AI Data Jobs Near Me

AI Data Jobs Near Me — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

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  Productivity software

  Productivity software (also called personal productivity software or office productivity software) is application software used for producing information (such as documents, presentations, worksheets, databases, charts, graphs, digital paintings, electronic music and digital video). Its names arose from it increasing productivity, especially of individual office workers, from typists to knowledge workers, although its scope is now wider than that. Office suites, which brought word processing, spreadsheet, and relational database programs to the desktop in the 1980s, are the core example of productivity software. They revolutionized the office with the magnitude of the productivity increase they brought as compared with the pre-1980s office environments of typewriters, paper filing, and handwritten lists and ledgers. In the United States, as of 2015, some 78% of "middle-skill" occupations (those that call for more than a high school diploma but less than a bachelor's degree) required the use of productivity software. == Details == Productivity software traditionally runs directly on a computer. For example, Plus/4 model of computer contains in ROM for applications of productivity software. Productivity software is one of the reasons people use personal computers. == Office suite == An office suite is a bundle of productivity software (a software suite) intended to be used by office workers. The components are generally distributed together, have a consistent user interface and usually can interact with each other, sometimes in ways that the operating system would not normally allow. The earliest office suite for personal computers was MicroPro International's StarBurst in the early 1980s, comprising the WordStar word processor, the CalcStar spreadsheet and the DataStar database software. Other suites arose in the 1980s, and Microsoft Office came to dominate the market in the 1990s, a position it retains as of 2024. During the 1990s, office suite products gained popularity by offering bundles of applications that, when bought as part of a suite, effectively discounted the individual applications, with four or five applications being bundled for the price of two applications bought separately. When faced with such potential savings, customers could be "tempted by the suite, rather than the value of a particular product", and by 1994 more than 60 percent of the sales of Microsoft Word and around 70 percent of the sales of Microsoft Excel were as part of sales of Microsoft Office. Such considerations had an impact on vendors of individual applications, often smaller companies, raising concerns that office suites were "stifling innovation", and even established vendors such as Borland and WordPerfect were having to adapt to the suite phenomenon, Borland ultimately deciding to sell its Quattro Pro spreadsheet to WordPerfect as the latter sought to assemble its own suite product. The dominant suite vendors, Microsoft and Lotus, downplayed competition and innovation concerns, claiming that users were still able to exercise choice and that "user-driven development" was guiding the evolution of office suites. Another view was that component-based software would eventually emerge, focusing development on more specialised components used by productivity software, empowering "a plethora of third-party developers", and that a "mix and match" approach of such components would adapt to the user's way of working. === Office suite components === The base components of office suites are: Word processor Spreadsheet Presentation program Other components include: Database software Graphics suite (raster graphics editor, vector graphics editor, image viewer) Desktop publishing software Formula editor Diagramming software Email client Communication software Personal information manager Notetaking Groupware Project management software Table (information) Web log analysis software

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  Cryptovirology

  Cryptovirology refers to the study of cryptography use in malware, such as ransomware and asymmetric backdoors. Traditionally, cryptography and its applications are defensive in nature, and provide privacy, authentication, and security to users. Cryptovirology employs a twist on cryptography, showing that it can also be used offensively. It can be used to mount extortion based attacks that cause loss of access to information, loss of confidentiality, and information leakage, tasks which cryptography typically prevents. The field was born with the observation that public-key cryptography can be used to break the symmetry between what an antivirus analyst sees regarding malware and what the attacker sees. The antivirus analyst sees a public key contained in the malware, whereas the attacker sees the public key contained in the malware as well as the corresponding private key (outside the malware) since the attacker created the key pair for the attack. The public key allows the malware to perform trapdoor one-way operations on the victim's computer that only the attacker can undo. == Overview == The field encompasses covert malware attacks in which the attacker securely steals private information such as symmetric keys, private keys, PRNG state, and the victim's data. Examples of such covert attacks are asymmetric backdoors. An asymmetric backdoor is a backdoor (e.g., in a cryptosystem) that can be used only by the attacker, even after it is found. This contrasts with the traditional backdoor that is symmetric, i.e., anyone that finds it can use it. Kleptography, a subfield of cryptovirology, is the study of asymmetric backdoors in key generation algorithms, digital signature algorithms, key exchanges, pseudorandom number generators, encryption algorithms, and other cryptographic algorithms. The NIST Dual EC DRBG random bit generator has an asymmetric backdoor in it. The EC-DRBG algorithm utilizes the discrete-log kleptogram from kleptography, which by definition makes the EC-DRBG a cryptotrojan. Like ransomware, the EC-DRBG cryptotrojan contains and uses the attacker's public key to attack the host system. The cryptographer Ari Juels indicated that NSA effectively orchestrated a kleptographic attack on users of the Dual EC DRBG pseudorandom number generation algorithm and that, although security professionals and developers have been testing and implementing kleptographic attacks since 1996, "you would be hard-pressed to find one in actual use until now." Due to public outcry about this cryptovirology attack, NIST rescinded the EC-DRBG algorithm from the NIST SP 800-90 standard. Covert information leakage attacks carried out by cryptoviruses, cryptotrojans, and cryptoworms that, by definition, contain and use the public key of the attacker is a major theme in cryptovirology. In "deniable password snatching," a cryptovirus installs a cryptotrojan that asymmetrically encrypts host data and covertly broadcasts it. This makes it available to everyone, noticeable by no one (except the attacker), and only decipherable by the attacker. An attacker caught installing the cryptotrojan claims to be a virus victim. An attacker observed receiving the covert asymmetric broadcast is one of the thousands, if not millions of receivers, and exhibits no identifying information whatsoever. The cryptovirology attack achieves "end-to-end deniability." It is a covert asymmetric broadcast of the victim's data. Cryptovirology also encompasses the use of private information retrieval (PIR) to allow cryptoviruses to search for and steal host data without revealing the data searched for even when the cryptotrojan is under constant surveillance. By definition, such a cryptovirus carries within its own coding sequence the query of the attacker and the necessary PIR logic to apply the query to host systems. == History == The first cryptovirology attack and discussion of the concept was by Adam L. Young and Moti Yung, at the time called "cryptoviral extortion" and it was presented at the 1996 IEEE Security & Privacy conference. In this attack, a cryptovirus, cryptoworm, or cryptotrojan contains the public key of the attacker and hybrid encrypts the victim's files. The malware prompts the user to send the asymmetric ciphertext to the attacker who will decipher it and return the symmetric decryption key it contains for a fee. The victim needs the symmetric key to decrypt the encrypted files if there is no way to recover the original files (e.g., from backups). The 1996 IEEE paper predicted that cryptoviral extortion attackers would one day demand e-money, long before Bitcoin even existed. Many years later, the media relabeled cryptoviral extortion as ransomware. In 2016, cryptovirology attacks on healthcare providers reached epidemic levels, prompting the U.S. Department of Health and Human Services to issue a Fact Sheet on Ransomware and HIPAA. The fact sheet states that when electronic protected health information is encrypted by ransomware, a breach has occurred, and the attack therefore constitutes a disclosure that is not permitted under HIPAA, the rationale being that an adversary has taken control of the information. Sensitive data might never leave the victim organization, but the break-in may have allowed data to be sent out undetected. California enacted a law that defines the introduction of ransomware into a computer system with the intent of extortion as being against the law. == Examples == === Tremor virus === While viruses in the wild have used cryptography in the past, the only purpose of such usage of cryptography was to avoid detection by antivirus software. For example, the tremor virus used polymorphism as a defensive technique in an attempt to avoid detection by anti-virus software. Though cryptography does assist in such cases to enhance the longevity of a virus, the capabilities of cryptography are not used in the payload. The One-half virus was amongst the first viruses known to have encrypted affected files. === Tro_Ransom.A virus === An example of a virus that informs the owner of the infected machine to pay a ransom is the virus nicknamed Tro_Ransom.A. This virus asks the owner of the infected machine to send $10.99 to a given account through Western Union. Virus.Win32.Gpcode.ag is a classic cryptovirus. This virus partially uses a version of 660-bit RSA and encrypts files with many different extensions. It instructs the owner of the machine to email a given mail ID if the owner desires the decryptor. If contacted by email, the user will be asked to pay a certain amount as ransom in return for the decryptor. === CAPI === It has been demonstrated that using just 8 different calls to Microsoft's Cryptographic API (CAPI), a cryptovirus can satisfy all its encryption needs. == Other uses of cryptography-enabled malware == Apart from cryptoviral extortion, there are other potential uses of cryptoviruses, such as deniable password snatching, cryptocounters, private information retrieval, and in secure communication between different instances of a distributed cryptovirus.

