AI Detector And Fixer

AI Detector And Fixer — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

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  Record sealing

  Record sealing is the process of making public records inaccessible to the public. In many cases, a person with a sealed record gains the legal right to deny or not acknowledge anything to do with the arrest and the legal proceedings from the case itself. Records are commonly sealed in a number of situations: Sealed birth records (typically after adoption or determination of paternity) Juvenile criminal records may be sealed Other types of cases involving juveniles may be sealed, anonymized, or pseudonymized ("impounded"); e.g., child sex offense or custody cases Cases using witness protection information may be partly sealed Cases involving trade secrets Cases involving state secrets == Filing under seal in US court == Normally, records should not be filed under seal without a court permission. However, FRCP 5.2 requires that sensitive text – like Social Security number, Taxpayer Identification Number, birthday, bank accounts, and children’s names – should be redacted off the filings made with the court and accompanying exhibits. A person making a redacted filing can file an unredacted copy under seal, or the Court can choose to order later that an additional filing be made under seal without redaction. Alternately, the filing party may ask the court’s permission to file some exhibits completely under seal. When the document is filed "under seal", it should have a clear indication for the court clerk to file it separately – most often by stamping words "Filed Under Seal" on the bottom of each page. Person making filing should also provide instructions to the court clerk that the document needs to be filed "under seal". Courts often have specific requirements to these filings in their Local Rules. == Difference from expungement == Expungement, which is a physical destruction, namely a complete erasure of one's criminal records, and therefore usually carries a higher standard, differs from record sealing, which is only to restrict the public's access to records, so that only certain law enforcement agencies or courts, under special circumstances, will have access to them. A record seal will greatly improve the chance of employment, as employers will not have access to damning records. There are occasions, like expungement, where one can truthfully state under oath that they have never been convicted before. Most of the time, a record seal has more relaxed requirements than an expungement. If an expungement is not allowed with a case, then sealing a record may be the best bet. Different states have different terms for what constitutes sealing of a record. == Cybersecurity incidents involving sealed records == Several cybersecurity incidents have demonstrated that sealed court documents are not always secure in practice, with vulnerabilities and data breaches exposing sensitive information. In January 2021, following the SolarWinds cyber attack, the U.S. Bankruptcy Court United States District Court for the District of Nevada announced that its Case Management/Electronic Case Files CM/ECF system had been potentially compromised. The judiciary stated that additional safeguards were being implemented to protect filings, and that the review of the incident and its impact was ongoing. Reports noted that the breach raised concerns about exposure of highly sensitive and sealed documents submitted through the CM/ECF system. In 2023, security researcher Jason Parker, following a tip from an activist, identified flaws in online court systems that exposed sealed records including confidential testimony and medical records through publicly accessible portals. In 2024, a cyber intrusion targeting attorneys in a civil case involving Representative Matt Gaetz led to the unauthorized access and leak of sealed depositions and related records. The breach exposed confidential testimony and financial records, some of which were later reported by news outlets, raising concerns about the security of electronically stored legal materials and the handling of sealed filings. In 2025, multiple reports confirmed that the federal judiciary's CM/ECF and PACER (law) filing system was compromised, exposing sealed indictments, confidential informant information, and other sensitive filings. Some courts temporarily reverted to paper-based filing to mitigate the risks of further disclosure. The FBI later confirmed that the breach had exposed sealed records, and investigators suspected foreign state actors were involved. == GAO publications referencing sealed records == Closed Criminal Plea and Sentencing Proceedings (1983) – Reviewed Department of Justice policies on closing plea and sentencing hearings. GAO noted that sealed transcripts should be unsealed once the reasons for closure no longer applied. Information on Plea Agreements and Settlements in Defense Procurement Fraud Cases (1992) – Examined outcomes of procurement fraud prosecutions. GAO observed that in some instances the results were sealed from public access. Military Recruiting: More Needs to Be Done to Better Screen Applicants and Detect Fraud (1999) – Investigated fraudulent enlistments in the armed forces. The report highlighted that sealed juvenile records often prevented recruiters from discovering prior offenses. Social Security Numbers: Governments Could Do More to Reduce Display in Public Records (2004) – Analyzed risks associated with SSN availability in state and local records. GAO pointed out that some categories of records, such as adoption proceedings, were sealed and less likely to expose identifiers. Social Security Numbers: Stronger Safeguards Needed to Protect Privacy (2005 testimony) – Testimony before Congress reiterating concerns over SSN exposure in public records, while noting that sealed categories (e.g., adoption) were exceptions. U.S. Supreme Court: Policies and Perspectives on Video and Audio Coverage of Appellate Court Proceedings (2016) – Surveyed appellate court policies on courtroom media coverage. The report acknowledged distinctions between public filings, confidential submissions, and sealed materials. Evictions: National Data Are Limited and Challenging to Collect (2024) – Examined nationwide eviction data. GAO reported that in some states eviction records may be sealed or expunged, limiting researchers' ability to compile datasets. DOD Fraud Risk Management: Enhanced Data and Collaboration Could Improve Efforts (2024) – Reviewed Department of Defense fraud-risk management. GAO noted that some adjudicative records in its dataset were sealed, restricting completeness of oversight data.

