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  • Vegas Pro

    Vegas Pro

    Vegas Pro (formerly known as Sony Vegas) is a professional video editing software package for non-linear editing (NLE), designed to run on the Microsoft Windows operating system. The first release of Vegas Beta was on June 11, 1999. Vegas was originally developed as a non-linear audio editing application. Version 2.0 would split the program into audio and video editing variants, with the former being dropped by version 4.0, making the video offering the only variant available to consumers. Vegas Pro features real-time multi-track video and audio editing on unlimited tracks, resolution-independent video sequencing, complex effects, compositing tools, 24-bit/192 kHz audio support, VST and DirectX plug-in effect support, and Dolby Digital surround sound mixing. The software was originally published by Sonic Foundry until May 2003, when Sony purchased Sonic Foundry and formed Sony Creative Software. On May 24, 2016, Sony announced that Vegas was sold to MAGIX, which formed VEGAS Creative Software, to continue support and development of the software. As of the end of March 2026, it was publicly announced that Boris FX had taken ownership of Vegas Pro. Each release of Vegas is sold standalone; however, upgrade discounts are sometimes provided. == Features == Vegas does not require any specialized hardware to run properly, allowing it to operate on any Windows computer that meets the system requirements. == History == Vegas 1.0 was released after a brief public beta by Sonic Foundry on July 23, 1999 at the NAMM Show in Nashville, Tennessee as an audio-only tool with a particular focus on re-scaling and resampling audio. It supported formats like DivX and Real Networks RealSystem G2 file formats. Martin Walker from Sound on Sound described working in Vegas 1.0 as a "very pleasurable experience, especially since so many functions are highly intuitive" though also criticizing some features as hard to figure out due to the lack of a central help file. Later, on June 12, 2000, Vegas Video and Audio 2.0 (also referred to as just Vegas 2.0) was released, with its beta releasing earlier that year on April 10. This was the first version of Vegas to include video-editing tools and was also the first to have a low-cost "LE" version alongside the regular release. The LE releases would continue through version 3.0 of Vegas but would be discontinued by the release of Vegas 4.0. Vegas 3.0 was released the next year on December 3, and added new video effects, features for ease-of-use with DV, and support for editing Windows Media files. Vegas 4.0 was released on 6 February 2003 and added application scripting, advanced color correction, 5.1 surround sound mixing, and Steinberg ASIO support. This was the last release under the Sonic Foundry name after it sold much of its software suite, including Sound Forge and Acid Pro, to Sony Pictures Digital for $18 million later in 2003. Under Sony's ownership, Vegas 5.0 was released on April 19, 2004, bringing 3D track motion, compositing, reversing, envelope automation, etc. 7.0 also added an improved video preview, enhanced layout management, improved snapping, and more customization. With the release of 8.0, Sony opted to go back to the original "Vegas Pro" branding that the first version released with. It added the ability to burn Blu-ray and DVD optical media, support for 32-bit floating point audio, support for tempo-based audio effects, and more. It also moved the timeline to the bottom of the window by default with the option of moving it back to the top if the user wished to. Sony was also experimenting with 64-bit at this time and ported Vegas Pro 8.0 to 64-bit systems under the name "Vegas Pro 8.1". Vegas Pro 9.0 added support for 4K resolution and pro camcorder formats like Red and XDCAM EX. In 2009, Sony Creative Software purchased the Velvetmatter Radiance suite of video FX plug-ins which were included in Sony Vegas Pro 9.0. As a result, they were no longer available as a separate product from Velvetmatter. Vegas Pro 10 was released in 2010 with stereoscopic 3D editing, image stabilization, OpenFX plugin support, real-time audio event effects, and a few UI changes. This was the last release to include support for Windows XP. Vegas Pro 11 was released the next year on 17 October, with GPGPU video acceleration, enhanced text tools, enhanced stereoscopic/3D features, RAW photo support, and new event synchronization mechanisms. In addition, Vegas Pro 11 comes pre-loaded with "NewBlue" Titler Pro, a 2D and 3D titling plug-in. Vegas Pro 12 would add two new configurations: Vegas Pro 12 Edit, for "Professional Video and Audio Production"; and Vegas Pro 12 Suite, for "Professional Editing, Disc Authoring, and Visual Effects Design". Vegas Pro 13 would be the last version released with Sony branding after the acquisition of much of Sony Creative Software's library by Magix. After they acquired Vegas, Magix released version 14 on September 20, 2016. It featured advanced 4K upscaling as well as many bug fixes, a higher video velocity limit, RED camera support, and a variety of other features. This was also the last version to have the light theme enabled by default. Released on August 28, 2017, Vegas Pro 15 features major UI changes that claim to bring usability improvements and customization. It was the first version of VEGAS Pro to have a dark theme; it also allows more efficient editing speeds, including adding new shortcuts to speed the video editing process. Vegas Pro 15 includes support for Intel Quick Sync Video (QSV) and other technologies, as well as various other features. It introduced a new VEGAS Pro icon as a V. Vegas Pro 16 has some new features including file backup, motion tracking, improved video stabilization, 360° editing and HDR support. Magix has continued to improve Vegas through version 21 with support for reading Matroska files, a more detailed render dialogue, live streaming, VST3 support, a VST 32-bit bridge, and a selective Paste Event Attributes menu. Magix would later release a subscription model for using Vegas named "Vegas Pro 365" on January 17, 2018, although the perpetual licence is still an option for customers. This version includes cloud-based speech synthesis among other features not included in the mainline Vegas release. == Version history == Each release of Vegas is sold standalone, however upgrade discounts are sometimes provided. === Vegas Beta === Sonic Foundry introduced a sneak preview version of Vegas Pro on June 11, 1999. It is called a "Multitrack Media Editing System". === Vegas 1.0 === Released on July 23, 1999 at the NAMM Show in Nashville, Tennessee, Vegas was an audio-only tool with a particular focus on rescaling and resampling audio. It supported formats like DivX and Real Networks RealSystem G2 file formats. Version 1.0 is the final Vegas release to include Windows 95 support. === Vegas Video beta (Vegas 2.0 beta) === Released on April 10, 2000, this was the first version of Vegas to include video-editing tools. === Vegas Video (Vegas 2.0) === Released on June 12, 2000. Version 2.0 is the final Vegas Video release to include Windows NT 4.0 support. === Vegas Video 3.0 === Released on December 3, 2001. This release added: New Video Effects – Lens Flare, Light Rays, Film FX, Color Curves, Mirror, Remap, Deform, Convolution, Linear Blur, Black Restore, Levels, Unsharp Mask, Color Grading, and Timecode Burn filter. Batch Capture with Automatic Scene Detection – Captures DV with automatic scene detection, batch capture, tape logging, still image capture and thumbnail previews. Red Book Audio CD Mastering with CD Architect (TM) Technology – Used for burning Red Book audio CD masters directly from the Vegas timeline with ISRC, UPC, and PQ list support. New Sonic Foundry DV Codec – Introduces a DV codec developed by Sonic Foundry that offers artifact-free compositing and DV chromakeying. DV Print-to-Tape from the Timeline – Prints projects to DV cameras and decks from the Vegas timeline. Windows Media (TM) File Editing – Creates and edits Windows Media (TM) files. New MPEG Encoding Tools – Used for producing MPEG-2 files for DVD productions. Dynamic RAM Previewing – Temporary RAM/render-free previews for analysis and tweaking of complex video FX without rendering. VideoCD and Data CD Burning – Burning projects directly to VideoCD for playback on most DVD players or data CDs for playback computers' CD-ROMs. === Vegas 4.0 === Released on February 6, 2003. This release added: Advanced Color Correction Tools Searchable Media Pool Bins Vectorscope, Histogram, Parade and Waveform Monitoring Application Scripting Improved Ripple Editing Motion Blur and Super-Sampling Envelopes 5.1 Surround Mixing Dolby® Digital AC-3 Encoding certified and tested by Dolby Laboratories DirectX® Audio Plug-In Effects Automation ASIO Driver Support Windows Media™ 9 Support, including Surround Encoding DVD Authoring with AC-3 File Import Capabilities Integration with DVD Architect via Chap

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  • Timeline of operating systems

