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The Shepp–Logan phantom is a standard test image created by Larry Shepp and Benjamin F. Logan for their 1974 paper "The Fourier Reconstruction of a Head Section". It serves as the model of a human head in the development and testing of image reconstruction algorithms. == Definition == The function describing the phantom is defined as the sum of 10 ellipses inside a 2×2 square:
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A software token (a.k.a. soft token) is a piece of a two-factor authentication security device that may be used to authorize the use of computer services. Software tokens are stored on a general-purpose electronic device such as a desktop computer, laptop, PDA, or mobile phone and can be duplicated. (Contrast hardware tokens, where the credentials are stored on a dedicated hardware device and therefore cannot be duplicated — absent physical invasion of the device) Because software tokens are something one does not physically possess, they are exposed to unique threats based on duplication of the underlying cryptographic material - for example, computer viruses and software attacks. Both hardware and software tokens are vulnerable to bot-based man-in-the-middle attacks, or to simple phishing attacks in which the one-time password provided by the token is solicited, and then supplied to the genuine website in a timely manner. Software tokens do have benefits: there is no physical token to carry, they do not contain batteries that will run out, and they are cheaper than hardware tokens. == Security architecture == There are two primary architectures for software tokens: shared secret and public-key cryptography. For a shared secret, an administrator will typically generate a configuration file for each end-user. The file will contain a username, a personal identification number, and the secret. This configuration file is given to the user. The shared secret architecture is potentially vulnerable in a number of areas. The configuration file can be compromised if it is stolen and the token is copied. With time-based software tokens, it is possible to borrow an individual's PDA or laptop, set the clock forward, and generate codes that will be valid in the future. Any software token that uses shared secrets and stores the PIN alongside the shared secret in a software client can be stolen and subjected to offline attacks. Shared secret tokens can be difficult to distribute, since each token is essentially a different piece of software. Each user must receive a copy of the secret, which can create time constraints. Some newer software tokens rely on public-key cryptography, or asymmetric cryptography. This architecture eliminates some of the traditional weaknesses of software tokens, but does not affect their primary weakness (ability to duplicate). A PIN can be stored on a remote authentication server instead of with the token client, making a stolen software token no good unless the PIN is known as well. However, in the case of a virus infection, the cryptographic material can be duplicated and then the PIN can be captured (via keylogging or similar) the next time the user authenticates. If there are attempts made to guess the PIN, it can be detected and logged on the authentication server, which can disable the token. Using asymmetric cryptography also simplifies implementation, since the token client can generate its own key pair and exchange public keys with the server.
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"Sharenting" is a portmanteau of "sharing" and "parenting", describing the practice of parents publicizing a large amount of potentially sensitive content about their children on internet platforms, most notably on social media. While the term was coined as recently as 2010, sharenting has become an international phenomenon with widespread presence in the United States, Spain, France, and the United Kingdom. Proponents of sharenting frame the practice as a natural expression of parental pride in their children and argue that critics take sharenting-related posts out of context. Detractors find that it violates child privacy and hurts a parent–child relationship. Academic research has been conducted over the potential social motivations for sharenting and legal frameworks to balance child privacy with this parental practice. Researchers have conducted several psychological surveys, outlining social media accessibility, parental self-identification with children, and social pressure as potential causes for sharenting. Legal scholars have identified international human rights laws, labor protections, and recent online child privacy statutes as potential legal standards to check sharenting abuses. == History == The origins of the term "sharenting" have been attributed to the Wall Street Journal, where they called it "oversharenting," a portmanteau of "oversharing" and "parenting." Priya Kumar suggests that recording life moments of children rearing is not a new practice: people have been using diaries, scrapbooks and baby log books as the media of documentation for centuries. Scholars assert that sharenting has become popular as a result of social media, which has made many people more comfortable with sharing their lives and those of their children online. The trend of oversharing on social media has raised public attention in the 2010s and become the focus of a number of editorials and academic research projects. It was also added to Times Word of the Day in February 2013 and Collins English Dictionary in 2016 given its influence. == Popularity == Several studies describe sharenting as an international phenomenon with widespread prevalence across households. In the United States, researchers at the University of Michigan C.S. Mott Children's Hospital found that almost 75% of American parents were familiar with someone who over-shared information about their child on social media, and an AVG survey determined that 92% of all American two-year-olds had some presence on the internet. In Australia, Fisher-Price conducted a survey which revealed that 90% of Australian parents admitted to over-sharing. In Spain and Czech Republic, a survey of approximately 1,500 parents found that 70-80% participated in sharenting. In the United Kingdom, France, Germany, and Italy, a Research Now report revealed that almost three-quarters of surveyed parents said that they were "willing to share images of their infants". Some claim that sharenting presents a violation of child privacy, and this backlash includes anti-sharenting sites and apps that block baby pictures. One particular outlet of protest was the blog STFU Parents, founded in 2009 to criticize parental oversharing on social media. Some parents felt that these criticisms of sharenting often took posts out of context and neglected some positive aspects of the practice, including advancing a stronger sense of online community. Others, while acknowledging the potential privacy violations of sharenting, suggested a more tailored approach that would only permit posting under certain conditions, notwithstanding audience and identification restrictions for social media posts. == Motivations == Research has suggested that sharenting is associated with a mix of parent self-identification with children, mothering pressures, and the accessibility of social media. Conducting 17 interviews with mothers in the United Kingdom, a London School of Economics study found that parent bloggers often re-explained their sharing practices in terms of expressing their own personal identity, representing their own child as part of themselves. In particular, the report surveyed the use of blogs as a networking vehicle to connect parents with similar family situations and found that sharenting parents, by filtering self-presentation through their parent-child relationship, adopted a more relational identity on social media websites. This included identifying oneself in terms of parental circumstances, whether it be raising a child with a disability or being a single mother. Alternatively, some have suggested that these online expressions indicate the infiltration of individual pride into the sphere of parenting, as family photography becomes a means to "show off" one's children to the others and strengthens a parent's sense of individuated self. Addressing the prevalence of mothers engaging in sharenting, those who purport this view argue that the rise of digital communication has pressured mothers into performing the role of a "good" parent on social media platforms. They claim that these developments may reinforce a dominant vision of a "normal" family, as sharenting posts could be motivated by the need to converge to a normative interpretation of family. == Controversy == While some people assert that online platforms enable parents to establish a community and seek parenting support, others are concerned about the children's data privacy and their lack of informed consent. Sharing content may not only embarrass children but also creates an initial digital footprint, a history of online activity, that the children themselves have no control over. This might bring some negative consequences, such as being ridiculed at school or leaving a negative impression on future employers. === Parental benefits === Many parents use social media to seek parenting advice and share information about their children. With the convenience of online platforms, parent bloggers can easily connect with other people in similar situations as well as those who are willing to contribute meaningful advice. By forming a community, parents can receive encouragement from empathetic peers and assistance from experts in children rearing. Parents whose children need special educational accommodations or have disabilities often found themselves detached from the mainstream parenting style. Therefore, they regard online blogs as a means to gain support from others and support back. Online blogging enables parents of children with disabilities and special needs to connect with other parents. The advice from similarly situated families can open up new possibilities that help the parents "negotiate the complexities of social services, health care, and schools". However, in some cases, posting online about a parent's struggles can cause a backlash, as advocates may accuse the parent of presenting people with that condition in a bad light, or wonder how the child will feel, if they later read these posts and see how much their parents struggled to care for them. Such advantages of social media are not limited to particular