AI Content Generator

AI Content Generator — hands-on reviews, top picks, pricing, pros and cons and a practical how-to guide on Aizhi.

  • Space-based data center

    Space-based data center

    Space-based data centers or orbital AI infrastructure are proposed concepts to build AI data centers in the sun-synchronous orbit or other orbits utilizing space-based solar power. Electric power has become the main bottleneck for terrestrial AI infrastructure. Space-based edge computing has historical roots in military architectures designed to bypass the latency of ground-based targeting networks. In the 1980s, the Strategic Defense Initiative's Brilliant Pebbles program first envisioned autonomous on-orbit data processing for missile defense. In 2019, the Space Development Agency (SDA) began to revive this decentralized approach through its Proliferated Warfighter Space Architecture (PWSA). This ambitious "sensor-to-shooter" infrastructure is treated as a prerequisite for the modern Golden Dome program, which would rely on space-based data processing to continuously track targets. == History == Early thinking about space-based computing infrastructure grew out of mid-20th-century visions for large orbital industrial systems, most notably proposals for space-based solar power, which were popularized in both technical literature and science writing by figures such as Isaac Asimov in the 1940s. These ideas emphasized exploiting the vacuum, continuous solar energy, and thermal characteristics of space to support power-intensive activities that would be difficult or inefficient on Earth. In the 21st century, advances in small satellites, reusable launch vehicles, and high-performance computing revived interest in space-based data centers, with governments and private companies exploring orbital or near-space platforms for edge computing, secure data handling, and low-latency processing of Earth-observation data. In September 2024, Y Combinator-backed Starcloud released a white paper detailing plans to build multiple gigawatts of AI compute in orbit. It was the first widely cited proposal to actually start building large orbital data centers. In 2025, Starcloud deployed an NVIDIA H100-class system and became the first company to train an LLM in space and run a version of Google Gemini in space. In March 2025, Lonestar deployed a data backup machine on the surface of the moon. In early January 2026, a team from the University of Pennsylvania presented a tether-based architecture for orbital data centers at the AIAA SciTech conference. The design relied on gravity gradient tension and solar-pressure-based passive attitude stabilization to minimize the mass of MW-scale orbital data centers. In January 2026, SpaceX filed plans with the Federal Communications Commission (FCC) for millions of satellites, leveraging reusable launches and Starlink integration to extend cloud and AI computing into orbit. Around the same time, Blue Origin announced the TeraWave constellation of about 5,400 satellites, designed to provide high‑throughput networking for data centers, enterprise, and government customers. Meanwhile, China announced a 200,000‑satellite constellation, focusing on state coordination, data sovereignty, and in-orbit processing for secure, time-critical applications. In February 2026, Starcloud submitted a proposal to the FCC for a constellation of up to 88,000 satellites for orbital data centers. In March, it announced intentions to be the first to mine Bitcoin in space, flying bitcoin mining ASICs on its second satellite, Starcloud-2. In May 2026, Edge Aerospace was awarded a contract by the European Space Agency under its Space Cloud program to study use cases, architectures and implementation roadmap for orbital data centers. == Feasibility == In October 2025, Nature Electronics published a study led by a research group at Nanyang Technological University on the development of carbon-neutral data centres in space. In November 2025, Google published a feasibility study on space-based data centers. The authors argued that if launch costs to low earth orbit reached US$200/kg, the launch cost for data center satellites could be cost effective relative to current energy costs for ground-based data centers. They project this may occur around 2035 if SpaceX's Starship project scales to 180 launches/year by then. == Advantages == Some sun-synchronous orbit (SSO) planes have constant sunlight in the dawn/dusk which could provide continuous solar energy. SSO is a limited resource and proper management and sharing of it is required. Solar irradiance is 36% higher in Earth orbit than on the surface No Earth weather storms or clouds, however more exposed to Solar storms. No property tax or land-use regulation. Saves space for other land use. Ample space for scalability. Won't strain the power grid. Direct access to power source without additional infrastructure. == Disadvantages == The deployment of space-based data centers raises several technical, economic, and environmental concerns. Existing launch costs are substantial and remains main cost of space infrastructure deployment Cooling is limited to heat dissipation through radiation only, which made in inefficient in comparison to convection in terrestrial data centers Space infrastructure must be designed to survive launch and to work under environment conditions of radiation, wide range of temperatures, in vacuum and in microgravity In-space assembly is on early development stage to enable deployment of mega-structures Megastructures are particularly exposed to orbital debris Solar arrays efficiency decrease 0.5% to 0.8% per year due to exposure of ultraviolet rays, space weather and orbital thermal cycles Hardware is designed for limited lifespan. Maintenance and repair in space (known as On-Orbit Servicing (OOS)) is still on early stage of practical implementation. Disposable data centre: technology obsolescence of AI data centre being a concern and difficult maintenance in space imply the single-use purpose of those space data centres. To extend lifetime, space infrastructure will require either refueling or orbit rasie by the servicer, which is going to increase its operational costs The environmental impact on Earth has its own challenges: The environmental impact of launches need to be addressed. Deployment consumes Earth resources that cannot be recovered or recycled. Computers require lots of resources, some of which are strategic. Recycling e-waste is already a challenge on Earth and extremely unlikely in space. Space debris (orbit pollution) is another sustainability challenge for space: Orbits are, like any resources, a limited physical and electromagnetic resource and available for all mankind. The accumulation of satellites on a particular orbit reduces the use of space for other purposes. A consequence of the increase of satellite in orbit is a higher risk of the runaway of space debris (see Kessler syndrome). This means some orbits could become unusable. Latency and bandwidth are constrained in space, and consumes limited electromagnetic resources. Satellite flares could inhibit ground-based and space-based observational astronomy. == Size and power generated == It would take ~1 square mile solar array in earth orbit to produce 1 gigawatt of power at 30% cell efficiency. == Companies pursuing space-based AI infrastructure == Blue Origin Cowboy Space Corporation (formerly Aetherflux) Edge Aerospace Google – Project Suncatcher Nvidia OpenAI SpaceX Starcloud

