AI For Students Pros And Cons

AI For Students Pros And Cons — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Supper (Spotify)

    Supper (Spotify)

    Supper is a web-based application on the Spotify digital music streaming platform. The Supper app was born from a group of friends who had backgrounds in the music and gastronomy industries. Digital music solutions company Artisan Council later executed it. The app now sits in the top 40 applications on Spotify. == About == The Supper Spotify application matches recipes for all occasions and skill levels with a playlist for both preparation and presentation, as envisioned by the chefs themselves. Supper is credited with being one of the first apps to pair music with food. Playing on the social nature of music and food culture, users can seamlessly experience both for the first time with real time music streaming. == Supper.mx == In May 2014 Supper was launched outside of the Spotify streaming platform. Though still in partnership with Spotify, supper.mx allows users to view Supper's music + food collaborations on mobile, tablet and desktop, without the need to download Spotify directly. == Curators == All of the recipes and playlists featured on the Supper app come straight from a growing network of tastemakers, including chefs, musicians and institutions around the world. Each month the recipes and playlists are updated in conjunction with current holidays, events and seasons. === Launch === Launching in October 2013 the first edition of Supper featured content from a range of eating institutions and culture makers from the US and Australia. Brooklyn Bowl (Brooklyn) Roberta's Pizza (Brooklyn) Fancy Hanks (Melbourne) The Foresters/Queenies Upstairs (Sydney) Hipstamatic Panama House (Bondi) Sweetwater Inn (Melbourne) Soul Clap (Syd record label) Yellow Birds (Melbourne) === November 2013 === Yardbird (Hong Kong) Sonoma Bakery (Sydney) Do or Dine (Brooklyn) Cameo Gallery (Brooklyn) Hypertrak (Blog) Blue Smoke (NYC) The Crepes of Wrath (Blog) Willin Low // Wild Rocket - Wild Oats - Relish === December 2013 === The Copper Mill (Sydney) Thug Kitchen Mamak (Sydney) Tutu's (Brooklyn) Chin Chin (Melbourne) Flat Iron Steak (London) Greasy Spoon (Copenhagen) === January 2014 === Mexicali Taco & Co. (LA) Church & State (LA) Salts Cure (LA) Nopa (SF) L & E Oyster (LA) 4100 bar (LA) Golden Gopher (LA) The Pie Hole (LA) State Bird Provisions (SF) === Momofuku === In February 2014 Supper teamed up with restaurant heavy weights Momofuku. The recipes featured came from their iconic New York, Toronto and Sydney restaurants. Head office also got involved with an instructional from Brand Director Sue Chan on how to paint Momofuku vibes on to any party. === SXSW === March sees the Supper team migrate to Austin, Texas for SXSW, bringing together the best eateries the city has to offer as well as the music that has influenced them. Restaurants and eateries on board in 2014 included: The Backspace Kelis Swifts Attic Uchi Jackalope Paul Qui/East Side King Thai Kun Wonderland Hole in the Wall Justine's Brasserie The Liberty === Kelis === In April 2014 Kelis presented 5 of her recipes paired with a personal playlist for Supper. Kelis shared her recipes for apple farro, jerk ribs, New York vanilla bean cheesecake and Jerk Ribs. The Kelis/Supper collaboration coincided with the release of Kelis' 2014 album titled 'Food'. === Roberta's Pizza === In May 2014 Bushwick's Roberta's Pizza was guest curator on the Supper app and website. Included in their selections were restaurants and bars from across New York including Bun-ker Vietnamese, Old Stanley's Bar, St. Anselm, Chuko, Frank's Cocktail Lounge, Junior's Cheesecake, Xi'an Famous Foods, Xe Lua, 124 Old Rabbit and Yuji Ramen.

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  • Color reproduction

    Color reproduction

    Color reproduction is an aspect of color science concerned with producing light spectra that evoke a desired color, either through additive (light emitting) or subtractive (surface color) models. It converts physical correlates of color perception (CIE 1931 XYZ color space tristimulus values and related quantities) into light spectra that can be experienced by observers. In this way, it is the opposite of colorimetry. It is concerned with the faithful reproduction of a color in one medium, with a color in another, so it is a central concept in color management and relies heavily on color calibration. For example, food packaging must be able to faithfully reproduce the colors of the foods therein in order to appeal to a customer. This involves proper color calibration of at least four devices: Lighting, which must have a high color rendering index and not give a color cast to the object. Camera, which measures the reflected spectrum of the object and converts to a trichromatic color space (e.g. RGB). Screen, which reproduces color so a designer can proof the captured image and make color corrections as necessary. Printer, which reproduces the final color on paper.