    Timeline of operating systems

    This article presents a timeline of events in the history of computer operating systems from 1951 to the current day. For a narrative explaining the overall developments, see the History of operating systems. == 20th Century == == 1940s == 1949 EDSAC was considered the first operating system developed by Maurice Wilkes and manufactured by the University of Cambridge == 1950s == 1951 LEO I 'Lyons Electronic Office' was the commercial development of EDSAC computing platform, supported by British firm J. Lyons and Co. 1953 DYSEAC - an early machine capable of distributing computing 1955 General Motors Operating System made for IBM 701 MIT's Tape Director operating system made for UNIVAC 1103 1956 GM-NAA I/O for IBM 704, based on General Motors Operating System 1957 Atlas Supervisor (Manchester University) (Atlas computer project start) BESYS (Bell Labs), for IBM 704, later IBM 7090 and IBM 7094 1958 University of Michigan Executive System (UMES), for IBM 704, 709, and 7090 1959 SHARE Operating System (SOS), based on GM-NAA I/O == 1960s == 1960 IBSYS (IBM for its 7090 and 7094) 1961 CTSS demonstration (MIT's Compatible Time-Sharing System for the IBM 7094) MCP (Burroughs Master Control Program) for B5000 1962 Atlas Supervisor (Manchester University) (Atlas computer commissioned) BBN Time-Sharing System GCOS (GE's General Comprehensive Operating System, originally GECOS, General Electric Comprehensive Operating Supervisor) 1963 ADMIRAL AN/FSQ-32, another early time-sharing system begun CTSS becomes operational (MIT's Compatible Time-Sharing System for the IBM 7094) JOSS, an interactive time-shared system that did not distinguish between operating system and language Titan Supervisor, early time-sharing system begun 1964 Berkeley Timesharing System (for Scientific Data Systems' SDS 940) Chippewa Operating System (for CDC 6600 supercomputer) Dartmouth Time-Sharing System (Dartmouth College's DTSS for GE computers) EXEC 8 (UNIVAC) KDF9 Timesharing Director (English Electric) – an early, fully hardware secured, fully pre-emptive process switching, multi-programming operating system for KDF9 (originally announced in 1960) OS/360 (IBM's primary OS for its S/360 series) (announced) PDP-6 Monitor (DEC) descendant renamed TOPS-10 in 1970 SCOPE (CDC 3000 series) 1965 BOS/360 (IBM's Basic Operating System) DECsys TOS/360 (IBM's Tape Operating System) Livermore Time Sharing System (LTSS) Multics (MIT, GE, Bell Labs for the GE-645) (announced) Pick operating system SIPROS 66 (Simultaneous Processing Operating System) THE multiprogramming system (Technische Hogeschool Eindhoven) development TSOS (later VMOS) (RCA) 1966 DOS/360 (IBM's Disk Operating System) GEORGE 1 & 2 for ICT 1900 series Mod 1 Mod 2 Mod 8 MS/8 (Richard F. Lary's DEC PDP-8 system) MSOS (Mass Storage Operating System) OS/360 (IBM's primary OS for its S/360 series) PCP and MFT (shipped) RAX Remote Users of Shared Hardware (RUSH), a time-sharing system developed by Allen-Babcock for the IBM 360/50 SODA for Elwro's Odra 1204 Universal Time-Sharing System (XDS Sigma series) 1967 CP-40, predecessor to CP-67 on modified IBM System/360 Model 40 CP-67 (IBM, also known as CP/CMS) Conversational Programming System (CPS), an IBM time-sharing system under OS/360 Michigan Terminal System (MTS) (time-sharing system for the IBM S/360-67 and successors) ITS (MIT's Incompatible Timesharing System for the DEC PDP-6 and PDP-10) OS/360 MVT ORVYL (Stanford University's time-sharing system for the IBM S/360-67) TSS/360 (IBM's Time-sharing System for the S/360-67, never officially released, canceled in 1969 and again in 1971) WAITS (SAIL, Stanford Artificial Intelligence Laboratory, time-sharing system for DEC PDP-6 and PDP-10, later TOPS-10) 1968 Airline Control Program (ACP) (IBM) B1 (NCR Century series) CALL/360, an IBM time-sharing system for System/360 HP Real-Time Executive (HP RTE) – Hewlett-Packard HP Time-Shared BASIC (HP TSB) – Hewlett-Packard (time-sharing system for the HP 2000) THE multiprogramming system (Eindhoven University of Technology) publication TSS/8 (DEC for the PDP-8) VP/CSS 1969 B2 (NCR Century series) B3 (NCR Century series) GEORGE 3 For ICL 1900 series MINIMOP Multics (MIT, GE, Bell Labs for the GE-645 and later the Honeywell 6180) (opened for paying customers in October) RC 4000 Multiprogramming System (RC) TENEX (Bolt, Beranek and Newman for DEC systems, later TOPS-20) Unics (later Unix) (AT&T, initially on DEC computers) Xerox Operating System == 1970s == 1970 DOS-11 (PDP-11) 1971 EMAS Kronos RSTS-11 2A-19 (First released version; PDP-11) RSX-15 OS/8 1972 B4 (NCR Century series) COS-300 Data General RDOS Edos MUSIC/SP OS/4 OS 1100 OS/2000 (Honeywell 2000-series) Operating System/Virtual Storage 1 (OS/VS1) Operating System/Virtual Storage 2 R1 (OS/VS2 SVS) PRIMOS (written in FORTRAN IV, that didn't have pointers, while later versions, around version 18, written in a version of PL/I, called PL/P) Virtual Machine/Basic System Extensions Program Product (BSEPP or VM/SE) Virtual Machine/System Extensions Program Product (SEPP or VM/BSE) Virtual Machine Facility/370 (VM/370), sometimes known as VM/CMS 1973 Эльбрус-1 (Elbrus-1) – Soviet computer – created using high-level language uЭль-76 (AL-76/ALGOL 68) Alto OS CP-V (Control Program V) RSX-11D RT-11 VME – implementation language S3 (ALGOL 68) 1974 ACOS-2 (NEC) ACOS-4 ACOS-6 CP/M DOS-11 V09-20C (Last stable release, June 1974) Hydra – capability-based, multiprocessing OS kernel MONECS Multi-Programming Executive (MPE) – Hewlett-Packard Operating System/Virtual Storage 2 R2 (MVS) OS/7 OS/16 OS/32 Sintran III 1975 BS2000 V2.0 (First released version) COS-350 ISIS NOS (Control Data Corporation) OS/3 (Univac) VS/9 (formerly RCA's TSOS, later named VMOS) Version 6 Unix XVM/DOS XVM/RSX 1976 Cambridge CAP computer – all operating system procedures written in ALGOL 68C, with some closely associated protected procedures in BCPL Cray Operating System DX10 FLEX TOPS-20 TX990/TXDS Tandem Nonstop OS v1 Thoth 1977 1BSD AMOS KERNAL OASIS operating system OS68 OS4000 RMX-80 System 88 (Exec) System Support Program (IBM System/34 and System/36) TRSDOS Virtual Memory System (VMS) V1.0 (Initial commercial release, October 25) VRX (Virtual Resource eXecutive) VS Virtual Memory Operating System 1978 2BSD Apple DOS Control Program Facility (IBM System/38) Cray Time Sharing System (CTSS) DPCX (IBM) DPPX (IBM) HDOS KSOS – secure OS design from Ford Aerospace KVM/370 – security retro-fit of IBM VM/370 Lisp machine (CADR) MVS/System Extensions (MVS/SE) OS4 (Naked Mini 4) PTDOS TRIPOS UCSD p-System (First released version) Z80-RIO 1979 Atari DOS 3BSD CP-6 Idris MP/M MVS/System Extensions R2 (MVS/SE2) NLTSS POS Sinclair BASIC Transaction Processing Facility (TPF) (IBM) UCLA Secure UNIX – an early secure UNIX OS based on security kernel UNIX/32V DOS/VSE Version 7 Unix == 1980s == 1980 86-DOS AOS/VS (Data General) Business Operating System CTOS DOSPLUS (TRS-80) MVS/System Product (MVS/SP) V1 NewDos/80 OS-9 RMX-86 RS-DOS SOS Virtual Machine/System Product (VM/SP) Xenix 1981 Acorn MOS Aegis SR1 (First Apollo/DOMAIN systems shipped on March 27) CP/M-86 DRX (Distributed Resource Executive) iMAX – OS for Intel's iAPX 432 capability machine MCS (Multi-user Control System) MS-DOS PC DOS Pilot (Xerox Star operating system) UNOS UTS V VERSAdos VRTX VSOS (Virtual Storage Operating System) Xinu first release 1982 Commodore DOS LDOS (By Logical Systems, Inc. – for the Radio Shack TRS-80 Models I, II & III) PCOS (Olivetti M20) pSOS QNX Stratus VOS Sun UNIX (later SunOS) 0.7 Ultrix Unix System III VAXELN 1983 Coherent DNIX EOS GNU (project start) Lisa Office System 7/7 LOCUS – UNIX compatible, high reliability, distributed OS MVS/System Product V2 (MVS/Extended Architecture, MVS/XA) Novell NetWare (S-Net) PERPOS ProDOS RTU (Real-Time Unix) STOP – TCSEC A1-class, secure OS for SCOMP hardware SunOS 1.0 VSE/System Package (VSE/SP) Version 1 1984 AMSDOS CTIX (Unix variant) DYNIX Mac OS (System 1.0) MSX-DOS NOS/VE PANOS PC/IX ROS Sinclair QDOS SINIX UNICOS Venix 2.0 Virtual Machine/Extended Architecture Migration Assistance (VM/XA MA) 1985 AmigaOS Atari TOS DG/UX DOS Plus Graphics Environment Manager Harmony MacOS 2 MIPS RISC/os Oberon – written in Oberon SunOS 2.0 Version 8 Unix Virtual Machine/Extended Architecture System Facility (VM/XA SF) Windows 1.0 Windows 1.01 Xenix 2.0 1986 AIX 1.0 Cronus distributed OS FlexOS GEMSOS – TCSEC A1-class, secure kernel for BLACKER VPN & GTNP GEOS Genera 7.0 HP-UX MacOS 3 SunOS 3.0 TR-DOS TRIX Version 9 Unix 1987 Arthur (much improved version came in 1989 under the name RISC OS) BS2000 V9.0 IRIX (3.0 is first SGI version) MacOS 4 MacOS 5 MDOS MINIX 1.0 OS/2 (1.0) PC-MOS/386 Topaz – semi-distributed OS for DEC Firefly workstation written in Modula-2+ and garbage collected VxWorks Windows 2.0 1988 A/UX (Apple Computer) AOS/VS II (Data General) CP/M rebranded as DR-DOS Flex machine – tagged, capability machine with OS and other software written