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  • Vulnerability Discovery Model

    Vulnerability Discovery Model

    A Vulnerability Discovery Model (VDM) uses discovery event data with software reliability models for predicting the same. A thorough presentation of VDM techniques is available in. Numerous model implementations are available in the MCMCBayes open source repository. Several VDM examples include: Alhazmi-Malaiya: Time based model (Alhazmi-Malaiya Logistic (AML) model) Alhazmi-Malaiya: Effort based model Rescorla: Quadratic Model and Exponential Model Anderson: Thermodynamic Model Kim: Weibull Model Linear Model Hump-Shaped Model Independent and Dependent Model Vulnerability Discovery Modeling using Bayesian model averaging Multivariate Vulnerability Discovery Models

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  • Spyglass (app)

    Spyglass (app)

    Spyglass is a navigation and orientation mobile application developed by Pavel Ahafonau. It combines data from a digital compass, GNSS positioning, motion sensors, maps, and the device camera to provide direction finding, waypoint navigation, and measurement tools. The application is designed for offline and off-road use and is used in outdoor navigation, orientation tasks, astronomy, and fieldwork. == History == Spyglass was created by independent software developer Pavel Ahafonau as a personal project in 2009, following the introduction of a digital compass sensor in the iPhone. It initially focused on combining compass, GPS, and camera data into an augmented-reality tool for navigation and orientation. In September 2009, a public prototype was demonstrated, showing a live camera view combined with a digital compass overlay aligned to device orientation, presenting an early augmented-reality, location-aware heads-up display. The application was released on the Apple App Store in October 2009. In February 2010, a major update introduced target-based navigation, allowing users to navigate to saved locations, bearings, and selected celestial objects. The update also added visual measurement tools, including an optical-style rangefinder, as well as a vertical speed indicator displaying ascent and descent rates derived from device sensor data. In December 2010, Spyglass was featured by Apple in iTunes Rewind 2010 under augmented-reality applications. The application expanded to Android on 28 October 2017. In May 2021, Spyglass expanded its offline mapping capabilities by adding support for additional map styles by Thunderforest, extending the range of available cartographic themes for offline use. Also in 2021, navigation satellite tracking was introduced, allowing visualization and tracking of major GPS/GNSS satellite constellations. In 2022, a searchable offline database of major locations was added, including airports, seaports, mountains, castles, and landmarks, along with nearest-airport tracking functionality. In July 2024, previously separate iOS editions (Spyglass, Commander Compass, and Commander Compass Go) were consolidated into a single Spyglass application. At the same time, the app transitioned to a freemium model. == Features == Spyglass provides navigation and orientation functions by combining sensor data from the device. Core functionality includes a digital compass, GNSS-based positioning, waypoint creation and tracking, and map-based navigation with offline support. The application includes an augmented-reality viewfinder mode that overlays navigation and sensor information onto the live camera view. Displayed data may include heading, bearing, distance to targets, pitch, roll, yaw, altitude, speed, and estimated time of arrival. Additional tools include an altimeter, speedometer, vertical speed indicator, inclinometer, artificial horizon, coordinate conversion utilities, optical rangefinding, and angular measurement tools. Spyglass also supports celestial navigation features, such as tracking of the Sun, Moon, stars, and global navigation satellite systems. Spyglass uses data from the device's GNSS receiver, digital compass, gyroscope, accelerometer, barometer (when available), and camera. Sensor data are combined to calculate position, orientation, movement, and measurement overlays. The application is designed to function without an internet connection. Navigation tools, sensor readings, waypoint tracking, augmented-reality features, celestial tracking, and the built-in location database operate offline. Internet access is required only for loading online map tiles; previously downloaded offline maps remain available without connectivity.

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  • Hint (app)

    Hint (app)

    Hint (hint.app) is an American software platform that provides astrological content, personality assessments, and relationship compatibility tools. The application was launched in 2018 and is based in Claymont, Delaware. The platform has been described in media coverage as part of a broader trend of astrology-based and self-reflection applications, particularly among younger users. As of 2026, the company reports that it has reached more than 25 million users worldwide. == History == Hint was founded in 2018 and is headquartered in Claymont, Delaware. The platform was developed to address a growing demand among Millennials and Gen Z for structured self-reflection tools that deviate from traditional religious or clinical psychological frameworks. The app has become a prominent figure in the "emotional technology" sector, reaching over 25 million global users by 2026. The platform is frequently cited by sociologists and media outlets as a primary driver of the Open-source intelligence trend, where individuals use digital tools to vet and analyze personal relationships in the dating economy. Media coverage has described the platform as part of a broader trend in which digital tools incorporate astrology and symbolic frameworks into wellness and relationship advice. == Reception == Coverage of Hint has appeared alongside reporting on changing attitudes toward dating and relationships, particularly among younger adults. Surveys reported by media outlets have described shifts in dating behavior, including reduced interest in casual relationships and increased reliance on digital tools for emotional reflection and compatibility assessment. Additional reporting has linked the use of astrology apps to broader trends in emotional fatigue and changing relationship expectations. Lifestyle and culture publications have described Hint, as an example of applications that integrate astrology into digital self-reflection and relationship analysis.

