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  Visual Turing Test

  The Visual Turing Test is “an operator-assisted device that produces a stochastic sequence of binary questions from a given test image”. The query engine produces a sequence of questions that have unpredictable answers given the history of questions. The test is only about vision and does not require any natural language processing. The job of the human operator is to provide the correct answer to the question or reject it as ambiguous. The query generator produces questions such that they follow a “natural story line”, similar to what humans do when they look at a picture. == History == Research in computer vision dates back to the 1960s when Seymour Papert first attempted to solve the problem. This unsuccessful attempt was referred to as the Summer Vision Project. The reason why it was not successful was because computer vision is more complicated than what people think. The complexity is in alignment with the human visual system. Roughly 50% of the human brain is devoted in processing vision, which indicates that it is a difficult problem. Later there were attempts to solve the problems with models inspired by the human brain. Perceptrons by Frank Rosenblatt, which is a form of the neural networks, was one of the first such approaches. These simple neural networks could not live up to their expectations and had certain limitations due to which they were not considered in future research. Later with the availability of the hardware and some processing power the research shifted to image processing which involves pixel-level operations, like finding edges, de-noising images or applying filters to name a few. There was some great progress in this field but the problem of vision which was to make the machines understand the images was still not being addressed. During this time the neural networks also resurfaced as it was shown that the limitations of the perceptrons can be overcome by Multi-layer perceptrons. Also in the early 1990s convolutional neural networks were born which showed great results on digit recognition but did not scale up well on harder problems. The late 1990s and early 2000s saw the birth of modern computer vision. One of the reasons this happened was due to the availability of key, feature extraction and representation algorithms. Features along with the already present machine learning algorithms were used to detect, localise and segment objects in Images. While all these advancements were being made, the community felt the need to have standardised datasets and evaluation metrics so the performances can be compared. This led to the emergence of challenges like the Pascal VOC challenge and the ImageNet challenge. The availability of standard evaluation metrics and the open challenges gave directions to the research. Better algorithms were introduced for specific tasks like object detection and classification. Visual Turing Test aims to give a new direction to the computer vision research which would lead to the introduction of systems that will be one step closer to understanding images the way humans do. == Current evaluation practices == A large number of datasets have been annotated and generalised to benchmark performances of difference classes of algorithms to assess different vision tasks (e.g., object detection/recognition) on some image domain (e.g., scene images). One of the most famous datasets in computer vision is ImageNet which is used to assess the problem of object level Image classification. ImageNet is one of the largest annotated datasets available and has over one million images. The other important vision task is object detection and localisation which refers to detecting the object instance in the image and providing the bounding box coordinates around the object instance or segmenting the object. The most popular dataset for this task is the Pascal dataset. Similarly there are other datasets for specific tasks like the H3D dataset for human pose detection, Core dataset to evaluate the quality of detected object attributes such as colour, orientation, and activity. Having these standard datasets has helped the vision community to come up with well performing algorithms for all these tasks. The next logical step is to create a larger task encompassing of these smaller subtasks. Having such a task would lead to building systems that would understand images, as understanding images would inherently involve detecting objects, localising them and segmenting them. == Details == The Visual Turing Test (VTT) unlike the Turing test has a query engine system which interrogates a computer vision system in the presence of a human co-ordinator. It is a system that generates a random sequence of binary questions specific to the test image, such that the answer to any question k is unpredictable given the true answers to the previous k − 1 questions (also known as history of questions). The test happens in the presence of a human operator who serves two main purposes: removing the ambiguous questions and providing the correct answers to the unambiguous questions. Given an Image infinite possible binary questions can be asked and a lot of them are bound to be ambiguous. These questions if generated by the query engine are removed by the human moderator and instead the query engine generates another question such that the answer to it is unpredictable given the history of the questions. The aim of the Visual Turing Test is to evaluate the Image understanding of a computer system, and an important part of image understanding is the story line of the image. When humans look at an image, they do not think that there is a car at ‘x’ pixels from the left and ‘y’ pixels from the top, but instead they look at it as a story, for e.g. they might think that there is a car parked on the road, a person is exiting the car and heading towards a building. The most important elements of the story line are the objects and so to extract any story line from an image the first and the most important task is to instantiate the objects in it, and that is what the query engine does. === Query engine === The query engine is the core of the Visual Turing Test and it comprises two main parts : Vocabulary and Questions ==== Vocabulary ==== Vocabulary is a set of words that represent the elements of the images. This vocabulary when used with appropriate grammar leads to a set of questions. The grammar is defined in the next section in a way that it leads to a space of binary questions. The vocabulary V {\displaystyle {\mathcal {V}}} consist of three components: Types of Objects T {\displaystyle {\mathcal {T}}} Type-dependent attributes of objects A ( t ) {\displaystyle {\mathcal {A}}(t)} Type-dependent relationships between two objects R ( t , t ′ ) {\displaystyle {\mathcal {R}}(t,t')} For Images of urban street scenes the types of objects include people, vehicle and buildings. Attributes refer to the properties of these objects, for e.g. female, child, wearing a hat or carrying something, for people and moving, parked, stopped, one tire visible or two tires visible for vehicles. Relationships between each pair of object classes can be either “ordered” or “unordered”. The unordered relationships may include talking, walking together and the ordered relationships include taller, closer to the camera, occluding, being occluded etc. Additionally all of this vocabulary is used in context of rectangular image regions w \in W which allow for the localisation of objects in the image. An extremely large number of such regions are possible and this complicates the problem, so for this test, regions at specific scales are only used which include 1/16 the size of image, 1/4 the size of image, 1/2 the size of image or larger. ==== Questions ==== The question space is composed of four types of questions: Existence questions: The aim of the existence questions is to find new objects in the image that have not been uniquely identified previously. They are of the form : Qexist = 'Is there an instance of an object of type t with attributes A partially visible in region w that was not previously instantiated?' Uniqueness questions: A uniqueness question tries to uniquely identify an object to instantiate it. Quniq = 'Is there a unique instance of an object of type t with attributes A partially visible in region w that was not previously instantiated?' The uniqueness questions along with the existence questions form the instantiation questions. As mentioned earlier instantiating objects leads to other interesting questions and eventually a story line. Uniqueness questions follow the existence questions and a positive answer to it leads to instantiation of an object. Attribute questions: An attribute question tries to find more about the object once it has been instantiated. Such questions can query about a single attribute, conjunction of two attributes or disjunction of two attributes. Qatt(ot) = {'Does object ot have attribute a?' , 'Does object