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  • Digital data

    Digital data

    Digital data or digital information, in information theory and information systems, is data or information represented as a string of discrete symbols, each of which can take on one of only a finite number of values from some alphabet, such as letters or digits. An example is a text document, which consists of a string of alphanumeric characters. The most common form of digital data in modern information systems is binary data, which is represented by a string of binary digits (bits) each of which can have one of two values, either 0 or 1. Digital data can be contrasted with analog data, which is represented by a value from a continuous range of real numbers. Analog data is transmitted by an analog signal, which not only takes on continuous values but can vary continuously with time, a continuous real-valued function of time. An example is the air pressure variation in a sound wave. Data requires interpretation to become information. In modern (post-1960) computer systems, all data is digital. The word digital comes from the same source as the words digit and digitus (the Latin word for finger), as fingers are often used for counting. Mathematician George Stibitz of Bell Telephone Laboratories used the word digital in reference to the fast electric pulses emitted by a device designed to aim and fire anti-aircraft guns in 1942. The term is most commonly used in computing and electronics, especially where real-world information is converted to binary numeric form as in digital audio and digital photography. == Symbol to digital conversion == Since symbols (for example, alphanumeric characters) are not continuous, representing symbols digitally is rather simpler than conversion of continuous or analog information to digital. Instead of sampling and quantization as in analog-to-digital conversion, such techniques as polling and encoding are used. A symbol input device usually consists of a group of switches that are polled at regular intervals to see which switches are switched. Data will be lost if, within a single polling interval, two switches are pressed, or a switch is pressed, released, and pressed again. This polling can be done by a specialized processor in the device to prevent burdening the main CPU. When a new symbol has been entered, the device typically sends an interrupt, in a specialized format, so that the CPU can read it. For devices with only a few switches (such as the buttons on a joystick), the status of each can be encoded as bits (usually 0 for released and 1 for pressed) in a single word. This is useful when combinations of key presses are meaningful, and is sometimes used for passing the status of modifier keys on a keyboard (such as shift and control). But it does not scale to support more keys than the number of bits in a single byte or word. Devices with many switches (such as a computer keyboard) usually arrange these switches in a scan matrix, with the individual switches on the intersections of x and y lines. When a switch is pressed, it connects the corresponding x and y lines together. Polling (often called scanning in this case) is done by activating each x line in sequence and detecting which y lines then have a signal, thus which keys are pressed. When the keyboard processor detects that a key has changed state, it sends a signal to the CPU indicating the scan code of the key and its new state. The symbol is then encoded or converted into a number based on the status of modifier keys and the desired character encoding. A custom encoding can be used for a specific application with no loss of data. However, using a standard encoding such as ASCII is problematic if a symbol such as 'ß' needs to be converted but is not in the standard. It is estimated that in the year 1986, less than 1% of the world's technological capacity to store information was digital and in 2007 it was already 94%. The year 2002 is assumed to be the year when humankind was able to store more information in digital than in analog format (the "beginning of the digital age"). == States == Digital data come in these three states: data at rest, data in transit, and data in use. The confidentiality, integrity, and availability have to be managed during the entire lifecycle from 'birth' to the destruction of the data. === Data at rest === Data at rest in information technology means data that is housed physically on computer data storage in any digital form (e.g. cloud storage, file hosting services, databases, data warehouses, spreadsheets, archives, tapes, off-site or cloud backups, mobile devices etc.). Data at rest includes both structured and unstructured data. This type of data is subject to threats from hackers and other malicious threats to gain access to the data digitally or physical theft of the data storage media. To prevent this data from being accessed, modified or stolen, organizations will often employ security protection measures such as password protection, data encryption, or a combination of both. The security options used for this type of data are broadly referred to as data-at-rest protection (DARP). Definitions include: "...all data in computer storage while excluding data that is traversing a network or temporarily residing in computer memory to be read or updated." "...all data in storage but excludes any data that frequently traverses the network or that which resides in temporary memory. Data at rest includes but is not limited to archived data, data which is not accessed or changed frequently, files stored on hard drives, USB thumb drives, files stored on backup tape and disks, and also files stored off-site or on a storage area network (SAN)." While it is generally accepted that archive data (i.e. which never changes), regardless of its storage medium, is data at rest and active data subject to constant or frequent change is data in use. “Inactive data” could be taken to mean data which may change, but infrequently. The imprecise nature of terms such as “constant” and “frequent” means that some stored data cannot be comprehensively defined as either data at rest or in use. These definitions could be taken to assume that Data at Rest is a superset of data in use; however, data in use, subject to frequent change, has distinct processing requirements from data at rest, whether completely static or subject to occasional change. ==== Security ==== Because of its nature data at rest is of increasing concern to businesses, government agencies and other institutions. Mobile devices are often subject to specific security protocols to protect data at rest from unauthorized access when lost or stolen and there is an increasing recognition that database management systems and file servers should also be considered as at risk; the longer data is left unused in storage, the more likely it might be retrieved by unauthorized individuals outside the network. Data encryption, which prevents data visibility in the event of its unauthorized access or theft, is commonly used to protect data in motion and increasingly promoted for protecting data at rest. The encryption of data at rest should only include strong encryption methods such as AES or RSA. Encrypted data should remain encrypted when access controls such as usernames and password fail. Increasing encryption on multiple levels is recommended. Cryptography can be implemented on the database housing the data and on the physical storage where the databases are stored. Data encryption keys should be updated on a regular basis. Encryption keys should be stored separately from the data. Encryption also enables crypto-shredding at the end of the data or hardware lifecycle. Periodic auditing of sensitive data should be part of policy and should occur on scheduled occurrences. Finally, only store the minimum possible amount of sensitive data. Tokenization is a non-mathematical approach to protecting data at rest that replaces sensitive data with non-sensitive substitutes, referred to as tokens, which have no extrinsic or exploitable meaning or value. This process does not alter the type or length of data, which means it can be processed by legacy systems such as databases that may be sensitive to data length and type. Tokens require significantly less computational resources to process and less storage space in databases than traditionally encrypted data. This is achieved by keeping specific data fully or partially visible for processing and analytics while sensitive information is kept hidden. Lower processing and storage requirements makes tokenization an ideal method of securing data at rest in systems that manage large volumes of data. A further method of preventing unwanted access to data at rest is the use of data federation especially when data is distributed globally (e.g. in off-shore archives). An example of this would be a European organisation which stores its archived data off-site in the US. Under the terms of the USA PATRIOT Act the American authorities can demand

