AI Email Helper

AI Email Helper — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Comparison gallery of image scaling algorithms

    Comparison gallery of image scaling algorithms

    This gallery shows the results of numerous image scaling algorithms. == Scaling methods == An image size can be changed in several ways. Consider resizing a 160x160 pixel photo to the following 40x40 pixel thumbnail and then scaling the thumbnail to a 160x160 pixel image. Also consider doubling the size of the following image containing text. == Examples of enlarged images == Below are examples of various images enlarged 4x using each scaling algorithm.

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  • Infone

    Infone

    Infone was a service launched by Metro One Telecommunications in 2003. The service was discontinued effective December 14, 2005. == How it worked == Infone included directory assistance and other services via a toll-free phone number. A user could call 888-411-1111 to request directory assistance, directions, traffic information, movie times, call completion, dinner reservation assistance and other services. Infone provided a number of innovative 411 'concierge'-like services, including movie listings from a live operator, and offered a feature where they could provide information from a linked Microsoft Outlook calendar when set up in advance. For a period of time they advertised heavily on U.S. television, featuring ads with then Governor of Minnesota Jesse Ventura, emphasizing their use of all U.S. based operators. The price offered was $0.89 per call up to 15 minutes (for use when the operator connects you to the requested number, as well as for additional information requests afterwards), with $0.05 for each additional minute, making Infone also a competitively priced long-distance service. New users received 5–10 free calls. Infone identified a registered user (along with billing information; the service was only payable by credit card) by caller ID (numbers were registered on signing up) and by an advanced voiceprint recognition system (VPRS) from SpeechWorks that identified the user when the user called from an unregistered telephone number (or no caller ID) through the use of a personal phrase spoken by the user (e.g., "Hello Infone!") after the welcome tone.

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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 signage

    Digital signage

    Digital signage is a segment of electronic signage that uses digital display technologies to present multimedia content in both public and private environments. Content may include video, images, text, or interactive media and is typically displayed for purposes such as advertising, information dissemination, branding, or entertainment. Digital signage systems can be either networked or standalone. Networked systems are managed through centralized content management systems (CMS), often cloud-based, enabling remote updates, scheduling, real-time data integration, and dynamic content delivery. These systems may also incorporate audience analytics, IoT sensors, or AI-driven personalization. Standalone systems, by contrast, operate without a network connection. They rely on local media playback via USB drives, SD cards, or internal storage. These solutions are simpler and suitable for locations where connectivity is limited or content changes infrequently. == Applications of digital signage == Digital signage is widely used in transportation hubs, retail stores, restaurants, corporate buildings, hotels, educational institutions, healthcare facilities, and public spaces. One prominent application of digital signage is Digital Out-of-Home (DOOH) advertising, which leverages digital signage displays in public spaces to deliver targeted advertisements to people outside of their homes. DOOH has become a significant segment of digital signage, providing advertisers with a dynamic and contextually relevant way to engage with audiences. == Components == === Hardware components === Digital signage hardware includes the physical equipment used to show multimedia content in public and private spaces. ==== Display devices ==== Display devices are the most prominent components of a digital signage system, serving as the primary medium for presenting content. Display devices come in various technologies, such as LCD, LED, and OLED formats, each offering different advantages in terms of clarity, color reproduction, and energy efficiency. In addition to flat-panel displays, projectors are also commonly used in digital signage, particularly in large-scale settings. Projectors can cast large-format visuals onto walls, screens, or other surfaces, providing flexibility in display size and positioning. Screen sizes vary widely to suit different applications. Smaller panels are often used in kiosks and point-of-sale systems, while larger displays, such as video walls and projection surfaces, are deployed in venues like stadiums, auditoriums, and other public spaces. Many digital signage displays are also equipped with touchscreen capabilities, allowing for interactive applications. These interactive displays are commonly used in information kiosks, wayfinding systems, and self-service applications. ==== Playback devices ==== Playback devices are specialized hardware components that manage the storage, processing, and transmission of multimedia content to digital signage displays and projectors. They serve as the crucial link between the content management system (CMS) and the visual output, ensuring seamless playback of static images, video files, animated graphics, and real-time content, such as news feeds. Playback devices can be standalone units or integrated into display hardware using System-on-Chip (SoC) technology. The latter reduces hardware complexity and installation time, making the system more efficient. These devices support remote or local content updates, allowing digital signage operators to manage networks effectively. Content can be updated via cloud-based platforms for centralized control or through direct interfaces on-site, depending on the system's configuration and deployment requirements. ==== Mounting systems ==== Mounting systems provide structural support for digital signage displays, enabling deployment across diverse environments. Typical configurations include wall mounts, ceiling mounts, and floor stands each engineered to meet specific spatial and functional requirements. === Software components === Digital signage software is responsible for content creation, scheduling, and management. It enables users to manage and distribute content to one or more playback devices. ==== Software compatibility ==== Digital signage software supports various operating systems, including Android, Windows, Linux, iOS, tvOS, webOS, Tizen, ChromeOS, macOS, and others. This allows customers to choose the hardware and software solution that best suits their digital signage needs. == Interactivity == Interactivity in digital signage allows users to interact directly with displays using input methods like touch, gestures, voice, or proximity sensors. This feature enables real-time responses and personalized content, improving the user experience. Interactive digital signage is commonly used in places like retail, transportation, education, and public spaces to create engaging and informative interactions. Additionally, self-service kiosks are often integrated into interactive signage solutions, allowing users to perform tasks such as ordering products, checking in for flights, accessing information, or making payments. These kiosks empower users to complete transactions or obtain services independently, improving efficiency and convenience in high-traffic locations. == Audience measurement and context-aware content adaptation == === Audience measurement === Cameras can be integrated into digital signage systems to enable audience measurement. They are used to detect and count viewers, estimate demographics such as age and gender, measure dwell time and attention, and sometimes analyze emotional reactions using computer vision techniques. This process is valuable for understanding audience behavior and refining business strategies. Privacy concerns are addressed by anonymizing collected data and avoiding the storage of personally identifiable information. === Context-aware digital signage === Context-aware digital signage refers to systems that adjust content based on environmental or audience data. The infrastructure supporting context awareness, including sensors and analytics systems, also facilitates the collection of audience insights. While these insights may be primarily used for reporting, optimization, or planning future campaigns rather than immediate content adjustments, they play a crucial role in the overall context-aware ecosystem. ==== Contextual information ==== Contextual information in the realm of context-aware digital signage refers to data about the environment, audience, and other factors that influence how digital signage content is displayed. This information helps the system to deliver more relevant, timely, and personalized content to its audience. Contextual information can include, but is not limited to: Audience demographics — this can involve detecting the age, gender, or even emotional state of viewers through cameras or sensors. It helps tailor content to specific audience segments, improving engagement. Time and weather — the system may adjust content based on the time of day or current weather conditions. For example, weather-appropriate content (like a raincoat ad on a rainy day) or time-specific content (like dinner menu promotions in the evening) can be shown. Emergency information — in situations of emergency, systems can prioritize displaying urgent notifications such as fire alerts, disaster warnings, or evacuation instructions. This can be crucial for public safety in crowded environments or densely populated areas. The system may adapt content in real-time to inform and guide individuals to safety, offering location-specific instructions or emergency service contacts. == Challenges == === Display blindness === Digital signage in public spaces has been found to lose visibility, significantly diminishing its ability to capture attention. This issue, known as "Display Blindness", was identified by Müller et al. and refers to the phenomenon where digital advertisements are largely overlooked by passersby. Observations indicate that many of these advertisements fail to resonate with their audience, often being irrelevant or unengaging, which leads to passive reception and reduced interaction. == Comparison with print signage == Digital signage and traditional print signage serve similar purposes by delivering visual information to a target audience, but they differ significantly in terms of flexibility, cost, maintenance, and environmental impact. Digital signage is advantageous in low-light or nighttime environments, where its internal illumination ensures visibility without the need for external lighting, unlike printed signs, which may require additional fixtures to be seen after dark. === Content and flexibility === Digital signage allows for dynamic and real-time content updates, often controlled remotely through content management systems. This makes it well-suited for environments where information chan

