 1990s, early research applied KART to neural network design. Kůrková et al. (1992), Hecht-Nielsen (1987), and Nees (1994) established theoretical foundations for multilayer networks based on KART. Igelnik et al. (2003) introduced the Kolmogorov Spline Network using cubic splines to model complex functions. Sprecher (1996, 1997) introduced numerical methods for building network layers, while Nakamura et al. (1993) created activation functions with guaranteed approximation accuracy. These works linked KART's theoretical potential with practical neural network implementation. KART has also been used in other computational and theoretical fields. Coppejans (2004) developed nonparametric regression estimators using B-splines, Bryant (2008) applied it to high-dimensional image tasks, Liu (2015) investigated theoretical applications in optimal transport and image encryption, and more recently, Polar and Poluektov (2021) used Urysohn operators for efficient KART construction, while Fakhoury et al. (2022) introduced ExSpliNet, integrating KART with probabilistic trees and multivariate B-splines for improved function approximation. == Architecture == KANs are based on the Kolmogorov–Arnold representation theorem, which was linked to the 13th Hilbert problem. Given x = ( x 1 , x 2 , … , x n ) {\displaystyle x=(x_{1},x_{2},\dots ,x_{n})} consisting of n variables, a multivariate continuous function f ( x ) {\displaystyle f(x)} can be represented as: f ( x ) = f ( x 1 , … , x n ) = ∑ q = 1 2 n + 1 Φ q ( ∑ p = 1 n φ q , p ( x p ) ) {\displaystyle f(x)=f(x_{1},\dots ,x_{n})=\sum _{q=1}^{2n+1}\Phi _{q}\left(\sum _{p=1}^{n}\varphi _{q,p}(x_{p})\right)} (1) This formulation contains two nested summations: an outer and an inner sum. The outer sum ∑ q = 1 2 n + 1 {\displaystyle \sum _{q=1}^{2n+1}} aggregates 2 n + 1 {\displaystyle 2n+1} terms, each involving a function Φ q : R → R {\displaystyle \Phi _{q}:\mathbb {R} \to \mathbb {R} } . The inner sum ∑ p = 1 n {\displaystyle \sum _{p=1}^{n}} computes n terms for each q, where each term φ q , p : [ 0 , 1 ] → R {\displaystyle \varphi _{q,p}:[0,1]\to \mathbb {R} } is a continuous function of the single variable x p {\displaystyle x_{p}} . The inner continuous functions φ q , p {\displaystyle \varphi _{q,p}} are universal, independent of f {\displaystyle f} , while the outer functions Φ q {\displaystyle \Phi _{q}} depend on the specific function f {\displaystyle f} being represented. The representation (1) holds for all multivariate functions f {\displaystyle f} as proved in . If f {\displaystyle f} is continuous, then the outer functions Φ q {\displaystyle \Phi _{q}} are continuous; if f {\displaystyle f} is discontinuous, then the corresponding Φ q {\displaystyle \Phi _{q}} are generally discontinuous, while the inner functions φ q , p {\displaystyle \varphi _{q,p}} remain the same universal functions. Liu et al. proposed the name KAN. A general KAN network consisting of L layers takes x to generate the output as: K A N ( x ) = ( Φ L − 1 ∘ Φ L − 2 ∘ ⋯ ∘ Φ 1 ∘ Φ 0 ) x {\displaystyle \mathrm {KAN} (x)=(\Phi ^{L-1}\circ \Phi ^{L-2}\circ \cdots \circ \Phi ^{1}\circ \Phi ^{0})x} (3) Here, Φ l {\displaystyle \Phi ^{l}} is the function matrix of the l-th KAN layer or a set of pre-activations. Let i denote the neuron of the l-th layer and j the neuron of the (l+1)-th layer. The activation function φ j , i l {\displaystyle \varphi _{j,i}^{l}} connects (l, i) to (l+1, j): φ j , i l , l = 0 , … , L − 1 , i = 1 , … , n l , j = 1 , … , n l + 1 {\displaystyle \varphi _{j,i}^{l},\quad l=0,\dots ,L-1,\;i=1,\dots ,n_{l},\;j=1,\dots ,n_{l+1}} (4) where nl is the number of nodes of the l-th layer. Thus, the function matrix Φ l {\displaystyle \Phi ^{l}} can be represented as an n l + 1 × n l {\displaystyle n_{l+1}\times n_{l}} matrix of activations: x l + 1 = ( φ 1 , 1 l ( ⋅ ) φ 1 , 2 l ( ⋅ ) ⋯ φ 1 , n l l ( ⋅ ) φ 2 , 1 l ( ⋅ ) φ 2 , 2 l ( ⋅ ) ⋯ φ 2 , n l l ( ⋅ ) ⋮ ⋮ ⋱ ⋮ φ n l + 1 , 1 l ( ⋅ ) φ n l + 1 , 2 l ( ⋅ ) ⋯ φ n l + 1 , n l l ( ⋅ ) ) x l {\displaystyle x^{l+1}={\begin{pmatrix}\varphi _{1,1}^{l}(\cdot )&\varphi _{1,2}^{l}(\cdot )&\cdots &\varphi _{1,n_{l}}^{l}(\cdot )\\\varphi _{2,1}^{l}(\cdot )&\varphi _{2,2}^{l}(\cdot )&\cdots &\varphi _{2,n_{l}}^{l}(\cdot )\\\vdots &\vdots &\ddots &\vdots \\\varphi _{n_{l+1},1}^{l}(\cdot )&\varphi _{n_{l+1},2}^{l}(\cdot )&\cdots &\varphi _{n_{l+1},n_{l}}^{l}(\cdot )\end{pmatrix}}x^{l}} == Implementations == To make the KAN layers optimizable, the inner function is formed by the combination of spline and basic functions as the formula: φ ( x ) = w b b ( x ) + w s spline ( x ) {\displaystyle \varphi (x)=w_{b}\,b(x)+w_{s}\,{\text{spline}}(x)} where b ( x ) {\displaystyle b(x)} is the basic function, usually defined as s i l u ( x ) = x / ( 1 + e x ) {\displaystyle silu(x)=x/(1+e^{x})} and w b {\displaystyle w_{b}} is the base weight matrix. Also, w s {\displaystyle w_{s}} is the spline weight matrix and spline ( x ) {\displaystyle {\text{spline}}(x)} is the spline function. The spline function can be a sum of B-splines. spline ( x ) = ∑ i c i B i ( x ) {\displaystyle {\text{spline}}(x)=\sum _{i}c_{i}B_{i}(x)} Many studies suggested to use other polynomial and curve functions instead of B-spline to create new KAN variants. == Functions used == The choice of functional basis strongly influences the performance of KANs. Common function families include: B-splines: Provide locality, smoothness, and interpretability; they are the most widely used in current implementations. RBFs (include Gaussian RBFs): Capture localized features in data and are effective in approximating functions with non-linear or clustered structures. Chebyshev polynomials: Offer efficient approximation with minimized error in the maximum norm, making them useful for stable function representation. Rational function: Useful for approximating functions with singularities or sharp variations, as they can model asymptotic behavior better than polynomials. Fourier series: Capture periodic patterns effectively and are particularly useful in domains such as physics-informed machine learning. Wavelet functions (DoG, Mexican hat, Morlet, and Shannon): Used for feature extraction as they can capture both high-frequency and low-frequency data components. Piecewise linear functions: Provide efficient approximation for multivariate functions in KANs. == Usage == In some modern neural architectures like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and Transformers, KANs are typically used as drop-in substitutes for MLP layers. Despite KANs' general-purpose design, researchers have created and used them for a number of tasks: Scientific machine learning (SciML): Function fitting, partial differential equations (PDEs) and physical/mathematical laws. Continual learning: KANs better preserve previously learned information during incremental updates, avoiding catastrophic forgetting due to the locality of spline adjustments. Graph neural networks: Extensions such as Kolmogorov–Arnold Graph Neural Networks (KA-GNNs) integrate KAN modules into message-passing architectures, showing improvements in molecular property prediction tasks. Sensor data processing: Kolmogorov–Arnold Networks (KANs) have recently been applied to sensor data processing due to their ability to model complex nonlinear relationships with relatively few parameters and improved interpretability compared to conventional multilayer perceptrons. Applications include industrial soft sensors, biomedical signal analysis, remote sensing, and environmental monitoring systems. == Drawbacks == KANs can be computationally intensive and require a large number of parameters due to their use of polynomial functions to capture data.

