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  • C-RAN

    C-RAN

    C-RAN (Cloud-RAN), also referred to as Centralized-RAN, is an architecture for cellular networks. C-RAN is a centralized, cloud computing-based architecture for radio access networks that supports 2G, 3G, 4G, 5G and future wireless communication standards. Its name comes from the four 'C's in the main characteristics of C-RAN system, "Clean, Centralized processing, Collaborative radio, and a real-time Cloud Radio Access Network". == Background == Traditional cellular, or Radio Access Networks (RAN), consist of many stand-alone base stations (BTS). Each BTS covers a small area, whereas a group BTS provides coverage over a continuous area. Each BTS processes and transmits its own signal to and from the mobile terminal, and forwards the data payload to and from the mobile terminal and out to the core network via the backhaul. Each BTS has its own cooling, back haul transportation, backup battery, monitoring system, and so on. Because of limited spectral resources, network operators 'reuse' the frequency among different base stations, which can cause interference between neighboring cells. There are several limitations in the traditional cellular architecture. First, each BTS is costly to build and operate. Moore's law helps reduce the size and power of an electrical system, but the supporting facilities of the BTS are not improved quite as well. Second, when more BTS are added to a system to improve its capacity, interference among BTS is more severe as BTS are closer to each other and more of them are using the same frequency. Third, because users are mobile, the traffic of each BTS fluctuates (called 'tide effect'), and as a result, the average utilization rate of individual BTS is pretty low. However, these processing resources cannot be shared with other BTS. Therefore, all BTS are designed to handle the maximum traffic, not average traffic, resulting in a waste of processing resources and power at idle times. == Evolution of base station architecture == === All-in-one macro base station === In the 1G and 2G cellular networks, base stations had an all-in-one architecture. Analog, digital, and power functions were housed in a single cabinet as large as a refrigerator. Usually the base station cabinet was placed in a dedicated room along with all necessary supporting facilitates such as power, backup battery, air conditioning, environment surveillance, and backhaul transmission equipment. The RF signal is generated by the base station RF unit and propagates through pairs of RF cables up to the antennas on the top of a base station tower or other mounting points. This all-in-one architecture was mostly found in macro cell deployments. === Distributed base station === For 3G, a distributed base station architecture was introduced by Ericsson, Nokia, Huawei, and other leading telecom equipment vendors. In this architecture the radio function unit, also known as the remote radio head (RRH), is separated from the digital function unit, or baseband unit (BBU) by fiber. Digital baseband signals are carried over fiber, using the Open Base Station Architecture Initiative (OBSAI) or Common Public Radio Interface (CPRI) standard. The RRH can be installed on the top of tower close to the antenna, reducing the loss compared to the traditional base station where the RF signal has to travel through a long cable from the base station cabinet to the antenna at the top of the tower. The fiber link between RRH and BBU also allows more flexibility in network planning and deployment as they can be placed a few hundred meters or a few kilometers away. Most modern base stations now use this decoupled architecture. === C-RAN/Cloud-RAN === C-RAN may be viewed as an architectural evolution of the above distributed base station system. It takes advantage of many technological advances in wireless, optical and IT communications systems. For example, it uses the latest CPRI standard, low cost Coarse or Dense Wavelength Division Multiplexing (CWDM/ DWDM) technology, and mmWave to allow transmission of baseband signal over long distance thus achieving large scale centralised base station deployment. It applies recent Data Centre Network technology to allow a low cost, high reliability, low latency and high bandwidth interconnect network in the BBU pool. It utilizes open platforms and real-time virtualization technology rooted in cloud computing to achieve dynamic shared resource allocation and support multi-vendor, multi-technology environments. == Architecture overview == C-RAN architecture has the following characteristics that are distinct from other cellular architectures: Large scale centralized deployment: Allows many RRHs to connect to a centralized BBU pool. The maximum distance can be 20km in fiber link for 4G (LTE/LTE-A) systems, and even longer distances (40~80km) for 3G (WCDMA/TD-SCDMA) and 2G (GSM/CDMA) systems. Native support to Collaborative Radio technologies: Any BBU can talk with any other BBU within the BBU pool with very high bandwidth (10 Gbit/s and above) and low latency (10 μs level). This is enabled by the interconnection of BBUs in the pool. This is one major difference from BBU Hotelling, or base station Hotelling; in the latter case, the BBUs of different base stations are simply stacked together and have no direct link between them to allow physical layer co-ordination. Real-time virtualization capability based on open platform: This is different from traditional base stations built on proprietary hardware, where the software and hardware are close-sourced and provided by single vendors. In contrast, a C-RAN BBU pool is built on open hardware, like x86/ARM CPU based servers, and interface cards that handle fiber links to RRHs and inter-connections in the pool. Real-time virtualization ensures that resources in the pool can be allocated dynamically to base station software stacks, say 4G/3G/2G function modules from different vendors, according to network load. However, to satisfy the strict timing requirements of wireless communication systems, the real-time performance for C-RAN is at the level of tens of microseconds, which is two orders of magnitude better than the millisecond level 'real-time' performance usually seen in Cloud Computing environments. == Similar architecture and systems == KT, a telecom operator in the Republic of Korea, introduced a Cloud Computing Center (CCC) system in their 3G (WCDMA/HSPA) and 4G (LTE/LTE-A) network in 2011 and 2012. The concept of CCC is basically the same as C-RAN. SK Telecom has also deployed Smart Cloud Access Network (SCAN) and Advanced-SCAN in their 4G (LTE/LTE-A) network in Korea no later than 2012. In 2014, Airvana (now CommScope) introduced OneCell, a C-RAN-based small cell system designed for enterprises and public spaces. == Competing architectures in cellular network evolution == === All-in-one BTS === One major alternative solution that is addressing similar challenges of RAN, is the small size, all-in-one outdoor BTS. Thanks to the achievements in the semiconductor industry, all the functionality of a BTS, including RF, baseband processing, MAC processing and package level processing, can now be implemented in a volume of <50 liters. This makes the system small and weatherproof, reduces the difficulty of BTS site choice and construction, eliminates the air conditioning requirement, and thus reduces operational costs. However, because each BTS is still working on its own, it cannot readily make use of the collaboration algorithms to reduce the interference between neighboring BTSs. It is also relatively hard to upgrade or repair because the all-in-one BTS units are usually mounted near the antenna. More processing units in less-protected environments also implies a higher failure rate compared to C-RAN, which only has the RRU deployed outdoors. The advantage of Cloud RAN lies in its ability to implement LTE-Advanced features such as Coordinated MultiPoint (CoMP) with very low latency between multiple radio heads. However, the economic benefit of improvements such as CoMP can be negated by the higher backhaul costs for some operators. === Small cell === The main competition between small cell and C-RAN occurs in two deployment scenarios: outdoor hotspot coverage and indoor coverage. == Academic research and publications == As one of the promising evolution paths for future cellular network architecture, C-RAN has attracted high academic research interest. Meanwhile, because the native support of cooperative radio capability built into the C-RAN architecture, it also enables many advanced algorithms that were hard to implement in cellular networks, including Cooperative Multi-Point Transmission/Receiving, Network Coding, etc. In October 2011, Wireless World Research Forum 27 was hosted in Germany, when China Mobile was invited to give a C-RAN presentation. In August 2012, IEEE C-RAN 2012 workshop was hosted in Kunming, China. CRC Press published a book, "Green Communications: Theore