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  Hardware trojan

  A hardware trojan (HT) is a malicious modification of the circuitry of an integrated circuit. A hardware trojan is completely characterized by its physical representation and its behavior. The payload of an HT is the entire activity that the Trojan executes when it is triggered. In general, trojans try to bypass or disable the security fence of a system: for example, leaking confidential information by radio emission. HTs also could disable, damage or destroy the entire chip or components of it. Hardware trojans may be introduced as hidden front-doors that are inserted while designing a computer chip, by using a pre-made application-specific integrated circuit (ASIC) semiconductor intellectual property core (IP core) that have been purchased from a non-reputable source, or inserted internally by a rogue employee, either acting on their own, or on behalf of rogue special interest groups, or state sponsored spying and espionage. One paper published by IEEE in 2015 explains how a hardware design containing a trojan could leak a cryptographic key leaked over an antenna or network connection, provided that the correct "easter egg" trigger is applied to activate the data leak. In high security governmental IT departments, hardware trojans are a well known problem when buying hardware such as: a KVM switch, keyboards, mice, network cards, or other network equipment. This is especially the case when purchasing such equipment from non-reputable sources that could have placed hardware trojans to leak keyboard passwords, or provide remote unauthorized entry. == Background == In a diverse global economy, outsourcing of production tasks is a common way to lower a product's cost. Embedded hardware devices are not always produced by the firms that design and/or sell them, nor in the same country where they will be used. Outsourced manufacturing can raise doubt about the evidence for the integrity of the manufactured product (i.e., one's certainty that the end-product has no design modifications compared to its original design). Anyone with access to the manufacturing process could, in theory, introduce some change to the final product. For complex products, small changes with large effects can be difficult to detect. The threat of a serious, malicious, design alteration can be especially relevant to government agencies. Resolving doubt about hardware integrity is one way to reduce technology vulnerabilities in the military, finance, energy and political sectors of an economy. Since fabrication of integrated circuits in untrustworthy factories is common, advanced detection techniques have emerged to discover when an adversary has hidden additional components in, or otherwise sabotaged, the circuit's function. == Characterization of hardware trojans == An HT can be characterized by several methods such as by its physical representation, activation phase and its action phase. Alternative methods characterize the HT by trigger, payload and stealth. === Physical characteristics === One of this physical trojan characteristics is the type. The type of a trojan can be either functional or parametric. A trojan is functional if the adversary adds or deletes any transistors or gates to the original chip design. The other kind of trojan, the parametric trojan, modifies the original circuitry, e.g. thinning of wires, weakening of flip-flops or transistors, subjecting the chip to radiation, or using focused ion-beams (FIB) to reduce the reliability of a chip. The size of a trojan is its physical extension or the number of components it is made of. Because a trojan can consist of many components, the designer can distribute the parts of a malicious logic on the chip. The additional logic can occupy the chip wherever it is needed to modify, add, or remove a function. Malicious components can be scattered, called loose distribution, or consist of only few components, called tight distribution, so the area is small where the malicious logic occupies the layout of the chip. In some cases, high-effort adversaries in may regenerate the layout so that the placement of the components of the IC is altered. In rare cases the chip dimension is altered. These changes are structural alterations. === Activation characteristics === The typical trojan is condition-based: It is triggered by sensors, internal logic states, a particular input pattern or an internal counter value. Condition-based trojans are detectable with power traces to some degree when inactive. That is due to the leakage currents generated by the trigger or counter circuit activating the trojan. Hardware trojans can be triggered in different ways. A trojan can be internally activated, which means it monitors one or more signals inside the IC. The malicious circuitry could wait for a count down logic an attacker added to the chip, so that the trojan awakes after a specific time-span. The opposite is externally activated. There can be malicious logic inside a chip, that uses an antenna or other sensors the adversary can reach from outside the chip. For example, a trojan could be inside the control system of a cruising missile. The owner of the missile does not know, that the enemy will be able to switch off the rockets by radio. A trojan which is always-on can be a reduced wire. A chip that is modified in this way produces errors or fails every time the wire is used intensely. Always-on circuits are hard to detect with power trace. In this context combinational trojans and sequential trojans are distinguished. A combinational trojan monitors internal signals until a specific condition happens. A sequential trojan is also an internally activated condition-based circuit, but it monitors the internal signals and searches for sequences not for a specific state or condition like the combinational trojans do. ==== Cryptographic key extraction ==== Extraction of secret keys by means of a hardware trojan without detecting the trojan requires that the trojan uses a random signal or some cryptographic implementation itself. To avoid storing a cryptographic key in the trojan itself and reduction, a physical unclonable function can be used. Physical unclonable functions are small in size and can have an identical layout while the cryptographic properties are different. === Action characteristics === A HT could modify the chip's function or could change the chip's parametric properties (e.g. provokes a process delay). Confidential information can also be transmitted to the adversary (transmission of key information). === Peripheral device hardware trojans === A relatively new threat vector to networks and network endpoints is a HT appearing as a physical peripheral device that is designed to interact with the network endpoint using the approved peripheral device's communication protocol. For example, a USB keyboard that hides all malicious processing cycles from the target network endpoint to which it is attached by communicating with the target network endpoint using unintended USB channels. Once sensitive data is ex-filtrated from the target network endpoint to the HT, the HT can process the data and decide what to do with the data: store the data to memory for later physical retrieval of the HT or possibly ex-filtrate the data to the internet using wireless or using the compromised network endpoint as a pivot. == Potential of threat == A common trojan is passive most of the time-span an altered device is in use. If a trojan is activated the device functionality can be changed, the device can be destroyed or disabled, the device can leak confidential information or the HT may tear down the security and safety of the device. Trojans are stealthy, to avoid detection of the trojan the precondition for activation is a very rare event. Traditional testing techniques are not sufficient. A manufacturing fault happens at a random position while malicious changes are well placed to avoid detection. == Detection == === Physical inspection === First, the molding coat is cut to reveal the circuitry. Then, the engineer repeatedly scans the surface while grinding the layers of the chip. There are several operations to scan the circuitry. Typical visual inspection methods are: scanning optical microscopy (SOM), scanning electron microscopy (SEM), pico-second imaging circuit analysis (PICA), voltage contrast imaging (VCI), light induced voltage alteration (LIVA) or charge induced voltage alteration (CIVA). To compare the floor plan of the chip has to be compared with the image of the actual chip. This is still quite challenging to do. To detect Trojan hardware which include (crypto) keys which are different, an image diff can be taken to reveal the different structure on the chip. The only known hardware Trojan using unique crypto keys but having the same structure is. This property enhances the undetectability of the trojan. === Functional testing === This detection method stimulates the input ports of a chip and monitors the output

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  Commercial skipping

  Commercial skipping is a feature of some digital video recorders that makes it possible to automatically skip commercials in recorded programs. This feature created controversy, with major television networks and movie studios claiming it violates copyright and should be banned. == History == After the video cassette recorder (VCR) became popular in the 1980s, the television industry began studying the impact of users fast forwarding through commercials. Advertising agencies fought the trend by making them more entertaining. For many years, video recorders manufactured for the Japanese market have been able to skip advertisements automatically, which is done by detecting when foreign language audio overdub tracks provided for many programmes go silent, as advertisements were broadcast with a single language only. The first digital video recorder (DVR) with a built-in commercial skipping feature was ReplayTV with its "4000 Series" and "5000 Series" units. In 2002, the main television networks and movie studios sued ReplayTV, claiming that skipping advertisements during replay violates copyright. Later, five owners of ReplayTV represented by Electronic Frontier Foundation and attorneys Ira Rothken and Richard Wiebe countersued, asking the federal judge to uphold consumers' rights to record TV shows and skip commercials, claiming that features like commercial skipping help parents protect their kids from excessive consumerism. ReplayTV ended up filing for bankruptcy in 2003 after fighting a copyright infringement suit over the ReplayTV's ability to skip commercials. === Commercial skipping software === In addition to the DVR devices which existed in the private market since the late 1990s, towards the mid-2000s, due to the significant advances in home computers, Home theater PCs started gaining popularity in the private market and many users began using their Home theater PCs in their living room for entertainment purposes. Following this, many DVR programs were developed, including popular programs such as Windows Media Center, which contained all of the features of the DVR devices in addition to advanced features such as HDTV and the use of Multiple TV Tuner Cards. Some independent developers began developing independent software capable of skipping the commercial segments when playing recorded videos, and permanently removing the commercial segments from recorded video files. By 2014, many DVR programs such as Windows Media Center, SageTV and MythTV had the capability to skip commercials segments in recorded TV broadcasts after installing third-party add-ons such as DVRMSToolbox, Comskip and ShowAnalyzer, which use various advanced techniques to locate the commercial segments in the video files and save their locations to text files. The text files can also be fed into programs such as MEncoder or DVRMSToolboxGUI which can delete the commercial segments from the recorded video files. A few third-party tools such as MCEBuddy automate detection and removal/marking of commercials. One of the weaknesses of commercial skippers is that, operating automatically, they may misidentify program material as a commercial. Some programs like MCEBuddy provide the ability to fine-tune commercial detection for groups of files (e.g. by channel or country) and provide tools to manually fine-tune commercial segments for individual files. In May 2012, the US Dish Network began offering a DVR with what it calls AutoHop. The device would automatically skip commercials when displaying programming that the viewer had previously recorded with the PrimeTime Anytime feature. It does not skip ads on any live programs. US broadcasters were angered at the news, and FOX embarked on legal action. Most, but not all, of Fox's claims were dismissed; ultimately an agreement was reached whereby AutoHop would only become available for Fox stations seven days after a program is transmitted; terms of the settlement were not disclosed. == The future of TV advertisements == The introduction of digital video recorders and services with skipping and fast-forward capabilities enables viewers to avoid viewing interruptive advertisements in recorded programs, either manually or automatically. While advertising separate to television shows can be skipped, advertising in TV shows themselves ("product placement") cannot be skipped. Streaming services such as Hulu show shorter advertisements with a countdown timer and tailored to the viewers interests, asking interactive questions like "Is this ad relevant to you?".

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  Digital goods

  Digital goods or e-goods are intangible goods that exist in digital form. Examples are Wikipedia articles; digital media, such as e-books, downloadable music, internet radio, internet television and streaming media; fonts, logos, photos and graphics; digital subscriptions; online ads (as purchased by the advertiser); internet coupons; electronic tickets; electronically treated documentation in many different fields; downloadable software (Digital Distribution) and mobile apps; cloud-based applications and online games; virtual goods used within the virtual economies of online games and communities; community access; workbooks; worksheets; planners; e-learning (online courses); webinars, video tutorials, blog posts; cards; patterns; website themes and templates. == Legal concerns about digital goods == Special legal concerns regarding digital goods include copyright infringement and taxation. Also the question of the ownership (versus licensed use or service only) of purely digital goods is not finally resolved. For instance, the software installers of the digital software distributor gog.com are technically independent to the account but are still subject to the EULA, where a "licensed, not sold" formulation is used. Therefore, it is not clear if the software can be legally used after a hypothetical loss of the account; a question which was also raised before in practice for the similar service Steam. In July 2012, the European Court of Justice ruled in the case UsedSoft GMbH v. Oracle International Corp. that the sale of a software product, either through a physical support or download, constituted a transfer of ownership in EU law, thus the first sale doctrine applies; the ruling thereby breaks the "licensed, not sold" legal theory, but leaves open numerous questions. Therefore, it is also permissible to resell software licenses even if the digital good has been downloaded directly from the Internet, as the first-sale doctrine applied whenever software was originally sold to a customer for an unlimited amount of time, thus prohibiting any software maker from preventing the resale of their software by any of their legitimate owners. The court requires that the previous owner must no longer be able to use the licensed software after the resale, but finds that the practical difficulties in enforcing this clause should not be an obstacle to authorizing resale, as they are also present for software which can be installed from physical supports, where the first-sale doctrine is in force. In several cases, content providers have faced criticism for revoking access to digital goods due to expired licenses or the discontinuation of a product, such as ebooks (which resulted in a lawsuit against Amazon.com, Inc.), digital video (with Sony Interactive Entertainment revoking access to purchased StudioCanal content from its now-defunct PlayStation video store; a similar move involving Warner Bros. Discovery content was averted by an updated license agreement), and video games (such as Ubisoft discontinuing and revoking access to its game The Crew without providing refunds or the ability to redownload the game) In September 2024, the U.S. state of California implemented a consumer protection law that prohibits the use of terms such as "buy" or "purchase" during transactions involving digital goods if there is no way to obtain the purchases in a manner that cannot be revoked by the seller (such as allowing it to be downloaded for permanent, offline access), and requires a disclaimer to be displayed to the customer at the time of purchase.