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  • Distributed manufacturing

    Distributed manufacturing

    Distributed manufacturing, also known as distributed production, cloud producing, distributed digital manufacturing, and local manufacturing, is a form of decentralized manufacturing practiced by enterprises using a network of geographically dispersed manufacturing facilities that are coordinated using information technology. It can also refer to local manufacture via the historic cottage industry model, or manufacturing that takes place in the homes of consumers. == Enterprise == In enterprise environments, the primary attribute of distributed manufacturing is the ability to create value at geographically dispersed locations. For example, shipping costs could be minimized when products are built geographically close to their intended markets. Also, products manufactured in a number of small facilities distributed over a wide area can be customized with details adapted to individual or regional tastes. Manufacturing components in different physical locations and then managing the supply chain to bring them together for final assembly of a product is also considered a form of distributed manufacturing. Digital networks combined with additive manufacturing allow companies a decentralized and geographically independent distributed production (cloud manufacturing). == Consumer == Within the maker movement and DIY culture, small scale production by consumers often using peer-to-peer resources is being referred to as distributed manufacturing. Consumers download digital designs from an open design repository website like Youmagine or Thingiverse and produce a product for low costs through a distributed network of 3D printing services such as 3D Hubs, Geomiq. In the most distributed form of distributed manufacturing the consumer becomes a prosumer and manufacturers products at home with an open-source 3-D printer such as the RepRap. In 2013 a desktop 3-D printer could be economically justified as a personal product fabricator and the number of free and open hardware designs were growing exponentially. Today there are millions of open hardware product designs at hundreds of repositories and there is some evidence consumers are 3-D printing to save money. For example, 2017 case studies probed the quality of: (1) six common complex toys; (2) Lego blocks; and (3) the customizability of open source board games and found that all filaments analyzed saved the prosumer over 75% of the cost of commercially available true alternative toys and over 90% for recyclebot filament. Overall, these results indicate a single 3D printing repository, MyMiniFactory, is saving consumers well over $60 million/year in offset purchases of only toys. These 3-D printers can now be used to make sophisticated high-value products like scientific instruments. Similarly, a study in 2022 found that 81% of open source designs provided economic savings and the total savings for the 3D printing community is more than $35 million from downloading only the top 100 products at YouMagine. In general, the savings are largest when compared to conventional products when prosumers use recycled materials in 'distributed recycling and additive manufacturing' (DRAM). == Emergency Distributed Manufacturing During COVID-19 Pandemic == Distributed manufacturing became far more visible during the COVID-19 pandemic because it offered a practical response to the breakdown of centralized global supply chains. As lock downs, border restrictions, and factory shutdowns disrupted conventional production, decentralized networks using local facilities such as Open Source Medical Supplies stepped in and manufactured over 48 million products. Additive manufacturing /3D printing were used to produce urgently needed items such as face shields, ventilators and their components, nasopharyngeal swabs, and other personal protective equipment. This demonstrated that distributed manufacturing could reduce lead times, improve responsiveness, and lessen dependence on distant suppliers during crisis conditions for a wide range of products. Peer-reviewed studies on pandemic-era manufacturing note that additive manufacturing was especially valuable because digital design files could be shared rapidly and produced close to the point of need, enabling hospitals, universities, small firms, and maker communities to supplement strained medical supply chains. The pandemic also helped shift distributed manufacturing from being seen as a niche or experimental model to a credible strategy for resilience, flexibility, and emergency response. At the same time, scholars caution that its wider adoption depends on solving issues related to quality assurance, regulation, material consistency, and coordination across distributed production sites. Overall, COVID-19 popularized distributed manufacturing by showing that localized, digitally enabled production could complement traditional manufacturing systems when speed, adaptability, and supply-chain resilience were critical. == Social change == Some call attention to the conjunction of commons-based peer production with distributed manufacturing techniques. The self-reinforced fantasy of a system of eternal growth can be overcome with the development of economies of scope, and here, the civil society can play an important role contributing to the raising of the whole productive structure to a higher plateau of more sustainable and customised productivity. Further, it is true that many issues, problems and threats rise due to the large democratization of the means of production, and especially regarding the physical ones. For instance, the recyclability of advanced nanomaterials is still questioned; weapons manufacturing could become easier; not to mention the implications on counterfeiting and on "intellectual property". It might be maintained that in contrast to the industrial paradigm whose competitive dynamics were about economies of scale, commons-based peer production and distributed manufacturing could develop economies of scope. While the advantages of scale rest on cheap global transportation, the economies of scope share infrastructure costs (intangible and tangible productive resources), taking advantage of the capabilities of the fabrication tools. And following Neil Gershenfeld in that "some of the least developed parts of the world need some of the most advanced technologies", commons-based peer production and distributed manufacturing may offer the necessary tools for thinking globally but act locally in response to certain problems and needs. As well as supporting individual personal manufacturing social and economic benefits are expected to result from the development of local production economies. In particular, the humanitarian and development sector are becoming increasingly interested in how distributed manufacturing can overcome the supply chain challenges of last mile distribution. Further, distributed manufacturing has been proposed as a key element in the Cosmopolitan localism or cosmolocalism framework to reconfigure production by prioritizing socio-ecological well-being over corporate profits, over-production and excess consumption. == Technology == By localizing manufacturing, distributed manufacturing may enable a balance between two opposite extreme qualities in technology development: Low technology and High tech. This balance is understood as an inclusive middle, a "mid-tech", that may go beyond the two polarities, incorporating them into a higher synthesis. Thus, in such an approach, low-tech and high-tech stop being mutually exclusive. They instead become a dialectic totality. Mid-tech may be abbreviated to "both…and…" instead of "neither…nor…". Mid-tech combines the efficiency and versatility of digital/automated technology with low-tech's potential for autonomy and resilience. == Contracting in Distributed Manufacturing == Research into contracting and order processing models tailored for distributed manufacturing has highlighted the need for flexible, role-based frameworks and advanced digital tools. These tools and frameworks are essential for addressing issues related to quality assurance, payment structures, legal compliance, and coordination among multiple actors. By addressing these challenges, contracting models for distributed manufacturing can unlock its potential for more localized, efficient, and sustainable production systems. A system prototype has been developed to simplify contracting for distributed manufacturing. This tool allows buyers to manage orders across multiple manufacturers using a single interface, automating workflows to ensure clarity and accountability for everyone involved. This research was led by the Internet of Production, as part of the mAkE project (African European Maker Innovation Ecosystem), funded by the European Horizon 2020 research and innovation programme.