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  • Gitter

    Gitter

    Gitter is an open-source instant messaging and chat room system for developers and users of GitLab and GitHub repositories. Gitter is provided as software as a service, with a free option providing all basic features and the ability to create a single private chat room, and paid subscription options for individuals and organisations, which allows them to create arbitrary numbers of private chat rooms. Individual chat rooms can be created for individual Git repositories on GitHub. Chatroom privacy follows the privacy settings of the associated GitHub repository: thus, a chatroom for a private (i.e. members-only) GitHub repository is also private to those with access to the repository. A graphical badge linking to the chat room can then be placed in the git repository's README file, bringing it to the attention of all users and developers of the project. Users can chat in the chat rooms, or access private chat rooms for repositories they have access to, by logging into Gitter via GitHub. Gitter is similar to Slack. Like Slack, it automatically logs all messages in the cloud. In late 2020, New Vector Limited acquired Gitter from GitLab, and announced Gitter's features would eventually be moved to New Vector's flagship product, Element, thereby replacing Gitter entirely. On February 13, 2023, Gitter migrated their service to a custom-branded Matrix instance that uses Element for its web interface. == Features prior to Migration to Matrix == Gitter supports: Notifications, which are batched up on mobile devices to avoid annoyance Inline media files Viewing and subscribing to ("starring") multiple chat rooms in one web browser tab Linking to individual files in the linked git repository Linking to GitHub issues (by typing # and then the issue number) in the linked Git repository, with hovercards showing the details of the issue GitHub-flavored Markdown in chat messages Online status for users User hovercards, based on their GitHub profiles and statistics (number of GitHub followers, etc.) Browsable and searchable message archives, grouped by month Connection from IRC clients Gitter on iOS support authentication using GitHub or Twitter === Integrations with non-GitHub sites and applications === Gitter integrates with Trello, Jenkins, Travis CI, Drone (software), Heroku, and Bitbucket, among others. === Apps === Official Gitter apps for Windows, Mac, Linux, iOS and Android are available. === Account registration === Like other chat technologies, Gitter allows clients to instant message each other. It allows people to authenticate using a GitHub account and join a chatroom from a web browser, thus not requiring one to install any software, or create additional online accounts. == History == Gitter was created by some developers who were initially trying to create a generic web-based chat product, but then wrote extra code to hook their chat application up to GitHub to meet their own needs, and realised that they could turn the combined product into a viable specialist product in its own right. Gitter came out of beta in 2014. During the beta period, Gitter delivered 1.8 million chat messages. On March 15, 2017, GitLab announced the acquisition of Gitter. Included in the announcement was the stated intent that Gitter would continue as a standalone project. It was published as open source under an MIT License as of June 2017. On September 30, 2020, New Vector Limited acquired Gitter from GitLab, and announced upcoming support for the Matrix protocol in Gitter, which went live by the end of the year. Gitter's features would eventually be moved to New Vector's flagship product, Element, thereby replacing Gitter entirely. On February 13, 2023, Gitter migrated their service to a custom-branded Matrix instance that uses Element for its web interface. == Implementation prior to Migration to Matrix == The Gitter web application is implemented entirely in JavaScript, with the back end being implemented on Node.js. The source code to the web application was formerly proprietary (it was open-sourced in June 2017), although Gitter had made numerous auxiliary projects available as open-source software, such as an IRC bridge for IRC users who prefer using IRC client applications (and their extra features) to converse in the Gitter chat rooms.

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  • Protocol Builder

    Protocol Builder

    Protocol Builder is a tool in programming languages to generate code to build protocols in a fast and reliable way. Network programming for all kinds of protocols (such as TCP, UDP, and SNMP) includes converting data to be transferred to raw bytes in the sending side and parsing these bytes in the receiving side. Protocol builders facilitate this stage, usually by automatically generating the code. Protocol Programming has many components to be developed, these are: server listener, server connection, client connection, packets, and loggers. Most protocol builders implement these components automatically so developers save time and money. Currently, there are two Protocol Builders in the market, one for C++ from UpRedSun which is for TCP and UDP protocols. The second one is for .Net languages which generates the code in C# for TCP Protocols, this tool is called .Net Protocol Builder.

