AI Art History

AI Art History — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

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  Image stitching

  Image stitching or photo stitching is the process of combining multiple photographic images with overlapping fields of view to produce a segmented panorama or high-resolution image. Commonly performed through the use of computer software, most approaches to image stitching require nearly exact overlaps between images and identical exposures to produce seamless results, although some stitching algorithms actually benefit from differently exposed images by doing high-dynamic-range imaging in regions of overlap. Some digital cameras can stitch their photos internally. == Applications == Image stitching is widely used in modern applications, such as the following: Document mosaicing Image stabilization feature in camcorders that use frame-rate image alignment High-resolution image mosaics in digital maps and satellite imagery Medical imaging Multiple-image super-resolution imaging Video stitching Object insertion == Process == The image stitching process can be divided into three main components: image registration, calibration, and blending. === Image stitching algorithms === In order to estimate image alignment, algorithms are needed to determine the appropriate mathematical model relating pixel coordinates in one image to pixel coordinates in another. Algorithms that combine direct pixel-to-pixel comparisons with gradient descent (and other optimization techniques) can be used to estimate these parameters. Distinctive features can be found in each image and then efficiently matched to rapidly establish correspondences between pairs of images. When multiple images exist in a panorama, techniques have been developed to compute a globally consistent set of alignments and to efficiently discover which images overlap one another. A final compositing surface onto which to warp or projectively transform and place all of the aligned images is needed, as are algorithms to seamlessly blend the overlapping images, even in the presence of parallax, lens distortion, scene motion, and exposure differences. === Image stitching issues === Since the illumination in two views cannot be guaranteed to be identical, stitching two images could create a visible seam. Other reasons for seams could be the background changing between two images for the same continuous foreground. Other major issues to deal with are the presence of parallax, lens distortion, scene motion, and exposure differences. In a non-ideal real-life case, the intensity varies across the whole scene, and so does the contrast and intensity across frames. Additionally, the aspect ratio of a panorama image needs to be taken into account to create a visually pleasing composite. For panoramic stitching, the ideal set of images will have a reasonable amount of overlap (at least 15–30%) to overcome lens distortion and have enough detectable features. The set of images will have consistent exposure between frames to minimize the probability of seams occurring. === Keypoint detection === Feature detection is necessary to automatically find correspondences between images. Robust correspondences are required in order to estimate the necessary transformation to align an image with the image it is being composited on. Corners, blobs, Harris corners, and differences of Gaussians of Harris corners are good features since they are repeatable and distinct. One of the first operators for interest point detection was developed by Hans Moravec in 1977 for his research involving the automatic navigation of a robot through a clustered environment. Moravec also defined the concept of "points of interest" in an image and concluded these interest points could be used to find matching regions in different images. The Moravec operator is considered to be a corner detector because it defines interest points as points where there are large intensity variations in all directions. This often is the case at corners. However, Moravec was not specifically interested in finding corners, just distinct regions in an image that could be used to register consecutive image frames. Harris and Stephens improved upon Moravec's corner detector by considering the differential of the corner score with respect to direction directly. They needed it as a processing step to build interpretations of a robot's environment based on image sequences. Like Moravec, they needed a method to match corresponding points in consecutive image frames, but were interested in tracking both corners and edges between frames. SIFT and SURF are recent key-point or interest point detector algorithms but a point to note is that SURF is patented and its commercial usage restricted. Once a feature has been detected, a descriptor method like SIFT descriptor can be applied to later match them. === Registration === Image registration involves matching features in a set of images or using direct alignment methods to search for image alignments that minimize the sum of absolute differences between overlapping pixels. When using direct alignment methods one might first calibrate one's images to get better results. Additionally, users may input a rough model of the panorama to help the feature matching stage, so that e.g. only neighboring images are searched for matching features. Since there are smaller group of features for matching, the result of the search is more accurate and execution of the comparison is faster. To estimate a robust model from the data, a common method used is known as RANSAC. The name RANSAC is an abbreviation for "RANdom SAmple Consensus". It is an iterative method for robust parameter estimation to fit mathematical models from sets of observed data points which may contain outliers. The algorithm is non-deterministic in the sense that it produces a reasonable result only with a certain probability, with this probability increasing as more iterations are performed. It being a probabilistic method means that different results will be obtained for every time the algorithm is run. The RANSAC algorithm has found many applications in computer vision, including the simultaneous solving of the correspondence problem and the estimation of the fundamental matrix related to a pair of stereo cameras. The basic assumption of the method is that the data consists of "inliers", i.e., data whose distribution can be explained by some mathematical model, and "outliers" which are data that do not fit the model. Outliers are considered points which come from noise, erroneous measurements, or simply incorrect data. For the problem of homography estimation, RANSAC works by trying to fit several models using some of the point pairs and then checking if the models were able to relate most of the points. The best model – the homography, which produces the highest number of correct matches – is then chosen as the answer for the problem; thus, if the ratio of number of outliers to data points is very low, the RANSAC outputs a decent model fitting the data. === Calibration === Image calibration aims to minimize differences between an ideal lens models and the camera-lens combination that was used, optical defects such as distortions, exposure differences between images, vignetting, camera response and chromatic aberrations. If feature detection methods were used to register images and absolute positions of the features were recorded and saved, stitching software may use the data for geometric optimization of the images in addition to placing the images on the panosphere. Panotools and its various derivative programs use this method. ==== Alignment ==== Alignment may be necessary to transform an image to match the view point of the image it is being composited with. Alignment, in simple terms, is a change in the coordinates system so that it adopts a new coordinate system which outputs image matching the required viewpoint. The types of transformations an image may go through are pure translation, pure rotation, a similarity transform which includes translation, rotation and scaling of the image which needs to be transformed, Affine or projective transform. Projective transformation is the farthest an image can transform (in the set of two dimensional planar transformations), where only visible features that are preserved in the transformed image are straight lines whereas parallelism is maintained in an affine transform. Projective transformation can be mathematically described as x ′ = H ⋅ x , {\displaystyle x'=H\cdot x,} where x {\displaystyle x} is points in the old coordinate system, x ′ {\displaystyle x'} is the corresponding points in the transformed image and H {\displaystyle H} is the homography matrix. Expressing the points x {\displaystyle x} and x ′ {\displaystyle x'} using the camera intrinsics ( K {\displaystyle K} and K ′ {\displaystyle K'} ) and its rotation and translation [ R t ] {\displaystyle [R\,t]} to the real-world coordinates X {\displaystyle X} and < m a t h > x {\displaystyle $x\}\; and\; x\; \prime \; \{\backslash displaystyle\; x\text{'}\}\; \text{'}$, we get Using the abo