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  • Bluelight (web forum)

    Bluelight (web forum)

    Bluelight is a web-forum, research portal, online community, and non-profit organisation dedicated to harm reduction in drug use. Its userbase includes current and former substance users, academic researchers, drug policy activists, and mental health advocates. It is believed to be the largest online international drug discussion website in the world. As of November 2025, the website claims over 475,900 registered members, the Discord community claims over 11,900 members, and additional members utilise other platforms such as Telegram. Bluelight has been utilised by academic researchers as a primary source of data in numerous publications. Researchers also utilise the site to advertise research studies, recruit study participants, and better understand the world of substance use. Research groups and organisations that have partnered with Bluelight to recruit study participants include Imperial College London, Johns Hopkins University, Health Canada, Karlstad University, Curtin University, Macquarie University, Columbia University, University of Pennsylvania, University of Michigan, Toronto Metropolitan University (then known as Ryerson University), and MAPS. Researchers have found that the most common reasons for substance users to visit Bluelight.org and similar online communities are to learn "how to use drugs safely" and "how to help others use drugs safely." Bluelight neither condemns or condones drug use, instead advocating for the principle of responsible drug use; educating and allowing individuals to make informed decisions regarding their drug use, providing information on local drug misuse services, and providing them with other drug harm reduction resources and public safety notices. == History == Bluelight.org was originally formed in 1997 as a message board on bluelight.net called the MDMA Clearinghouse. The board was created as a side project by the owner of West Palm Beach design company Bluelight Designs. 200–300 users joined the site between 1998 and 1999, but the site's servers were heavily limited and could only store a few threads at a time; this led to the creation of 'The New Bluelight' forum in May 1999 and the registration of the bluelight.nu domain in June 1999. The site began to explode in popularity in the early 2000s with the rise of MDMA in the club scene, amassing nearly 7,000 members by the year 2000 and 59,000 by the start of 2006. The site switched to the bluelight.ru domain in October 2005, and switched again to bluelight.org in January 2014. In early 2024, Bluelight was re-structured and the forum became a subsidiary of the newly formed Australian non-profit organisation & registered charity Bluelight Communities Ltd. == Partnerships == In the early 2000s, Bluelight worked with reagent test supplier EZ-Test to promote the sale of drug checking kits. In 2007, Bluelight partnered with the Multidisciplinary Association for Psychedelic Studies (MAPS), a non-profit organisation working to raise awareness and understanding of psychedelic drugs through education, clinical research, and advocacy. MAPS utilised Bluelight to recruit participants for its first MDMA-assisted psychotherapy trial for PTSD. In 2013, the official MAPS forums were migrated to Bluelight. Bluelight's other partners include Erowid, a non-profit organisation dedicated to education surrounding psychoactive drugs; TripSit, a harm reduction education website; Pill Reports, a web-based database for drug checking results that was initially formed as an offshoot of the site; and the Global Drug Survey, an independent research organisation focused on collecting data about substance use. == Notable users == Alan Woods – funded the site's maintenance costs from 1999 until his death in 2008 Hamilton Morris John McAfee – created an infamous series of troll posts about the stimulant MDPV

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  • G7 Rapid Response Mechanism

