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  Educational robotics

  Educational robotics teaches the design, analysis, application and operation of robots. Robots include articulated robots, mobile robots or autonomous vehicles. Educational robotics can be taught from elementary school to graduate programs. Robotics may also be used to motivate and facilitate the instruction other, often foundational, topics such as computer programming, artificial intelligence or engineering design. == Education and training == Robotics engineers design robots, maintain them, develop new applications for them, and conduct research to expand the potential of robotics. Robots have become a popular educational tool in some middle and high schools, as well as in numerous youth summer camps, raising interest in programming, artificial intelligence and robotics among students. First-year computer science courses at several universities now include programming of a robot in addition to traditional software engineering-based coursework. == Category of Educational robotics == The categories of educational robots seen as having more than one category. It can be alienated into different categories based on their physical design and coding method. Generally they are categorised as arm robots, wheeled mobile robots and humanoid robots. Tangibly, coded robots uses a physical means of coding instead of the screens coding. === Initiatives in schools === Leachim, was a robot teacher programmed with the class curricular, as well as certain biographical information on the 40 students whom it was programmed to teach. Leachim could synthesize human speech using Diphone synthesis. It was invented by Michael J. Freeman in 1974 and was tested in a fourth grade classroom in the Bronx, New York. === Post-secondary degree programs === From approximately 1960 through 2005, robotics education at post-secondary institutions took place through elective courses, thesis experiences and design projects offered as part of degree programs in traditional academic disciplines, such as mechanical engineering, electrical engineering, industrial engineering or computer science. Since 2005, more universities have begun granting degrees in robotics as a discipline in its own right, often under the name "Robotic Engineering". Based on a 2015 web-based survey of robotics educators, the degree programs and their estimates annual graduates are listed alphabetically below. Note that only official degree programs where the word "robotics" appears on the transcript or diploma are listed here; whereas degree programs in traditional disciplines with course concentrations or thesis topics related to robotics are deliberately omitted. === Certification === The Robotics Certification Standards Alliance (RCSA) is an international robotics certification authority that confers various industry- and educational-related robotics certifications. === Summer robotics camp === Several summer camp programs include robotics as part of their core curriculum. In addition, youth summer robotics programs are frequently offered by celebrated museums such as the American Museum of Natural History and The Tech Museum of Innovation in Silicon Valley, CA, just to name a few. There are of benefits that come from attending robotics camps. It teaches students how to use teamwork, resilience and motivation, and decision-making. Students learn teamwork because most camps involve exciting activities requiring teamwork. Resilience and motivation is expected because by completing the challenging programs, students feel talented and accomplished after they complete the program. Also students are given unique situations making them make decisions to further their situation. === Educational robotics in special education === Educational robotics can be a useful tool in early and special education. According to a journal on new perspectives in science education, educational robotics can help to develop abilities that promote autonomy and assist their integration into society. Social and personal skills can also be developed through educational robotics. Using Lego Mindstorms NXT, schoolteachers were able to work with middle school aged children in order to develop programs and improve the children's social and personal skills. Additionally, problem solving skills and creativity were utilized through the creation of artwork and scenery to house the robots. Other studies show the benefits of educational robotics in special education as promoting superior cognitive functions, including executive functions. This can lead to an increased ability in "problem solving, reasoning and planning in typically developing preschool children." Through eight weeks of weekly forty-five-minute group sessions using the Bee-Bot, an increase in interest, attention, and interaction between both peers and adults was found in the school and preschool-aged children with Down Syndrome. This study suggests that educational robotics in the classroom can also lead to an improvement in visuo-spatial memory and mental planning. Furthermore, executive functions seemed to be possible in one child during this study.