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  Web presence

  A web presence is a location on the World Wide Web where a person, business, or some other entity is represented (see also web property and point of presence). Examples of a web presence for a person could be a personal website, a blog, a profile page, a wiki page, or a social media point of presence (e.g. a LinkedIn profile, a Facebook account, or a Twitter account). Examples of a web presence for a business or some other entity could be a corporate website, a microsite, a page on a review site, a wiki page, or a social media point of presence (e.g., a LinkedIn company page and/or group, a Facebook business/brand/product page, or a Twitter account). Every web presence is associated with a unique web address to distinguish one point of presence from another. == Owned vs. unowned == Web presence can either be owned or unowned. Owned media exists when a single person or group can control the content that is published on its web presence (e.g. a corporate website or a personal Twitter account). However, when a single person or group cannot solely control the content, the creator is different from the owner. This is considered unowned media (see earned media). A Wikipedia page or a Yelp page about a person, company, or product would be an example of a known (or "earned") web presence. Occasionally, a first form of media known as "paid media" is often included in the discussion of media types: "earned vs. owned vs. paid". Paid media is commonly found in the form of advertisements, but it is not considered a form of web presence. == Management == Web presence management is the process of establishing and maintaining a digital footprint on the web. The three factors that are considered include the following: where a person or business has web presence; how each web presence represents its enterprise; and what is published at a point of presence. Web presence management is the discipline of determining and governing: the distribution of policy documents which platforms are most appropriate (e.g. internal vs. external blog, YouTube vs. Vimeo) the single inventory of personal or corporate web presence (e.g. partners or advocates) where on the web a business and any relatable assets are represented where on the web a business and any relatable assets are impersonated or pirated web properties with the particular entities they represent who has control over which web properties new web properties which are not in the personal or corporate inventory (e.g. someone creates a new presence) authorized and unauthorized changes to the creation (e.g. branding) of a web presence a workflow for creating a web property that follows its corporate standards === Management system === The purpose of a web presence management system is to manage the web presence of a person or business. This includes the collection of domain names, websites, social media, and other web pages where he, she, or it is being represented. The tool generally offers the following key functions: new presence discovery, inventory management, change detection, access control, stakeholder coordination, and compliance workflow. A web presence management system is meant to have a broader reach so that it emphasizes where a presence has been established, will be established, must be maintained, or must be remediated. An example of a web presence management system is the Brandle Presence Manager. In order to publish content to the various points of web presence, multiple content management systems and sometimes even social media management systems are often used. The primary focus of most content and social media management systems is limited to their specific web platforms. === Domain names === Another aspect of web presence management is managing the collection of domain names registered to the person or business. Any entity may register multiple domain names for the same property. As a result, they can link alternative spellings, different top-level domains, aliases, brands, or products to the same website. Similarly, negative or derogatory domain names may also be registered. This is done to prevent certain domain names from being used against the person or business. It is common for a larger business to have domain names registered by multiple employees at multiple domain name registrars, possibly a result of organizational or geographical requirements. Consequently, a web presence management system can be used to monitor all domain names registered by the business, regardless of the registrars used. == Discovery == Web presence discovery is the process of monitoring the web for a new point of presence about a person or business. Web presence discovery is often included in a web presence management system. Whether a new domain is registered, a new website is published, or a new social media account is established, it occurs outside of the person's or business’ control. As a result, its purpose is to assess a new point of presence and appropriately handle any violations. Web presence discovery differs from content listening. The former involves looking for new properties on the web, whereas the latter refers to analyzing content that already exists to hear how a person or business is seen often in near real time. Examples of content listening systems include Sysomos and Radian6, which is now a subsidiary of Salesforce.com. === Brand protection === A person or business may choose to watch for a new web presence that might appear to misrepresent or mislead an audience, such as counterfeiters, spoofers, or malicious hackers. One of the early software in the online brand protection marketplace was MarkMonitor, now part of Thomson Reuters. This software helped detect rogue domain names and websites. However, the modern day growth of social media has seen a rise in the number of fraudulent brand impersonations. It has become much easier for a new web presence to be created on those platforms, which results in a greater frequency of them today. As a preventive measure, online brand protection providers are now adding social media to their domain and website discovery options. === Security === The widespread growth of social media has also made it easier for unauthorized individuals to impersonate an employee. Consequently, social media has now become a recognized threat vector in that it can be used to socially engineer an attack on a business. To counter this, companies are able to use web presence monitoring tools to detect new points of presence on the web and thereby defend against socially engineered attacks. === Distributed inventory management === A web presence monitoring system can be used by a business to associate a new web property with its corporate inventory. It is designed to address autonomous, distributed behaviors. This usually applies to larger businesses whose geographically diverse employees are more prone to creating new points of presence on the web. For example, a retail chain may allow each local store to create and manage their web presence to market to and communicate with their local customer base. Similarly, a global business may have teams in each country or region who create and manage a web presence to adapt to local languages or cultures. == Monitoring == Web presence monitoring is the process of monitoring a known inventory of web presence to detect any changes that are made. Web presence monitoring is often included in a web presence management system and can serve multiple purposes for both larger corporations and certain individuals, such as celebrities. It is important to note that presence monitoring differs from content listening. The former involves monitoring the properties (e.g. branding) of a web property in an established inventory, whereas the latter refers to analyzing content that already exists to hear how a person or business is seen often in near real time. Additionally, presence monitoring focuses on owned media and content listening on earned media. === Corporate, brand, and regulatory compliance === Many companies ensure that certain standards are met for a property on the web that represents their business. For companies in regulated industries, such as finance and healthcare, the company may be required by law to ensure that all publicized content, regardless of platform or technology, follow specific requirements. The widespread growth of social media has seen a rise in the number of fraudulent corporate impersonations. It has become much easier for a new web presence to be created on these platforms, and so these are much more prevalent than they used to be. As a preventive measure, a web presence monitoring system alerts the company when a known property is changed, allowing for the property to be reviewed and amended so that it follows the proper standards. . A web presence monitoring system helps alert the company when a known property is changed, so it can be reviewed and brought back, if necessary, into compliance with the appro

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  Social media as a public utility

