AI Coding Claude

AI Coding Claude — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

Realization (linguistics)

In linguistics, realization is the process by which some kind of surface representation is derived from its underlying representation; that is, the way in which some abstract object of linguistic analysis comes to be produced in actual language. Phonemes are often said to be realized by speech sounds. The different sounds that can realize a particular phoneme are called its allophones. Realization is also a subtask of natural language generation, which involves creating an actual text in a human language (English, French, etc.) from a syntactic representation. There are a number of software packages available for realization, most of which have been developed by academic research groups in NLG. The remainder of this article concerns realization of this kind. == Example == For example, the following Java code causes the simplenlg system [2] to print out the text The women do not smoke.: In this example, the computer program has specified the linguistic constituents of the sentence (verb, subject), and also linguistic features (plural subject, negated), and from this information the realiser has constructed the actual sentence. == Processing == Realisation involves three kinds of processing: Syntactic realisation: Using grammatical knowledge to choose inflections, add function words and also to decide the order of components. For example, in English the subject usually precedes the verb, and the negated form of smoke is do not smoke. Morphological realisation: Computing inflected forms, for example the plural form of woman is women (not womans). Orthographic realisation: Dealing with casing, punctuation, and formatting. For example, capitalising The because it is the first word of the sentence. The above examples are very basic, most realisers are capable of considerably more complex processing. == Systems == A number of realisers have been developed over the past 20 years. These systems differ in terms of complexity and sophistication of their processing, robustness in dealing with unusual cases, and whether they are accessed programmatically via an API or whether they take a textual representation of a syntactic structure as their input. There are also major differences in pragmatic factors such as documentation, support, licensing terms, speed and memory usage, etc. It is not possible to describe all realisers here, but a few of the emerging areas are: Simplenlg [3]: a document realizing engine with an api which intended to be simple to learn and use, focused on limiting scope to only finding the surface area of a document. KPML [4]: this is the oldest realiser, which has been under development under different guises since the 1980s. It comes with grammars for ten different languages. FUF/SURGE [5]: a realiser which was widely used in the 1990s, and is still used in some projects today OpenCCG [6]: an open-source realiser which has a number of nice features, such as the ability to use statistical language models to make realisation decisions.
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Bioelectronics

Bioelectronics is a field of research in the convergence of biology and electronics. == Definitions == At the first C.E.C. Workshop, in Brussels in November 1991, bioelectronics was defined as 'the use of biological materials and biological architectures for information processing systems and new devices'. Bioelectronics, specifically bio-molecular electronics, were described as 'the research and development of bio-inspired (i.e. self-assembly) inorganic and organic materials and of bio-inspired (i.e. massive parallelism) hardware architectures for the implementation of new information processing systems, sensors and actuators, and for molecular manufacturing down to the atomic scale'. The National Institute of Standards and Technology (NIST), an agency of the United States Department of Commerce, defined bioelectronics in a 2009 report as "the discipline resulting from the convergence of biology and electronics". Sources for information about the field include the Institute of Electrical and Electronics Engineers (IEEE) with its Elsevier journal Biosensors and Bioelectronics published since 1990. The journal describes the scope of bioelectronics as seeking to : "... exploit biology in conjunction with electronics in a wider context encompassing, for example, biological fuel cells, bionics and biomaterials for information processing, information storage, electronic components and actuators. A key aspect is the interface between biological materials and micro and nano-electronics." == History == The first known study of bioelectronics took place in the 18th century when Italian physician-scientist Luigi Galvani applied a voltage to a pair of detached frog legs. The legs moved, sparking the genesis of bioelectronics. Electronics technology has been applied to biology and medicine since the pacemaker was invented and with the medical imaging industry. In 2009, a survey of publications using the term in title or abstract suggested that the center of activity was in Europe (43 percent), followed by Asia (23 percent) and the United States (20 percent). == Materials == Organic bioelectronics is the application of organic electronic material to the field of bioelectronics. Organic materials (i.e. containing carbon) show great promise when it comes to interfacing with biological systems. Current applications focus around neuroscience and infection. Conducting polymer coatings, an organic electronic material, shows massive improvement in the technology of materials. It was the most sophisticated form of electrical stimulation. It improved the impedance of electrodes in electrical stimulation, resulting in better recordings and reducing "harmful electrochemical side reactions." Organic Electrochemical Transistors (OECT) were invented in 1984 by Mark Wrighton and colleagues, which had the ability to transport ions. This improved signal-to-noise ratio and gives for low measured impedance. The Organic Electronic Ion Pump (OEIP), a device that could be used to target specific body parts and organs to adhere medicine, was created by Magnuss Berggren. As one of the few materials well established in CMOS technology, titanium nitride (TiN) turned out as exceptionally stable and well suited for electrode applications in medical implants. == Significant applications == Bioelectronics is used to help improve the lives of people with disabilities and diseases. For example, the glucose monitor is a portable device that allows diabetic patients to control and measure their blood sugar levels. Electrical stimulation used to treat patients with epilepsy, chronic pain, Parkinson's, deafness, Essential Tremor and blindness. Magnuss Berggren and colleagues created a variation of his OEIP, the first bioelectronic implant device that was used in a living, free animal for therapeutic reasons. It transmitted electric currents into GABA, an acid. A lack of GABA in the body is a factor in chronic pain. GABA would then be dispersed properly to the damaged nerves, acting as a painkiller. Vagus Nerve Stimulation (VNS) is used to activate the Cholinergic Anti-inflammatory Pathway (CAP) in the vagus nerve, ending in reduced inflammation in patients with diseases like arthritis. Since patients with depression and epilepsy are more vulnerable to having a closed CAP, VNS can aid them as well. At the same time, not all the systems that have electronics used to help improving the lives of people are necessarily bioelectronic devices, but only those which involve an intimate and directly interface of electronics and biological systems. Bioelectronics could be used to develop new label-free methods for monitoring cancer cell invasion and drug resistance. For example, the electrical resistance of cancer cells could be used to predict the effectiveness of cancer drugs and to identify drugs that are most likely to be effective against a particular type of cancer. === Human tissue regeneration === Human tissue, like most tissue in multicellular life, is known to be capable of regeneration. While tissue such as skin and even large organs such as the liver have been shown significant capacity for regeneration much of the adult body is thought to possess limited natural regenerative ability. Research in the field of regenerative medicine has identified that developmental bioelectricity can be used to stimulate and modify tissue growth beyond what naturally occurs with efforts to demonstrate its feasibility in mammals underway. Some researchers believe that future advancements could allow for the regeneration of organs or even entire limbs using bioelectronic devices providing the correct signals. == Future == The improvement of standards and tools to monitor the state of cells at subcellular resolutions is lacking funding and employment. This is a problem because advances in other fields of science are beginning to analyze large cell populations, increasing the need for a device that can monitor cells at such a level of sight. Cells cannot be used in many ways other than their main purpose, like detecting harmful substances. Merging this science with forms of nanotechnology could result in incredibly accurate detection methods. The preserving of human lives like protecting against bioterrorism is the biggest area of work being done in bioelectronics. Governments are starting to demand devices and materials that detect chemical and biological threats. The more the size of the devices decrease, there will be an increase in performance and capabilities.
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Radio network