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  • Lexical substitution

    Lexical substitution

    Lexical substitution is the task of identifying a substitute for a word in the context of a clause. For instance, given the following text: "After the match, replace any remaining fluid deficit to prevent chronic dehydration throughout the tournament", a substitute of game might be given. Lexical substitution is strictly related to word sense disambiguation (WSD), in that both aim to determine the meaning of a word. However, while WSD consists of automatically assigning the appropriate sense from a fixed sense inventory, lexical substitution does not impose any constraint on which substitute to choose as the best representative for the word in context. By not prescribing the inventory, lexical substitution overcomes the issue of the granularity of sense distinctions and provides a level playing field for automatic systems that automatically acquire word senses (a task referred to as Word Sense Induction). == Evaluation == In order to evaluate automatic systems on lexical substitution, a task was organized at the Semeval-2007 evaluation competition held in Prague in 2007. A Semeval-2010 task on cross-lingual lexical substitution has also taken place. == Skip-gram model == The skip-gram model takes words with similar meanings into a vector space (collection of objects that can be added together and multiplied by numbers) that are found close to each other in N-dimensions (list of items). A variety of neural networks (computer system modeled after a human brain) are formed together as a result of the vectors and networks that are related together. This all occurs in the dimensions of the vocabulary that has been generated in a network. The model has been used in lexical substitution automation and prediction algorithms. One such algorithm developed by Oren Melamud, Omer Levy, and Ido Dagan uses the skip-gram model to find a vector for each word and its synonyms. Then, it calculates the cosine distance between vectors to determine which words will be the best substitutes. === Example === In a sentence like "The dog walked at a quick pace" each word has a specific vector in relation to the other. The vector for "The" would be [1,0,0,0,0,0,0] because the 1 is the word vocabulary and the 0s are the words surrounding that vocabulary, which create a vector.

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  • Roadie (app)

    Roadie (app)

    Roadie Inc. is an American package delivery company for business and private same-day, urgent and scheduled delivery in the United States. The company was founded in 2014 and launched its web and mobile apps in January 2015. As of September 2021, it reported having over 200,000 drivers covering more than 20,000 zip codes. Roadie states it matches gig drivers with deliveries that are directed along the routes they plan to travel. Major customers include The Home Depot, Walmart, Tractor Supply Company, Best Buy and Delta Air Lines. In September 2021, UPS entered into an agreement to acquire Roadie for an undisclosed amount with the transaction expected to be closed in the fourth quarter. == History == Roadie was founded by Marc Gorlin, a co-founder of Kabbage and founder of VerticalOne and Pretty Good Privacy, as a same-day and urgent delivery company in 2014. In January 2015, Roadie launched the first consumer to consumer (C2C) version of its app with a Series A funding round of $10 million. In February, Roadie announced a partnership with Waffle House to designate its restaurants "Roadie Roadhouses", offering a neutral meeting place for drivers and senders. Drivers receive free food and drink through the partnership. In May, late-night host Jimmy Kimmel discussed the Roadie-Waffle House relationship in an opening monologue on Jimmy Kimmel Live!. Roadie's driver network expanded significantly as a result. Roadie closed a Series B round of funding in June, raising $15 million, and its first business to business (B2B) app version launched that November. In 2015, Delta Air Lines signed an agreement with Roadie to deliver mishandled luggage, becoming Roadie’s first enterprise customer. Roadie launched a pilot program with Delta at Daytona Beach International Airport. Since then, the relationship has expanded to include over 70 airports around the United States and a first mile/last mile line haul relationship with Delta Cargo. In 2017, the company signed a deal with The Home Depot, also based in Atlanta, and in February 2019, closed a Series C round of funding. In October 2019, Roadie and Delta Cargo announced a partnership to create a same-day cross-country delivery offering, DASH Door-to-Door, the first of its kind from a U.S. passenger airline. Tractor Supply Company became the first general merchandise retailer to offer same-day delivery from every store in April 2020 through Roadie. In September 2021, UPS entered an agreement to acquire Roadie for an undisclosed amount. The transaction was expected to close in the fourth quarter of 2021. Roadies, which at the time reported having 200,000 operators serving over 20,000 ZIP Codes, was expected to continue operations under its name as a separate company with no transfer of packages between the UPS and Roadies networks. The relationship between the companies goes back several years with UPS being an early investor. Earlier in 2021, UPS had begun a pilot program testing same-day deliveries via Roadies. == Operations == === On-the-way model === Roadie’s app works by connecting drivers with senders, businesses or consumers who have items that need to be delivered. Deliveries within the app are referred to as "Gigs", which Gorlin said was inspired by live music road crews, also known as roadies. A sender creates a Gig on Roadie's web app or via its API. Drivers then review deliveries in their area on their mobile app and may choose to offer to take on individual or groups of deliveries along the same route. Gigs are then assigned to drivers by Roadie's algorithm. According to the company, this model encourages drivers to choose Gigs that align with their planned schedules and routes. Roadie calls this its "on-the-way" delivery model. The go-to-market approach taken by Roadie also differs from its competitors. Rather than launching in major cities and sequentially adding new markets city-by-city, Roadie launched nationwide from its inception. The company relies on retail and airline partners to drive volume of deliveries in individual markets, which in turn builds up a network of drivers in those areas, making it easier for small businesses and consumers to send deliveries as well. This strategy allows Roadie to reach smaller cities and towns in rural or exurban communities, traditionally difficult markets for delivery providers to serve. === Service lines === Roadie’s platform is most popular for same-day, on-demand or scheduled first mile/last mile delivery, especially delivery from stores and warehouses. Some retailers also use it for returns and reverse logistics, moving inventory, and hot shot shipping. Roadie operates 1-hour grocery delivery for Walmart, and delivers perishable food items for others including small, independent retailers. The on-the-way model complements the grocery industry’s just in time model, making last-mile deliveries that do not break the cold chain. === Cross-country same-day delivery === In October 2019, Roadie and Delta Cargo launched DASH Door-to-Door, a 24/7 door-to-door pick-up and delivery service. Roadie handles the first and last mile and Delta manages the line haul via passenger flights. The service launched originally from Atlanta to 55 cities and is an industry-first for a US commercial airline. === Promotion, awards and corporate citizenship === In September 2015, Roadie announced a partnership with Atlanta-based musician Ludacris, to promote the app. Following the devastation caused by flooding in Baton Rouge in 2016, Roadie offered free pickup and delivery for all deliveries traveling to and from the Baton Rouge area. In December 2020, Walmart named Roadie its top delivery partner for "Highest Driver Customer Satisfaction" and "Highest Net Promoter Score", after expanding into general merchandise deliveries as well as grocery that same year.