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  Remote scripting

  Remote scripting is a technology which allows scripts and programs that are running inside a browser to exchange information with a server. The local scripts can invoke scripts on the remote side and process the returned information. The earliest form of asynchronous remote scripting was developed before XMLHttpRequest existed, and made use of very simple process: a static web page opens a dynamic web page (e.g. at other target frame) that is reloaded with new JavaScript content, generated remotely on the server side. The XMLHttpRequest and similar "client-side script remote procedure call" functions, open the possibility of use and triggering web services from the web page interface. The web development community subsequently developed a range of techniques for remote scripting in order to enable consistent results across different browsers. Early examples include JSRS library from 2000, the introduction of the Image/Cookie technique in 2000. == JavaScript Remote Scripting == JavaScript Remote Scripting (JSRS) is a web development technique for creating interactive web applications using a combination of: HTML (or XHTML) The Document Object Model manipulated through JavaScript to dynamically display and interact with the information presented A transport layer. Different technologies may be used, though using a script tag or an iframe is used the most because it has better browser support than XMLHttpRequest A data format. XML with WDDX can be used as well as JSON or any other text format. Schematic A similar approach is Ajax, though it depends on the XmlHttpRequest in newer web browsers. === Libraries === Brent Ashley's original JSRS library released in 2000 BlueShoes JSRS with added encoding and OO RPC abstractions Simple Tutorials: Javascript Remote Scripting with PHP at the Wayback Machine (archived 2006-04-14) MSDN article

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  Awwwards

  Awwwards (Awwwards Online SL) is an organization that hosts web design competitions and conferences across Europe and the United States. Website owners and developers can participate by submitting their websites for review. Submissions are assessed by a jury, and top entries are presented and awarded prizes on a rotational basis. == Nomination process == Web designers submit their websites through Awwwards' platform for consideration for the Site of the Day. A jury, composed of industry professionals, and the Awwwards community evaluate the entries. The best daily sites are published annually in "The 365 Best Websites Around the World" book. == Jury == The jury consists of international designers, developers, and agencies who assess the creativity, technical skills, and insight of the submitted web projects. The panel's expertise ensures a comprehensive review process. === Developer Award === Awwwards, in partnership with Microsoft, created the Developer Award to recognize web developers who demonstrate excellence in creating websites that meet modern standards. The award highlights websites that work seamlessly across various platforms and devices, using best practices in HTML5, JavaScript, and CSS. == Annual winners == Some prominent Site of the Year winners include Mercedes-Benz, Bloomberg L.P., Bose Corporation, Warner Brothers, Volkswagen, Uber, and Google. == Awwwards conference == Awwwards also organizes two-day conferences featuring speakers from major tech companies and industry leaders such as Microsoft, Google, Spotify, Adobe, Opera, and Smashing Magazine. These events focus on the latest trends in web design and development. Speakers at Awwwards conferences have included notable figures in the design and technology industry such as Stefan Sagmeister, Paula Scher, and design leaders from companies including Wix. == Corporate affairs == === Platform === Awwwards operates an online platform where web designers and developers submit websites for evaluation and awards. Submitted projects are reviewed by a jury based on design, usability, creativity, and content. The platform also serves as a community hub for discovering digital trends, showcasing work, and accessing educational resources including talks and interviews. Design professionals from international companies have participated in Awwwards events and platform content. For example, Wix, a cloud-based web development company known for its website builder tools, has featured prominently in Awwwards conferences, with its design leadership contributing to discussions on design trends and creative thinking.

