Supersampling or supersampling anti-aliasing (SSAA) is a spatial anti-aliasing method, i.e. a method used to remove aliasing (jagged and pixelated edges, colloquially known as "jaggies") from images rendered in computer games or other computer programs that generate imagery. Aliasing occurs because unlike real-world objects, which have continuous smooth curves and lines, a computer screen shows the viewer a large number of small squares. These pixels all have the same size, and each one has a single color. A line can only be shown as a collection of pixels, and therefore appears jagged unless it is perfectly horizontal or vertical. The aim of supersampling is to reduce this effect. Color samples are taken at several instances inside the pixel (not just at the center as normal)—hence the term "supersampling"—and an average color value is calculated. This can for example be achieved by rendering the image at a much higher resolution than the one being displayed, then shrinking it to the desired size, using the extra pixels for calculation, with the result being a downsampled image with smoother transitions from one line of pixels to another along the edges of objects, but each pixel could also be supersampled using other strategies (see the Supersampling patterns section). The number of samples determines the quality of the output. == Motivation == Aliasing is manifested in the case of 2D images as moiré pattern and pixelated edges, colloquially known as "jaggies". Common signal processing and image processing knowledge suggests that to achieve perfect elimination of aliasing, proper spatial sampling at the Nyquist rate (or higher) after applying a 2D Anti-aliasing filter is required. As this approach would require a forward and inverse fourier transformation, computationally less demanding approximations like supersampling were developed to avoid domain switches by staying in the spatial domain ("image domain"). == Method == === Computational cost and adaptive supersampling === Supersampling is computationally expensive because it requires much greater video card memory and memory bandwidth, since the amount of buffer used is several times larger. A way around this problem is to use a technique known as adaptive supersampling, where only pixels at the edges of objects are supersampled. Initially only a few samples are taken within each pixel. If these values are very similar, only these samples are used to determine the color. If not, more are used. The result of this method is that a higher number of samples are calculated only where necessary, thus improving performance. === Supersampling patterns === When taking samples within a pixel, the sample positions have to be determined in some way. Although the number of ways in which this can be done is infinite, there are a few ways which are commonly used. ==== Grid ==== The simplest algorithm. The pixel is split into several sub-pixels, and a sample is taken from the center of each. It is fast and easy to implement. Although, due to the regular nature of sampling, aliasing can still occur if a low number of sub-pixels is used. ==== Random ==== Also known as stochastic sampling, it avoids the regularity of grid supersampling. However, due to the irregularity of the pattern, samples end up being unnecessary in some areas of the pixel and lacking in others. ==== Poisson disk ==== The Poisson disk sampling algorithm places the samples randomly, but then checks that any two are not too close. The end result is an even but random distribution of samples. The naive "dart throwing" algorithm is extremely slow for large data sets, which once limited its applications for real-time rendering. However, many fast algorithms now exist to generate Poisson disk noise, even those with variable density. The Delone set provides a mathematical description of such sampling. ==== Jittered ==== A modification of the grid algorithm to approximate the Poisson disk. A pixel is split into several sub-pixels, but a sample is not taken from the center of each, but from a random point within the sub-pixel. Congregation can still occur, but to a lesser degree. ==== Rotated grid ==== A 2×2 grid layout is used but the sample pattern is rotated to avoid samples aligning on the horizontal or vertical axis, greatly improving antialiasing quality for the most commonly encountered cases. For an optimal pattern, the rotation angle is arctan (1/2) (about 26.6°) and the square is stretched by a factor of √5/2, making it also a 4-queens solution.