    G7 Rapid Response Mechanism

    The G7 Rapid Response Mechanism (RRM) is an initiative introduced in the "Charlevoix Commitment on Defending Democracy from Foreign Threats", issued by the leaders of the Group of Seven (G7) countries—United States, Canada, Japan, United Kingdom, France, Germany and Italy—on June 9, 2018, during their summit in Charlevoix, Quebec. The RRM's mandate is to strengthen the coordination of G7 member countries, as well as "to identify and respond to diverse and evolving threats to our democracies, including through sharing information and analysis, and identifying opportunities for coordinated response" The G7 is an informal international intergovernmental economic organization that meets annually, whose members represent the seven wealthiest advanced economies in the world, as measured by the International Monetary Fund (IMF). == Constituents == The following countries and organisations are members and observers (associate members) of the G7 Rapid Response Mechanism: Australia Canada France Germany Italy Japan Netherlands New Zealand Poland Sweden United Kingdom United States European Union North Atlantic Treaty Organization == Mandate == The RRM was mandated to "strengthen coordination to prevent, thwart and respond to malign and evolving threats to G7 democracies." It "will share information and threat analysis related to various threats to democracy, and is an established mechanism to identify opportunities for coordinated response." According to the Institute for Research on Public Policy's Policy Options magazine, the "RRM initiative seeks to strengthen the leading democracies' coordination to identify and respond to diverse and evolving threats…including through sharing information and analysis, and identifying opportunities for a coordinated response." == Administration == The RRM initiative is led by Canada through Global Affairs Canada's Centre for International Digital Policy. Tara Denham, Director of the Centre for International Digital Policy at Global Affairs Canada, directed the team responsible for setting up the RRM Coordination Unit. Global Affairs Canada—the Department of Foreign Affairs, Trade and Development—is the federal Canadian ministry responsible for diplomatic and consular relations, international trade, and international development and humanitarian assistance. The Centre for International Digital Policy includes the Digital Inclusion Lab and the RRM. Denham is also the RRM's Canadian Focal Point. At a briefing on "the security and intelligence threats to elections" of the House of Commons Standing Committee on Access to Information, Privacy and Ethics, the chair Bob Zimmer (CPC), said that the 2019 general election "may be different" from past elections in Canada. as the "tools that were used to strengthen civic engagement are being used to undermine, disrupt and destabilize democracy." "Democracies around the world have entered a new era—an era of heightened threat and heightened vigilance—and 2019 will see a number of countries brace for volleys of attempted disruption: India, Australia, Ukraine, Switzerland, Belgium, the EU and, of course, Canada. Evidence has confirmed that the most recent Canadian general election, in 2015, was unencumbered by interference, although there were some relatively primitive attempts to disrupt, misinform and divide. These efforts were few in number and uncoordinated, and had no visible impact on the voter, either online or in line." Zimmer described the initiative's three pillars. "enhancing citizen preparedness" through the "digital citizen initiative" "improving organizational readiness" with national security and intelligence agencies supporting Elections Canada "ensure a comprehensive understanding of and response to any threats to Canada's democratic process." by establishing the Security and Intelligence Threats to Elections Task Force (SITE) which works as a team with the Communications Security Establishment (CSE), the Canadian Security Intelligence Service (CSIS), the Royal Canadian Mounted Police (RCMP), as well as Global Affairs Canada Zimmer said that as part of the third pillar, "We have activated the G7 rapid response mechanism, announced at the G7 leaders' summit in Charlevoix, to strengthen coordination among our G7 allies and to ensure that there is international collaboration and coordination in responding to foreign threats to democracy." == Background == === Charlevoix summit === The G7 met from June 8 to 9, 2018 during their summit at the Manoir Richelieu in Charlevoix, in La Malbaie, Quebec. The Charlevoix Summit was the 44th G7 summit. The group issued eight "Commitments" at the summit. They included: Commitment on Defending Democracy from Foreign Threats Commitment on Equality and Economic Growth Commitment to End Sexual and Gender-Based Violence, Abuse and Harassment in Digital Contexts Declaration on Quality Education for Girls, Adolescent Girls and Women in Developing Countries Commitment on Innovative Financing for Development. Prime Minister Justin Trudeau announced five themes for Canada's G7 presidency which began in January 2018. === Defending Democracy from Foreign Threats === "We commit to take concerted action in responding to foreign actors who seek to undermine our democratic societies and institutions, our electoral processes, our sovereignty and our security as outlined in the Charlevoix Commitment on Defending Democracy from Foreign Threats. We recognize that such threats, particularly those originating from state actors, are not just threats to G7 nations, but to international peace and security and the rules-based international order. We call on others to join us in addressing these growing threats by increasing the resilience and security of our institutions, economies and societies, and by taking concerted action to identify and hold to account those who would do us harm." They committed to "cooperate in defending democracies from foreign threats and establish a response mechanism for that purpose". "Democracy and the rules-based international order are increasingly being challenged by authoritarianism and the defiance of international norms. In particular, foreign actors seek to undermine our democratic societies and institutions, our electoral processes, our sovereignty and our security. These malicious, multi-faceted and ever-evolving tactics constitute a serious strategic threat which we commit to confront together, working with other governments that share our democratic values." The Charlevoix Commitment states that "foreign actors seek to undermine our democratic societies and institutions, our electoral processes, our sovereignty and our security. These malicious, multi-faceted and ever-evolving tactics constitute a serious strategic threat which we commit to confront together, working together with other governments that share our democratic values." The Charlevoix Summit resolved to "establish a G7 Rapid Response Mechanism to strengthen our coordination to identify and respond to diverse and evolving threats to our democracies, including through sharing information and analysis, and identifying opportunities for coordinated response." == Monitored elections == === 2019 European Parliament election === RRM Canada's comprehensive report on the 2019 European Parliament election analyzed open data "related to foreign interference during and leading up to the 2019 European Union Parliamentary Elections, May 23–26, 2019". RRM Canada did not find "significant evidence of state-based foreign interference, or any large-scale, organized and coordinated efforts by non-state actors". They did find that "national or international non-state actors" used tactics based on those used by the Russian sponsored Internet Research Agency (IRA) in previous elections, "such as the 2016 U.S. Elections". For example, blogs, webpages, and social media accounts on Twitter, Facebook and Reddit "were used to spread divisive and false information to damage and negatively impact social cohesion and trust in democratic processes and institutions" in coordinated networks of Facebook groups. === 2019 Alberta general election === RRM Canada's analyz report on the 2019 Alberta general election was intended to "identify any emerging tactics in foreign interference and draw lessons learned for the Canadian general elections scheduled to take place in October 2019." No foreign activity was detected, although the data revealed ""suspicious account creation pattern that is indicative of troll or bot activity". They found "automated inauthentic behaviour and trolling activities" but concluded that they were "very likely domestic". The data showed "suspicious account creation pattern that is indicative of troll or bot activity", and "spikes in account creation" which suggested the "presence of accounts developed for a specific purpose." The accounts were very likely domestic and were "mainly comprised of supporters of the United Conservative Party (UCP)." A seco