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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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  Graphics

  Graphics (from Ancient Greek γραφικός (graphikós) 'pertaining to drawing, painting, writing, etc.') are visual images or designs on some surface, such as a wall, canvas, screen, paper, or stone, to inform, illustrate, or entertain. In contemporary usage, it includes a pictorial representation of data, as in design and manufacture, in typesetting and the graphic arts, and in educational and recreational software. Images that are generated by a computer are called computer graphics. Examples are photographs, drawings, line art, mathematical graphs, line graphs, charts, diagrams, typography, numbers, symbols, geometric designs, maps, engineering drawings, or other images. Graphics often combine text, illustration, and color. Graphic design may consist of the deliberate selection, creation, or arrangement of typography alone, as in a brochure, flyer, poster, web site, or book without any other element. The objective can be clarity or effective communication, association with other cultural elements, or merely the creation of a distinctive style. Graphics can be functional or artistic. The latter can be a recorded version, such as a photograph, or an interpretation by a scientist to highlight essential features, or an artist, in which case the distinction with imaginary graphics may become blurred. It can also be used for architecture. == History == The earliest graphics known to anthropologists studying prehistoric periods are cave paintings and markings on boulders, bone, ivory, and antlers, which were created during the Upper Palaeolithic period from 40,000 to 10,000 B.C. or earlier. Many of these were found to record astronomical, seasonal, and chronological details. Some of the earliest graphics and drawings are known to the modern world, from almost 6,000 years ago, are that of engraved stone tablets and ceramic cylinder seals, marking the beginning of the historical periods and the keeping of records for accounting and inventory purposes. Records from Egypt predate these and papyrus was used by the Egyptians as a material on which to plan the building of pyramids; they also used slabs of limestone and wood. From 600 to 250 BC, the Greeks played a major role in geometry. They used graphics to represent their mathematical theories such as the Circle Theorem and the Pythagorean theorem. In art, "graphics" is often used to distinguish work in a monotone and made up of lines, as opposed to painting. === Drawing === Drawing generally involves making marks on a surface by applying pressure from a tool or moving a tool across a surface. In which a tool is always used as if there were no tools it would be art. Graphical drawing is an instrumental guided drawing. === Printmaking === Woodblock printing, including images is first seen in China after paper was invented (about A.D. 105). In the West, the main techniques have been woodcut, engraving and etching, but there are many others. ==== Etching ==== Etching is an intaglio method of printmaking in which the image is incised into the surface of a metal plate using an acid. The acid eats the metal, leaving behind roughened areas, or, if the surface exposed to the acid is very thin, burning a line into the plate. The use of the process in printmaking is believed to have been invented by Daniel Hopfer (c. 1470–1536) of Augsburg, Germany, who decorated armour in this way. Etching is also used in the manufacturing of printed circuit boards and semiconductor devices. === Line art === Line art is a rather non-specific term sometimes used for any image that consists of distinct straight and curved lines placed against a (usually plain) background, without gradations in shade (darkness) or hue (color) to represent two-dimensional or three-dimensional objects. Line art is usually monochromatic, although lines may be of different colors. === Illustration === An illustration is a visual representation such as a drawing, painting, photograph or other work of art that stresses the subject more than form. The aim of an illustration is to elucidate or decorate a story, poem or piece of textual information (such as a newspaper article), traditionally by providing a visual representation of something described in the text. The editorial cartoon, also known as a political cartoon, is an illustration containing a political or social message. Illustrations can be used to display a wide range of subject matter and serve a variety of functions, such as: giving faces to characters in a story displaying a number of examples of an item described in an academic textbook (e.g. A Typology) visualizing step-wise sets of instructions in a technical manual communicating subtle thematic tone in a narrative linking brands to the ideas of human expression, individuality, and creativity making a reader laugh or smile for fun (to make laugh) funny === Graphs === A graph or chart is a graphic that represents tabular or numeric data. Charts are often used to make it easier to understand large quantities of data and the relationships between different parts of the data. === Diagrams === A diagram is a simplified and structured visual representation of concepts, ideas, constructions, relations, statistical data, etc., used to visualize and clarify the topic. === Symbols === A symbol, in its basic sense, is a representation of a concept or quantity; i.e., an idea, object, concept, quality, etc. In more psychological and philosophical terms, all concepts are symbolic in nature, and representations for these concepts are simply token artifacts that are allegorical to (but do not directly codify) a symbolic meaning, or symbolism. === Maps === A map is a simplified depiction of a space, a navigational aid which highlights relations between objects within that space. Usually, a map is a two-dimensional, geometrically accurate representation of a three-dimensional space. One of the first 'modern' maps was made by Waldseemüller. === Photography === One difference between photography and other forms of graphics is that a photographer, in principle, just records a single moment in reality, with seemingly no interpretation. However, a photographer can choose the field of view and angle, and may also use other techniques, such as various lenses to choose the view or filters to change the colors. In recent times, digital photography has opened the way to an infinite number of fast, but strong, manipulations. Even in the early days of photography, there was controversy over photographs of enacted scenes that were presented as 'real life' (especially in war photography, where it can be very difficult to record the original events). Shifting the viewer's eyes ever so slightly with simple pinpricks in the negative could have a dramatic effect. The choice of the field of view can have a strong effect, effectively 'censoring out' other parts of the scene, accomplished by cropping them out or simply not including them in the photograph. This even touches on the philosophical question of what reality is. The human brain processes information based on previous experience, making us see what we want to see or what we were taught to see. Photography does the same, although the photographer interprets the scene for their viewer. === Engineering drawings === An engineering drawing is a type of drawing and is technical in nature, used to fully and clearly define requirements for engineered items. It is usually created in accordance with standardized conventions for layout, nomenclature, interpretation, appearance (such as typefaces and line styles), size, etc. === Computer graphics === There are two types of computer graphics: raster graphics, where each pixel is separately defined (as in a digital photograph), and vector graphics, where mathematical formulas are used to draw lines and shapes, which are then interpreted at the viewer's end to produce the graphic. Using vectors results in infinitely sharp graphics and often smaller files, but, when complex, like vectors take time to render and may have larger file sizes than a raster equivalent. In 1950, the first computer-driven display was attached to MIT's Whirlwind I computer to generate simple pictures. This was followed by MIT's TX-0 and TX-2, interactive computing which increased interest in computer graphics during the late 1950s. In 1962, Ivan Sutherland invented Sketchpad, an innovative program that influenced alternative forms of interaction with computers. In the mid-1960s, large computer graphics research projects were begun at MIT, General Motors, Bell Labs, and Lockheed Corporation. Douglas T. Ross of MIT developed an advanced compiler language for graphics programming. S.A.Coons, also at MIT, and J. C. Ferguson at Boeing, began work in sculptured surfaces. GM developed their DAC-1 system, and other companies, such as Douglas, Lockheed, and McDonnell, also made significant developments. In 1968, ray tracing was first described by Arthur Appel of the IBM Research Center, Yorktown Heights, N