  Social media as a public utility is a theory postulating that social networking sites (such as Meta - ie:Facebook & Instagram or Alphabet - ie: YouTube & Google, but also independent sites such as Twitter, Tumblr, Snapchat etc.) are essential public services that should be regulated by the government, in a manner similar to how electric and phone utilities are typically government regulated. It is based on the notion that social media platforms have monopoly power and broad social influence. == Background == === Definitions === Social media is defined as "a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of User Generated Content." Furthermore, the New Zealand Government of Internal Affairs describes it as "a set of online technologies, sites, and practices which are used to share opinions, experiences and perspectives. Fundamentally it is about the conversation. In contrast with traditional media, the nature of social media is to be highly interactive." Moreover, the term social media is described as online tools that let people interact and communicate with each other. This has become a standard word for online cultural exchange and a dominant way for individuals to engage on the internet. By using social media individuals become more closely and strongly connected than ever before. The traditional definition of the term public utility is "an infrastructural necessity for the general public where the supply conditions are such that the public may not be provided with a reasonable service at reasonable prices because of monopoly in the area." Conventional public utilities include water, natural gas, and electricity. In order to secure the interests of the public, utilities are regulated. Public utilities can also be seen as natural monopolies implying that the highest degree of efficiency is accomplished under one operator in the marketplace. Public utility regulation for social media has been largely criticized because people believe it would produce undesirable and indirect effects. However, others say that truly effective government regulation would produce valuable results. Social media as a public utility is a crucial debate because utilities get regulated, so marking social media websites as utilities would require government regulation of various social media websites and platforms such as Facebook, Google, and Twitter. Applying the term public utility to social media implies that social media websites are public necessities, and, consequently, should be regulated by the government. While social media are not as essential for survival as traditional public utilities such as electricity, water, and natural gas, many people believe it has become vital for living in an interconnected world and without it, living a successful life would be difficult. Therefore, many people believe that social media has reached utility status and should be treated as a public utility. However, others believe that this is not true because social media are constantly revolutionizing and giving such platforms "utility status" would result in government regulation, which would consequently hinder innovation. Over the past decade many have debated and questioned whether or not "Internet service providers should be considered essential facilities or natural monopolies and regulated as public utilities." === Monopoly === A monopoly is defined as "a firm that is the only seller of a product or service having no close substitutes." A natural monopoly is when the entire demand within a relevant market can be satisfied at lowest cost by one firm rather than by two or more, and if such a market contains more than one firm then the firms will "quickly shake down to one through mergers or failures, or production will continue to consume more resources than necessary." In a monopoly competition is said to be short-lived, and in a natural monopoly it is said to produce inefficient results." Public utility companies can be regulated to prevent them from gaining monopolistic control. In November 2011 AT&T's proposal for merging with T-Mobile was rejected because it would have "diminished competition," and have led to the company having monopolistic power within the telephone industry. Such regulation is permitted because the telephone industry is a public utility. Similarly, Microsoft has also been prevented from taking various business actions that could result in the company gaining monopolistic power. If social media were a public utility then regulation of Google and Facebook would similarly dictate what they could and could not do. The possibility was raised in 2018 by U.S. Representative Steve King during a House Judiciary hearing on social media filtering practices. == Arguments == Advocates of this theory believe that social media websites already act like public utilities, and therefore regulation is needed. Additionally, advocates say that in the 21st century, using such websites are as necessary for communication as using traditional public utilities such as telephone, water, electricity, and natural gas are for other everyday uses. Specifically, advocates note that Google search should be treated as a public utility and needs to be regulated because it dominates the search engine market and no website can afford to ignore it. There is the position that a social media website such as Google "is a common carrier and should be regulated as such (Newman 2011)." These are reinforced by a perception that social media companies fail to properly maintain fair platforms for discourse. === Individual level === Advocates of regulating social media as a public utility believe that having an Internet presence using social media websites is imperative for individuals to adequately take part in the 21st century. Consequently, they argue that these sites are public utilities that need to be regulated to ensure that the constitutional rights of users are protected. For example, regulation may be needed to protect freedom of speech against risks such as Internet censorship and deplatforming. Social media affects people's behavior. For instance, it plays an important role in shaping its users' decisions and actions pertaining to health. This is demonstrated in a Pew Research Center research, which showed that 72 percent of American adults turned to social media for health information in 2011. Around 70 percent of people with chronic illnesses also use the platform to find cure, diagnoses, and other health answers. This development becomes a public issue as social media are likely to provide wrong medical information. Additionally, social media sites can also facilitate deleterious health behavior such as smoking, drug use, and harmful sexual behavior. === Business level === Advocates of social media as a public utility maintain that social media services dominate the Internet and are mainly owned by three or four companies that have unparalleled power to shape user interaction, and because of this power such businesses need to be regulated as public utilities. Zeynep Tufekci, University of North Carolina Chapel Hill, claims that services on the Internet such as Google, eBay, Facebook, Amazon.com, are all natural monopolies. She has stated that these services "benefit greatly from network externalities[,] which means that the more people on the service, the more useful it is for everyone," and thus it is difficult to replace the market leader. === Government level === Advocates of social media as a public utility believe that the government should impose restrictions on social media websites, such as Google, that are designed to benefit its rivals. Due to the recent substantial growth of social media websites such as Google, advocates claim that such a website "might need search neutrality regulation modeled after net neutrality regulation and that a Federal Search Commission might be needed to enforce such a regime." danah boyd expresses a future issue which the government may have to deal with in her research: Facebook is becoming an international social media website, specifically prevalent in Canada and Europe which are "two regions that love to regulate their utilities." Furthermore, recent books by New America Foundation Senior Fellow Rebecca MacKinnon and law professor Lori Andrews advise society to start considering Facebook and Google as nation-states or the "sovereigns of cyberspace." Overall, advocates of social media as a public utility believe that due to the immense popularity and necessity of social media websites, it is imperative that the Government imposes regulations in the same manner they do for electricity, water, and natural gas. == Counterarguments == Opponents of this theory say that social media websites should not be treated as public utilities because these platforms are changing every year, and because they are not essential services for s

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  .ai

  .ai is the Internet country code top-level domain (ccTLD) for Anguilla, a British Overseas Territory in the Caribbean. It is administered by the government of Anguilla. It is a popular domain hack with companies and projects related to the artificial intelligence industry (AI). Google's ad targeting treats .ai as a generic top-level domain (gTLD) because "users and website owners frequently see [the domain] as being more generic than country-targeted." In 2021, Google Search analyst Gary Illyes announced that ".ai" had been added to Google’s list of generic country-code top-level domains, meaning that Google would no longer infer Anguilla-specific targeting from the ccTLD. Identity Digital began managing the domain as of January 2025. == Second and third level registrations == Registrations within off.ai, com.ai, net.ai, and org.ai are available worldwide without restriction. From 15 September 2009, second level registrations within .ai are available to everyone worldwide. == Registration == The minimum registration term allowed for .ai domains is 2 through 10 years for registration and renewal, and a 2-year renewal for domain transfer. Identity Digital is the authority in charge of managing this extension. Registrations began on 16 February 1995. The limits on the number of characters used for the domain name are, at a minimum, from 1 to 3, depending on the registrar, and always at most 63 characters. The character set supported for .ai domain names includes A–Z, a–z, 0–9, and hyphen. As of November 2022, .ai domains cannot accommodate IDN characters. There are no requirements for registering a domain, including local and foreign residents. A .ai domain can be suspended or revoked, if the domain is involved in illegal activity such as violating trademarks or copyrights. Usage must not violate the laws of Anguilla. Anguilla uses the UDRP. Filing a UDRP challenge requires using one of the ICANN Approved Dispute Resolution Service Providers. If the domain is with an ICANN accredited registrar, they should work with the arbitrator. Usually this means either doing nothing or transferring a domain. .ai domains are transferable to any desired registrars as the registration of domain is done maintaining EPP. There used to be a whois.ai-based platform of expired domains in which those could be procured and auctioned every ten days through a standard online process. The last auctions of such kind closed there in December 2024; the platform had been scheduled for shutdown on 30 June 2025, but remained online in the months following that date. == Valuation == Domains cost depends on the registrar, with yearly fees ranging from US$140 (the base fee, as established by Anguilla) to $200. As of July 2025, the highest-valued .ai domain is an undisclosed one sold on 8 November 2023, on Escrow.com, for US$1,500,000—months after an initial $300,000 sale to the same buyer. Among the publicly disclosed ones, the most valued, fin.ai, was sold for $1,000,000 in March 2025. On 16 December 2017, the .ai registry started supporting the Extensible Provisioning Protocol (EPP) and migrated all of its domains onto an EPP system. Consequently, many registrars are allowed to sell .ai domains. Since that date, the .ai ccTLD has also been popular with artificial intelligence companies and organisations. Though such trends are primarily seen among new AI based companies or startups, many established AI and Tech companies preferred not to opt for .ai domains. For example, DeepMind has its domain retained at .com; Meta has redirected its facebook.ai domain to ai.meta.com. == Impact on Anguilla's economy == The registration fees earned from the .ai domains go to the treasury of the Government of Anguilla. As per a 2018 New York Times report, the total revenue generated out of selling .ai domains was $2.9 million. In 2023, Anguilla's government made about US$32 million from fees collected for registering .ai domains; that amounted to over 10% of gross domestic product for the territory. "In the years before the real breakthrough of AI, revenue from .ai domains made up less than 1% of our state income, by 2025 it will be around 47%," explained Jose Vanterpool, Minister of Infrastructure and Communications (MICUHITES), in an interview with BBC. The high 90% renewal rate of .ai domains and the 2025 renewal wave of domains registered in 2023 are driving another surge in state revenues, according to Domaintechnik.