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  • List of Go software and tools

    List of Go software and tools

    This is a list of Go software and tools, including compilers, development environments, build tools, testing frameworks, web frameworks, database tools, and related software for the Go programming language. == Core toolchain == Go — programming language and toolchain go command — build and package tool gofmt — source code formatter go vet — static analysis tool == Compilers and runtimes == gc — default Go compiler gccgo — GCC front end for Go GopherJS — Go-to-JavaScript compiler gollvm — Go compiler using the LLVM backend llgo — experimental Go frontend for LLVM TinyGo — compiler for embedded systems and WebAssembly Yaegi — Go interpreter == Development environments and editors == Emacs — text editor with Go support GoLand — JetBrains integrated development environment LiteIDE — Go-focused integrated development environment Neovim — text editor with Go support TextMate — text editor with Go support Vim — text editor with Go support Visual Studio Code — editor with Go support == Language servers and editor tools == delve — debugger gopls — Go language server golangci-lint — lint runner revive — linter staticcheck — static analysis tool == Build, dependency and release tools == Air — live reload development tool dep — deprecated dependency manager Go modules — dependency management system Goreleaser — release automation tool Mage — build tool Task — task runner == Testing and benchmarking == benchstat — benchmark comparison tool Ginkgo — testing framework GoMock — mock generation tool testify — testing toolkit testing — standard testing package == Web frameworks and HTTP tools == Beego — web framework Caddy — web server Chi — router Echo — web framework Fiber — web framework Gin — web framework Gorilla Mux — router Hugo — static site generator Revel — web framework Traefik — reverse proxy and load balancer == RPC and API tools == Goa — API design framework gRPC — remote procedure call framework grpc-gateway — REST gateway oapi-codegen — OpenAPI code generator Swag — OpenAPI documentation tool == Database and ORM tools == Bun — SQL toolkit and ORM CockroachDB client libraries — database drivers and tools ent — entity framework GORM — object–relational mapper sqlx — SQL toolkit == Command-line and terminal tools == Bubble Tea — terminal user interface framework Cobra — command-line framework pflag — flag parsing library urfave/cli — command-line framework Viper — configuration library == GUI toolkits and application frameworks == Fyne — cross-platform graphical user interface toolkit == Documentation, generation and analysis == errcheck — unchecked error checker godoc — documentation tool goimports — import management tool mockgen — mock generator pkgsite — package documentation site Prometheus — monitoring and alerting toolkit stringer — code generation tool wire — dependency injection code generator == Package hosting and community services == GoCenter — former Go package repository pkg.go.dev — package documentation and discovery site proxy.golang.org — module proxy == Major applications written in Go == Consul — service networking platform Docker — containerization platform InfluxDB — time-series database written in Go Kubernetes — container orchestration platform Ollama — platform for running and managing large language models locally Terraform — infrastructure as code tool Vault — secrets management tool

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  • Color image pipeline

    Color image pipeline

    An image pipeline or video pipeline is the set of components commonly used between an image source (such as a camera, a scanner, or the rendering engine in a computer game), and an image renderer (such as a television set, a computer screen, a computer printer or cinema screen), or for performing any intermediate digital image processing consisting of two or more separate processing blocks. An image/video pipeline may be implemented as computer software, in a digital signal processor, on an FPGA, or as fixed-function ASIC. In addition, analog circuits can be used to do many of the same functions. Typical components include image sensor corrections (including debayering or applying a Bayer filter), noise reduction, image scaling, gamma correction, image enhancement, colorspace conversion (between formats such as RGB, YUV or YCbCr), chroma subsampling, framerate conversion, image compression/video compression (such as JPEG), and computer data storage/data transmission. Typical goals of an imaging pipeline may be perceptually pleasing end-results, colorimetric precision, a high degree of flexibility, low cost/low CPU utilization/long battery life, or reduction in bandwidth/file size. Some functions may be algorithmically linear. Mathematically, those elements can be connected in any order without changing the end-result. As digital computers use a finite approximation to numerical computing, this is in practice not true. Other elements may be non-linear or time-variant. For both cases, there is often one or a few sequences of components that makes sense for optimum precision and minimum hardware-cost/CPU-load.