Vector database
A vector database, vector store or vector search engine is a database that stores and retrieves embeddings of data in vector space. Vector databases typically implement approximate nearest neighbor algorithms so users can search for records semantically similar to a given input, unlike traditional databases which primarily look up records by exact match. Use-cases for vector databases include similarity search, semantic search, multi-modal search, recommendations engines, object detection, and retrieval-augmented generation (RAG). Vector embeddings are mathematical representations of data in a high-dimensional space. In this space, each dimension corresponds to a feature of the data, with the number of dimensions ranging from a few hundred to tens of thousands, depending on the complexity of the data being represented. Each data item is represented by one vector in this space. Words, phrases, or entire documents, as well as images, audio, and other types of data, can all be vectorized. These feature vectors may be computed from the raw data using machine learning methods such as feature extraction algorithms, word embeddings or deep learning networks. The goal is that semantically similar data items receive feature vectors close to each other. Vector retrieval can be combined with metadata filtering or lexical search to support filtered and hybrid retrieval workflows. == Techniques == Common techniques for similarity search on high-dimensional vectors include: Hierarchical Navigable Small World (HNSW) graphs Locality-sensitive hashing (LSH) and sketching Product quantization (PQ) Inverted files These techniques may also be combined in vector search systems. In recent benchmarks, HNSW-based implementations have been among the best performers. Conferences such as the International Conference on Similarity Search and Applications (SISAP) and the Conference on Neural Information Processing Systems (NeurIPS) have hosted competitions on vector search in large databases. == Applications == Vector databases are used in a wide range of machine learning applications including similarity search, semantic search, multi-modal search, recommendations engines, object detection, and retrieval-augmented generation. === Retrieval-augmented generation === An especially common use-case for vector databases is in retrieval-augmented generation (RAG), a method to improve domain-specific responses of large language models. The retrieval component of a RAG can be any search system, but is most often implemented as a vector database. Text documents describing the domain of interest are collected, and for each document or document section, a feature vector (known as an "embedding") is computed, typically using a deep learning network, and stored in a vector database along with a link to the document. Given a user prompt, the feature vector of the prompt is computed, and the database is queried to retrieve the most relevant documents. These are then automatically added into the context window of the large language model, and the large language model proceeds to create a response to the prompt given this context. == Implementations ==
Digital anthropology
Digital anthropology is the anthropological study of the relationship between humans and digital-era technology. The field is new, and thus has a variety of names with a variety of emphases. These include techno-anthropology, digital ethnography, cyberanthropology, and virtual anthropology. == Definition and scope == Most anthropologists who use the phrase "digital anthropology" are specifically referring to online and Internet technology. The study of humans' relationship to a broader range of technology may fall under other subfields of anthropological study, such as cyborg anthropology. The Digital Anthropology Group (DANG) is classified as an interest group in the American Anthropological Association. DANG's mission includes promoting the use of digital technology as a tool of anthropological research, encouraging anthropologists to share research using digital platforms, and outlining ways for anthropologists to study digital communities. Cyberspace or the "virtual world" itself can serve as a "field" site for anthropologists, allowing the observation, analysis, and interpretation of the sociocultural phenomena springing up and taking place in any interactive space. National and transnational communities, enabled by digital technology, establish a set of social norms, practices, traditions, storied history and associated collective memory, migration periods, internal and external conflicts, potentially subconscious language features and memetic dialects comparable to those of traditional, geographically confined communities. This includes the various communities built around free and open-source software, online platforms such as Facebook, Twitter/X, Instagram, 4chan and Reddit and their respective sub-sites, and politically motivated groups like Anonymous, WikiLeaks, or the Occupy movement. A number of academic anthropologists have conducted traditional ethnographies of virtual worlds, such as Bonnie Nardi's study of World of Warcraft or Tom Boellstorff's study of Second Life. Academic Gabriella Coleman has done ethnographic work on the Debian software community and the Anonymous hacktivist network. Theorist Nancy Mauro-Flude conducts ethnographic field work on computing arts and computer subcultures such as systerserver.net a part of the communities of feminist web servers and the Feminist Internet network. Eitan Y. Wilf examines the intersection of artists' creativity and digital technology and artificial intelligence. Yongming Zhou studied how in China the internet is used to participate