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  • Physical information security

    Physical information security

    Physical information security is the intersection or common ground between physical security and information security. It primarily concerns the protection of tangible information-related assets such as computer systems and storage media against physical, real-world threats such as unauthorized physical access, theft, fire and flood. It typically involves physical controls such as protective barriers and locks, uninterruptible power supplies, and shredders. Information security controls in the physical domain complement those in the logical domain (such as encryption), and procedural or administrative controls (such as information security awareness and compliance with policies and laws). == Background == Asset are inherently valuable and yet vulnerable to a wide variety of threats, both malicious (e.g. theft, arson) and accidental/natural (e.g. lost property, bush fire). If threats materialize and exploit those vulnerabilities causing incidents, there are likely to be adverse impacts on the organizations or individuals who legitimately own and utilize the assets, varying from trivial to devastating in effect. Security controls are intended to reduce the probability or frequency of occurrence and/or the severity of the impacts arising from incidents, thus protecting the value of the assets. Physical security involves the use of controls such as smoke detectors, fire alarms and extinguishers, along with related laws, regulations, policies and procedures concerning their use. Barriers such as fences, walls and doors are obvious physical security controls, designed to deter or prevent unauthorized physical access to a controlled area, such as a home or office. The moats and battlements of Mediaeval castles are classic examples of physical access controls, as are bank vaults and safes. Information security controls protect the value of information assets, particularly the information itself (i.e. the intangible information content, data, intellectual property, knowledge etc.) but also computer and telecommunications equipment, storage media (including papers and digital media), cables and other tangible information-related assets (such as computer power supplies). The corporate mantra "Our people are our greatest assets" is literally true in the sense that so-called knowledge workers qualify as extremely valuable, perhaps irreplaceable information assets. Health and safety measures and even medical practice could therefore also be classed as physical information security controls since they protect humans against injuries, diseases and death. This perspective exemplifies the ubiquity and value of information. Modern human society is heavily reliant on information, and information has importance and value at a deeper, more fundamental level. In principle, the subcellular biochemical mechanisms that maintain the accuracy of DNA replication could even be classed as vital information security controls, given that genes are 'the information of life'. Malicious actors who may benefit from physical access to information assets include computer crackers, corporate spies, and fraudsters. The value of information assets is self-evident in the case of, say, stolen laptops or servers that can be sold-on for cash, but the information content is often far more valuable, for example encryption keys or passwords (used to gain access to further systems and information), trade secrets and other intellectual property (inherently valuable or valuable because of the commercial advantages they confer), and credit card numbers (used to commit identity fraud and further theft). Furthermore, the loss, theft or damage of computer systems, plus power interruptions, mechanical/electronic failures and other physical incidents prevent them being used, typically causing disruption and consequential costs or losses. Unauthorized disclosure of confidential information, and even the coercive threat of such disclosure, can be damaging as we saw in the Sony Pictures Entertainment hack at the end of 2014 and in numerous privacy breach incidents. Even in the absence of evidence that disclosed personal information has actually been exploited, the very fact that it is no longer secured and under the control of its rightful owners is itself a potentially harmful privacy impact. Substantial fines, adverse publicity/reputational damage and other noncompliance penalties and impacts that flow from serious privacy breaches are best avoided, regardless of cause! == Examples of physical attacks to obtain information == There are several ways to obtain information through physical attacks or exploitations. A few examples are described below. === Dumpster diving === Dumpster diving is the practice of searching through trash in the hope of obtaining something valuable such as information carelessly discarded on paper, computer disks or other hardware. === Overt access === Sometimes attackers will simply go into a building and take the information they need. Frequently when using this strategy, an attacker will masquerade as someone who belongs in the situation. They may pose as a copy room employee, remove a document from someone's desk, copy the document, replace the original, and leave with the copied document. Individuals pretending to building maintenance may gain access to otherwise restricted spaces. They might walk right out of the building with a trash bag containing sensitive documents, carrying portable devices or storage media that were left out on desks, or perhaps just having memorized a password on a sticky note stuck to someone's computer screen or called out to a colleague across an open office. == Examples of Physical Information Security Controls == Shredding paper documents prior to their disposal can prevent unintended information leakage. Digital data can be encrypted or securely wiped. Offices may require visitors to present valid identification cards or valid access keys. Office workers may be required to obey "clear desk" policies, protecting documents and other storage media (including portable IT devices) by tidying them away out of sight (for example in locked drawers, filing cabinets, safes or a Bank vault). Workers may be required to memorize their passwords or use a password manager instead of writing passwords on paper. Computers are vulnerable to outages caused by power cuts, accidental disconnection, flat batteries, brown-outs, surges, spikes, electrical interference and electronic failures. Physical information security controls to address the associated risks include: fuses, no-break battery-backed power supplies, electrical generators, redundant power sources and cabling, "Do not remove" warning signs on plugs, surge protectors, power quality monitoring, spare batteries, professional design and installation of power circuits plus regular inspections/tests and preventive maintenance.