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  • Linux Trace Toolkit

    Linux Trace Toolkit

    The Linux Trace Toolkit (LTT) is a set of tools that is designed to log program execution details from a patched Linux kernel and then perform various analyses on them, using console-based and graphical tools. LTT has been mostly superseded by its successor LTTng (Linux Trace Toolkit Next Generation). LTT allows the user to see in-depth information about the processes that were running during the trace period, including when context switches occurred, how long the processes were blocked for, and how much time the processes spent executing vs. how much time the processes were blocked. The data is logged to a text file and various console-based and graphical (GTK+) tools are provided for interpreting that data. In order to do data collection, LTT requires a patched Linux kernel. The authors of LTT claim that the performance hit for a patched kernel compared to a regular kernel is minimal; Their testing has reportedly shown that this is less than 2.5% on a "normal use" system (measured using batches of kernel makes) and less than 5% on a file I/O intensive system (measured using batches of tar). == Usage == === Collecting trace data === Data collection is Started by: trace 15 foo This command will cause the LTT tracedaemon to do a trace that lasts for 15 seconds, writing trace data to foo.trace and process information from the /proc filesystem to foo.proc. The trace command is actually a script which runs the program tracedaemon with some common options. It is possible to run tracedaemon directly and in that case, the user can use a number of command-line options to control the data which is collected. For the complete list of options supported by tracedaemon, see the online manual page for tracedaemon. === Viewing the results === Viewing the results of a trace can be accomplished with: traceview foo This command will launch a graphical (GTK+) traceview tool that will read from foo.trace and foo.proc. This tool can show information in various interesting ways, including Event Graph, Process Analysis, and Raw Trace. The Event Graph is perhaps the most interesting view, showing the exact timing of events like page faults, interrupts, and context switches, in a simple graphical way. The traceview command is a wrapper for a program called tracevisualizer. For the complete list of options supported by tracevisualizer, see the online manual page for tracevisualizer.

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  • Mobile Passport Control

    Mobile Passport Control

    Mobile Passport Control (MPC) is a mobile app that enables eligible travelers entering the United States to submit their passport information and customs declaration form to Customs and Border Protection via smartphone or tablet and go through the inspections process using an expedited lane. It is available to "U.S. citizens, U.S. lawful permanent residents, Canadian B1/B2 citizen visitors and returning Visa Waiver Program travelers with approved ESTA". The app is available on iOS and Android devices and is operational at 34 US airports, 14 international airports offering preclearance facilities, and 4 seaports. The use of Mobile Passport Control operations have increased threefold from 2016 to 2017. == History == Mobile Passport Control operations were launched in Atlanta at the Hartsfield-Jackson International Airport in 2016 and is now available at 34 U.S. airports, 14 international airports that offer preclearance and 4 U.S. cruise ports. The Mobile Passport app is authorized by CBP and sponsored by the Airports Council International-North America, Boeing, and the Port of Everglades. Airside Mobile, Inc. secured a Series A funding of $6 million in the fall of 2017. == How it works == During the customs process at the Federal Inspection Service (FIS) area of a U.S. airport, travelers arriving from international locations typically wait in long lines before presenting passports and paperwork and verbally answering questions made by CBP officials. Eligible travelers who have downloaded the Mobile Passport app can expedite this process by submitting information regarding their passport and trip details, and a newly-taken selfie, via their mobile device to CBP officials, then access an expedited line. Mobile Passport Control users will be required to show their physical passport(s) and briefly talk to a CBP officer. == Locations == === US airports === Atlanta (ATL) Baltimore (BWI) Boston (BOS) Charlotte (CLT) Chicago (ORD) Dallas/Ft Worth (DFW) Denver (DEN) Detroit (DTW) as of 7/2024 Ft. Lauderdale (FLL) Honolulu (HNL) Houston (HOU and IAH) Kansas City (MCI) Las Vegas (LAS) Los Angeles (LAX) Miami (MIA) Minneapolis (MSP) New York (JFK) Newark (EWR) Oakland (OAK) Orlando (MCO) Palm Beach (PBI) Philadelphia (PHL) Phoenix (PHX) Pittsburgh (PIT) Portland (PDX) Sacramento (SMF) San Diego (SAN) San Francisco (SFO) San Jose (SJC) San Juan (SJU) Seattle (SEA) Tampa (TPA) Washington Dulles (IAD) === International Preclearance locations === Abu Dhabi (AUH) Aruba (AUA) Bermuda (BDA) Calgary (YYC) Dublin (DUB) Edmonton (YEG) Halifax (YHZ) Montreal (YUL) Nassau (NAS) Ottawa (YOW) Shannon (SNN) Toronto (YYZ) Vancouver (YVR) Winnipeg (YWG) Sepinggan (BPN) === Seaports === Fort Lauderdale (PEV) Miami (MSE) San Juan (PUE) West Palm Beach (WPB)

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  • List & Label

    List & Label

    List & Label is a professional reporting tool for software developers. It provides comprehensive design, print and export functions. The software component runs on Microsoft Windows and can be implemented in desktop, cloud and web applications. List & Label can be used to create user-defined dashboards, lists, invoices, forms and labels. It supports many development environments, frameworks and programming languages such as Microsoft Visual Studio, Embarcadero RAD Studio, .NET Framework, .NET Core, ASP.NET, C++, Delphi, Java, C Sharp and some more. List & Label either retrieves data from various sources via data binding, or works database independent. Reports are designed and created in the so-called List & Label Designer and then exported into a multitude of formats like PDF, Excel, XHTML and RTF. Since version 27 a web report designer for ASP.NET MVC is available. == History == The product was first released in 1992 by combit. The current version is 30. A new major version of List & Label is released every fall, usually in October. Updates are available several times a year via Service Pack. == Features == === Report Designer === The Designer enables users to graphically layout the report. It offers report objects such as tables, charts, crosstabs, gauges, HTML, conditionally formatted text, barcodes, matrix codes, and graphics, and is extensible using third-party add-ons. User applications can interact with the report via the programmable object model of the report. The real-time preview functionality allows users to view changes instantly. Usability features include layer and appearance management, enabling conditional logic to dynamically control the visibility of objects in reports. The Designer also supports the inclusion of multiple report containers in a single project, accommodating complex layouts such as parallel tables and charts. A formula wizard and support for scripting languages such as C# facilitate advanced calculations and logic. The Designer's object model (DOM) provides developers with the ability to modify layouts and behaviors programmatically. === Web Report Designer === The web report designer works browser-based and independent from printer drivers and spoolers - that makes deployments to the cloud easier. Just like the use of the Visual Studio deployment pipeline. === Data Sources === Depending on the programming language, the product offers automatic support for data sources: Databases such as Microsoft SQL Server, Oracle, MySQL, PostgreSQL, IBM Db2, SQLite, MariaDB, MongoDB, Cosmos DB XML data, CSV Business objects Data sources that can be accessed via OLE DB, ODBC or ADO.NET LINQ data and data from web services GraphQL Additionally, the product offers support for unbound data and can be extended to support other data sources via interfaces. === Output Options === Printer Image Formats (JPEG, BMP, EMF, TIFF, PNG, SVG, HEIF, WebP) Document Formats: PDF, PDF/A, Word (DOCX), Excel (XLS), PowerPoint (PPTX) HTML, XHTML, MHTML Barcodes Plain Text, RTF, CSV, JSON XML, ZIP, Email, JSON List & Label preview file === Target Audience === List & Label can be used in Windows development environments. While it competes most notably on the Microsoft .NET platform with other products such as Crystal Reports, SQL Server Reporting Services, ActiveReports, there are few competing products for other programming languages (e.g. Progress, Alaska Xbase++, Visual DataFlex). == Awards == Reader's Choice Award 2005–2008 Stevie Awards 2021: Best Technology for Data Visualization Top 100 Publisher Award Component Source 2013-2014, 2014-2015,2016, 2018, 2019, 2020, 2021, 2022