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  Subpixel rendering

  Subpixel rendering is a method used to increase the effective resolution of a color display device. It utilizes the composition of each pixel, which consists of three subpixels of which are red, green, and blue that can each be individually addressable on the display matrix. Subpixel rendering is primarily used for text rendering on standard DPI displays. Despite the inherent color anomalies, it can also be used to render general graphics. == History == The origin of subpixel rendering as used today remains controversial. Apple Inc., IBM, and Microsoft patented various implementations that differed in technical details owing to the different purposes for which their technologies were intended. Microsoft held several patents in the United States for subpixel rendering technology used in text rendering on RGB Stripe layouts. The patents 6,219,025; 6,239,783; 6,307,566; 6,225,973; 6,243,070; 6,393,145; 6,421,054; 6,282,327; and 6,624,828 were filed between October 7, 1998, and October 7, 1999, and expired on July 30, 2019. Analysis of the patent by FreeType indicates that the patent does not cover the idea of subpixel rendering, but rather the actual filter used as a last step to balance the color. Microsoft's patent describes the smallest possible filter that distributes each subpixel value equally among the R, G, and B pixels. Any other filter will either be blurrier or will introduce color artifacts. Apple was able to use it in Mac OS X due to a patent cross-licensing agreement. == Characteristics == A single pixel on a color display is made of several subpixels, typically three arranged left-to-right as red, green, and blue (RGB). The components are readily visible with a small magnifying glass, such as a loupe. These pixel components appear as a single color to the human eye because of blurring by optics and spatial integration by nerve cells in the eye. However, the eye is much more sensitive to the location. Therefore, turning on the G and B of one pixel and the R of the next pixel to the right will produce a white dot, but it will appear to be 1/3 of a pixel to the right of the white dot that would be seen from the RGB of only the first pixel. Subpixel rendering leverages this to provide three times the horizontal resolution of the rendered image. However, it has to blur this image to produce the correct color by ensuring the same amount of red, green, and blue are turned on as when no subpixel rendering is being done. Subpixel rendering does not necessitate the use of antialiasing. It gives a smoother result regardless of whether antialiasing is used or not since it artificially increases the resolution. However, it introduces color aliasing since subpixels are colored. Subsequent filtering applied to remove the color artifacts is a form of antialiasing, although its purpose is not smoothing jagged shapes as in conventional antialiasing. Subpixel rendering requires the software to know the layout of the subpixels. The most common reason it is wrong is monitors that can be rotated 90 (or 180) degrees, though monitors are manufactured with other arrangements of the subpixels, such as BGR or in triangles, or with 4 colors like RGBW squares. On any such display the result of incorrect subpixel rendering will be worse than if no subpixel rendering was done at all (it will not produce color artifacts, but it will produce noisy edges). == Implementations == === Apple II === Steve Gibson has claimed that the Apple II, introduced in 1977, supports an early form of subpixel rendering in its high-resolution (280×192) graphics mode. The Wozniak patent only used 2 "sub-pixels". The bytes that comprise the Apple II high-resolution screen buffer contain seven visible bits (each corresponding directly to a pixel) and a flag bit used to select between purple/green or blue/orange color sets. Each pixel, since it is represented by a single bit, is either on or off; there are no bits within the pixel itself for specifying color or brightness. Color is instead created as an artifact of the NTSC color encoding scheme, determined by horizontal position: pixels with even horizontal coordinates are always purple (or blue, if the flag bit is set), and odd pixels are always green (or orange). Two lit pixels next to each other are always white, regardless of whether the pair is even/odd or odd/even, and irrespective of the value of the flag bit. This is an approximation, but it is what most programmers of the time would have in mind while working with the Apple's high-resolution mode. Gibson's example claims that because two adjacent bits form a white block, there are, in fact, two bits per pixel: one that activates the pixel's purple left half and the other that activates its green right half. If the programmer instead activates the green right half of a pixel and the purple left half of the next pixel, the result is a white block 1/2 pixel to the right, which is indeed an instance of subpixel rendering. However, it is not clear whether any programmers of the Apple II have considered the pairs of bits as pixels—instead calling each bit a pixel. The flag bit in each byte affects color by shifting pixels half a pixel-width to the right. This half-pixel shift was exploited by some graphics software, such as HRCG (High-Resolution Character Generator), an Apple utility that displayed text using the high-resolution graphics mode, to smooth diagonals. === ClearType === Microsoft announced its subpixel rendering technology, called ClearType, at COMDEX in 1998. Microsoft published a paper in May 2000, Displaced Filtering for Patterned Displays, describing the filtering behind ClearType. It was then made available in Windows XP. Still, it was not activated by default until Windows Vista, while Windows XP OEMs could and did change the default setting. === FreeType === FreeType, the library used by most current software on the X Window System, contains two open source implementations. The original implementation uses the ClearType antialiasing filters and carries the following notice: "The colour filtering algorithm of Microsoft's ClearType technology for subpixel rendering is covered by patents; for this reason, the corresponding code in FreeType is disabled by default. Note that subpixel rendering per se is prior art; using a different colour filter thus easily circumvents Microsoft's patent claims." FreeType offers a variety of color filters. Since version 2.6.2, the default filter is light, a filter that is both normalized (value sums up to 1) and color-balanced (eliminate color fringes at the cost of resolution). Since version 2.8.1, a second implementation exists, called Harmony, that "offers high quality LCD-optimized output without resorting to ClearType techniques of resolution tripling and filtering". This is the method enabled by default. When using this method, "each color channel is generated separately after shifting the glyph outline, capitalizing on the fact that the color grids on LCD panels are shifted by a third of a pixel. This output is indistinguishable from ClearType with a light 3-tap filter." Since the Harmony method does not require additional filtering, it is not covered by the ClearType patents. === CoolType === Adobe created their own subpixel renderer called CoolType, allowing them to display documents the same way across various operating systems: Windows, MacOS, Linux etc. When it was launched around the year 2001, CoolType supported a wider range of fonts than Microsoft's ClearType, which at the time was limited to TrueType fonts. In contrast, Adobe's CoolType also supported PostScript fonts (and their OpenType equivalents). === macOS === Mac OS X (later OS X, now macOS) also used subpixel rendering, as part of Quartz 2D. However, it was removed after the introduction of Retina displays. Unlike Microsoft's implementation, which favors a tight fit to the grid (font hinting) to maximize legibility, Apple's implementation prioritizes the shape of the glyphs as set out by their designer.

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  Fantavision

  Fantavision is an animation program by Scott Anderson for the Apple II and published by Broderbund in 1985. Versions were released for the Apple IIGS (1987), Amiga (1988), and MS-DOS (1988). Fantavision allows the creation of vector graphics animations using the mouse and keyboard. The user creates frames, and the software generates the frames between them. Because this is done in real-time, it allows for creative exploration and quick changes. The program uses a graphical user interface in the style of the Macintosh with pull-down menus and black text on a white background. Advertisements claimed Fantavision a revolutionary breakthrough that brings the animation features of "tweening" and "transforming" to home computers. == Reception == Compute! in 1989 called Fantavision the best animation program for the IBM PC, although it noted the inability to draw curves. == Reviews == Games #70

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  Crackme

  A crackme is a small computer program designed to test a programmer's reverse engineering skills. Crackmes are made as a legal way to crack software, since no intellectual property is being infringed. == Description == Crackmes often incorporate protection schemes and algorithms similar to those used in proprietary software. However, they can sometimes be more challenging because they may use advanced packing or protection techniques, making the underlying algorithm harder to analyze and modify. == Keygenme == A keygenme is specifically designed for the reverser to not only identify the protection algorithm used in the application but also create a small key generator (keygen) in the programming language of their choice. Most keygenmes, when properly manipulated, can be made self-keygenning. For example, during validation, they might generate the correct key internally and compare it to the user's input. This allows the key generation algorithm to be easily replicated. Anti-debugging and anti-disassembly routines are often used to confuse debuggers or render disassembly output useless. Code obfuscation is also used to further complicate reverse engineering.