A radio network is a system that distributes radio signals to multiple receivers or enables two-way communication between stations and mobile units. Worldwide, radio networks include broadcast networks, such as BBC Radio in the United Kingdom and NPR in the United States, which transmit one-to-many signals for news, entertainment, and public information; two-way radio networks, used by police, fire services, taxicabs, and delivery fleets for operational communication; and cellular networks, such as Verizon, Vodafone, and China Mobile, which provide mobile telephony and data services using frequency or time division duplexing. While all rely on radio-frequency technology like transmitters, receivers, and antennas, their network architectures, protocols, and regulatory frameworks differ substantially across applications and regions. The two-way type of radio network shares many of the same technologies and components as the broadcast-type radio network but is generally set up with fixed broadcast points (transmitters) with co-located receivers and mobile receivers/transmitters or transceivers. In this way both the fixed and mobile radio units can communicate with each other over broad geographic regions ranging in size from small single cities to entire states/provinces or countries. There are many ways in which multiple fixed transmit/receive sites can be interconnected to achieve the range of coverage required by the jurisdiction or authority implementing the system: conventional wireless links in numerous frequency bands, fibre-optic links, or microwave links. In all of these cases the signals are typically backhauled to a central switch of some type where the radio message is processed and resent (repeated) to all transmitter sites where it is required to be heard. In contemporary two-way radio systems, a concept called trunking is commonly used to achieve better efficiency of radio spectrum use. It provides a very wide range of coverage, with no switching of channels required by the mobile radio user as it roams throughout the system coverage. Trunking of two-way radio is identical to the concept used for cellular phone systems where each fixed and mobile radio is specifically identified to the system controller and its operation is switched by the controller. == Broadcasting networks == The broadcast type of radio network is a network system which distributes radio programming to multiple stations simultaneously, or slightly delayed, for the purpose of extending total coverage beyond the limits of a single broadcast signal. The resulting expanded audience for radio programming or information essentially applies the benefits of mass-production to the broadcasting enterprise. A radio network has two sales departments, one to package and sell programs to radio stations, and one to sell the audience of those programs to advertisers. Most radio networks also produce much of their programming. Originally, radio networks owned some or all of the stations that broadcast the network's radio format programming. Presently however, there are many networks that do not own any stations and only produce and/or distribute programming. Similarly station ownership does not always indicate network affiliation. A company might own stations in several different markets and purchase programming from a variety of networks. Radio networks rose rapidly with the growth of regular broadcasting of radio to home listeners in the 1920s. This growth took various paths in different places. In Britain the BBC was developed with public funding, in the form of a broadcast receiver license, and a broadcasting monopoly in its early decades. In contrast, in the United States various competing commercial broadcasting networks arose funded by advertising revenue. In that instance, the same corporation that owned or operated the network often manufactured and marketed the listener's radio. Major technical challenges to be overcome when distributing programs over long distances are maintaining signal quality and managing the number of switching/relay points in the signal chain. Early on, programs were sent to remote stations (either owned or affiliated) by various methods, including leased telephone lines, pre-recorded gramophone records and audio tape. The world's first all-radio, non-wireline network was claimed to be the Rural Radio Network, a group of six upstate New York FM stations that began operation in June 1948. Terrestrial microwave relay, a technology later introduced to link stations, has been largely supplanted by coaxial cable, fiber, and satellite, which usually offer superior cost-benefit ratios. Many early radio networks evolved into television networks.
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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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Tokken

Tokken is a payment system and mobile app most known for being a legal and secure option for businesses transactions within the cannabis industry, because of its compliance with bank requirements. The startup company was created by Lamine Zarrad, a former regulator at the Office of the Comptroller of the Currency. == Operability == In order for a person to start using the app, they need to provide evidence, in the form of bioidentification data and mobile carrier records, that they can legally purchase weed. After they have been verified, customers can pay directly through the app at any dispensary that is using Tokken. Tokken turns credit card transactions into a digital token, which can be exchanged back for money that can later be deposited into a bank account. All transactions are logged publicly through a blockchain leger, making the process both anonymous and verified. === Banking services === Tokken has a "pay taxes" function which enables dispensaries to pay their taxes directly to the department.
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Digital data