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  Digital anthropology

  Digital anthropology is the anthropological study of the relationship between humans and digital-era technology. The field is new, and thus has a variety of names with a variety of emphases. These include techno-anthropology, digital ethnography, cyberanthropology, and virtual anthropology. == Definition and scope == Most anthropologists who use the phrase "digital anthropology" are specifically referring to online and Internet technology. The study of humans' relationship to a broader range of technology may fall under other subfields of anthropological study, such as cyborg anthropology. The Digital Anthropology Group (DANG) is classified as an interest group in the American Anthropological Association. DANG's mission includes promoting the use of digital technology as a tool of anthropological research, encouraging anthropologists to share research using digital platforms, and outlining ways for anthropologists to study digital communities. Cyberspace or the "virtual world" itself can serve as a "field" site for anthropologists, allowing the observation, analysis, and interpretation of the sociocultural phenomena springing up and taking place in any interactive space. National and transnational communities, enabled by digital technology, establish a set of social norms, practices, traditions, storied history and associated collective memory, migration periods, internal and external conflicts, potentially subconscious language features and memetic dialects comparable to those of traditional, geographically confined communities. This includes the various communities built around free and open-source software, online platforms such as Facebook, Twitter/X, Instagram, 4chan and Reddit and their respective sub-sites, and politically motivated groups like Anonymous, WikiLeaks, or the Occupy movement. A number of academic anthropologists have conducted traditional ethnographies of virtual worlds, such as Bonnie Nardi's study of World of Warcraft or Tom Boellstorff's study of Second Life. Academic Gabriella Coleman has done ethnographic work on the Debian software community and the Anonymous hacktivist network. Theorist Nancy Mauro-Flude conducts ethnographic field work on computing arts and computer subcultures such as systerserver.net a part of the communities of feminist web servers and the Feminist Internet network. Eitan Y. Wilf examines the intersection of artists' creativity and digital technology and artificial intelligence. Yongming Zhou studied how in China the internet is used to participate in politics. Eve M. Zucker and colleagues study the shift to digital memorialization of mass atrocities and the emergent role of artificial intelligence in these processes. Victoria Bernal conducted ethnographic research on the themes of nationalism and citizenship among Eritreans participating in online political engagement with their homeland. Anthropological research can help designers adapt and improve technology. Australian anthropologist Genevieve Bell did extensive user experience research at Intel that informed the company's approach to its technology, users, and market. == Methodology == === Digital fieldwork === Many digital anthropologists who study online communities use traditional methods of anthropological research. They participate in online communities in order to learn about their customs and worldviews, and back their observations with private interviews, historical research, and quantitative data. Their product is an ethnography, a qualitative description of their experience and analyses. Other anthropologists and social scientists have conducted research that emphasizes data gathered by websites and servers. However, academics often have trouble accessing user data on the same scale as social media corporations like Facebook and data mining companies like Acxiom. In terms of method, there is a disagreement in whether it is possible to conduct research exclusively online or if research will only be complete when the subjects are studied holistically, both online and offline. Tom Boellstorff, who conducted a three-year research as an avatar in the virtual world Second Life, defends the first approach, stating that it is not just possible, but necessary to engage with subjects “in their own terms”. Others, such as Daniel Miller, have argued that an ethnographic research should not exclude learning about the subject's life outside the internet. === Digital technology as a tool of anthropology === The American Anthropological Association offers an online guide for students using digital technology to store and share data. Data can be uploaded to digital databases to be stored, shared, and interpreted. Text and numerical analysis software can help produce metadata, while a codebook may help organize data. == Ethics == Online fieldwork offers new ethical challenges. According to the American Anthropological Association's ethics guidelines, anthropologists researching a community must make sure that all members of that community know they are being studied and have access to data the anthropologist produces. However, many online communities' interactions are publicly available for anyone to read, and may be preserved online for years. Digital anthropologists debate the extent to which lurking in online communities and sifting through public archives is ethical. The Association also asserts that anthropologists' ability to collect and store data at all is "a privilege", and researchers have an ethical duty to store digital data responsibly. This means protecting the identity of participants, sharing data with other anthropologists, and making backup copies of all data. == Prominent figures == Genevieve Bell is an Australian cultural anthropologist credited for pioneering the User Experience field. During her time working for Intel Corporation, Bell studied how various cultures from around the world interacted with and experienced technology. Researching and improving user experience allows companies and designers to gather data regarding how users utilize their digital products and what requires improvement or expansion. Tom Boellstorff is an anthropologist known for Coming of Age in Second Life: An Anthropologist Explores the Virtually Human where he conducted research on how engaging in virtual worlds affects the player’s sense of self. Gabriella Coleman is an American anthropologist concerned with the politics, ethics, and culture of hacking and online activism. Coleman’s most notable ethnography features the hacktivist collective Anonymous, where she argues that various genres of hacking exist according to the social conditions at play. Coleman is dedicated to making her ethnography accessible to a diverse audience, including academics and non-academics. Diana E. Forsythe was an American anthropologist of science and technology and the author of the essays featured in Studying Those Who Study Us: An Anthropologist in the World of Artificial Intelligence. She asked relevant questions such as how should humans interact with computers and how gender roles are maintained in technology-oriented occupations. Heather Horst is a sociocultural anthropologist interested in the relationship between digital social relations and material culture. Nancy Mauro-Flude is a design anthropologist whose work explores the tacit relations between embodied cognition, computational materiality, maker culture, self-hosted webserver cooperatives, creative practice, and artistic research in digital infrastructure and Internet publishing. Mizuko Ito is a Japanese cultural anthropologist specializing in technology use and the intersection between computers and the social sciences. Her primary interest is in how young people utilize media technology and how it can be used to engage students in education. Daniel Miller is an anthropologist with a concentration in digital anthropology. His research includes the smartphone and perpetual opportunism, the intent and consequences of posting on social media in various geographical locations, and how hospice patients use media to socialize in the last stage of their lives. Mike Wesch is a cultural anthropologist interested in how people share their lives, cultures, and beliefs through digital media.

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  New media

  New media are communication technologies that enable or enhance interaction between users, as well as interaction between users and content. In the middle of the 1990s, the phrase "new media" became widely used as part of a sales pitch for the influx of interactive CD-ROMs for entertainment and education. The new media technologies, sometimes known as Web 2.0, include a wide range of web-related communication tools such as blogs, wikis, online social networking, virtual worlds, and other social media platforms. The phrase "new media" refers to computational media that share material online and through computers. New media inspire new ways of thinking about older media. Media do not replace one another in a clear, linear succession, instead evolving in a more complicated network of interconnected feedback loops . What is different about new media is how they specifically refashion traditional media and how older media refashion themselves to meet the challenges of new media. Unless they contain technologies that enable digital generative or interactive processes, broadcast television programs, non-interactive news websites, feature films, magazines, and books are not considered to be new media. The term "new media" stands in contrast to old media, which dominated the media landscape as a form of mass media for many years. == History == In the 1950s, connections between computing and radical art began to grow stronger. It was not until the 1980s that Alan Kay and his co-workers at Xerox PARC began to give the computability of a personal computer to the individual, rather than have a big organization be in charge of this. In the late 1980s and early 1990s, however, we seem to witness a different kind of parallel relationship between social changes and computer design. Although causally unrelated, conceptually, it makes sense that the Cold War and the design of the Web took place at exactly the same time. Writers and philosophers such as Marshall McLuhan were instrumental in the development of media theory during this period which is now famous declaration in Understanding Media: The Extensions of Man, that "the medium is the message" drew attention to the too often ignored influence media and technology themselves, rather than their "content," have on humans' experience of the world and on society broadly. Until the 1980s, media relied primarily upon print and analog broadcast models such as television and radio. The last twenty-five years have seen the rapid transformation into media which are predicated upon the use of digital technologies such as the Internet and video games. However, these examples are only a small representation of new media. The use of digital computers has transformed the remaining 'old' media, as suggested by the advent of digital television and online publications. Even traditional media forms such as the printing press have been transformed through the application of technologies by using of image manipulation software like Adobe Photoshop and desktop publishing tools. Andrew L. Shapiro argues that the "emergence of new, digital technologies signals a potentially radical shift of who is in control of information, experience and resources". W. Russell Neuman suggests that whilst the "new media" have technical capabilities to pull in one direction, economic and social forces pull back in the opposite direction. According to Neuman, "We are witnessing the evolution of a universal interconnected network of audio, video, and electronic text communications that will blur the distinction between interpersonal and mass communication; and between public and private communication". Neuman argues that new media will: Alter the meaning of geographic distance. Allow for a huge increase in the volume of communication. Provide the possibility of increasing the speed of communication. Provide opportunities for interactive communication. Allow forms of communication that were previously separate to overlap and interconnect. Consequently, it has been the contention of scholars such as Douglas Kellner and James Bohman that new media and particularly the Internet will provide the potential for a democratic postmodern public sphere, in which citizens can participate in well informed, non-hierarchical debate pertaining to their social structures. Contradicting these positive appraisals of the potential social impacts of new media are scholars such as Edward S. Herman and Robert McChesney who have suggested that the transition to new media has seen a handful of powerful transnational telecommunications corporations who achieve a level of global influence which was hitherto unimaginable. Scholars have highlighted both the positive and negative potential and actual implications of new media technologies, suggesting that some of the early work in new media studies was guilty of technologicaldeterminism – whereby the effects of media were determined by the technologies themselves, rather than by tracing the complex social networks that governed the development, funding, implementation, and future evolution of any technology. Based on the argument that people have a limited amount of time to spend on the consumption of different media, displacement theory argue that the viewership or readership of one particular outlet leads to the reduction in the amount of time spent by the individual on another. The introduction of new media, such as the internet, therefore reduces the amount of time individuals would spend on existing "old" media, which could ultimately lead to the end of such traditional media. == Definition == Although, there are several ways that new media may be described, Lev Manovich, in an introduction to The New Media Reader, defines new media by using eight propositions: New media versus cyberculture – Cyberculture is the various social phenomena that are associated with the Internet and network communications (blogs, online multi-player gaming), whereas new media is concerned more with cultural objects and paradigms (digital to analog television, smartphones). New media as computer technology used as a distribution platform – New media are the cultural objects which use digital computer technology for distribution and exhibition. e.g. (at least for now) Internet, Web sites, computer multimedia, Blu-ray disks etc. The problem with this is that the definition must be revised every few years. The term "new media" will not be "new" anymore, as most forms of culture will be distributed through computers. New media as digital data controlled by software – The language of new media is based on the assumption that, in fact, all cultural objects that rely on digital representation and computer-based delivery do share a number of common qualities. New media is reduced to digital data that can be manipulated by software as any other data. Now media operations can create several versions of the same object. An example is an image stored as matrix data which can be manipulated and altered according to the additional algorithms implemented, such as color inversion, gray-scaling, sharpening, rasterizing, etc. New media as the mix between existing cultural conventions and the conventions of software – New media today can be understood as the mix between older cultural conventions for data representation, access, and manipulation and newer conventions of data representation, access, and manipulation. The "old" data are representations of visual reality and human experience, and the "new" data is numerical data. The computer is kept out of the key "creative" decisions, and is delegated to the position of a technician. e.g. In film, software is used in some areas of production, in others are created using computer animation. New media as the aesthetics that accompanies the early stage of every new modern media and communication technology – While ideological tropes indeed seem to be reappearing rather regularly, many aesthetic strategies may reappear two or three times ... In order for this approach to be truly useful it would be insufficient to simply name the strategies and tropes and to record the moments of their appearance; instead, we would have to develop a much more comprehensive analysis which would correlate the history of technology with social, political, and economical histories or the modern period. New media as faster execution of algorithms previously executed manually or through other technologies – Computers are a huge speed-up of what were previously manual techniques. e.g. calculators. Dramatically speeding up the execution makes possible previously non-existent representational technique. This also makes possible of many new forms of media art such as interactive multimedia and video games. On one level, a modern digital computer is just a faster calculator, we should not ignore its other identity: that of a cybernetic control device. New media as the encoding of modernist avant-garde; new media as metamedia – Manovi