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  Chunked transfer encoding

  Chunked transfer encoding is a streaming data transfer mechanism available in Hypertext Transfer Protocol (HTTP) version 1.1, defined in RFC 9112 §7.1. In chunked transfer encoding, the data stream is divided into a series of non-overlapping "chunks". The chunks are sent out and received independently of one another. At any given time, no knowledge of the data stream outside the currently-being-processed chunk is necessary for either the sender or the receiver. Each chunk is preceded by its size in bytes and transmission ends when a zero-length chunk is received. The chunked keyword in the Transfer-Encoding header is used to indicate chunked transfer. Chunked transfer encoding is not supported in HTTP/2, which provides its own mechanisms for data streaming. == Rationale == The introduction of chunked encoding provided various benefits: Chunked transfer encoding allows a server to maintain an HTTP persistent connection for dynamically generated content. In this case, the HTTP Content-Length header cannot be used to delimit the content and the next HTTP request/response, as the content size is not yet known. Chunked encoding has the benefit that it is not necessary to generate the full content before writing the header, as it allows streaming of content as chunks and explicitly signaling the end of the content, making the connection available for the next HTTP request/response. Chunked encoding allows the sender to send additional header fields after the message body. This is important in cases where values of a field cannot be known until the content has been produced, such as when the content of the message must be digitally signed. Without chunked encoding, the sender would have to buffer the content until it was complete in order to calculate a field value and send it before the content. == Applicability == For version 1.1 of the HTTP protocol, the chunked transfer mechanism is considered to be always and anyway acceptable, even if not listed in the Transfer-Encoding (TE) request header field, and when used with other transfer mechanisms, should always be applied last to the transferred data and never more than one time. This transfer encoding method also allows additional entity header fields to be sent after the last chunk if the client specified the "trailers" parameter as an argument of the TE request field. The origin server of the response can also decide to send additional entity trailers even if the client did not specify the "trailers" parameter, but only if the metadata is optional (i.e. the client can use the received entity without them). Whenever the trailers are used, the server should list their names in the Trailer header field; three header field types are specifically prohibited from appearing as a trailer field: Content-Length, Trailer, and Transfer-Encoding. == Format == If a Transfer-Encoding field with a value of "chunked" is specified in an HTTP message (either a request sent by a client or the response from the server), the body of the message consists of one or more chunks and one terminating chunk with an optional trailer before the final ␍␊ sequence (i.e. carriage return followed by line feed). Each chunk starts with the number of octets of the data it embeds expressed as a hexadecimal number in ASCII followed by optional parameters (chunk extension) and a terminating ␍␊ sequence, followed by the chunk data. The chunk is terminated by ␍␊. If chunk extensions are provided, the chunk size is terminated by a semicolon and followed by the parameters, each also delimited by semicolons. Each parameter is encoded as an extension name followed by an optional equal sign and value. These parameters could be used for a running message digest or digital signature, or to indicate an estimated transfer progress, for instance. The terminating chunk is a special chunk of zero length. It may contain a trailer, which consists of a (possibly empty) sequence of entity header fields. Normally, such header fields would be sent in the message's header; however, it may be more efficient to determine them after processing the entire message entity. In that case, it is useful to send those headers in the trailer. Header fields that regulate the use of trailers are Transfer-Encoding with the "trailers" parameter (used in requests) and Trailer (used in responses). == Use with compression == HTTP servers often use compression to optimize transmission, for example with Content-Encoding: gzip or Content-Encoding: deflate. If both compression and chunked encoding are enabled, then the content stream is first compressed, then chunked; so the chunk encoding itself is not compressed, and the data in each chunk is compressed holistically (i.e. based on the whole content). The remote endpoint then decodes the stream by concatenating the chunks and uncompressing the result. == Example == === Encoded data === The following example contains three chunks of size 4, 7, and 11 (hexadecimal "B") octets of data. 4␍␊Wiki␍␊7␍␊pedia i␍␊B␍␊n ␍␊chunks.␍␊0␍␊␍␊ Below is an annotated version of the encoded data. 4␍␊ (chunk size is four octets) Wiki (four octets of data) ␍␊ (end of chunk) 7␍␊ (chunk size is seven octets) pedia i (seven octets of data) ␍␊ (end of chunk) B␍␊ (chunk size is eleven octets) n ␍␊chunks. (eleven octets of data) ␍␊ (end of chunk) 0␍␊ (chunk size is zero octets, no more chunks) ␍␊ (end of final chunk with zero data octets) Note: Each chunk's size excludes the two ␍␊ bytes that terminate the data of each chunk. === Decoded data === Decoding the above example produces the following octets: Wikipedia in ␍␊chunks. The bytes above are typically displayed as Wikipedia in chunks.

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  Data storage

  Data storage is the recording (storing) of information (data) in a storage medium. Handwriting, phonographic recording, magnetic tape, and optical discs are all examples of storage media. Biological molecules such as RNA and DNA are considered by some as data storage. Recording may be accomplished with virtually any form of energy. Electronic data storage requires electrical power to store and retrieve data. Data stored in a digital, machine-readable medium is called digital data. Computer data storage is one of the core functions of a general-purpose computer. Electronic documents can be stored in much less space than paper documents. Barcodes and magnetic ink character recognition (MICR) are two ways of recording machine-readable data on paper. == Recording media == A recording medium is physical material that holds information. Newly created information is distributed and can be stored in four storage media–print, film, magnetic, and optical–and seen or heard in four information flows–telephone, radio, TV, and the Internet as well as being observed directly. Digital information is stored on electronic media in many different recording formats. With electronic media, the data and the recording media are sometimes referred to as "software" despite the more common use of the word to describe computer software. With (traditional art) static media, art materials such as crayons may be considered both equipment and medium as the wax, charcoal or chalk material from the equipment becomes part of the surface of the medium. Some recording media may be temporary, either by design or by nature. Volatile organic compounds may be used to purposely make data expire over time or to reduce environmental impact. Data such as smoke signals or skywriting are temporary by nature. Depending on the volatility, a gas (e.g., atmosphere, smoke) or a liquid surface such as a lake would be considered a temporary recording medium, if it could be considered a recording medium at all. == Global capacity, digitization, and trends == A 2003 UC Berkeley report estimated that about five exabytes of new information were produced in 2002 and that 92% of this data was stored on magnetic media (primarily hard disk drives). This was about twice the data produced in 1999. The amount of data transmitted over telecommunications systems in 2002 was nearly 18 exabytes—three and a half times more than was recorded on non-volatile storage. Telephone calls constituted 98% of the telecommunicated information in 2002. The researchers' highest estimate for the growth rate of newly stored information (uncompressed) was more than 30% per year. In a more limited study, the International Data Corporation estimated that the total amount of digital data in 2007 was 281 exabytes and that the total amount of digital data produced exceeded the global storage capacity for the first time. A 2011 article in Science estimated that the year 2002 was the beginning of the digital age for information storage: an age in which more information is stored on digital storage devices than on analog storage devices. In 1986, approximately 1% of the world's capacity to store information was in digital format; this grew to 3% by 1993, to 25% by 2000, and to 94% by 2007. These figures correspond to less than three compressed exabytes in 1986, and 295 compressed exabytes in 2007. The quantity of digital storage doubled roughly every three to four years. It is estimated that around 120 zettabytes of data will be generated in 2023, an increase of 60x from 2010, and that it will increase to 181 zettabytes generated in 2025. == Mass storage ==