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  • DesktopTwo

    DesktopTwo

    Desktoptwo was a free Webtop (whose URL was desktoptwo.com and which is now a parked domain) developed by Sapotek (whose URL was sapotek.com, which also is now a parked domain). It's also been called a WebOS although Sapotek stated on its website that the term is premature and presumptuous. It mimics the look, feel and functionality of the desktop environment of an operating system. The software only reached beta stage. It had a Spanish version called Computadora.de. Desktoptwo was web-based and required Adobe Flash Player to operate. The web applications' found on Desktoptwo were built on PHP in the back end. Features included drag-and-drop functionality. Sapotek had liberated all the web applications found on Desktoptwo through Sapodesk on an AGPL license. Desktoptwo belonged to a category of services that intended to turn the Web into a full-fledged platform by using web services as a foundation along with presentation technologies that replicated the experience of desktop applications for users. In a "Cloud OS" the functionality of a server was granularized and abstracted as Web services that Web developers used to create composite applications similar to how desktop software developers use several APIs of the OS to create their applications. Sites like Facebook attempt to create a similar effect by exposing their APIs and allowing developers to create applications upon these. Some of the features found on Desktoptwo were: File sharing, Webmail, Blog creator, Instant messenger, Address book, Calendar, RSS Reader and Office productivity applications. Desktoptwo.com and the Sapotek website no longer operate.

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  • FarPoint Spread

    FarPoint Spread

    FarPoint Spread is a suite of Microsoft Excel-compatible spreadsheet components available for .NET, COM, and Microsoft BizTalk Server. Software developers use the components to embed Microsoft Excel-compatible spreadsheet features into their applications, such as importing and exporting Microsoft Excel files, displaying, modifying, analyzing, and visualizing data. Spread components handle spreadsheet data at the cell, row, column, or worksheet level. This article is about the last FarPoint edition of the Spread product line. Spread is now developed by GrapeCity, Inc. Since the acquisition, Spread for Biztalk Server has been removed from the product line and SpreadJS, a JavaScript version, has been added. == History == 1991 Spread released as a DLL control as the initial product offering from FarPoint Technologies, Inc. 1990s Spread VBX released. Spread ActiveX released. These components are now known as Spread COM. 2003 Spread for Windows Forms released as a completely new managed C# version prompted by the launch of Visual Studio .NET. 2003 Spread for Web Forms (now Spread for ASP.NET) released. 2006 Spread for BizTalk released. 2009 FarPoint Technologies acquired by GrapeCity. == Versions == Spread for Windows Forms: 5.0 Spread for Web Forms: 5.0 Spread COM: 8.0 Spread for BizTalk: 3.0 === Spread for Windows Forms === FarPoint Spread for Windows Forms is a Microsoft Excel-compatible spreadsheet component for Windows Forms applications developed using Microsoft Visual Studio and the .NET Framework. Developers use it to add grids and spreadsheets to their applications, and to bind them to data sources. In version 4.0, new cell types were added to display barcodes and fractions, and exports for XML and PDF were added. === Spread for ASP.NET === FarPoint Spread for ASP.NET is a Microsoft Excel-compatible spreadsheet component for ASP.NET applications. Developers use it to add grids and spreadsheets to their applications, === Spread for COM === FarPoint Spread 8 COM allows COM and ActiveX applications to incorporate spreadsheet features. In the 1997 book Visual Basic 5 for Windows for Dummies, Wally Wang lists an early version of Spread COM in Chapter 35: The Ten Most Useful Visual Basic Add-On Programs. === Spread for BizTalk === FarPoint Spread for BizTalk Server allows developers to integrate Microsoft Excel documents into Microsoft BizTalk applications. Spread for BizTalk Server includes two components: Spreadsheet Pipeline Disassembler - Parses data from Microsoft Excel (XLS and Excel 2007 XML, CSV, TXT) documents into XML data for processing through Microsoft BizTalk Server receive pipelines. Spreadsheet Pipeline Assembler - Assembles data from Microsoft BizTalk applications into Microsoft Excel (XLS or Excel 2007 XML) or PDF documents for transport through Microsoft BizTalk Server send pipelines. Developers find it a useful tool for organizations with Microsoft BizTalk Server Enterprise Application Integration. Prior to this release, BizTalk users wanting to use Excel data had to manually open the files and copy and paste data between the two applications. == Features == These features are common to all versions. Predefined cell types, including: currency date time number percent regular expression button check box combo box hyperlink image Formula support, including: cross-sheet referencing over 300 built-in functions Import and export: import to Microsoft Excel-compatible files export to Microsoft Excel-compatible files export to HTML files export to XML files Design-time spreadsheet designer Data-binding with customizable options Hierarchical data views, with parent rows and child views Grouping of rows or columns Sorting by row or column on multiple keys Cell spanning Multiple row and column headers Bound and unbound modes == Version-Specific Features == === Spread for Windows Forms === Support for Microsoft Visual Studio 2010 Support for Windows Azure AppFabric Integrated chart control Custom cell types Cell notes Child controls Splitter bars Built-in and custom skins and styles PDF export Microsoft Excel 2007 XML Support (Office Open XML, XLSX) Floating Formula Bar Range Selection for Formula Automatic Completion (type ahead) === Spread for ASP.NET === Support for Microsoft Visual Studio 2010 Support for Windows Azure AppFabric Integrated chart control AJAX-enabled Support for Open Document Format (ODF) files Multiple edits on multiple rows without server round trips Client-side column and row resizing Load on demand, which loads data from the server as needed for viewing Native Microsoft Excel import and export In-cell editing Multiple edits on multiple rows without server round trips Client-side column and row resizing Multiple sheets Searching Filtering Validations Cell spans PDF export === Spread COM === Custom cell types Cell notes Virtual mode for data loading Unicode support Customizable printing Text tips Import and export: Microsoft Excel 97 Excel 2000 Excel 2007 (requires the .NET Framework) Enhanced printing 64 bit DLL === Spread for BizTalk === Integration of Microsoft Excel data into Microsoft BizTalk applications Design-time spreadsheet schema wizard and spreadsheet format designer == Supported document formats == Adobe Portable Document Format PDF (.pdf) HTML Web Page (.html) Microsoft Excel Workbook (.xls) Plain Text (.txt) Comma-Separated Values (.csv) Open Document Format (Spread for ASP.NET)