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  • Creepiness

    Creepiness

    Creepiness is the state of being creepy, or causing an unpleasant feeling of fear or unease to someone and/or something. Certain traits or hobbies may make people seem creepy to others; interest in horror or the macabre might come across as 'creepy', and often people who are perverted or exhibit predatory behavior are called 'creeps'. The internet, especially some functions of social media, has been described as increasingly creepy. Adam Kotsko has compared the modern conception of creepiness to the Freudian concept of unheimlich. The term has also been used to describe paranormal or supernatural phenomena. Some people have phobias which are irrational fears, which can make them perceive something as creepy. == History and studies == "Creepiness" is subjective: for example some dolls have been described as creepy, while what makes something "creepy" or "strange" to someone might seem normal to someone else. The adjective "creepy", referring to a feeling of creeping in the flesh, was first used in 1831, but it was Charles Dickens who coined and popularized the term "the creeps" in his 1849 novel David Copperfield. In the 20th century, association was made between involuntary celibacy and creepiness. The concept of creepiness has only recently been formally addressed in social media marketing. The sensation of creepiness has only recently been the subject of psychological research, despite the widespread colloquial use of the word throughout the years. Francis T. McAndrew of Knox College is the first psychologist to do an empirical study on creepiness. == Causes == The state of creepiness has been associated with "feeling scared, nervous, anxious or worried", "awkward or uncomfortable", "vulnerable or violated" in a study conducted by Watt et al. This state arises in the presence of a creepy element, which can be an individual or, as recently observed, new technologies. === Individuals === Creepiness can be caused by the appearance of an individual. Another study investigated the characteristics that make people creepy. Creepy people were thought to be more often male than female by an overwhelming majority of participants (around 95% of both male and female participants). Another study conducted by Watt et al. also found that participants associated the ectomorphic body type (more linear) with creepiness, more than the other two body types (51% vs mesomorphic, 24% and endomorphic, 23%). Other cues of creepiness included low hygiene, especially according to female participants, and a disheveled appearance. Participants also identified the face as an area with potentially creepy features: in particular the eyes and the teeth. Both of those physical features were deemed creepy not only for their unpleasant appearance (ex. squinty eyes or crooked teeth) but also for the movements and expressions they engaged it (ex. darting eye movements and odd smiles). In fact, appearance does not seem to be the only factor making an individual creepy: behaviors provide cues as well. Behaviors such as "being unusually quiet and staring (34%), following or lurking (15%), behaving abnormally (21%), or in a socially awkward, "sketchy" or suspicious way (20%)" are all contributing to a feeling of creepiness, as described by Watt et al.'s study. === Technology === In addition to other individuals, new technologies, such as marketing's targeted ads and AI, have been qualified as creepy. A study by Moore et al. described what aspect of marketing participants considered creepy. The main three reasons are the following: using invasive tactics, causing discomfort and violating of norms. Invasive tactics are practiced by marketers that know so much about the consumer that the ads are "creepily" personalized. Secondly, some ads create discomfort by making the consumer question "the motives of the company advertising the product". Finally, some ads violate social norms by having inappropriate content, for example by unnecessarily sexualizing it. It is marketing's extensive knowledge used in an improper way, together with a certain loss of control over our data, that creates a feeling of creepiness. Another creepy aspect of technology is human-looking AI: this phenomenon is called the uncanny valley. Humans find robots creepy when they start closely resembling humans. It has been hypothesized that the reason why they are viewed as creepy is because they violate our notion of how a robot should look. A study focusing on children's responses to this phenomenon found evidence to support the hypothesis. == Evolutionary explanation == Several studies have hypothesized that creepiness is an evolutionary response to potentially dangerous situations. It could be linked to a mechanism called agent detection which makes individuals expect malignant agents to be responsible for small changes in the environment. McAndrew et al. illustrates the idea with the example of a person hearing some noises while walking in a dark alley. That person would go in high alert, fearing that some dangerous individual was there. If that was not the case the loss would be small. If, on the other hand, a dangerous individual was actually in the alley and the person had not been alerted by this creepy feeling, the loss could have been significant. Creepiness would therefore serve the purpose of alerting us in situations in which the danger is not outright obvious but rather ambiguous. In this case, ambiguity both refers to the possible presence of a threat and to its nature, sexual or physical for example. Creepiness "may reside in between the unknowing and the fear" in the sense that individuals experiencing it are unsure if there truly is something to fear or not. Creepy characteristics are not simply caused by threat potential: in fact, ectomorphic body types are not the most powerful bodies and facial expressions are not a proxy of physical strength either. Therefore, creepiness is not only related to how threatening a characteristic is, in the sense of how dangerous and strong the individual can be. There are more facets to consider. Another characteristic of creepiness is unpredictable behavior. Unpredictability links back to this idea of ambiguity. When an individual is unpredictable it is not possible to tell when their behavior will turn violent: this adds to the ambiguity of a potentially dangerous situation. This theory is endorsed by studies. Not only is unpredictability directly listed as a creepy characteristic, but other behaviors, such as norm-breaking behaviors are indirectly linked with unpredictability. Such behaviors show that the individual does not conform to some social standards others would expect in a given situation. For example, the aforementioned staring at strangers or lack of hygiene—behaviors that make us uneasy or creeped out because they do not fit the norm and therefore are not expected. More generally, participants tended to define creepiness as "different" in the sense of not behaving, or looking, socially acceptable. Such differences point towards a "social mismatch". Humans have a natural system of detection of such mismatch: a physical feeling of coldness. When an individual is creeped out, they report feeling those "cold chills". This phenomenon has been studied by Leander et al, with relation to nonverbal mimicry in social interactions, meaning the unintentional copying of another's behavior. Inappropriate mimicry may leave a person feeling like something is off about the other. Absence of non-verbal mimicry in a friendly interaction, or the presence of it in a professional setting, raises suspicion as it does not follow the relevant social norms. Individuals are left wondering what other unusual behavior the other might engage in.

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  • List of data science software