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  • Insider threat

    Insider threat

    An insider threat is a perceived threat to an organization that comes from people within the organization, such as employees, former employees, contractors or business associates, who have inside information concerning the organization's security practices, data and computer systems. The threat may involve fraud, the theft of confidential or commercially valuable information, the theft of intellectual property, or the sabotage of computer systems. == Overview == Insiders may have accounts giving them legitimate access to computer systems, with this access originally having been given to them to serve in the performance of their duties; these permissions could be abused to harm the organization. Insiders are often familiar with the organization's data and intellectual property as well as the methods that are in place to protect them. This makes it easier for the insider to circumvent any security controls of which they are aware. Physical proximity to data means that the insider does not need to hack into the organizational network through the outer perimeter by traversing firewalls; rather they are in the building already, often with direct access to the organization's internal network. Insider threats are harder to defend against than attacks from outsiders, since the insider already has legitimate access to the organization's information and assets. An insider may attempt to steal property or information for personal gain or to benefit another organization or country. The threat to the organization could also be through malicious software left running on its computer systems by former employees, a so-called logic bomb. == Research == Insider threat is an active area of research in academia and government. The CERT Coordination Center at Carnegie-Mellon University maintains the CERT Insider Threat Center, which includes a database of more than 850 cases of insider threats, including instances of fraud, theft and sabotage; the database is used for research and analysis. CERT's Insider Threat Team also maintains an informational blog to help organizations and businesses defend themselves against insider crime. The Threat Lab and Defense Personnel and Security Research Center (DOD PERSEREC) has also recently emerged as a national resource within the United States of America. The Threat Lab hosts an annual conference, the SBS Summit. They also maintain a website that contains resources from this conference. Complimenting these efforts, a companion podcast was created, Voices from the SBS Summit. In 2022, the Threat Lab created an interdisciplinary journal, Counter Insider Threat Research and Practice (CITRAP) which publishes research on insider threat detection. === Findings === In the 2022 Data Breach Investigations Report (DBIR), Verizon found that 82% of breaches involved the human element, noting that employees continue to play a leading role in cybersecurity incidents and breaches. According to the UK Information Commissioners Office, 90% of all breaches reported to them in 2019 were the result of mistakes made by end users. This was up from 61% and 87% over the previous two years. A 2018 whitepaper reported that 53% of companies surveyed had confirmed insider attacks against their organization in the previous 12 months, with 27% saying insider attacks have become more frequent. A report published in July 2012 on the insider threat in the U.S. financial sector gives some statistics on insider threat incidents: 80% of the malicious acts were committed at work during working hours; 81% of the perpetrators planned their actions beforehand; 33% of the perpetrators were described as "difficult" and 17% as being "disgruntled". The insider was identified in 74% of cases. Financial gain was a motive in 81% of cases, revenge in 23% of cases, and 27% of the people carrying out malicious acts were in financial difficulties at the time. The US Department of Defense Personnel Security Research Center published a report that describes approaches for detecting insider threats. Earlier it published ten case studies of insider attacks by information technology professionals. Cybersecurity experts believe that 38% of negligent insiders are victims of a phishing attack, whereby they receive an email that appears to come from a legitimate source such as a company. These emails normally contain malware in the form of hyperlinks. == Typologies and ontologies == Multiple classification systems and ontologies have been proposed to classify insider threats. Traditional models of insider threat identify three broad categories: Malicious insiders, which are people who take advantage of their access to inflict harm on an organization; Negligent insiders, which are people who make errors and disregard policies, which place their organizations at risk; and Infiltrators, who are external actors that obtain legitimate access credentials without authorization. == Criticisms == Insider threat research has been criticized. Critics have argued that insider threat is a poorly defined concept. Forensically investigating insider data theft is notoriously difficult, and requires novel techniques such as stochastic forensics. Data supporting insider threat is generally proprietary (i.e., encrypted data). Theoretical/conceptual models of insider threat are often based on loose interpretations of research in the behavioral and social sciences, using "deductive principles and intuitions of subject matter expert." Adopting sociotechnical approaches, researchers have also argued for the need to consider insider threat from the perspective of social systems. Jordan Schoenherr said that "surveillance requires an understanding of how sanctioning systems are framed, how employees will respond to surveillance, what workplace norms are deemed relevant, and what ‘deviance’ means, e.g., deviation for a justified organization norm or failure to conform to an organizational norm that conflicts with general social values." By treating all employees as potential insider threats, organizations might create conditions that lead to insider threats. == Sector-specific concerns == === Healthcare === The healthcare industry faces particularly acute insider threat risks due to the large number of workforce members who require access to sensitive patient records for legitimate clinical purposes. The U.S. Department of Health and Human Services has identified unauthorized access by insiders, including workforce snooping on patient records and theft of protected health information for identity fraud, as a persistent enforcement concern. The Health Insurance Portability and Accountability Act (HIPAA) Security Rule addresses insider threats through several administrative safeguards, including workforce security procedures requiring covered entities to implement policies for authorizing and supervising workforce members who work with electronic protected health information, as well as termination procedures to revoke access when employment ends (45 CFR 164.308(a)(3)). The rule also requires audit controls to record and examine information system activity (45 CFR 164.312(b)), enabling detection of unauthorized access by insiders. The December 2024 Notice of proposed rulemaking (NPRM) to overhaul the HIPAA Security Rule would strengthen insider threat defenses by mandating role-based access controls, requiring notification of relevant workforce members within 24 hours of any changes to access privileges, and requiring regular review of audit logs to detect anomalous access patterns.