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  Redshift (theory)

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

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  AppyStore

  AppyStore is a comprehensive learning videos and games app for kids up to the age of 8 years. The platform developed by Mauj Mobile, a mobile value-added services (VAS) provider curates content to help in child development by leveraging technology. Mauj is funded by Sequoia Capital, Westbridge Capital and Intel Capital. == Background == AppyStore was launched in 2014 as a platform providing content for kids between the ages of 1.5 and 6 years. AppyStore subsequently extended its services for kids up to 8 years of age. The company operates on a subscription-based model and claims to have 5,000 learning games and videos segregated in 18 learning areas developed to help children gain optimal skills and qualities. According to an article published in Business Standard, the application is claimed to be one of the top 5 apps that help to enhance the logical and imaginative capabilities of children. AppyStore was awarded the Best app for kids by Google Play in December 2017. == Service == The company provides content via a website and an Android app. The website and android app provide learning games, rhymes, phonics, reading, stories, science, numbers, maths, logic videos comprising puzzles, worksheets, videos and fun activities and the premium subscription also includes physical worksheets which are home delivered. This content is educational and has been handpicked by teachers and experts with an understanding of the major areas of child development milestones for children up to 8 years of age. The mobile application also allows parents to track the progress of their child on the basis of the number of videos viewed.

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  Interference (communication)

  In telecommunications, an interference is that which modifies a signal in a disruptive manner, as it travels along a communication channel between its source and receiver. The term is often used to refer to the addition of unwanted signals to a useful signal. Common examples include: Electromagnetic interference (EMI) Co-channel interference (CCI), also known as crosstalk Adjacent-channel interference (ACI) Intersymbol interference (ISI) Inter-carrier interference (ICI), caused by doppler shift in OFDM modulation (multitone modulation). Common-mode interference (CMI) Conducted interference Noise is a form of interference but not all interference is noise. Radio resource management aims at reducing and controlling the co-channel and adjacent-channel interference. == Interference alignment == A solution to interference problems in wireless communication networks is interference alignment, which was crystallized by Syed Ali Jafar at the University of California, Irvine. A specialized application was previously studied by Yitzhak Birk and Tomer Kol for an index coding problem in 1998. For interference management in wireless communication, interference alignment was originally introduced by Mohammad Ali Maddah-Ali, Abolfazl S. Motahari, and Amir Keyvan Khandani, at the University of Waterloo, for communication over wireless X channels. Interference alignment was eventually established as a general principle by Jafar and Viveck R. Cadambe in 2008, when they introduced "a mechanism to align an arbitrarily large number of interferers, leading to the surprising conclusion that wireless networks are not essentially interference limited." This led to the adoption of interference alignment in the design of wireless networks. Jafar explained: My research group crystallized the concept of interference alignment and showed that through interference alignment, it is possible for everyone to access half of the total bandwidth free from interference. Initially this result was shown under a number of idealized assumptions that are typical in theoretical studies. We have since continued to work on peeling off these idealizations one at a time, to bring the theory closer to practice. Along the way we have made numerous discoveries through the lens of interference alignment, which reveal new and powerful signaling schemes. According to New York University senior researcher Paul Horn: Syed Jafar revolutionized our understanding of the capacity limits of wireless networks. He demonstrated the astounding result that each user in a wireless network can access half of the spectrum without interference from other users, regardless of how many users are sharing the spectrum. This is a truly remarkable result that has a tremendous impact on both information theory and the design of wireless networks.