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  Computational semantics

  Computational semantics is a subfield of computational linguistics. Its goal is to elucidate the cognitive mechanisms supporting the generation and interpretation of meaning in humans. It usually involves the creation of computational models that simulate particular semantic phenomena, and the evaluation of those models against data from human participants. While computational semantics is a scientific field, it has many applications in real-world settings and substantially overlaps with Artificial Intelligence. Broadly speaking, the discipline can be subdivided into areas that mirror the internal organization of linguistics. For example, lexical semantics and frame semantics have active research communities within computational linguistics. Some popular methodologies are also strongly inspired by traditional linguistics. Most prominently, the area of distributional semantics, which underpins investigations into embeddings and the internals of Large Language Models, has roots in the work of Zellig Harris. Some traditional topics of interest in computational semantics are: construction of meaning representations, semantic underspecification, anaphora resolution, presupposition projection, and quantifier scope resolution. Methods employed usually draw from formal semantics or statistical semantics. Computational semantics has points of contact with the areas of lexical semantics (word-sense disambiguation and semantic role labeling), discourse semantics, knowledge representation and automated reasoning (in particular, automated theorem proving). Since 1999 there has been an ACL special interest group on computational semantics, SIGSEM.

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  Swizzling (computer graphics)

  In computer graphics, swizzles are a class of operations that transform vectors by rearranging components. Swizzles can also project from a vector of one dimensionality to a vector of another dimensionality, such as taking a three-dimensional vector and creating a two-dimensional or five-dimensional vector using components from the original vector. For example, if A = {1,2,3,4}, where the components are x, y, z, and w respectively, one could compute B = A.wwxy, whereupon B would equal {4,4,1,2}. Additionally, one could create a two-dimensional vector with A.wx or a five-dimensional vector with A.xyzwx. Combining vectors and swizzling can be employed in various ways. This is common in GPGPU applications. In terms of linear algebra, this is equivalent to multiplying by a matrix whose rows are standard basis vectors. If A = ( 1 , 2 , 3 , 4 ) T {\displaystyle A=(1,2,3,4)^{T}} , then swizzling A {\displaystyle A} as above looks like A . w w x y = [ 0 0 0 1 0 0 0 1 1 0 0 0 0 1 0 0 ] [ 1 2 3 4 ] = [ 4 4 1 2 ] . {\displaystyle A.\!wwxy={\begin{bmatrix}0&0&0&1\\0&0&0&1\\1&0&0&0\\0&1&0&0\end{bmatrix}}{\begin{bmatrix}1\\2\\3\\4\end{bmatrix}}={\begin{bmatrix}4\\4\\1\\2\end{bmatrix}}.}

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  Clipmap

  In computer graphics, clipmapping is a method of clipping a mipmap to a subset of data pertinent to the geometry being displayed. This is useful for loading as little data as possible when memory is limited, such as on a graphics processing unit. The technique is used for LODing in NVIDIA’s implementation of voxel cone tracing. The high-resolution levels of the mipmapped scene representation are clipped to a region near the camera, while lower resolution levels are clipped further away. == MegaTexture == MegaTexture is a clipmap implementation developed by id Software. It was introduced in their id Tech 4 engine and also appeared in id Tech 5 and id Tech 6 before being removed in id Tech 7. MegaTexture is a texture allocation technique that uses a single, extremely large texture rather than repeating multiple smaller textures. It is also featured in Splash Damage's game Enemy Territory: Quake Wars, and was developed by id Software former technical director John Carmack. MegaTexture employs a single large texture space for static terrain. The texture is stored on removable media or a computer's hard drive and streamed as needed, allowing large amounts of detail and variation over a large area with comparatively little RAM usage. Depending on the pixel resolution per square meter, covering a large area could require several gigabytes of memory. However, RAM is also filled by the rest of the game and the underlying operating system, limiting the amount available for texturing. As the player moves around the game, different sections of the MegaTexture are loaded into memory. They are then scaled to the correct size and applied to the 3D models of the terrain. Id has presented a more advanced technique that builds upon the MegaTexture idea and virtualizes both the geometry and the textures to obtain unique geometry down to the equivalent of the texel: the sparse voxel octree (SVO). It works by raycasting the geometry represented by voxels (instead of triangles) stored in an octree. The goal is to stream parts of the octree into video memory, going further down along the tree for nearby objects to give them more details, and to use higher level, larger voxels for farther objects, which give an automatic level of detail (LOD) system for both geometry and textures at the same time. The geometric detail that can be obtained using this method is nearly infinite, which removes the need for faking 3-dimensional details with techniques such as normal mapping. Despite that most voxel rendering tests use very large amounts of memory (up to several GB), Jon Olick of id Software claimed the technology is able to compress such SVO to 1.15 bits per voxel of position data. == Virtual texturing == Unlike clipmaps, which clip each mip level around a viewpoint-dependent clipcenter and therefore work best for terrain, virtual texturing preprocesses texture data into equally sized tiles that can be streamed for arbitrary textured geometry. Rage, powered by the id Tech 5 engine, uses a more advanced technique called virtual texturing. Textures can measure up to 128000×128000 pixels and are also used for in-game models and sprites, etc. and not just the terrain. Wolfenstein: The New Order and the 2016 version of Doom also use these. Carmageddon: Reincarnation also uses virtual texturing, though unlike id's virtual texturing system, which is designed for unique texture-mapping everywhere, their system is designed to use storage space sparingly while still offering good blend of texture variation and resolution.