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  • Gnowit

    Gnowit

    Gnowit (pronounced "know it") is a Canadian software company that provides automated, near-real-time monitoring of legislative, regulatory, and political activity across Canada. Its platform aggregates and analyzes information from government publications, parliamentary debates, committee, and proceedings to provide searchable alerts and reports for organizations monitoring public policy and regulatory developments. The system uses natural-language processing and machine learning techniques to organize and filter large volumes of public information.; the company reports that new publication documents are captured and millions of items are added to its repository daily. == History, Founders and Leadership == Gnowit was co-founded in Ottawa in 2010 by Shahzad Khan and Mohammad Al-Azzouni; Khan serves as chief executive officer. Khan holds a PhD in Computer Science from the University of Cambridge, has more than two decades of experience in AI/ML and computational linguistics, and has authored or co-authored 37 peer-reviewed publications and five patents. Traditionally, companies performed this analysis manually; Gnowit has delivered efficiencies achieved through AI innovations. The company has participated in several Canadian startup and accelerator programs, including Carleton University's Lead To Win initiative, the University of Ottawa's Startup Garage, the Invest Ottawa incubator, and the League of Innovators' BOOST program. === Kubernetes validation (2019–2020) === As part of a Canada's Centre of Excellence in Next Generation Networks (CENGN) project, Gnowit validated a containerized version of its web-intelligence software on Kubernetes. Between 2019 and 2020, Gnowit participated in a project with Canada’s Centre of Excellence in Next Generation Networks (CENGN) to test and scale its platform using containerized infrastructure based on Kubernetes. The initiative focused on improving scalability and supporting the company’s transition from a monolithic software architecture to a cloud-native deployment model. == Products and services == Gnowit markets several modules for public-affairs, compliance, and market-intelligence teams. Legislative & Regulatory Monitoring (vAnalyst). vAnalyst is a monitoring platform that tracks legislative and regulatory activity across Canadian federal, provincial, and territorial jurisdictions. The system aggregates parliamentary debates, bills, committee proceedings, and regulatory publications and provides searchable alerts and reporting tools. The product monitors more than two million web sources to surface relevant items quickly. Parliamentary Live (vAnalyst). Monitors live video feeds from parliamentary sessions and committees with same-day transcripts, AI-generated summaries, witness summaries, and motion detection; municipal coverage is offered as an option. Gnowit can avail transcripts up to two weeks before official releases. These transcripts enable users to navigate and review lengthy parliamentary sittings and committee discussions through searchable text. Municipal Monitoring (vAnalyst). The platform also tracks council meetings, agendas, bylaws, and other municipal government publications from hundreds of Canadian municipalities. The platform aggregates these sources into a single searchable interface for reviewing local government decisions. Curation Edge (analyst service). Curation Edge is an add-on service in which expert analysts work and collaborate with clients to develop a tailored curation guide and deliver daily newsletters or briefs on legislation and media. These reports provide concise summaries, relevant links, and optional metadata, prioritizing key updates with additional context and analysis. The service is customizable, including branding and formatting for executive audiences, and is intended to reduce information overload, support decision-making, and streamline the synthesis and distribution of information. === Coverage and sources === Gnowit monitors sources span Canadian government materials across federal, provincial, and territorial jurisdictions Hansard transcripts (All Jurisdictions, including committees), order papers, committee transcripts, gazettes, bills, acts and regulations, consultations, regulatory-agency publications, and global news media as well as press releases and council-meeting materials from hundreds of municipalities. == Partnerships and support == Gnowit reports collaborations with Canadian academic and ecosystem partners, including: Algonquin College Carleton University McGill University University of Ottawa Université du Québec en Outaouais (UQO) Queen's University The company also participated in the accelerator program at Invest Ottawa and has received support from Canadian research and innovation programs, including: NRC Industrial Research Assistance Program (NRC-IRAP) Mitacs Ontario Centre of Innovation (OCI) (formerly OCE) Gnowit has also referenced membership in the Southern Ontario Smart Computing Innovation Platform (Government of Canada profile: FedDev Ontario – SOSCIP overview). == Technology == Gnowit develops technology intended to support timely decision-making by delivering updates from monitored web sources as they are published. The platform applies artificial intelligence (AI) and machine learning (ML) techniques to monitor, capture, clean, analyze, filter, and organize text, and to generate concise briefs. Its technical approach combines Boolean queries, shallow language processing techniques, and machine learning classifiers within a self-service interface. The company has described its longer-term development framework in relation to a belief–desire–intention (BDI) model of intelligent agents on the web. Gnowit and its founder are listed as inventors/assignees on patents concerning multi-document clustering, salient-content extraction, and sentiment analysis methods that are consistent with these features: US 9,600,470 – Method and system relating to re-labelling multi-document clusters (assignee: Whyz Technologies Ltd.). US 9,336,202 – Method and system relating to salient content extraction for information retrieval (assignee: Whyz Technologies Ltd.). CA 2,865,184 C – Method and system relating to re-labelling multi-document clusters. CA 2,865,186 C – Procédé et système concernant l'analyse de sentiment d'un contenu (sentiment analysis; French record). CA 2,865,187 C – Method and system relating to salient content extraction for information retrieval. == Research and community == In January 2025, Gnowit personnel contributed to regulatory NLP by co-authoring a peer-reviewed paper at the 1st Regulatory NLP Workshop (RegNLP 2025), co-located with COLING in Abu Dhabi. Titled Unifying Large Language Models and Knowledge Graphs for Efficient Regulatory Information Retrieval and Answer Generation, the work introduces PolicyInsight, a framework that joins a dynamic policy data model and knowledge graph with LLMs to monitor policy texts, detect changes, and support retrieval and answer generation; the author list includes Shahzad Khan (CEO, Gnowit Inc.). (ACL Anthology, aclweb.org). Similar information-retrieval technologies are widely used for competitive intelligence, policy monitoring, and media analysis. == White paper == Gnowit has published a practical guide, Automated Government Information Monitoring, which outlines how GR and regulatory teams can design a monitoring and briefing workflow and describes Gnowit's automation features and export options (PDF, email, dashboards, CSV/JSON/XML/API).

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  • Language Server Protocol

    Language Server Protocol

    The Language Server Protocol (LSP) is an open, JSON-RPC-based protocol for use between source-code editors or integrated development environments (IDEs) and servers that provide "language intelligence tools": programming language-specific features like code completion, syntax highlighting and marking of warnings and errors, as well as refactoring routines. The goal of the protocol is to allow programming language support to be implemented and distributed independently of any given editor or IDE. In the early 2020s, LSP quickly became a "norm" for language intelligence tools providers. == History == LSP was originally developed for Microsoft Visual Studio Code and is now an open standard. On June 27, 2016, Microsoft announced a collaboration with Red Hat and Codenvy to standardize the protocol's specification. Its specification is hosted and developed on GitHub. == Background == Modern IDEs provide programmers with sophisticated features like code completion, refactoring, navigating to a symbol's definition, syntax highlighting, and error and warning markers. For example, in a text-based programming language, a programmer might want to rename a method read. The programmer could either manually edit the respective source code files and change the appropriate occurrences of the old method name into the new name, or instead use an IDE's refactoring capabilities to make all the necessary changes automatically. To be able to support this style of refactoring, an IDE needs a sophisticated understanding of the programming language that the program's source is written in. A programming tool without such an understanding—for example, one that performs a naive search-and-replace instead—could introduce errors. When renaming a read method, for example, the tool should not replace the partial match in a variable that might be called readyState, nor should it replace the portion of a code comment containing the word "already". Neither should renaming a local variable read, for example, end up altering identically-named variables in other scopes. Conventional compilers or interpreters for a specific programming language are typically unable to provide these language services, because they are written with the goal of either transforming the source code into object code or immediately executing the code. Additionally, language services must be able to handle source code that is not well-formed, e.g. because the programmer is in the middle of editing and has not yet finished typing a statement, procedure, or other construct. Additionally, small changes to a source code file which are done during typing usually change the semantics of the program. In order to provide instant feedback to the user, the editing tool must be able to very quickly evaluate the syntactical and semantical consequences of a specific modification. Compilers and interpreters therefore provide a poor candidate for producing the information needed for an editing tool to consume. Prior to the design and implementation of the Language Server Protocol for the development of Visual Studio Code, most language services were generally tied to a given IDE or other editor. In the absence of the Language Server Protocol, language services are typically implemented by using a tool-specific extension API. Providing the same language service to another editing tool requires effort to adapt the existing code so that the service may target the second editor's extension interfaces. The Language Server Protocol allows for decoupling language services from the editor so that the services may be contained within a general-purpose language server. Any editor can inherit sophisticated support for many different languages by making use of existing language servers. Similarly, a programmer involved with the development of a new programming language can make services for that language available to existing editing tools. Making use of language servers via the Language Server Protocol thus also reduces the burden on vendors of editing tools, because vendors do not need to develop language services of their own for the languages the vendor intends to support, as long as the language servers have already been implemented. The Language Server Protocol also enables the distribution and development of servers contributed by an interested third party, such as end users, without additional involvement by either the vendor of the compiler for the programming language in use or the vendor of the editor to which the language support is being added. LSP is not restricted to programming languages. It can be used for any kind of text-based language, like specifications or domain-specific languages (DSL). == Technical overview == When a user edits one or more source code files using a language server protocol-enabled tool, the tool acts as a client that consumes the language services provided by a language server. The tool may be a text editor or IDE and the language services could be refactoring, code completion, etc. The client informs the server about what the user is doing, e.g., opening a file or inserting a character at a specific text position. The client can also request the server to perform a language service, e.g. to format a specified range in the text document. The server answers a client's request with an appropriate response. For example, the formatting request is answered either by a response that transfers the formatted text to the client or by an error response containing details about the error. The Language Server Protocol defines the messages to be exchanged between client and language server. They are JSON-RPC preceded by headers similar to HTTP. Messages may originate from the server or client. The protocol does not make any provisions about how requests, responses and notifications are transferred between client and server. For example, client and server could be components within the same process exchanging JSON strings via method calls. They could also be different processes on the same or on different machines communicating via network sockets. == Registry == There are lists of LSP-compatible implementations, maintained by the community-driven Langserver.org or Microsoft.