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  Modulation error ratio

  The modulation error ratio (MER) is a measure used to quantify the performance of a digital radio (or digital TV) transmitter or receiver in a communications system using digital modulation (such as QAM). A signal sent by an ideal transmitter or received by a receiver would have all constellation points precisely at the ideal locations, however various imperfections in the implementation (such as noise, low image rejection ratio, phase noise, carrier suppression, distortion, etc.) or signal path cause the actual constellation points to deviate from the ideal locations. Transmitter MER can be measured by specialized equipment, which demodulates the received signal in a similar way to how a real radio demodulator does it. Demodulated and detected signal can be used as a reasonably reliable estimate for the ideal transmitted signal in MER calculation. == Definition == An error vector is a vector in the I-Q plane between the ideal constellation point and the point received by the receiver. The Euclidean distance between the two points is its magnitude. The modulation error ratio is equal to the ratio of the root mean square (RMS) power (in Watts) of the reference vector to the power (in Watts) of the error. It is defined in dB as: M E R ( d B ) = 10 log 10 ⁡ ( P s i g n a l P e r r o r ) {\displaystyle \mathrm {MER(dB)} =10\log _{10}\left({P_{\mathrm {signal} } \over P_{\mathrm {error} }}\right)} where Perror is the RMS power of the error vector, and Psignal is the RMS power of ideal transmitted signal. MER is defined as a percentage in a compatible (but reciprocal) way: M E R ( % ) = P e r r o r P s i g n a l × 100 % {\displaystyle \mathrm {MER(\%)} ={\sqrt {P_{\mathrm {error} } \over P_{\mathrm {signal} }}}\times 100\%} with the same definitions. MER is closely related to error vector magnitude (EVM), but MER is calculated from the average power of the signal. MER is also closely related to signal-to-noise ratio. MER includes all imperfections including deterministic amplitude imbalance, quadrature error and distortion, while noise is random by nature.

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  GPU switching

  GPU switching is a mechanism used on computers with multiple graphic controllers. This mechanism allows the user to either maximize the graphic performance or prolong battery life by switching between the graphic cards. It is mostly used on gaming laptops which usually have an integrated graphic device and a discrete video card. == Basic components == Most computers using this feature contain integrated graphics processors and dedicated graphics cards that applies to the following categories. === Integrated graphics === Also known as: Integrated graphics, shared graphics solutions, integrated graphics processors (IGP) or unified memory architecture (UMA). This kind of graphics processors usually have much fewer processing units and share the same memory with the CPU. Sometimes the graphics processors are integrated onto a motherboard. It is commonly known as: on-board graphics. A motherboard with on-board graphics processors doesn't require a discrete graphics card or a CPU with graphics processors to operate. === Dedicated graphics cards === Also known as: discrete graphics cards. Unlike integrated graphics, dedicated graphics cards have much more processing units and have its own RAM with much higher memory bandwidth. In some cases, a dedicated graphics chip can be integrated onto the motherboards, B150-GP104 for example. Regardless of the fact that the graphics chip is integrated, it is still counted as a dedicated graphics cards system because the graphics chip is integrated with its own memory. == Theory == Most Personal Computers have a motherboard that uses a Southbridge and Northbridge structure. === Northbridge control === The Northbridge is one of the core logic chipset that handles communications between the CPU, GPU, RAM and the Southbridge. The discrete graphics card is usually installed onto the graphics card slot such as PCI-Express and the integrated graphics is integrated onto the CPU itself or occasionally onto the Northbridge. The Northbridge is the most responsible for switching between GPUs. The way how it works usually has the following process (refer to the Figure 1. on the right): The Northbridge receives input from Southbridge through the internal bus. The Northbridge signals to CPU through the Front-side bus. The CPU runs the task assignment application (usually the graphics card driver) to determine which GPU core to use. The CPU passes down the command to the Northbridge. The Northbridge passes down the command to the according GPU core. The GPU core processes the command and returns the rendered data back to the Northbridge. The Northbridge sends the rendered data back to Southbridge. === Southbridge control === The Southbridge is a set of integrated circuits such Intel's I/O Controller Hub (ICH). It handles all of a computer's I/O functions, such as receiving the keyboard input and outputting the data onto the screen. The way how it usually works usually has two steps: Take in the user input and pass it down to the Northbridge. (Optional) Receive the rendered data from the Northbridge and output it. The reason why the second step can be optional is that sometimes the rendered the data is outputted directly from the discrete graphics card which is located on the graphics card slot so there is no need to output the data through the Southbridge. == Main purpose == GPU switching is mostly used for saving energy by switching between graphic cards. The dedicated graphics cards consume much more power than integrated graphics but also provides higher 3D performances, which is needed for a better gaming and CAD experience. Following is a list of the TDPs of the most popular CPU with integrated graphics and dedicated graphics cards. The dedicated graphics cards exhibit much higher power consumption than the integrated graphics on both platforms. Disabling them when no heavy graphics processing is needed can significantly lower the power consumption. == Technologies == === Nvidia Optimus === Nvidia Optimus™ is a computer GPU switching technology created by Nvidia that can dynamically and seamlessly switch between two graphic cards based on running programs. === AMD Enduro === AMD Enduro™ is a collective brand developed by AMD that features many new technologies that can significantly save power. It was previously named as: PowerXpress and Dynamic Switchable Graphics (DSG). This technology implements a sophisticated system to predict the potential usage need for graphics cards and switch between graphics cards based on predicted need. This technology also introduces a new power control plan that allows the discrete graphics cards consume no energy when idling. == Manufacturers == === Integrated graphics === In personal computers, the IGP (integrated graphics processors) are mostly manufactured by Intel and AMD and are integrated onto their CPUs. They are commonly known as: Intel HD and Iris Graphics - also called HD series and Iris series AMD Accelerated Processing Unit (APU) - also formerly known as: fusion === Dedicated graphics cards === The most popular dedicated graphics cards are manufactured by AMD and Nvidia. They are commonly known as: AMD Radeon Nvidia GeForce == Drivers and OS support == Most common operating systems have built-in support for this feature. However, the users may download the updated drivers from Nvidia or AMD for better experience. === Windows support === Windows 7 has built-in support for this feature. The system automatically switches between GPUs depending on the program that's running. However, the user may switch the GPUs manually through device manager or power manager. === Linux === Modern Linux systems handle hybrid graphics in two parts: power/control for the inactive GPU, and optional render offloading for individual applications. vga_switcheroo (in the kernel since 2.6.34) coordinates power and mux control on systems with multiple GPUs. It was designed primarily for muxed designs (hardware display switch), and on muxless laptops it is typically used only for power control. A display server restart is no longer required for offloading on muxless systems. DRI PRIME (Mesa) enables per-process render offload on muxless systems: an app renders on the discrete GPU and the integrated GPU presents the result. Users can opt in via the DRI_PRIME environment variable (e.g., DRI_PRIME=1) or desktop integration. On GNOME, the switcheroo-control service exposes the discrete GPU to the shell, adding a “Launch using Discrete Graphics Card” entry to app menus on supported systems (Wayland or Xorg), which invokes render offload under the hood. With the proprietary Nvidia driver, render offload is provided as PRIME Render Offload (supported since driver 435.xx). Distributions commonly ship a helper like prime-run or desktop menu entries that set the required environment for offloading. ==== Notes and limitations (Linux) ==== On muxless systems the internal display is hard-wired to the integrated GPU; the discrete GPU cannot directly drive that panel and instead renders offscreen for composition by the iGPU. External displays connected to the dGPU may allow direct output depending on the laptop’s wiring. Power-saving behavior varies by driver and distro defaults. Some setups need explicit configuration to power down the inactive GPU when idle. Desktop integrations (e.g., GNOME's menu item) simply opt an app into offload; they do not "auto-switch" the whole session. Users can still launch apps on either GPU as needed.