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  Fyuse

  Fyuse is a spatial photography app which lets users capture and share interactive 3D images. By tilting or swiping one's smartphone, one can view such "fyuses" from various angles — as if one were walking around an object or subject. The app blends photography and video to create an interactive medium and was first published for iOS in April 2014. The Android version was released at the end of 2014. == The app == Fyuse lets users capture panoramas, selfies, and full 360° views of objects and allows one to view captured moments from different angles. It has its own personal gallery, social network and standalone web integration. With the app, Fyusion also created a social networking platform similar to Instagram. Fyuses can be shared, commented on, liked and re-shared to one's followers (called Echoes). One can build a network of followers and with engagement tracking, one can see how many times an image has been interacted with The images can also be saved for private, offline view, or shared to other social networks, like Facebook or Twitter, or embedded on a website where the images can be interacted with by desktop users via dragging the mouse. Furthermore, in the compass tab other fyuses can be discovered using the app's system of tags and categories. One's Fyuse feed is prepopulated with top users, and one can follow people to see when they post a new fyuse. The app will also find one's friends if one signs up with Facebook or connects it with one's Twitter account. To create a fyuse one moves around a person or object with one's phone's camera in one direction or moving/tilting one's phone around while holding one's finger on the screen. By combining photography and video the app allows one to capture moments that one may not have otherwise been able to capture by recording not one moment in time but stitched together little moments. According to Fyusion CEO Radu Rusu, a photo freezes a moment in time, while a video captures moments in a linear timeline — both still flat, when viewed. A fyuse image captures a moment in space, where one can not only see one side of something, but also around it. When it is done rendering, fyuses can also be edited – one can trim the fyuse for length and edit the brightness, contrast, exposure, saturation and sharpness. One can also add a vignette and apply a filters, with options to adjust their intensity. After editing, one can write a description, add hashtags, and tag parts of the fyuse before one can (voluntarily) publish and share it. Version 1.0 has been described as "alpha prototype" and version 2.0 was released on 17 December 2014. Version 3.0 introduced 3D tagging by which users can layer 3D graphic that animate accordingly with each interaction to add some context to the content. Version 4.0 was released on December 21, 2016 for iOS. Since January 2016 (v3.2) the app allows the export of fyuses as Live Photos. The app has also been described as a more sophisticated version of 3D stickers and flip images. == Applications == The app has many applications for e-commerce such as for fashion designers who want to showcase a garment from every angle, or real estate listings and Airbnb-type sites that want to make their rental properties seem as enticing as possible. The app can also be used for interactive art, 360° panoramas and selfies. == History == San Francisco-based Fyusion Inc.'s three founders — Radu B. Rusu, CTO Stefan Holzer, and VP of Engineering Stephen Miller — worked together at Willow Garage, the robotics research lab started by early Google employee Scott Hassan in the area of "personal robotics" — Hassan decided to turn the lab into more of an incubator, suggesting that the members spin off their technologies into consumer-facing enterprises. Rusu first set out with an open-source 3D perception software startup called Open Perception. Fyusion was officially founded in 2013, and soon after Rusu and his cofounders patented the technology for spatial photography. The company closed a seed funding round at the end of May, raising $3.35 million from investors, including an angel investment from Sun Microsystems cofounder Andreas Bechtolsheim. In 2014 the Fyuse team consisted of 13 employees, mostly engineers and designers, recruited from around the globe. In March 2015 the team displayed their app at Katy Perry's premiere for the movie "Prismatic World Tour on Epix" where Perry also took Fyuse for a test run. == Augmented reality == In September 2016 Fyusion unveiled its platform for creating augmented reality content using ones smartphone. It takes the images from ones smartphone and converts them into 3D holographic images, which one can then view on an AR headset. According to Rusu "by making it easy for people to capture their surroundings on any mobile device, [Fyusion is] revolutionizing the way that people view the world around them" and also states that for "AR to be successful, anyone should be able to create content for it" opposed to the current "small number of content creators and an even smaller number of hardware players". According to him "the applications of [Fyusion's] technology for consumers and businesses are incredibly limitless". The platform uses the company's patented 3D spatio-temporal platform that uses advanced sensor fusion, machine learning and computer vision algorithms and part of the platform is built into the Fyuse app. Before committing to releasing a separate consumer product the company intends to wait until the HoloLens device becomes available to the public. Until then any Fyuse representation created using Fyuse is AR ready and will be able to be shown in HoloLens in the future. == Fyuse - Point of No Return == Fyuse - Point of No Return is a science fiction short advert for Fyuse 3.0 in which Fyuse's digital medium is extrapolated into the future. In the film a woman uses a mini scanning-drone to 3D scan a tree with Fyuse and later recreate it as an augmented reality object at another place.

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  GPU switching

  GPU switching is a mechanism used on computers with multiple graphic controllers. This mechanism allows the user to either maximize the graphic performance or prolong battery life by switching between the graphic cards. It is mostly used on gaming laptops which usually have an integrated graphic device and a discrete video card. == Basic components == Most computers using this feature contain integrated graphics processors and dedicated graphics cards that applies to the following categories. === Integrated graphics === Also known as: Integrated graphics, shared graphics solutions, integrated graphics processors (IGP) or unified memory architecture (UMA). This kind of graphics processors usually have much fewer processing units and share the same memory with the CPU. Sometimes the graphics processors are integrated onto a motherboard. It is commonly known as: on-board graphics. A motherboard with on-board graphics processors doesn't require a discrete graphics card or a CPU with graphics processors to operate. === Dedicated graphics cards === Also known as: discrete graphics cards. Unlike integrated graphics, dedicated graphics cards have much more processing units and have its own RAM with much higher memory bandwidth. In some cases, a dedicated graphics chip can be integrated onto the motherboards, B150-GP104 for example. Regardless of the fact that the graphics chip is integrated, it is still counted as a dedicated graphics cards system because the graphics chip is integrated with its own memory. == Theory == Most Personal Computers have a motherboard that uses a Southbridge and Northbridge structure. === Northbridge control === The Northbridge is one of the core logic chipset that handles communications between the CPU, GPU, RAM and the Southbridge. The discrete graphics card is usually installed onto the graphics card slot such as PCI-Express and the integrated graphics is integrated onto the CPU itself or occasionally onto the Northbridge. The Northbridge is the most responsible for switching between GPUs. The way how it works usually has the following process (refer to the Figure 1. on the right): The Northbridge receives input from Southbridge through the internal bus. The Northbridge signals to CPU through the Front-side bus. The CPU runs the task assignment application (usually the graphics card driver) to determine which GPU core to use. The CPU passes down the command to the Northbridge. The Northbridge passes down the command to the according GPU core. The GPU core processes the command and returns the rendered data back to the Northbridge. The Northbridge sends the rendered data back to Southbridge. === Southbridge control === The Southbridge is a set of integrated circuits such Intel's I/O Controller Hub (ICH). It handles all of a computer's I/O functions, such as receiving the keyboard input and outputting the data onto the screen. The way how it usually works usually has two steps: Take in the user input and pass it down to the Northbridge. (Optional) Receive the rendered data from the Northbridge and output it. The reason why the second step can be optional is that sometimes the rendered the data is outputted directly from the discrete graphics card which is located on the graphics card slot so there is no need to output the data through the Southbridge. == Main purpose == GPU switching is mostly used for saving energy by switching between graphic cards. The dedicated graphics cards consume much more power than integrated graphics but also provides higher 3D performances, which is needed for a better gaming and CAD experience. Following is a list of the TDPs of the most popular CPU with integrated graphics and dedicated graphics cards. The dedicated graphics cards exhibit much higher power consumption than the integrated graphics on both platforms. Disabling them when no heavy graphics processing is needed can significantly lower the power consumption. == Technologies == === Nvidia Optimus === Nvidia Optimus™ is a computer GPU switching technology created by Nvidia that can dynamically and seamlessly switch between two graphic cards based on running programs. === AMD Enduro === AMD Enduro™ is a collective brand developed by AMD that features many new technologies that can significantly save power. It was previously named as: PowerXpress and Dynamic Switchable Graphics (DSG). This technology implements a sophisticated system to predict the potential usage need for graphics cards and switch between graphics cards based on predicted need. This technology also introduces a new power control plan that allows the discrete graphics cards consume no energy when idling. == Manufacturers == === Integrated graphics === In personal computers, the IGP (integrated graphics processors) are mostly manufactured by Intel and AMD and are integrated onto their CPUs. They are commonly known as: Intel HD and Iris Graphics - also called HD series and Iris series AMD Accelerated Processing Unit (APU) - also formerly known as: fusion === Dedicated graphics cards === The most popular dedicated graphics cards are manufactured by AMD and Nvidia. They are commonly known as: AMD Radeon Nvidia GeForce == Drivers and OS support == Most common operating systems have built-in support for this feature. However, the users may download the updated drivers from Nvidia or AMD for better experience. === Windows support === Windows 7 has built-in support for this feature. The system automatically switches between GPUs depending on the program that's running. However, the user may switch the GPUs manually through device manager or power manager. === Linux === Modern Linux systems handle hybrid graphics in two parts: power/control for the inactive GPU, and optional render offloading for individual applications. vga_switcheroo (in the kernel since 2.6.34) coordinates power and mux control on systems with multiple GPUs. It was designed primarily for muxed designs (hardware display switch), and on muxless laptops it is typically used only for power control. A display server restart is no longer required for offloading on muxless systems. DRI PRIME (Mesa) enables per-process render offload on muxless systems: an app renders on the discrete GPU and the integrated GPU presents the result. Users can opt in via the DRI_PRIME environment variable (e.g., DRI_PRIME=1) or desktop integration. On GNOME, the switcheroo-control service exposes the discrete GPU to the shell, adding a “Launch using Discrete Graphics Card” entry to app menus on supported systems (Wayland or Xorg), which invokes render offload under the hood. With the proprietary Nvidia driver, render offload is provided as PRIME Render Offload (supported since driver 435.xx). Distributions commonly ship a helper like prime-run or desktop menu entries that set the required environment for offloading. ==== Notes and limitations (Linux) ==== On muxless systems the internal display is hard-wired to the integrated GPU; the discrete GPU cannot directly drive that panel and instead renders offscreen for composition by the iGPU. External displays connected to the dGPU may allow direct output depending on the laptop’s wiring. Power-saving behavior varies by driver and distro defaults. Some setups need explicit configuration to power down the inactive GPU when idle. Desktop integrations (e.g., GNOME's menu item) simply opt an app into offload; they do not "auto-switch" the whole session. Users can still launch apps on either GPU as needed.

