Apache CarbonData is a free and open-source column-oriented data storage format of the Apache Hadoop ecosystem. It is similar to the other columnar-storage file formats available in Hadoop namely RCFile and ORC. It is compatible with most of the data processing frameworks in the Hadoop environment. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in bulk. == History == CarbonData was developed at Huawei in 2013. The project was donated to the Apache Community in 2015 submitted to the Apache Incubator in June 2016. The project won top honors in the BlackDuck 2016 Open Source Rookies of the Year's Big Data category. Apache CarbonData has been a top-level Apache Software Foundation (ASF)-sponsored project since May 1, 2017.
Decision list
Decision lists are a representation for Boolean functions which can be easily learned from examples. Single term decision lists are more expressive than disjunctions and conjunctions; however, 1-term decision lists are less expressive than the general disjunctive normal form and the conjunctive normal form. The language specified by a k-length decision list includes as a subset the language specified by a k-depth decision tree. Learning decision lists can be used for attribute efficient learning, a type of machine learning. == Definition == A decision list (DL) of length r is of the form: if f1 then output b1 else if f2 then output b2 ... else if fr then output br where fi is the ith formula and bi is the ith boolean for i ∈ { 1... r } {\displaystyle i\in \{1...r\}} . The last if-then-else is the default case, which means formula fr is always equal to true. A k-DL is a decision list where all of formulas have at most k terms. Sometimes "decision list" is used to refer to a 1-DL, where all of the formulas are either a variable or its negation.
VistaCreate
VistaCreate (formerly Crello) is an online graphic design platform for non-designers, launched in 2016. As of 2022, it has more than 10 million users in 192 countries. == Overview == VistaCreate (then known as Crello) was launched in 2016 as a part of Depositphotos. In 2019, the product hit a milestone of 1 million registered users and also launched mobile apps. In 2020, the library of templates and objects became free. A music library and a background remover tool were added to the platform. In May 2021, Moufflons Basketball, in collaboration with VistaCreate, organized a poster design competition in support of gender equality in sports. In October 2021, Vistaprint acquired Crello and its parent company, Depositphotos, for a total price of $85 million. After the acquisition, Crello was rebranded to VistaCreate. Along with Vistaprint and 99designs, it became part of the new Vista parent brand. After Russia started a full-scale war on the territory of Ukraine in February 2022, VistaCreate suspended all business in Russia and Belarus. VistaCreate's team and Depositphotos gathered collections of images and templates dedicated to the war in Ukraine.
Corel VideoStudio
Corel VideoStudio (formerly Ulead VideoStudio) is a video editing software package for Microsoft Windows. == Features == === Basic editing === The software allows storyboard and timeline-oriented editing. Various formats are supported for source clips, and the resulting video can be exported to a video file. DVD and AVCHD DVD authoring capabilities are included, and Blu-ray authoring is available via a plug-in. VideoStudio supports direct DV and HDV capture and burning. === Overlay === Users can overlay videos, images, and text. Using the overlay track, up to 50 clips can be displayed simultaneously. It can handle videos in MOV and AVI formats, including alpha channel, and images in PSP, PSD, PNG, and GIF formats. Clips that do not contain an alpha channel can have specific colours removed from the overlay video so that the required background or image is displayed in the foreground. === Proxy video files === VideoStudio supports high-definition video. Proxy files are smaller versions of the video source that stand in for the full-resolution source during editing to improve performance. === Plug-ins/bundles === VideoStudio supports VFX-type plug-ins from providers, including NewBlue and proDAD. proDAD plug-ins Roto-Pen, Script, Vitascene, and Mercalli-Stabilizer are bundled with X4 and later Ultimate Editions. == Version history == Ulead VideoStudio 4 (1999) Ulead VideoStudio 5 (2001) Ulead VideoStudio 6 (2002) Ulead VideoStudio 7 (2003) Ulead VideoStudio 8 (2004) Ulead VideoStudio 9 (2005) Ulead VideoStudio 10 plus. (2006) Corel Ulead VideoStudio 11 plus. (2007) Corel VideoStudio Pro X2 (v12, 2008) Corel VideoStudio Pro X3 (v13, 2010) 2011: Corel VideoStudio Pro X4 (v14, 2011) Adds support for stop motion animation, time-lapse mode photography, 3D movies, and 2nd generation Intel Core. Corel VideoStudio Pro X5 (v15, March 9, 2012): Adds HTML5 export (Comparison of HTML5 and Flash). Corel VideoStudio Pro X6 (v16, April 25, 2013): Windows 8 compatible. Adds UHD 4K support. Corel VideoStudio Pro X7 (v17, March 5, 2014): Software becomes 64-bit. Corel VideoStudio Pro X8 (v18, May 8, 2015): Several improvements. Corel VideoStudio Pro X9 (v19, February 16, 2016): Windows 10 compatible. Adds H.265 support, Multi-Camera Editor, and Match moving. Corel VideoStudio Pro X10 (v20, February 15, 2017): Adds Mask Creator, Track Transparency, and 360-degree video support. Corel VideoStudio Pro 2018 (v21, February 13, 2018): Adds split screen Video, Lens Correction, and 3D Title Editor. Corel VideoStudio Pro 2019 (v22, February 12, 2019): Adds Color Grading, Morph Transitions, and MultiCam Capture Lite. Corel VideoStudio Pro 2020 (v23, February 25, 2020). Corel VideoStudio Pro 2021 (v24, March 26, 2021): Adds Instant Project Templates, AR Stickers, and performance improvements (particularly regarding hardware acceleration). Corel VideoStudio Pro 2022 (v25, March 6, 2022): Adds face effects, GIF Creator, transitions for Camera Movements, a speech to text converter, and ProRes Smart Proxy.