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  • Glossary of computer graphics

    Glossary of computer graphics

    This is a glossary of terms relating to computer graphics. For more general computer hardware terms, see glossary of computer hardware terms. == 0–9 == 2D convolution Operation that applies linear filtering to image with a given two-dimensional kernel, able to achieve e.g. edge detection, blurring, etc. 2D image 2D texture map A texture map with two dimensions, typically indexed by UV coordinates. 2D vector A two-dimensional vector, a common data type in rasterization algorithms, 2D computer graphics, graphical user interface libraries. 2.5D Also pseudo 3D. Rendering whose result looks 3D while actually not being 3D or having great limitations, e.g. in camera degrees of freedom. 3D graphics pipeline A graphics pipeline taking 3D models and producing a 2D bitmap image result. 3D paint tool A 3D graphics application for digital painting of multiple texture map image channels directly onto a rotated 3D model, such as zbrush or mudbox, also sometimes able to modify vertex attributes. 3D scene A collection of 3D models and lightsources in world space, into which a camera may be placed, describing a scene for 3D rendering. 3D unit vector A unit vector in 3D space. 4D vector A common datatype in graphics code, holding homogeneous coordinates or RGBA data, or simply a 3D vector with unused W to benefit from alignment, naturally handled by machines with 4-element SIMD registers. 4×4 matrix A matrix commonly used as a transformation of homogeneous coordinates in 3D graphics pipelines. 7e3 format A packed pixel format supported by some graphics processing units (GPUs) where a single 32-bit word encodes three 10-bit floating-point color channels, each with seven bits of mantissa and three bits of exponent. == A == AABB Axis-aligned bounding box (sometimes called "axis oriented"), a bounding box stored in world coordinates; one of the simplest bounding volumes. Additive blending A compositing operation where d s t = d s t + s r c , {\displaystyle dst=dst+src,} without the use of an alpha channel, used for various effects. Also known as linear dodge in some applications. Affine texture mapping Linear interpolation of texture coordinates in screen space without taking perspective into account, causing texture distortion. Aliasing Unwanted effect arising when sampling high-frequency signals, in computer graphics appearing e.g. when downscaling images. Antialiasing methods can prevent it. Alpha channel An additional image channel (e.g. extending an RGB image) or standalone channel controlling alpha blending. Ambient lighting An approximation to the light entering a region from a wide range of directions, used to avoid needing an exact solution to the rendering equation. Ambient occlusion (AO) Effect approximating, in an inexpensive way, one aspect of global illumination by taking into account how much ambient light is blocked by nearby geometry, adding visual clues about the shape. Analytic model A mathematical model for a phenomenon to be simulated, e.g. some approximation to surface shading. Contrasts with Empirical models based purely on recorded data. Anisotropic filtering Advanced texture filtering improving on mipmapping, preventing aliasing while reducing blur in textured polygons at oblique angles to the camera. Anti-aliasing Methods for filtering and sampling to avoid visual artifacts associated with the uniform pixel grid in 3D rendering. Array texture A form of texture map containing an array of 2D texture slices selectable by a 3rd 'W' texture coordinate; used to reduce state changes in 3D rendering. Augmented reality Computer-rendered content inserted into the user's view of the real world. AZDO Approaching zero driver overhead, a set of techniques aimed at reducing the CPU overhead in preparing and submitting rendering commands in the OpenGL pipeline. A compromise between the traditional GL API and other high-performance low-level rendering APIs. == B == Back-face culling Culling (discarding) of polygons that are facing backwards from the camera. Baking Performing an expensive calculation offline, and caching the results in a texture map or vertex attributes. Typically used for generating lightmaps, normal maps, or low level of detail models. Barycentric coordinates Three-element coordinates of a point inside a triangle. Beam tracing Modification of ray tracing which instead of lines uses pyramid-shaped beams to address some of the shortcomings of traditional ray tracing, such as aliasing. Bicubic interpolation Extension of cubic interpolation to 2D, commonly used when scaling textures. Bilinear interpolation Linear interpolation extended to 2D, commonly used when scaling textures. Binding Selecting a resource (texture, buffer, etc.) to be referenced by future commands. Billboard A textured rectangle that keeps itself oriented towards the camera, typically used e.g. for vegetation or particle effects. Binary space partitioning (BSP) A data structure that can be used to accelerate visibility determination, used e.g. in Doom engine. Bit depth The number of bits per pixel, sample, or texel in a bitmap image (holding one or more image channels, typical values being 4, 8, 16, 24, 32) Bitmap Image stored by pixels. Bit plane A format for bitmap images storing 1 bit per pixel in a contiguous 2D array; Several such parallel arrays combine to produce the a higher-bit-depth image. Opposite of packed-pixel format. Blend operation A render state controlling alpha blending, describing a formula for combining source and destination pixels. Bone Coordinate systems used to control surface deformation (via Weight maps) during skeletal animation. Typically stored in a hierarchy, controlled by key frames, and other procedural constraints. Bounding box One of the simplest type of bounding volume, consisting of axis-aligned or object-aligned extents. Bounding volume A mathematically simple volume, such as a sphere or a box, containing 3D objects, used to simplify and accelerate spatial tests (e.g. for visibility or collisions). BRDF Bidirectional reflectance distribution functions (BRDFs), empirical models defining 4D functions for surface shading indexed by a view vector and light vector relative to a surface. Bump mapping Technique similar to normal mapping that instead of normal maps uses so called bump maps (height maps). BVH Bounding volume hierarchy is a tree structure on a set of geometric objects. == C == Camera A virtual camera from which rendering is performed, also sometimes referred to as 'eye'. Camera space A space with the camera at the origin, aligned with the viewer's direction, after the application of the world transformation and view transformation. Cel shading Cartoon-like shading effect. Clipping Limiting specific operations to a specific region, usually the view frustum. Clipping plane A plane used to clip rendering primitives in a graphics pipeline. These may define the view frustum or be used for other effects. Clip space Coordinate space in which clipping is performed. Clip window A rectangular region in screen space, used during clipping. A clip window may be used to enclose a region around a portal in portal rendering. CLUT A table of RGB color values to be indexed by a lower-bit-depth image (typically 4–8 bits), a form of vector quantization. Color bleeding Unwanted effect in texture mapping. A color from a border of unmapped region of the texture may appear (bleed) in the mapped result due to interpolation. Color channels The set of channels in a bitmap image representing the visible color components, i.e. distinct from the alpha channel or other information. Color resolution Command buffer A region of memory holding a set of instructions for a graphics processing unit for rendering a scene or portion of a scene. These may be generated manually in bare metal programming, or managed by low level rendering APIs, or handled internally by high level rendering APIs. Command list A group of rendering commands ready for submission to a graphics processing unit, see also Command buffer. Compute API An API for efficiently processing large amounts of data. Compute shader A compute kernel managed by a rendering API, with easy access to rendering resources. Cone tracing Modification of ray tracing which instead of lines uses cones as rays in order to achieve e.g. antialiasing or soft shadows. Connectivity information Indices defining [rendering primitive]s between vertices, possibly held in index buffers. describes geometry as a graph or hypergraph. CSG Constructive solid geometry, a method for generating complex solid models from boolean operations combining simpler modelling primitives. Cube mapping A form of environment reflection mapping in which the environment is captured on a surface of a cube (cube map). Culling Before rendering begins, culling removes objects that don't significantly contribute to the rendered result (e.g. being obscured or outside camera view). == D == Decal A "sticker" picture applied onto a surface (e.g. a