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  Digital Cinema Package

  A Digital Cinema Package (DCP) is a collection of digital files used to store and convey digital cinema (DC) audio, image, and data streams. The term was popularized by Digital Cinema Initiatives, LLC in its original recommendation for packaging DC contents. However, the industry tends to apply the term to the structure more formally known as the composition. A DCP is a container format for compositions, a hierarchical file structure that represents a title version. The DCP may carry a partial composition (e.g. not a complete set of files), a single complete composition, or multiple and complete compositions. The composition consists of a Composition Playlist (in XML format) that defines the playback sequence of a set of Track Files. Track Files carry the essence (audio, image, subtitles), which is wrapped using Material eXchange Format (MXF). Track Files must contain only one essence type. Two track files at a minimum must be present in every composition (see SMPTE ST429-2 D-Cinema Packaging – DCP Constraints, or Cinepedia): a track file carrying picture essence, and a track file carrying audio essence. The composition, consisting of a Composition Playlist (CPL) and associated track files, are distributed as a Digital Cinema Package (DCP). A composition is a complete representation of a title version, while the DCP need not carry a full composition. However, as already noted, it is commonplace in the industry to discuss the title in terms of a DCP, as that is the deliverable to the cinema. The Picture Track File essence is compressed using JPEG 2000 and the Audio Track File carries a 24-bit linear PCM uncompressed multichannel WAV file. Encryption may optionally be applied to the essence of a track file to protect it from unauthorized use. The encryption used is AES 128-bit in CBC mode. In practice, there are two versions of composition in use. The original version is called Interop DCP. In 2009, a specification was published by SMPTE (SMPTE ST 429-2 Digital Cinema Packaging – DCP Constraints) for what is commonly referred to as SMPTE DCP. SMPTE DCP is similar but not backwards compatible with Interop DCP, resulting in an uphill effort to transition the industry from Interop DCP to SMPTE DCP. SMPTE DCP requires significant constraints to ensure success in the field, as shown by ISDCF. While legacy support for Interop DCP is necessary for commercial products, new productions are encouraged to be distributed in SMPTE DCP. == Technical specifications == The DCP root folder (in the storage medium) contains a number of files, some used to store the image and audio contents, and some other used to organize and manage the whole playlist. === Picture MXF files === Picture contents may be stored in one or more reels corresponding to one or more MXF files. Each reel contains pictures as MPEG-2 or JPEG 2000 essence, depending on the adopted codec. MPEG-2 is no longer compliant with the DCI specification. JPEG 2000 is the only accepted compression format. Supported frame rates are: SMPTE (JPEG 2000) 24, 25, 30, 48, 50, and 60 fps @ 2K 24, 25, and 30 fps @ 4K 24 and 48 fps @ 2K stereoscopic MXF Interop (JPEG 2000) – Deprecated 24 and 48 fps @ 2K (MXF Interop can be encoded at 25 frame/s but support is not guaranteed) 24 fps @ 4K 24 fps @ 2K stereoscopic MXF Interop (MPEG-2) – Deprecated 23.976 and 24 fps @ 1920 × 1080 Maximum frame sizes are 2048 × 1080 for 2K DC, and 4096 × 2160 for 4K DC. Common formats are: SMPTE (JPEG 2000) Flat (1998 × 1080 or 3996 × 2160), = 1.85:1 aspect ratio Scope (2048 × 858 or 4096 × 1716), ~2.39:1 aspect ratio HDTV (1920 × 1080 or 3840 × 2160), 16:9 aspect ratio (~1.78:1) (although not specifically defined in the DCI specification, this resolution is DCI compliant per section 8.4.3.2). Full (2048 × 1080 or 4096 × 2160) (~1.9:1 aspect ratio, official name by DCI is Full Container. Not widely accepted in cinemas.) MXF Interop (MPEG-2) – Deprecated Full Frame (1920 × 1080) 12 bits per component precision (36 bits total per pixel) XYZ' colorspace; the prime mark indicates gamma encoding (gamma=2.6) Maximum bit rate is 250 Mbit/s (1.3 MBytes per frame at 24 frame per second) === Sound MXF files === Sound contents are also stored in reels corresponding to picture reels in number and duration. In case of multilingual features, separate reels are required to convey different languages. Each file contains linear PCM essence. Sampling rate is 48,000 or 96,000 samples per second Sample precision of 24 bits Linear mapping (no companding) Up to 16 independent channels === Asset map file === List of all files included in the DCP, in XML format. === Composition playlist file === Defines the playback order during presentation. The order is saved in XML format in this file; each picture and sound reel is identified by its UUID. In the following example, a reel is composed by picture and sound: === Packing list file or package key list (PKL) === All files in the composition are hashed and their hash is stored here, in XML format. This file is generally used during ingestion in a digital cinema server to verify if data have been corrupted or tampered with in some way. For example, an MXF picture reel is identified by the following element: The hash value is the Base64 encoding of the SHA-1 checksum. It can be calculated with the command: openssl sha1 -binary "FILE_NAME" | openssl base64 === Volume index file === A single DCP may be stored in more than one medium (e.g., multiple hard disks). The XML file VOLINDEX is used to identify the volume order in the series. == 3D DCP == The DCP format is also used to store stereoscopic (3D) contents for 3D films. In this case, 48 frames exist for every second – 24 frames for the left eye, 24 frames for the right. Depending on the projection system used, the left eye and right eye pictures are either shown alternately (double or triple flash systems) at 48 fps or, on 4k systems, both left and right eye pictures are shown simultaneously, one above the other, at 24 fps. In triple flash systems, active shutter glasses are required whereas optical filtering such as circular polarisation is used in conjunction with passive glasses on polarized systems. Since the maximum bit rate is always 250 Mbit/s, this results in a net 125 Mbit/s for single frame, but the visual quality decrease is generally unnoticeable. == D-Box == D-Box codes for motion controlled seating (labelled as "Motion Data" in the DCP specification), if present, are stored as a monoaural WAV file on Sound Track channel 13. Motion Data tracks are unencrypted and not watermarked. == Creation == Most film producers and distributors rely on digital cinema encoding facilities to produce and quality control check a digital cinema package before release. Facilities follow strict guidelines set out in the DCI recommendations to ensure compatibility with all digital cinema equipment. For bigger studio release films, the facility will usually create a Digital Cinema Distribution Master (DCDM). A DCDM is the post-production step prior to a DCP. The frames are in XYZ TIFF format and both sound and picture are not yet wrapped into MXF files. A DCP can be encoded directly from a DCDM. A DCDM is useful for archiving purposes and also facilities can share them for international re-versioning purposes. They can easily be turned into alternative version DCPs for foreign territories. For smaller release films, the facility will usually skip the creation of a DCDM and instead encode directly from the Digital Source Master (DSM) the original film supplied to the encoding facility. A DSM can be supplied in a multitude of formats and color spaces. For this reason, the encoding facility needs to have extensive knowledge in color space handling including, on occasion, the use of 3D LUTs to carefully match the look of the finished DCP to a celluloid film print. This can be a highly involved process in which the DCP and the film print are "butterflied" (shown side by side) in a highly calibrated cinema. Less demanding DCPs are encoded from tape formats such as HDCAM SR. Quality control checks are always performed in calibrated cinemas and carefully checked for errors. QC checks are often attended by colorists, directors, sound mixers and other personnel to check for correct picture and sound reproduction in the finished DCP. == Accessibility == === Hearing impaired audio === A Hearing Impaired (HI) audio track is designed for people who are hearing-impaired to better hear dialog. Moviegoers can wear headphones which play this audio track synchronized with the film. Hearing Impaired audio is stored in the DCP on Sound Track channel 7. === Audio description === Audio description is narration for people who are blind or visually impaired. Audio description is stored in the DCP as "Visually Impaired-Native" (VI-N) audio on Sound Track channel 8. === Sign Language Video === A Sign Language Video track can be included in a DCP to allow for display of sign la