Dating app
An online dating application, commonly known as a dating app, is an online dating service presented through a mobile phone application. These apps often take advantage of a smartphone's GPS location capabilities, always on-hand presence, and access to mobile wallets. These apps aim to speed up the online dating process of sifting through potential dating partners, chatting, flirting, and potentially meeting or becoming romantically involved. Online dating apps are now mainstream in the United States. As of 2017, online dating (which included both apps and other online dating services) was the principal method by which new couples in the U.S. met. The percentage of couples meeting online is predicted to increase to 70% by 2040. == Origins == The first computerized dating service was launched in 1964, the St. James Computer Dating Service, which became known as Com-Pat. The first U.S. dating service that used computerized match making was Operation Match. It required men and women to complete a questionnaire and was launched in 1965. Operation Match inspired the methodology of Dateline, which became popular in the 1970s and 1980s. Match.com was launched in 1995 and turned computerized match making into a profitable business. Grindr targeted gay and bisexual men at launch. Tinder, launched in 2012, led to a growth of online dating applications by both new providers and existing online dating services that expanded into the mobile app market. == Usage by demographic group == Online dating applications typically target a younger demographic group, though some apps, like Senior Match and Silver Singles are geared toward the 50 and up demographic. In 2016, almost 50% of people knew of someone who use the services or had met their loved one through the service. After the iPhone launch in 2007, online dating data has mushroomed as application usage increased. In 2005, only 10% of 18-24 year olds reported to have used online dating services; this number quickly grew to over 27%, making this target demographic the largest number of users for most applications. When Pew Research Center conducted a study in 2016, they found that 59% of U.S. adults agreed that online dating is a good way to meet people compared to 44% in 2005. This explosion in usage can be explained by the increased use of smartphones. By the end of 2022, it is expected there will be 413 million active users of online dating services worldwide. A 2023 Pew Research Center survey of 6,034 American adults found that 30% had ever used an online dating site or app, including 53% of those aged 18 to 29, 37% of those aged 30 to 49, and 17% of those aged 50 and over. Lesbian, gay and bisexual respondents reported using dating apps at nearly twice the rate of straight respondents (51% versus 28%), and 36% of divorced, separated or widowed adults had used one, compared with 16% of married adults. The increased use of smartphones by those 65 and older has also driven that population to the use dating apps. The Pew Research Center found that usage increase by 8 points since last surveyed in 2012. A study in 2021 found that more than one-third of seniors have dated in the past 5 years, and roughly one-third of those dating seniors have turned to dating apps. During the COVID-19 pandemic, Morning Consult found that more Americans were using online dating apps than ever before. In one survey in April 2020, the company discovered that 53% of U.S. adults who use online dating apps have been using them more during the pandemic. As of February 2021, that share increased to 71 percent. Research using Hofstede's cultural dimensions theory has indicated that norms about online dating applications tend to differ across cultures. A study published in the Journal of Creative Communications looked into the relationships between dating-app advertisements from over 51 countries and the cultural dimensions of these countries. The results revealed that dating-app advertisements appealed to multiple cultural needs, including the needs for relationships, friendship, entertainment, sex, status, design and identity. The use of these appeals was found to be 'congruent with ... the individualism/collectivism and uncertainty avoidance cultural dimensions.' == Popular applications == Following Tinder's success, other companies released dating applications. Raya was released in 2015 as a membership-based dating app, allowing entrance only through referrals, which was marketed as a dating app for celebrities. In early 2026, Hily surpassed Bumble to become the third most-used dating application in the United States and the fifth highest-grossing overall, driven largely by growing popularity among Generation Z users, while remaining behind Tinder and Hinge, both owned by Match Group. A number of dating apps have been created targeting adherents of particular religions seeking partners of the same religion, such as Muzmatch for Muslims, Christian Mingle, SALT, and Christian Connection for Christians, and JSwipe and JDate for Jews. === VR Dating === VR Dating is an application of Social VR where people can exist, collaborate, and perform various activities together. Virtual reality apps use virtual and augmented realities to make the dating experience more lifelike and more effective, as well as allow people to expand what is already possible in the world of online dating. There are several online