groups of parents. In general, most parents benefit from exchanging parenting experience. Statistically speaking, 72% of parents rate social media useful for emotional connection and affirmations, and 74% of them receive support about parenting from friends on social media. Sharenting also plays a role in fostering interpersonal relationships. As the images and words about children's lives initiate conversations, parents use sharenting to stay connected with distant friends and relatives. In particular, mothers, as a research study reveals, are willing to engage in sharenting since they believe that the positive contents can help avoid digital conflicts and maintain close relations with those in their social circles. Researchers also found that female participants in this study carefully chose photos and phrases to express love and present laudable behaviors of children in their updates, which indicates their intention to convey positive messages. These messages also promote a close social network for a child as the parents invites supportive family members and friends into daily life. === Children's privacy === Given the potential misuse of digital data, people are critical about sharenting, and the majority of parents are cautious about the wrongdoing with online posts. The disclosure of minors' personal information, such as geographic location, name, date of birth, pictures, and the schools they attend, might expose them to illegal practices by recipients with malicious intentions. Sharented information is often abused for "identity theft", when imposters manage to track, stalk, commit fraud against children, or even blackmail the family. According to Barclays, online fraud targeting the young generation will contribute to a loss of £670 million (approximately $790 million) by 2030, and two-thirds of identity fraud will be related to s
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A data steward is an oversight or data governance role within an organization, and is responsible for ensuring the quality and fitness for purpose of the organization's data assets, including the metadata for those data assets. A data steward may share some responsibilities with a data custodian, such as the awareness, accessibility, release, appropriate use, security and management of data. A data steward would also participate in the development and implementation of data assets. A data steward may seek to improve the quality and fitness for purpose of other data assets their organization depends upon but is not responsible for. Data stewards have a specialist role that utilizes an organization's data governance processes, policies, guidelines and responsibilities for administering an organizations' entire data in compliance with policy and/or regulatory obligations (e.g., GDPR, HIPAA). The overall objective of a data steward is the data quality of the data assets, datasets, data records and data elements. This includes documenting metainformation for the data, such as definitions, related rules/governance, physical manifestation, and related data models (most of these properties being specific to an attribute/concept relationship), identifying owners/custodian's various responsibilities, relations insight pertaining to attribute quality, aiding with project requirement data facilitation and documentation of capture rules. Data stewards begin the stewarding process with the identification of the data assets and elements which they will steward, with the ultimate result being standards, controls and data entry. The steward works closely with business glossary standards analysts (for standards), with data architect/modelers (for standards), with DQ analysts (for controls) and with operations team members (good-quality data going in per business rules) while entering data. Data stewardship roles are common when organizations attempt to exchange data precisely and consistently between computer systems and to reuse data-related resources. Master data management often makes references to the need for data stewardship for its implementation to succeed. Data stewardship must have precise purpose, fit for purpose or fitness. == Data steward responsibilities == A data steward ensures that each assigned data element: Has clear and unambiguous data element definition Does not conflict with other data elements in the metadata registry (removes duplicates, overlap etc.) Has clear enumerated value definitions if it is of type Code Is still being used (remove unused data elements) Is being used consistently in various computer systems Is being used, fit for purpose = Data Fitness Has adequate documentation on appropriate usage and notes Documents the origin and sources of authority on each metadata element Is protected against unauthorised access or change Responsibilities of data stewards vary between different organisations and institutions. For example, at Delft University of Technology, data stewards are perceived as the first contact point for any questions related to research data. They also have subject-specific background allowing them to easily connect with researchers and to contextualise data management problems to take into account disciplinary practices. == Types of data stewards == Depending on the set of data stewardship responsibilities assigned to an individual, there are 4 types (or dimensions of responsibility) of data stewards typically found within an organization: Data object data steward - responsible for managing reference data and attributes of one business data entity Business data steward - responsible for managing critical data, both reference and transactional, created or used by one business function. The data steward may also serve as a liaison between the organization's data users and technical teams, helping to bridge the gap between business needs and technical requirements. They may also play a role in educating others within the organization about best practices for data management, and advocating for data-driven decision-making. Process data steward - responsible for managing data across one business process System data steward - responsible for managing data for at least one IT system == Benefits of data stewardship == Systematic data stewardship can foster: Faster analysis Consistent use of data management resources Easy mapping of data between computer systems and exchange documents Lower costs associated with migration to (for example) service-oriented architecture (SOA) Mitigation of data risk Better control of dangers associated with privacy, legal, errors, etc. Assignment of each data element to a person sometimes seems like an unimportant process. But multiple groups have found that users have greater trust and usage rates in systems where they can contact a person with questions on each data element. == Examples == Delft University of Technology (TU Delft) offers an example of data stewardship implementation at a research institution. In 2017 the Data Stewardship Project was initiated at TU Delft to address research data management needs in a disciplinary manner across the whole campus. Dedicated data stewards with subject-specific background were appointed at every TU Delft faculty to support researchers with data management questions and to act as a linking point with the other institutional support services. The project is coordinated centrally by TU Delft Library, and it has its own website, blog and a YouTube channel. The [1]EPA metadata registry furnishes an example of data stewardship. Note that each data element therein has a "POC" (point of contact). In 2023, ETH Zurich launched the Data Stewardship Network (DSN) to facilitate collaboration among employees engaged in data management, analysis, and code development across research groups. The DSN serves as a platform for networking and knowledge exchange, aiming to professionalize the role of data stewards who support research data management and reproducible workflows. Established by the team for Research Data Management and Digital Curation at the ETH Library, the DSN collaborates with Scientific IT Services to provide expertise in areas such as storage infrastructure and reproducible workflows. == Data stewardship applications == Information stewardship applications are business solutions used by business users acting in the role of information steward (interpreting and enforcing information governance policy, for example). These developing solutions represent, for the most part, an amalgam of a number of disparate, previously IT-centric tools already on the market, but are organized and presented in such a way that information stewards (a business role) can support the work of information policy enforcement as part of their normal, business-centric, day-to-day work in a range of use cases. The initial push for the formation of this new category of packaged software came from operational use cases — that is, use of business data in and between transactional and operational business applications. This is where most of the master data management efforts are undertaken in organizations. However, there is also now a faster-growing interest in the new data lake arena for more analytical use cases.