in politics. Eve M. Zucker and colleagues study the shift to digital memorialization of mass atrocities and the emergent role of artificial intelligence in these processes. Victoria Bernal conducted ethnographic research on the themes of nationalism and citizenship among Eritreans participating in online political engagement with their homeland. Anthropological research can help designers adapt and improve technology. Australian anthropologist Genevieve Bell did extensive user experience research at Intel that informed the company's approach to its technology, users, and market. == Methodology == === Digital fieldwork === Many digital anthropologists who study online communities use traditional methods of anthropological research. They participate in online communities in order to learn about their customs and worldviews, and back their observations with private interviews, historical research, and quantitative data. Their product is an ethnography, a qualitative description of their experience and analyses. Other anthropologists and social scientists have conducted research that emphasizes data gathered by websites and servers. However, academics often have trouble accessing user data on the same scale as social media corporations like Facebook and data mining companies like Acxiom. In terms of method, there is a disagreement in whether it is possible to conduct research exclusively online or if research will only be complete when the subjects are studied holistically, both online and offline. Tom Boellstorff, who conducted a three-year research as an avatar in the virtual world Second Life, defends the first approach, stating that it is not just possible, but necessary to engage with subjects “in their own terms”. Others, such as Daniel Miller, have argued that an ethnographic research should not exclude learning about the subject's life outside the internet. === Digital technology as a tool of anthropology === The American Anthropological Association offers an online guide for students using digital technology to store and share data. Data can be uploaded to digital databases to be stored, shared, and interpreted. Text and numerical analysis software can help produce metadata, while a codebook may help organize data. == Ethics == Online fieldwork offers new ethical challenges. According to the American Anthropological Association's ethics guidelines, anthropologists researching a community must make sure that all members of that community know they are being studied and have access to data the anthropologist produces. However, many online communities' interactions are publicly available for anyone to read, and may be preserved online for years. Digital anthropologists debate the extent to which lurking in online communities and sifting through public archives is ethical. The Association also asserts that anthropologists' ability to collect and store data at all is "a privilege", and researchers have an ethical duty to store digital data responsibly. This means protecting the identity of participants, sharing data with other anthropologists, and making backup copies of all data. == Prominent figures == Genevieve Bell is an Australian cultural anthropologist credited for pioneering the User Experience field. During her time working for Intel Corporation, Bell studied how various cultures from around the world interacted with and experienced technology. Researching and improving user experience allows companies and designers to gather data regarding how users utilize their digital products and what requires improvement or expansion. Tom Boellstorff is an anthropologist known for Coming of Age in Second Life: An Anthropologist Explores the Virtually Human where he conducted research on how engaging in virtual worlds affects the player’s sense of self. Gabriella Coleman is an American anthropologist concerned with the politics, ethics, and culture of hacking and online activism. Coleman’s most notable ethnography features the hacktivist collective Anonymous, where she argues that various genres of hacking exist according to the social conditions at play. Coleman is dedicated to making her ethnography accessible to a diverse audience, including academics and non-academics. Diana E. Forsythe was an American anthropologist of science and technology and the author of the essays featured in Studying Those Who Study Us: An Anthropologist in the World of Artificial Intelligence. She asked relevant questions such as how should humans interact with computers and how gender roles are maintained in technology-oriented occupations. Heather Horst is a sociocultural anthropologist interested in the relationship between digital social relations and material culture. Nancy Mauro-Flude is a design anthropologist whose work explores the tacit relations between embodied cognition, computational materiality, maker culture, self-hosted webserver cooperatives, creative practice, and artistic research in digital infrastructure and Internet publishing. Mizuko Ito is a Japanese cultural anthropologist specializing in technology use and the intersection between computers and the social sciences. Her primary interest is in how young people utilize media technology and how it can be used to engage students in education. Daniel Miller is an anthropologist with a concentration in digital anthropology. His research includes the smartphone and perpetual opportunism, the intent and consequences of posting on social media in various geographical locations, and how hospice patients use media to socialize in the last stage of their lives. Mike Wesch is a cultural anthropologist interested in how people share their lives, cultures, and beliefs through digital media.