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  Automotive security

  Automotive security refers to the branch of computer security focused on the cyber risks related to the automotive context. The increasingly high number of ECUs in vehicles and, alongside, the implementation of multiple different means of communication from and towards the vehicle in a remote and wireless manner led to the necessity of a branch of cybersecurity dedicated to the threats associated with vehicles. Not to be confused with automotive safety. == Causes == The implementation of multiple ECUs (Electronic Control Units) inside vehicles began in the early '70s thanks to the development of integrated circuits and microprocessors that made it economically feasible to produce the ECUs on a large scale. Since then the number of ECUs has increased to up to 100 per vehicle. These units nowadays control almost everything in the vehicle, from simple tasks such as activating the wipers to more safety-related ones like brake-by-wire or ABS (Anti-lock Braking System). Autonomous driving is also strongly reliant on the implementation of new, complex ECUs such as the ADAS, alongside sensors (lidars and radars) and their control units. Inside the vehicle, the ECUs are connected with each other through cabled or wireless communication networks, such as CAN bus (controller area network), MOST bus (Media Oriented System Transport), FlexRay (Automotive Network Communications Protocol) or RF (radio frequency) as in many implementations of TPMSs (tire-pressure monitoring systems). Many of these ECUs require data received through these networks that arrive from various sensors to operate and use such data to modify the behavior of the vehicle (e.g., the cruise control modifies the vehicle's speed depending on signals arriving from a button usually located on the steering wheel). Since the development of cheap wireless communication technologies such as Bluetooth, LTE, Wi-Fi, RFID and similar, automotive producers and OEMs have designed ECUs that implement such technologies with the goal of improving the experience of the driver and passengers. Safety-related systems such as the OnStar from General Motors, telematic units, communication between smartphones and the vehicle's speakers through Bluetooth, Android Auto and Apple CarPlay. == Threat model == Threat models of the automotive world are based on both real-world and theoretically possible attacks. Most real-world attacks aim at the safety of the people in and around the car, by modifying the cyber-physical capabilities of the vehicle (e.g., steering, braking, accelerating without requiring actions from the driver), while theoretical attacks have been supposed to focus also on privacy-related goals, such as obtaining GPS data on the vehicle, or capturing microphone signals and similar. Regarding the attack surfaces of the vehicle, they are usually divided in long-range, short-range, and local attack surfaces: LTE and DSRC can be considered long-range ones, while Bluetooth and Wi-Fi are usually considered short-range although still wireless. Finally, USB, OBD-II and all the attack surfaces that require physical access to the car are defined as local. An attacker that is able to implement the attack through a long-range surface is considered stronger and more dangerous than the one that requires physical access to the vehicle. In 2015 the possibility of attacks on vehicles already on the market has been proven possible by Miller and Valasek, that managed to disrupt the driving of a Jeep Cherokee while remotely connecting to it through remote wireless communication. === Controller area network attacks === The most common network used in vehicles and the one that is mainly used for safety-related communication is CAN, due to its real-time properties, simplicity, and cheapness. For this reason the majority of real-world attacks have been implemented against ECUs connected through this type of network. The majority of attacks demonstrated either against actual vehicles or in testbeds fall in one or more of the following categories: ==== Sniffing ==== Sniffing in the computer security field generally refers to the possibility of intercepting and logging packets or more generally data from a network. In the case of CAN, since it is a bus network, every node listens to all communication on the network. It is useful for the attacker to read data to learn the behavior of the other nodes of the network before implementing the actual attack. Usually, the final goal of the attacker is not to simply sniff the data on CAN, since the packets passing on this type of network are not usually valuable just to read. ==== Denial of service ==== Denial of service (DoS) in information security is usually described as an attack that has the objective of making a machine or a network unavailable. DoS attacks against ECUs connected to CAN buses can be done both against the network, by abusing the arbitration protocol used by CAN to always win the arbitration, and targeting the single ECU, by abusing the error handling protocol of CAN. In this second case the attacker flags the messages of the victim as faulty to convince the victim of being broken and therefore shut itself off the network. ==== Spoofing ==== Spoofing attacks comprise all cases in which an attacker, by falsifying data, sends messages pretending to be another node of the network. In automotive security usually spoofing attacks are divided into masquerade and replay attacks. Replay attacks are defined as all those where the attacker pretends to be the victim and sends sniffed data that the victim sent in a previous iteration of authentication. Masquerade attacks are, on the contrary, spoofing attacks where the data payload has been created by the attacker. == Real life automotive threat example == Security researchers Charlie Miller and Chris Valasek have successfully demonstrated remote access to a wide variety of vehicle controls using a Jeep Cherokee as the target. They were able to control the radio, environmental controls, windshield wipers, and certain engine and brake functions. The method used to hack the system was implementation of pre-programmed chip into the controller area network (CAN) bus. By inserting this chip into the CAN bus, he was able to send arbitrary message to CAN bus. One other thing that Miller has pointed out is the danger of the CAN bus, as it broadcasts the signal which the message can be caught by the hackers throughout the network. The control of the vehicle was all done remotely, manipulating the system without any physical interaction. Miller states that he could control any of some 1.4 million vehicles in the United States regardless of the location or distance, the only thing needed is for someone to turn on the vehicle to gain access. The work by Miller and Valasek replicated earlier work completed and published by academics in 2010 and 2011 on a different vehicle. The earlier work demonstrated the ability to compromise a vehicle remotely, over multiple wireless channels (including cellular), and the ability to remotely control critical components on the vehicle post-compromise, including the telematics unit and the car's brakes. While the earlier academic work was publicly visible, both in peer-reviewed scholarly publications and in the press, the Miller and Valesek work received even greater public visibility. == Security measures == The increasing complexity of devices and networks in the automotive context requires the application of security measures to limit the capabilities of a potential attacker. Since the early 2000 many different countermeasures have been proposed and, in some cases, applied. Following, a list of the most common security measures: Sub-networks: to limit the attacker capabilities even if he/she manages to access the vehicle from remote through a remotely connected ECU, the networks of the vehicle are divided in multiple sub-networks, and the most critical ECUs are not placed in the same sub-networks of the ECUs that can be accessed from remote. Gateways: the sub-networks are divided by secure gateways or firewalls that block messages from crossing from a sub-network to the other if they were not intended to. Intrusion Detection Systems (IDS): on each critical sub-network, one of the nodes (ECUs) connected to it has the goal of reading all data passing on the sub-network and detect messages that, given some rules, are considered malicious (made by an attacker). The arbitrary messages can be caught by the passenger by using IDS which will notify the owner regarding with unexpected message. Authentication protocols: in order to implement authentication on networks where it is not already implemented (such as CAN), it is possible to design an authentication protocol that works on the higher layers of the ISO OSI model, by using part of the data payload of a message to authenticate the message itself. Hardware Security Modules: since many ECUs are not powerful enough to keep real-time delays whi