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  • Instance selection

    Instance selection

    Instance selection (or dataset reduction, or dataset condensation) is an important data pre-processing step that can be applied in many machine learning (or data mining) tasks. Approaches for instance selection can be applied for reducing the original dataset to a manageable volume, leading to a reduction of the computational resources that are necessary for performing the learning process. Algorithms of instance selection can also be applied for removing noisy instances, before applying learning algorithms. This step can improve the accuracy in classification problems. Algorithm for instance selection should identify a subset of the total available data to achieve the original purpose of the data mining (or machine learning) application as if the whole data had been used. Considering this, the optimal outcome of IS would be the minimum data subset that can accomplish the same task with no performance loss, in comparison with the performance achieved when the task is performed using the whole available data. Therefore, every instance selection strategy should deal with a trade-off between the reduction rate of the dataset and the classification quality. == Instance selection algorithms == The literature provides several different algorithms for instance selection. They can be distinguished from each other according to several different criteria. Considering this, instance selection algorithms can be grouped in two main classes, according to what instances they select: algorithms that preserve the instances at the boundaries of classes and algorithms that preserve the internal instances of the classes. Within the category of algorithms that select instances at the boundaries it is possible to cite DROP3, ICF and LSBo. On the other hand, within the category of algorithms that select internal instances, it is possible to mention ENN and LSSm. In general, algorithm such as ENN and LSSm are used for removing harmful (noisy) instances from the dataset. They do not reduce the data as the algorithms that select border instances, but they remove instances at the boundaries that have a negative impact on the data mining task. They can be used by other instance selection algorithms, as a filtering step. For example, the ENN algorithm is used by DROP3 as the first step, and the LSSm algorithm is used by LSBo. There is also another group of algorithms that adopt different selection criteria. For example, the algorithms LDIS, CDIS and XLDIS select the densest instances in a given arbitrary neighborhood. The selected instances can include both, border and internal instances. The LDIS and CDIS algorithms are very simple and select subsets that are very representative of the original dataset. Besides that, since they search by the representative instances in each class separately, they are faster (in terms of time complexity and effective running time) than other algorithms, such as DROP3 and ICF. Besides that, there is a third category of algorithms that, instead of selecting actual instances of the dataset, select prototypes (that can be synthetic instances). In this category it is possible to include PSSA, PSDSP and PSSP. The three algorithms adopt the notion of spatial partition (a hyperrectangle) for identifying similar instances and extract prototypes for each set of similar instances. In general, these approaches can also be modified for selecting actual instances of the datasets. The algorithm ISDSP adopts a similar approach for selecting actual instances (instead of prototypes).

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  • Netvibes

    Netvibes

    Netvibes is a French brand of Dassault Systèmes that previously ran a web service offering a dashboard and feed reader. Currently, the company offers business intelligence tools. == History == === 2005–2012 === Founded in 2005 by Tariq Krim, the company provided software for personalized dashboards for real-time monitoring, social analytics, knowledge sharing, and decision support. === 2012–present === On February 9, 2012, Dassault Systèmes announced the acquisition of Netvibes. As of 2024, Netvibes also contains the operations of two other software companies acquired by Dassault Systèmes: Exalead: founded in 2000 by François Bourdoncle, the company provided search platforms and search-based applications for consumer and business users. On June 9, 2010, Dassault Systèmes acquired the company. Proxem: Founded in 2007 by François-Régis Caumartin, the company provided AI-powered semantic processing software and services. On June 23, 2020, Dassault Systèmes acquired Proxem and integrated its technology into the 3DEXPERIENCE® platform to complement its information intelligence applications. Dassault Systèmes announced in April 2025 that Netvibes would retire its standalone web service offering on June 2, 2025. == Activities == Brand monitoring – to track clients, customers and competitors across media sources all in one place, analyze live results with third party reporting tools, and provide media monitoring dashboards for brand clients. E-reputation management – to visualize real-time online conversations and social activity online feeds, and track new trending topics. Product marketing – to create interactive product microsites, with drag-and-drop publishing interface. Community portals – to engage online communities Personalized workspaces – to gather all essential company updates to support specific divisions (e.g. sales, marketing, human resources) and localizations. The software was a multi-lingual Ajax-based start page or web portal. It was organized into tabs, with each tab containing user-defined modules. Built-in Netvibes modules included an RSS/Atom feed reader, local weather forecasts, a calendar supporting iCal, bookmarks, notes, to-do lists, multiple searches, support for POP3, IMAP4 email as well as several webmail providers including Gmail, Yahoo! Mail, Hotmail, and AOL Mail, Box.net web storage, Delicious, Meebo, Flickr photos, podcast support with a built-in audio player, and several others. A page could be personalized further through the use of existing themes or by creating personal theme. Customized tabs, feeds and modules can be shared with others individually or via the Netvibes Ecosystem. For privacy reasons, only modules with publicly available content could be shared.