    List of data science software

    This is a list of data science software and platforms used in data science, which includes programming languages, programming environments, machine learning frameworks, data engineering tools, statistical software, data analysis, plotting, MLOps systems, and more. == Programming languages == == Development environments == These interactive notebooks, IDEs, and platforms provide specialised development environments. Apache Zeppelin Architect — Eclipse (software) CoCalc Dataiku Data Science Studio FreeMat GNU Octave Google Colab DataSpell Jupyter Notebook / JupyterLab Kaggle Notebooks MATLAB O-Matrix PyCharm RStudio SAS (software) and SAS Studio Spyder Visual Studio Code == Machine and deep learning software == The Machine learning / deep learning tools support development in those fields. == Data engineering == Examples of Data engineering tools. Apache Airflow Apache Flink Apache Hadoop Apache Kafka Apache NiFi Apache Spark Dask Data build tool (dbt) == Data mining == Examples of Data mining tools. === Free and open-source === === Proprietary === == Database management == === List of RDBMS === ==== Proprietary ==== == Data warehouses == Data warehouse environments include: Amazon Redshift Snowflake Google BigQuery Microsoft Azure Synapse Teradata Vertica == Data lakes == Data lake environments include: Apache Hadoop Cloudera Databricks Delta Lake Amazon S3 Google Cloud Storage Azure Data Lake == Algorithms == Apriori algorithm – frequent itemset mining and association rule learning in market basket analysis Backpropagation – algorithm for training artificial neural networks using gradient descent Decision Trees – tree-based algorithm for classification and regression Expectation–maximization algorithm – iterative procedure for maximum likelihood estimation with latent variables Gradient descent – iterative optimization algorithm for minimizing a loss function ID3 algorithm – used to generate a decision tree from a dataset K-Means – clustering algorithm based on minimizing within-cluster distances K-Nearest Neighbors (KNN) – instance-based learning and classification method Linear regression – estimation method for predicting a dependent variable based on independent variables Logistic regression – classification algorithm for predicting a binary outcome Naive Bayes – probabilistic classifier based on Bayes' theorem Ordinary least squares – estimation method for parameters in linear regression PageRank – graph-based algorithm for link analysis and search ranking Principal component analysis – technique to reduce high-dimensional data while preserving variance Q-learning – reinforcement learning algorithm for learning optimal actions Random forest – ensemble of decision trees for improved classification or regression Sequential minimal optimization – solver for training support vector machines Stochastic gradient descent – randomized variant of gradient descent for large-scale machine learning Support Vector Machines (SVM) – algorithm for finding a hyperplane to separate classes == Statistical software == === Open-source === === Public domain === CSPro Dataplot Epi Map X-13ARIMA-SEATS === Freeware === BV4.1 MINUIT WinBUGS Winpepi === Proprietary === == Data processing == Tools for Data processing and analysis: == Data and information visualization == Software for Data visualization: == Plotting software == Software for plotting data to support processing and visualise results. == Maps and geospatial visualization == ArcGIS Carto Epi Map GeoDA Google Earth Engine Leaflet Mapbox MountainsMap QGIS == Machine learning == MLOps and model deployment: BentoML Data Version Control (DVC) Kubeflow MLflow Seldon Core Streamlit TensorFlow Serving Weights & Biases == Data repositories == Kaggle – platform for data science competitions, datasets, and notebooks. OpenML – collaborative platform for sharing datasets, algorithms, and experiments. University of California, Irvine Machine Learning Repository Zenodo – open-access repository supported by CERN and the EU. == Educational data science software == Kaggle – online platform for data science education, competitions, datasets, and collaborative learning. KNIME – open-source data analytics platform used for teaching data science, machine learning, and workflow-based analysis. RapidMiner – used in academic research and education for data mining and machine learning. Statistics Online Computational Resource (SOCR) – online tools and instructional resources for statistics education. Tanagra (machine learning) – data mining software developed for research and teaching purposes. TinkerPlots – explore and analyze data through visual modeling.

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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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  • Key & See

    Key & See

    Key & See is a variation of the TV Key service that forms part of the open, standards-based interactive TV services platform provided by Miniweb Interactive. Key & See allows viewers to access the interactive TV content made available by broadcasters and channel owners while leaving quarter of their screen tuned to the programme they are already watching Like TV Key, Key & See can be used with interactive TV services on UK satellite TV provider Sky Digital (BSkyB) Key & See works in the same way as a TV Key but the numeric shortcut code is associated with a broadcaster and a particular TV channel or programme. Miniweb Interactive offers commercial brands and broadcasters the chance to utilise TV Key and Key & See technology as part of its interactive TV services platform

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  • News ticker

    News ticker

    A news ticker (sometimes called a crawler, crawl, slide, zipper, ticker tape, or chyron) is a horizontal or vertical (depending on the language's writing system) text-based display either in the form of a graphic that typically resides in the lower third of the screen space on a television station or network (usually during news programming) or as a long, thin scoreboard-style display seen around the facades of some offices or public buildings dedicated to presenting headlines or minor pieces of news. It is an evolution of the paper strips tapes, a continuous paper print-out of stock quotes from a printing telegraph which was mainly used to transmit companies' share price information over telegraph lines before the advance of technology in the 1960s. News tickers have been used in Europe in countries such as United Kingdom, Germany and Ireland for some years; they are also used in several Asian countries and Australia. In the United States, tickers were long used on a special event basis by broadcast television stations to disseminate weather warnings, school closings, and election results. Sports telecasts occasionally used a ticker to update other contests in progress before the expansion of cable news networks and the internet for news content. In addition, some ticker displays are used to relay continuous business and financial information. Most tickers are traditionally displayed in the form of scrolling text running from right to left across the screen or building display (or in the opposite direction for right-to-left writing systems such as Arabic script and Hebrew), allowing for headlines of varying degrees of detail; some used by television broadcasters, however, display stories in a static manner (allowing for the seamless switching of each story individually programmed for display) or utilize a "flipping" effect (in which each individual headline is shown for a few seconds before transitioning to the next, instead of scrolling across the screen, usually resulting in a relatively quicker run through of all of the information programmed into the ticker). Since the growth in usage of the World Wide Web, some news tickers have syndicated news stories posted largely on websites of broadcasters or by other independent news agencies. == Current uses == === Television === The presentation of headlines or other information in a news ticker has become a common element of many different news networks. The use of the ticker has differed on a number of channels: News networks and local newscasts commonly use a setup in which news headlines are scrolled across an area near the bottom of the screen, though some variations have formed, such as showing one headline at a time with a scrolling or "flipper" effect. Financial news channels use two or more tickers displaying company shares prices and business headlines. Networks with a focus on sports often use a slightly different system, where scores and statuses of ongoing and finished games are displayed one by one, along with minor sports highlights, statistics and sports news headlines. They are typically divided into categories devoted to specific leagues and events (with college basketball and football usually focusing on the top 25 ranked teams on the AP Poll, occasionally supplemented by sections for specific conferences). Some programs, including news-based programs emphasizing viewer interactivity, or special events, may also use tickers to display messages and reactions from viewers and others that relate to the program. These comments are often sourced from social networking services such as Facebook and Twitter, typically curating comments from a specific page or hashtag. Due to their current prevalence, they have been occasionally been made targets of pranks and vandalism. In one such example, News 14 Carolina allowed viewers to submit relevant information such as school closings or traffic delays via telephone or the Internet that would be incorporated into the ticker; the system was exploited in February 2004 to display humorous and crude messages, including the infamous "All your base are belong to us". Occasionally messages intended for training accidentally end up being put on the live ticker as happened on BBC News in 2022 when "Weather rain everywhere" and "Manchester United are rubbish" appeared on the live news ticker. Some businesses and organizations have utilized tickers intended for relaying weather-related closings as a surreptitious source for free guerrilla marketing, proclaiming they were open rather than closed and giving their phone number if possible, allowing them to 'advertise' on a television station all day for free. Since then, many stations have required pre-registration of businesses or organizations with an authorized representative and a signed affidavit on company letterhead affirming their authenticity, along with filtering out unfamiliar businesses and organizations, before being able to display their closing announcements. Stations also confirm all closings involving school districts with authorized officials to prevent situations in which students either show up to canceled classes in dangerous conditions, or do not attend school due to an erroneous, prank-submitted, or false listing. === On personal computers === Various applications have been developed over time to install news tickers on personal computer desktops using RSS feeds from news organizations, which are displayed in a fashion similar to those used by television channels but enable the user to access to underlying news stories, a feature not offered by traditional television channels. The Bloomberg Terminal and other financial information-tracking programs and devices also utilize tickers. A ticker may also be used as an unobtrusive method by businesses in order to deliver important information to their staff. The ticker can be set to reappear, stay on screen, or be put into a retractable mode (where a small tab is left visible on-screen). In the United Kingdom, broadcasters have stopped using this technology as other forms of communications have become available and increased in popularity. BBC News and Sky News discontinued their respective desktop tickers in March 2011 and 2012 to focus on other products, such as smartphone applications, to deliver updated information on breaking news and sport stories. === News tickers on buildings === Since the advent of the telegraph, newspapers commonly used their buildings to share the latest headlines. At first simple chalkboard signs were used for bulletins, but limelight illumination, electric lights, magic lantern projections, and other novel techniques were later employed. The method of using electric lights to spell out moving letters was invented by Frank C. Reilly (August 20, 1888 – April 10, 1947) and patented in 1923. Reilly called his invention the Motograph News Bulletin. In 1928, The New York Times installed a Motograph News Bulletin to display news headlines on the sides of Times Tower. The display was 388 feet (118 m) long, 5 feet (1.5 m) high, and employed over 14,800 light bulbs. Popularly known as the "Zipper", the sign remained in use until the building was sold in 1961. The sign was darkened during World War II to comply with wartime lighting restrictions. The Motograph operated until 1994 and was replaced by an electronic version in 1995, which was in turn removed in 2017 due to the replacement of all individual screens on the front of One Times Square with a 350 foot (110 m)-tall LED billboard in 2018. Ticker displays appear today on the exterior of the News Corp Building, which houses the headquarters for Fox News Channel/News Corp in the west extension of Manhattan's Rockefeller Center, as well as one that displays delayed stock market data that is located in Times Square. NASDAQ itself features a large display screen on the facade of the NASDAQ MarketSite building in Times Square. The Reuters buildings at Canary Wharf and in Toronto have news and stock tickers; the latter type features market data for the New York Stock Exchange, NASDAQ and London Stock Exchange, while the Toronto building's ticker also includes quotes from the Toronto Stock Exchange. A red-LED ticker was added to the perimeter of 10 Rockefeller Center in 1994, as the building was being renovated to accommodate the studios for NBC's Today. Placed at the juncture of the first and second floors, the ticker is visible to spectators in Rockefeller Plaza and passersby on West 49th Street and updates continuously, even at times when Today is not being produced and broadcast. As of 2015, the ticker strip is only a small part of a large two-floor LCD video display that is placed within the window of the studio showing promotional information. The Martin Place Headquarters of Seven News, the news division of Australian television broadcaster Seven Network, also incorporates a ticker that wraps around the building. == In popular culture == The use of new