Svelte
Svelte is a free and open-source component-based front-end software framework and language created by Rich Harris and maintained by the Svelte core team. Svelte is not a monolithic JavaScript library imported by applications: instead, Svelte compiles HTML templates to specialized code that manipulates the DOM directly, which may reduce the size of transferred files and give better client performance. Application code is also processed by the compiler, inserting calls to automatically recompute data and re-render UI elements when the data they depend on is modified. This also avoids the overhead associated with runtime intermediate representations, such as virtual DOM, unlike traditional frameworks (such as React and Vue) which carry out the bulk of their work at runtime, i.e. in the browser. The compiler itself is written in JavaScript. Its source code is licensed under MIT License and hosted on GitHub. Among comparable frontend libraries, Svelte has one of the smallest bundle footprints at merely 2KB. == History == The predecessor of Svelte is Ractive.js, which Rich Harris created in 2013. Version 1 of Svelte was written in JavaScript and was released on 29 November 2016. The name Svelte was chosen by Rich Harris and his coworkers at The Guardian. Version 2 of Svelte was released on 19 April 2018. It set out to correct what the maintainers viewed as mistakes in the earlier version such as replacing double curly braces with single curly braces. Version 3 of Svelte was written in TypeScript and was released on 21 April 2019. It rethought reactivity by using the compiler to instrument assignments behind the scenes. The SvelteKit web framework was announced in October 2020 and entered beta in March 2021. SvelteKit 1.0 was released in December 2022 after two years in development. Version 4 of Svelte was released on 22 June 2023. It was a maintenance release, smaller and faster than version 3. A part of this release was an internal rewrite from TypeScript back to JavaScript, with JSDoc type annotations. This was met with confusion from the developer community, which was addressed by the creator of Svelte, Rich Harris. Version 5 of Svelte was released on October 19, 2024 at Svelte Summit Fall 2024 with Rich Harris cutting the release live while joined by other Svelte maintainers. Svelte 5 was a ground-up rewrite of Svelte, changing core concepts such as reactivity and reusability. Its primary feature, runes, reworked how reactive state is declared and used. Runes are function-like macros that are used to declare a reactive state, or code that uses reactive states. These runes are used by the compiler to indicate values that may change and are depended on by other states or the DOM. Svelte 5 also introduces Snippets, which are reusable "snippets" of code that are defined once and can be reused anywhere else in the component. Svelte 5 was initially met with controversy due to its many changes, and thus deprecations caused primarily by runes. However, most of this has subsided since the initial announcement of runes, and the further refining of Svelte 5. Also at Svelte Summit Fall 2024, Ben McCann announced the Svelte CLI under the sv package name on npm. In early 2025, the Svelte team announced Asynchronous Svelte, an experimental feature set centered around asynchronous reactivity in Svelte using await expressions. As of August 2025, the feature is available via an experimental compiler option. This coincided with the experimental release of remote functions, an RPC feature in SvelteKit, Svelte's metaframework. Key early contributors to Svelte became involved with Conduitry joining with the release of Svelte 1, Tan Li Hau joining in 2019, and Ben McCann joining in 2020. Rich Harris and Simon Holthausen joined Vercel to work on Svelte fulltime in 2022. Dominic Gannaway joined Vercel from the React core team to work on Svelte fulltime in 2023. == Syntax == Svelte applications and components are defined in .svelte files, which are HTML files extended with templating syntax that is based on JavaScript and is similar to JSX. Svelte's core features are accessed through runes, which syntactically look like functions, but are used as macros by the compiler. These runes include: The $state rune, used for declaring a reactive state value The $derived rune, used for declaring reactive state derived from one or more states The $effect rune, used for declaring code that reruns whenever its dependencies change Starting with Svelte 5, the framework introduced a significant reactivity overhaul that replaces the previous `$:` reactive declarations with new runes such as $state, $derived, and $effect. The $effect rune is now used for post-render operations without modifying state, while $derived is used for computations that depend on other reactive values. This change aims to simplify the mental model of reactivity