Digital data or digital information, in information theory and information systems, is data or information represented as a string of discrete symbols, each of which can take on one of only a finite number of values from some alphabet, such as letters or digits. An example is a text document, which consists of a string of alphanumeric characters. The most common form of digital data in modern information systems is binary data, which is represented by a string of binary digits (bits) each of which can have one of two values, either 0 or 1. Digital data can be contrasted with analog data, which is represented by a value from a continuous range of real numbers. Analog data is transmitted by an analog signal, which not only takes on continuous values but can vary continuously with time, a continuous real-valued function of time. An example is the air pressure variation in a sound wave. Data requires interpretation to become information. In modern (post-1960) computer systems, all data is digital. The word digital comes from the same source as the words digit and digitus (the Latin word for finger), as fingers are often used for counting. Mathematician George Stibitz of Bell Telephone Laboratories used the word digital in reference to the fast electric pulses emitted by a device designed to aim and fire anti-aircraft guns in 1942. The term is most commonly used in computing and electronics, especially where real-world information is converted to binary numeric form as in digital audio and digital photography. == Symbol to digital conversion == Since symbols (for example, alphanumeric characters) are not continuous, representing symbols digitally is rather simpler than conversion of continuous or analog information to digital. Instead of sampling and quantization as in analog-to-digital conversion, such techniques as polling and encoding are used. A symbol input device usually consists of a group of switches that are polled at regular intervals to see which switches are switched. Data will be lost if, within a single polling interval, two switches are pressed, or a switch is pressed, released, and pressed again. This polling can be done by a specialized processor in the device to prevent burdening the main CPU. When a new symbol has been entered, the device typically sends an interrupt, in a specialized format, so that the CPU can read it. For devices with only a few switches (such as the buttons on a joystick), the status of each can be encoded as bits (usually 0 for released and 1 for pressed) in a single word. This is useful when combinations of key presses are meaningful, and is sometimes used for passing the status of modifier keys on a keyboard (such as shift and control). But it does not scale to support more keys than the number of bits in a single byte or word. Devices with many switches (such as a computer keyboard) usually arrange these switches in a scan matrix, with the individual switches on the intersections of x and y lines. When a switch is pressed, it connects the corresponding x and y lines together. Polling (often called scanning in this case) is done by activating each x line in sequence and detecting which y lines then have a signal, thus which keys are pressed. When the keyboard processor detects that a key has changed state, it sends a signal to the CPU indicating the scan code of the key and its new state. The symbol is then encoded or converted into a number based on the status of modifier keys and the desired character encoding. A custom encoding can be used for a specific application with no loss of data. However, using a standard encoding such as ASCII is problematic if a symbol such as 'ß' needs to be converted but is not in the standard. It is estimated that in the year 1986, less than 1% of the world's technological capacity to store information was digital and in 2007 it was already 94%. The year 2002 is assumed to be the year when humankind was able to store more information in digital than in analog format (the "beginning of the digital age"). == States == Digital data come in these three states: data at rest, data in transit, and data in use. The confidentiality, integrity, and availability have to be managed during the entire lifecycle from 'birth' to the destruction of the data. === Data at rest === Data at rest in information technology means data that is housed physically on computer data storage in any digital form (e.g. cloud storage, file hosting services, databases, data warehouses, spreadsheets, archives, tapes, off-site or cloud backups, mobile devices etc.). Data at rest includes both structured and unstructured data. This type of data is subject to threats from hackers and other malicious threats to gain access to the data digitally or physical theft of the data storage media. To prevent this data from being accessed, modified or stolen, organizations will often employ security protection measures such as password protection, data encryption, or a combination of both. The security options used for this type of data are broadly referred to as data-at-rest protection (DARP). Definitions include: "...all data in computer storage while excluding data that is traversing a network or temporarily residing in computer memory to be read or updated." "...all data in storage but excludes any data that frequently traverses the network or that which resides in temporary memory. Data at rest includes but is not limited to archived data, data which is not accessed or changed frequently, files stored on hard drives, USB thumb drives, files stored on backup tape and disks, and also files stored off-site or on a storage area network (SAN)." While it is generally accepted that archive data (i.e. which never changes), regardless of its storage medium, is data at rest and active data subject to constant or frequent change is data in use. “Inactive data” could be taken to mean data which may change, but infrequently. The imprecise nature of terms such as “constant” and “frequent” means that some stored data cannot be comprehensively defined as either data at rest or in use. These definitions could be taken to assume that Data at Rest is a superset of data in use; however, data in use, subject to frequent change, has distinct processing requirements from data at rest, whether completely static or subject to occasional change. ==== Security ==== Because of its nature data at rest is of increasing concern to businesses, government agencies and other institutions. Mobile devices are often subject to specific security protocols to protect data at rest from unauthorized access when lost or stolen and there is an increasing recognition that database management systems and file servers should also be considered as at risk; the longer data is left unused in storage, the more likely it might be retrieved by unauthorized individuals outside the network. Data encryption, which prevents data visibility in the event of its unauthorized access or theft, is commonly used to protect data in motion and increasingly promoted for protecting data at rest. The encryption of data at rest should only include strong encryption methods such as AES or RSA. Encrypted data should remain encrypted when access controls such as usernames and password fail. Increasing encryption on multiple levels is recommended. Cryptography can be implemented on the database housing the data and on the physical storage where the databases are stored. Data encryption keys should be updated on a regular basis. Encryption keys should be stored separately from the data. Encryption also enables crypto-shredding at the end of the data or hardware lifecycle. Periodic auditing of sensitive data should be part of policy and should occur on scheduled occurrences. Finally, only store the minimum possible amount of sensitive data. Tokenization is a non-mathematical approach to protecting data at rest that replaces sensitive data with non-sensitive substitutes, referred to as tokens, which have no extrinsic or exploitable meaning or value. This process does not alter the type or length of data, which means it can be processed by legacy systems such as databases that may be sensitive to data length and type. Tokens require significantly less computational resources to process and less storage space in databases than traditionally encrypted data. This is achieved by keeping specific data fully or partially visible for processing and analytics while sensitive information is kept hidden. Lower processing and storage requirements makes tokenization an ideal method of securing data at rest in systems that manage large volumes of data. A further method of preventing unwanted access to data at rest is the use of data federation especially when data is distributed globally (e.g. in off-shore archives). An example of this would be a European organisation which stores its archived data off-site in the US. Under the terms of the USA PATRIOT Act the American authorities can demand
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Giditraffic