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  Locative media

  Locative media or location-based media (LBM) is a virtual medium of communication functionally bound to a location. The physical implementation of locative media, however, is not bound to the same location to which the content refers. Location-based media delivers multimedia and other content directly to the user of a mobile device dependent upon their location. Location information determined by means such as mobile phone tracking and other emerging real-time locating system technologies like Wi-Fi or RFID can be used to customize media content presented on the device. Locative media are digital media applied to real places and thus triggering real social interactions. While mobile technologies such as the Global Positioning System (GPS), laptop computers and mobile phones enable locative media, they are not the goal for the development of projects in this field. == Description == Media content is managed and organized externally of the device on a standard desktop, laptop, server, or cloud computing system. The device then downloads this formatted content with GPS or other RTLS coordinate-based triggers applied to each media sequence. As the location-aware device enters the selected area, centralized services trigger the assigned media, designed to be of optimal relevance to the user and their surroundings. Use of locative technologies "includes a range of experimental uses of geo-technologies including location-based games, artistic critique of surveillance technologies, experiential mapping, and spatial annotation." Location based media allows for the enhancement of any given environment offering explanation, analysis and detailed commentary on what the user is looking at through a combination of video, audio, images and text. The location-aware device can deliver interpretation of cities, parklands, heritage sites, sporting events or any other environment where location based media is required. The content production and pre-production are integral to the overall experience that is created and must have been performed with ultimate consideration of the location and the users position within that location. The media offers a depth to the environment beyond that which is immediately apparent, allowing revelations about background, history and current topical feeds. == Locative, ubiquitous and pervasive computing == The term 'locative media' was coined by Karlis Kalnins. Locative media is closely related to augmented reality (reality overlaid with virtual reality) and pervasive computing (computers everywhere, as in ubiquitous computing). Whereas augmented reality strives for technical solutions, and pervasive computing is interested in embedded computers, locative media concentrates on social interaction with a place and with technology. Many locative media projects have a social, critical or personal (memory) background. While strictly spoken, any kind of link to additional information set up in space (together with the information that a specific place supplies) would make up location-dependent media, the term locative media is strictly bound to technical projects. Locative media works on locations and yet many of its applications are still location-independent in a technical sense. As in the case of digital media, where the medium itself is not digital but the content is digital, in locative media the medium itself might not be location-oriented, whereas the content is location-oriented. Japanese mobile phone culture embraces location-dependent information and context-awareness. It is projected that in the near future locative media will develop to a significant factor in everyday life. == Enabling technologies == Locative media projects use technology such as Global Positioning System (GPS), laptop computers, the mobile phone, Geographic Information System (GIS), and web map services such as Mapbox, OpenStreetMap, and Google Maps among others. Whereas GPS allows for the accurate detection of a specific location, mobile computers allow interactive media to be linked to this place. The GIS supplies arbitrary information about the geological, strategic or economic situation of a location. Web maps like Google Maps give a visual representation of a specific place. Another important new technology that links digital data to a specific place is radio-frequency identification (RFID), a successor to barcodes like Semacode. Research that contributes to the field of locative media happens in fields such as pervasive computing, context awareness and mobile technology. The technological background of locative media is sometimes referred to as "location-aware computing". == Creative representation == Place is often seen as central to creativity; in fact, "for some—regional artists, citizen journalists and environmental organizations for example—a sense of place is a particularly important aspect of representation, and the starting point of conversations." Locative media can propel such conversations in its function as a "poetic form of data visualization," as its output often traces how people move in, and by proxy, make sense of, urban environments. Given the dynamism and hybridity of cities and the networks which comprise them, locative media extends the internet landscape to physical environments where people forge social relations and actions which can be "mobile, plural, differentiated, adventurous, innovative, but also estranged, alienated, impersonalized." Moreover, in using locative technologies, users can expand how they communicate and assert themselves in their environment and, in doing so, explore this continuum of urban interactions. Furthermore, users can assume a more active role in constructing the environments they are situated in accordingly. In turn, artists have been intrigued with locative media as a means of "user-led mapping, social networking and artistic interventions in which the fabric of the urban environment and the contours of the earth become a 'canvas.'" Such projects demystify how resident behaviors in a given city contribute to the culture and sense of personality that cities are often perceived to take on. Design scholars Anne Galloway and Matthew Ward state that "various online lists of pervasive computing and locative media projects draw out the breadth of current classification schema: everything from mobile games, place-based storytelling, spatial annotation and networked performances to device-specific applications." A prominent use of locative media is in locative art. A sub-category of interactive art or new media art, locative art explores the relationships between the real world and the virtual or between people, places or objects in the real world. == Examples == Notable locative media projects include Bio Mapping by Christian Nold in 2004, locative art projects such as the SpacePlace ZKM/ZKMax bluecasting and participatory urban media access in Munich in 2005 and Britglyph by Alfie Dennen in 2009, and location-based games such as AR Quake by the Wearable Computer Lab at the University of South Australia and Can You See Me Now? in 2001 by Blast Theory in collaboration with the Mixed Reality Lab at the University of Nottingham. In 2005, the Silicon Valley–based collaborators of C5 first exhibited the C5 Landscape Initiative, a suite of four GPS inspired projects that investigate perception of landscape in light of locative media. In William Gibson's 2007 novel Spook Country, locative art is one of the main themes and set pieces in the story. Narrative projects which engage with locative media are sometimes referred to as Location-Aware Fiction, as explored in "Data and Narrative: Location Aware Fiction" a 2003 essay by Kate Armstrong. This location-aware fiction is also known as locative literature, where locative stories and poems can be experienced via digital portals, apps, QR codes and e-books, as well as via analogue forms such as labelling tape, Scrabble tiles, fridge magnets or Post-It notes, and these are forms often used by the writer and artist Matt Blackwood. The Transborder Immigrant Tool by the Electronic Disturbance Theater is a locative media project aimed at providing life saving directions to water for people trying to cross the US / Mexico border. The project attracted global media attention in 2009 and 2010. Articles included a Los Angeles Times cover story focusing on Ricardo Dominguez and an AP story interviewing Micha Cárdenas and Brett Stalbaum. The articles focused on concerns over the legality of the project and the ensuing investigations of the group, which are still underway. The Transborder Immigrant Tool has recently been included in a number of major exhibitions including Here, Not There at the Museum of Contemporary Art San Diego and the 2010 California Biennial at the Orange County Museum of Art. Invisible Threads by Stephanie Rothenberg and Jeff Crouse is a locative media project aimed at creating embodied awareness of sweatshops and just-in-time production t

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  Discrete skeleton evolution

  Discrete Skeleton Evolution (DSE) describes an iterative approach to reducing a morphological or topological skeleton. It is a form of pruning in that it removes noisy or redundant branches (spurs) generated by the skeletonization process, while preserving information-rich "trunk" segments. The value assigned to individual branches varies from algorithm to algorithm, with the general goal being to convey the features of interest of the original contour with a few carefully chosen lines. Usually, clarity for human vision (aka. the ability to "read" some features of the original shape from the skeleton) is valued as well. DSE algorithms are distinguished by complex, recursive decision-making processes with high computational requirements. Pruning methods such as by structuring element (SE) convolution and the Hough transform are general purpose algorithms which quickly pass through an image and eliminate all branches shorter than a given threshold. DSE methods are most applicable when detail retention and contour reconstruction are valued. == Methodology == === Pre-processing === Input images will typical contain more data than is necessary to generate an initial skeleton, and thus must be reduced in some way. Reducing the resolution, converting to grayscale, and then binary by masking or thresholding are common first steps. Noise removal may occur before and/or after converting an image to binary. Morphological operations such as closing, opening, and smoothing of the binary image may also be part of pre-processing. Ideally, the binarized contour should be as noise-free as possible before the skeleton is generated. === Skeletonization === DSE techniques may be applied to an existing skeleton or incorporated as part of the skeleton growing algorithm. Suitable skeletons may be obtained using a variety of methods: Thinning algorithms, such as the Grassfire transform Voronoi diagram Medial Axis Transform or Symmetry Axis Transform Distance Mapping === Significance Measures === DSE and related methods remove entire spurious branches while leaving the main trunk intact. The intended result is typically optimized for visual clarity and retention of information, such that the original contour can be reconstructed from the fully pruned skeleton. The value of various properties must be weighted by the application, and improving the efficiency is an ongoing topic of research in computer vision and image processing. Some significance measures include: Discrete Bisector Function Contour length Bending Potential Ratio Discrete Curve Evolution === Iteration === Each branch is evaluated during a pass through the skeletonized image according to the specific algorithm being used. Low value branches are removed and the process is repeated until a desired threshold of simplicity is reached. === Reconstruction === If all points on the output skeleton are the center points of maximal disks of the image and the radius information is retained, a contour image can be reconstructed == Applications == === Handwriting and text parsing === Variability in hand-written text is an ongoing challenge, simplification makes it somewhat easier for computer vision algorithms to make judgements about intended characters. === Soft body classification (animals) === The maximal disks centered on the skeleton imply roughly spherical masses, the features of the extracted skeleton are relatively unchanged even as the soft body deforms or self-occludes. Skeleton information is one facet of determining whether two animals are the "same" some way, though it must usually be paired with another technique to effectively identify a target. === Medical uses === Investigation of organs, tissue damage and deformation caused by disease.