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  Color balance

  In photography and image processing, color balance is the global adjustment of the intensities of the colors (typically red, green, and blue primary colors). An important goal of this adjustment is to render specific colors – particularly neutral colors like white or grey – correctly. Hence, the general method is sometimes called gray balance, neutral balance, or white balance. Color balance changes the overall mixture of colors in an image and is used for color correction. Generalized versions of color balance are used to correct colors other than neutrals or to deliberately change them for effect. White balance is one of the most common kinds of balancing, and is when colors are adjusted to make a white object (such as a piece of paper or a wall) appear white and not a shade of any other colour. Image data acquired by sensors – either film or electronic image sensors – must be transformed from the acquired values to new values that are appropriate for color reproduction or display. Several aspects of the acquisition and display process make such color correction essential – including that the acquisition sensors do not match the sensors in the human eye, that the properties of the display medium must be accounted for, and that the ambient viewing conditions of the acquisition differ from the display viewing conditions. The color balance operations in popular image editing applications usually operate directly on the red, green, and blue channel pixel values, without respect to any color sensing or reproduction model. In film photography, color balance is typically achieved by using color correction filters over the lights or on the camera lens. == Generalized color balance == Sometimes the adjustment to keep neutrals neutral is called white balance, and the phrase color balance refers to the adjustment that in addition makes other colors in a displayed image appear to have the same general appearance as the colors in an original scene. It is particularly important that neutral (gray, neutral, white) colors in a scene appear neutral in the reproduction. === Psychological color balance === Humans relate to flesh tones more critically than other colors. Trees, grass and sky can all be off without concern, but if human flesh tones are 'off' then the human subject can look sick or dead. To address this critical color balance issue, the tri-color primaries themselves are formulated to not balance as a true neutral color. The purpose of this color primary imbalance is to more faithfully reproduce the flesh tones through the entire brightness range. == Illuminant estimation and adaptation == Most digital cameras have means to select color correction based on the type of scene lighting, using either manual lighting selection, automatic white balance, or custom white balance. The algorithms for these processes perform generalized chromatic adaptation. Many methods exist for color balancing. Setting a button on a camera is a way for the user to indicate to the processor the nature of the scene lighting. Another option on some cameras is a button which one may press when the camera is pointed at a gray card or other neutral colored object. This captures an image of the ambient light, which enables a digital camera to set the correct color balance for that light. There is a large literature on how one might estimate the ambient lighting from the camera data and then use this information to transform the image data. A variety of algorithms have been proposed, and the quality of these has been debated. A few examples and examination of the references therein will lead the reader to many others. Examples are Retinex, an artificial neural network or a Bayesian method. == Chromatic colors == Color balancing an image affects not only the neutrals, but other colors as well. An image that is not color balanced is said to have a color cast, as everything in the image appears to have been shifted towards one color. Color balancing may be thought in terms of removing this color cast. Color balance is also related to color constancy. Algorithms and techniques used to attain color constancy are frequently used for color balancing, as well. Color constancy is, in turn, related to chromatic adaptation. Conceptually, color balancing consists of two steps: first, determining the illuminant under which an image was captured; and second, scaling the components (e.g., R, G, and B) of the image or otherwise transforming the components so they conform to the viewing illuminant. Viggiano found that white balancing in the camera's native RGB color model tended to produce less color inconstancy (i.e., less distortion of the colors) than in monitor RGB for over 4000 hypothetical sets of camera sensitivities. This difference typically amounted to a factor of more than two in favor of camera RGB. This means that it is advantageous to get color balance right at the time an image is captured, rather than edit later on a monitor. If one must color balance later, balancing the raw image data will tend to produce less distortion of chromatic colors than balancing in monitor RGB. == Mathematics of color balance == Color balancing is sometimes performed on a three-component image (e.g., RGB) using a 3x3 matrix. This type of transformation is appropriate if the image was captured using the wrong white balance setting on a digital camera, or through a color filter. Changing the color balance of an image can improve classifier results on a trained ML model. === Scaling monitor R, G, and B === In principle, one wants to scale all relative luminances in an image so that objects which are believed to be neutral appear so. If, say, a surface with R = 240 {\displaystyle R=240} was believed to be a white object, and if 255 is the count which corresponds to white, one could multiply all red values by 255/240. Doing analogously for green and blue would result, at least in theory, in a color balanced image. In this type of transformation the 3x3 matrix is a diagonal matrix. [ R G B ] = [ 255 / R w ′ 0 0 0 255 / G w ′ 0 0 0 255 / B w ′ ] [ R ′ G ′ B ′ ] {\displaystyle \left[{\begin{array}{c}R\\G\\B\end{array}}\right]=\left[{\begin{array}{ccc}255/R'_{w}&0&0\\0&255/G'_{w}&0\\0&0&255/B'_{w}\end{array}}\right]\left[{\begin{array}{c}R'\\G'\\B'\end{array}}\right]} where R {\displaystyle R} , G {\displaystyle G} , and B {\displaystyle B} are the color balanced red, green, and blue components of a pixel in the image; R ′ {\displaystyle R'} , G ′ {\displaystyle G'} , and B ′ {\displaystyle B'} are the red, green, and blue components of the image before color balancing, and R w ′ {\displaystyle R'_{w}} , G w ′ {\displaystyle G'_{w}} , and B w ′ {\displaystyle B'_{w}} are the red, green, and blue components of a pixel which is believed to be a white surface in the image before color balancing. This is a simple scaling of the red, green, and blue channels, and is why color balance tools in Photoshop have a white eyedropper tool. It has been demonstrated that performing the white balancing in the phosphor set assumed by sRGB tends to produce large errors in chromatic colors, even though it can render the neutral surfaces perfectly neutral. === Scaling X, Y, Z === If the image may be transformed into CIE XYZ tristimulus values, the color balancing may be performed there. This has been termed a "wrong von Kries" transformation. Although it has been demonstrated to offer usually poorer results than balancing in monitor RGB, it is mentioned here as a bridge to other things. Mathematically, one computes: [ X Y Z ] = [ X w / X w ′ 0 0 0 Y w / Y w ′ 0 0 0 Z w / Z w ′ ] [ X ′ Y ′ Z ′ ] {\displaystyle \left[{\begin{array}{c}X\\Y\\Z\end{array}}\right]=\left[{\begin{array}{ccc}X_{w}/X'_{w}&0&0\\0&Y_{w}/Y'_{w}&0\\0&0&Z_{w}/Z'_{w}\end{array}}\right]\left[{\begin{array}{c}X'\\Y'\\Z'\end{array}}\right]} where X {\displaystyle X} , Y {\displaystyle Y} , and Z {\displaystyle Z} are the color-balanced tristimulus values; X w {\displaystyle X_{w}} , Y w {\displaystyle Y_{w}} , and Z w {\displaystyle Z_{w}} are the tristimulus values of the viewing illuminant (the white point to which the image is being transformed to conform to); X w ′ {\displaystyle X'_{w}} , Y w ′ {\displaystyle Y'_{w}} , and Z w ′ {\displaystyle Z'_{w}} are the tristimulus values of an object believed to be white in the un-color-balanced image, and X ′ {\displaystyle X'} , Y ′ {\displaystyle Y'} , and Z ′ {\displaystyle Z'} are the tristimulus values of a pixel in the un-color-balanced image. If the tristimulus values of the monitor primaries are in a matrix P {\displaystyle \mathbf {P} } so that: [ X Y Z ] = P [ L R L G L B ] {\displaystyle \left[{\begin{array}{c}X\\Y\\Z\end{array}}\right]=\mathbf {P} \left[{\begin{array}{c}L_{R}\\L_{G}\\L_{B}\end{array}}\right]} where L R {\displaystyle L_{R}} , L G {\displaystyle L_{G}} , and L B {\displaystyle L_{B}} are the un-gamma corrected monitor RGB, one may use: [ L R L G L B ] = P − 1 [ X w / X w ′ 0 0