GidiTraffic (or GIDITRAFFIC) is an online social service started on 23 September 2011. Based primarily on social media, the service employs crowdsourcing as its primary means of providing real-time traffic updates to subscribers on its platform. The service, delivered free of charge, affords its users access to various types of information. Though its broadest category of users is road users and motorists, GIDITRAFFIC lends itself as a platform for answering inquiries from anyone who requires information on any subject of interest. GIDITRAFFIC's core competence is in vehicular traffic reports, however, the service also handles all other forms of traffic (going by the fact that the word traffic also means "the mutual exchange of information"). == Operation == Users of the service log on to its Twitter feed to get up-to-date traffic information or to post a general inquiry, which GIDITRAFFIC then publishes to all subscribers. Through crowdsourced replies, a requester receives numerous responses from other subscribers who have seen the question and can provide a relevant answer. In addition, updates are provided by subscribers to the platform via their mobile devices, thereby making the service effective in delivering traffic updates as they occur, and providing timely answers to other user inquiries. This informs GIDITRAFFIC's motto of "Lending each other an eye", alluding to the collaboration and cooperation between the platform's users in making the service indispensable to its users. == Reception == On Twitter, which is its primary platform, the service caters to over 1,800,000 subscribers, with the number increasing daily. The popularity of the platform stems from the fact that it not only keeps its subscribers abreast of the traffic situation in Lagos, the commercial capital city of Nigeria (well known for its many traffic jams), but users in other parts of the world. For a regular user of the platform, knowing where to avoid getting to a set destination in good time is well worth the two or three minutes it takes to access and scroll through the GIDITRAFFIC feed for updates. Another interesting aspect of this platform is the identity of the person behind it. The sustained anonymity of this individual has sparked many discussions centering on his or her possible identity. Online, GIDITRAFFIC continuously publishes traffic updates and user questions, while keeping up witty interactions with the platform's followers round the clock – adding to the mystery and persona of the GIDITRAFFIC owner. == Awards and recognition == In early 2012, GIDITRAFFIC received a nomination for a Shorty Award in the Life-Saving Hero category. Although this did not translate into a win, it brought recognition and wider exposure for the service from international news outlets such as the BBC, Washington Post. and New York Times. Back home in Nigeria, also in 2012, GIDITRAFFIC was honored with a Future Award for Best Use of New Media in recognition of the huge impact the service has had in terms of helping Lagos residents better manage time spent in traffic. == Mobile Applications == In 2012, GIDITRAFFIC partnered with telecommunications company Nokia to produce a downloadable mobile traffic application (the GIDITRAFFIC application, available for Nokia Asha phones on Nokia's online store). There are plans to extend the application to a wider range of mobile phone platforms. On 4 September 2013, the GIDITRAFFIC application for Nokia Lumia phones using Windows Phone 8 was launched on the Windows App Store.
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Feature detection (web development)

Feature detection (also feature testing) is a technique used in web development for handling differences between runtime environments (typically web browsers or user agents), by programmatically testing for clues that the environment may or may not offer certain functionality. This information is then used to make the application adapt in some way to suit the environment: to make use of certain APIs, or tailor for a better user experience. Its proponents claim it is more reliable and future-proof than other techniques like user agent sniffing and browser-specific CSS hacks. == Techniques == A feature test can take many forms. It is essentially any snippet of code which gives some level of confidence that a required feature is indeed supported. However, in contrast to other techniques, feature detection usually focuses on performing actions which directly relate to the feature to be detected, rather than heuristics. === JavaScript === JavaScript feature detection can inspect the DOM and the local JavaScript environment to test whether browser features or APIs are supported. The simplest technique is to check for the existence of a relevant object or property. For example, the Geolocation API (used for accessing the device's knowledge of its geographical location, possibly obtained from a GPS navigation device) exposes a geolocation property on the navigator object in the DOM; the presence of which implies the Geolocation API is supported: if ('geolocation' in navigator) { // Geolocation API is supported } For a higher level of confidence, some feature tests will attempt to invoke the feature then look for clues that it behaved properly. For example, a test for support for cookies might attempt to set a value as a cookie and then verify it can be read back. === CSS === In CSS, the at-rule @supports introduced in 2015 allows to test if a given feature is supported. For instance the following code activates the declarations only if the user agent supports display: flex: == Undetectables == Some browser features are considered undetectable, because no clues are known to give sufficient confidence that a feature is supported. These are often because of limited information available to the JavaScript environment in the browser; generally features must be exposed via the DOM in some way in order to be detectable using JavaScript. When undetectables are encountered, it is common to turn to user agent sniffing as an alternative mechanism, or to employ defensive coding to minimise the impact if the feature turns out not to be supported. The Modernizr project maintains a record of known undetectables on their wiki.
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Content as a service

Content as a service (CaaS) or managed content as a service (MCaaS) is a service-oriented model, where the service provider delivers the content on demand to the service consumer via web services that are licensed under subscription. The content is hosted by the service provider centrally in the cloud and offered to a number of consumers that need the content delivered into any applications or system, hence content can be demanded by the consumers as and when required. Content as a Service is a way to provide raw content (in other words, without the need for a specific human compatible representation, such as HTML) in a way that other systems can make use of it. Content as a Service is not meant for direct human consumption, but rather for other platforms to consume and make use of the content according to their particular needs. This happens usually on the cloud, with a centralized platform which can be globally accessible and provides a standard format for your content. With Content as a Service, you centralize your content into a single repository, where you can manage it, categorize it, make it available to others, search for it, or do whatever you wish with it. == Overview == The content delivered typically could be one or more of the following The technical terminology related to equipment or spares that is required to procure or design the materials The industrial terminology of the equipment or spares Technical values pertaining to various types, specifications, applications, characteristics of equipment or spares Sourcing information which will help in procurement or supply-chain management of equipment or spares Descriptive specifications of equipment or spares based on the product reference number or identifier UNSPSC codes or industry practiced classifications ISO, IEC compliant terminology Ontology or Technical Dictionary of products & services Predefined content for specific business needs The term "Content as a service" (CaaS) is considered to be part of the nomenclature of cloud computing service models & Service-oriented architecture along with Software as a service (SaaS), Infrastructure as a service (IaaS), and Platform as a service (PaaS).
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Are We Dating The Same Guy?