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  JQuery

  jQuery is a JavaScript library designed to simplify HTML DOM tree traversal and manipulation, as well as event handling, CSS animations, and Ajax. It is free, open-source software using the permissive MIT License. As of August 2022, jQuery is used by 77% of the 10 million most popular websites. Web analysis indicates that it is the most widely deployed JavaScript library by a large margin, having at least three to four times more usage than any other JavaScript library. jQuery's syntax is designed to make it easier to navigate a document, select DOM elements, create animations, handle events, and develop Ajax applications. jQuery also provides capabilities for developers to create plug-ins on top of the JavaScript library. This enables developers to create abstractions for low-level interaction and animation, advanced effects and high-level, theme-able widgets. The modular approach to the jQuery library allows the creation of powerful dynamic web pages and Web applications. The set of jQuery core features—DOM element selections, traversal, and manipulation—enabled by its selector engine (named "Sizzle" from v1.3), created a new "programming style", fusing algorithms and DOM data structures. This style influenced the architecture of other JavaScript frameworks like YUI v3 and Dojo, later stimulating the creation of the standard Selectors API. Microsoft and Nokia bundle jQuery on their platforms. Microsoft includes it with Visual Studio for use within Microsoft's ASP.NET AJAX and ASP.NET MVC frameworks while Nokia has integrated it into the Web Run-Time widget development platform. == Overview == jQuery, at its core, is a Document Object Model (DOM) manipulation library. The DOM is a tree-structure representation of all the elements of a Web page. jQuery simplifies the syntax for finding, selecting, and manipulating these DOM elements. For example, jQuery can be used for finding an element in the document with a certain property (e.g. all elements with the h1 tag), changing one or more of its attributes (e.g. color, visibility), or making it respond to an event (e.g. a mouse click). jQuery also provides a paradigm for event handling that goes beyond basic DOM element selection and manipulation. The event assignment and the event callback function definition are done in a single step in a single location in the code. jQuery also aims to incorporate other highly used JavaScript functionality (e.g. fade ins and fade outs when hiding elements, animations by manipulating CSS properties). The principles of developing with jQuery are: Separation of JavaScript and HTML: The jQuery library provides simple syntax for adding event handlers to the DOM using JavaScript, rather than adding HTML event attributes to call JavaScript functions. Thus, it encourages developers to completely separate JavaScript code from HTML markup. Brevity and clarity: jQuery promotes brevity and clarity with features like "chainable" functions and shorthand function names. Elimination of cross-browser incompatibilities: The JavaScript engines of different browsers differ slightly so JavaScript code that works for one browser may not work for another. Like other JavaScript toolkits, jQuery handles all these cross-browser inconsistencies and provides a consistent interface that works across different browsers. Extensibility: New events, elements, and methods can be easily added and then reused as a plugin. == History == jQuery was originally created in January 2006 at BarCamp NYC by John Resig, influenced by Dean Edwards' earlier cssQuery library. It is currently maintained by a team of developers led by Timmy Willison (with the jQuery selector engine, Sizzle, being led by Richard Gibson). jQuery was originally licensed under the CC BY-SA 2.5, and relicensed to the MIT License in 2006. At the end of 2006, it was dual-licensed under GPL and MIT licenses. As this led to some confusion, in 2012 the GPL was dropped and is now only licensed under the MIT license. === Popularity === In 2015, jQuery was used on 62.7% of the top 1 million websites (according to BuiltWith), and 17% of all Internet websites. In 2017, jQuery was used on 69.2% of the top 1 million websites (according to Libscore). In 2018, jQuery was used on 78% of the top 1 million websites. In 2019, jQuery was used on 80% of the top 1 million websites (according to BuiltWith), and 74.1% of the top 10 million (per W3Techs). In 2021, jQuery was used on 77.8% of the top 10 million websites (according to W3Techs). == Features == jQuery includes the following features: DOM element selections using the multi-browser open source selector engine Sizzle, a spin-off of the jQuery project DOM manipulation based on CSS selectors that uses elements' names and attributes, such as id and class, as criteria to select nodes in the DOM Events Effects and animations Ajax Deferred and Promise objects to control asynchronous processing JSON parsing Extensibility through plug-ins Utilities, such as feature detection Compatibility methods that are natively available in modern browsers, but need fallbacks for old browsers, such as jQuery.inArray() and jQuery.each(). Cross-browser support === Browser support === jQuery 3.0 and newer supports "current−1 versions" (meaning the current stable version of the browser and the version that preceded it) of Firefox (and ESR), Chrome, Safari, and Edge as well as Internet Explorer 9 and newer. On mobile it supports iOS 7 and newer, and Android 4.0 and newer. == Distribution == The jQuery library is typically distributed as a single JavaScript file that defines all its interfaces, including DOM, Events, and Ajax functions. It can be included within a Web page by linking to a local copy or by linking to one of the many copies available from public servers. jQuery has a content delivery network (CDN) hosted by MaxCDN. Google in Google Hosted Libraries service and Microsoft host the library as well. Example of linking a copy of the library locally (from the same server that hosts the Web page): Example of linking a copy of the library from jQuery's public CDN: == Interface == === Functions === jQuery provides two kinds of functions, static utility functions and jQuery object methods. Each has its own usage style. Both are accessed through jQuery's main identifier: jQuery. This identifier has an alias named $. All functions can be accessed through either of these two names. ==== jQuery methods ==== The jQuery function is a factory for creating a jQuery object that represents one or more DOM nodes. jQuery objects have methods to manipulate these nodes. These methods (sometimes called commands), are chainable as each method also returns a jQuery object. Access to and manipulation of multiple DOM nodes in jQuery typically begins with calling the $ function with a CSS selector string. This returns a jQuery object referencing all the matching elements in the HTML page. $("div.test"), for example, returns a jQuery object with all the div elements that have the class test. This node set can be manipulated by calling methods on the returned jQuery object. ==== Static utilities ==== These are utility functions and do not directly act upon a jQuery object. They are accessed as static methods on the jQuery or $ identifier. For example, $.ajax() is a static method. === No-conflict mode === jQuery provides a $.noConflict() function, which relinquishes control of the $ name. This is useful if jQuery is used on a Web page also linking another library that demands the $ symbol as its identifier. In no-conflict mode, developers can use jQuery as a replacement for $ without losing functionality. === Typical start-point === Typically, jQuery is used by putting initialization code and event handling functions in $(handler). This is triggered by jQuery when the browser has finished constructing the DOM for the current Web page. or Historically, $(document).ready(callback) has been the de facto idiom for running code after the DOM is ready. However, since jQuery 3.0, developers are encouraged to use the much shorter $(handler) signature instead. === Chaining === jQuery object methods typically also return a jQuery object, which enables the use of method chains: This line finds all div elements with class attribute test , then registers an event handler on each element for the "click" event, then adds the class attribute foo to each element. Certain jQuery object methods retrieve specific values (instead of modifying a state). An example of this is the val() method, which returns the current value of a text input element. In these cases, a statement such as $('#user-email').val() cannot be used for chaining as the return value does not reference a jQuery object. === Creating new DOM elements === Besides accessing existing DOM nodes through jQuery, it is also possible to create new DOM nodes, if the string passed as the argument to $() factory looks like HTML. For example, the below code finds an HTML select element, and cr