platforms of VR Dating. The VR dating app Nevermet is the VR equivalent of Tinder, where people can search and find on dates. However, instead of actual real-life pictures, users will update pictures of virtual selves and will be interacting with avatars rather than real faces. Flirtual is a self-contained social VR app that serves to match users who then decide where and how to meet in VR. Flirtual hosts speed dating and social events in VR. == Effects on dating == The usage of online dating applications can have both advantages and disadvantages: === Advantages === Many of the applications provide personality tests for matching or use algorithms to match users. These factors enhance the possibility of users getting matched with a compatible candidate. Users are in control; they are provided with many options so there are enough matches that fit their particular type. Users can simply choose to not match the candidates that they know they are not interested in. Narrowing down options is easy. Once users think they are interested, they are able to chat and get to know the potential candidate. This form of communication can reduce the time, cost, and uncertainty often associated with traditional dating methods. Online dating offers convenience; people want dating to work around their schedules. Online dating can also increase self-confidence; even if users get rejected, they know there are hundreds of other candidates that will want to match with them so they can simply move on to the next option. In fact, 60% of U.S. adults agree that online dating is a good way to meet people and 66% say they have gone on a real date with someone they met through an application. Today, 5% of married Americans or Americans in serious relationships said they met their significant other online. The 39% of online dating users (representing 12% of all U.S. adults) say they have been in a committed relationship or married someone they met on a dating site or app. ==== Rejection sensitive individuals ==== Individuals high in rejection sensitivity are more likely to use online dating applications. As they tend to expect, perceive and overreact to rejection, rejection sensitive individuals struggle with traditional dating. Online dating applications allow for them to better reveal their true selves, potentially increasing their dating success. Online dating applications also obscure rejection cues, alleviating the rejection-related distress experienced by rejection sensitive individuals. ==== Anxiously attached individuals ==== Individuals high in attachment anxiety are also more likely to use online dating applications. While they harbour negative self-views, anxiously attached individuals are also more eager to enter and commit to relationships. Online dating applications allow for them to present "an authentic yet ideal version of themselves", mitigating their tendencies to view themselves as undesirable. This increases their romantic confidence, and potentially alleviates their anxiety when searching for a romantic partner. === Disadvantages === Sometimes having too many options can be overwhelming. With so many options available, users can get lost in their choices and end up spending too much time looking for the "perfect" candidate instead of using that time to start a real relationship. In addition, the algorithms and matching systems put in place may not always be as accurate as users think. There is no perfect system that can match two people's personalities perfectly every time. Communication online also lacks the physical chemistry aspec
H2O (software)
H2O is an open-source, in-memory, distributed machine learning and predictive analytics platform developed by the company H2O.ai (previously 0xdata). The software uses a distributed architecture for parallel processing on standard hardware. It supports algorithms for large-scale data analysis and model deployment. H2O is primarily used by data scientists and developers for statistical modeling and data-driven decision-making. The platform is designed to handle in-memory computations across a distributed computing environment. It offers implementations for numerous statistical and machine learning algorithms, which are accessible through various programming interfaces. The software is released under the Apache License 2.0. == Functionality and features == H2O provides a suite of supervised and unsupervised machine learning algorithms. Its core functions include: Supervised learning: algorithms in the field of statistics, data mining and machine learning such as generalized linear models, random forests, gradient boosting and deep learning are implemented for classification and regression tasks. Unsupervised learning: including K-Means clustering and principal component analysis. Automated machine learning: a features designed to automate the processes of model selection, tuning, and ensemble creation. The software can ingest data from various sources, including the Hadoop Distributed File System, Amazon S3, SQL databases, as well as local file systems. It operates natively on Apache Spark clusters through Sparkling Water. Proponents claim that improved performance is achieved compared to other analysis tools. The software is distributed free of charge, under a business model based on the development of individual applications and support. == Architecture == H2O is primarily written