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  • Software requirements

    Software requirements

    Software requirements for a system are the description of what the system should do, the service or services that it provides and the constraints on its operation. The IEEE Standard Glossary of Software Engineering Terminology defines a requirement as: A condition or capability needed by a user to solve a problem or achieve an objective A condition or capability that must be met or possessed by a system or system component to satisfy a contract, standard, specification, or other formally imposed document A documented representation of a condition or capability as in 1 or 2 The activities related to working with software requirements can broadly be broken down into elicitation, analysis, specification, and management. Note that the wording Software requirements is additionally used in software release notes to explain, which depending on software packages are required for a certain software to be built/installed/used. == Elicitation == Elicitation is the gathering and discovery of requirements from stakeholders and other sources. A variety of techniques can be used such as joint application design (JAD) sessions, interviews, document analysis, focus groups, etc. Elicitation is the first step of requirements development. == Analysis == Analysis is the logical breakdown that proceeds from elicitation. Analysis involves reaching a richer and more precise understanding of each requirement and representing sets of requirements in multiple, complementary ways. Requirements Triage or prioritization of requirements is another activity which often follows analysis. This relates to Agile software development in the planning phase, e.g. by Planning poker, however it might not be the same depending on the context and nature of the project and requirements or product/service that is being built. == Specification == Specification involves representing and storing the collected requirements knowledge in a persistent and well-organized fashion that facilitates effective communication and change management. Use cases, user stories, functional requirements, and visual analysis models are popular choices for requirements specification. == Validation == Validation involves techniques to confirm that the correct set of requirements has been specified to build a solution that satisfies the project's business objectives, and to detect and correct errors in the requirements before implementation. == Management == Requirements change during projects and there are often many of them. Management of this change becomes paramount to ensuring that the correct software is built for the stakeholders. == Tool support for Requirements Engineering == === Tools for Requirements Elicitation, Analysis and Validation === Taking into account that these activities may involve some artifacts such as observation reports (user observation), questionnaires (interviews, surveys and polls), use cases, user stories; activities such as requirement workshops (charrettes), brainstorming, mind mapping, role-playing; and even, prototyping; software products providing some or all of these capabilities can be used to help achieve these tasks. There is at least one author who advocates, explicitly, for mind mapping tools such as FreeMind; and, alternatively, for the use of specification by example tools such as Concordion. Additionally, the ideas and statements resulting from these activities may be gathered and organized with wikis and other collaboration tools such as Trello. The features actually implemented and standards compliance vary from product to product. === Tools for Requirements Specification === A Software requirements specification (SRS) document might be created using general-purpose software like a word processor or one of several specialized tools. Some of these tools can import, edit, export and publish SRS documents. It may help to make SRS documents while following a standardised structure and methodology, such as ISO/IEC/IEEE 29148:2018. Likewise, software may or not use some standard to import or export requirements (such as ReqIF) or not allow these exchanges at all. === Tools for Requirements Document Verification === Tools of this kind verify if there are any errors in a requirements document according to some expected structure or standard. === Tools for Requirements Comparison === Tools of this kind compare two requirement sets according to some expected document structure and standard. === Tools for Requirements Merge and Update === Tools of this kind allow the merging and update of requirement documents. === Tools for Requirements Traceability === Tools of this kind allow tracing requirements to other artifacts such as models and source code (forward traceability) or, to previous ones such as business rules and constraints (backwards traceability). === Tools for Model-Based Software or Systems Requirement Engineering === Model-based systems engineering (MBSE) is the formalised application of modelling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later lifecycle phases. It is also possible to take a model-based approach for some stages of the requirements engineering and, a more traditional one, for others. Very many combinations might be possible. The level of formality and complexity depends on the underlying methodology involved (for instance, i is much more formal than SysML and, even more formal than UML) === Tools for general Requirements Engineering === Tools in this category may provide some mix of the capabilities mentioned previously and others such as requirement configuration management and collaboration. The features actually implemented and standards compliance vary from product to product. There are even more capable or general tools that support other stages and activities. They are classified as ALM tools.