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  • Key & See

    Key & See

    Key & See is a variation of the TV Key service that forms part of the open, standards-based interactive TV services platform provided by Miniweb Interactive. Key & See allows viewers to access the interactive TV content made available by broadcasters and channel owners while leaving quarter of their screen tuned to the programme they are already watching Like TV Key, Key & See can be used with interactive TV services on UK satellite TV provider Sky Digital (BSkyB) Key & See works in the same way as a TV Key but the numeric shortcut code is associated with a broadcaster and a particular TV channel or programme. Miniweb Interactive offers commercial brands and broadcasters the chance to utilise TV Key and Key & See technology as part of its interactive TV services platform

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  • MicroTCA

    MicroTCA

    MicroTCA (short for Micro Telecommunications Computing Architecture, also: μTCA) is a modular, open standard, created and maintained by the PCI Industrial Computer Manufacturers Group (PICMG). It provides the electrical, mechanical, thermal and management specifications to create a switched fabric computer system, using Advanced Mezzanine Cards (AMC), connected directly to a backplane. MicroTCA is a descendant of the AdvancedTCA standard. == History == The rapid expansion of mobile telecommunications and their associated services (such as text messages) at the beginning of the millennium increased the demand of processing power in telecommunication systems. The existing "carrier grade" (see RAS) computing architectures were not fit to house the high performance processors of the time. In order to answer those demands, about 100 companies worked together in PICMG, resulting in the Advanced Telecommunications Architecture (AdvancedTCA, ATCA), published in 2002. After the introduction of AdvancedTCA, a standard was developed, to cater towards smaller telecommunications systems at the edge of the network. This standard was geared towards a more compact, less expensive systems, without cutting back on reliability or data throughput. This standard, called MicroTCA, was ratified 2006. MicroTCA systems migrated after its release into non-telecommunication sectors, like defence, avionics and science. This resulted in extensions to the base-standard, called modules. == Modules == === MicroTCA.0 === The base-specification for properties common to all other modules, ratified July 6, 2006. This includes: Mechanical specifications, like possible dimensions of card cages, backplanes and supported AMC-modules Electrical specifications, like power distribution and interface layout Thermal specifications, like possible cooling layouts or available cooling power Management specifications A second revision of the base-specifications was ratified January 16, 2020, containing some corrections, as well as alterations, necessary to implement higher speed Ethernet fabrics, like 10GBASE-KR and 40GBASE-KR4. === MicroTCA.1 === This module adds specifications for ruggedized systems, using forced air for cooling. Possible scenarios for MicroTCA.1-based systems include outside plant telecom, industrial and aerospace environments === MicroTCA.2 === This module adds specifications for more stringent requirements with regards to temperature, shock, vibration and other environmental conditions. These specifications are geared towards use in outside plant telecom, machine and transport industry, as well as military airborne, shipboard and ground mobile equipment. MicroTCA.2 allows the use of air- and conduction-cooled AMC-modules. === MicroTCA.3 === This module adds specifications for even more stringent requirements with regards to temperature, shock, vibration and other environmental conditions. These specifications are geared towards use in outside plant telecom, machine and transport industry, as well as military airborne, shipboard and ground mobile equipment. MicroTCA.3 requires the use of conduction-cooled AMC-modules. === MicroTCA.4 === This module extends the AMC with a Rear Transition Module (RTM), increasing PCB-space and modularity. AMC and RTM are connected with a connector, located in zone 3, defined in MicroTCA.0. These specifications are geared towards use in large-scale scientific devices, like particle accelerators or telescopes. == Components of MicroTCA == === Card Cage === The card cage (also: shelf, crate) houses all the other components and as such has two primary functions: Provide mechanical stability to the other components Ensure sufficient cooling There exist a wide array of card cages. They usually differ in: the type of modules they support (MTCA.0, MTCA.1, ...) the number of slots they provide (typically between 2 and 12) the architecture of the installed backplane (see below) the cooling scheme they use (i.e. airflow