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  • Amazon Elastic Compute Cloud

    Amazon Elastic Compute Cloud

    Amazon Elastic Compute Cloud (EC2) is a part of Amazon's cloud-computing platform, Amazon Web Services (AWS), that allows users to rent virtual computers on which to run their own computer applications. EC2 encourages scalable deployment of applications by providing a web service through which a user can boot an Amazon Machine Image (AMI) to configure a virtual machine, which Amazon calls an "instance", containing any software desired. A user can create, launch, and terminate server-instances as needed, paying by the second for active servers – hence the term "elastic". EC2 provides users with control over the geographical location of instances that allows for latency optimization and high levels of redundancy. In November 2010, Amazon switched its own retail website platform to EC2 and AWS. == History == Amazon announced a limited public beta test of EC2 on August 25, 2006, offering access on a first-come, first-served basis. Amazon added two new instance types (Large and Extra-Large) on October 16, 2007. On May 29, 2008, two more types were added, High-CPU Medium and High-CPU Extra Large. There were twelve types of instances available. Amazon added three new features on March 27, 2008: static IP addresses, availability zones, and user-selectable kernels. On August 20, 2008, Amazon added Elastic Block Store (EBS). This provides persistent storage, a feature that had been lacking since the service was introduced. Amazon EC2 went into full production when it dropped the beta label on October 23, 2008. On the same day, Amazon announced the following features: a service level agreement for EC2, Microsoft Windows in beta form on EC2, Microsoft SQL Server in beta form on EC2, plans for an AWS management console, and plans for load balancing, autoscaling, and cloud monitoring services. These features were subsequently added on May 18, 2009. Amazon EC2 was developed mostly by a team in Cape Town, South Africa led by Chris Pinkham. Pinkham provided the initial architecture guidance for EC2 and then built the team and led the development of the project along with Willem van Biljon. == Instance types == Initially, EC2 used Xen virtualization exclusively. However, on November 6, 2017, Amazon announced the new C5 family of instances that were based on a custom architecture around the KVM hypervisor, called Nitro. Each virtual machine, called an "instance", functions as a virtual private server. Amazon sizes instances based on "Elastic Compute Units". The performance of otherwise identical virtual machines may vary. On November 28, 2017, AWS announced a bare-metal instance, a departure from exclusively offering virtualized instance types. As of January 2019, the following instance types were offered: General Purpose: A1, T3, T2, M5, M5a, M4, T3a Compute Optimized: C5, C5n, C4 Memory Optimized: R5, R5a, R4, X1e, X1, High Memory, z1d Accelerated Computing: P3, P2, G3, F1 Storage Optimized: H1, I3, D2 As of April 2018, the following payment methods by instance were offered: On-demand: pay by the hour without commitment. Reserved: rent instances with one-time payment receiving discounts on the hourly charge. Spot: bid-based service: runs the jobs only if the spot price is below the bid specified by bidder. The spot price is claimed to be supply-demand based, however a 2011 study concluded that the price was generally not set to clear the market, but was dominated by an undisclosed reserve price. In 2025, AWS expanded EC2 with the compute-optimized C8gn family, powered by Graviton4 and offering up to 600 Gbit/s network bandwidth (about 30% higher compute performance than C7gn), and introduced G6f fractional-GPU instances that let customers provision one-eighth, one-quarter, or one-half of an NVIDIA L4 GPU for right-sized graphics/ML workloads. === Cost === As of April 2018, Amazon charged about $0.0058 per hour ($4.176 per month) for the smallest "Nano Instance" (t2.nano) virtual machine running Linux or Windows. Storage-optimized instances cost as much as $4.992 per hour (i3.16xlarge). "Reserved" instances can go as low as $2.50 per month for a three-year prepaid plan. The data transfer charge ranges from free to $0.12 per gigabyte, depending on the direction and monthly volume (inbound data transfer is free on all AWS services). EC2 costs can be analyzed using the Amazon Cost and Usage Report. There are many different cost categories for EC2 including: hourly Instance Charges, Data Transfer, EBS Volumes, EBS Volume Snapshots, and Nat Gateway. === Free tier === As of December 2010 Amazon offered a bundle of free resource credits to new account holders. The credits are designed to run a "micro" sized server, storage (EBS), and bandwidth for one year. Unused credits cannot be carried over from one month to the next. === Reserved instances === Reserved instances enable EC2 or RDS service users to reserve an instance for one or three years. The corresponding hourly rate charged by Amazon to operate the instance is 35 to 75% lower than the rate charged for on-demand instances. Reserved instances can be purchased with three different payment options: All Upfront, Partial Upfront and No Upfront. The different purchase options allow for different structuring of payment models, with a larger discount given to customers that pay their reservation upfront. Reserved Instances are purchased based on a resource commitment. These reservations are made based on an instance type and a count of that instance type. For example, you could reserve 100 i3.large instances for a 3-year term. In September 2016, AWS announced several enhancements to Reserved instances, introducing a new feature called scope and a new reservation type called a Convertible. In October 2017, AWS announced the allowance to subdivide the instances purchased for more flexibility. === Spot instances === Cloud providers maintain large amounts of excess capacity they have to sell or risk incurring losses. Amazon EC2 Spot instances are spare compute capacity in the AWS cloud available