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  • Web API

    Web API

    A web API is an application programming interface (API) for either a web server or a web browser. As a web development concept, it can be related to a web application's client side (including any web frameworks being used). A server-side web API consists of one or more publicly exposed endpoints to a defined request–response message system, typically expressed in JSON or XML by means of an HTTP-based web server. A server API (SAPI) is not considered a server-side web API, unless it is publicly accessible by a remote web application. == Client side == A client-side web API is a programmatic interface to extend functionality within a web browser or other HTTP client. Originally these were most commonly in the form of native plug-in browser extensions however most newer ones target standardized JavaScript bindings. The Mozilla Foundation created their WebAPI specification which is designed to help replace native mobile applications with HTML5 applications. Google created their Native Client architecture which is designed to help replace insecure native plug-ins with secure native sandboxed extensions and applications. They have also made this portable by employing a modified LLVM AOT compiler. == Server side == A server-side web API consists of one or more publicly exposed endpoints to a defined request–response message system, typically expressed in JSON or XML. The web API is exposed most commonly by means of an HTTP-based web server. Mashups are web applications which combine the use of multiple server-side web APIs. Webhooks are server-side web APIs that take input as a Uniform Resource Identifier (URI) that is designed to be used like a remote named pipe or a type of callback such that the server acts as a client to dereference the provided URI and trigger an event on another server which handles this event thus providing a type of peer-to-peer IPC. === Endpoints === Endpoints are important aspects of interacting with server-side web APIs, as they specify where resources can be accessed by third-party software. Usually the access is via a URI to which HTTP requests are posted, and from which the response is thus expected. Web APIs may be public or private, the latter of which requires an access token. Endpoints need to be static, otherwise the correct functioning of software that interacts with them cannot be guaranteed. If the location of a resource changes (and with it the endpoint) then previously written software will break, as the required resource can no longer be found at the same place. As API providers still want to update their web APIs, many have introduced a versioning system in the URI that points to an endpoint. === Resources versus services === Web 2.0 Web APIs often use machine-based interactions such as REST and SOAP. RESTful web APIs use HTTP methods to access resources via URL-encoded parameters, and use JSON or XML to transmit data. By contrast, SOAP protocols are standardized by the W3C and mandate the use of XML as the payload format, typically over HTTP. Furthermore, SOAP-based Web APIs use XML validation to ensure structural message integrity, by leveraging the XML schemas provisioned with WSDL documents. A WSDL document accurately defines the XML messages and transport bindings of a Web service. === Documentation === Server-side web APIs are interfaces for the outside world to interact with the business logic. For many companies this internal business logic and the intellectual property associated with it are what distinguishes them from other companies, and potentially what gives them a competitive edge. They do not want this information to be exposed. However, in order to provide a web API of high quality, there needs to be a sufficient level of documentation. One API provider that not only provides documentation, but also links to it in its error messages is Twilio. However, there are now directories of popular documented server-side web APIs. === Growth and impact === The number of available web APIs has grown consistently over the past years, as businesses realize the growth opportunities associated with running an open platform, that any developer can interact with. ProgrammableWeb tracks over 24000 Web APIs that were available in 2022, up from 105 in 2005. Web APIs have become ubiquitous. There are few major software applications/services that do not offer some form of web API. One of the most common forms of interacting with these web APIs is via embedding external resources, such as tweets, Facebook comments, YouTube videos, etc. In fact there are very successful companies, such as Disqus, whose main service is to provide embeddable tools, such as a feature-rich comment system. Any website of the TOP 100 Alexa Internet ranked websites uses APIs and/or provides its own APIs, which is a very distinct indicator for the prodigious scale and impact of web APIs as a whole. As the number of available web APIs has grown, open source tools have been developed to provide more sophisticated search and discovery. APIs.json provides a machine-readable description of an API and its operations, and the related project APIs.io offers a searchable public listing of APIs based on the APIs.json metadata format. === Business === ==== Commercial ==== Many companies and organizations rely heavily on their Web API infrastructure to serve their core business clients. In 2014 Netflix received around 5 billion API requests, most of them within their private API. ==== Governmental ==== Many governments collect a lot of data, and some governments are now opening up access to this data. The interfaces through which this data is typically made accessible are web APIs. Web APIs allow for data, such as "budget, public works, crime, legal, and other agency data" to be accessed by any developer in a convenient manner. == Example == An example of a popular web API is the Astronomy Picture of the Day API operated by the American space agency NASA. It is a server-side API used to retrieve photographs of space or other images of interest to astronomers, and metadata about the images. According to the API documentation, the API has one endpoint: https://api.nasa.gov/planetary/apod The documentation states that this endpoint accepts GET requests. It requires one piece of information from the user, an API key, and accepts several other optional pieces of information. Such pieces of information are known as parameters. The parameters for this API are written in a format known as a query string, which is separated by a question mark character (?) from the endpoint. An ampersand (&) separates the parameters in the query string from each other. Together, the endpoint and the query string form a URL that determines how the API will respond. This URL is also known as a query or an API call. In the below example, two parameters are transmitted (or passed) to the API via the query string. The first is the required API key and the second is an optional parameter — the date of the photograph requested. https://api.nasa.gov/planetary/apod?api_key=DEMO_KEY&date=1996-12-03 Visiting the above URL in a web browser will initiate a GET request, calling the API and showing the user a result, known as a return value or as a return. This API returns JSON, a type of data format intended to be understood by computers, but which is somewhat easy for a human to read as well. In this case, the JSON contains information about a photograph of a white dwarf star: The above API return has been reformatted so that names of JSON data items, known as keys, appear at the start of each line. The last of these keys, named url, indicates a URL which points to a photograph: https://apod.nasa.gov/apod/image/9612/ngc2440_hst2.jpg Following the above URL, a web browser user would see this photo: Although this API can be called by an end user with a web browser (as in this example) it is intended to be called automatically by software or by computer programmers while writing software. JSON is intended to be parsed by a computer program, which would extract the URL of the photograph and the other metadata. The resulting photo could be embedded in a website, automatically sent via text message, or used for any other purpose envisioned by a software developer.

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  • FreePBX Distro

    FreePBX Distro

    The FreePBX Distro was a freeware unified communications software system that consisted of FreePBX, a graphical user interface (GUI) for configuring, controlling and managing Asterisk PBX software. The FreePBX Distro included packages that offer VoIP, PBX, Fax, IVR, voice-mail and email functions. The FreePBX Distro Linux distribution was based on CentOS, which maintains binary compatibility with Red Hat Enterprise Linux. FreePBX has contributed to the popularity of Asterisk. As a result of CentOS Linux being discontinued and the last version of CentOS 7 going out of support on June 30, 2024, FreePBX 17 has moved over to and is supported on Debian Linux. FreePBX will no longer be providing a pre-configured FreePBX Distro, but will provide a script to install FreePBX on a fresh install of Debian Linux. In-place migration will not be possible, but will be possible by restoring a backup on the new version from the previous version. As FreePBX 16 will be supported until the release of FreePBX 18, FreePBX on this distribution will still work and be supported, however, there will be no further support for the underlying operating system. == Installation == The Official FreePBX Distro is installed from a ISO image available by web download, that includes the system CentOS, Asterisk, FreePBX GUI and assorted dependencies. This can then either be burned to DVD or written to a USB stick for installation == Support for telephony hardware == The FreePBX Distro has built-in support for cards from multiple vendors, including Digium, OpenVox, Alto, Rhino Equipment, Xorcom and Sangoma. The FreePBX Distro supports a large number of phone models via open-source modules. Supported VoIP phone manufacturers include Algo, AND, AudioCodes, Cisco, Cyberdata, Digium, Grandstream, Mitel/Aastra, Nortel/Avaya, Panasonic, Polycom, Sangoma, Snom, Xorcom and Yealink. == Development == FreePBX made its debut in 2004 as the AMP project (Asterisk Management Portal). The FreePBX Distro was released in 2011 as an turnkey solution for building a PBX using Asterisk, CentOS and FreePBX. FreePBX has over 1 million active production PBXs and over 20,000 new systems added each month. The core telephony engine is Asterisk, as configured by the Open Source FreePBX GUI. The last stable release is FreePBX Distro Stable SNG7-PBX16-64bit-2302-1 based on these main components: FreePBX 16 CentOS 7.8 Asterisk 16, 18, 19 (20 supported by upgrade once installed)