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In 3D computer graphics, ray tracing is a technique for modeling light transport for use in a wide variety of rendering algorithms for generating digital images. On a spectrum of computational cost and visual fidelity, ray tracing-based rendering techniques, such as ray casting, recursive ray tracing, distribution ray tracing, photon mapping and path tracing, are generally slower and higher fidelity than scanline rendering methods. Thus, ray tracing was first deployed in applications where taking a relatively long time to render could be tolerated, such as still CGI images, and film and television visual effects (VFX), but was less suited to real-time applications such as video games, where speed is critical in rendering each frame. Since 2018, however, hardware acceleration for real-time ray tracing has become standard on new commercial graphics cards, and graphics APIs have followed suit, allowing developers to use hybrid ray tracing and rasterization-based rendering in games and other real-time applications with a lesser hit to frame render times. Ray tracing is capable of simulating a variety of optical effects, such as reflection, refraction, soft shadows, scattering, depth of field, motion blur, caustics, ambient occlusion and dispersion phenomena (such as chromatic aberration). It can also be used to trace the path of sound waves in a similar fashion to light waves, making it a viable option for more immersive sound design in video games by rendering realistic reverberation and echoes. In fact, any physical wave or particle phenomenon with approximately linear motion can be simulated with ray tracing. Ray tracing–based rendering techniques that sample light over a domain typically generate multiple rays and often rely on denoising to reduce the resulting noise. == History == The idea of ray tracing comes from as early as the 16th century, when it was described by Albrecht Dürer, who is credited for its invention. Dürer described multiple techniques for projecting 3-D scenes onto an image plane. Some of these project chosen geometry onto the image plane, as is done with rasterization today. Others determine what geometry is visible along a given ray, as is done with ray tracing. Using a computer for ray tracing to generate shaded pictures was first accomplished by Arthur Appel in 1968. Appel used ray tracing for primary visibility (determining the closest surface to the camera at each image point) by tracing a ray through each point to be shaded into the scene to identify the visible surface. The closest surface intersected by the ray was the visible one. This non-recursive ray tracing-based rendering algorithm is today called "ray casting". His algorithm then traced secondary rays to the light source from each point being shaded to determine whether the point was in shadow or not. Later, in 1971, Goldstein and Nagel of MAGI (Mathematical Applications Group, Inc.) published "3-D Visual Simulation", wherein ray tracing was used to make shaded pictures of solids. At the ray-surface intersection point found, they computed the surface normal and, knowing the position of the light source, computed the brightness of the pixel on the screen. Their publication describes a short (30-second) film "made using the University of Maryland's display hardware outfitted with a 16mm camera. The film showed the helicopter and a simple ground-level gun emplacement. The helicopter was programmed to undergo a series of maneuvers including turns, take-offs, and landings, etc., until it eventually is shot down and crashed." A CDC 6600 computer was used. MAGI produced an animation video called MAGI/SynthaVision Sampler in 1974. Another early instance of ray casting came in 1976, when Scott Roth created a flip book animation in Bob Sproull's computer graphics course at Caltech. The scanned pages are shown as a video in the accompanying image. Roth's computer program noted an edge point at a pixel location if the ray intersected a bounded plane different from that of its neighbors. Of course, a ray could intersect multiple planes in space, but only the surface point closest to the camera was noted as visible. The platform was a DEC PDP-10, a Tektronix storage-tube display, and a printer which would create an image of the display on rolling thermal paper. Roth extended the framework, introduced the term ray casting in the context of computer graphics and solid modeling, and in 1982 published his work while at GM Research Labs. Turner Whitted was the first to show recursive ray tracing for mirror reflection and for refraction through translucent objects, with an angle determined by the solid's index of refraction, and to use ray tracing for anti-aliasing. Whitted also showed ray traced shadows. He produced a recursive ray traced film called The Compleat Angler in 1979 while an engineer at Bell Labs. Whitted's deeply recursive ray tracing algorithm reframed rendering from being primarily a matter of surface visibility determination to being a matter of light transport. His paper inspired a series of subsequent work by others that included distribution ray tracing and finally unbiased path tracing, which provides the rendering equation framework that has allowed computer-generated imagery to be faithful to reality. For decades, global illumination in major films using computer-generated imagery was approximated with additional lights. Ray tracing-based rendering eventually changed that by enabling physically based light transport. Early feature films rendered entirely using path tracing include Monster House (2006), Cloudy with a Chance of Meatballs (2009), and Monsters University (2013). == Algorithm overview == Optical ray tracing describes a method for producing visual images constructed in 3D computer graphics environments, with more photorealism than either ray casting or scanline rendering techniques. It works by tracing a path from an imaginary eye through each pixel in a virtual screen, and calculating the color of the object visible through it. Scenes in ray tracing are described mathematically by a programmer or by a visual artist (normally using intermediary tools). Scenes may also incorporate data from images and models captured by means such as digital photography. Typically, each ray must be tested for intersection with some subset of all the objects in the scene. Once the nearest object has been identified, the algorithm will estimate the incoming light at the point of intersection, examine the material properties of the object, and combine this information to calculate the final color of the pixel. Certain illumination algorithms and reflective or translucent materials may require more rays to be re-cast into the scene. It may at first seem counterintuitive or "backward" to send rays away from the camera, rather than into it (as actual light does in reality), but doing so is many orders of magnitude more efficient. Since the overwhelming majority of light rays from a given light source do not make it directly into the viewer's eye, a "forward" simulation could potentially waste a tremendous amount of computation on light paths that are never recorded. Therefore, the shortcut taken in ray tracing is to presuppose that a given ray intersects the view frame. After either a maximum number of reflections or a ray traveling a certain distance without intersection, the ray ceases to travel and the pixel's value is updated. === Calculate rays for rectangular viewport === On input we have (in calculation we use vector normalization and cross product): E ∈ R 3 {\displaystyle E\in \mathbb {R^{3}} } eye position T ∈ R 3 {\displaystyle T\in \mathbb {R^{3}} } target position θ ∈ [ 0 , π ] {\displaystyle \theta \in [0,\pi ]} field of view - for humans, we can assume ≈ π / 2 rad = 90 ∘ {\displaystyle \approx \pi /2{\text{ rad}}=90^{\circ }} m , k ∈ N {\displaystyle m,k\in \mathbb {N} } numbers of square pixels on viewport vertical and horizontal direction i , j ∈ N , 1 ≤ i ≤ k ∧ 1 ≤ j ≤ m {\displaystyle i,j\in \mathbb {N} ,1\leq i\leq k\land 1\leq j\leq m} numbers of actual pixel v → ∈ R 3 {\displaystyle {\vec {v}}\in \mathbb {R^{3}} } vertical vector which indicates where is up and down, usually v → = [ 0 , 1 , 0 ] {\displaystyle {\vec {v}}=[0,1,0]} - roll component which determine viewport rotation around point C (where the axis of rotation is the ET section) The idea is to find the position of each viewport pixel center P i j {\displaystyle P_{ij}} which allows us to find the line going from eye E {\displaystyle E} through that pixel and finally get the ray described by point E {\displaystyle E} and vector R → i j = P i j − E {\displaystyle {\vec {R}}_{ij}=P_{ij}-E} (or its normalization r → i j {\displaystyle {\vec {r}}_{ij}} ). First we need to find the coordinates of the bottom left viewport pixel P 1 m {\displaystyle P_{1m}} and find the next pixel by making a shift along directions parallel to viewport (vectors b → n {\displaystyle {\vec {b}}_{n
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Key Transparency allows communicating parties to verify public keys used in end-to-end encryption. In many end-to-end encryption services, to initiate communication a user will reach out to a central server and request the public keys of the user with which they wish to communicate. If the central server is malicious or becomes compromised, a man-in-the-middle attack can be launched through the issuance of incorrect public keys. The communications can then be intercepted and manipulated. Additionally, legal pressure could be applied by surveillance agencies to manipulate public keys and read messages. With Key Transparency, public keys are posted to a public log that can be universally audited. Communicating parties can verify public keys used are accurate.
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Omni-Path Architecture (OPA) is a high-performance communication architecture developed by Intel. It aims for low communication latency, low power consumption and a high throughput. It directly competes with InfiniBand. Intel planned to develop technology based on this architecture for exascale computing. The current owner of Omni-Path is Cornelis Networks. == History == Production of Omni-Path products started in 2015 and delivery of these products started in the first quarter of 2016. In November 2015, adapters based on the 2-port "Wolf River" ASIC were announced, using QSFP28 connectors with channel speeds up to 100 Gbit/s. Simultaneously, switches based on the 48-port "Prairie River" ASIC were announced. First models of that series were available starting in 2015. In April 2016, implementation of the InfiniBand "verbs" interface for the Omni-Path fabric was discussed. In October 2016, IBM, Hewlett Packard Enterprise, Dell, Lenovo, Samsung, Seagate Technology, Micron Technology, Western Digital and SK Hynix announced a joint consortium called Gen-Z to develop an open specification and architecture for non-volatile storage and memory products—including Intel's 3D Xpoint technology—which might in part compete against Omni-Path. Intel offered their Omni-Path products and components via other (hardware) vendors. For example, Dell EMC offered Intel Omni-Path as Dell Networking H-series, following the naming-standard of Dell Networking in 2017. In July 2019, Intel announced it would not continue development of Omni-Path networks and canceled OPA 200 series (200-Gbps variant of Omni-Path). In September 2020, Intel announced that the Omni-Path network products and technology would be spun out into a new venture with Cornelis Networks. Intel would continue to maintain support for legacy Omni-Path products, while Cornelis Networks continues the product line, leveraging existing Intel intellectual property related to Omni-Path architecture. In 2021, Cornelis announced Omni-Path Express, which replaces PSM2-based drivers and middleware, which trace back to PathScale's PSM created in 2003, for the existing Omni-Path hardware, with a native libfabric provider.