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  Objective vision

  Objective Vision (Object Oriented Visionary) is a project mainly aimed at real-time computer vision and simulation vision of living creatures. it has three sections containing an open-source library of programming functions for using inside the projects, Virtual laboratory for scholars to check the application of functions directly and by command-line code for external and instant access, and the research section consists of paperwork and libraries to expand the scientific prove of works. == Background == The process has been used in the OVC libraries is as same as what's happening when living see a picture, and it's designed to give the researchers to experience the brain's visual cortex most close simulation for picture perception. The OVC was designed to work as a simulated visual cortex that has a critical job in processing and classify the objects to make it easier to work with pictures and graphical perception and processing. The human brain is much more aware of how it solves complex problems such as playing chess or solving algebra equations, which is why computer programmers have had so much success building machines that emulate this type of activity. but when the whole process is still a riddle that how the entities visionary system works. The project was simulated the visionary system by how it starts to convert the signals to image(actually the edges and colors) and then recognizing the shapes to find a relation between brain's information and image. The Objective Visionary system actually is concentrating on the separable sections, this separation gives the application visionary system the excellence processing result, because with this method the system do not waste much time on processing non significant sections and signals. this operation in the Objective Vision project called objective processing and because the O.V. mission is focused on human visionary simulation, so the developer refers with Objective Vision. == History == Objective-Vision is a Human (Natural) Visionary simulation Project developed by Michael Bidollahkhany. Following an explosion of interest during the 21st century were characterized by the maturing of the field and the significant growth of active applications; simulation of visionary systems, visionary based autonomous vehicle guidance, medical imaging (2D and 3D) and automatic surveillance are the most rapidly developing areas. This progress can be seen in an increasing number of software and hardware products on the market, as well as in a number of digital image processing software and APIs and also machine vision courses offered at universities worldwide. Therefore, the OVC project has been released as a research software project in 2016. One of important parts of this project was O.V.C. (Objective Vision Class library), that was designed to able companies and scientists to use the brain's most likely functionalities as visionary libraries to simplify and accelerate the image processing algorithms developments. The project started under MIT copyright license, but since 2018 the project continued as classified based on sponsors opinion. == The Algorithm == As developers claimed the algorithm used in the class library and developer's kit of project has been developed based on natural visionary system, and the functionalities containing image processing, optimization and labeling etc. are mostly upgraded and near techniques. Suppose that we've a picture of a jungle, or somewhere else, with this library developer will be able to manipulate not only the pixel of images for data extraction, but automatically based on which algorithm is used and image quality, he can manipulate directly a list of objects, same pixels and every data project needs to have, said the developer in his lecture answering how the algorithm works. === Viewpoint === For long times digital image processing and storing, was actually by processing just pixels; this Project tries to present a new kind of image processing and even storing, "objective vision" or "object-oriented visionary" is called. This project officially launched in May 2016, with the aim of making more adaptation between Computer Vision (Include Visionary, Digital image processing, discernment and even Perception) and Human Visual System; about development of the project: "...so we decided to research on Human Vision System, besides we worked on Artificial Retinal image processing and new visionary optimization unit(Presented at Istanbul Technical University Conference(Turkey 2015-2016)) and grew our research to Visionary CORTEX of Brain", Michael Bidollahkhany said. == Applications == The OVC application areas include: 2D and 3D feature toolkits Egomotion estimation Human–computer interaction (HCI) Mobile robotics Motion understanding Object identification Segmentation and recognition Stereopsis stereo vision: depth perception from two cameras Structure from motion (SFM) Motion tracking == Programming language == In first initial release of Objective Visionary Project the algorithm has been written in C++ and C#, and the virtual laboratory has been developed in C# and Delphi. Based on developers last lecture since the second release the complete algorithm has been re-written in C# based on .Net Core 1.0 to make it easier to work on different operating systems.