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  • WebAR

    WebAR

    WebAR, previously known as the Augmented Web, is a web technology that allows for augmented reality functionality within a web browser. It is a combination of HTML, Web Audio, WebGL, and WebRTC. From 2020s more known as web-based Augmented Reality or WebAR, which is about the use of augmented reality elements in browsers. It was the focus of a Birds of a Feather meeting at ISMAR2012 and is now the focus of the W3C Augmented Web Community Group. == Features == Browser augmented reality for smartphones has a number of features that distinguish it from similar content in special apps. No special applications are needed for Web AR. A regular browser is enough. And it can run to a certain extent on most browsers. It is easy to set up marketing analytics. By connecting the website to services that collect statistics, it is convenient to receive geographic coordinates, demographic characteristics and other information about users. Ability to add a CTA button. It is extremely important for marketing websites to place it so that the user can add contact information or place an order after considering the offer. Rich content. Browser augmented reality for tablets and smartphones supports 2D and 3D graphics, animation and other formats. Image marker tracking. If a QR code is selected as an activator for an AR element or just a picture on a flat surface, the device can easily read it. Various activation ways. Web AR can be marker and markerless, attached to geolocation, it can also be hidden in a direct link. Game content. Even simple games with simple mechanics, transferred into augmented reality, can delight the website visitor. Cross-platform. You can view content that complements our usual reality using any modern smartphone model. == Limitations == Performance is simply better on an app, where there's capacity for more memory and programs are executed in native code therefore it provides better visuals, better animations and better interactivity than in WebAR experience. A web page can only have access to certain parts of the device you're using, whereas a native app can access all of a device's capabilities. Meaning if you want the convenience of WebAR, you need to be thinking of simple but effective experiences instead. Compatibility. Not every mobile device has the required HW for AR performance. == Implementation == Browser support is evolving quickly and can best be monitored using services like Can I Use. Since this is a web application, there are platforms that support the creation of WebAR that are similar to normal web development platforms. Something which enables the creation of 3D assets and environments using a web framework that looks similar to HTML. Applications (like for example – A-Frame) are supported by 8th Wall, which is by the end of 2021 the leading SLAM tracking SDK for WebAR on the market. WebAR is currently limited mostly by the browser – so how much the technology will develop rather depends on what the big players like Google and Apple develop. For iOS device users, Apple developed AR Quick Look, an extension that enables users to use ARKit on the web. For Android devices your browser should support WebXR, an API that allows users to view AR/VR content without installing extra plugins or software, and have ARCore installed. There are many tools and frameworks that help developers in expanding the immersive web with WebAR. For example, AR.js is an open-source library for Augmented Reality on the Web for improved WebAR performance on smartphones that includes marker-based technology (simplified QR-codes) and location-based AR. Apple at the WWDC Conference 2018, announced that it has developed a new file format, working together with Pixar, called USDZ Universal. This file will allow developers to create 3d models for augmented reality. USDZ format was created by Apple together with Pixar Animation Studio and allowed developers to create 3D models for AR. == Industries == Where WebAR can be used from virtual guides, which can help students navigate through campus to virtual film posters: E-commerce and Advertising. Education. Entertainment. Business. Fashion. == Examples == Promotion of Spider-Man: Into the Spider-Verse for which 8th Wall developed the AR platform that made this interactive WebAR promoting the Sony animated smash hit. Everyone can invite teenage Spiderman/Miles Morales into their homes for some one-on-one interaction, take pictures and share the experience with friends. Sony Pictures included the QR code to launch this WebAR site in print promotions for the movie. Also in 2017 the advertising of Jumanji: The Next Level gave us the world's first WebAR activation with usage of Amazon Lex to power voice interaction (the same tool that powers Amazon Alexa), the experience sends users on a wild 3D adventure into the world of Jumanji! This was a collaboration between Sony Pictures and Trigger - The Mixed Reality Agency. The WebAR technology is powered by 8th Wall. And you can check it via the link to the official YouTube recording of the experience. RPR & Microsoft's Holographic Retail Platform, where Web AR brings a new twist to online shopping by allowing users to interact with 3D holographic images of models right from their smartphones' browsers. This experience is designed to increase buyer confidence and reduce clothing returns, which are two of the greatest challenges to purchasing clothing online. Digital Porsche Brand Academy was developed by the Team of svarmony Technologies GmbH and it is the first-to-market training tool that uses augmented reality to provide Porsche employees an immersive experience learning about the company's history and values. The star of this WebAR experience is an animated avatar that serves as a tour guide for Porsche's past, present, and future. Employees can explore realistically animated Porsche-locations, take a ride in a virtual Porsche, help assemble a car, and test Porsche knowledge via a quiz. The Digital Porsche Brand Academy is a great starter kit for employees to establish a relationship with the brand and align with the company's plans. == Future == By freeing smartphone users from having to install numerous apps, WebAR can make Augmented Reality far more accessible for them and more beneficial for business. The further development of the WebAR can be accelerated by the widespread social acceptance of the headsets that can give the whole other level of AR experience. This means instant access to the information when the contextually relevant content is appearing as the person's real background is changing.

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  • Unfold (app)

    Unfold (app)

    Unfold is a mobile application that allows users to create social media content using a variety of templates and other tools. It was founded in 2018 by Alfonso Cobo and Andy McCune. It enables users to add photos, video, and text with a variety of tools. In 2019, Unfold was acquired by Squarespace. == History == In January 2017, Alfonso Cobo was studying at Parsons School of Design when he realized there was no software or app that could create a portfolio of his work on an iPad. Cobo created an app called Portfolio, a basic version of a portfolio layout app, and the first one to exist for iPad. He launched it in 2017. After launching the first version of Portfolio, Cobo realized the more popular market and use case was on mobile. Around that time, Instagram was launching Stories. As a result, Cobo pivoted the app away from portfolios and instead focused on an app to showcase one's stories. Cobo later contacted Andy McCune, founder of social media account Earth, to collaborate with Unfold. Unfold also partnered with various companies to create custom templates. These include Equinox, Tommy Hilfiger, NARS, Billboard Music Awards, and Product Red. Unfold also launched a collection of Product Red templates to help eliminate HIV/AIDS in several African countries. In 2019, Squarespace acquired Unfold. The Unfold app has been downloaded over 60 million times and has been used to create over 1 billion Instagram stories. == Features == With Unfold, users can utilize hundreds of templates to make social content for social media platforms such as Instagram, Snapchat, and Facebook. The free app offers users basic templates and standard fonts, filters, and stickers, and there are also premium templates available for a monthly subscription. With Unfold+ and Unfold Pro (previously Unfold for Brands), users can access premium templates and tools, as well as upload custom brand assets and fonts. In 2020, Unfold launched Bio Sites, which allows users to link to multiple sites and platforms.

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  • W3C Device Description Working Group

    W3C Device Description Working Group

    The W3C Device Description Working Group (DDWG), operating as part of the World Wide Web Consortium (W3C) Mobile Web Initiative (MWI), was chartered to "foster the provision and access to device descriptions that can be used in support of Web-enabled applications that provide an appropriate user experience on mobile devices." Mobile devices exhibit the greatest diversity of capabilities, and therefore present the greatest challenge to content adaptation technologies. The group published several documents, including a list of requirements for an interface to a Device Description Repository (DDR) and a standard interface meeting those requirements. The group was rechartered in 2006 to work in public towards the development of the Application Programming Interface (API) for a DDR. Early in 2007, the group launched a wiki and a blog to add to the public mailing list. The group subsequently published a formal vocabulary of core device properties, and an API called the DDR Simple API, which became a W3C Recommendation in December 2008. The group closed at the end of 2008, but with the intention of maintaining the Web pages, blog and wiki through W3C volunteer effort. == Publications == The DDWG published several W3C Working Group Notes and one W3C Recommendation. A W3C WG Note that articulates what the W3C and other organizations are doing or have already done with regard to device information. This document suggests an environment in which these technologies work together to meet the goals of content adaptation. The completed document was published on 31 October 2007. A W3C WG Note describing the ecosystem surrounding creation, maintenance and use of device descriptions. The completed document was published on 31 October 2007. A W3C WG Note describing a set of requirements for a reference repository of device descriptions. The completed document was published on 17 December 2007. A W3C WG Note describing a process to manage contributions to an initial core vocabulary, identification of key device properties, a formal initial core vocabulary and the identification of a maintainer for the core vocabulary. The details were contained in the Working Group Note describing the DDWG Core Vocabulary published on 14 April 2008. A W3C WG Note defining useful grouping and structure patterns in device descriptions. The Device Description Structures document was published as a Working Draft on 5 December 2008. The intention is that this document will be future input to other W3C groups. A W3C Recommendation defining a language-neutral programming interface to a Device Description Repository. The DDR Simple API was published on 5 December 2008. There is the possibility of future publications on the DDWG wiki describing implementations of the API in various languages, including Java, IDL, WSDL, C# etc. Much of the DDWG's material was developed in public via the DDWG Wiki and through their public mailing lists.