and make component logic more explicit. Additionally, the { JavaScript code } syntax can be used for templating in HTML elements and components, similar to template literals in JavaScript. This syntax can also be used in element attributes for uses such as two-way data binding, event listeners, and CSS styling. A Todo List example made in Svelte is below: == Associated projects == The Svelte maintainers created SvelteKit as the official way to build projects with Svelte. It is a Next.js/Nuxt-style full-stack framework that dramatically reduces the amount of code that gets sent to the browser. The maintainers had previously created Sapper, which was the predecessor of SvelteKit. The Svelte maintainers also maintain a number of integrations for popular software projects under the Svelte organization including integrations for Vite, Rollup, Webpack, TypeScript, VS Code, Chrome Developer Tools, ESLint, and Prettier. A number of external projects such as Storybook have also created integrations with Svelte and SvelteKit. == Influence == Vue.js modeled its API and single-file components after Ractive.js, the predecessor of Svelte. == Adoption == Svelte is widely praised by developers. Taking the top ranking in multiple large scale developer surveys, it was chosen as the Stack Overflow 2021 most loved web framework and 2020 State of JS frontend framework with the most satisfied developers. Recent surveys continue to show Svelte's strong developer satisfaction, with the 2024 State of JS survey maintaining its position among the most praised frontend frameworks. The 2024 Stack Overflow Developer Survey reported that 73% of developers who used Svelte want to continue working with it, and noted that Stack Overflow's own team used Svelte for building their 2024 Developer Survey results site. Svelte has been adopted by a number of high-profile web companies including The New York Times, Google, Apple, Spotify, Radio France, Square, Yahoo, ByteDance, Rakuten, Bloomberg, Reuters, Ikea, Facebook, Logitech, and Brave. A community group of primarily non-maintainers, known as the Svelte Society, run the Svelte Summit conference, write a Svelte newsletter, host a Svelte podcast, and host a directory of Svelte tooling, components, and templates.
FreePBX Distro
The FreePBX Distro was a freeware unified communications software system that consisted of FreePBX, a graphical user interface (GUI) for configuring, controlling and managing Asterisk PBX software. The FreePBX Distro included packages that offer VoIP, PBX, Fax, IVR, voice-mail and email functions. The FreePBX Distro Linux distribution was based on CentOS, which maintains binary compatibility with Red Hat Enterprise Linux. FreePBX has contributed to the popularity of Asterisk. As a result of CentOS Linux being discontinued and the last version of CentOS 7 going out of support on June 30, 2024, FreePBX 17 has moved over to and is supported on Debian Linux. FreePBX will no longer be providing a pre-configured FreePBX Distro, but will provide a script to install FreePBX on a fresh install of Debian Linux. In-place migration will not be possible, but will be possible by restoring a backup on the new version from the previous version. As FreePBX 16 will be supported until the release of FreePBX 18, FreePBX on this distribution will still work and be supported, however, there will be no further support for the underlying operating system. == Installation == The Official FreePBX Distro is installed from a ISO image available by web download, that includes the system CentOS, Asterisk, FreePBX GUI and assorted dependencies. This can then either be burned to DVD or written to a USB stick for installation == Support for telephony hardware == The FreePBX Distro has built-in support for cards from multiple vendors, including Digium, OpenVox, Alto, Rhino Equipment, Xorcom and Sangoma. The FreePBX Distro supports a large number of phone models via open-source modules. Supported VoIP phone manufacturers include Algo, AND, AudioCodes, Cisco, Cyberdata, Digium, Grandstream, Mitel/Aastra, Nortel/Avaya, Panasonic, Polycom, Sangoma, Snom, Xorcom and Yealink. == Development == FreePBX made its debut in 2004 as the AMP project (Asterisk Management Portal). The FreePBX Distro was released in 2011 as an turnkey solution for building a PBX using Asterisk, CentOS and FreePBX. FreePBX has over 1 million active production PBXs and over 20,000 new systems added each month. The core telephony engine is Asterisk, as configured by the Open Source FreePBX GUI. The last stable release is FreePBX Distro Stable SNG7-PBX16-64bit-2302-1 based on these main components: FreePBX 16 CentOS 7.8 Asterisk 16, 18, 19 (20 supported by upgrade once installed)
Concurrency control