Are We Dating The Same Guy?, also abbreviated AWDTSG is a series of over 200 individual Facebook groups where women share dating profiles of men they matched with on dating networks to seek the opinion of other women who may have dated the same man in the past. The first group was created by Paola Sanchez and aimed at women living in the New York City environs. The groups have over 3.5 million members as of January 2024. The group's function is to post screenshots of a man's dating profile to that city's designated Facebook group, after which the poster asks "any tea?". Other users in the group will then share information about the man and share warnings. The groups are moderated by volunteers, and have been described as a feminist group. The groups have rules saying that personal information such as addresses must not be included in the Facebook posts. Users attempting to join the group are also examined to prevent fake profiles. The group is mainly for straight women. According to Vice, the men being posted about have no way to defend against accusations made about them, and on the other hand, posters cannot prove their stories unless backed up by others. Often times, members post pictures alongside personal information such as names, which may infringe on subjects' legal right to privacy. Lawyers have said these issues can lead to defamation lawsuits, and members can make false allegations and create fabricated stories. If members tell a man that he's been talked about on the group, the "snitch" will be banned and be "exposed to the whole group". == History == The first Are We Dating The Same Guy group was created by Paola Sanchez. The first group was created in March 2022 in New York City. A male counterpart, named "Are We Dating the Same Girl NYC" was created for New York, with mostly the same guidelines and rules to the original. When the original Are We Dating The Same Guy group found it, they denounced the new group. == Operations == Administrators are told not to respond to men asking to have posts about them removed, and to not remove said posts. The people being posted about have reported being questioned by their employers about things they have not done. Members of the groups sometimes criticise the physical appearance of the men being posted about. According to the Evening Standard, the groups "frequent[ly] mock" the appearance or dating profiles of the men who are posted about, despite being against the rules. For this behaviour, women are sometimes kicked out, or the group is disciplined en masse by admins. The groups have rules against hate towards men, but the rules can be difficult to enforce in large groups, with some having over 100,000 members. Some men have also been able to join the groups without being noticed. == Reception == In October 2023, Sera Bozza of Body+Soul wrote that consistently using Are We Dating The Same Guy can "affect your real-world view". She wrote that "A few stories of cheating may persuade you to believe that all men are unfaithful". Some lawyers and commentators have expressed concern that the groups fail to acknowledge the legal right to privacy and users can create false allegations and fabricated stories, and cyberbully men without them being able to defend themselves. This may lead to civil lawsuits against the author for defamation, harassment, and other related privacy torts. Netsafe, an online safety organisation in New Zealand, advises users of a similar group to familiarise themselves with the Harmful Digital Communications Act to ensure that posts do not lead to "harmful consequences". The Independent reported that men who have been posted on the dating groups have felt violated, and that even if reviewed positively by potentially thousands of strangers, the men being discussed about may have their reputation slightly decreased due to the association with being on the groups. The Independent also reported that some men believe that the groups are created to spread lies or mock them. Mashable reported that the growth of AWDTSG in recent years has led to the rise of a small industry of online reputation and content removal services, as increasing numbers of men seek assistance. A co-founder of Maximatic Media, one such agency offering these removal services, stated that many of the men contacting the firm do so in a state of panic after learning that allegations about them have circulated among tens of thousands of participants without their knowledge. Mashable similarly reported that the growing visibility of AWDTSG and similar platforms has contributed to what commentators describe as a "public trial" dynamic, where subjective accounts about dating behavior are interpreted as factual assessments and can influence a person's reputation among large audiences within their locale. The Oklahoman reported that anonymous, unverified claims in these groups have led some men to experience social and dating repercussions, although legal analysts argue that the benefits of community-based safety networks still outweigh these concerns in modern, app based dating environments. UTV/ITV News reportedly spoke to a man who was posted who alleged he attempted suicide, was clinically dead for three minutes, and spent three weeks in a psychiatric hospital as a result of the posts made about him. Many other men have talked about malicious false claims made about them. Self-described men’s rights activists have taken a dislike to these groups and have gotten multiple North American groups shut down by running campaigns, threatening lawsuits, and mass Facebook reporting. They also have Reddit communities dedicated to getting rid of such groups. Women who have posted in the groups have felt that they have put their safety at risk, with some having been confronted by the men they posted about. The group has been noted for exposing men who use dating apps while already in a relationship, misrepresent their ages, or repeatedly stand up the women they meet through apps, among other bad dating behaviors. For example, some members of the group had matched on a dating site with a man who had, several years prior, killed a stranger while having a mental break. After this information came to light, members of the group were warned. The group has also been noted to be complimentary of some men. == Lawsuits == In 2023, a 41-year-old man sued the administrators of the London group for $35,000 under defamation, alleging that the group "called names, accused of sending lewd photos and of being a bad parent". In January 2024 a man sued Meta, the owner of Facebook, along with Patreon, GoFundMe, and the AWDTSG website, as well as almost 30 group members due to alleged defamation, emotional distress, and invasion of privacy. Claiming that the groups violate anti-doxxing laws and do not fact check, seeking $75,000 in damages. He claims that the group shared fake images of him sending women texts containing harassment, his name and photo. His attorneys claim that if the images were real, they would fall under free speech in the First Amendment. By February, groups had raised $80,000. The Washington Post said that this case caused AWDTSG to "explode into public view". The case was dismissed in 2025 by the United States District Court for the Northern District of Illinois. On May 15, 2026, the United States Court of Appeals for the Seventh Circuit declined to renew the case in D'Ambrosio v. Meta Platforms Inc., et al. The plaintiff and his attorneys, Marc Trent and Aaron Walner of Trent Law Firm, were sanctioned "for frivolously appealing the dismissal of the claims," "misrepresentations of law," in connection with falsified citations included in the plaintiff's brief, and " disputing at oral argument without any evidentiary basis that [the plaintiff] client sent the text message she attributed to him." == By country == === Australia === In Australia, there are groups for multiple cities including Sydney, Melbourne, Adelaide, Perth, Brisbane and Rockhampton with many having several thousand members. The Sydney group has 30,000 members. In March 2023, the Adelaide version of the group, which had 7,000 members, was shut down. In 2024, groups titled "Sis, Are We Dating The Same Guy" stopped accepting new posts after an admin was sued for defamation and had to pay over AU$20,000 in legal fees. The case was settled out of court. The administrator announcing these closures cited a 2021 defamation High Court case involving detainee Dylan Voller, which led to the High Court saying that owners of Facebook groups can be held liable for defamatory comments, even if they did not know the comments had been made. === Canada === In 2023, a group was started for Ottawa. The founder previously was in a relationship full of "cheating and lies", which prompted her to creating the Facebook community. In 2023, the group for Vancouver and British Columbia was shut down after concerns about men being unable to protect themselves against fa
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Open Media Framework Interchange