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  • Motion picture film scanner

    Motion picture film scanner

    A motion picture film scanner is a device used in digital filmmaking to scan original film for storage as high-resolution digital intermediate files. A film scanner scans original film stock: negative or positive print or reversal/IP. Units may scan gauges from 8 mm to 70 mm (8 mm, Super 8, 9.5 mm, 16 mm, Super 16, 35 mm, Super 35, 65 mm and 70 mm) with very high resolution scanning at 2K, 4K, 8K, or 16K resolutions. (2K is approximately 2048×1080 pixels and 4K is approximately 4096×2160 pixels). Some models of film scanner are intermittent pull-down film scanners which scan each frame individually, locked down in a pin-registered film gate, taking roughly a second per frame. Continuous-scan film scanners, where the film frames are scanned as the film is continuously moved past the imaging pick up device, are typically evolved from earlier telecine mechanisms, and can act as such at lower resolutions. The scanner scans the film frames into a file sequence (using high-end computer data storage devices), whose single file contains a digital scan of each still frame; the preferred image file format used as output are usually Cineon, DPX or TIFF, because they can store color information as raw data, preserving the optical characteristics of the film stock. These systems take a lot of storage area network (SAN) disk space. The files can be played back one after each other on high-end workstation non-linear editing system (NLE) or a virtual telecine systems. The playback is at the normal rate of 24 frames per second (or original projection frame rate of: 25, 30 or other speeds). Each year hard disks get larger and are able to hold more hours of movies on SAN systems. The challenge is to archive this massive amount of data on to data storage devices. The scanned footage is edited and composited on work stations then mastered back on film, see film-out and digital intermediate. Scanned film frames may also be used in digital film restoration. The film may also be projected directly on a digital projector in the theater. The data film files may be converted to SDTV (NTSC or PAL) video TV systems. Film recorders are the opposite of film scanners, copying content from a computer system onto film stock, for preservation or for display using film projectors. Telecines are similar to film scanners. == Imaging device == The front end of a motion picture film scanner is similar to a telecine. The imaging system may be either a charge-coupled device (CCD), a complementary metal–oxide–semiconductor (CMOS) or photomultipliers imaging pick up. A lamp is used as the light source in a CCD imaging front end. The CCDs convert the light to the video signals. In a cathode-ray tube (CRT) imaging system the CRT (also called a Flying spot tube) is used as the light source and part of the scanning system. Photomultipliers or avalanche photodiodes are used to convert the light to electrical video signals. A prism and/or dichroic mirrors or color filters are used to separate the light into the three: red, green and blue, imaging pick up devices. == Image processing == The three color signals (RGB) are electronically processed and color graded. A 3D look up table (3D LUT) is usually applied to the RGB values before it is coded into the DPX output files. The DPX files are usually made output through a network port cable or an optical fiber port: HIPPI, Fibre Channel or newer systems like gigabit Ethernet. A computer then stores the files on to hard drives of a storage area network for later processing and use. Modern motion picture film scanners many have an option for an infrared CCD channel for dirt mapping, that can be used to automatically or in post manually remove dirt-dust spots on the film. The IR camera channel can be used with IR dirt and scratch removal system or made output on a four IR channel for downstream dirt and dirt and scratch removal systems. Popular downstream dirt and dirt and scratch removal systems are PF Clean and Digital ICE. HDR or high dynamic range is a new system, using a compositing and tone-mapping of images to extend the dynamic range beyond the native capability of the capturing device. This may be done by using a triple exposure for the film and then compositing the three back together. Compositing can be done in a workstation in none real time or in the scanner in real time. == Models == Bold indicates a currently produced model Single frame intermittent pull-down: ARRI - Arriscan Cintel - diTTo Filmlight - Northlight 1 (up to 6K, 16mm to VistaVision), Northlight 2 (up to 8K, 16mm to VistaVision) Imagica scanner, single frame intermittent scanner. Kodak - Cineon, the first system designed for DI work, included a scanner, tapes drives, workstations and a film recorder. Lasergraphics Director 13.5K, 8mm to 70mm, IMAX & VistaVision) Continuous motion scanning: Arri - ARRISCAN XT (up to 6K, S35 down to 16mm) Cintel's C-Reality/DSX and ITK - Millennium/dataMill. Under ownership of Blackmagic Design, the Cintel Scanner was released, with the current 3rd generation capable of up to 4K scans at 30 fps. DFT - Spirit Classic (up to 2K), Spirit 4k/2k/HD (up to 4K), POLAR HQ (up to 8K, 8mm to S35), OXScan 14K (up to 14K, 16mm to 70mm), Scanity HDR (up to 4K, 16mm to S35) Filmfabriek - HDS+ (up to 4k), Pictor Pro (up to 2.7K), Pictor (up to 1080p). Filmfabriek scanners can only scan 17.5mm or smaller film formats. GE4 - Golden Eye Four - Filmscanner, 38 Mega Pixel camera. LED light source and continuous film transport using Capstan. From Digital Vision. Lasergraphics ScanStation (6.5K, 8mm to 70mm, IMAX & VistaVision) Lasergraphics Archivist (up to 5K) MWA Nova Vario series with patented laser-based, sprocket and claw free transport for 16/35mm for realtime (24/25fps) scanning with sensors for either 2K+ 2236 x 1752, or 2.5K+ HDR High Dynamic Range at 2560 x 2160, direct optical and magnetic sound on and 16 and 35mm. MWA Nova Choice 2K+ patented laser-based, sprocket and claw free transport for 8/Super8, 9.5mm, 16mm realtime (24/25fps) scanning w at 2K+, 2236 x 1752 with direct optical and magnetic sound on 16mm, magnetic from main and balance stripes on 8, Super8. Faster than real time scanning at lower resolution. P+S Technik - SteadyFrame Universal Format Film Scanner Walde - FilmStar 4K UHD 2K @ 25fps, 4K UHD @ 6fps. 35mm/16mm/8mm archive quality, continuous motion capstan driven.

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  • Mosaik Solutions

    Mosaik Solutions

    Mosaik Solutions (formerly American Roamer) was a company that specializes in wireless coverage data and wireless coverage maps, based in Memphis, Tennessee before being acquired by Ookla. The company collects and crowdsources carrier signal quality from major telecommunications providers or users who have its consumer or enterprise mobile application installed. The data is used to provide insights into places around the world without access to cellular coverage and the development of new coverage patterns, as well as to provide maps showing what provider offers the best service in an area. In 2011, the Federal Communications Commission (FCC), recognized Mosaik Solutions as the "industry standard" for the presence of wireless service at the census-block level. == History == In 2016, Mosaik purchased Sensorly, a free app developed to crowdsource cellular network performance service and provide coverage mapping for wireless networks worldwide. == Products and services == === MapELEMENTS === MapELEMENTS software is a visualization tool that allows users to analyze data from the largest cellular coverage database in the world. === CellMaps === CellMaps is an interactive mapping solution that allows companies to show their network coverage directly on their website through an iframe or API. In 2013 Mosaik launched an android app for CellMaps that provides data directly from carriers so that users can determine what carrier meets their needs in a given area. On the map you can overlay multiple carriers, zoom to street-view level, and drop a pin onto any given spot to get a breakdown of carrier service in that area. === Signal Insights App === Signal Insights is an SaaS platform service available for android users that measures and analyzes the customer's experience in cellular or Wi-Fi networks. Indoor mode allows a user to upload a building floor plan and then map and test specific points in the building for cellular or Wi-Fi connectivity. === Sensorly App === Sensorly is a free app that crowdsources cellular network performance to provide coverage mapping worldwide and mobile speed data to help consumers make informed decisions when choosing a cellular carrier. In February 2017, Sensorly launched Map Trip, a feature that allows users to map their routes and share with others their signal data at a particular point in real time. === TowerSource === TowerSource is a resource for locating cell towers and identifying ownership, availability, fiber routes, type and height. It was acquired by Mosaik Solutions in September 2014. === Network Validator === Network Validator is a SaaS solution designed for users to quickly determine whether global cellular networks exist - by country, operator and wireless technology. === CoverageRight === CoverageRight is composed of licensed GIS file datasets that identify the marketed coverage of wireless operators in the United States and worldwide. It enables users to perform spatial analyses, monitor competitive build-outs, analyze coverage trends and assemble roaming footprints. This data has been utilized by the FCC to analyze wireless coverage nationwide. === Network QoE === Network QoE is an enterprise platform that uses crowdsourced data from cellular devices to detect wireless network issues including 3G, 4G and wifi accessibility, network coverage holes and data performance issues. === Wireless Spectrum Report === In March 2017, Mosaik Solutions launched the Wireless Spectrum Report, a tabular dataset detailing facts about spectrum ownership and availability in the United States.