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  Static web page

  A static web page, sometimes called a flat page or a stationary page, is a web page that is delivered to a web browser exactly as stored, in contrast to dynamic web pages which are generated by a web application. Consequently, a static web page displays the same information for all users, from all contexts, subject to modern capabilities of a web server to negotiate content-type or language of the document where such versions are available and the server is configured to do so. However, a webpage's JavaScript can introduce dynamic functionality which may make the static web page dynamic. == Overview == Static web pages are often HTML documents, stored as files in the file system and made available by the web server over HTTP (nevertheless URLs ending with ".html" are not always static). However, loose interpretations of the term could include web pages stored in a database, and could even include pages formatted using a template and served through an application server, as long as the page served is unchanging and presented essentially as stored. The content of static web pages remains stationary irrespective of the number of times it is viewed. Such web pages are suitable for the contents that rarely need to be updated, though modern web template systems are changing this. Maintaining large numbers of static pages as files can be impractical without automated tools, such as static site generators. Any personalization or interactivity has to run client-side, which is restricting. Cloud-based website builders, including Wix, Weebly, and Duda, offer no-code platforms for creating static and dynamic web pages through graphical interfaces, without requiring programming expertise. === Advantages === Provide improved security over dynamic websites (dynamic websites are at risk to web shell attacks if a vulnerability is present) Improved performance for end users compared to dynamic websites Fewer or no dependencies on systems such as databases or other application servers Cost savings from utilizing cloud storage, as opposed to a hosted environment Security configurations are easy to set up, which makes it more secure Static files can be cached by content delivery networks (CDNs) and other intermediate caches, which both reduces page load times at the user and also reduces load on the origin server. Static websites can have improved uptime, since they are still available through any available CDN exit node even when other CDN nodes or the origin webserver are temporarily offline. === Disadvantages === Dynamic functionality must be performed on the client side. After each update of a static website, some or all users may see old, stale, outdated previous versions instead of the latest version until the old version is flushed from CDNs and other caches. == Static site generators == Static site generators are applications that compile static websites - typically populating HTML templates in a predefined folder and file structure, with content supplied in a format such as Markdown or AsciiDoc. === Implementations === Jekyll (powers GitHub Pages) Middleman Hugo Next.js Astro.build Pelican Franklin