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  • Security and Privacy in Computer Systems

    Security and Privacy in Computer Systems

    Security and Privacy in Computer Systems is a paper by Willis Ware that was first presented to the public at the 1967 Spring Joint Computer Conference. == Significance == Ware's presentation was the first public conference session about information security and privacy in respect of computer systems, especially networked or remotely-accessed ones. The IEEE Annals of the History of Computing said that Ware's 1967 Spring Joint Computer Conference session, together with 1970's Ware report, marked the start of the field of computer security.

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  • Magiran

    Magiran

    Magiran (Persian: مگیران)—Iran's publications database—is a digital library that was founded in 2000 and includes digitized versions of scientific journals, which currently provides the possibility of searching among the full text of 1,500 journals. Registration is required for full access to the database, but access to some items such as newspapers is also possible without registration. A list of Iranian researchers is also maintained there.

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  • Line Drawing System-1

    Line Drawing System-1

    LDS-1 (Line Drawing System-1) was a calligraphic (vector, rather than raster) display processor and display device created by Evans & Sutherland in 1969. This model was known as the first graphics device with a graphics processing unit. == Features == It was controlled by a variety of host computers. Straight lines were smoothly rendered in real-time animation. General principles of operation were similar to the systems used today: 4x4 transformation matrices, 1x4 vertices. Possible uses included flight simulation (in the product brochure there are screenshots of landing on a carrier), scientific imaging and GIS systems. == History == The first LDS-1 was shipped to the customer (BBN) in August 1969. Only a few of these systems were ever built. One was used by the Los Angeles Times as their first typesetting/layout computer. One went to NASA Ames Research Center for Human Factors Research. Another was bought by the Port Authority of New York to develop a tugboat pilot trainer for navigation in the harbor. The MIT Dynamic Modeling had one, and there was a program for viewing an ongoing game of Maze War.

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  • Visible (mobile app)

    Visible (mobile app)

    Visible is a health tracking mobile app for people with long COVID and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The company was founded by a Harry Leeming, an engineer from London living with long Covid since 2020, and Luke Martin-Fuller. In November 2022, Visible released an open beta of an app that aims to help people pace their activities to avoid post-exertional malaise. The app gathers data on exertion levels, symptom severity, and heart-rate variability. HRV is approximated using a smartphone's camera via a technique called photoplethysmography, and according to the app's developers, can indicate how much someone needs rest. The app is currently free, but is expected to be freemium in the future. Users can also opt to allow their data be used for research purposes. In July 2023, Visible and Imperial College London announced the start of the first two studies. One is on the effects of the menstrual cycle on long COVID symptoms, and the other is on the condition's epidemiology and economic impact. Visible has announced plans to couple the app with activity trackers for continuous monitoring of heart-rate and actimetry data, which the developers claim will be more effective. As of 2022, no clinical trials on Visible's effectiveness have been conducted.

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  • Sprite (computer graphics)

    Sprite (computer graphics)