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  • Visual hull

    Visual hull

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

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  • Algorithmic radicalization

    Algorithmic radicalization

    Algorithmic radicalization is the concept that recommender algorithms on popular social media sites, such as YouTube and Facebook, drive users toward progressively more extreme content over time, leading to the development of radicalized extremist political views. Algorithms meticulously record user interactions, encompassing likes, dislikes and the duration of time watching content, with the objective of generating an endless stream of media designed to sustain user engagement. The phenomenon of echo chamber channels has been demonstrated to exacerbate the polarization of consumers, primarily through the reinforcement of media preferences and the validation of one's existing beliefs. Algorithmic radicalization remains a controversial phenomenon as it is often not in the best interest of social media companies to remove echo chamber channels. To what extent recommender algorithms are actually responsible for radicalization remains disputed. Studies have found contradictory results regarding the promotion of extremist content by algorithms. == Social media echo chambers and filter bubbles == Social media platforms learn the interests and likes of the user to modify their experiences in their feed to keep them engaged and scrolling, known as a filter bubble. An echo chamber is formed when users come across beliefs that magnify or reinforce their thoughts and form a group of like-minded users in a closed system. Echo chambers spread information without any opposing beliefs and can possibly lead to confirmation bias. According to group polarization theory, an echo chamber can potentially lead users and groups towards more extreme radicalized positions. According to the National Library of Medicine, "Users online tend to prefer information adhering to their worldviews, ignore dissenting information, and form polarized groups around shared narratives. Furthermore, when polarization is high, misinformation quickly proliferates." == By site == === Facebook === Facebook's algorithm focuses on recommending content that makes the user want to interact. They rank content by prioritizing popular posts by friends, viral content, and sometimes divisive content. Each feed is personalized to the user's specific interests which can sometimes lead users towards an echo chamber of troublesome content. Users can find their list of interests the algorithm uses by going to the "Your ad Preferences" page. According to a Pew Research study, 74% of Facebook users did not know that list existed until they were directed towards that page in the study. It is also relatively common for Facebook to assign political labels to their users. In recent years, Facebook has started using artificial intelligence to change the content users see in their feed and what is recommended to them. A document known as The Facebook Files has revealed that their AI system prioritizes user engagement over everything else. The Facebook Files has also demonstrated that controlling the AI systems has proven difficult to handle. In an August 2019 internal memo leaked in 2021, Facebook has admitted that "the mechanics of our platforms are not neutral", concluding that in order to reach maximum profits, optimization for engagement is necessary. In order to increase engagement, algorithms have found that hate, misinformation, and politics are instrumental for app activity. As referenced in the memo, "The more incendiary the material, the more it keeps users engaged, the more it is boosted by the algorithm." According to a 2018 study, "false rumors spread faster and wider than true information... They found falsehoods are 70% more likely to be retweeted on Twitter than the truth, and reach their first 1,500 people six times faster. This effect is more pronounced with political news than other categories." === YouTube === YouTube has been around since 2005 and has more than 2.5 billion monthly users. YouTube discovery content systems focus on the user's personal activity (watched, favorites, likes) to direct them to recommended content. YouTube's algorithm is accountable for roughly 70% of users' recommended videos and what drives people to watch certain content. According to a 2022 study by the Mozilla Foundation, users have little power to keep unsolicited videos out of their suggested recommended content. This includes videos about hate speech, livestreams, etc. YouTube has been identified as an influential platform for spreading radicalized content. Al-Qaeda and similar extremist groups have been linked to using YouTube for recruitment videos and engaging with international media outlets. In a research study published by the American Behavioral Scientist Journal, they researched "whether it is possible to identify a set of attributes that may help explain part of the YouTube algorithm's decision-making process". The results of the study showed that YouTube's algorithm recommendations for extremism content factor into the presence of radical keywords in a video's title. In February 2023, in the case of Gonzalez v. Google, the question at hand is whether or not Google, the parent company of YouTube, is protected from lawsuits claiming that the site's algorithms aided terrorists in recommending ISIS videos to users. Section 230 is known to generally protect online platforms from civil liability for the content posted by its users. Multiple studies have found little to no evidence to suggest that YouTube's algorithms direct attention towards far-right content to those not already engaged with it. === TikTok === TikTok is a platform that recommends videos to a user's 'For You Page' (FYP), making every users' page different. With the nature of the algorithm behind the app, TikTok's FYP has been linked to showing more explicit and radical videos over time based on users' previous interactions on the app. Since TikTok's inception, the app has been scrutinized for misinformation and hate speech as those forms of media usually generate more interactions to the algorithm. Various extremist groups, including jihadist organizations, have utilized TikTok to disseminate propaganda, recruit followers, and incite violence. The platform's algorithm, which recommends content based on user engagement, can expose users to extremist content that aligns with their interests or interactions. As of 2022, TikTok's head of US Security has put out a statement that "81,518,334 videos were removed globally between April – June for violating our Community Guidelines or Terms of Service" to cut back on hate speech, harassment, and misinformation. Studies have noted instances where individuals were radicalized through content encountered on TikTok. For example, in early 2023, Austrian authorities thwarted a plot against an LGBTQ+ pride parade that involved two teenagers and a 20-year-old who were inspired by jihadist content on TikTok. The youngest suspect, 14 years old, had been exposed to videos created by Islamist influencers glorifying jihad. These videos led him to further engagement with similar content, eventually resulting in his involvement in planning an attack. Another case involved the arrest of several teenagers in Vienna, Austria, in 2024, who were planning to carry out a terrorist attack at a Taylor Swift concert. The investigation revealed that some of the suspects had been radicalized online, with TikTok being one of the platforms used to disseminate extremist content that influenced their beliefs and actions. == Self-radicalization == The U.S. Department of Justice defines 'Lone-wolf' (self) terrorism as "someone who acts alone in a terrorist attack without the help or encouragement of a government or a terrorist organization". Through social media outlets on the internet, 'Lone-wolf' terrorism has been on the rise, being linked to algorithmic radicalization. Through echo-chambers on the internet, viewpoints typically seen as radical were accepted and quickly adopted by other extremists. These viewpoints are encouraged by forums, group chats, and social media to reinforce their beliefs. == References in media == === The Social Dilemma === The Social Dilemma is a 2020 docudrama about how algorithms behind social media enables addiction, while possessing abilities to manipulate people's views, emotions, and behavior to spread conspiracy theories and disinformation. The film repeatedly uses buzz words such as 'echo chambers' and 'fake news' to prove psychological manipulation on social media, therefore leading to political manipulation. In the film, Ben falls deeper into a social media addiction as the algorithm found that his social media page has a 62.3% chance of long-term engagement. This leads into more videos on the recommended feed for Ben and he eventually becomes more immersed into propaganda and conspiracy theories, becoming more polarized with each video. == Proposed solutions == === United States: Weakening Section 230 protections === In the Communications Decency Act, Section 230 states t