at up to 90% discount compared to On-Demand prices. As a trade-off, AWS offers no SLA on these instances and customers take the risk that it can be interrupted with only two minutes of notification when Amazon needs the capacity back. Researchers from the Israeli Institute of Technology found that "they (Spot instances) are typically generated at random from within a tight price interval via a dynamic hidden reserve price". Some companies, like Spotinst, are using machine learning to predict spot interruptions up to 15 minutes in advance. === Savings Plans === In November 2019, Amazon announced Savings Plans. Savings Plans are an alternative to Reserved Instances that come in two different plan types: Compute Savings Plans and EC2 Instances Savings Plans. Compute Savings Plans allow an organization to commit to EC2 and Fargate usage with the freedom to change region, family, size, availability zone, OS and tenancy inside the lifespan of the commitment. EC2 Instance Savings plans provide a larger discount than Compute Savings Plans but are less flexible meaning a user must commit to individual instance families within a region to take advantage, but with the freedom to change instances within the family in that region. AWS uses the Cost Explorer to automatically calculate recommendations for the commitments you should make how that commitment will look like as a monthly charge on your AWS bill. AWS Savings Plans are purchased based on hourly spend commitment. This hourly commitment is made using the discounted pricing of the savings plan you are purchasing. For example, you could commit to spending $5 per hour, on a Compute Savings Plan, for a 3-year term. == Features == === Operating systems === When it launched in August 2006, the EC2 service offered Linux and later Sun Microsystems' OpenSolaris and Solaris Express Community Edition. In October 2008, EC2 added the Windows Server 2003 and Windows Server 2008 operating systems to the list of available operating systems. In March 2011, NetBSD AMIs became available. In November 2012, Windows Server 2012 support was added. Since 2006, Colin Percival, a FreeBSD developer and Security Officer, solicited Amazon to add FreeBSD. In November 2012, Amazon officially supported running FreeBSD in EC2. The FreeBSD/EC2 platform is maintained by Percival who also developed the secure deduplicating Amazon S3-cloud based backup service Tarsnap. Amazon has their own Linux distribution based on Fedora and Red Hat Enterprise Linux as a low cost offering known as the Amazon Linux AMI. Version 2013.03 included: Linux kernel, Java OpenJDK Runtime Environment and GNU Compiler Collection. On November 30, 2020, Amazon announced that it would be adding macOS to the EC2 service. Initial support was announced for macOS Mojave and macOS Catalina running on Mac Mini. === Managed Container and Kubernetes Services === Amazon Elastic Container Registry (ECR) is a Docker registry service for Amazon EC2

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  • Social software engineering

    Social software engineering

    Social software engineering (SSE) is a branch of software engineering that is concerned with the social aspects of software development and the developed software. SSE focuses on the socialness of both software engineering and developed software. On the one hand, the consideration of social factors in software engineering activities, processes and CASE tools is deemed to be useful to improve the quality of both development process and produced software. Examples include the role of situational awareness and multi-cultural factors in collaborative software development. On the other hand, the dynamicity of the social contexts in which software could operate (e.g., in a cloud environment) calls for engineering social adaptability as a runtime iterative activity. Examples include approaches which enable software to gather users' quality feedback and use it to adapt autonomously or semi-autonomously. SSE studies and builds socially-oriented tools to support collaboration and knowledge sharing in software engineering. SSE also investigates the adaptability of software to the dynamic social contexts in which it could operate and the involvement of clients and end-users in shaping software adaptation decisions at runtime. Social context includes norms, culture, roles and responsibilities, stakeholder's goals and interdependencies, end-users perception of the quality and appropriateness of each software behaviour, etc. The participants of the 1st International Workshop on Social Software Engineering and Applications (SoSEA 2008) proposed the following characterization: Community-centered: Software is produced and consumed by and/or for a community rather than focusing on individuals Collaboration/collectiveness: Exploiting the collaborative and collective capacity of human beings Companionship/relationship: Making explicit the various associations among people Human/social activities: Software is designed consciously to support human activities and to address social problems Social inclusion: Software should enable social inclusion enforcing links and trust in communities Thus, SSE can be defined as "the application of processes, methods, and tools to enable community-driven creation, management, deployment, and use of software in online environments". One of the main observations in the field of SSE is that the concepts, principles, and technologies made for social software applications are applicable to software development itself as software engineering is inherently a social activity. SSE is not limited to specific activities of software development. Accordingly, tools have been proposed supporting different parts of SSE, for instance, social system design or social requirements engineering. Consequently vertical market software, such as software development tools, engineering tools, marketing tools or software that helps users in a decision-making process can profit from social components. Such vertical social software differentiates strongly in its user-base from traditional social software such as Yammer.