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  SFINKS

  Sfinks (Polish for "Sphynx") was also the initial name of the Janusz A. Zajdel Award In cryptography, SFINKS is a stream cypher algorithm developed by An Braeken, Joseph Lano, Nele Mentens, Bart Preneel, and Ingrid Verbauwhede. It includes a message authentication code. It has been submitted to the eSTREAM Project of the eCRYPT network. In 2005, Nicolas T. Courtois noted that, while the cipher is elegant and secure against some simple algebraic attacks, it is vulnerable to more elaborate known attacks.

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  Colloquis

  Colloquis, previously known as ActiveBuddy and Conversagent, was a company that created conversation-based interactive agents originally distributed via instant messaging platforms. The company had offices in New York, New York, and Sunnyvale, California. == History == Founded in 2000, the company was the brainchild of Robert Hoffer, Timothy Kay, and Peter Levitan. The idea for interactive agents (also known as Internet bots) came from the team's vision to add functionality to increasingly popular instant messaging services. The original implementation took shape as a word-based adventure game but quickly grew to include a wide range of database applications, including access to news, weather, stock information, movie times, Yellow Pages listings, and detailed sports data, as well as a variety of tools (calculators, translator, etc.). These various applications were bundled into one entity and launched as SmarterChild in 2001. SmarterChild acted as a showcase for the quick data access and possibilities for fun conversation that the company planned to turn into customized, niche-specific products. The rapid success of SmarterChild led to targeted promotional products for Radiohead, Austin Powers, The Sporting News, and others. ActiveBuddy sought to strengthen its hold on the interactive agent market for the future by filing for, and receiving, a controversial patent on their creation in 2002. The company also released the BuddyScript SDK, a free developer kit that allow programmers to design and launch their own interactive agents using ActiveBuddy's proprietary scripting language, in 2002. Ultimately, however, the decline in ad spending in 2001 and 2002 led to a shift in corporate strategy towards business focused Automated Service Agents, building products for clients including Cingular, Comcast and Cox Communications. The company subsequently changed its name from ActiveBuddy to Conversagent in 2003, and then again to Colloquis in 2006. Colloquis was purchased by Microsoft in October 2006.

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  Dashboard (computing)

  In computer information systems, a dashboard is a type of graphical user interface which often provides at-a-glance views of data relevant to a particular objective or process through a combination of visualizations and summary information. In other usage, "dashboard" is another name for "progress report" or "report" and is considered a form of data visualization. The dashboard is often accessible by a web browser and is typically linked to regularly updating data sources. Dashboards are often interactive and facilitate users to explore the data themselves, usually by clicking into elements to view more detailed information. The term dashboard originates from the automobile dashboard where drivers monitor the major functions at a glance via the instrument panel. == History == The idea of digital dashboards followed the study of decision support systems in the 1970s. Early predecessors of the modern business dashboard were first developed in the 1980s in the form of Executive Information Systems (EISs). Due to problems primarily with data refreshing and handling, it was soon realized that the approach wasn't practical as information was often incomplete, unreliable, and spread across too many disparate sources. Thus, EISs hibernated until the 1990s when the information age quickened pace and data warehousing, and online analytical processing (OLAP) allowed dashboards to function adequately. Despite the availability of enabling technologies, the dashboard use didn't become popular until later in that decade, with the rise of key performance indicators (KPIs), and the introduction of Robert S. Kaplan and David P. Norton's balanced scorecard. In the late 1990s, Microsoft promoted a concept known as the Digital Nervous System and "digital dashboards" were described as being one leg of that concept. Today, the use of dashboards forms an important part of Business Performance Management (BPM). Initially dashboards were used for monitoring purposes, now with the advancement of technology, dashboards are being used for more analytical purposes. The use of dashboards has now been incorporating; scenario analysis, drill down capabilities, and presentation format flexibility. == Benefits == Digital dashboards allow managers to monitor the contribution of the various departments in their organization. In addition, they enable “rolling up” of information to present a consolidated view across an organization. To gauge exactly how well an organization is performing overall, digital dashboards allow you to capture and report specific data points from each department within the organization, thus providing a "snapshot" of performance. Benefits of using digital dashboards include: Visual presentation of performance measures Ability to identify and correct negative trends Measure efficiencies/inefficiencies Ability to generate detailed reports showing new trends Ability to make more informed decisions based on collected business intelligence Dashboards offers a holistic view of the entire business as it gives the manager a bird's eye view into the performance of sales, data inventory, web traffic, social media analytics and other associated data that is visually presented on a single dashboard. Dashboards lead to better management of marketing/financial strategies as a dashboard for the display of marketing data makes the process of marketing easier and more reliable as compared to doing it manually. Web analytics play a crucial role in shaping the marketing strategy of many businesses. Dashboards also facilitate for better tracking of sales and financial reporting as the data is more precise and in one area. Lastly, dashboards offer for better customer service through monitoring because they keep both the managers and the clients updated on the project progress through automated emails and notifications. == Align strategies and organizational goals == Gain total visibility of all systems instantly Quick identification of data outliers and correlations Consolidated reporting into one location Available on mobile devices to quickly access metrics == Classification == Dashboards can be broken down according to role and are either strategic, analytical, operational, or informational. Dashboards are the 3rd step on the information ladder, demonstrating the conversion of data to increasingly valuable insights. Strategic dashboards support managers at any level in an organization and provide the quick overview that decision-makers need to monitor the health and opportunities of the business. Dashboards of this type focus on high-level measures of performance and forecasts. Strategic dashboards benefit from static snapshots of data (daily, weekly, monthly, and quarterly) that are not constantly changing from one moment to the next. Dashboards for analytical purposes often include more context, comparisons, and history, along with subtler performance evaluators. In addition, analytical dashboards typically support interactions with the data, such as drilling down into the underlying details. Dashboards for monitoring operations are often designed differently from those that support strategic decision making or data analysis and often require monitoring of activities and events that are constantly changing and might require attention and response at a moment's notice. == Types of dashboards == Digital dashboards may be laid out to track the flows inherent in the business processes that they monitor. Graphically, users may see the high-level processes and then drill down into low-level data. This level of detail is often buried deep within the corporate enterprise and otherwise unavailable to the senior executives. Three main types of digital dashboards dominate the market today: desktop software applications, web-browser-based applications, and desktop applications are also known as desktop widgets. The last are driven by a widget engine. Both Desktop and Browser-based providers enable the distribution of dashboards via a web browser. An example of the latter is web-based-browser Asana, which helps teams orchestrate their work, from daily tasks to strategic cross-functional initiatives. With it, teams can manage everything from company objectives to digital transformation to product launches and marketing campaigns. Specialized dashboards may track all corporate functions. Examples include human resources, recruiting, sales, operations, security, information technology, project management, customer relationship management, digital marketing and many more departmental dashboards. For a smaller organization like a startup a compact startup scorecard dashboard tracks important activities across lot of domains ranging from social media to sales. Digital dashboard projects involve business units as the driver and the information technology department as the enabler. Therefore, the success of dashboard projects depends on the relevancy/importance of information provided within the dashboard. This includes the metrics chosen to monitor and the timeliness of the data forming those metrics; data must be up to date and accurate. Key performance indicators, balanced scorecards, and sales performance figures are some of the content appropriate on business dashboards. === Performance Dashboards === Dashboards involve the combination of visual and functional features. This combination of features helps improve cognition and interpretation. A performance dashboard sits at the intersection of two powerful disciplines: business intelligence and performance management. Therefore, there are different users who could use these dashboards for different reasons. For example, a level of workers could look at monitoring inventory while those in more managerial roles can look at lagging measure. Then executives could utilize the dashboard to evaluate strategic performance against objectives. == Dashboards and scorecards == Balanced scorecards and dashboards have been linked together as if they were interchangeable. However, although both visually display critical information, the difference is in the format: Scorecards can open the quality of an operation while dashboards provide calculated direction. A balanced scorecard has what they called a "prescriptive" format. It should always contain these components: Perspectives – group Objectives – verb-noun phrases pulled from a strategy plan Measures – also called metric or key performance indicators (KPIs) Spotlight indicators – red, yellow, or green symbols that provide an at-a-glance view of a measure's performance. Each of these sections ensures that a Balanced Scorecard is essentially connected to the businesses critical strategic needs. The design of a dashboard is more loosely defined. Dashboards are usually a series of graphics, charts, gauges and other visual indicators that can be monitored and interpreted. Even when there is a strategic link, on a dashboard, it may not be noticed as such since objectives are not normally pre