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  • Contrast-to-noise ratio

    Contrast-to-noise ratio

    Contrast-to-noise ratio (CNR) is a measure used to determine image quality. CNR is similar to the metric signal-to-noise ratio (SNR), but subtracts a term before taking the ratio. This is important when there is a significant bias in an image, such as from haze. As can be seen in the picture at right, the intensity is rather high even though the features of the image are washed out by the haze. Thus this image may have a high SNR metric, but will have a low CNR metric. One way to define contrast-to-noise ratio is: C = | S A − S B | σ o {\displaystyle C={\frac {|S_{A}-S_{B}|}{\sigma _{o}}}} where SA and SB are signal intensities for signal producing structures A and B in the region of interest and σo is the standard deviation of the pure image noise.

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  • Round-trip engineering

    Round-trip engineering

    Round-trip engineering (RTE) in the context of model-driven architecture is a functionality of software development tools that synchronizes two or more related software artifacts, such as, source code, models, configuration files, documentation, etc. between each other. The need for round-trip engineering arises when the same information is present in multiple artifacts and when an inconsistency may arise in case some artifacts are updated. For example, some piece of information was added to/changed in only one artifact (source code) and, as a result, it became missing in/inconsistent with the other artifacts (in models). == Overview == Round-trip engineering is closely related to traditional software engineering disciplines: forward engineering (creating software from specifications), reverse engineering (creating specifications from existing software), and reengineering (understanding existing software and modifying it). Round-trip engineering is often wrongly defined as simply supporting both forward and reverse engineering. In fact, the key characteristic of round-trip engineering that distinguishes it from forward and reverse engineering is the ability to synchronize existing artifacts that evolved concurrently by incrementally updating each artifact to reflect changes made to the other artifacts. Furthermore, forward engineering can be seen as a special instance of RTE in which only the specification is present and reverse engineering can be seen as a special instance of RTE in which only the software is present. Many reengineering activities can also be understood as RTE when the software is updated to reflect changes made to the previously reverse engineered specification. === Types === Various books describe two types of RTE: partial or uni-directional RTE: changes made to a higher level representation of a code and model are reflected in lower level, but not otherwise; the latter might be allowed, but with limitations that may not affect higher-level abstractions full or bi-directional RTE: regardless of changes, both higher and lower-level code and model representations are synchronized if any of them altered === Auto synchronization === Another characteristic of round-trip engineering is automatic update of the artifacts in response to automatically detected inconsistencies. In that sense, it is different from forward- and reverse engineering which can be both manual (traditionally) and automatic (via automatic generation or analysis of the artifacts). The automatic update can be either instantaneous or on-demand. In instantaneous RTE, all related artifacts are immediately updated after each change made to one of them. In on-demand RTE, authors of the artifacts may concurrently update the artifacts (even in a distributed setting) and at some point choose to execute matching to identify inconsistencies and choose to propagate some of them and reconcile potential conflicts. === Iterative approach === Round trip engineering may involve an iterative development process. After you have synchronized your model with revised code, you are still free to choose the best way to work – make further modifications to the code or make changes to your model. You can synchronize in either direction at any time and you can repeat the cycle as many times as necessary. == Software == Many commercial tools and research prototypes support this form of RTE; a 2007 book lists Rational Rose, Together, ESS-Model, BlueJ, and Fujaba among those capable, with Fujaba said to be capable to also identify design patterns. == Limitations == A 2005 book on Visual Studio notes for instance that a common problem in RTE tools is that the model reversed is not the same as the original one, unless the tools are aided by leaving laborious annotations in the source code. The behavioral parts of UML impose even more challenges for RTE. Usually, UML class diagrams are supported to some degree; however, certain UML concepts, such as associations and containment do not have straightforward representations in many programming languages which limits the usability of the created code and accuracy of code analysis/reverse engineering (e.g., containment is hard to recognize in the code). A more tractable form of round-trip engineering is implemented in the context of framework application programming interfaces (APIs), whereby a model describing the usage of a framework API by an application is synchronized with that application's code. In this setting, the API prescribes all correct ways the framework can be used in applications, which allows precise and complete detection of API usages in the code as well as creation of useful code implementing correct API usages. Two prominent RTE implementations in this category are framework-specific modeling languages and Spring Roo (Java). Round-trip engineering is critical for maintaining consistency among multiple models and between the models and the code in Object Management Group's (OMG) Model-driven architecture. OMG proposed the QVT (query/view/transformation) standard to handle model transformations required for MDA. To date, a few implementations of the standard have been created. (Need to present practical experiences with MDA in relation to RTE). == Controversies == === Code generation controversy === Code generation (forward-engineering) from models means that the user abstractly models solutions, which are connoted by some model data, and then an automated tool derives from the models parts or all of the source code for the software system. In some tools, the user can provide a skeleton of the program source code, in the form of a source code template where predefined tokens are then replaced with program source code parts during the code generation process. UML (if used for MDA) diagrams specification was criticized for lack the detail which is needed to contain the same information as is covered with the program source. Some developers even claim that "the Code is the design". == Disadvantages == There is a serious risk that the generated code will rapidly differ from the model or that the reverse-engineered model will lose its reflection on the code or a mix of these two problems as result of cycled reengineering efforts. Regarding behavioral/dynamic part of UML for features like statechart diagram there is no equivalents in programming languages. Their translation during code-generation will result in common programming statement (.e.g if,switch,enum) being either missing or misinterpreted. If edited and imported back may result in different or incomplete model. The same goes for code snippets used for code generation stage for the pattern-implementation and user-specific logic: intermixed they may not be easily reverse-engineered back. There is also general lack of advanced tooling for modelling that are comparable to that of modern IDEs (for testing, debugging, navigation, etc.) for general-purpose programming languages and domain-specific languages. == Examples in software engineering == Perhaps the most common form of round-trip engineering is synchronization between UML (Unified Modeling Language) models and the corresponding source code and entity–relationship diagrams in data modelling and database modelling. Round-trip engineering based on Unified Modeling Language (UML) needs three basic tools for software development: Source Code Editor; UML Editor for the Attributes and Methods; Visualisation of UML structure