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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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  • Colloquis

    Colloquis

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

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  • Inbox by Gmail

    Inbox by Gmail

    Inbox by Gmail was an email service developed by Google. Announced on a limited invitation-only basis on October 22, 2014, it was officially released to the public on May 28, 2015. Inbox was shut down by Google on April 2, 2019. Available on the web, and through mobile apps for Android and iOS, Inbox by Gmail aimed to improve email productivity and organization through several key features. Bundles gathered emails on the same topic together; highlighted surface key details from messages, reminders and assists; and a "snooze" functionality enabled users to control when specific information would appear. Updates to the service enabled an "undo send" feature; a "Smart Reply" feature that automatically generated short reply examples for certain emails; integration with Google Calendar for event organization, previews of newsletters; and a "Save to Inbox" feature that let users save links for later use. Inbox by Gmail received generally positive reviews. At its launch, it was called "minimalist and lovely, full of layers and easy to navigate", with features deemed helpful in finding the right messages—one reviewer noted that the service felt "a lot like the future of email". However, it also received criticism, particularly for a low density of information, algorithms that needed tweaking, and because the service required users to "give up the control" of organizing their own email, meaning that "Anyone who already has a system for organizing their emails will likely find themselves fighting Google's system". Google noted in March 2016 that 10% of all replies on mobile originated from Inbox's Smart Reply feature. Google announced it would discontinue Inbox by Gmail in March 2019, with many of its features integrated into Gmail proper. == Features == Inbox by Gmail scanned the user's incoming Gmail messages for information. It gathered email messages related to the same overall topic into an organized bundle, with a title describing the bundle's content. For example, flight tickets, car rentals, and hotel reservations were grouped under "Travel", giving the user an easier overview of emails. Users could also group emails together manually, to "teach" the Inbox how the user worked. The service highlighted key details and important information in messages, such as flight itineraries, event information, photos and documents. Inbox could retrieve updated information from the Internet, including the real-time status of flights and package deliveries. Users could set reminders to bring up important messages later. When a user needed particular information, Inbox could assist the user by displaying the necessary details. Where Inbox highlights information was not needed immediately, users could "snooze" a message or reminder, with options to make the information reappear at a later time or specific location. In June 2015, Google added an "Undo Send" feature to Inbox, giving the user 10 seconds to undo sending a message. In November 2015, Google added "Smart Reply" functionality to the mobile apps. With Smart Reply, Inbox determined which emails could be answered with a short reply, generating three example responses from which the user could select one with a single tap. Smart Reply (initially available only on the Android and iOS mobile apps) was added to the Inbox website in March 2016, Google announcing that "10% of all your replies on mobile already use Smart Reply". By May 2017, Google said Smart Reply was driving about 12% of replies in inbox on mobile. In April 2016, Google updated Inbox with three new features; Google Calendar event organization, newsletter previews, and a "Save to Inbox" functionality that let the user save links for later use, rather than having to email links to themselves. In December 2017, Google introduced an "Unsubscribe" card that let users easily unsubscribe from mailing lists. The card appeared for email messages (from specific senders) that the user had not opened for a month. A few popular Inbox by Gmail features were subsequently added to Gmail: "Snoozing" of emails Nudges: Gmail could move old messages back to the top of the inbox when it thought a follow up or reply might be required. Hover actions: Placing the mouse cursor over a certain part of the message could quickly effect an action, such as archiving, without its being opened. Smart reply: This feature employed boilerplate text to suggest appropriate replies. Google reportedly wished, at a time then to be decided, to add the "bundles" feature to Gmail, which at the time was available only in Inbox for Gmail. By March 2020, many Inbox features were still missing from Gmail. == Platforms == Inbox by Gmail was announced on a limited invitation-only basis on October 22, 2014, available on the web, and through the Android and iOS mobile operating systems. It was officially released to the public on May 28, 2015. == Reception == David Pierce of The Verge praised the service, writing that it was "minimalist and lovely, full of layers and easy to navigate. It's remarkably fast and smooth on all platforms, and far better on iOS than the Gmail app". However, he criticized the app's low density of information, with only a few emails visible on the screen at a time, making it "a bit of a challenge" for users who need to go through "hundreds of emails" every day. Although positive that "Inbox feels a lot like the future of email", Pierce wrote that there was "plenty of algorithm tweaking and design condensing to do", with particular attention needed on a "compact view" for denser view of information on the screen. Sarah Mitroff of CNET also praised Inbox, writing, "Not only is it visually appealing, it's also full of features that help you find every message you need, when you need it". She added that users must "give up the control" to organize their email, and that it "won't vibe with everyone", but admitted that "if you're willing ... the app will reward you with a smarter and cleaner inbox." Mitroff noted that, initially, users had to coach the app about which bundle was appropriate for certain emails, writing, "It's a tedious process at first, by [sic] in just a few days Inbox starts to get it right." Regarding any downsides of the service, Mitroff wrote that "Inbox has a built-in strategy for managing your emails that works best on its own. Anyone who already has a system for organizing their emails will likely find themselves fighting Google's system". == Discontinuation and legacy == Google ended the service in March 2019. Google called Inbox "a great place to experiment with new ideas" and noted that many of those ideas had been migrated to Gmail. The company wanted, going forward, to focus its resources on a single email system. Several services, like Shortwave, attempted to resurrect some of the features of Inbox by Gmail to attract its old users. Similarly, Inbox Reborn, an actively maintained browser extension developed by a team of volunteer developers from around the world since 2018, aims to recreate the core features and visual style of Inbox by Gmail within the standard Gmail interface. The project continues to focus on preserving functionalities such as email bundling and streamlined workflows to provide users with a familiar productivity experience. Afterwards, most people moved to Spark, Spike, or Newton. According to a product manager at Google, a "more focused approach" regarding email was the companies goal. This is likely the reason they moved away from Inbox.

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  • Quickly (software)

    Quickly (software)

    Quickly is a framework for creating software programs for a Linux distribution using Python, PyGTK, Glade Interface Designer and Desktop Couch. It then allows for easy publishing using bzr and Launchpad. Quickly is designed to speed up the start of new projects with the use of templates, not only for programs but for any type of project. These templates are used to automate project configuration and maintenance. Delegating into templates and not into a specific library allows projects created using Quickly not to require dependencies on any particular library or runtime of Quickly itself. The project was started by Rick Spencer after his frustration as a beginner Ubuntu developer. == Updates == Last available software update is on 2013-01-31 for Ubuntu 11.04.

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