    In computer graphics, a sprite is a two-dimensional bitmap that is integrated into a larger scene, most often in a 2D video game. Originally, the term sprite referred to fixed-sized objects composited together, by hardware, with a background. Use of the term has since become more general. Systems with hardware sprites include arcade video games of the 1970s and 1980s; game consoles including as the Atari VCS (1977), ColecoVision (1982), Famicom (1983), Genesis/Mega Drive (1988); and home computers such as the TI-99/4 (1979), Atari 8-bit computers (1979), Commodore 64 (1982), MSX (1983), Amiga (1985), and X68000 (1987). Hardware varies in the number of sprites supported, the size and colors of each sprite, and special effects such as scaling or reporting pixel-precise overlap. Hardware composition of sprites occurs as each scan line is prepared for the video output device, such as a cathode-ray tube, without involvement of the main CPU and without the need for a full-screen frame buffer. Sprites can be positioned or altered by setting attributes used during the hardware composition process. The number of sprites which can be displayed per scan line is often lower than the total number of sprites a system supports. For example, the Texas Instruments TMS9918 chip supports 32 sprites, but only four can appear on the same scan line. The CPUs in modern computers, video game consoles, and mobile devices are fast enough that bitmaps can be drawn into a frame buffer without special hardware assistance. Beyond that, GPUs can render vast numbers of scaled, rotated, anti-aliased, partially translucent, very high resolution images in parallel with the CPU. == Etymology == According to Karl Guttag, one of two engineers for the 1979 Texas Instruments TMS9918 video display processor, this use of the word sprite came from David Ackley, a manager at TI. It was also used by Danny Hillis at Texas Instruments in the late 1970s. The term was derived from the fact that sprites "float" on top of the background image without overwriting it, much like a ghost or mythological sprite. Some hardware manufacturers used different terms, especially before sprite became common: Player/Missile Graphics was a term used by Atari, Inc. for hardware sprites in the Atari 8-bit computers (1979) and Atari 5200 console (1982). The term reflects the use for both characters ("players") and smaller associated objects ("missiles") that share the same color. The earlier Atari Video Computer System and some Atari arcade games used player, missile, and ball. Stamp was used in some arcade hardware in the early 1980s, including Ms. Pac-Man. Movable Object Block, or MOB, was used in MOS Technology's graphics chip literature. Commodore, the main user of MOS chips and the owner of MOS for most of the chip maker's lifetime, instead used the term sprite for the Commodore 64. OBJs (short for objects) is used in the developer manuals for the NES, Super NES, and Game Boy. The region of video RAM used to store sprite attributes and coordinates is called OAM (Object Attribute Memory). This also applies to the Game Boy Advance and Nintendo DS. == History == === Arcade video games === The use of sprites originated with arcade video games. Nolan Bushnell came up with the original concept when he developed the first arcade video game, Computer Space (1971). Technical limitations made it difficult to adapt the early mainframe game Spacewar! (1962), which performed an entire screen refresh for every little movement, so he came up with a solution to the problem: controlling each individual game element with a dedicated transistor. The rockets were essentially hardwired bitmaps that moved around the screen independently of the background, an important innovation for producing screen images more efficiently and providing the basis for sprite graphics. The earliest video games to represent player characters as human player sprites were arcade sports video games, beginning with Taito's TV Basketball, released in April 1974 and licensed to Midway Manufacturing for release in North America. Designed by Tomohiro Nishikado, he wanted to move beyond simple Pong-style rectangles to character graphics, by rearranging the rectangle shapes into objects that look like basketball players and basketball hoops. Ramtek released another sports video game in October 1974, Baseball, which similarly displayed human-like characters. The Namco Galaxian arcade system board, for the 1979 arcade game Galaxian, displays animated, multi-colored sprites over a scrolling background. It became the basis for Nintendo's Radar Scope and Donkey Kong arcade hardware and home consoles such as the Nintendo Entertainment System. According to Steve Golson from General Computer Corporation, the term "stamp" was used instead of "sprite" at the time. === Home systems === Signetics devised the first chips capable of generating sprite graphics (referred to as objects by Signetics) for home systems. The Signetics 2636 video processors were first used in the 1978 1292 Advanced Programmable Video System and later in the 1979 Elektor TV Games Computer. The Atari VCS, released in 1977, has a hardware sprite implementation where five graphical objects can be moved independently of the game playfield. The term sprite was not in use at the time. The VCS's sprites are called movable objects in the programming manual, further identified as two players, two missiles, and one ball. These each consist of a single row of pixels that are displayed on a scan line. To produce a two-dimensional shape, the sprite's single-row bitmap is altered by software from one scan line to the next. The 1979 Atari 400 and 800 home computers have similar, but more elaborate, circuitry capable of moving eight single-color objects per scan line: four 8-bit wide players and four 2-bit wide missiles. Each is the full height of the display—a long, thin strip. DMA from a table in memory automatically sets the graphics pattern registers for each scan line. Hardware registers control the horizontal position of each player and missile. Vertical motion is achieved by moving the bitmap data within a player or missile's strip. The feature was called player/missile graphics by Atari. Texas Instruments developed the TMS9918 chip with sprite support for its 1979 TI-99/4 home computer. An updated version is used in the 1981 TI-99/4A. === In 2.5D and 3D games === Sprites remained popular with the rise of 2.5D games (those which recreate a 3D game space from a 2D map) in the late 1980s and early 1990s. A technique called billboarding allows 2.5D games to keep onscreen sprites rotated toward the player view at all times. Some 2.5D games, such as 1993's Doom, allow the same entity to be represented by different sprites depending on its rotation relative to the viewer, furthering the illusion of 3D. Fully 3D games usually present world objects as 3D models, but sprites are supported in some 3D game engines, such as GoldSrc and Unreal, and may be billboarded or locked to fixed orientations. Sprites remain useful for small details, particle effects, and other applications where the lack of a third dimension is not a major detriment. == Systems with hardware sprites == These are base hardware specs and do not include additional programming techniques, such as using raster interrupts to repurpose sprites mid-frame.

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  • DigitaltMuseum

    DigitaltMuseum

    DigitaltMuseum (lit. 'The Digital Museum') is a website database in Norwegian and Swedish for art, images and cultural history museums. The service was established in 2009 after a trial period. The database is developed and operated by KulturIT. KulturIT ANS was established by the Norwegian Museum of Cultural History and Maihaugen in consultation with the Norwegian Archive, Library and Museum Authority (ABM) in 2007. In 2015, the company underwent a corporate transformation and KulturIT AS was established on 12 February. The website has per 2025 around 2,548,022 images. Many of the images are in the public domain or under Creative Commons licenses and are being imported into Wikimedia Commons. The website's API was developed in 2012. == Institutions == As of 2025, there are 223 collaborating museums. == Mission == DigitaltMuseum aims to make the museums' collections accessible to all interested parties, regardless of time and place. The website aims to facilitate easy use of the collections through various methods including image searches, research, teaching and joint knowledge development. DigitaltMuseum contains collections from several hundred Norwegian and Swedish museums, totalling around five million objects. The website contains both historical images from the areas and themes covered by the museums, as well as images of artefacts from the collections. Parts of the collection have previously only been shown in the museums' exhibitions and books and have therefore rarely or never been shown to the public.

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