Open Media Format (OMF), Open Media Framework, or Open Media Framework Interchange (OMFI), is a platform-independent file format intended for transfer of digital media between different software applications. OMFI is a file format that aids in exchange of digital media across applications and platforms. This framework enables users to import media elements and to edit information and effects summaries. Sequential media representation is the primary concern that is addressed by this format. The primary objective of OMFI is video production. However, there are a number of additional features which can be listed as follows: The origin of the data can be easily backtracked or identified since the import material is in the form of a videotape or film. There are predefined effects and transitions, which paves the way for easy and quick overlapping and sequencing of various track. The format supports motion control. (i.e. enabling a particular segment to play at a ratio of the speed of another segment) Some of the key benefits of OMFI are: It saves time by getting rid of tape-based file transfers. It brings in flexibility owing to its ability to use a number of applications on multiple workstations. The format preserves the best sound and picture quality during all imports. It eliminates the risk of file formatting and incompatibilities, which in turn allows users to spend their productive time on the creative aspects of their work. It preserves the formatting information during file transfers between applications or workstations. Hence, the need for rebuilding the effects and sequences is eliminated. The OMFI format consists of four primary sections namely Header, Object data, Object dictionary and Track data. The header contains an index of all the segments that constitute the file.
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Grid network

A grid network is a computer network consisting of a number of computer systems connected in a grid topology. In a regular grid topology, each node in the network is connected with two neighbors along one or more dimensions. If the network is one-dimensional, and the chain of nodes is connected to form a circular loop, the resulting topology is known as a ring. Network systems such as FDDI use two counter-rotating token-passing rings to achieve high reliability and performance. In general, when an n-dimensional grid network is connected circularly in more than one dimension, the resulting network topology is a torus, and the network is called "toroidal". When the number of nodes along each dimension of a toroidal network is 2, the resulting network is called a hypercube. A parallel computing cluster or multi-core processor is often connected in regular interconnection network such as a de Bruijn graph, a hypercube graph, a hypertree network, a fat tree network, a torus, or cube-connected cycles. A grid network is not the same as a grid computer or a computational grid, although the nodes in a grid network are usually computers, and grid computing requires some kind of computer network or "universal coding" to interconnect the computers.
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Wink Bingo

Wink Bingo is an online bingo website launched in 2008. It is part of Broadway Gaming Ireland DF Limited and is based and licensed in Ireland. == History == Wink Bingo launched in 2008 and under chief executive Eitan Boyd it grew to 60,000 active players within two years. It had an estimated £1.3 million profit in the first 11 months of trading, and by 2009 it had estimated annual revenue of £15 million. In 2009 Wink Bingo was purchased by 888 Holdings Plc, which operates a number of entertainment brands including 888casino, 888poker and 888sport. The initial up front fee was reported in the London Evening Standard to be £11 million, rising as high as £59.7 million depending on performance-based earn out arrangements. The acquisition included Daub Ltd’s other online bingo businesses Posh Bingo and Bingo Fabulous. In 2011, the sellers agreed to amend the terms and accept two subsequent payments in addition to the initial cost, of £9.2 million in May and £6.1 million in August. In 2011 Wink Bingo sponsored ITV2's The Only Way Is Essex, and other notable advertising campaigns have included sponsorship of Harry Hill's TV Burp. In 2014, Wink Bingo rebranded with an updated slogan 'Wink if you're in!', with an aim of creating a 'sunny, calm and inclusive' online destination, and an accompanying TV commercial featuring the Ottawan song D.I.S.C.O. re-recorded as B.I.N.G.O.. Wink also launched a new digital magazine, 'Winkly', and 'Winkipedia, a bingo encyclopedia'. Wink Bingo is available on desktop and as a mobile app. Wink launched Wink Slots in 2016 as a companion site to Wink Bingo. The Advertising Standards Authority has ruled on Wink Bingo's advertisements on a number of occasions. In August 2008, Wink ran a television ad which showed a midwife celebrating while at work at a hospital maternity unit. The ASA banned the ad, concluding that it condoned gambling in the workplace and suggested that it took priority over professional commitments. In June 2013, the Gambling Reform & Society Perception Group (GRASP) challenged the use of semi-naked "athletic" men together with the claim "Go on ... you know you want to" on an outdoor ad, suggesting it linked gambling to seduction and enhanced attractiveness. The complaint was not upheld. The site underwent another rebrand and pop art inspired redesign in April 2018, taking on a new tone of voice and a new slogan, "You’ve Earned It". An online shop was added, where players can redeem reward points for free play or vouchers for online high street retailers. In 2021 Wink Bingo was purchased by Saphalata Holdings, a company that forms part of the Broadway Gaming group. === Cancer Research UK campaign === In 2015 Wink Bingo began an open-ended partnership with the Peter Andre Fund to raise money for Cancer Research UK. Peter Andre also met with players who were selected in a raffle. == Awards ==
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Mean opinion score