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  New media

  New media are communication technologies that enable or enhance interaction between users, as well as interaction between users and content. In the middle of the 1990s, the phrase "new media" became widely used as part of a sales pitch for the influx of interactive CD-ROMs for entertainment and education. The new media technologies, sometimes known as Web 2.0, include a wide range of web-related communication tools such as blogs, wikis, online social networking, virtual worlds, and other social media platforms. The phrase "new media" refers to computational media that share material online and through computers. New media inspire new ways of thinking about older media. Media do not replace one another in a clear, linear succession, instead evolving in a more complicated network of interconnected feedback loops . What is different about new media is how they specifically refashion traditional media and how older media refashion themselves to meet the challenges of new media. Unless they contain technologies that enable digital generative or interactive processes, broadcast television programs, non-interactive news websites, feature films, magazines, and books are not considered to be new media. The term "new media" stands in contrast to old media, which dominated the media landscape as a form of mass media for many years. == History == In the 1950s, connections between computing and radical art began to grow stronger. It was not until the 1980s that Alan Kay and his co-workers at Xerox PARC began to give the computability of a personal computer to the individual, rather than have a big organization be in charge of this. In the late 1980s and early 1990s, however, we seem to witness a different kind of parallel relationship between social changes and computer design. Although causally unrelated, conceptually, it makes sense that the Cold War and the design of the Web took place at exactly the same time. Writers and philosophers such as Marshall McLuhan were instrumental in the development of media theory during this period which is now famous declaration in Understanding Media: The Extensions of Man, that "the medium is the message" drew attention to the too often ignored influence media and technology themselves, rather than their "content," have on humans' experience of the world and on society broadly. Until the 1980s, media relied primarily upon print and analog broadcast models such as television and radio. The last twenty-five years have seen the rapid transformation into media which are predicated upon the use of digital technologies such as the Internet and video games. However, these examples are only a small representation of new media. The use of digital computers has transformed the remaining 'old' media, as suggested by the advent of digital television and online publications. Even traditional media forms such as the printing press have been transformed through the application of technologies by using of image manipulation software like Adobe Photoshop and desktop publishing tools. Andrew L. Shapiro argues that the "emergence of new, digital technologies signals a potentially radical shift of who is in control of information, experience and resources". W. Russell Neuman suggests that whilst the "new media" have technical capabilities to pull in one direction, economic and social forces pull back in the opposite direction. According to Neuman, "We are witnessing the evolution of a universal interconnected network of audio, video, and electronic text communications that will blur the distinction between interpersonal and mass communication; and between public and private communication". Neuman argues that new media will: Alter the meaning of geographic distance. Allow for a huge increase in the volume of communication. Provide the possibility of increasing the speed of communication. Provide opportunities for interactive communication. Allow forms of communication that were previously separate to overlap and interconnect. Consequently, it has been the contention of scholars such as Douglas Kellner and James Bohman that new media and particularly the Internet will provide the potential for a democratic postmodern public sphere, in which citizens can participate in well informed, non-hierarchical debate pertaining to their social structures. Contradicting these positive appraisals of the potential social impacts of new media are scholars such as Edward S. Herman and Robert McChesney who have suggested that the transition to new media has seen a handful of powerful transnational telecommunications corporations who achieve a level of global influence which was hitherto unimaginable. Scholars have highlighted both the positive and negative potential and actual implications of new media technologies, suggesting that some of the early work in new media studies was guilty of technologicaldeterminism – whereby the effects of media were determined by the technologies themselves, rather than by tracing the complex social networks that governed the development, funding, implementation, and future evolution of any technology. Based on the argument that people have a limited amount of time to spend on the consumption of different media, displacement theory argue that the viewership or readership of one particular outlet leads to the reduction in the amount of time spent by the individual on another. The introduction of new media, such as the internet, therefore reduces the amount of time individuals would spend on existing "old" media, which could ultimately lead to the end of such traditional media. == Definition == Although, there are several ways that new media may be described, Lev Manovich, in an introduction to The New Media Reader, defines new media by using eight propositions: New media versus cyberculture – Cyberculture is the various social phenomena that are associated with the Internet and network communications (blogs, online multi-player gaming), whereas new media is concerned more with cultural objects and paradigms (digital to analog television, smartphones). New media as computer technology used as a distribution platform – New media are the cultural objects which use digital computer technology for distribution and exhibition. e.g. (at least for now) Internet, Web sites, computer multimedia, Blu-ray disks etc. The problem with this is that the definition must be revised every few years. The term "new media" will not be "new" anymore, as most forms of culture will be distributed through computers. New media as digital data controlled by software – The language of new media is based on the assumption that, in fact, all cultural objects that rely on digital representation and computer-based delivery do share a number of common qualities. New media is reduced to digital data that can be manipulated by software as any other data. Now media operations can create several versions of the same object. An example is an image stored as matrix data which can be manipulated and altered according to the additional algorithms implemented, such as color inversion, gray-scaling, sharpening, rasterizing, etc. New media as the mix between existing cultural conventions and the conventions of software – New media today can be understood as the mix between older cultural conventions for data representation, access, and manipulation and newer conventions of data representation, access, and manipulation. The "old" data are representations of visual reality and human experience, and the "new" data is numerical data. The computer is kept out of the key "creative" decisions, and is delegated to the position of a technician. e.g. In film, software is used in some areas of production, in others are created using computer animation. New media as the aesthetics that accompanies the early stage of every new modern media and communication technology – While ideological tropes indeed seem to be reappearing rather regularly, many aesthetic strategies may reappear two or three times ... In order for this approach to be truly useful it would be insufficient to simply name the strategies and tropes and to record the moments of their appearance; instead, we would have to develop a much more comprehensive analysis which would correlate the history of technology with social, political, and economical histories or the modern period. New media as faster execution of algorithms previously executed manually or through other technologies – Computers are a huge speed-up of what were previously manual techniques. e.g. calculators. Dramatically speeding up the execution makes possible previously non-existent representational technique. This also makes possible of many new forms of media art such as interactive multimedia and video games. On one level, a modern digital computer is just a faster calculator, we should not ignore its other identity: that of a cybernetic control device. New media as the encoding of modernist avant-garde; new media as metamedia – Manovi

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  Watcher Entertainment

  Watcher Entertainment is an American digital media and entertainment company, founded by Steven Lim, Shane Madej, and Ryan Bergara. The channel features a variety of comedy, paranormal, gaming, cooking, and educational shows – typically hosted by Madej and Bergara. The Watcher main channel has over 400 million views and 2.9 million subscribers. The company launched their own streaming service, WatcherTV, in 2024. == History == === Buzzfeed and the creation of Watcher Entertainment (2019) === Madej, Bergara, and Lim met while working at the digital media company BuzzFeed. Madej and Bergara were co-hosts of the popular true crime and paranormal series Buzzfeed Unsolved and Lim was the creator and co-host of the popular internet food series Worth It. Both shows generated a combined 2 billion views with 15 billion minutes watched, making them two of the most successful shows on Buzzfeed. In 2019, Madej, Bergara, and Lim quit Buzzfeed as full-time employees. They each stayed on as contracted employees to complete their respective shows. The trio credited their departure to their desire to found a company with more "creative opportunities" and the ability to have "actual ownership of the content" made. The company is majority-owned by the trio. They received funding from Neuro, a caffeinated energy gum company; Boba Guys, a bubble-milk tea chain; and Steve Chen, a YouTube co-founder. Watcher Entertainment gained its name from the infamous true crime case of The Westfield Watcher, which Madej and Bergara had covered in a Buzzfeed Unsolved episode. The trio began the company as co-CEOs; however, Bergara and Madej stepped down from the role in 2023 to focus on content creation. === Watcher Entertainment (2020–present) === Watcher Entertainment was launched in January 2020. The company debuted with seven series and a weekly interactive talk show: Homemade, Grocery Run, Weird Wonderful World, Puppet History, Tourist Trapped, Top 5 Beatdown, Spooky Small Talk, and Watcher Weekly. The channel reached over 300,000 subscribers within the first month of launching. They were signed by talent agency CAA in the same year. Puppet History, a comedy educational game show, quickly became a success and gained a significant audience. The show, which stars Madej as a fluffy blue puppet, has spanned seven seasons and led to the creation of a variety of merchandise. It has featured a variety of guest stars on every episode, including other former Buzzfeed employees. The company premiered its first horror series in July 2020 with Are You Scared?. Following the end of Buzzfeed Unsolved: Supernatural in 2021, the studio premiered its highly anticipated successor, Ghost Files, just months after. The show followed a similar format, with Bergara and Madej investigating reportedly haunted locations and attempting to find evidence of the paranormal. The show had significant success, with critics noting the improved production value and design from its predecessor. In 2023, Bergara and Madej went on a tour across the United States to premiere episodes of the second season. The series was renewed for a third season, which they premiered with a United Kingdom tour in 2024. That year, Watcher premiered a light-hearted successor to the graphic Buzzfeed Unsolved: True Crime, with Mystery Files. In this rendition, Bergara or Madej present unusual crime or supernatural mysteries with a collection of theoretical solutions. The show was met with great success by audiences and was quickly renewed for a second season. Watcher launched a second channel, 'WatcherPodcasts,' in October 2023. The channel features podcasts hosted by Lim, Bergara, and Madej. On April 19, 2024, the company launched its Watcher streaming service. Going forward, all of their content would be released exclusively on the service and the company planned to transition away from YouTube. This announcement was met with overwhelmingly negative reactions from their fans, with many calling for the company to reverse the decision. Additionally, their YouTube channel lost over 50,000 subscribers in the day following the announcement. On April 22, 2024, the company issued an apology and changed their decision, stating that episodes would instead be released on the streaming service a month before their premiere on YouTube. In May 2025, the channel 'Andrew, Steven, and Adam' was launched as a subsidiary of Watcher with the release of the second season of Travel Season. Travel Season is a spiritual successor to Worth It with the same cast of Lim, Andrew Ilnyckyj, and Adam Bianchi. The channel focuses on food reviews and the behind of the scenes of making it. The main channel is now set to be focused primarily on horror, creepy, and paranormal content. == Channels and shows == === Watcher === ==== Current shows ==== Puppet History (2020–present) A whimsical puppet host walks through history's wildest tales as two guests compete for the title of history wizard. Making Watcher (2020–present) What happens when 3 creators with no business experience decide to make their own company? A multi-series documentary on the journey of creating Watcher Entertainment. Weird Wonderful World (2020–present) Curious pals Madej and Bergara explore lesser-known destinations and the fascinating subcultures within them. Too Many Spirits (2020–present) Bergara and Madej read and rate audience-submitted ghost stories, while getting progressively more tipsy drinking cocktails prepared by Steven and Ricky Wang. Top 5 Beatdown (2020–present) Bergara and Madej compare asinine top 5 lists with a topical expert, inspiring surprisingly heated debate. Are You Scared? (2020–2022, 2024–present) Bergara reads the internet's scariest stories (some true, some false) to his pal Madej as they try to figure out if the story is experienced or imagined. Ghost Files (2021–present) Bergara and Madej investigate haunted locations to discover whether something paranormal really lies within. Mystery Files (2023–present) Bergara and Madej present unusual crime or supernatural mysteries with a collection of theoretical solutions. Survival Mode (2023–present) Bergara and Madej play a variety of horror games and give a spooky review. ==== Former shows ==== Grocery Run (2020) Madej interviews a celeb on their typical grocery run, before returning to their home to help prepare their signature dish. Homemade (2020) Lim examines popular food by comparing an elevated restaurant experience vs. a home-cooked experience. Spooky Small Talk (2020) Bergara interviews celebs in a haunted house, exposing their fears and if they can manage it, a little about themselves too. Social Distancing D&D (2020) Socially Distance along with the motley gang of Watchers as they embark on a great quest of Dungeons and Dragons! Tourist Trapped (2020) Begara and Madej battle for tour guide supremacy, highlighting the two sides of a city, tourist attractions and hidden gems. Watcher Weekly (2020–2021) Lim, Bergara, and Madej chat the week's content and answer questions, with the occasional musical guest! Dish Granted (2021–2022) A show where host and amateur home cook Lim attempts to create the most extravagant dishes for his friends. Pretty Historic (2022) Selorm and guests explore beauty and fashion trends from history, try them, and decide whether the trends should remain in the past or come to the present. Worth a Shot (2022–2023) Take a seat at a Master Mixologist's bar as pro Ricky Wang crafts the unbelievable into a digestible drink for his guests. === Watcher Podcast === ==== Current shows ==== Get Scared with Shane, Ryan, and Steven (2023–2025) Previously named 'Pod Watcher' Madej, Bergara, and Lim host a weekly podcasts, exploring a variety of topics and answering viewer questions. Guests occasionally appear to replace one host. Matt Real serves as the producer and a fourth voice for the podcast. For Your Amusement (2023–present) Bergara explores a variety of topics surrounding theme parks. === Andrew, Steven, and Adam === Travel Season (2024–present) Lim reunites with Worth It costars Andrew Ilnyckyj and Adam Bianchi in a new food review show. == Awards and nominations ==