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  SCADA Strangelove

  SCADA Strangelove is an independent group of information security researchers founded in 2012, focused on security assessment of industrial control systems (ICS) and SCADA. == Activities == Main fields of research include: Discovery of 0-day vulnerabilities in cyber physical systems and coordinated vulnerability disclosure; Security assessment of ICS protocols and development suites; Identification of publicly Internet-connected ICS components and secure it with help of proper authorities; Development of security hardening guides for ICS software; Mapping cybersecurity on to functional safety; Awareness control and delivery of information regarding the actual security state of ICS systems. SCADA Strangelove's interests expand further than classic ICS components and covers various embedded systems, however, and encompass smart home components, solar panels, wind turbines, SmartGrid as well as other areas. == Projects == Group members have and continue to develop and publish numerous open source tools for scanning, fingerprinting, security evaluation and password bruteforcing for ICS devices. These devices work over industrial protocols such as modbus, Siemens S7, MMS, ISO EC 60870, ProfiNet. In 2014 Shodan used some of the published tools for building a map of ICS devices which is publicly available on the Internet. Open source security assessment frameworks, such as THC Hydra, Metasploit, and DigitalBond Redpoint have used Shodan-developed tools and techniques. The group has published security-hardening guidelines for industrial solutions based on Siemens SIMATIC WinCC and WinCC Flexible. The guidelines contain detailed security configuration walk-throughs, descriptions of internal security features and appropriate best practices. Among the group’s more noticeable projects is Choo Choo PWN (CCP) also named the Critical Infrastructure Attack (CIA). This is an interactive laboratory built upon ICS software and hardware used in real world. Every system is connected to a toy city infrastructure, which includes factories, railroads and other facilities. The laboratory has been demonstrated at various conferences including PHDays, Power of Community, and 30C3. Primarily the laboratory is used for the discovery of new vulnerabilities and for evaluation of security mechanisms, however it is also used for workshops and other educational activities. At Positive Hack Days IV, contestants found several 0-day vulnerabilities in Indusoft Web Studio 7.1 by Schneider Electric, and in specific ICS hardware RTU PET-7000 during the ICS vulnerability discovery challenge. The group supports Secure Open SmartGrid (SCADASOS) project to find and fix vulnerabilities in intellectual power grid components such as photovoltaic power station, wind turbine, power inverter. More than 80 000 industrial devices were discovered and isolated from the Internet in 2015. == Appearances == Group members are frequently seen presenting at conferences like CCC, SCADA Security Scientific Symposium, Positive Hack Days. Most notable talks are: === 29C3 === An overview of vulnerabilities discovered in the widely distributed Siemens SIMATIC WinCC software and tools that are implemented for searching ICS on the Internet. === PHDays === This talk consisted of an overview of vulnerabilities discovered in various systems produced by ABB, Emerson, Honeywell and Siemens and was presented at PHDays III and PHDays IV. === Confidence 2014 === Implications of security research aimed at realization of various industrial network protocols Profinet, Modbus, DNP3, IEC 61850-8-1 (MMS), IEC (International Electrotechnical Commission) 61870-5-101/104, FTE (Fault Tolerant Ethernet), Siemens S7. === PacSec 2014 === Presentations of security research showing the impact of radio and 3G/4G networks on the security of mobile devices as well as on industrial equipment. === 31C3 === Analysis of security architecture and implementation of the most wide spread platforms for wind and solar energy generation which produce many gigawatts of it. === 32C3 === Cybersecurity assessment of railway signaling systems such as Automatic Train Control (ATC), Computer-based interlocking (CBI) and European Train Control System (ETCS). === China Internet Security Conference 2016 === In "Greater China Cyber Threat Landscape" keynote by Sergey Gordeychik an overview of vulnerabilities, attacks and cyber-security incidents in Greater China region was presented. === Recon 2017 === In talk "Hopeless: Relay Protection for Substation Automation" by Kirill Nesterov and Alexander Tlyapov security analysis results of key Digital Substation component - Relay Protection Terminals was presented. Vulnerabilities, including remote code execution in Siemens SIPROTEC, General Electric Line Distance Relay, NARI and ABB protective relays was presented. == Philosophy == All names, catchwords and graphical elements refer to Stanley Kubrick’s film, Dr. Strangelove. In their talks, group members often refer to Cold War events such as the Caribbean Crisis, and draw parallels between nuclear arms race and the current escalation of cyberwar. Group members follow the approach of “responsible disclosure” and “ready to wait for years, while vendor is patching the vulnerability”. Public exploits for discovered vulnerabilities are not published. This is on account of the longevity of ICS and by implication the long process of patching ICS. However, conflicts still happen, notably in 2012 when the talk at DEF CON was called off due to a dispute of persistent weaknesses in Siemens industrial software.

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  E-on Vue

  Vue is a software tool for world generation by Bentley Systems, with support for many visual effects, animations, and various other features. The tool has been used in several feature-length films. In 2024, Bentley Systems announced that Vue would be discontinued, and be freely available to those that still wish to use it. == Versions == == Features == This is a list of features as of the 2023 release of Vue: === Terrains === Heightfield terrains Procedural terrains Infinite terrains Planetary terrains Real-world terrains 3D terrain sculpting Terrain export === EcoSystem Instancing Technology === Material-based EcoSystems Global EcoSystems Dynamic EcoSystems 360° EcoSystem Population Paint EcoSystem instances EcoParticles Export EcoSystem populations === Vegetation === Built-in Plant editor Compatible with PlantFactory Vegetation assets === Atmosphere, Skies and Clouds === Standard atmospheric model Spectral atmospheric model Photometric atmospheric model Atmosphere presets Procedural Volumetric 3D cloud layers Standalone 3D Metaclouds Convert meshes to Clouds Cloud morphing Import OpenVDB Export standalone and cloud layer zones to OpenVDB Export skies as HDRI === Modeling === Primitive and Feature modeling 3D Text edition tool Metablobbing Hyperblobs Export baked hyperblobs Splines Built in Road Construction toolkit Random rock generator Export rocks === Texturing and UVs === Material presets PBR Substance support Node-based procedural materials Volumetric materials and Hypertextures Stacked UVs Unwrapped UVs Ptex === Interoperability, Integration And Export === Export single assets to generic 3D formats Full scene export Integration plugins Import and Export Camera data as FBX and Nuke.chan Python API ZBrush GoZ bridge === Animation === Animate objects, materials, atmospheres, clouds, waves... Automatic wind and breeze Localized wind effects per plant / per EcoSystem population Omni and directional ventilators for local modifications of plants Time spline editor Automatic keyframe creation Automatic synchronization of cameras and lights Animation export as AfterEffects Import motion tracking information === Lighting === Global illumination, Global Radiosity, Ambient occlusion Subsurface Scattering HDRI image based lighting Point light, Quadratic point light, Spotlight, Quadratic spotlight, Directional light Use IES distribution profiles on photometric lights Area lights, light panels, light portals Physically accurate caustics computation === Rendering === Render with Ray Tracer Render with Path Tracer Stereoscopic rendering 360/180 VR Panorama Render Option Spherical panoramic rendering Tone mapping options Multipass & G-Buffer Network rendering with HyperVue / RenderCows Network rendering with RenderNodes == Users == Blue Sky Studios Digital Domain DreamWorks Animation: Kung Fu Panda Industrial Light & Magic: Indiana Jones and the Kingdom of the Crystal Skull, Pirates of the Caribbean: Dead Man's Chest Sony Pictures Imageworks Warner Bros. Interactive Entertainment Weta Digital