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  • Google Vids

    Google Vids

    Google Vids (not to be confused with Google Video) is an online timeline-based video editing application included as part of the Google Workspace suite. It is designed to help users create informational videos for work-related purposes. The app uses Google's Gemini technology to enable users to create video storyboards manually or with AI assistance using simple prompts. Features include uploading media, choosing stock videos, images, background music, and a voiceover feature with script generation using AI. The app is currently in testing with select Google Workspace Labs users. Like Kapwing and Capcut, Google Vids is primarily for creating work-related content like sales training, onboarding videos, vendor outreach, and project updates. It offers various styles and templates, collaborative features, and is not limited to videos without the short integration at the moment. Google Vids was announced on April 9, 2024. In September 2025, Google began to roll out a basic version of the application to Google Workspace users.

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  • Single address space operating system

    Single address space operating system

    In computer science, a single address space operating system (or SASOS) is an operating system that provides only one globally shared address space for all processes. In a single address space operating system, numerically identical (virtual memory) logical addresses in different processes all refer to exactly the same byte of data. In a traditional OS with private per-process address space, memory protection is based on address space boundaries ("address space isolation"). Single address-space operating systems make translation and protection orthogonal, which in no way weakens protection. The core advantage is that pointers (i.e. memory references) have global validity, meaning their meaning is independent of the process using it. This allows sharing pointer-connected data structures across processes, and making them persistent, i.e. storing them on backup store. Some processor architectures have direct support for protection independent of translation. On such architectures, a SASOS may be able to perform context switches faster than a traditional OS. Such architectures include Itanium, and Version 5 of the Arm architecture, as well as capability architectures such as CHERI. A SASOS should not be confused with a flat memory model, which provides no address translation and generally no memory protection. In contrast, a SASOS makes protection orthogonal to translation: it may be possible to name a data item (i.e. know its virtual address) while not being able to access it. SASOS projects using hardware-based protection include the following: Angel IBM i (formerly called OS/400) Iguana at NICTA, Australia Mungi at NICTA, Australia Nemesis Opal Scout Sombrero Related are OSes that provide protection through language-level type safety: Br1X Genera JX a research Java OS Phantom OS Singularity Theseus OS Torsion

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  • Packingham v. North Carolina

    Packingham v. North Carolina

    Packingham v. North Carolina, 582 U.S. 98 (2017), is a case in which the Supreme Court of the United States held that a North Carolina statute that prohibited registered sex offenders from using social media websites was unconstitutional because it violated the First Amendment to the U.S. Constitution, which protects freedom of speech. In 2010, Lester Gerard Packingham, a registered sex offender, posted on Facebook under a pseudonym to comment favorably on a recent traffic court experience. Police then identified Packingham and charged him with violating North Carolina's law. Packingham moved to dismiss the charges, arguing that the state's law violated the First Amendment. The trial court dismissed this motion and ultimately convicted Packingham. A state appellate court initially reversed the trial court, holding that the law did violate the First Amendment, but the North Carolina Supreme Court, the state's highest court, disagreed and reinstated the conviction. In June 2017, the U.S. Supreme Court unanimously reversed the North Carolina Supreme Court's judgment. In the majority opinion authored by Justice Anthony Kennedy, the Court held that social media—defined broadly to include Facebook, Amazon.com, The Washington Post, and WebMD, among many others—is a "protected space" under the First Amendment for lawful speech. The Court offered that North Carolina could protect children through less restrictive means, such as prohibiting "conduct that often presages a sexual crime, like contacting a minor or using a website to gather information about a minor". == Background == === North Carolina statute === In 2008, the state of North Carolina passed a law that made it a felony for a registered sex offender "to access a commercial social networking Web site where the sex offender knows that the site permits minor children to become members or to create or maintain personal Web pages". The law defined a "commercial social networking Web site" using four criteria. Specifically, the website must: be "operated by a person who derives revenue from membership fees, advertising, or other sources related to the operation of the Web site". facilitate "the social introduction between two or more persons for the purposes of friendship, meeting other persons, or information exchanges". allow "users to create Web pages or personal profiles that contain information such as the name or nickname of the user, photographs placed on the personal Web page by the user, other personal information about the user, and links to other personal Web pages on the commercial social networking Web site of friends or associates of the user that may be accessed by other users or visitors to the Web site". provide "users or visitors... mechanisms to communicate with other users, such as a message board, chat room, electronic mail, or instant messenger". The law exempted websites that "Provid[e] only one of the following discrete services: photo-sharing, electronic mail, instant messenger, or chat room or message board platform", as well as websites that have as their primary purpose "the facilitation of commercial transactions involving goods or services between [their] members or visitors". === Facts of the case === In 2002, Lester Gerard Packingham was convicted of taking "indecent liberties with a child", a felony that required him to register as a sex offender. A North Carolina court sentenced him to 10–12 months in prison with 24 months of supervised release. He was given no other special instructions on his behavior outside of prison other than to "remain away from" the minor. In 2010, after a state court dismissed a traffic ticket against Packingham, he submitted a post on Facebook under the name "J. R. Gerrard", stating: "Man God is Good! How about I got so much favor they dismissed the ticket before court even started? No fine, no court cost, no nothing spent. . . . . .Praise be to GOD, WOW! Thanks JESUS!" The Durham Police Department identified Packingham as the author of the post after cross-checking the time of the post with recently dismissed traffic tickets, and a grand jury indicted him for violating the North Carolina statute. === Lower court proceedings === Initially, Packingham moved to dismiss his indictment, arguing that it violated the First Amendment. A North Carolina Superior Court judge denied this motion, and he was convicted of violating the North Carolina social media law. Packingham appealed his conviction to the North Carolina Court of Appeals, which reversed the trial court's decision in 2013. Applying intermediate scrutiny, the court of appeals determined that North Carolina's law violated the First Amendment because it was too broad, applying to all registered sex offenders regardless of whether the offender had committed a crime involving a minor or whether the offender was a continuing threat to minors. The appeals court also stated that the law had been defined broadly enough to prohibit a registered sex offender from conducting a wide array of Internet activity, such as "conducting a 'Google' search, purchasing items on Amazon.com, or accessing a plethora of Web sites unrelated to online communication with minors". In 2015, the North Carolina Supreme Court, the state's highest court, reversed the court of appeals, holding that the law was "constitutional in all respects". The North Carolina Supreme Court found that the statute was a "limitation on conduct" and did not impede any free speech. The state had a vested interest in “forestalling the illicit lurking and contact of minors” by registered sex offenders and potential future victims, and upheld Packingham's conviction. == Supreme Court ruling == Packingham filed a petition for a writ of certiorari with the Supreme Court of the United States. The federal government also filed a brief recommending that the Supreme Court grant certiorari, arguing that the North Carolina Supreme Court incorrectly decided the case in favor of the state. The U.S. Supreme Court granted certiorari in October 2016. Amicus briefs in support of Packingham were filed by the libertarian Cato Institute and the American Civil Liberties Union. The North Carolina Supreme Court filed a brief supporting its prior decision, urging the importance of protecting minors from being stalked online. === Oral argument === The oral argument took place in February 2017. Packingham’s lawyer, David T. Goldberg, argued that the law banned “vast swaths of First Amendment activity”, went too far in restricting which Internet sites could be accessed, and forbade use of the Internet in general. The law targeted speech on some of the platforms that Americans use most often, Goldberg noted, and that under the law Packingham could not even use Twitter to read the myriad messages discussing his own case. He further noted that the law imposes punishment without regard to whether the offender actually did anything wrong. North Carolina’s senior deputy Attorney General, Robert C. Montgomery, argued for the state, and claimed that communication through social media sites is a “crucial channel”. Justice Sonia Sotomayor asked Montgomery to provide evidence as to the claim that by giving Packingham Internet privileges, he would commit another crime. Justice Stephen Breyer added that “It seems to be well-settled law that the state can’t (bar usage) unless there is a 'clear and present danger'." === Opinion of the Court === In June 2017 the Supreme Court delivered a judgment in favor of Packingham, unanimously voting to reverse the state court's ruling. Justice Anthony Kennedy authored the decision, joined by Justice Ginsburg, Justice Breyer, Justice Sotomayor, and Justice Kagan. Kennedy explained the decision: "A fundamental principle of the First Amendment is that all persons have access to places where they can speak and listen, and then, after reflection, speak and listen once more." He continued that "By prohibiting sex offenders from using those websites, North Carolina with one broad stroke bars access to what for many are the principal sources for knowing current events, checking ads for employment, speaking and listening in the modern public square, and otherwise exploring the vast realms of human thought and knowledge." Citing Ashcroft v. Free Speech Coalition as a precedent, Kennedy also wrote: "It is well established that, as a general rule, the Government 'may not suppress lawful speech as the means to suppress unlawful speech'." === Concurring opinion === Justice Samuel Alito wrote an opinion concurring in the judgment, joined by John Roberts and Clarence Thomas. While Alito agreed that the state statute at issue violated the First Amendment, he noted that there are reasonable scenarios for which legal bans for sex offenders can be placed, such as for sites targeted at teenagers. Justice Gorsuch took no part in the decision of the case. == Impact == Packingham v. North Carolina was one of the first U.S. Supreme Court cases to ana

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