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A social news website is a website that features user-posted stories. Such stories are ranked based on popularity, as voted on by other users of the site or by website administrators. Users typically comment online on the news posts and these comments may also be ranked in popularity. Since their emergence with the birth of Web 2.0, social news sites have been used to link many types of information, including news, humor, support, and discussion. All such websites allow the users to submit content and each site differs in how the content is moderated. On the Slashdot and Fark websites, administrators decide which articles are selected for the front page. On Reddit and Digg, the articles that get the most votes from the community of users will make it to the front page. Many social news websites also feature an online comment system, where users discuss the issues raised in an article. Some of these sites have also applied their voting system to the comments, so that the most popular comments are displayed first. Some social news websites also have a social networking service, in that users can set up a user profile and follow other users' online activity on the website. Like many other Web 2.0 tools, social news websites use the collective intelligence of all of the users to operate. Social news websites also "impl[y] the technical, economic, legal, and human enhancement of a universally distributed intelligence that will unleash a positive dynamic of recognition and skills mobilization". Social news websites help participants to share a collective vision and awareness of how their actions are integrated with those of other individuals. Social news websites provide a new and innovative way to participate in a community that is constantly being flooded with new information. These social news websites "include opportunities for peer-to-peer learning, a changed attitude toward intellectual property, the diversification of cultural expression, the development of skills valued in the modern workplace, and a more empowered conception of citizenship". These websites can help to shape and reshape democratic opinions and perspectives. Social news sites may mitigate the gatekeeping of mainstream news sources and allow the public to decide what counts as "news", which may facilitate a more participatory culture. Social news sites may also support democratic participation by allowing users from across geographic and national boundaries to access the same information, respond to fellow users' views and beliefs, and create a virtual sphere for users to contribute within. == Websites == === Active === ==== Fark ==== Fark, which started in 1997, features news on any topic. On Fark, users can submit articles to the administrators of the site. Each day, these administrators pick out 50 articles to display on the front page. ==== Slashdot ==== Slashdot, started in 1997, was one of the first social news websites. It focuses mainly on science and technology-related news. Users can submit stories and the editors pick out the best stories each day for the front page. Users can then post comments on the stories. The influx of web traffic that resulted from Slashdot linking to external websites led to the effect being called the Slashdot effect ==== Digg ==== Digg, started in December 2004, introduced the voting system. This system allows users to "digg" or "bury" articles. "Digging" is the equivalent of voting positively, so that popular articles are displayed first. "Burying" does not lower an article's score. However, if an article is buried enough times, it will be automatically deleted from the site. Digg offers a social networking service, as members can follow other members and build personal profiles with information about their interests. ==== Reddit ==== Reddit, started in June 2005, is a social news website where users can submit articles and comments and vote on these submissions. The submissions are organized into categories called "subreddits". Unlike Digg, with Reddit, users can directly affect an article's score. An "upvote" will increase the score and a "downvote" will decrease it. Articles with the highest scores are displayed on the front page. There is also a page for "controversial" articles, that have an almost equal number of upvotes and downvotes. Free speech debates have arisen due to the shutting down of obscene or potentially illegal "subreddits" (including /r/jailbait, a collection of sexually suggestive underage pictures.) Reddit introduced a system of user-created communities called "subreddits", which are essentially categories for a specific type of news. Comments on the featured posts are shown in a hierarchical fashion also based on votes. Users have the ability to earn "karma" for their participation and time on the website. ==== Hacker News ==== Hacker News, started in February 2007, is a social news site focusing on computer science and entrepreneurship, created by Paul Graham and run by his startup incubator, Y Combinator. === Defunct === ==== Newsvine ==== Newsvine, started in March 2006, was a social news website mostly focused on politics, both international and domestic. The Newsvine home page allowed users to customize "seeds" and story feeds. Users received articles via "The Wire" from sources including The Associated Press or The Huffington Post, and from "The Vine" a stream of content from other Newsvine users. The "Top of the Vine" displayed the most voted and commented on articles of the day, week, month, or year. Additionally, Newsvine allowed members to create their own "Customizable Column", which could highlight a user's content posted, recent comments, and information about the specific Newsvine member. ==== feedalizr ==== feedalizr was a cross-platform, desktop social media aggregator built using Adobe Integrated Runtime that consolidates the updates from social media and social networking websites. Users can then use this application to update those sites from their desktop and view a consolidated stream of information. ==== Voat ==== Voat, launched in April 2014 and discontinued in December of 2020, was also a social news website and is very similar to Reddit visually and functionally. The site's userbase included a large number of alt right users, many of whom migrated to Voat after being banned on Reddit. ==== Prismatic ==== Prismatic combined machine learning, user experience design, and interaction design to create a new way to discover, consume, and share media. Prismatic software used social network aggregation and machine learning algorithms to filter the content that aligns with the interests of a specific user. Prismatic integrated with Facebook, Twitter, and Pocket to gather information about user's interests and suggest the most relevant stories to read. ==== Artifact ==== Artifact was an iOS and Android app that used machine learning to personalize news recommendations to readers, and also had social features such as liking articles, commenting, and reputation scores for users.
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A biometric device is a security identification and authentication device. Such devices use automated methods of verifying or recognising the identity of a living person based on a physiological or behavioral characteristic. These characteristics include fingerprints, facial images, iris and voice recognition. == History == Biometric devices have been in use for thousands of years. Non-automated biometric devices have been in use since 500 BC, when ancient Babylonians would sign their business transactions by pressing their fingertips into clay tablets. Automation in biometric devices was first seen in the 1960s. The Federal Bureau of Investigation (FBI) in the 1960s, introduced the Indentimat, which started checking for fingerprints to maintain criminal records. The first systems measured the shape of the hand and the length of the fingers. Although discontinued in the 1980s, the system set a precedent for future Biometric Devices. == Subgroups == The characteristic of the human body is used to access information by the users. According to these characteristics, the sub-divided groups are Chemical biometric devices: Analyses the segments of the DNA to grant access to the users. Visual biometric devices: Analyses the visual features of the humans to grant access which includes iris recognition, face recognition, Finger recognition, and Retina Recognition. Behavioral biometric devices: Analyses the Walking Ability and Signatures (velocity of sign, width of sign, pressure of sign) distinct to every human. Olfactory biometric devices: Analyses the odor to distinguish between varied users. Auditory biometric devices: Analyses the voice to determine the identity of a speaker for accessing control. == Uses == === Workplace === Biometrics are being used to establish better and accessible records of the hour's employee's work. With the increase in "Buddy Punching" (a case where employees clocked out coworkers and fraudulently inflated their work hours) employers have looked towards new technology like fingerprint recognition to reduce such fraud. Additionally, employers are also faced with the task of proper collection of data such as entry and exit times. Biometric devices make for largely fool proof and reliable ways of enabling to collect data as employees have to be present to enter biometric details which are unique to them. === Immigration === As the demand for air travel grows and more people travel, modern-day airports have to implement technology in such a way that there are no long queues. Biometrics are being implemented in more and more airports as they enable quick recognition of passengers and hence lead to lower volume of people standing in queues. One such example is of the Dubai International Airport which plans to make immigration counters a relic of the past as they implement IRIS on the move technology (IOM) which should help the seamless departures and arrivals of passengers at the airport. === Handheld and personal devices === Fingerprint sensors can be found on mobile devices. The fingerprint sensor is used to unlock the device and authorize actions, like money and file transfers, for example. It can be used to prevent a device from being used by an unauthorized person. It is also used in attendance in number of colleges and universities. == Present day biometric devices == === Personal signature verification systems === This is one of the most highly recognised and acceptable biometrics in corporate surroundings. This verification has been taken one step further by capturing the signature while taking into account many parameters revolving around this like the pressure applied while signing, the speed of the hand movement and the angle made between the surface and the pen used to make the signature. This system also has the ability to learn from users as signature styles vary for the same user. Hence by taking a sample of data, this system is able to increase its own accuracy. === Iris recognition system === Iris recognition involves the device scanning the pupil of the subject and then cross referencing that to data