in Java. It uses a distributed architecture that allows the platform to cluster nodes for parallel processing and in-memory storage of data and models. Users interact with the H2O platform through several primary interfaces: Programming language interfaces: APIs are provided for the R and Python programming languages, and various Apache offerings (Apache Hadoop and Spark, as well as Maven). H2O Flow: a graphical web-based interactive computational environment that functions as a notebook interface for data exploration, model building, and scripting. REST-API: allows for integration with other applications and frameworks such as Microsoft Excel or RStudio. With the H2O Machine Learning Integration Nodes, KNIME offers algorithmic workflows. While the algorithm executes, approximate results are displayed, so that users can track the progress and intervene if needed. == History, influences, and extensions == The software project was initiated by the company 0xdata, which later changed its name to H2O.ai. The three Stanford professors Stephen P. Boyd, Robert Tibshirani and Trevor Hastie form a panel that advises H2O on scientific issues. Since its inception, H2O provides open-source machine learning libraries for enterprise use. The core H2O platform is often complemented by offerings from H2O.ai, such as H2O Driverless AI. == Reception == H2O is referenced in peer-reviewed literature regarding automated machine learning (AutoML). The platform has been categorized as a "Leader" and a "Strong Performer" in industry reports by Forrester Research. H2O (the open-source platform) and the associated commercial platform Driverless AI have been recurring winners of InfoWorld's most prestigious awards, including both the Best of Open Source Software ("Bossies") and the Technology of the Year awards.
Opponent process
The opponent process is a hypothesis of color vision that states that the human visual system interprets information about color by processing signals from the three types of photoreceptor cells in an antagonistic manner. The three types of cones are called L, M, and S. The names stand for "Long wavelength sensitive,” "middle wavelength sensitive," and "short wavelength sensitive." The opponent-process theory implicates three opponent channels: L versus M, S versus (L+M), and a luminance channel (+ versus -). These cone-opponent mechanisms were at one time thought to be the neural substrate for a psychological theory called Hering's Opponent Colors Theory, which calls for three psychologically important opponent color processes: red versus green, blue versus yellow, and black versus white (luminance). The Opponent Colors Theory is named for the German physiologist Ewald Hering who proposed the idea in the late 19th century. However, it has been argued that Hering’s Opponent Colors Theory lacks adequate phenomenological and empirical support, and may not be a necessary feature of normal human color experience. Correspondingly, considerable physiological and behavioral evidence proves that the physiological cone opponent mechanisms do not constitute the neurobiological basis for Hering's Opponent Colors Theory. == Color theory == === Complementary colors === When staring at a bright color for a while (e.g. red), then looking away at a white field, an afterimage is perceived, such that the original color will evoke its complementary color (cyan, in the case of red input). When complementary colors are combined or mixed, they "cancel each other out" and become neutral (white or gray). That is, complementary colors are never perceived as a mixture; there is no "greenish red" or "yellowish blue", despite claims to the contrary. The strongest color contrast that a color can have is its complementary color. Complementary colors may also be called "opposite colors" and they were originally considered the primary evidence in support of Hering's Opponent Colors Theory. There are two fatal problems with this evidence. First, the complement of red is not green, as called for by Hering's theory; it is bluish-green. And second, there exists a complementary color for every color, so there is nothing special about the set of complementary pairs picked out by Hering's theory. === Unique hues === The colors that define the extremes for each opponent channel are called unique hues, as opposed to composite (mixed) hues. Ewald Hering first defined the unique hues as red, green, blue, and yellow, and based them on the concept that these colors could not be simultaneously perceived. For example, a color cannot appear both red and green. These definitions have been experimentally refined and are represented today by average hue angles of 353° (carmine red), 128° (cobalt green), 228° (cobalt blue), 58° (yellow). The unique hues are a defining feature of many psychological color spaces, but there is substantial evidence showing that the unique hues are not hard wired in the nervous system, contrary to the stipulations of Hering's Opponent Colors Theory. Unique hues can differ between individuals and are often used in psychophysical research to measure variations in color perception due to color-vision deficiencies or color adaptation. While there is considerable inter-subject variability when defining unique hues experimentally, an individual's unique hues are very consistent, to within a few nanometers of wavelength. == Physiological basis == === Relation to LMS color space === The trichromatic theory is in conflict with Hering's Opponent Colors Theory, although it is compatible with a physiological opponent process that compares the outputs of the different classes of cone types. The poles of these cone opponent mechanisms do not correspond to the unique hues of Hering's Opponent Colors Theory and unlike the unique hues, have no privilege in color perception. Most humans have three different cone cells in their retinas that facilitate trichromatic color vision. Colors are determined by the proportional excitation of these three cone types, i.e. their quantum catch. The levels of excitation of each cone type are the parameters that define LMS color space. To calculate the opponent process tristimulus values from the LMS color space, the cone excitations must be compared: The luminous (achromatic) opponent channel is a weighted sum of all three cone cells (plus the rod cells in some conditions). The red–green opponent channel is equal to the difference of the L- and M-cones. The blue–yellow opponent channel is equal to the difference of the S-cone and the average/weighted sum of the L- and M-cones. Most mammals have no L cone (the primate L cone arose from a gene duplication of the M cone opsin gene). These mammals still show two kinds of opponent channels in their retinal ganglion cells: the achromatic channel and the blue-yellow opponency channel. === Cone opponent mechanisms are encoded in the retina === The output of different types of cones are compared by cells in the retina including retina bipolar cells (which compare signals from L and M cones) and bistratified retinal ganglion cells (which compare S cone signals with L and M cone signals). The output of bipolar cells is relayed to the visual cortex by the retinal ganglion cells (RGCs) by way of a thalamic relay station called the lateral geniculate nucleus (LGN) of the thalamus. Much of the scientific knowledge of retinal ganglion cell physiology was obtained by neural recordings of cells in the LGN. The cone-opponent mechanisms in the retina and LGN represent a fundamental physiological opponent process but do not represent the unique hues (or Hering's Opponent Colors Theory). For example, the colors that best elicit responses of the bistratified S-(L+M)-opponent neurons are best described as purplish (or lavender) and lime-green, not "blue" and "yellow". The neurons are sometimes referred to as "blue–yellow" neurons, but this is a historical artifact dating to the time when it was thought that Hering's Opponent Colors Theory was hardwired by the retina and the mismatch between the colors to which they are optimally tuned and Hering's Opponent Colors was overlooked. Cone opponent mechanisms exist in the retinas of many mammals, including monkeys, mice, and cats. In primates, the LGN contains three major classes of layers: Magnocellular layers (M, large-cell) – responsible largely for the luminance channel Parvocellular layers (P, small-cell) – responsible largely for red–green opponency Koniocellular layers (K) – responsible largely for blue–yellow opponency, poor spatial resolution, long latency Other mammals such as cats also have three cell types denoted as X (magno), Y (parvo), and W (konio). The W type is beyond most doubt homologous to the primate K type. There are some subtle differences between the M and X types as well as the Y and P types to make the correspondence unclear. === Advantage === Transmitting information in opponent-channel color space could be advantageous over transmitting it in LMS color space ("raw" signals from each cone type). There is some overlap in the wavelengths of light to which the three types of cones (L for long-wave, M for medium-wave, and S for short-wave light) respond, so it is more efficient for the visual system (from a perspective of dynamic range) to record differences between the responses of cones, rather than each type of cone's individual response. Hurvich and Jameson argued that the use of opponent-channel color space would increase color contrast, making the information easier to process by later stages of vision. === Color blindness === Color blindness can be classified by the cone cell that is affected (protan, deutan, tritan) or by the opponent channel that is affected (red–green or blue–yellow). In either case, the channel can either be inactive (in the case of dichromacy) or have a lower dynamic range (in the case of anomalous trichromacy). For example, individuals with deuteranopia see little difference between the red and green unique hues. == History == Johann Wolfgang von Goethe first studied the physiological effect of opposed colors in his Theory of Colours in 1810. Goethe arranged his color wheel symmetrically "for the colours diametrically opposed to each other in this diagram are those which reciprocally evoke each other in the eye. Thus, yellow demands purple; orange, blue; red, green; and vice versa: Thus again all intermediate gradations reciprocally evoke each other." Ewald Hering proposed opponent color theory in 1892. He thought that the colors red, yellow, green, and blue are special in that any other color can be described as a mix of them, and that they exist in opposite pairs. That is, either red or green is perceived and never greenish-red: Even though yellow is a mixture of red and green in the RGB color theory, humans