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  • Visual hull

    Visual hull

    A visual hull is a geometric entity created by shape-from-silhouette 3D reconstruction technique introduced by A. Laurentini. This technique assumes the foreground object in an image can be separated from the background. Under this assumption, the original image can be thresholded into a foreground/background binary image, which we call a silhouette image. The foreground mask, known as a silhouette, is the 2D projection of the corresponding 3D foreground object. Along with the camera viewing parameters, the silhouette defines a back-projected generalized cone that contains the actual object; this cone is called a silhouette cone. The intersection of the two silhouette cones defines a visual hull. which is a bounding geometry of the actual 3D object. When the reconstructed geometry is only used for rendering from a different viewpoint, the implicit reconstruction together with rendering can be done using graphics hardware. == In two dimensions == A technique used in some modern touchscreen devices employs cameras placed in the corners situated opposite infrared LEDs. The one-dimensional projection (shadow) of objects on the surface may be used to reconstruct the convex hull of the object. Visual hull generation method has also been used within experimental tele-meeting systems that aim to allow a user in a remote location to interact with virtual objects. The method uses multiple cameras to capture the real-world movements and interactions of the "sender", employing hardware-accelerated volumetric visual hull representation to create 3D volume from 2D multi-view images. Its ultimate aim is to allow 3D collaboration between the two users in the virtual realm, with the visual hull technique reducing the computational power required to allow this type of interaction and enabling the use of consumer goods such as the Wii Remote as a tool for interaction.

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  • Actifsource

    Actifsource

    Actifsource is a domain-specific modeling workbench. It is realized as plug-in for the software development environment Eclipse. Actifsource supports the creation of multiple domain models which can be linked together. It comes with a UML-like graphical editor to create domain-specific languages and a general graphical editor to edit structures in the created languages. It supports code generation using user-defined generic code templates which are directly linked to the domain models. Code generation is integrated into Eclipse's incremental build process. == Interoperability == Actifsource can use models from other modelling tools by importing and exporting the ecore format which is defined by the Eclipse Modeling Framework. == Licensing policy == There are two versions of actifsource available: The free community edition which can be used freely for non-commercial projects and the enterprise edition which contains additional features. The enterprise edition comes with customer support and maintenance for a limited period of time. This package allows the customers to upgrade to new versions and maintenance releases during their support period.