stored on the database. It is one of the most secure forms of authentication, as while fingerprints can be left behind on surfaces, iris prints are extremely hard to be stolen. Iris recognition is widely applied by organisations dealing with the masses, one being the Aadhaar identification system issued by the Government of India to keep records of its population. The reason for this is that iris recognition makes use of iris prints of humans, which change little over the course of one's lifetime. == Problems with present day biometric devices == === Biometric spoofing === Biometric spoofing is a method of fooling a biometric identification management system, where a counterfeit mold is presented in front of the biometric scanner. This counterfeit mold emulates the unique biometric attributes of an individual so as to confuse the system between the artifact and the real biological target and gain access to sensitive data/materials. One such high-profile case of Biometric spoofing came to the limelight when it was found that German Defence Minister, Ursula von der Leyen's fingerprint had been successfully replicated by Chaos Computer Club. The group used high quality camera lenses and shot images from 6 feet away. They used a professional finger software and mapped the contours of the Ministers thumbprint. Although progress has been made to stop spoofing. Using the principle of pulse oximetry — the liveliness of the test subject is taken into account by measure of blood oxygenation and the heart rate. This reduces attacks like the ones mentioned above, although these methods aren't commercially applicable as costs of implementation are high. This reduces their real world application and hence makes biometrics insecure until these methods are commercially viable. === Accuracy === Accuracy is a major issue with biometric recognition. Passwords are still extremely popular, because a password is static in nature, while biometric data can be subject to change (such as one's voice becoming heavier due to puberty, or an accident to the face, which could lead to improper reading of facial scan data). When testing voice recognition as a substitute to PIN-based systems, Barclays reported that their voice recognition system is 95 percent accurate. This statistic means that many of its customers' voices might still not be recognised even when correct. This uncertainty revolving around the system could lead to slower adoption of biometric devices, continuing the reliance of traditional password-based methods. == Benefits of biometric devices over traditional methods of authentication == Biometric data cannot be lent and hacking of Biometric data is complicated hence it makes it safer to use than traditional methods of authentication like passwords which can be lent and shared. Passwords do not have the ability to judge the user but rely only on the data provided by the user, which can easily be stolen while Biometrics work on the uniqueness of each individual. Passwords can be forgotten and recovering them can take time, whereas Biometric devices rely on biometric data which tends to be unique to a person, hence there is no risk of forgetting the authentication data. A study conducted among Yahoo! users found that at least 1.5 percent of Yahoo users forgot their passwords every month, hence this makes accessing services more lengthy for consumers as the process of recovering passwords is lengthy. These shortcomings make Biometric devices more efficient and reduces effort for the end user. == Future == Researchers are targeting the drawbacks of present-day biometric devices and developing to reduce problems like biometric spoofing and inaccurate intake of data. Technologies which are being developed are- The United States Military Academy are developing an algorithm that allows identification through the ways each individual interacts with their own computers; this algorithm considers unique traits like typing speed, rhythm of writing and common spelling mistakes. This data allows the algorithm to create a unique profile for each user by combining their multiple behavioral and stylometric information. This can be very difficult to replicate collectively. A recent innovation by Kenneth Okereafor and, presented an optimized and secure design of applying biometric liveness detection technique using a trait randomization approach. This novel concept potentially opens up new ways of mitigating biometric spoofing more accurately, and making impostor predictions intractable or very difficult in future biometric devices. A simulation of Kenneth Okereafor's biometric liveness detection algorithm using a 3D multi-biometric framework consisting of 15 liveness parameters from facial print, finger print and iris pattern traits resulted in a system efficiency of the 99.2% over a cardinality of 125 distinct randomization combinat
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The IBM 2780 and the IBM 3780 are devices developed by IBM for performing remote job entry (RJE) and other batch functions over telephone lines; they communicate with the mainframe via Binary Synchronous Communications (BSC or Bisync) and replaced older terminals using synchronous transmit-receive (STR). In addition, IBM has developed workstation programs for the 1130, 360/20, 2922, System/360 other than 360/20, System/370 and System/3. == 2780 Data Transmission Terminal == The 2780 Data Transmission Terminal first shipped in 1967. It consists of: A line printer similar to the IBM 1443 that can print up to 240 lines per minute (lpm), or 300 lpm using an extremely restricted character set. A card reader/punch unit, similar to an IBM 1442, that can read up to 400 cards per minute (cpm) and can punch up to 355 cpm. A line buffer that stores data received or to be transmitted over the communications line. A binary synchronous adapter which controls the flow of data over the communications line. The 2780 is capable of local (offline) card to print operation. It comes in four models: Model 1: Can read punched cards and transmit the data to a remote host computer, and can receive and print data sent by the host. Model 2: Same as Model 1 but adds the ability to punch card data received from the host. Model 3: Can only print data received from the host, but not send data to it. Model 4: Can read and punch card data, but has no printing capabilities. The 2780 uses a dedicated communication line at speeds of 1200, 2000, 2400 or 4800 bits per second. It is a half duplex device, although full duplex lines can be used with some increase in throughput. It can communicate in Transcode (a 6-bit code), 8-bit EBCDIC, or 7-bit ASCII. == 2770 Data Communication System == The 2770, announced in 1969, "was said to surpass all other IBM terminals in the variety of available input-output devices." The 2770 was developed by the IBM General Products Division (GPD) in Rochester, MN. It comes standard with a desktop terminal with keyboard. The printer and other devices (any two in any combination) can be attached to the 2772 Multi-Purpose Control unit. Possible devices include: 50 Magnetic Data Inscriber 545 Card Punch Model 3 (non-printing) or Model 4 (printing) 1017 Paper Tape Reader 1018 Paper Tape Punch 1053 Printer Model 1 1255 Magnetic Character Reader Models 1, 2 or 3 2203 Printer Model A1 or A2 2213 Printer Model 1 or 2 2265 Display Station Model 2 2502 Card Reader Model A1 or A2 5496 Data Recorder == 3780 Data Communications Terminal == In May 1972, IBM announced the IBM 3780, an enhanced version of the 2780. The 3780 was developed by IBM's Data Processing Division (DPD). There is one model, with an optional card punch. The 3780 drops Transcode support and incorporates several performance enhancements. It supports compression of blank fields in data using run-length encoding. It provides the ability to interleave data between devices, introduces double buffering, and adds support for the Wait-before-transmit ACKnowledgement (WACK) and Temporary Text Delay (TTD) Binary Synchronous control characters. The integrated punched card unit can read cards at 600 cards per minute. The integrated printer is rated at 300, 350 or 425 lines per minute based on characters set (63, 52 or 39 characters). The 3781 Card Punch is an optional feature. It punches 160 columns per second, or 91 cards per minute if all 80 columns are punched. The IBM 2780 and 3780 were later emulated on various types of equipment, including eventually the personal computer. A notable early emulation was the DN60, by Digital Equipment Corporation in the late 1970s. == 3770 Data Communications System == In 1974 IBM Data Processing Division (DPD) offered a successor to the 3780, called the 3770 Data Communications System, supporting SDLC, BSC, BSC Multi-leaving and SNA, depending on the configuration. The 3770 is a family of desk console style terminals that offers a variety of keyboard and printer combinations as well as I/O equipment attachment and communications features. The terminals come built into a desk and include the following models: 3771 Communication Terminal (optional card reader, optional card punch, wire matrix printer) Models 1 (40 cps printer), 2 (80 cps printer), and 3 (120 cps printer). 3773 Communication Terminal (diskette, wire matrix printer) Models 1 (40 cps printer), 2 (80 cps printer), and 3 (120 cps printer). Each model has a P version which adds some programming features. 3774 Communication Terminal (optional card reader, optional card punch, optional belt printer, wire matrix printer) Models 1 (80 cps printer), and 2 (120 cps printer). Each model has a P version which adds some programming features, a 480-character display and a non-removable diskette. 3775 Communication Terminal (optional card reader, optional card punch, optional diskette, belt printer) Model 1 (120 lpm printer). The model P1 adds some programming features, a 480-character display and a non-removable diskette. 3776 Communication Terminal (optional card reader, optional card punch, optional diskette, belt printer) Models 1 (300 lpm printer) and 2 (400 lpm printer). Models 3 and 4 are similar to models 1 and 2. 3777 Communication Terminal (optional card reader, optional diskette, train printer) Model 1 (up to 1000 lpm printer depending on character set). Model 2 adds an optional card punch, model 3 adds an optional magnetic tape drive and model 4 replaces the train printer with a slower model called the IBM 3262. The model 4 also allows a second, optional, 3262. The following I/O devices can be attached to a 3770 terminal: IBM 2502 Card Reader: Models A1 (up to 150 card per minute), A2 (up to 300 cards per minute) or A3 (up to 400 cards per minute) IBM 3203 Printer Model 3: 1000 LPM using 48 character set IBM 3501 Card Reader: Up to 50 cards per minute desktop unit IBM 3521 Card Punch: Up to 50 cards per minute IBM 3782 Card Attachment unit, which allows the 2502 or 3521 to be attached to any terminal except the 3777 IBM 3784 Line Printer, can be attached to a 3774 as a second printer. Up to 155 LPM with 48 characters set print belt. == Workstation programs == IBM distributes workstation programs with systems software including OS/360 Attached Support Processor (ASP) Houston Automatic Spooling Priority (HASP and HASP II) Operating System/Virtual Storage 1 (OS/VS1) Operating System/Virtual Storage 2 (OS/VS2 MVS) Release 2 through 3.8 MVS versions from MVS/SP Version 1 through z/OS Priority Output Writers, Execution processors and input Readers (POWER) Remote Spooling Communications Subsystem (RSCS) Except for the RJE workstation programs in OS/360, these programs use a variation of BSC known as Multi-leaving. In addition, IBM provides separately ordered workstation programs using BSC. Systems Network Architecture (SNA) and TCP/IP. Workstation programs are available from IBM and third-party vendors to support all of these protocols: 2770/3770 2780/3780 Multileaving Network Job Entry (NJE) OS/360 RJE SNA TCP/IP