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  Universal IR Evaluation

  In computer science, Universal IR Evaluation (information retrieval evaluation) aims to develop measures of database retrieval performance that shall be comparable across all information retrieval tasks. == Measures of "relevance" == IR (information retrieval) evaluation begins whenever a user submits a query (search term) to a database. If the user is able to determine the relevance of each document in the database (relevant or not relevant), then for each query, the complete set of documents is naturally divided into four distinct (mutually exclusive) subsets: relevant documents that are retrieved, not relevant documents that are retrieved, relevant documents that are not retrieved, and not relevant documents that are not retrieved. These four subsets (of documents) are denoted by the letters a, b, c, d respectively and are called Swets variables, named after their inventor. In addition to the Swets definitions, four relevance metrics have also been defined: Recall refers to the fraction of relevant documents that are retrieved (a/(a+b)), and Precision refers to the fraction of retrieved documents that are relevant (a/(a+c)). These are the most commonly used and well-known relevance metrics found in the IR evaluation literature. Two less commonly used metrics include the Fallout, i.e., the fraction of not relevant documents that are retrieved (b/(b+d)), and the Miss, which refers to the fraction of relevant documents that are not retrieved (c/(c+d)) during any given search. == Universal IR evaluation techniques == Universal IR evaluation addresses the mathematical possibilities and relationships among the four relevance metrics Precision, Recall, Fallout and Miss, denoted by P, R, F and M, respectively. One aspect of the problem involves finding a mathematical derivation of a complete set of universal IR evaluation points. The complete set of 16 points, each one a quadruple of the form (P, R, F, M), describes all the possible universal IR outcomes. For example, many of us have had the experience of querying a database and not retrieving any documents at all. In this case, the Precision would take on the undetermined form 0/0, the Recall and Fallout would both be zero, and the Miss would be any value greater than zero and less than one (assuming a mix of relevant and not relevant documents were in the database, none of which were retrieved). This universal IR evaluation point would thus be denoted by (0/0, 0, 0, M), which represents only one of the 16 possible universal IR outcomes. The mathematics of universal IR evaluation is a fairly new subject since the relevance metrics P, R, F, M were not analyzed collectively until recently (within the past decade). A lot of the theoretical groundwork has already been formulated, but new insights in this area await discovery.

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  Threat actor

  In cybersecurity and risk assessment, a threat actor (or threat agents, attackers, or adversaries) is a person, group, organisation, state, or other entity with the ability to cause, carry, transmit, support, or exploit a threat. Threat actors are commonly analysed according to their motivations, resources, technical capability, access to systems, relationship to a target, and degree of connection to state authority. They may exploit vulnerabilities, conduct social engineering, steal or monetise data, disrupt operations, or support other actors who carry out such activity. Because the term covers a wide range of actors, researchers and security organisations use taxonomies that distinguish between groups such as cybercriminals, state-linked actors, ideologically motivated actors, thrill seekers or trolls, insiders, and competitors. Threat actor classifications are used in risk management, cyber threat intelligence, and incident response to connect observed behaviour with possible objectives and likely future activity. The categories are not always mutually exclusive: the same actor may combine criminal, ideological, commercial, or state-linked motivations, and different organisations may use different names for similar actors. == Risk assessment and security management == In risk assessment, threat actor analysis is used to identify who or what may create, carry, transmit, support, or exploit a threat, and how that actor relates to the system being assessed. Rausand and Haugen classify threat actors by their relationship to the system, distinguishing between internal and external actors, and by intent, distinguishing between intentional and unintentional actors. Threat actor classification may also support incident investigation. Rogers argued that actor categories could be inferred from observable case points, such as tools used, messages left, data targeted, forensic knowledge, and the degree of damage, allowing investigators to assess likely motivation and skill level. Later work similarly linked actor classification to operational analysis. Chng, Lu, Kumar and Yau proposed a framework connecting hacker types, motivations and typical strategies, arguing that observed behaviour before or during an attack can help analysts infer the likely type of actor involved. At the strategic level, actor analysis may consider an actor's resources, capabilities, degree of state involvement, motivations and objectives. == Landscape == The United Nations Institute for Disarmament Research has described the contemporary cyberthreat landscape as involving an increasingly diverse and interconnected set of actors, including state-led operations, cybercriminal syndicates, ideological hacktivists, commercial cyber mercenaries, private companies and civilian volunteers. Its 2026 report argued that these actors vary in resources, technical sophistication and relationships with states, making it traditional distinctions between state, civilian combatant roles, and legitimate and illegitimate conduct harder to apply. == Academic taxonomies == Early taxonomies classified hackers by activity, skill, motivation, or criminal profile. Landreth proposed six categories based on activity: novice, student, tourist, crasher, and thief. Hollinger classified computer misuse into pirates, browsers, and crackers, describing a progression from less-skilled activity to more technically serious offences. Chantler used attributes including activity, skill, knowledge, motivation, and duration of involvement to distinguish between an elite group, neophytes, and "losers and lamers". Parker proposed seven profiles of cybercriminals: pranksters, hacksters, malicious hackers, personal problem solvers, career criminals, extreme advocates, and malcontents, addicts, and irrational or incompetent people. In 2000, Marc Rogers proposed a taxonomy of hackers with seven, non-mutually-exclusive categories: newbie/tool kit users, cyber-punks, internals, coders, old guard hackers, professional criminals, and cyber-terrorists. Rausand and Haugen distinguish between internal and external threat actors, and between intentional and unintentional threat actors. Internal actors have some relationship with, access to, or position inside the system or organisation, while external actors operate from outside it. Intentional actors seek to create, exploit, or support a threat event, whereas unintentional actors may cause or enable a threat event through error, negligence, accident, or lack of awareness. Rogers later revised his hacker taxonomy into Novices, Cyber-punks, Internals, Petty Thieves, Virus Writers, Old Guard hackers, Professional Criminals, Information Warriors, and, more tentatively, Political Activists. In the model, motivation is grouped into four broad domains: curiosity, notoriety, revenge, and financial gain. A 2022 review by Chng, Lu, Kumar and Yau examined 11 hacker typologies published over three decades and proposed a unified framework linking hacker types, motivations, and strategies. The framework identified 13 hacker types and seven motivations, and argued that observed strategies during an attack can help analysts infer the likely type of actor involved. == Government taxonomies == Taxonomies of threat actors by governments are much more likely to include state-level threat actors. In the United States the National Institute of Standards and Technology (NIST) uses the term threat source in its risk-assessment guidance: organisations are directed to identify and characterise threat sources of concern, including capability, intent and targeting for adversarial threat sources, and the range of effects for non-adversarial threat sources. NIST treats threat-source identification as part of the risk-assessment process, alongside identifying threat events, vulnerabilities, likelihood and impact. In the EU, European Union Agency for Cybersecurity publishes the annual ENISA Threat Landscape, which analyses cyber incidents and adversary behaviour affecting the European Union. The 2025 report analysed selected incidents from the previous year and grouped activity around cybercrime, state-aligned activity, foreign information manipulation and interference, and hacktivism. In ENISA's 2025 analysis, hacktivist activity dominated reporting, representing almost 80% of recorded incidents and consisting mainly of low-level distributed denial-of-service operations. ENISA also reported increasing convergence between hacktivism, cybercrime and state-nexus activity, including state-aligned use of hacktivist personas, hacktivist adoption of ransomware, and false-flag or impersonation activity. At the UN level, A 2026 report by the United Nations Institute for Disarmament Research described the cyberthreat landscape as involving state-led operations, cybercriminal syndicates, ideological hacktivists, commercial cyber mercenaries, and civilian volunteers, with actors varying in resources, technical sophistication, and links to states. Canada defines threat actors as states, groups, or individuals who aim to cause harm by exploiting a vulnerability with malicious intent. A threat actor must be trying to gain access to information systems to access or alter data, devices, systems, or networks. The Japanese government's National Centre of Incident Readiness and Strategy (NISC) was established in 2015 to create a "free, fair and secure cyberspace" in Japan. The NICS created a cybersecurity strategy in 2018 that outlines nation-states and cybercrime to be some of the most key threats. It also indicates that terrorist usage of the cyberspace needs to be monitored and understood. The Security Council of the Russian Federation published the cyber security strategy doctrine in 2016. This strategy highlights the following threat actors as a risk to cyber security measures: nation-state actors, cyber criminals, and terrorists. == Techniques == Threat actors use techniques like Social engineering (security), and Phishing, alongside technical exploits like Cross-site scripting, SQL injection, and denial-of-service attacks. == Limitations == In practice, actor categories may overlap (Edward Snowden for example), and the same activity may combine features associated with hacktivism, cybercrime and state-linked operations. The lines between hacktivism, cybercrime and state-nexus activity had continued to blur, with shared toolsets, overlapping methods, fake personas, hacktivist adoption of ransomware, and cybercriminal or state-linked actors masquerading as other groups. Threat actor analysis also has limits as a risk-management method. NIST notes that risk assessments depend on their purpose, scope, assumptions, constraints, information sources, risk model and analytic approach, and that assessments are tied to particular time frames and organisational contexts. NIST also warns that simple threat-vulnerability pairing may be undesirable or problematic where there are many threats and vulnerabilities, and recom