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  • Thinkfree Office

    Thinkfree Office

    Thinkfree Office is a web-based commercial office productivity suite developed by South Korea-based Thinkfree Inc. It includes Word (a word processor), Spreadsheet (a spreadsheet) and Presentation (a presentation program). They are compatible with Microsoft Office's Word, PowerPoint, and Excel. It also features collaborative editing. The product is hosted on the client's server. == Supported file formats == Thinkfree Office supports ISO/IEC international standard ISO/IEC 26300 Open Document Format for Office Applications (odf, odt, odp, ods, odg). It also supports Microsoft's XML formats (docx, pptx, xlsx) and Microsoft's legacy binary formats (doc, ppt, xls). == Naming == The software was previously marketed under different names, such as Thinkfree Server, Thinkfree Online, Hancom Office Online, and Hancom Office Web. Eventually, the brand was consolidated under the name Thinkfree Office. == History == In June 2000, Thinkfree Inc. released Thinkfree Office, based in Silicon Valley, California. It is recognized as the world's first online office editor (predating Google Docs and Microsoft 365) and attracted significant media coverage, including reports on CNN. In 2001, Microsoft CEO Steve Ballmer highlighted Thinkfree as a significant competitor in a magazine interview, considering it a potential threat to his company, second only to Linux. In November 2003, Hancom, a South Korean office software company, signed a memorandum of understanding and subsequently acquired Thinkfree. In January 2004, Thinkfree expanded into other foreign markets. Subsidiary Haansoft USA, Inc. was created in San Jose, California to begin formal commercial operations in the US market. At the same time, a partnership was established with Riverdeep with the purpose of improving marketshare. In February 2004, expansion into the Japanese market began. A commercial agency agreement was signed with PSI in Shinjuku, Japan, which allowed for localized distribution. In addition, a global agreement was entered into with Yamada Denki, one of the three main computer distributors in Japan, for a total of 180,000 units. In May 2006, Thinkfree Office received the "Product of the Year" award at the Well-Connected Awards, USA. In January 2009, Thinkfree Mobile was launched at CES 2009 in Las Vegas. In April 2009, Thinkfree Live, Korea's first web office service, was launched. In June 2018, a partnership was formed with Amazon Web Services to integrate Thinkfree Office into WorkDocs, an in-house office suite. In October 2023, Hancom split its online office business unit as "Thinkfree Inc.".

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  • Digital image

    Digital image

    A digital image is an image composed of picture elements, also known as pixels, each with finite, discrete quantities of numeric representation for its intensity or gray level that is an output from its two-dimensional functions fed as input by its spatial coordinates denoted with x, y on the x-axis and y-axis, respectively. An image can be vector or raster type. By itself, the term "digital image" usually refers to raster images or bitmapped images (as opposed to vector images). == Raster == Raster images have a finite set of digital values, called picture elements or pixels. The digital image contains a fixed number of rows and columns of pixels. Pixels are the smallest individual element in an image, holding quantized values that represent the brightness of a given color at any specific point. Typically, the pixels are stored in computer memory as a raster image or raster map, a two-dimensional array of small integers. These values are often transmitted or stored in a compressed form. Raster images can be created by a variety of input devices and techniques, such as digital cameras, scanners, coordinate-measuring machines, seismographic profiling, airborne radar, and more. They can also be synthesized from arbitrary non-image data, such as mathematical functions or three-dimensional geometric models; the latter being a major sub-area of computer graphics. The field of digital image processing is the study of algorithms for their transformation. === Raster file formats === Most users come into contact with raster images through digital cameras, which use any of several image file formats. Some digital cameras give access to almost all the data captured by the camera, using a raw image format. The Universal Photographic Imaging Guidelines (UPDIG) suggests these formats be used when possible since raw files produce the best quality images. These file formats allow the photographer and the processing agent the greatest level of control and accuracy for output. Their use is inhibited by the prevalence of proprietary information (trade secrets) for some camera makers, but there have been initiatives such as OpenRAW to influence manufacturers to release these records publicly. An alternative may be Digital Negative (DNG), a proprietary Adobe product described as "the public, archival format for digital camera raw data". Although this format is not yet universally accepted, support for the product is growing, and increasingly professional archivists and conservationists, working for respectable organizations, variously suggest or recommend DNG for archival purposes. == Vector == Vector images resulted from mathematical geometry (vector). In mathematical terms, a vector consists of both a magnitude, or length, and a direction. Often, both raster and vector elements will be combined in one image; for example, in the case of a billboard with text (vector) and photographs (raster). Example of vector file types are EPS, PDF, and AI. == Image viewing == Image viewer software displayed on images. Web browsers can display standard internet images formats including JPEG, GIF and PNG. Some can show SVG format which is a standard W3C format. In the past, when the Internet was still slow, it was common to provide "preview" images that would load and appear on the website before being replaced by the main image (to give a preliminary impression). Now Internet is fast enough and this preview image is seldom used. Some scientific images can be very large (for instance, the 46 gigapixel size image of the Milky Way, about 194 GB in size). Such images are difficult to download and are usually browsed online through more complex web interfaces. Some viewers offer a slideshow utility to display a sequence of images. == History == Early digital fax machines such as the Bartlane cable picture transmission system preceded digital cameras and computers by decades. The first picture to be scanned, stored, and recreated in digital pixels was displayed on the Standards Eastern Automatic Computer (SEAC) at NIST. The advancement of digital imagery continued in the early 1960s, alongside development of the space program and in medical research. Projects at the Jet Propulsion Laboratory, MIT, Bell Labs and the University of Maryland, among others, used digital images to advance satellite imagery, wirephoto standards conversion, medical imaging, videophone technology, character recognition, and photo enhancement. Rapid advances in digital imaging began with the introduction of MOS integrated circuits in the 1960s and microprocessors in the early 1970s, alongside progress in related computer memory storage, display technologies, and data compression algorithms. The invention of computerized axial tomography (CAT scanning), using x-rays to produce a digital image of a "slice" through a three-dimensional object, was of great importance to medical diagnostics. As well as origination of digital images, digitization of analog images allowed the enhancement and restoration of archaeological artifacts and began to be used in fields as diverse as nuclear medicine, astronomy, law enforcement, defence and industry. Advances in microprocessor technology paved the way for the development and marketing of charge-coupled devices (CCDs) for use in a wide range of image capture devices and gradually displaced the use of analog film and tape in photography and videography towards the end of the 20th century. The computing power necessary to process digital image capture also allowed computer-generated digital images to achieve a level of refinement close to photorealism. === Digital image sensors === The first semiconductor image sensor was the CCD, developed by Willard S. Boyle and George E. Smith at Bell Labs in 1969. While researching MOS technology, they realized that an electric charge was the analogy of the magnetic bubble and that it could be stored on a tiny MOS capacitor. As it was fairly straightforward to fabricate a series of MOS capacitors in a row, they connected a suitable voltage to them so that the charge could be stepped along from one to the next. The CCD is a semiconductor circuit that was later used in the first digital video cameras for television broadcasting. Early CCD sensors suffered from shutter lag. This was largely resolved with the invention of the pinned photodiode (PPD). It was invented by Nobukazu Teranishi, Hiromitsu Shiraki and Yasuo Ishihara at NEC in 1980. It was a photodetector structure with low lag, low noise, high quantum efficiency and low dark current. In 1987, the PPD began to be incorporated into most CCD devices, becoming a fixture in consumer electronic video cameras and then digital still cameras. Since then, the PPD has been used in nearly all CCD sensors and then CMOS sensors. The NMOS active-pixel sensor (APS) was invented by Olympus in Japan during the mid-1980s. This was enabled by advances in MOS semiconductor device fabrication, with MOSFET scaling reaching smaller micron and then sub-micron levels. The NMOS APS was fabricated by Tsutomu Nakamura's team at Olympus in 1985. The CMOS active-pixel sensor (CMOS sensor) was later developed by Eric Fossum's team at the NASA Jet Propulsion Laboratory in 1993. By 2007, sales of CMOS sensors had surpassed CCD sensors. === Digital image compression === An important development in digital image compression technology was the discrete cosine transform (DCT), a lossy compression technique first proposed by Nasir Ahmed in 1972. DCT compression is used in JPEG, which was introduced by the Joint Photographic Experts Group in 1992. JPEG compresses images down to much smaller file sizes, and has become the most widely used image file format on the Internet. == Mosaic == In digital imaging, a mosaic is a combination of non-overlapping images, arranged in some tessellation. Gigapixel images are an example of such digital image mosaics. Satellite imagery are often mosaicked to cover Earth regions. Interactive viewing is provided by virtual-reality photography.