front-to-back, bottom-to-top, side-to-side, conductive,...) === Backplane === The backplane is a printed circuit board, mounted directly into the card cage. It connects all other components of a MicroTCA system to each other and provides power, data access and management access to them. Two types of power are distributed over the backplane, Management Power (+3.3 V) and Payload Power (+12 V). Unlike typical backplanes, where power is distributed to all components via a common "powerplane" in the PCB, on a MicroTCA backplane, Management and Payload Power are distributed to each component individually. While Management Power is provided to each module connected to a powered backplane, Payload Power has to be granted by the MicroTCA Carrier Hub (MCH), after ensuring that the module is MicroTCA-compatible. The standard defines various communication buses, which the backplane can/should provide: Gigabit Ethernet IPMI SATA Fat pipe (can be used for PCIe, SRIO or 10G/40G Ethernet) Point to Point Links Clocks JTAG === Cooling Unit === The Cooling Unit (CU) provides controlled air flow in air-flow-cooled card cages. It usually consists of an array of fans and a controller, which is connected to the backplane. The MicroTCA Carrier Hub (MCH) can read-out temperature sensors (if present) and fan speed, as well as change fan speed via IPMI. The Cooling Unit is usually fitted to a specific card cage. Some CUs are easily detachable (i.e. for cleaning or replacement), while other card cages come with integrated, non-detachable CUs. === Power Module === The Power Module (PM, also: Power Supply) converts the AC power from the power line to the +3.3 V Management Power (MP) and +12 V Payload Power (PP), both of which are DC. There exist a variety of power modules, which differ in: form factor (i.e. double width, single width) input voltage (110 V, 220 V, both) output power (i.e. 600 W, 1000 W) The power module senses the presence of a module in a slot via a specified pin in the module connector, and immediately provides that module with management power. Payload power is managed by the MicroTCA Carrier Hub (MCH), which communicates with the power module via IPMI. The power module uses its own type of connector, and can thus only be installed into designated slots, which in turn can't carry any other type of module. Some card cages provide an additional power module slot for redundancy. In such a case, one slot is the primary, which will provide power by default, and the other one is secondary, providing power only, if the primary does not. === MicroTCA Carrier Hub === The MicroTCA Carrier Hub (MCH) is the central managing device of a MicroTCA card cage. It manages power distribution and cooling. It usually also provides Gigabit Ethernet and/or PCIe/Serial RapidIO switching. Some MCHs additionally provide clocking. As the name indicates, they are the hub of various star topologies (i.e. for Ethernet, PCIe) on the backplane and thus require dedicated slot(s). Some backplanes support two MCHs for redundancy. In this case there are two MCH slots, with one being designated primary, and one secondary. === Advanced Mezzanine Card === Advanced Mezzanine Card (AMC) is a standard for hot-pluggable PCBs. It was originally developed to be used in AdvancedTCA systems. The standard specifies: the dimensions of the PCB with two width variants (single, double) and three height variants (Compact, Mid-size, Full) type, location and orientation of connectors (i.e. Zone 1, 2, 3) There is a huge variation of functionalities, an AMC can fulfill: Computing (i.e. a module with CPU, RAM, SSD and on-board graphics) Storage (i.e. SSD carrier) Graphics card FPGA card (i.e. for signal processing) FMC carrier Digitizer card (Analog-Digital and Digital-Analog Conversion) Clocking and Triggering and others === Rear Transition Module (MTCA.4 only) === The Rear Transition Module (RTM) was added in the MicroTCA.4 standard. It is connected directly to an AMC via a connector, located in zone 3, requiring a double width AMC and RTM. An RTM has about the same dimensions, as an AMC, basically doubling the available PCB-space per slot in an MTCA.4 card cage. Its power is provided by the AMC. Thus an RTM can not operate on its own, but requires a paired AMC. The zone 3 connector is electrically free configurable, making it possible, that a mechanically fitting AMC-RTM pair is electrically incompatible. To avoid damage due to that incompatibility, a mechanical code-pin was added to MTCA.4-compatible AMCs and RTMs, mechanically preventing the installation of an electrically incompatible RTM to an AMC. The functionality of RTMs includes, but is not limited to: RF-signal pre-/post-processing (i.e. filtering, Up-/Down-conversion, Vector De-/Modulation) Digital signal pre-/post-processing Clock-generation/-distribution Device interfaces Date storage CPU (only MCH-RTM)

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