In information technology and computer science, especially in the fields of computer programming, operating systems, multiprocessors, and databases, concurrency control ensures that correct results for concurrent operations are generated, while getting those results as quickly as possible. Computer systems, both software and hardware, consist of modules, or components. Each component is designed to operate correctly, i.e., to obey or to meet certain consistency rules. When components that operate concurrently interact by messaging or by sharing accessed data (in memory or storage), a certain component's consistency may be violated by another component. The general area of concurrency control provides rules, methods, design methodologies, and theories to maintain the consistency of components operating concurrently while interacting, and thus the consistency and correctness of the whole system. Introducing concurrency control into a system means applying operation constraints which typically result in some performance reduction. Operation consistency and correctness should be achieved with as good as possible efficiency, without reducing performance below reasonable levels. Concurrency control can require significant additional complexity and overhead in a concurrent algorithm compared to the simpler sequential algorithm. For example, a failure in concurrency control can result in data corruption from torn read or write operations. == Concurrency control in databases == Comments: This section is applicable to all transactional systems, i.e., to all systems that use database transactions (atomic transactions; e.g., transactional objects in Systems management and in networks of smartphones which typically implement private, dedicated database systems), not only general-purpose database management systems (DBMSs). DBMSs need to deal also with concurrency control issues not typical just to database transactions but rather to operating systems in general. These issues (e.g., see Concurrency control in operating systems below) are out of the scope of this section. Concurrency control in Database management systems (DBMS; e.g., Bernstein et al. 1987, Weikum and Vossen 2001), other transactional objects, and related distributed applications (e.g., Grid computing and Cloud computing) ensures that database transactions are performed concurrently without violating the data integrity of the respective databases. Thus concurrency control is an essential element for correctness in any system where two database transactions or more, executed with time overlap, can access the same data, e.g., virtually in any general-purpose database system. Consequently, a vast body of related research has been accumulated since database systems emerged in the early 1970s. A well established concurrency control theory for database systems is outlined in the references mentioned above: serializability theory, which allows to effectively design and analyze concurrency control methods and mechanisms. An alternative theory for concurrency control of atomic transactions over abstract data types is presented in (Lynch et al. 1993), and not utilized below. This theory is more refined, complex, with a wider scope, and has been less utilized in the Database literature than the classical theory above. Each theory has its pros and cons, emphasis and insight. To some extent they are complementary, and their merging may be useful. To ensure correctness, a DBMS usually guarantees that only serializable transaction schedules are generated, unless serializability is intentionally relaxed to increase performance, but only in cases where application correctness is not harmed. For maintaining correctness in cases of failed (aborted) transactions (which can always happen for many reasons) schedules also need to have the recoverability (from abort) property. A DBMS also guarantees that no effect of committed transactions is lost, and no effect of aborted (rolled back) transactions remains in the related database. Overall transaction characterization is usually summarized by the ACID rules below. As databases have become distributed, or needed to cooperate in distributed environments (e.g., Federated databases in the early 1990, and Cloud computing currently), the effective distribution of concurrency control mechanisms has received special attention. === Database transaction and the ACID rules === The concept of a database transaction (or atomic transaction) has evolved in order to enable both a well understood database system behavior in a faulty environment where crashes can happen any time, and recovery from a crash to a well understood database state. A database transaction is a unit of work, typically encapsulating a number of operations over a database (e.g., reading a database object, writing, acquiring lock, etc.), an abstraction supported in database and also other systems. Each transaction has well defined boundaries in terms of which program/code executions are included in that