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  • Content adaptation

    Content adaptation

    Content adaptation is the action of transforming content to adapt to device capabilities. Content adaptation is usually related to mobile devices, which require special handling because of their limited computational power, small screen size, and constrained keyboard functionality. Content adaptation could roughly be divided to two fields: Media content adaptation that adapts media files. Browsing content adaptation that adapts a website to mobile devices. == Browsing content adaptation == Advances in the capabilities of small, mobile devices such as mobile phones (cell phones) and Personal Digital Assistants have led to an explosion in the number of types of device that can now access the Web. Some commentators refer to the Web that can be accessed from mobile devices as the Mobile Web. The sheer number and variety of Web-enabled devices poses significant challenges for authors of websites who want to support access from mobile devices. The W3C Device Independence Working Group described many of the issues in its report Authoring Challenges for Device Independence. Content adaptation is one approach to a solution. Rather than requiring authors to create pages explicitly for each type of device that might request them, content adaptation transforms an author's materials automatically. For example, content might be converted from a device-independent markup language, such as XDIME, an implementation of the W3C's DIAL specification, into a form suitable for the device, such as XHTML Basic, C-HTML, or WML. Similarly, a suitable device-specific CSS style sheet or a set of in-line styles might be generated from abstract style definitions. Likewise, a device specific layout might be generated from abstract layout definitions. Once created, the device-specific materials form the response returned to the device from which the request was made. Another way is to use the latest trend responsive design based on CSS, covered in this article (RWD). Content adaptation requires a processor that performs the selection, modification, and generation of materials to form the device-specific result. IBM's Websphere Everyplace Mobile Portal (WEMP), BEA Systems' WebLogic Mobility Server, Morfeo's MyMobileWeb, and Apache Cocoon are examples of such processors. Wurfl and WALL are popular open source tools for content adaptation. WURFL is an XML-based Device Description Repository with APIs to access the data in Java and PHP (and other popular programming languages). WALL (Wireless Abstraction Library) lets a developer author mobile pages which look like plain HTML, but converts them to WML, C-HTML, or XHTML Mobile Profile, depending on the capabilities of the device from which the HTTP request originates. GreasySpoon lets the developer build plugins for content editing, in JavaScript, Ruby (programming language), and more, just like the Firefox application GreaseMonkey. Alembik (Media Transcoding Server) is a Java (J2EE) application providing transcoding services for variety of clients and for different media types (image, audio, video, etc.). It is fully compliant with OMA's Standard Transcoder Interface specification and is distributed under the LGPL open source license. In 2007, the first large scale carrier-grade deployments of content transformation, on existing mass-market handsets, with no software download required, were deployed by Vodafone in the UK and globally for Yahoo! oneSearch, using the Novarra Vision solution. Novarra's content adaptation solution had been used in enterprise intranet deployments as early as 2003 (at that time, the platform was named "Engines for Wireless Data"). InfoGin, the 9-year-old content-adaptation company with customers like Vodafone, Orange, Telefónica and PCCW. The patented "Web to Mobile adaptation", Mobile Matrix Transcoder, Multimedia and Documents transcoders, Video adaptation supporte. Launched in 2007, Bytemobile's Web Fidelity Service was another carrier-grade, commercial infrastructure solution, which provided wireless content adaptation to mobile subscribers on their existing mass-market handsets, with no client download required.

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