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A social news website is a website that features user-posted stories. Such stories are ranked based on popularity, as voted on by other users of the site or by website administrators. Users typically comment online on the news posts and these comments may also be ranked in popularity. Since their emergence with the birth of Web 2.0, social news sites have been used to link many types of information, including news, humor, support, and discussion. All such websites allow the users to submit content and each site differs in how the content is moderated. On the Slashdot and Fark websites, administrators decide which articles are selected for the front page. On Reddit and Digg, the articles that get the most votes from the community of users will make it to the front page. Many social news websites also feature an online comment system, where users discuss the issues raised in an article. Some of these sites have also applied their voting system to the comments, so that the most popular comments are displayed first. Some social news websites also have a social networking service, in that users can set up a user profile and follow other users' online activity on the website. Like many other Web 2.0 tools, social news websites use the collective intelligence of all of the users to operate. Social news websites also "impl[y] the technical, economic, legal, and human enhancement of a universally distributed intelligence that will unleash a positive dynamic of recognition and skills mobilization". Social news websites help participants to share a collective vision and awareness of how their actions are integrated with those of other individuals. Social news websites provide a new and innovative way to participate in a community that is constantly being flooded with new information. These social news websites "include opportunities for peer-to-peer learning, a changed attitude toward intellectual property, the diversification of cultural expression, the development of skills valued in the modern workplace, and a more empowered conception of citizenship". These websites can help to shape and reshape democratic opinions and perspectives. Social news sites may mitigate the gatekeeping of mainstream news sources and allow the public to decide what counts as "news", which may facilitate a more participatory culture. Social news sites may also support democratic participation by allowing users from across geographic and national boundaries to access the same information, respond to fellow users' views and beliefs, and create a virtual sphere for users to contribute within. == Websites == === Active === ==== Fark ==== Fark, which started in 1997, features news on any topic. On Fark, users can submit articles to the administrators of the site. Each day, these administrators pick out 50 articles to display on the front page. ==== Slashdot ==== Slashdot, started in 1997, was one of the first social news websites. It focuses mainly on science and technology-related news. Users can submit stories and the editors pick out the best stories each day for the front page. Users can then post comments on the stories. The influx of web traffic that resulted from Slashdot linking to external websites led to the effect being called the Slashdot effect ==== Digg ==== Digg, started in December 2004, introduced the voting system. This system allows users to "digg" or "bury" articles. "Digging" is the equivalent of voting positively, so that popular articles are displayed first. "Burying" does not lower an article's score. However, if an article is buried enough times, it will be automatically deleted from the site. Digg offers a social networking service, as members can follow other members and build personal profiles with information about their interests. ==== Reddit ==== Reddit, started in June 2005, is a social news website where users can submit articles and comments and vote on these submissions. The submissions are organized into categories called "subreddits". Unlike Digg, with Reddit, users can directly affect an article's score. An "upvote" will increase the score and a "downvote" will decrease it. Articles with the highest scores are displayed on the front page. There is also a page for "controversial" articles, that have an almost equal number of upvotes and downvotes. Free speech debates have arisen due to the shutting down of obscene or potentially illegal "subreddits" (including /r/jailbait, a collection of sexually suggestive underage pictures.) Reddit introduced a system of user-created communities called "subreddits", which are essentially categories for a specific type of news. Comments on the featured posts are shown in a hierarchical fashion also based on votes. Users have the ability to earn "karma" for their participation and time on the website. ==== Hacker News ==== Hacker News, started in February 2007, is a social news site focusing on computer science and entrepreneurship, created by Paul Graham and run by his startup incubator, Y Combinator. === Defunct === ==== Newsvine ==== Newsvine, started in March 2006, was a social news website mostly focused on politics, both international and domestic. The Newsvine home page allowed users to customize "seeds" and story feeds. Users received articles via "The Wire" from sources including The Associated Press or The Huffington Post, and from "The Vine" a stream of content from other Newsvine users. The "Top of the Vine" displayed the most voted and commented on articles of the day, week, month, or year. Additionally, Newsvine allowed members to create their own "Customizable Column", which could highlight a user's content posted, recent comments, and information about the specific Newsvine member. ==== feedalizr ==== feedalizr was a cross-platform, desktop social media aggregator built using Adobe Integrated Runtime that consolidates the updates from social media and social networking websites. Users can then use this application to update those sites from their desktop and view a consolidated stream of information. ==== Voat ==== Voat, launched in April 2014 and discontinued in December of 2020, was also a social news website and is very similar to Reddit visually and functionally. The site's userbase included a large number of alt right users, many of whom migrated to Voat after being banned on Reddit. ==== Prismatic ==== Prismatic combined machine learning, user experience design, and interaction design to create a new way to discover, consume, and share media. Prismatic software used social network aggregation and machine learning algorithms to filter the content that aligns with the interests of a specific user. Prismatic integrated with Facebook, Twitter, and Pocket to gather information about user's interests and suggest the most relevant stories to read. ==== Artifact ==== Artifact was an iOS and Android app that used machine learning to personalize news recommendations to readers, and also had social features such as liking articles, commenting, and reputation scores for users.
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PitchYaGame or #PitchYaGame (sometimes abbreviated to PYG) is a volunteer movement hosted on the social media platform Twitter to showcase, and present awards for, independent video games from around the world. == Description == PitchYaGame is hosted on the social media platform Twitter to showcase independent video games from around the world. Video pitches are presented by developers in June and November each year, and use the hashtag #PitchYaGame to identify and reference news about the showcase and the individual pitches, and the presentation of awards. The showcase was founded in May 2020 by Liam Twose, with the mission of recognising independent video games, and "focused on empowering indie game developers to strengthen their position in the industry." Twose has made clear that PitchYaGame is a showcase and not a hardcore competition, with "[j]ust enough of a push to make sure people put their best pitch forward." The team now comprises Twose (@LiamTwose at Twitter), operations manager "Indie Game Lover" (@IndieGameLover), and host Sarah Clancy (@ImSarahNow). The pitches were originally made monthly, with entries split into a number of categories, but this proved unmanageable. PitchYaGame collaborator, Sarah Clancy reported that judging the many entries on a monthly basis was "difficult and unwieldy." Therefore, pitches were later switched to six monthly, "feature creep" was reduced, and awards streamlined into gold, silver, bronze, runners-up, and most viral. == Sponsorship == In June 2021, PitchYaGame prizes were sponsored by Xsolla, and in November 2021 by Aurora Punks and Cold Pixel. No cash prizes were available in 2022, as the organisers moved PitchYaGame into a less-competitive, "more showcase centric format". == Reception == In October 2020, Elijah Beahm at The Escapist wrote that "One of the greatest challenges for any game is landing a solid pitch. You have to sell people, maybe even a publisher, to take your idea seriously. Most of the time, it's an obfuscated process that leaves the average developer scratching their heads, but Liam Twose and his team behind #PitchYaGame, 'PYG' for short, are looking to change all that with some clever social engineering." In March 2021, Cameron Koch at GameSpot wrote that "Using the #PitchYaGame, thousands of indie developers tweeted out pitches for their games on November 2 as part of a social media contest, and the results are astounding." He went on to say that "There is no arguing with the results. According to Twose, around 1100-1300 games were shared with the hashtag, and some real gems look to have shined through." In November 2021, Stafano "Stef" Castelli at IGN Italia wrote that "I myself enjoyed 'browsing through' the competitors, discovering a handful of intriguing video games in development." (translated from Italian). In November 2022, Eric Bartelson at Premortem Games wrote that "It's a great way to get games noticed by fellow developers, but also publishers, investors and press." In June 2023, Mark Plunkett in Kotaku wrote about the impossibility of keeping up with all the video game releases, and described PitchYaGame, which has attracted over 10,000 pitches since 2020, as an "astoundingly simple idea" that has "become an increasingly useful spot to catch up on some excellent-looking games that we may have otherwise completely slept on."