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  Key & See

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

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  FreePBX Distro

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

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  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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  Incremental heuristic search

  Incremental heuristic search algorithms combine both incremental and heuristic search to speed up searches of sequences of similar search problems, which is important in domains that are only incompletely known or change dynamically. Incremental search has been studied at least since the late 1960s. Incremental search algorithms reuse information from previous searches to speed up the current search and solve search problems potentially much faster than solving them repeatedly from scratch. Similarly, heuristic search has also been studied at least since the late 1960s. Heuristic search algorithms, often based on A, use heuristic knowledge in the form of approximations of the goal distances to focus the search and solve search problems potentially much faster than uninformed search algorithms. The resulting search problems, sometimes called dynamic path planning problems, are graph search problems where paths have to be found repeatedly because the topology of the graph, its edge costs, the start vertex or the goal vertices change over time. So far, three main classes of incremental heuristic search algorithms have been developed: The first class restarts A at the point where its current search deviates from the previous one (example: Fringe Saving A). The second class updates the h-values (heuristic, i.e. approximate distance to goal) from the previous search during the current search to make them more informed (example: Generalized Adaptive A). The third class updates the g-values (distance from start) from the previous search during the current search to correct them when necessary, which can be interpreted as transforming the A search tree from the previous search into the A search tree for the current search (examples: Lifelong Planning A, D, D Lite). All three classes of incremental heuristic search algorithms are different from other replanning algorithms, such as planning by analogy, in that their plan quality does not deteriorate with the number of replanning episodes. == Applications == Incremental heuristic search has been extensively used in robotics, where a larger number of path planning systems are based on either D (typically earlier systems) or D Lite (current systems), two different incremental heuristic search algorithms.