transaction (determined by the transaction's programmer via special transaction commands). Every database transaction obeys the following rules (by support in the database system; i.e., a database system is designed to guarantee them for the transactions it runs): Atomicity - Either the effects of all or none of its operations remain ("all or nothing" semantics) when a transaction is completed (committed or aborted respectively). In other words, to the outside world a committed transaction appears (by its effects on the database) to be indivisible (atomic), and an aborted transaction does not affect the database at all. Either all the operations are done or none of them are. Consistency - Every transaction must leave the database in a consistent (correct) state, i.e., maintain the predetermined integrity rules of the database (constraints upon and among the database's objects). A transaction must transform a database from one consistent state to another consistent state (however, it is the responsibility of the transaction's programmer to make sure that the transaction itself is correct, i.e., performs correctly what it intends to perform (from the application's point of view) while the predefined integrity rules are enforced by the DBMS). Thus since a database can be normally changed only by transactions, all the database's states are consistent. Isolation - Transactions cannot interfere with each other (as an end result of their executions). Moreover, usually (depending on concurrency control method) the effects of an incomplete transaction are not even visible to another transaction. Providing isolation is the main goal of concurrency control. Durability - Effects of successful (committed) transactions must persist through crashes (typically by recording the transaction's effects and its commit event in a non-volatile memory). The concept of atomic transaction has been extended during the years to what has become Business transactions which actually implement types of Workflow and are not atomic. However also such enhanced transactions typically utilize atomic transactions as components. === Why is concurrency control needed? === If transactions are executed serially, i.e., sequentially with no overlap in time, no transaction concurrency exists. However, if concurrent transactions with interleaving operations are allowed in an uncontrolled manner, some unexpected, undesirable results may occur, such as: The lost update problem: A second transaction writes a second value of a data-item (datum) on top of a first value written by a first concurrent transaction, and the first value is lost to other transactions running concurrently which need, by their precedence, to read the first value. The transactions that have read the wrong value end with incorrect results. The dirty read problem: Transactions read a value written by a transaction that has been later aborted. This value disappears from the database upon abort, and should not have been read by any transaction ("dirty read"). The reading transactions end with incorrect results. The incorrect summary problem: While one transaction takes a summary over the values of all the instances of a repeated data-item, a second transaction updates some instances of that data-item. The resulting summary does not reflect a correct result for any (usually needed for correctness) precedence order between the two transactions (if one is executed before the other), but rather some random result, depending on the timing of the updates, and whether certain update results have been included in the summary or not. Most high-performance transactional systems need to run transactions concurrently to meet their performance requirements. Thus, without concurrency control such systems can neither provide correct results nor maintain their databases consistently. === Concurrency control mechanisms === ==== Categories ==== The main categories of concurrency control mechanis
The Dodo (website)
The Dodo is an American online publisher focused on animals. The website was launched in January 2014 by Izzie Lerer, the daughter of media executive Kenneth Lerer, and journalist Kerry Lauerman. The Dodo has become one of the most popular Facebook publishers, garnering 1 billion video views from the social network in November 2015. The Dodo is headquartered in New York, New York. == History == The company—named after the first recorded species that humans drove to extinction—was founded by Lerer out of "a personal passion for the subject manner". Lerer has a PhD in animal studies with a focus on animal ethics and human relationships from Columbia University, launching the website after noticing the viral success of animal videos online but seeing no one "really owned the space." The Dodo's editorial and video production staff unionized with the Writers Guild of America, East in April 2018.