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  • BBC Own It

    BBC Own It

    The BBC Own It app was a British information site designed to protect and support children using the Internet. The app was launched in 2017 and retired in 2022, though the website retired in 2024 and has since moved to BBC Teach. As part of the BBC's partnership with Internet Matters, the not-for-profit contributed to content on the BBC Own It website. == History == In 2016, The Royal Foundation of The Duke and Duchess of Cambridge established The Royal Foundation Taskforce on the Prevention of Cyberbullying. Work began in 2017 by the BBC to create an app about cyberbullying and online safety (later titled Own It) in response to a call for action from the Taskforce. In December 2017, the BBC launched Own It. In November 2018, work on the BBC Own It App was announced by Prince William. In September 2019, the BBC Own It App was launched into the AppStore and Google Play. In 2022, the BBC discontinued the app, although the website was still active, however in 2024, the website was discontinued, and now any links to the website now redirect to a BBC Teach page. == Awards == UXUK award for Best Education or Learning Experience (2019) Banff World Media Festival Rockies Award for Children & Youth Interactive Content (2020) CogX Award for Best Innovation In Natural Language Processing (2020)

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  • Clean Email

    Clean Email

    Clean Email is an automated software as a service email management application which identifies and clears junk mail from inboxes. The service uses a subscription business model with a free trial for the first 1,000 emails. and is available on macOS, iOS, Android, and on the web. == History == Clean Email is a self-funded company headquartered in Los Angeles, California. Initially developed by the founder for personal use, the service was designed to address the growing issue of inbox clutter and privacy concerns. In 2017, John Gruber recognized Clean Email as a trustworthy alternative to Unroll.me after the latter was found to be selling user data. == Features == Clean Email uses algorithms to identify and categorize emails, enabling users to group, remove, label, and archive email messages in bulk. Its Unsubscriber tool consolidates all subscriptions and newsletters into a single view for quick management, allowing users to bulk unsubscribe or temporarily pause mail. Its Screener feature transforms the inbox into an "opt-in" system, enabling users to pre-approve mail from new senders. Cleaning Suggestions identifies frequently cleaned mail, recommending actions accordingly. Additional functionalities include automatic deletion of aging emails, delivery of messages to specified folders, and options to mute or block senders.