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  Creative work

  A creative work is a manifestation of creative effort in the world through a creative process involving one or more individuals. The term includes fine artwork (sculpture, paintings, drawing, sketching, performance art), dance, writing (literature), filmmaking, and musical composition. The term is frequently used in the context of copyright. It is an important concept in both philosophy and law. Creative works require a creative mindset and are not typically rendered in an arbitrary fashion, although works may demonstrate (i.e., have in common) a degree of arbitrariness, such that it is improbable that two people would independently create the same work. At its base, creative work involves two main steps – having an idea, and then turning that idea into a substantive form or process. Typically, the creative process results in work that has some aesthetic value, identified as a creative expression. Naturally, this expression generally invokes external stimuli (e.g., influences and experiences) which a person draws on because they view the source as creative or inspirational; the degree to which this is reflected may be used in determinations of the derivativeness of the created work. Alternatively, the creator may draw on imagination, and their references may be clouded even to them, for the nature of imagination is as yet not fully understood philosophically, and the level of necessary self-examination of an artist's internal processing is a challenge for even those most self-aware of their minds and mental processes. == Legal definition == === United Kingdom === For the purpose of section 221(2)(c) of the Income Tax (Trading and Other Income) Act 2005, the expression "creative works" means: (a) literary, dramatic, musical or artistic works, or (b) designs,created by the taxpayer personally or, if the qualifying trade, profession or vocation is carried on in partnership, by one or more of the partners personally.

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  Photonically Optimized Embedded Microprocessors

  The Photonically Optimized Embedded Microprocessors (POEM) is DARPA program. It should demonstrate photonic technologies that can be integrated within embedded microprocessors and enable energy-efficient high-capacity communications between the microprocessor and DRAM. For realizing POEM technology CMOS and DRAM-compatible photonic links should operate at high bit-rates with very low power dissipation. == Current research == Currently research in this field is at University of Colorado, Berkley University, and Nanophotonic Systems Laboratory ( Ultra-Efficient CMOS-Compatible Grating Coupler Design).

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  Digital first

  Digital first is a communication theory that publishers should release content into new media channels in preference to old media. The premise behind the theory is that after the advent of Internet, most established media organizations continued to give priority to traditional media. Over time, those organizations faced a choice to either publish first in digital media or traditional media. A "digital first" decision occurs when a publisher chooses to distribute information online in preference to or at the expense of traditional media like print publishing. Many employers and employees find it challenging to imagine using digital first practices. Distributing content digital first introduces new practices, including a need to manage the data which tracks readership. Many paper print publishers feel intimidated by the idea of publishing content online before publishing it in paper media. Comedian John Oliver in the show Last Week Tonight criticized digital first practices as a cause of lower standards in journalism. == Digital-First Transformation in Business and Education == The classical perspective of an information system is that it represents and reflects physical reality. However, it is increasingly evident that digital technologies not only represent reality but also actively shape it, as, in many instances, the digital version is created first, and the physical version follows. Gradually, digital infrastructures are integrated in people's work and life, shaping a digital environment through technologies such as 5G, sensors, and blockchain. The Digital First Framework, developed by Professor Youngjin Yoo, is a conceptual approach that helps the physical companies in the integration of digital technologies into the core of product and service design. The shift from traditional cars, where the physical vehicle precedes its digital representation on Google maps, to autonomous vehicles, where the digital representation (the blue dot) is created first, emphasizes the digital-first mindset in the design and operation of systems. In today's business environment, it's critical for organizations to embrace a digital-first strategy. Companies built on digital platforms will significantly diverge from traditional, hierarchical business structures that typically focus on a single product or market. These digitally-centered enterprises will offer products and services that are tailored to individual requirements, utilizing algorithms to assess needs based on specific situations, and relying on external partners to provide these solutions. This highlights the need to transform traditional R&D practices. It's essential for R&D teams to move beyond their laboratories and immerse themselves in the environments of their users. Understanding the context of use is fundamental to creating a relevant platform. As an illustration, the concept of Digital-first, as defined by Rohm et al. (2019), involves the integration of digital projects within educational courses, exemplified by institutions like M-School. The program adopts a programmatic approach, where successive courses progressively build upon one another, adopting an all-encompassing perspective that regards all aspects of marketing as inherently digital. Students actively participate in real-world projects, including campaigns for community improvement, and are tasked with generating content for diverse platforms. Through hands-on collaboration with live clients and the utilization of tools such as Google AdWords and Facebook Advertising, students acquire practical experience in the realms of digital marketing and analytics. == vBook == A vBook is an eBook that is digital first media with embedded video, images, graphs, tables, text, and other media.