Mean opinion score (MOS) is a measure used in the domain of Quality of Experience and telecommunications engineering, representing overall quality of a stimulus or system. It is the arithmetic mean over all individual "values on a predefined scale that a subject assigns to his opinion of the performance of a system quality". Such ratings are usually gathered in a subjective quality evaluation test, but they can also be algorithmically estimated. MOS is a commonly used measure for video, audio, and audiovisual quality evaluation, but not restricted to those modalities. ITU-T has defined several ways of referring to a MOS in Recommendation ITU-T P.800.1, depending on whether the score was obtained from audiovisual, conversational, listening, talking, or video quality tests. == Rating scales and mathematical definition == The MOS is expressed as a single rational number, typically in the range 1–5, where 1 is lowest perceived quality, and 5 is the highest perceived quality. Other MOS ranges are also possible, depending on the rating scale that has been used in the underlying test. The Absolute Category Rating scale is very commonly used, which maps ratings between Bad and Excellent to numbers between 1 and 5, as seen in below table. Other standardized quality rating scales exist in ITU-T Recommendations (such as ITU-T P.800 or ITU-T P.910). For example, one could use a continuous scale ranging between 1–100. Which scale is used depends on the purpose of the test. In certain contexts there are no statistically significant differences between ratings for the same stimuli when they are obtained using different scales. The MOS is calculated as the arithmetic mean over single ratings performed by human subjects for a given stimulus in a subjective quality evaluation test. Thus: M O S = ∑ n = 1 N R n N {\displaystyle MOS={\frac {\sum _{n=1}^{N}{R_{n}}}{N}}} Where R {\displaystyle R} are the individual ratings for a given stimulus by N {\displaystyle N} subjects. == Properties of the MOS == The MOS is subject to certain mathematical properties and biases. In general, there is an ongoing debate on the usefulness of the MOS to quantify Quality of Experience in a single scalar value. When the MOS is acquired using a categorical rating scales, it is based on – similar to Likert scales – an ordinal scale. In this case, the ranking of the scale items is known, but their interval is not. Therefore, it is mathematically incorrect to calculate a mean over individual ratings in order to obtain the central tendency; the median should be used instead. However, in practice and in the definition of MOS, it is considered acceptable to calculate the arithmetic mean. It has been shown that for categorical rating scales (such as ACR), the individual items are not perceived equidistant by subjects. For example, there may be a larger "gap" between Good and Fair than there is between Good and Excellent. The perceived distance may also depend on the language into which the scale is translated. However, there exist studies that could not prove a significant impact of scale translation on the obtained results. Several other biases are present in the way MOS ratings are typically acquired. In addition to the above-mentioned issues with scales that are perceived non-linearly, there is a so-called "range-equalization bias": subjects, over the course of a subjective experiment, tend to give scores that span the entire rating scale. This makes it impossible to compare two different subjective tests if the range of presented quality differs. In other words, the MOS is never an absolute measure of quality, but only relative to the test in which it has been acquired. For the above reasons – and due to several other contextual factors influencing the perceived quality in a subjective test – a MOS value should only be reported if the context in which the values have been collected in is known and reported as well. MOS values gathered from different contexts and test designs therefore should not be directly compared. Recommendation ITU-T P.800.2 prescribes how MOS values should be reported. Specifically, P.800.2 says:it is not meaningful to directly compare MOS values produced from separate experiments, unless those experiments were explicitly designed to be compared, and even then the data should be statistically analysed to ensure that such a comparison is valid. == MOS for speech and audio quality estimation == MOS historically originates from subjective measurements where listeners would sit in a "quiet room" and score a telephone call quality as they perceived it. This kind of test methodology had been in use in the telephony industry for decades and was standardized in Recommendation ITU-T P.800. It specifies that "the talker should be seated in a quiet room with volume between 30 and 120 m³ and a reverberation time less than 500 ms (preferably in the range 200–300 ms). The room noise level must be below 30 dBA with no dominant peaks in the spectrum." Requirements for other modalities were similarly specified in later ITU-T Recommendations. == MOS estimation using quality models == Obtaining MOS ratings may be time-consuming and expensive as it requires the recruitment of human assessors. For various use cases such as codec development or service quality monitoring purposes – where quality should be estimated repeatedly and automatically – MOS scores can also be predicted by objective quality models, which typically have been developed and trained using human MOS ratings. A question that arises from using such models is whether the MOS differences produced are noticeable to the users. For example, when rating images on a five point MOS scale, an image with a MOS equal to 5 is expected to be noticeably better in quality than one with a MOS equal to 1. Contrary to that, it is not evident whether an image with a MOS equal to 3.8 is noticeably better in quality than one with a MOS equal to 3.6. Research conducted on determining the smallest MOS difference that is perceptible to users for digital photographs showed that a MOS difference of approximately 0.46 is required in order for 75% of the users to be able to detect the higher quality image. Nevertheless, image quality expectation, and hence MOS, changes over time with the change of user expectations. As a result, minimum noticeable MOS differences determined using analytical methods such as in may change over time.
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Content creation