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  Public computer

  A public computer (or public access computer) is any of various computers available in public areas. Some places where public computers may be available are libraries, schools, or dedicated facilities run by government. Public computers share similar hardware and software components to personal computers, however, the role and function of a public access computer is entirely different. A public access computer is used by many different untrusted individuals throughout the course of the day. The computer must be locked down and secure against both intentional and unintentional abuse. Users typically do not have authority to install software or change settings. A personal computer, in contrast, is typically used by a single responsible user, who can customize the machine's behavior to their preferences. Public access computers are often provided with tools such as a PC reservation system to regulate access. The world's first public access computer center was the Marin Computer Center in California, co-founded by David and Annie Fox in 1977. == Kiosks == A kiosk is a special type of public computer using software and hardware modifications to provide services only about the place the kiosk is in. For example, a movie ticket kiosk can be found at a movie theater. These kiosks are usually in a secure browser with zero access to the desktop. Many of these kiosks may run Linux, however, ATMs, a kiosk designed for depositing money, often run Windows XP. == Public computers in the United States == === Library computers === In the United States and Canada, almost all public libraries have computers available for the use of patrons, though some libraries will impose a time limit on users to ensure others will get a turn and keep the library less busy. Users are often allowed to print documents that they have created using these computers, though sometimes for a small fee. ==== Privacy ==== Privacy is an important part of the public library institution, since the libraries entitle the public to intellectual freedom. Use of any computer or network may create records of users' activities that can jeopardize their privacy. It is possible for a patron to jeopardize their privacy if they do not delete cache, clear cookies, or documents from the public computer. In order for a member of the public to remain private on a computer, the American Library Association (ALA) has guidelines. These give patrons an idea of the right way to keep using public library computers. In their provision of services to library users, librarians have an ethical responsibility, expressed in the ALA Code of Ethics, to preserve users' right to privacy. A librarian is also responsible for giving users an understanding of private patron use and access. Libraries must ensure that users have the following rights when browsing on public computers: the computer automatically will clear a users history; libraries should display privacy screens so users do not see another patron's screen; updating software for effective safety measures; restoration data software to clear documents that users may have left on their computers and to combat possible malware; security practices; and making users aware of any possible monitoring of their browsing activities. Users can also view the Library Privacy Checklist for Public Access Computers and Networks to better understand what libraries strive for when protecting privacy. === School computers === The U.S. government has given money to many school boards to purchase computers for educational applications. Schools may have multiple computer labs, which contain these computers for students to use. There is usually Internet access on these machines, but some schools will put up a blocking service to limit the websites that students are able to access to only include educational resources, such as Google. In addition to controlling the content students are viewing, putting up these blocks can also help to keep the computers safe by preventing students from downloading malware and other threats. However, the effectiveness of such content filtering systems is questionable since it can easily be circumvented by using proxy websites, Virtual Private Networks, and for some weak security systems, merely knowing the IP address of the intended website is enough to bypass the filter. School computers often have advanced operating system security to prevent tech-savvy students from inflicting damage (i.e. the Windows Registry Editor and Task Manager, etc.) are disabled on Microsoft Windows machines. Schools with very advanced tech services may also install a locked down BIOS/firmware or make kernel-level changes to the operating system, precluding the possibility of unauthorized activity.

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  Texture atlas

  In computer graphics, a texture atlas (also called a spritesheet or an image sprite in 2D game development) is an image containing multiple smaller images, usually packed together to reduce overall dimensions. An atlas can consist of uniformly-sized images or images of varying dimensions. A sub-image is drawn using custom texture coordinates to pick it out of the atlas. == Benefits == In an application where many small textures are used frequently, it is often more efficient to store the textures in a texture atlas which is treated as a single unit by the graphics hardware. This reduces both the disk I/O overhead and the overhead of a context switch by increasing memory locality. Careful alignment may be needed to avoid bleeding between sub textures when used with mipmapping and texture compression. In web development, images are packed into a sprite sheet to reduce the number of image resources that need to be fetched in order to display a page. == Gallery ==

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