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Visual servoing, also known as vision-based robot control and abbreviated VS, is a technique which uses feedback information extracted from a vision sensor (visual feedback) to control the motion of a robot. One of the earliest papers that talks about visual servoing was from the SRI International Labs in 1979. == Visual servoing taxonomy == There are two fundamental configurations of the robot end-effector (hand) and the camera: Eye-in-hand, or end-point open-loop control, where the camera is attached to the moving hand and observing the relative position of the target. Eye-to-hand, or end-point closed-loop control, where the camera is fixed in the world and observing the target and the motion of the hand. Visual Servoing control techniques are broadly classified into the following types: Image-based (IBVS) Position/pose-based (PBVS) Hybrid approach IBVS was proposed by Weiss and Sanderson. The control law is based on the error between current and desired features on the image plane, and does not involve any estimate of the pose of the target. The features may be the coordinates of visual features, lines or moments of regions. IBVS has difficulties with motions very large rotations, which has come to be called camera retreat. PBVS is a model-based technique (with a single camera). This is because the pose of the object of interest is estimated with respect to the camera and then a command is issued to the robot controller, which in turn controls the robot. In this case the image features are extracted as well, but are additionally used to estimate 3D information (pose of the object in Cartesian space), hence it is servoing in 3D. Hybrid approaches use some combination of the 2D and 3D servoing. There have been a few different approaches to hybrid servoing 2-1/2-D Servoing Motion partition-based Partitioned DOF Based == Survey == The following description of the prior work is divided into 3 parts Survey of existing visual servoing methods. Various features used and their impacts on visual servoing. Error and stability analysis of visual servoing schemes. === Survey of existing visual servoing methods === Visual servo systems, also called servoing, have been around since the early 1980s , although the term visual servo itself was only coined in 1987. Visual Servoing is, in essence, a method for robot control where the sensor used is a camera (visual sensor). Servoing consists primarily of two techniques, one involves using information from the image to directly control the degrees of freedom (DOF) of the robot, thus referred to as Image Based Visual Servoing (IBVS). While the other involves the geometric interpretation of the information extracted from the camera, such as estimating the pose of the target and parameters of the camera (assuming some basic model of the target is known). Other servoing classifications exist based on the variations in each component of a servoing system , e.g. the location of the camera, the two kinds are eye-in-hand and hand–eye configurations. Based on the control loop, the two kinds are end-point-open-loop and end-point-closed-loop. Based on whether the control is applied to the joints (or DOF) directly or as a position command to a robot controller the two types are direct servoing and dynamic look-and-move. Being one of the earliest works the authors proposed a hierarchical visual servo scheme applied to image-based servoing. The technique relies on the assumption that a good set of features can be extracted from the object of interest (e.g. edges, corners and centroids) and used as a partial model along with global models of the scene and robot. The control strategy is applied to a simulation of a two and three DOF robot arm. Feddema et al. introduced the idea of generating task trajectory with respect to the feature velocity. This is to ensure that the sensors are not rendered ineffective (stopping the feedback) for any the robot motions. The authors assume that the objects are known a priori (e.g. CAD model) and all the features can be extracted from the object. The work by Espiau et al. discusses some of the basic questions in visual servoing. The discussions concentrate on modeling of the interaction matrix, camera, visual features (points, lines, etc..). In an adaptive servoing system was proposed with a look-and-move servoing architecture. The method used optical flow along with SSD to provide a confidence metric and a stochastic controller with Kalman filtering for the control scheme. The system assumes (in the examples) that the plane of the camera and the plane of the features are parallel., discusses an approach of velocity control using the Jacobian relationship s˙ = Jv˙ . In addition the author uses Kalman filtering, assuming that the extracted position of the target have inherent errors (sensor errors). A model of the target velocity is developed and used as a feed-forward input in the control loop. Also, mentions the importance of looking into kinematic discrepancy, dynamic effects, repeatability, settling time oscillations and lag in response. Corke poses a set of very critical questions on visual servoing and tries to elaborate on their implications. The paper primarily focuses the dynamics of visual servoing. The author tries to address problems like lag and stability, while also talking about feed-forward paths in the control loop. The paper also, tries to seek justification for trajectory generation, methodology of axis control and development of performance metrics. Chaumette in provides good insight into the two major problems with IBVS. One, servoing to a local minima and second, reaching a Jacobian singularity. The author show that image points alone do not make good features due to the occurrence of singularities. The paper continues, by discussing the possible additional checks to prevent singularities namely, condition numbers of J_s and Jˆ+_s, to check the null space of ˆ J_s and J^T_s . One main point that the author highlights is the relation between local minima and unrealizable image feature motions. Over the years many hybrid techniques have been developed. These involve computing partial/complete pose from Epipolar Geometry using multiple views or multiple cameras. The values are obtained by direct estimation or through a learning or a statistical scheme. While others have used a switching approach that changes between image-based and position-based on a Lyapnov function. The early hybrid techniques that used a combination of image-based and pose-based (2D and 3D information) approaches for servoing required either a full or partial model of the object in order to extract the pose information and used a variety of techniques to extract the motion information from the image. used an affine motion model from the image motion in addition to a rough polyhedral CAD model to extract the object pose with respect to the camera to be able to servo onto the object (on the lines of PBVS). 2-1/2-D visual servoing developed by Malis et al. is a well known technique that breaks down the information required for servoing into an organized fashion which decouples rotations and translations. The papers assume that the desired pose is known a priori. The rotational information is obtained from partial pose estimation, a homography, (essentially 3D information) giving an axis of rotation and the angle (by computing the eigenvalues and eigenvectors of the homography). The translational information is obtained from the image directly by tracking a set of feature points. The only conditions being that the feature points being tracked never leave the field of view and that a depth estimate be predetermined by some off-line technique. 2-1/2-D servoing has been shown to be more stable than the techniques that preceded it. Another interesting observation with this formulation is that the authors claim that the visual Jacobian will have no singularities during the motions. The hybrid technique developed by Corke and Hutchinson, popularly called portioned approach partitions the visual (or image) Jacobian into motions (both rotations and translations) relating X and Y axes and motions related to the Z axis. outlines the technique, to break out columns of the visual Jacobian that correspond to the Z axis translation and rotation (namely, the third and sixth columns). The partitioned approach is shown to handle the Chaumette Conundrum discussed in. This technique requires a good depth estimate in order to function properly. outlines a hybrid approach where the servoing task is split into two, namely main and secondary. The main task is keep the features of interest within the field of view. While the secondary task is to mark a fixation point and use it as a reference to bring the camera to the desired pose. The technique does need a depth estimate from an off-line procedure. The paper discusses two examples for which depth estimates are obtained from robot odometry and by assuming that all
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The knapsack problem is the following problem in combinatorial optimization: Given a set of items, each with a weight and a value, determine which items to include in the collection so that the total weight is less than or equal to a given limit and the total value is as large as possible. It derives its name from the problem faced by someone who is constrained by a fixed-size knapsack and must fill it with the most valuable items. The problem often arises in resource allocation where the decision-makers have to choose from a set of non-divisible projects or tasks under a fixed budget or time constraint, respectively. The knapsack problem has been studied for more than a century, with early works dating back to 1897. The subset sum problem is a special case of the decision and 0-1 problems where for each kind of item, the weight equals the value: w i = v i {\displaystyle w_{i}=v_{i}} . In the field of cryptography, the term knapsack problem is often used to refer specifically to the subset sum problem. The subset sum problem is one of Karp's 21 NP-complete problems. == Applications == Knapsack problems appear in real-world decision-making processes in a wide variety of fields, such as finding the least wasteful way to cut raw materials, selection of investments and portfolios, selection of assets for asset-backed securitization, and generating keys for the Merkle–Hellman and other knapsack cryptosystems. One early application of knapsack algorithms was in the construction and scoring of tests in which the test-takers have a choice as to which questions they answer. For small examples, it is a fairly simple process to provide the test-takers with such a choice. For example, if an exam contains 12 questions each worth 10 points, the test-taker need only answer 10 questions to achieve a maximum possible score of 100 points. However, on tests with a heterogeneous distribution of point values, it is more difficult to provide choices. Feuerman and Weiss proposed a system in which students are given a heterogeneous test with a total of 125 