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  Condensation algorithm

  The condensation algorithm (Conditional Density Propagation) is a computer vision algorithm. The principal application is to detect and track the contour of objects moving in a cluttered environment. Object tracking is one of the more basic and difficult aspects of computer vision and is generally a prerequisite to object recognition. Being able to identify which pixels in an image make up the contour of an object is a non-trivial problem. Condensation is a probabilistic algorithm that attempts to solve this problem. The algorithm itself is described in detail by Isard and Blake in a publication in the International Journal of Computer Vision in 1998. One of the most interesting facets of the algorithm is that it does not compute on every pixel of the image. Rather, pixels to process are chosen at random, and only a subset of the pixels end up being processed. Multiple hypotheses about what is moving are supported naturally by the probabilistic nature of the approach. The evaluation functions come largely from previous work in the area and include many standard statistical approaches. The original part of this work is the application of particle filter estimation techniques. The algorithm's creation was inspired by the inability of Kalman filtering to perform object tracking well in the presence of significant background clutter. The presence of clutter tends to produce probability distributions for the object state which are multi-modal and therefore poorly modeled by the Kalman filter. The condensation algorithm in its most general form requires no assumptions about the probability distributions of the object or measurements. == Algorithm overview == The condensation algorithm seeks to solve the problem of estimating the conformation of an object described by a vector x t {\displaystyle \mathbf {x_{t}} } at time t {\displaystyle t} , given observations z 1 , . . . , z t {\displaystyle \mathbf {z_{1},...,z_{t}} } of the detected features in the images up to and including the current time. The algorithm outputs an estimate to the state conditional probability density p ( x t | z 1 , . . . , z t ) {\displaystyle p(\mathbf {x_{t}} |\mathbf {z_{1},...,z_{t}} )} by applying a nonlinear filter based on factored sampling and can be thought of as a development of a Monte-Carlo method. p ( x t | z 1 , . . . , z t ) {\displaystyle p(\mathbf {x_{t}} |\mathbf {z_{1},...,z_{t}} )} is a representation of the probability of possible conformations for the objects based on previous conformations and measurements. The condensation algorithm is a generative model since it models the joint distribution of the object and the observer. The conditional density of the object at the current time p ( x t | z 1 , . . . , z t ) {\displaystyle p(\mathbf {x_{t}} |\mathbf {z_{1},...,z_{t}} )} is estimated as a weighted, time-indexed sample set { s t ( n ) , n = 1 , . . . , N } {\displaystyle \{s_{t}^{(n)},n=1,...,N\}} with weights π t ( n ) {\displaystyle \pi _{t}^{(n)}} . N is a parameter determining the number of sample sets chosen. A realization of p ( x t | z 1 , . . . , z t ) {\displaystyle p(\mathbf {x_{t}} |\mathbf {z_{1},...,z_{t}} )} is obtained by sampling with replacement from the set s t {\displaystyle s_{t}} with probability equal to the corresponding element of π t {\displaystyle \pi _{t}} . The assumptions that object dynamics form a temporal Markov chain and that observations are independent of each other and the dynamics facilitate the implementation of the condensation algorithm. The first assumption allows the dynamics of the object to be entirely determined by the conditional density p ( x t | x t − 1 ) {\displaystyle p(\mathbf {x_{t}} |\mathbf {x_{t-1}} )} . The model of the system dynamics determined by p ( x t | x t − 1 ) {\displaystyle p(\mathbf {x_{t}} |\mathbf {x_{t-1}} )} must also be selected for the algorithm, and generally includes both deterministic and stochastic dynamics. The algorithm can be summarized by initialization at time t = 0 {\displaystyle t=0} and three steps at each time t: === Initialization === Form the initial sample set and weights by sampling according to the prior distribution. For example, specify as Gaussian and set the weights equal to each other. === Iterative procedure === Sample with replacement N {\displaystyle N} times from the set { s 0 ( n ) , n = 1 , . . . , N } {\displaystyle \{s_{0}^{(n)},n=1,...,N\}} with probability { π 0 ( n ) , n = 1 , . . . , N } {\displaystyle \{\pi _{0}^{(n)},n=1,...,N\}} to generate a realization of p ( x t | z 1 , . . . , z t ) {\displaystyle p(\mathbf {x_{t}} |\mathbf {z_{1},...,z_{t}} )} . Apply the learned dynamics p ( x t | x t − 1 ) {\displaystyle p(\mathbf {x_{t}} |\mathbf {x_{t-1}} )} to each element of this new set, to generate a new set { s t ( n ) } {\displaystyle \{s_{t}^{(n)}\}} . To take into account the current observation z t {\displaystyle \mathbf {z_{t}} } , set π t ( n ) = p ( z t | s ( n ) ) ∑ j = 1 N p ( z t | s ( j ) ) {\displaystyle \pi _{t}^{(n)}={\frac {p(\mathbf {z_{t}} |s^{(n)})}{\sum _{j=1}^{N}p(\mathbf {z_{t}} |s^{(j)})}}} for each element { s t ( n ) } {\displaystyle \{s_{t}^{(n)}\}} . This algorithm outputs the probability distribution p ( x t | z 1 , . . . , z t ) {\displaystyle p(\mathbf {x_{t}} |\mathbf {z_{1},...,z_{t}} )} which can be directly used to calculate the mean position of the tracked object, as well as the other moments of the tracked object. Cumulative weights can instead be used to achieve a more efficient sampling. == Implementation considerations == Since object-tracking can be a real-time objective, consideration of algorithm efficiency becomes important. The condensation algorithm is relatively simple when compared to the computational intensity of the Ricatti equation required for Kalman filtering. The parameter N {\displaystyle N} , which determines the number of samples in the sample set, will clearly hold a trade-off in efficiency versus performance. One way to increase efficiency of the algorithm is by selecting a low degree of freedom model for representing the shape of the object. The model used by Isard 1998 is a linear parameterization of B-splines in which the splines are limited to certain configurations. Suitable configurations were found by analytically determining combinations of contours from multiple views, of the object in different poses, and through principal component analysis (PCA) on the deforming object. Isard and Blake model the object dynamics p ( x t | x t − 1 ) {\displaystyle p(\mathbf {x_{t}} |\mathbf {x_{t-1}} )} as a second order difference equation with deterministic and stochastic components: p ( x t | x t − 1 ) ∝ e − 1 2 | | B − 1 ( ( x t − x ¯ ) − A ( x t − 1 − x ¯ ) ) | | 2 ) {\displaystyle p(\mathbf {x_{t}} |\mathbf {x_{t-1}} )\propto e^{-{\frac {1}{2}}||B^{-1}((\mathbf {x_{t}} -\mathbf {\bar {x}} )-A(\mathbf {x_{t-1}} -\mathbf {\bar {x}} ))||^{2})}} where x ¯ {\displaystyle \mathbf {\bar {x}} } is the mean value of the state, and A {\displaystyle A} , B {\displaystyle B} are matrices representing the deterministic and stochastic components of the dynamical model respectively. A {\displaystyle A} , B {\displaystyle B} , and x ¯ {\displaystyle \mathbf {\bar {x}} } are estimated via Maximum Likelihood Estimation while the object performs typical movements. The observation model p ( z | x ) {\displaystyle p(\mathbf {z} |\mathbf {x} )} cannot be directly estimated from the data, requiring assumptions to be made in order to estimate it. Isard 1998 assumes that the clutter which may make the object not visible is a Poisson random process with spatial density λ {\displaystyle \lambda } and that any true target measurement is unbiased and normally distributed with standard deviation σ {\displaystyle \sigma } . The basic condensation algorithm is used to track a single object in time. It is possible to extend the condensation algorithm using a single probability distribution to describe the likely states of multiple objects to track multiple objects in a scene at the same time. Since clutter can cause the object probability distribution to split into multiple peaks, each peak represents a hypothesis about the object configuration. Smoothing is a statistical technique of conditioning the distribution based on both past and future measurements once the tracking is complete in order to reduce the effects of multiple peaks. Smoothing cannot be directly done in real-time since it requires information of future measurements. == Applications == The algorithm can be used for vision-based robot localization of mobile robots. Instead of tracking the position of an object in the scene, however, the position of the camera platform is tracked. This allows the camera platform to be globally localized given a visual map of the environment. Extensions of the condensation algorithm have also been used to recognize human gestures in image sequences. This application of the condensation algorithm impacts the ran