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  AS1 (networking)

  AS1 (Applicability Statement 1) is a specification about how to transport structured business-to-business data securely and reliably over the Internet. Security is achieved by using digital certificates and encryption. == AS1 technical overview == The AS1 protocol is based on SMTP and S/MIME. It was the first AS protocol developed and uses signing, encryption and MDN conventions. In other words: Files are sent as "attachments" in a specially coded SMIME email message Messages can be signed, but do not have to be Messages can be encrypted, but do not have to be Messages may request an MDN back if all went well, but do not have to request such a message If the original AS1 message requested an MDN... Upon the receipt of the message and its successful decryption or signature validation (as necessary) a "success" MDN will be sent back to the original sender. This MDN is typically signed but not encrypted. Upon the receipt and successful verification of the signature on the MDN, the original sender will "know" that the recipient got their message (this provides the "Non-repudiation" element of AS1) If there are any problems receiving or interpreting the original AS1 message, a "failed" MDN may be sent back. Like any other AS file transfer, AS1 file transfers typically require both sides of the exchange to trade X.509 certificates and specific "trading partner" names before any transfers can take place.

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  Social media use in African politics

  Since the Egyptian Revolution in 2011 and the Tunisian Revolution, social media, especially Facebook, Twitter, and YouTube, began to gain traction as a political tool in Africa. Various political actors have used social media to pursue a wide range of political objectives. State actors can use social media to encourage political discourse, campaign, or implement censorship and surveillance. Non-state actors, such as civil society organizations and opposition movements, can use social media to address political concerns and to organize widespread uprisings, such as the 2014 Burkinabé uprising. Meanwhile, extremist organizations can use social media to further their propaganda and recruitment. However, social media has been criticized for its limited accessibility and for facilitating the spread of misinformation, causing some skepticism about its effectiveness. Due to low entry barriers and user-generated content, social media provides a platform where people from different social classes can engage and interact with one another. Under traditional media, the public had limited opportunities to voice their political opinions. Social media enables people to both create and consume content. The public has become increasingly comfortable and confident in expressing political opinions online, often away from government scrutiny. Scholars argue that social media use has democratizing effects in African countries. == State actors == === Promoting political discourse === Through social media, the government and its citizens can discuss policy ideas, policy implementation, and political actions. Regardless of geographical location and distance, people are able to voice their opinions to the government. Social media includes citizens who were previously not able to express their discontent or share their ideas to the government. As state actors keep the public informed, social media can increase civic engagement. With more civic engagement, policies can be discussed without politicization. Before the commonplace use of social media, African countries faced weak feedback mechanisms that effectively excluded the average African citizen from policy discourse. In South Africa, the government uses social media to connect with constituencies. The South African president runs an official Twitter, Facebook, YouTube, and Flickr accounts to engage with the public. === Campaigning === Political parties also use social media for political campaigns during election periods. In South Africa, the ANC (African National Congress) and DA (Democratic Alliance) use social media for political purposes. These parties specifically use Facebook as a tool for campaigning and engaging with the public to improve their relationship with citizens. Nigerian President Goodluck Jonathan employed social media to campaign for the presidential election in 2011, which he won. When President Goodluck Jonathan announced his bid for the presidency on social media in 2010, it reached about 217,000 people. As his campaign progressed, President Goodluck Jonathan was able to increase his followers to half a million by early 2011. === Censorship & Surveillance === While state actors can use social media to encourage their party or discourse, social media can be used to censor and surveil citizens. For example, the ANC and DA use Facebook to monitor South Africans. The government is able to track down people who have spoken against the government and translate this information into physical action to stop any possibility of a revolution. Social media platforms can be shut down to manipulate the flow of information. In Chad, citizens cannot access information through online platforms. This censorship blocked "Facebook, Twitter, WhatsApp and Viber". In the Democratic Republic of Congo, the government shut down the internet before contested elections. In Zimbabwe, the government shut down the internet to hide civilian protests against fuel price increases. == Non-state actors == === Civil society organizations (CSOs) === Civil society organizations have also used social media networks in an effort to recruit supporters and communicate with the public. CSOs can use social media to mobilize people to support their cause, such as the Ghanaian Committee for Joint Action (CJA). In 2005 and 2006, the CJA gathered support to protest against the 50% fuel price increase. CSOs can play the role of a counterforce against state actors and state propaganda during times of crises, such as protests and military clashes. In some cases, CSOs release their own videos and photos on social media which challenges traditional forms of media. CSOs have also served to monitor elections to reduce corruption and violence during election day. For instance, the Zambian Bantu Watch started the #bantuwatch social media campaign to monitor the 2011 presidential election. Zambians used Facebook and Twitter to report polling station results to mitigate election fraud and election violence. In South Africa, CSOs created 'amandla.mobi' to campaign for public policies by creating petitions. Through 'amandla.mobi', CSOs are able to circulate petitions on social media to collect signatures. South African CSOs reported how social media helped their organizations to gain support and share ideas. However, CSOs struggle to attract media attention and often have to pay for media coverage. === Opposition forces against the government === Social media is also used by the public or opposition forces against the government. Through horizontal social media, organizing can lead to street protests and revolutions, some of which are successful. For instance, during the Egyptian revolution of 2011, "The Day of the Revolution Against Torture, Poverty, Corruption, and Unemployment" and "We Are All Khaled Said" gathered support against President Hosni Mubarak. In particular, "We Are All Khaled Said" had Egyptian citizens gather around the death of Khaled Said who was brutally tortured and killed by the Egyptian government because Said wanted to uncover government corruption. As unrest erupted into public demonstrations, President Hosni Mubarak was forced to resign. Witnessing the success of social media during the Egyptian revolution, the Tunisian Revolution, or the Jasmine Revolution, mobilized through Facebook and Twitter. Likewise, in South Africa, Malawi, and Mozambique, these countries have used social media as "new protest drums." Due to social media's low entry barrier, opposition forces against the government can facilitate political discourse that can lead to accountability. Whistleblowers and opposition forces are able to expose corruption through social media, where they face less repression while reaching a larger audience. For example, the youth of Zimbabwe and South Africa use Facebook to discuss politics without judgment. Specifically, in Zimbabwe, political youth used Facebook to avoid state surveillance. Social media is used as a supplemental tool for activism. In 2015, South African student activists started the hashtag #RhodesMustFall to push the issue of colonialism and racism at the forefront of the public. === Extremist organizations === Social media is easily accessible and created by user-based content. Therefore, marginalized groups are able to use social media to spread extremist ideas. For instance, Boko Haram created the Media Office of West Africa Province and perpetuated propaganda through Twitter and YouTube. Boko Haram's online propaganda campaign targets and persuades young dissuaded Nigerians to join their cause. It is important to note that social media has also been used against Boko Haram. In April 2014, Boko Haram kidnapped 276 schoolgirls and an international campaign fought for their return through #BringBackOurGirls. Another extremist group, Al-Shabaab, has created an online presence through Twitter and YouTube. Through these social media networks, Al-Shabaab recruits new members to their extremist group through their propaganda which emphasizes the group's successes. Albeit their efforts, Al-Shabaab has not been very successful in coordinating their members but they are successful in financing their group. Furthermore, the Islamic State of Iraq and the Levant (ISIL) use social media to target and recruit individuals to their cause. ISIL's social media usage is more diverse compared to Boko Haram and Al-Shabaab; ISIL uses "Facebook, Twitter, YouTube, WhatsApp, Telegram, JustPaste.it, Kik and Ask.fm." Since ISIL's Twitter accounts kept getting shut down, ISIL uses Telegram and WhatsApp chat rooms to privately conduct meetings. Due to the spread of extremist ideology, Zhuravskaya et al. acknowledge social media's potential to be misused. == Challenges == Although social media can be used as a political tool, it faces challenges in Africa. Due to low literacy rates in Africa, social media networks exclude many of the population members. In addition, lack of access to electricity and the internet can fur