possible points. The students are asked to answer all of the questions to the best of their abilities. Of the possible subsets of problems whose total point values add up to 100, a knapsack algorithm would determine which subset gives each student the highest possible score. A 1999 study of the Stony Brook University Algorithm Repository showed that, out of 75 algorithmic problems related to the field of combinatorial algorithms and algorithm engineering, the knapsack problem was the 19th most popular and the third most needed after suffix trees and the bin packing problem. == Definition == The most common problem being solved is the 0-1 knapsack problem, which restricts the number x i {\displaystyle x_{i}} of copies of each kind of item to zero or one. Given a set of n {\displaystyle n} items numbered from 1 up to n {\displaystyle n} , each with a weight w i {\displaystyle w_{i}} and a value v i {\displaystyle v_{i}} , along with a maximum weight capacity W {\displaystyle W} , maximize ∑ i = 1 n v i x i {\displaystyle \sum _{i=1}^{n}v_{i}x_{i}} subject to ∑ i = 1 n w i x i ≤ W {\displaystyle \sum _{i=1}^{n}w_{i}x_{i}\leq W} and x i ∈ { 0 , 1 } {\displaystyle x_{i}\in \{0,1\}} . Here x i {\displaystyle x_{i}} represents the number of instances of item i {\displaystyle i} to include in the knapsack. Informally, the problem is to maximize the sum of the values of the items in the knapsack so that the sum of the weights is less than or equal to the knapsack's capacity. The bounded knapsack problem (BKP) removes the restriction that there is only one of each item, but restricts the number x i {\displaystyle x_{i}} of copies of each kind of item to a maximum non-negative integer value c {\displaystyle c} : maximize ∑ i = 1 n v i x i {\displaystyle \sum _{i=1}^{n}v_{i}x_{i}} subject to ∑ i = 1 n w i x i ≤ W {\displaystyle \sum _{i=1}^{n}w_{i}x_{i}\leq W} and x i ∈ { 0 , 1 , 2 , … , c } . {\displaystyle x_{i}\in \{0,1,2,\dots ,c\}.} The unbounded knapsack problem (UKP) places no upper bound on the number of copies of each kind of item and can be formulated as above except that the only restriction on x i {\displaystyle x_{i}} is that it is a non-negative integer. maximize ∑ i = 1 n v i x i {\displaystyle \sum _{i=1}^{n}v_{i}x_{i}} subject to ∑ i = 1 n w i x i ≤ W {\displaystyle \sum _{i=1}^{n}w_{i}x_{i}\leq W} and x i ∈ N . {\displaystyle x_{i}\in \mathbb {N} .} One example of the unbounded knapsack problem is given using the figure shown at the beginning of this article and the text "if any number of each book is available" in the caption of that figure. == Computational complexity == The knapsack problem is interesting from the perspective of computer science for many reasons: The decision problem form of the knapsack problem (Can a value of at least V be achieved without exceeding the weight W?) is NP-complete, thus there is no known algorithm that is both correct and fast (polynomial-time) in all cases. There is no known polynomial algorithm which can tell, given a solution, whether it is optimal (which would mean that there is no solution with a larger V). This problem is co-NP-complete. There is a pseudo-polynomial time algorithm using dynamic programming. There is a fully polynomial-time approximation scheme, which uses the pseudo-polynomial time algorithm as a subroutine, described below. Many cases that arise in practice, and "random instances" from some distributions, can nonetheless be solved exactly. There is a link between the "decision" and "optimization" problems in that if there exists a polynomial algorithm that solves the "decision" problem, then one can find the maximum value for the optimization problem in polynomial time by applying this algorithm iteratively while increasing the value of k. On the other hand, if an algorithm finds the optimal value of the optimization problem in polynomial time, then the decision problem can be solved in polynomial time by comparing the value of the solution output by this algorithm with the value of k. Thus, both versions of the problem are of similar difficulty. One theme in research literature is to identify what the "hard" instances of the knapsack problem look like, or viewed another way, to identify what properties of instances in practice might make them more amenable than their worst-case NP-complete behaviour suggests. The goal in finding these "hard" instances is for their use in public-key cryptography systems, such as the Merkle–Hellman knapsack cryptosystem. More generally, better understanding of the structure of the space of instances of an optimization problem helps to advance the study of the particular problem and can improve algorithm selection. Furthermore, notable is the fact that the hardness of the knapsack problem depends on the form of the input. If the weights and profits are given as integers, it is weakly NP-complete, while it is strongly NP-complete if the weights and profits are given as rational numbers. However, in the case of rational weights and profits it still admits a fully polynomial-time approximation scheme. === Unit-cost models === The NP-hardness of the Knapsack problem relates to computational models in which the size of integers matters (such as the Turing machine). In contrast, decision trees count each decision as a single step. Dobkin and Lipton show an 1 2 n 2 {\displaystyle {1 \over 2}n^{2}} lower bound on linear decision trees for the knapsack problem, that is, trees where decision nodes test the sign of affine functions. This was generalized to algebraic decision trees by Steele and Yao. If the elements in the problem are real numbers or rationals, the decision-tree lower bound extends to the real random-access machine model with an instruction set that includes addition, subtraction and multiplication of real numbers, as well as comparison and either division or remaindering ("floor"). This model covers more algorithms than the algebraic decision-tree model, as it encompasses algorithms that use indexing into tables. However, in this model all program steps are counted, not just decisions. An upper bound for a decision-tree model was given by Meyer auf der Heide who showed that for every n there exists an O(n4)-deep linear decision tree that solves the subset-sum problem with n items. Note that this does not imply any upper bound for an algorithm that should solve the problem for any given n. == Solving == Several algorithms are available to solve knapsack problems, based on the dynamic programming approach, the branch and bound approach or hybridizations of both approaches. === Dynamic programming in-advance algorithm === The unbounded knapsack problem (UKP) places no restriction on the number of copies of each kind of item. Besides, here we assume that x i > 0 {\displaystyle x_{i}>0} m [ w ′ ] = max ( ∑ i = 1 n v i x i ) {\displaystyle m[w']=\max \left(\sum _{i=1}^{n}v_{i}x_{i}\right)} subject to ∑
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In database systems, atomicity (; from Ancient Greek: ἄτομος, romanized: átomos, lit. 'undividable') is the property of a database transaction consisting of an indivisible and irreducible series of database operations such that either all occur, or none occur. It is one of the ACID transaction properties: Atomicity, Consistency, Isolation, Durability. A guarantee of atomicity prevents partial database updates from occurring, because they can cause greater problems than rejecting the whole series outright. As a consequence, an atomic transaction cannot be observed to be in progress by another database client: at one moment in time, it has not yet happened, and at the next it has already occurred in whole (or nothing happened if the transaction was cancelled in progress). An example of transaction atomicity could be a digital monetary transfer from bank account A to account B. It consists of two operations, debiting the money from account A and crediting it to account B. Performing both of these operations inside of an atomic transaction ensures that the database remains in a consistent state, if either operation fails there will not be any unaccountable credits or debits affecting either account. The same term is also used in the definition of First normal form in database systems, where it instead refers to the concept that the values for fields may not consist of multiple smaller values to be decomposed, such as a string into which multiple names, numbers, dates, or other types may be packed. == Orthogonality == Atomicity does not behave completely orthogonally with regard to the other ACID properties of transactions. For example, isolation relies on atomicity to roll back the enclosing transaction in the event of an isolation violation such as a deadlock; consistency also relies on atomicity to roll back the enclosing transaction in the event of a consistency violation by an illegal transaction. As a result of this, a failure to detect a violation and roll back the enclosing transaction may cause an isolation or consistency failure. == Implementation == Typically, systems implement Atomicity by providing some mechanism to indicate which transactions have started and which finished; or by keeping a copy of the data before any changes occurred (Read-copy-update). Several filesystems have developed methods for avoiding the need to keep multiple copies of data, using journaling (see journaling file system). Databases usually implement this using some form of logging/journaling to track changes. The system synchronizes the logs (often the metadata) as necessary after changes have successfully taken place. Afterwards, crash recovery ignores incomplete entries. Although implementations vary depending on factors such as concurrency issues, the principle of atomicity – i.e. complete success or complete failure – remain. Ultimately, any application-level implementation relies on operating-system functionality. At the file-system level, POSIX-compliant systems provide system calls such as open(2) and flock(2) that allow applications to atomically open or lock a file. At the process level, POSIX Threads provide adequate synchronization primitives. The hardware level requires atomic operations such as Test-and-set, Fetch-and-add, Compare-and-swap, or Load-Link/Store-Conditional, together with memory barriers. Portable operating systems cannot simply block interrupts to implement synchronization, since hardware that lacks concurrent execution such as hyper-threading or multi-processing is now extremely rare. In distributed and sharded databases, atomicity is complicated by network latency and the potential for partial failures. While traditional distributed systems often employ locking protocols (like 2PC) to ensure cross-shard atomicity, these can introduce performance bottlenecks. Recent research into distributed ledger consensus suggests alternative models, such as "braided synchronization". This technique, utilized in protocols like Cerberus, intertwines the consensus phases of multiple shards to enforce atomic guarantees without a global ordering of all transactions.
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