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  Horus Music

  Horus Music Limited is a global digital distribution and label services company. Established in 2006, Horus Music allows artists, labels and right-holders to send their music to over 200 download, streaming, and interactive platforms including iTunes, Google Play, Amazon, VEVO, 7digital, Spotify, Beatport, Deezer, Tidal, as well as offering digital marketing and playlisting opportunities. == History == The company were named Best Business Partner of 2014 by Huawei Technology of China, and were also a finalist in the International Trade category as part of the Leicester Mercury Business Awards during that same year. Their client base consists of unsigned and independent musicians and record labels, as well as well known recording artists. In November 2015, Horus Music sponsored the UK’s first Independent Label Week, in order to highlight the music that is released by the UK’s indie labels. In 2016, Horus Music celebrated their 10th anniversary Horus Music's sister companies Help for Bands and Help For Writers, provide advice and opportunities for musicians and E-book distribution for writers, respectively. Anara Publishing opened in 2017 which allows the company to work closely with a handpicked roster of musicians to provide royalty administration and sync licensing services. On 21 April 2017, Her Majesty Queen Elizabeth II’s 91st birthday, Horus Music was awarded with the Queen’s Award for Enterprise in International Trade. In 2021, Horus Music, UnitedMasters, and Symphonic Distribution partnered with pioneering music fintech company, beatBread, to offer clients access to more capital. beatBread's chordCashAI technology provides an automated advance experience for independent musicians while enable clients to choose their own terms and retain ownership of their music. == Clients == Horus Music has partnered with a number of charities including Save the Children, for the recording "Look into Your Heart", featuring Beverley Knight with Rolling Stones' Mick Jagger and Ronnie Wood, 100% of proceeds from the single were donated to the charity. The Pixel Project, who produced songs about violence against women and the blood cancer charity Bloodwise. The company have spoken openly about the state of the music industry and artists' rights and were one of the first distributors to remove their catalogue from Rdio after the streaming service was acquired by Pandora. Their relationships with artists and labels, as well as leading industry contacts, means they have the ability to work with musicians in a myriad of ways, including offering performance opportunities and even local auditions for TV shows such as The Voice UK. == Horus Music India == Horus Music India opened in 2016 and is based in Mumbai. By opening Horus Music India, the company are able to expand on their local connections as well as to provide a much more personalised service to musicians based in this area. The appointment of two Business Development Managers in India cemented their move.