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  Temporal resolution

  Temporal resolution (TR) refers to the discrete resolution of a measurement with respect to time. It is defined as the amount of time needed to revisit and acquire data for the same location. When applied to remote sensing, this amount of time is influenced by the sensor platform's orbital characteristics and the features of the sensor itself. The temporal resolution is low when the revisiting delay is high and vice versa. Temporal resolution is typically expressed in days. == Physics == Often there is a trade-off between the temporal resolution of a measurement and its spatial resolution, due to Heisenberg's uncertainty principle. In some contexts, such as particle physics, this trade-off can be attributed to the finite speed of light and the fact that it takes a certain period of time for the photons carrying information to reach the observer. In this time, the system might have undergone changes itself. Thus, the longer the light has to travel, the lower the temporal resolution. == Technology == === Computing === In another context, there is often a tradeoff between temporal resolution and computer storage. A transducer may be able to record data every millisecond, but available storage may not allow this, and in the case of 4D PET imaging the resolution may be limited to several minutes. === Electronic displays === In some applications, temporal resolution may instead be equated to the sampling period, or its inverse, the refresh rate, or update frequency in Hertz, of a TV, for example. The temporal resolution is distinct from temporal uncertainty. This would be analogous to conflating image resolution with optical resolution. One is discrete, the other, continuous. The temporal resolution is a resolution somewhat the 'time' dual to the 'space' resolution of an image. In a similar way, the sample rate is equivalent to the pixel pitch on a display screen, whereas the optical resolution of a display screen is equivalent to temporal uncertainty. Note that both this form of image space and time resolutions are orthogonal to measurement resolution, even though space and time are also orthogonal to each other. Both an image or an oscilloscope capture can have a signal-to-noise ratio, since both also have measurement resolution. === Oscilloscopy === An oscilloscope is the temporal equivalent of a microscope, and it is limited by temporal uncertainty the same way a microscope is limited by optical resolution. A digital sampling oscilloscope has also a limitation analogous to image resolution, which is the sample rate. A non-digital non-sampling oscilloscope is still limited by temporal uncertainty. The temporal uncertainty can be related to the maximum frequency of continuous signal the oscilloscope could respond to, called the bandwidth and given in Hertz. But for oscilloscopes, this figure is not the temporal resolution. To reduce confusion, oscilloscope manufacturers use 'Sa/s' instead of 'Hz' to specify the temporal resolution. Two cases for oscilloscopes exist: either the probe settling time is much shorter than the real time sampling rate, or it is much larger. The case where the settling time is the same as the sampling time is usually undesirable in an oscilloscope. It is more typical to prefer a larger ratio either way, or if not, to be somewhat longer than two sample periods. In the case where it is much longer, the most typical case, it dominates the temporal resolution. The shape of the response during the settling time also has as strong effect on the temporal resolution. For this reason probe leads usually offer an arrangement to 'compensate' the leads to alter the trade off between minimal settling time, and minimal overshoot. If it is much shorter, the oscilloscope may be prone to aliasing from radio frequency interference, but this can be removed by repeatedly sampling a repetitive signal and averaging the results together. If the relationship between the 'trigger' time and the sample clock can be controlled with greater accuracy than the sampling time, then it is possible to make a measurement of a repetitive waveform with much higher temporal resolution than the sample period by upsampling each record before averaging. In this case the temporal uncertainty may be limited by clock jitter.

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  HTTP cookie

  An HTTP cookie (also called web cookie, Internet cookie, browser cookie, or simply cookie) is a small block of data created by a web server while a user is browsing a website and placed on the user's computer or other device by the user's web browser. Cookies are placed on the device used to access a website, and more than one cookie may be placed on a user's device during a session. Cookies serve useful and sometimes essential functions on the web. They enable web servers to store stateful information (such as items added in the shopping cart in an online store) on the user's device or to track the user's browsing activity (including clicking particular buttons, logging in, or recording which pages were visited in the past). They can also be used to save information that the user previously entered into form fields, such as names, addresses, passwords, and payment card numbers for subsequent use. Authentication cookies are commonly used by web servers to authenticate that a user is logged in, and with which account they are logged in. Without the cookie, users would need to authenticate themselves by logging in on each page containing sensitive information that they wish to access. The security of an authentication cookie generally depends on the security of the issuing website and the user's web browser, and on whether the cookie data is encrypted. Security vulnerabilities may allow a cookie's data to be read by an attacker, used to gain access to user data, or used to gain access (with the user's credentials) to the website to which the cookie belongs (see cross-site scripting and cross-site request forgery for examples). Tracking cookies, and especially third-party tracking cookies, are commonly used as ways to compile long-term records of individuals' browsing histories — a potential privacy concern that prompted European and U.S. lawmakers to take action in 2011. European law requires that all websites targeting European Union member states gain "informed consent" from users before storing non-essential cookies on their device. == Background == === Origin of the name === The term cookie was coined by web-browser programmer Lou Montulli. It was derived from the term magic cookie, which is a packet of data a program receives and sends back unchanged, used by Unix programmers. === History === Magic cookies were already used in computing when computer programmer Lou Montulli had the idea of using them in web communications in June 1994. At the time, he was an employee of Netscape Communications, which was developing an e-commerce application for MCI. Vint Cerf and John Klensin represented MCI in technical discussions with Netscape Communications. MCI did not want its servers to have to retain partial transaction states, which led them to ask Netscape to find a way to store that state in each user's computer instead. Cookies provided a solution to the problem of reliably implementing a virtual shopping cart. Together with John Giannandrea, Montulli wrote the initial Netscape cookie specification the same year. Version 0.9beta of Mosaic Netscape, released on 13 October 1994, supported cookies. The first use of cookies (out of the labs) was checking whether visitors to the Netscape website had already visited the site. Montulli applied for a patent for the cookie technology in 1995, which was granted in 1998. Support for cookies was integrated with Internet Explorer in version 2, released in October 1995. The introduction of cookies was not widely known to the public at the time. In particular, cookies were accepted by default, and users were not notified of their presence. The public learned about cookies after the Financial Times published an article about them on 12 February 1996. In the same year, cookies received a lot of media attention, especially because of potential privacy implications. Cookies were discussed in two U.S. Federal Trade Commission hearings in 1996 and 1997. The development of the formal cookie specifications was already ongoing. In particular, the first discussions about a formal specification started in April 1995 on the www-talk mailing list. A special working group within the Internet Engineering Task Force (IETF) was formed. Two alternative proposals for introducing state in HTTP transactions had been proposed by Brian Behlendorf and David Kristol respectively. But the group, headed by Kristol himself and Lou Montulli, soon decided to use the Netscape specification as a starting point. In February 1996, the working group identified third-party cookies as a considerable privacy threat. The specification produced by the group was eventually published as RFC 2109 in February 1997. It specifies that third-party cookies were either not allowed at all, or at least not enabled by default. At this time, advertising companies were already using third-party cookies. The recommendation about third-party cookies of RFC 2109 was not followed by Netscape and Internet Explorer. RFC 2109 was superseded by RFC 2965 in October 2000. RFC 2965 added a Set-Cookie2 header field, which informally came to be called "RFC 2965-style cookies" as opposed to the original Set-Cookie header field which was called "Netscape-style cookies". Set-Cookie2 was seldom used, however, and was deprecated in RFC 6265 in April 2011 which was written as a definitive specification for cookies as used in the real world. No modern browser recognizes the Set-Cookie2 header field. == Terminology == === Session cookie === A session cookie (also known as an in-memory cookie, transient cookie or non-persistent cookie) exists only in temporary memory while the user navigates a website. Session cookies expire or are deleted when the user closes the web browser. Session cookies are identified by the browser by the absence of an expiration date assigned to them. === Persistent cookie === A persistent cookie expires at a specific date or after a specific length of time. For the persistent cookie's lifespan set by its creator, its information will be transmitted to the server every time the user visits the website that it belongs to, or every time the user views a resource belonging to that website from another website (such as an advertisement). For this reason, persistent cookies are sometimes referred to as tracking cookies because they can be used by advertisers to record information about a user's web browsing habits over an extended period of time. Persistent cookies are also used for reasons such as keeping users logged into their accounts on websites, to avoid re-entering login credentials at every visit. (See § Uses, below.) === Secure cookie === A secure cookie can only be transmitted over an encrypted connection (i.e. HTTPS). They cannot be transmitted over unencrypted connections (i.e. HTTP). This makes the cookie less likely to be exposed to cookie theft via eavesdropping. A cookie is made secure by adding the Secure flag to the cookie. === Http-only cookie === An http-only cookie cannot be accessed by client-side APIs, such as JavaScript. This restriction eliminates the threat of cookie theft via cross-site scripting (XSS). However, the cookie remains vulnerable to cross-site tracing (XST) and cross-site request forgery (CSRF) attacks. A cookie is given this characteristic by adding the HttpOnly flag to the cookie. === Same-site cookie === In 2016 Google Chrome version 51 introduced a new kind of cookie with attribute SameSite with possible values of Strict, Lax or None. With attribute SameSite=Strict, the browsers would only send cookies to a target domain that is the same as the origin domain. This would effectively mitigate cross-site request forgery (CSRF) attacks. With SameSite=Lax, browsers would send cookies with requests to a target domain even it is different from the origin domain, but only for safe requests such as GET (POST is unsafe) and not third-party cookies (inside iframe). Attribute SameSite=None would allow third-party (cross-site) cookies, however, most browsers require secure attribute on SameSite=None cookies. The Same-site cookie is incorporated into a new RFC draft for "Cookies: HTTP State Management Mechanism" to update RFC 6265 (if approved). Chrome, Firefox, and Edge started to support Same-site cookies. The key of rollout is the treatment of existing cookies without the SameSite attribute defined, Chrome has been treating those existing cookies as if SameSite=None, this would let all website/applications run as before. Google intended to change that default to SameSite=Lax in Chrome 80 planned to be released in February 2020, but due to potential for breakage of those applications/websites that rely on third-party/cross-site cookies and COVID-19 circumstances, Google postponed this change to Chrome 84. === Supercookie === A supercookie is a cookie with an origin of a top-level domain (such as .com) or a public suffix (such as .co.uk). Ordinary cookies, by contrast, have an origin of a specific domain name, such as ex