Content creation is the act of making and sharing media content, particularly in digital contexts. A content creator is the person or studio behind such content. According to Dictionary.com, content refers to "something that is to be expressed through some medium, as speech, writing or any of various arts" for self-expression, distribution, marketing and/or publication. Content creation encompasses various activities, including maintaining and updating web sites, blogging, article writing, photography, videography, online commentary, social media accounts, and editing and distribution of digital media. In a survey conducted by the Pew Research Center, the content thus created was defined as "the material people contribute to the online world". In addition to traditional forms of content creation, digital platforms face growing challenges related to privacy, copyright, misinformation, platform moderation policies, and the repercussions of violating community guidelines. == Content creators == Content creation is the process of producing and sharing various forms of content such as text, images, audio, and video, designed to engage and inform a specific audience. It plays a crucial role in digital marketing, branding, and online communication and brand awareness. Content can be created for a range of platforms, including social media, websites, blogs, and multimedia channels. Whether it's through written articles, compelling photography, or engaging videos, content creation helps businesses build a connection with their audience, increase visibility, and drive traffic. The process typically involves identifying the target audience, brainstorming ideas, creating the content, and distributing it across various channels. Successful content creation combines creativity with strategic planning, considering audience preferences, trends, and platform characteristics to achieve marketing and branding goals. === News organizations === News organizations, especially those with a large and global reach like The New York Times, NPR, and CNN, consistently create some of the most shared content on the Web, especially in relation to current events. In the words of a 2011 report from the Oxford School for the Study of Journalism and the Reuters Institute for the Study of Journalism, "Mainstream media is the lifeblood of topical social media conversations in the UK." While the rise of digital media has disrupted traditional news outlets, many have adapted and have begun to produce content that is designed to function on the web and be shared on social media. The social media site Twitter is a major distributor and aggregator of breaking news from various sources, and the function and value of Twitter in the distribution of news is a frequent topic of discussion and research in journalism. User-generated content, social media blogging and citizen journalism have changed the nature of news content in recent years. The company Narrative Science is now using artificial intelligence to produce news articles and interpret data. === Colleges, universities, and think tanks === Academic institutions, such as colleges and universities, create content in the form of books, journal articles, white papers, and some forms of digital scholarship, such as blogs that are group edited by academics, class wikis, or video lectures that support a massive open online course (MOOC). Through an open data initiative, institutions may make raw data supporting their experiments or conclusions available on the Web. Academic content may be gathered and made accessible to other academics or the public through publications, databases, libraries, and digital libraries. Academic content may be closed source or open access (OA). Closed-source content is only available to authorized users or subscribers. For example, an important journal or a scholarly database may be a closed source, available only to students and faculty through the institution's library. Open-access articles are open to the public, with the publication and distribution costs shouldered by the institution publishing the content. === Companies === Corporate content includes advertising and public relations content, as well as other types of content produced for profit, including white papers and sponsored research. Advertising can also include auto-generated content, with blocks of content generated by programs or bots for search engine optimization. Companies also create annual reports which are part of their company's workings and a detailed review of their financial year. This gives the stakeholders of the company insight into the company's current and future prospects and direction. === Artists and writers === Cultural works, like music, movies, literature, and art, are also major forms of content. Examples include traditionally published books and e-books as well as self-published books, digital art, fanfiction, and fan art. Independent artists, including authors and musicians, have found commercial success by making their work available on the Internet. === Government === Through digitization, sunshine laws, open records laws and data collection, governments may make statistical, legal or regulatory information available on the Internet. National libraries and state archives turn historical documents, public records, and unique relics into online databases and exhibits. This has raised significant privacy issues. In 2012, The Journal News, a New York state paper, sparked an outcry when it published an interactive map of the state's gun owner locations using legally obtained public records. Governments also create online or digital propaganda or misinformation to support domestic and international goals. This can include astroturfing, or using media to create a false impression of mainstream belief or opinion. Governments can also use open content, such as public records and open data, in service of public health, educational and scientific goals, such as crowdsourcing solutions to complex policy problems. In 2013, the National Aeronautics and Space Administration (NASA) joined the asteroid mining company Planetary Resources to crowdsource the hunt for near-Earth objects. Describing NASA's crowdsourcing work in an interview, technology transfer executive David Locke spoke of the "untapped cognitive surplus that exists in the world" which could be used to help develop NASA technology. In addition to making governments more participatory, open records and open data have the potential to make governments more transparent and less corrupt. === Users === The introduction of Web 2.0 made it possible for content consumers to be more involved in the generation and sharing of content. With the advent of digital media, the amount of user generated content, as well as the age and class range of users, has increased. 8% of Internet users are very active in content creation and consumption. Worldwide, about one in four Internet users are significant content creators, and users in emerging markets lead the world in engagement. Research has also found that young adults of a higher socioeconomic background tend to create more content than those from lower socioeconomic backgrounds. 69% of American and European internet users are "spectators", who consume—but do not create—online and digital media. The ratio of content creators to the amount of content they generate is sometimes referred to as the 1% rule, a rule of thumb that suggests that only 1% of a forum's users create nearly all of its content. Motivations for creating new content may include the desire to gain new knowledge, the possibility of publicity, or simple altruism. Users may also create new content in order to bring about social reforms. However, researchers caution that in order to be effective, context must be considered, a diverse array of people must be included, and all users must participate throughout the process. According to a 2011 study, minorities create content in order to connect with their communities online. African-American users have been found to create content as a means of self-expression that was not previously available. Media portrayals of minorities are sometimes inaccurate and stereotypical which affects the general perception of these minorities. African-Americans respond to their portrayals digitally through the use of social media such as Twitter and Tumblr. The creation of Black Twitter has allowed a community to share their problems and ideas. ==== Teens ==== Younger users now have greater access to content, content creating applications, and the ability to publish to different types of media, such as Facebook, Blogger, Instagram, DeviantArt, or Tumblr. As of 2005, around 21 million teens used the internet and 57%, or 12 million teens, consider themselves content creators. This proportion of media creation and sharing is higher than that of adults. With the advent of the Internet, teens have had more access to tools for sharing an
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