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  Web engineering

  The World Wide Web has become a major delivery platform for a variety of complex and sophisticated enterprise applications in several domains. In addition to their inherent multifaceted functionality, these Web applications exhibit complex behaviour and place some unique demands on their usability, performance, security, and ability to grow and evolve. However, a vast majority of these applications continue to be developed in an ad hoc way, contributing to problems of usability, maintainability, quality and reliability. While Web development can benefit from established practices from other related disciplines, it has certain distinguishing characteristics that demand special considerations. In recent years, there have been developments towards addressing these considerations. Web engineering focuses on the methodologies, techniques, and tools that are the foundation of Web application development and which support their design, development, evolution, and evaluation. Web application development has certain characteristics that make it different from traditional software, information systems, or computer application development. Web engineering is multidisciplinary and encompasses contributions from diverse areas: systems analysis and design, software engineering, hypermedia/hypertext engineering, requirements engineering, human-computer interaction, user interface, data engineering, information science, information indexing and retrieval, testing, modelling and simulation, project management, and graphic design and presentation. Web engineering is neither a clone nor a subset of software engineering, although both involve programming and software development. While Web Engineering uses software engineering principles, it encompasses new approaches, methodologies, tools, techniques, and guidelines to meet the unique requirements of Web-based applications. == As a discipline == Proponents of Web engineering supported the establishment of Web engineering as a discipline at an early stage of Web. Major arguments for Web engineering as a new discipline are: Web-based Information Systems (WIS) development process is different and unique. Web engineering is multi-disciplinary; no single discipline (such as software engineering) can provide a complete theory basis, body of knowledge and practices to guide WIS development. Issues of evolution and lifecycle management when compared to more 'traditional' applications. Web-based information systems and applications are pervasive and non-trivial. The prospect of Web as a platform will continue to grow and it is worth being treated specifically. However, it has been controversial, especially for people in other traditional disciplines such as software engineering, to recognize Web engineering as a new field. The issue is how different and independent Web engineering is, compared with other disciplines. Main topics of Web engineering include, but are not limited to, the following areas: === Modeling disciplines === Business Processes for Applications on the Web Process Modelling of Web applications Requirements Engineering for Web applications B2B applications === Design disciplines, tools, and methods === UML and the Web Conceptual Modeling of Web Applications (aka. Web modeling) Prototyping Methods and Tools Web design methods CASE Tools for Web Applications Web Interface Design Data Models for Web Information Systems === Implementation disciplines === Integrated Web Application Development Environments Code Generation for Web Applications Software Factories for/on the Web Web 2.0, AJAX, E4X, ASP.NET, PHP and Other New Developments Web Services Development and Deployment === Testing disciplines === Testing and Evaluation of Web systems and Applications. Testing Automation, Methods, and Tools. === Applications categories disciplines === Semantic Web applications Document centric Web sites Transactional Web applications Interactive Web applications Workflow-based Web applications Collaborative Web applications Portal-oriented Web applications Ubiquitous and Mobile Web Applications Device Independent Web Delivery Localization and Internationalization of Web Applications Personalization of Web Applications == Attributes == === Web quality === Web Metrics, Cost Estimation, and Measurement Personalisation and Adaptation of Web applications Web Quality Usability of Web Applications Web accessibility Performance of Web-based applications === Content-related === Web Content Management Content Management System (CMS) Multimedia Authoring Tools and Software Authoring of adaptive hypermedia == Education == Master of Science: Web Engineering as a branch of study within the MSc program Web Sciences at the Johannes Kepler University Linz, Austria Diploma in Web Engineering: Web Engineering as a study program at the International Webmasters College (iWMC), Germany

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