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  Memory color effect

  The memory color effect is the phenomenon that the canonical hue of a type of object acquired through experience (e.g. the sky, a leaf, or a strawberry) can directly modulate the appearance of the actual colors of objects. Human observers acquire memory colors through their experiences with instances of that type. For example, most human observers know that an apple typically has a reddish hue; this knowledge about the canonical color which is represented in memory constitutes a memory color. As an example of the effect, normal human trichromats, when presented with a gray banana, often perceive the gray banana as being yellow - the banana's memory color. In light of this, subjects typically adjust the color of the banana towards the color blue - the opponent color of yellow - when asked to adjust its surface to gray to cancel the subtle activation of banana's memory color. Subsequent empirical studies have also shown the memory color effect on man-made objects (e.g. smurfs, German mailboxes), the effect being especially pronounced for blue and yellow objects. To explain this, researchers have argued that because natural daylight shifts from short wavelengths of light (i.e., bluish hues) towards light of longer wavelengths (i.e., yellowish-orange hues) during the day, the memory colors for blue and yellow objects are recruited by the visual system to a higher degree to compensate for this fluctuation in illumination, thereby providing a stronger memory color effect. == Form identification == Memory color plays a role when detecting an object. In a study where participants were given objects, such as an apple, with two alternate forms for each, a crooked apple and a circular apple, researchers changed the colors of the alternate forms and asked if they could identify them. Most of the participants answered "unsure," suggesting that we use memory color when identifying an object. The research redefined memory color as a phenomenon when "a form's identity affects the phenomenal hue of that form." == Color effect on memorization == Memory color effect can be derived from the human instinct to memorize objects better. Comparing the effect of recognizing gray-scaled images and colored images, results showed that people were able to recall colored images 5% higher compared to gray-scaled images. An important factor was that higher level of contrast between the object and background color influences memory. In a specific study related to this, participants reported that colors were 5% to 10% easier to recognize compared to black and white. == Color constancy and memory color effect == Color constancy is the phenomenon where a surface to appear to be of the same color under a wide rage of illumination. A study tested two hypotheses with regards to color memory; the photoreceptor hypothesis and the surface reflectance hypothesis. The test color was surround either by various color patches forming a complex pattern or a uniform “grey” field at the same chromaticity as that of the illuminant. The test color was presented on a dark background for the control group. It was observed that complex surround results where in line with the surface-reflectance hypothesis and not the photoreceptor hypothesis, showing that the accuracy and precision of color memory are fundamentals to understanding the phenomenon of color constancy. == Significance to the evolution of trichromacy == While objects that possess canonical hues make up a small percentage of the objects which populate humans’ visual experience, the human visual system evolved in an environment populated with objects that possess canonical hues. This suggests that the memory color effect is related to the emergence of trichromacy because it has been argued that trichromacy evolved to optimize the ability to detect ripe fruits—objects that appear in canonical hues. == In perception research == In perception research, the memory color effect is cited as evidence for the opponent color theory, which states that four basic colors can be paired with its opponent color: red—green, blue—yellow. This explains why participants adjust the ripe banana color to a blueish tone to make its memory color yellow as gray. Researchers have also found empirical evidence that suggests memory color is recruited by the visual system to achieve color constancy. For example, participants had a lower percentage of color constancy when looking at a color incongruent scene, such as a purple banana, compared to a color diagnostical scene, a yellow banana. This suggests that color constancy is influenced by the color of objects that we are familiar with, which the memory color effect takes part.