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  Butler in a Box

  Butler in a Box was an early voice-controlled home automation device developed in 1983 by magician Gus Searcy and programmer Franz Kavan. The device allowed users to control various home electronics, such as lights and phones, using voice commands. It predated modern smart speakers and virtual assistants by several decades. == History == The idea for the Butler in a Box originated in 1983 when Searcy was asked by friends why he couldn't simply command lights to turn on and off if he could pull rabbits out of hats, given his background as a professional magician. Searcy partnered with former IBM programmer Kavan to develop the device, with their first prototype being named "Sidney". The Butler in a Box combined remote control technology with voice recognition to enable control of home devices. However, it faced challenges due to the technological limitations of the era and its high price point of nearly $1,500 (equivalent to around $3,700 in 2021). == Features and functionality == Users could activate the Butler in a Box by speaking a wake word, typically a traditional butler name, and the device would address the user as "boss". It was capable of performing tasks such as: Turning lights on and off, controlling individual zones if lights were connected to remote control modules Making and receiving phone calls Setting timers Pairing with sensors to function as a security alarm system However, the device required extensive voice training for each user, a time-consuming process compared to modern voice recognition. Additionally, settings and trained commands would be lost if power was out for over 3 hours due to the volatile memory technology used at the time. == Reception and legacy == While innovative for its time, the Butler in a Box did not achieve widespread commercial success due to its high price and the technical limitations of the 1980s. Nevertheless, it served as an important early step in the development of home automation and showcased the potential for voice-controlled technology to enhance accessibility and convenience in the home. Decades later, products like Amazon Alexa, Google Home, and Apple's Siri would make voice-controlled smart home devices commonplace and affordable, building on the groundwork laid by early attempts like the Butler in a Box.

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  Gnowit

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

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  Bainu (website)

  Bainu ("how are you?") is a Chinese social networking website written in the Mongolian language. As of 2020 it had about 400,000 users, concentrated in Inner Mongolia. == Core features and positioning == Language and Cultural Characteristics Bainu is based on Traditional Mongolian Script and supports social interactions in the Mongolian language, including various message formats such as text, voice, images, and video. This design aims to preserve and promote Mongolian language and culture, particularly appealing to users in Inner Mongolia and other Mongolian-populated areas. Social Features Instant Messaging: Supports one-on-one private chats and group chats. Users can create interest-based groups or join local communities. Life Sharing: Through the "Chomorlig" feature (similar to Moments or a dynamic feed), users can share daily highlights to enhance community interaction. Location-Based Socializing: Recommends nearby users based on location, making it easier to connect with Mongolian friends in the same city or neighboring regions. Multilingual Support The app interface is available in English, Mongolian, and Simplified Chinese. == Technical Features and User Experience == Cross-Platform Compatibility Supports iPhone, iPad, Mac (with M1 chip or above), and Apple Vision Pro devices, covering users across the Apple ecosystem. Pricing Model Free download and basic features are available. Premium services (e.g., ad-free experience, extended social functions) require a subscription, with pricing options including $0.99/month, $2.99/quarter, and $6.99/year. User Feedback Positive Reviews: Some users praise it as the "best Mongolian-language chat app," recognizing its cultural value and social convenience. Negative Feedback: Reports of app crashes and technical issues, with some users calling for improved stability (e.g., frequent crashes in the iOS version). == Privacy and Data Policy == Bainu collects user data such as location, contact information, and device identifiers, which are linked to user identities. Additionally, user behavior may be tracked through third-party services, raising some privacy concerns. == Current Development and Challenges == User Base As of 2020, Bainu had approximately 400,000 users, primarily concentrated in Inner Mongolia. Policy Impact It was reported by Voice of America (VOA) that the Chinese authorities blocked Bainu on 23 August 2020 in order to prohibit Mongolians from discussing the issue of the authorities’ implementation of "bilingual education" in elementary schools. But now, in 2025, this software is completely available for download and use. see:https://bainu.com/

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