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  • Tradeshift

    Tradeshift

    Tradeshift is a cloud based business network and platform for purchase-to-pay automation, supply chain payments, marketplaces, virtual cards and supply chain financing. Its 2018 round of funding, led by Goldman Sachs, raised US$250 million at a valuation of $1.1 billion, giving the company unicorn status. Tradeshift is headquartered in San Francisco, California and has offices in London, Copenhagen, Bucharest and Kuala Lumpur. Tradeshift has reprocessed over $1 trillion USD through transactions on its network. == History == Tradeshift was founded in 2010 by Christian Lanng, Mikkel Hippe Brun, and Gert Sylvest. Inspiration for Tradeshift came after they created the world's first large scale peer-to-peer infrastructure for an e-business called NemHandel. The founders also had leading roles (Governing board member, Technical Director) in the European Commission project PEPPOL inside the European Union. In 2010, the Tradeshift platform launched in May in Copenhagen. Tradeshift won the European Startup Awards in the category of "Best Business or Enterprise Startup." In 2011, Tradeshift made its app marketplace available. In 2012, Tradeshift moved their headquarters from Copenhagen to San Francisco. In 2013, Tradeshift opened an R&D center in Suzhou, China. Tradeshift opened an additional office in London. And LATAM e-invoicing capabilities were added through partnership with Invoiceware. In 2014, Tradeshift expanded with offices in Tokyo, Paris, and Munich. The EU Commission officially approved the Universal Business Language (UBL) data format – a format Tradeshift supports – as eligible for referencing in tenders from public administrations. In 2015, Tradeshift won the Circulars "Digital Disruptor" Award at the WEF conference in Davos, Switzerland. Tradeshift also acquired product information management company Merchantry, and launched e-procurement and supplier risk management solutions. In 2016, Tradeshift acquired Hyper Travel and secured a $75 million series-D round funding. In 2017, Tradeshift acquired IBX Business Network and launches Tradeshift Ada. In 2018, Tradeshift secured a $250 million series-E round funding. and launched Blockchain Payments, the latter as part of Tradeshift Pay. In December 2018 Tradeshift acquired Babelway, an online B2B integration platform. The acquisition added three new office locations to Tradeshift (Salt Lake City, Louvain-la-neuve, Belgium, Cairo Egypt). In Q3 2018, Tradeshift reported year-over-year revenue growth of 400%, new bookings growth of 284%, and gross merchandise volume (GMV) growth of 262%. New total contract value also grew by US$47 million. Additionally, it added 27 new customers including Hertz, Shiseido, ECU and multiple Fortune 500 companies. In July 2023, HSBC and Tradeshift announced an agreement to launch a new, jointly owned business focused on the development of embedded finance solutions and financial services apps. As part of the agreement, HSBC made a $35 million investment into Tradeshift and joined its board. The agreement was part of a funding round which is expected to raise a minimum of $70 million from HSBC and other investors. The new joint venture will allow HSBC and Tradeshift to deploy a range of digital solutions across Tradeshift and other platforms. This includes payment and fintech services embedded into trade, e-commerce and marketplace experiences. In September 2023, CEO Lanng was fired for "gross misconduct on multiple grounds," including "allegations of sexual assault and harassment." Tradeshift was alleged to have fired his accuser after she complained to the company's human resources department, its co-founders and members of its board of directors about his abuse. == Financials == The company's valuation as of May 2018 was $1.1 billion. Tradeshift is now considered a unicorn, and, according to Bloomberg, will not need any further funding. Jan 14, 2020, Tradeshift announced that they had raised $240 million in Series F finance. == Acquisitions == In 2015, Tradeshift acquired product information management company Merchantry. Merchantry is a retail product information management (PIM) software for multi-vendor ecommerce retailers. In 2016, Tradeshift acquired Hyper Travel. Hyper Travel is a travel management service that allows customers to access travel agents via its native messaging apps, SMS, and email. In 2017, Tradeshift acquired IBX Group. In 2018, Tradeshift acquired Babelway, an online B2B integration platform.

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