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  ISO 15765-2

  ISO 15765-2, or ISO-TP (Transport Layer), is an international standard for sending data packets over a CAN bus. The protocol allows for the transport of messages that exceed the eight byte maximum payload of CAN frames. ISO-TP segments longer messages into multiple frames, adding metadata (CAN-TP Header) that allows the interpretation of individual frames and reassembly into a complete message packet by the recipient. It can carry up to 232-1 (4294967295) bytes of payload per message packet starting from the 2016 version. Prior versions were limited to a maximum payload size of 4095 bytes. In the OSI model, ISO-TP covers the layer 3 (network layer) and 4 (transport layer). The most common application for ISO-TP is the transfer of diagnostic messages with OBD-II equipped vehicles using KWP2000 and UDS, but is used broadly in other application-specific CAN implementations where one might need to send messages longer than what the CAN protocol physical layer allows (eight bytes for CAN, 64 bytes for CAN FD, and 2048 bytes for CAN-XL). ISO-TP can be operated with its own addressing as so-called Extended Addressing or without address using only the CAN ID (so-called Normal Addressing). Extended addressing uses the first data byte of each frame as an additional element of the address, reducing the application payload by one byte. For clarity the protocol description below is based on Normal Addressing with eight byte CAN frames. In total, six types of addressing are allowed by the ISO 15765-2 Protocol. ISO-TP prepends one or more metadata bytes to the payload data in the eight byte CAN frame, reducing the payload to seven or fewer bytes per frame. The metadata is called the Protocol Control Information, or PCI. The PCI is one, two or three bytes. The initial field is four bits indicating the frame type, and implicitly describing the PCI length. ISO 15765-2 is a part of ISO 15765 (headlined Road vehicles — Diagnostic communication over Controller Area Network (DoCAN)), which has the following parts: ISO 15765-1 Part 1: General information and use case definition ISO 15765-2 Part 2: Transport protocol and network layer services ISO 15765-3 Part 3: Implementation of unified diagnostic services (UDS on CAN) – replaced by ISO 14229-3 Road vehicles — Unified diagnostic services ISO 15765-4 Part 4: Requirements for emissions-related systems == List of protocol control information (PCI) field types == The ISO-TP defines four frame types: A message of seven bytes or less is sent in a single frame, with the initial byte containing the type (0) and payload length (1-7 bytes). With the 0 in the type field, this can also pass as a simpler protocol with a length-data format and is often misinterpreted as such. A message longer than 7 bytes requires segmenting the message packet over multiple frames. A segmented transfer starts with a First Frame. The PCI is two bytes in this case, with the first 4 bit field the type (type 1) and the following 12 bits the message length (excluding the type and length bytes). The recipient confirms the transfer with a flow control frame. The flow control frame has three PCI bytes specifying the interval between subsequent frames and how many consecutive frames may be sent (Block Size). For CAN FD, the ISO 15765-2 protocol has been extended for Single and First frame, to allow larger size values, but still backwards compatible with traditional ISO 15765. See CAN FD. The initial byte contains the type (type = 3) in the first four bits, and a flag in the next four bits indicating if the transfer is allowed (0 = Continue To Send, 1 = Wait, 2 = Overflow/abort). The next byte is the block size, the count of frames that may be sent before waiting for the next flow control frame. A value of zero allows the remaining frames to be sent without flow control or delay. The third byte is the minimum Separation Time (STmin), the minimum delay time between frames. STmin values up to 127 (0x7F) specify the minimum number of milliseconds to delay between frames, while values in the range 241 (0xF1) to 249 (0xF9) specify delays increasing from 100 to 900 microseconds. Note that the Separation Time is defined as the minimum time between the end of one frame to the beginning of the next. Robust implementations should be prepared to accept frames from a sender that misinterprets this as the frame repetition rate i.e. from start-of-frame to start-of-frame. Even careful implementations may fail to account for the minor effect of bit-stuffing in the physical layer. The sender transmits the rest of the message using Consecutive Frames. Each Consecutive Frame has a one byte PCI, with a four bit type (type = 2) followed by a 4-bit sequence number. The sequence number starts at 1 and increments with each frame sent (1, 2,..., F, 0, 1,...), with which lost or discarded frames can be detected. Each consecutive frame starts at 0, initially for the first set of data in the first frame will be considered as 0th data. So the first set of CF(Consecutive frames) start from 0x1. There afterwards when it reaches 0x2F, will be started from 0x20 (e.g. 0x21, 0x22, 0x23...0x2F, 0x20, 0x21...). The 12-bit length field (as indicated in the First Frame) allows up to 4095 bytes of user data in a segmented message, but in practice the typical application-specific limit is considerably lower because of receive buffer or hardware limitations. == Timing parameters == Timing parameters, such as P1 and P2 timers, have to be mentioned. == Standards == ISO 15765-2:2016 Road vehicles -- Diagnostic communication over Controller Area Network (DoCAN) -- Part 2: Transport protocol and network layer services

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  Chunked transfer encoding

  Chunked transfer encoding is a streaming data transfer mechanism available in Hypertext Transfer Protocol (HTTP) version 1.1, defined in RFC 9112 §7.1. In chunked transfer encoding, the data stream is divided into a series of non-overlapping "chunks". The chunks are sent out and received independently of one another. At any given time, no knowledge of the data stream outside the currently-being-processed chunk is necessary for either the sender or the receiver. Each chunk is preceded by its size in bytes and transmission ends when a zero-length chunk is received. The chunked keyword in the Transfer-Encoding header is used to indicate chunked transfer. Chunked transfer encoding is not supported in HTTP/2, which provides its own mechanisms for data streaming. == Rationale == The introduction of chunked encoding provided various benefits: Chunked transfer encoding allows a server to maintain an HTTP persistent connection for dynamically generated content. In this case, the HTTP Content-Length header cannot be used to delimit the content and the next HTTP request/response, as the content size is not yet known. Chunked encoding has the benefit that it is not necessary to generate the full content before writing the header, as it allows streaming of content as chunks and explicitly signaling the end of the content, making the connection available for the next HTTP request/response. Chunked encoding allows the sender to send additional header fields after the message body. This is important in cases where values of a field cannot be known until the content has been produced, such as when the content of the message must be digitally signed. Without chunked encoding, the sender would have to buffer the content until it was complete in order to calculate a field value and send it before the content. == Applicability == For version 1.1 of the HTTP protocol, the chunked transfer mechanism is considered to be always and anyway acceptable, even if not listed in the Transfer-Encoding (TE) request header field, and when used with other transfer mechanisms, should always be applied last to the transferred data and never more than one time. This transfer encoding method also allows additional entity header fields to be sent after the last chunk if the client specified the "trailers" parameter as an argument of the TE request field. The origin server of the response can also decide to send additional entity trailers even if the client did not specify the "trailers" parameter, but only if the metadata is optional (i.e. the client can use the received entity without them). Whenever the trailers are used, the server should list their names in the Trailer header field; three header field types are specifically prohibited from appearing as a trailer field: Content-Length, Trailer, and Transfer-Encoding. == Format == If a Transfer-Encoding field with a value of "chunked" is specified in an HTTP message (either a request sent by a client or the response from the server), the body of the message consists of one or more chunks and one terminating chunk with an optional trailer before the final ␍␊ sequence (i.e. carriage return followed by line feed). Each chunk starts with the number of octets of the data it embeds expressed as a hexadecimal number in ASCII followed by optional parameters (chunk extension) and a terminating ␍␊ sequence, followed by the chunk data. The chunk is terminated by ␍␊. If chunk extensions are provided, the chunk size is terminated by a semicolon and followed by the parameters, each also delimited by semicolons. Each parameter is encoded as an extension name followed by an optional equal sign and value. These parameters could be used for a running message digest or digital signature, or to indicate an estimated transfer progress, for instance. The terminating chunk is a special chunk of zero length. It may contain a trailer, which consists of a (possibly empty) sequence of entity header fields. Normally, such header fields would be sent in the message's header; however, it may be more efficient to determine them after processing the entire message entity. In that case, it is useful to send those headers in the trailer. Header fields that regulate the use of trailers are Transfer-Encoding with the "trailers" parameter (used in requests) and Trailer (used in responses). == Use with compression == HTTP servers often use compression to optimize transmission, for example with Content-Encoding: gzip or Content-Encoding: deflate. If both compression and chunked encoding are enabled, then the content stream is first compressed, then chunked; so the chunk encoding itself is not compressed, and the data in each chunk is compressed holistically (i.e. based on the whole content). The remote endpoint then decodes the stream by concatenating the chunks and uncompressing the result. == Example == === Encoded data === The following example contains three chunks of size 4, 7, and 11 (hexadecimal "B") octets of data. 4␍␊Wiki␍␊7␍␊pedia i␍␊B␍␊n ␍␊chunks.␍␊0␍␊␍␊ Below is an annotated version of the encoded data. 4␍␊ (chunk size is four octets) Wiki (four octets of data) ␍␊ (end of chunk) 7␍␊ (chunk size is seven octets) pedia i (seven octets of data) ␍␊ (end of chunk) B␍␊ (chunk size is eleven octets) n ␍␊chunks. (eleven octets of data) ␍␊ (end of chunk) 0␍␊ (chunk size is zero octets, no more chunks) ␍␊ (end of final chunk with zero data octets) Note: Each chunk's size excludes the two ␍␊ bytes that terminate the data of each chunk. === Decoded data === Decoding the above example produces the following octets: Wikipedia in ␍␊chunks. The bytes above are typically displayed as Wikipedia in chunks.

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