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  Cygwin

  Cygwin ( SIG-win) is a free and open-source Unix-like environment and command-line interface (CLI) for Microsoft Windows. The project also provides a software repository containing open-source packages. Cygwin allows source code for Unix-like operating systems to be compiled and run on Windows. Cygwin provides native integration of Windows-based applications. The terminal emulator mintty is the default command-line interface provided to interact with the environment. The Cygwin installation directory layout mimics the root file system of Unix-like systems, with directories such as /bin, /home, /etc, /usr, and /var. Cygwin is released under the GNU Lesser General Public License version 3. It was originally developed by Cygnus Solutions, which was later acquired by Red Hat (now part of IBM), to port the GNU toolchain to Win32, including the GNU Compiler Suite. Rather than rewrite the tools to use the Win32 runtime environment, Cygwin implemented a POSIX-compatible environment in the form of a DLL. The brand motto is "Get that Linux feeling – on Windows", although Cygwin doesn't have Linux in it. == History == Cygwin began in 1995 as a project of Steve Chamberlain, a Cygnus engineer who observed that Windows NT and 95 used COFF as their object file format, and that GNU already included support for x86 and COFF, and the C library newlib. He thought that it would be possible to retarget GCC and produce a cross compiler generating executables that could run on Windows. A prototype was later developed. Chamberlain bootstrapped the compiler on a Windows system, to emulate Unix to let the GNU configure shell script run. Initially, Cygwin was called Cygwin32. When Microsoft registered the trademark Win32, the "32" was dropped to simply become Cygwin. In 1999, Cygnus offered Cygwin 1.0 as a commercial product. Subsequent versions have not been released, instead relying on continued open source releases. Geoffrey Noer was the project lead from 1996 to 1999. Christopher Faylor was lead from 1999 to 2004; he left Red Hat and became co-lead with Corinna Vinschen. Corinna Vinschen has been the project lead from mid-2014 to date (as of September, 2024). From June 23, 2016, the Cygwin library version 2.5.2 was licensed under the GNU Lesser General Public License (LGPL) version 3. == Description == Cygwin is provided in two versions: the full 64-bit version and a stripped-down 32-bit version, whose final version was released in 2022. Cygwin consists of a library that implements the POSIX system call API in terms of Windows system calls to enable the running of a large number of application programs equivalent to those on Unix systems, and a GNU development toolchain (including GCC and GDB). Programmers have ported the X Window System, K Desktop Environment 3, GNOME, Apache, and TeX. Cygwin permits installing inetd, syslogd, sshd, Apache, and other daemons as standard Windows services. Cygwin programs have full access to the Windows API and other Windows libraries. Cygwin programs are installed by running Cygwin's "setup" program, which downloads them from repositories on the Internet. The Cygwin API library is licensed under the GNU Lesser General Public License version 3 (or later), with an exception to allow linking to any free and open-source software whose license conforms to the Open Source Definition. Cygwin consists of two parts: A dynamic-link library in the form of a C standard library that acts as a compatibility layer for the POSIX API and A collection of software tools and applications that provide a Unix-like look and feel. Cygwin supports POSIX symbolic links, representing them as plain-text files with the system attribute set. Cygwin 1.5 represented them as Windows Explorer shortcuts, but this was changed for reasons of performance and POSIX correctness. Cygwin also recognises NTFS junction points and symbolic links and treats them as POSIX symbolic links, but it does not create them. The POSIX API for handling access control lists (ACLs) is supported. === Technical details === A Cygwin-specific version of the Unix mount command allows mounting Windows paths as "filesystems" in the Unix file space. Initial mount points can be configured in /etc/fstab, which has a format very similar to Unix systems, except that Windows paths appear in place of devices. Filesystems can be mounted in binary mode (by default), or in text mode, which enables automatic conversion between LF and CRLF endings (which only affects programs that open files without explicitly specifying text or binary mode). Cygwin 1.7 introduced comprehensive support for POSIX locales, and the UTF-8 Unicode encoding became the default. The fork system call for duplicating a process is fully implemented, but the copy-on-write optimization strategy could not be used. Cygwin's default user interface is the bash shell running in the mintty terminal emulator. The DLL also implements pseudo terminal (pty) devices, and Cygwin ships with a number of terminal emulators that are based on them, including rxvt/urxvt and xterm. The version of GCC that comes with Cygwin has various extensions for creating Windows DLLs, such as specifying whether a program is a windowing or console-mode program. Support for compiling programs that do not require the POSIX compatibility layer provided by the Cygwin DLL used to be included in the default GCC, but as of 2014, it is provided by cross-compilers contributed by the MinGW-w64 project. == Software packages == Cygwin's base package selection is approximately 100MB, containing the bash (interactive user) and dash (installation) shells and the core file and text manipulation utilities. Additional packages are available as optional installs from within the Cygwin "setup" program and package manager ("setup-x86_64.exe" – 64 bit). The Cygwin Ports project provided additional packages that were not available in the Cygwin distribution itself. Examples included GNOME, K Desktop Environment 3, MySQL database, and the PHP scripting language. Most ports have been adopted by volunteer maintainers as Cygwin packages, and Cygwin Ports are no longer maintained. Cygwin ships with GTK+ and Qt. The Cygwin/X project allows graphical Unix programs to display their user interfaces on the Windows desktop for both local and remote programs.

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  Computer aided transceiver

  Computer aided transceiver (CAT) is a non-generic serial protocol used by radio amateurs for (remotely) controlling a transceiver radio receiver equipment using a computer. Conventional transmitters are manually controlled and used to transmit voice using buttons, dials, etc. However, advances in electronics have come to market devices that can be controlled by a computer and allow digital modes such as packet radio and also the use of satellite tracking, because it can continuously change the device's frequency according to the Doppler effect. This is done by connecting a Radio receiver and a PC using a CAT interface and a CAT Program Additionally, CAT interfaces can also be used to position tracking antennas, in controllers. As a satellite moves overhead. A CAT interface is a piece of hardware that connects the PC and radio that provides a connection to allows the radio and the PC to communicate with each other. The CAT interface provides the signals to and fro via correct voltage levels and in the case of a Universal Serial Bus (USB) CAT interface it requires a "protocol" for communication but communication itself is down to the radio and the software on the PC. Software that may be called a CAT program allows a radio to be controlled through the PC. Changes made on the radio through user interactions on the CAT Program are (generally) shown on the PC's screen. The functionality of CAT equipment (software & interface) depends on the radio and what features the software writers included in the CAT software. Modern radio systems do have more CAT functionality If you run a logging program that supports CAT, then that software may take advantage of the CAT system by retrieving information from the radio to help fill in log details, such as the frequency that the contact was made. CAT is also useful on many radios where there are many sub-menus in the radios menu system, and many of the sub-menu items can be easily changed via the PC. On many HF radios, the CAT system is also used to program the memories on the radio, but you would need to use appropriate programming software. A CAT interface does not receive or transmit any DATA mode, that is the purpose of a DATA interface. Although, both may be used at the same time with the correct CAT Equipment. DATA modes, and getting audio to and from the PC is the function of a DATA interface. A completely different thing but it is easier and more useful when CAT and DATA are used at the same time. Wouldn't it be nice to have an interface that could operate Frequency-shift keying (FSK), Audio FSK (AFSK), (real) Morse Code (CW), with a CAT interface and its own sound card..... (eg. The DigiMaster Pro3).

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  Gnowit

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

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