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Office automation

Office automation refers to the varied computer machinery and software used to digitally create, collect, store, manipulate, and relay office information needed for accomplishing basic tasks. Raw data storage, electronic transfer, and the management of electronic business information comprise the basic activities of an office automation system. Office automation helps in optimizing or automating existing office procedures. The backbone of office automation is a local area network, which allows users to transfer data, mail and voice across the network. All office functions, including dictation, typing, filing, copying, fax, telex, microfilm and records management, telephone and telephone switchboard operations, fall into this category. Office automation was a popular term in the 1970s and 1980s as the desktop computer exploded onto the scene. Advantages of office automation include that it can get many tasks accomplished faster, it eliminates the need for a large staff, less storage is required to store data, and multiple people can update data simultaneously in the event of changes in schedule. == Outline == Businesses can easily purchase and stock their wares with the aid of technology. Many of the manual tasks that used to be done by hand can now be done through hand held devices and UPC and SKU coding. In the retail setting, automation also increases choice. Customers can easily process their payments through automated credit card machines and no longer have to wait in line for an employee to process and manually type in the credit card numbers. Office payrolls have been automated, which means no one has to manually cut checks, and those checks that are cut can be printed through computer programs. Direct deposit can be automatically set up and this further reduces the manual process, and most employees who participate in direct deposit often find their paychecks come earlier than if they'd have to wait for their checks to be written and then cleared by the bank. Other ways automation has reduced employee manpower on tasks is automated voice direction. Through the use of prompts, automated phone menus and directed calls, the need for employees to be dedicated to answer the phones has been reduced, and in some cases, eliminated.
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Shaded Picture System

The Shaded Picture System was a 3D raster computer display processor introduced by Evans & Sutherland in October 1973. The Shaded Picture System was the first general-purpose, commercially available raster computer graphics display processor capable of real-time, shaded 3D graphics. It could only display black and white graphics at a resolution of 256 by 256. It was extremely expensive, and very few units were ever sold. == History == The principles of shaded, hidden-line true 3D graphics were pioneered at the University of Utah in 1967. However, this algorithm was slow and would take several minutes to produce an image. In 1970, Gary Watkins developed a FORTRAN simulator of a faster algorithm that would theoretically generate shaded 3D images in real-time, "if implemented in suitable hardware". The simulator itself was still not capable of real-time shaded 3D image rendering. Evans & Sutherland developed a functional prototype of this "suitable hardware", which was later sold as the Shaded Picture System in 1973. About a year earlier in 1972, Evans & Sutherland sold the first and only CT1 to Case Western Reserve University. The CT1, or Continuous Tone 1, was a specialized image generator, not meant as a marketable or mass-produced product. At the time, the CT1, along with G.E./NASA's upgraded Electronic Scene Generator from 1971, would have been the only real-time raster graphics systems sold to customers comparable to the Shaded Picture System, although both the CT1 and Electronic Scene Generator were intentionally produced as one-off products and specialized for the needs of their customers. The Shaded Picture System, in contrast, was intentionally marketed.In early 1975, Evans & Sutherland demonstrated a random-access video frame buffer using relatively low-cost semiconductor memory, which was much more capable than the Shaded Picture System. When interfaced with a (non-shaded) E&S Picture System, the frame buffer had a resolution of 512 by 512 in grayscale and partial color capabilities. By the end of 1975, this frame buffer was commercially available.
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Dark mode

A dark mode, dark theme, night mode, or light-on-dark color scheme is a color scheme that uses light-colored text, icons, and graphical user interface elements on a dark background. It is often discussed in terms of computer user interface design and web design. Many modern websites and operating systems offer the user an optional light-on-dark display mode. Some users find dark mode displays more visually appealing, and claim that it can reduce eye strain. Displaying white at full brightness uses roughly six times as much power as pure black on a 2016 Google Pixel, which has an OLED display. However, conventional LED displays may not benefit from reduced power consumption; but if a LED display has the partial dimming features, it still benefits from reduced power consumption. Most modern operating systems support an optional light-on-dark color scheme. == History == Microsoft introduced the high contrast themes in Windows 95. Later, Microsoft introduced a dark theme in the Anniversary Update of Windows 10 in 2016. In 2018, Apple followed in macOS Mojave. In September 2019, iOS 13 and Android 10 both introduced dark modes. Some operating systems provide tools to change the dark mode state automatically at sundown or sunrise. A "prefers-color-scheme" option was created for front-end web developers in 2019, being a CSS property that signals a user's choice for their system to use a light or dark color theme. Firefox and Chromium have optional dark theme for all internal screens. It is also possible for third-party developers to implement their own dark themes. There are also a variety of browser add-ons that can re-theme web sites with dark color schemes, also aligning with system theme. Wikipedia's mobile and desktop versions received a dark mode option in 2024. == Implementation == There is a prefers-color-scheme media query in CSS, to detect if the user has requested light or dark color scheme and serve the requested color scheme. It can be indicated from the user's operating system preference or a user agent. CSS example: JavaScript example: == Energy usage == Light on dark color schemes require less energy to display on OLED displays. This positively impacts battery life and reduces energy consumption. While an OLED will consume around 40% of the power of an LCD displaying an image that is primarily black, it can use more than three times as much power to display an image with a white background, such as a document or web site. This can lead to reduced battery life and higher energy usage unless a light-on-dark color scheme is used. The long-term reduced power usage may also prolong battery life or the useful life of the display and battery. The energy savings that can be achieved using a light-on-dark color scheme are because of how OLED screens work: in an OLED screen, each subpixel generates its own light and it only consumes power when generating light. This is in contrast to how an LCD works: in an LCD, subpixels either block or allow light from an always-on (lit) LED backlight to pass through. "AMOLED Black" color schemes (that use pure black instead of dark gray) do not necessarily save more energy than other light-on-dark color schemes that use dark gray instead of black, as the power consumption on an AMOLED screen decreases proportionately to the average brightness of the displayed pixels. Although it is true that AMOLED black does save more energy than dark gray, the additional energy savings are often negligible; AMOLED black will only give an additional energy saving of less than 1%, for instance, over the dark gray that's used in the dark theme for Google's official Android apps. In November 2018, Google confirmed that dark mode on Android saved battery life. == Web issues == Some argue that a color scheme with light text on a dark background is easier to read on the screen, because the lower overall brightness causes less eyestrain, while others argue to the contrary. Some pages on the web are designed for white backgrounds; Image assets (GIF, PNG, SVG, WOFF, etc) can be used improperly causing visual artifacts if dark mode is forced (instead of designed for) with a plugin like Dark Reader.
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Joox

Joox (stylised in all caps) is a music streaming service owned by Tencent, launched in January 2015. Joox is the biggest music streaming app in Asian markets such as Hong Kong, Macau, Indonesia, Malaysia, Myanmar, Thailand and also in South Africa before it was shut down in early 2022. Joox is a freemium service, providing most of its songs free, while some songs are only available for premium users, offered via paid subscriptions or by doing different tasks offered. In 2017, Joox launched their service in their first non-Asian market, South Africa, which for an unknown reason shut down five years later. The service now accounts for more than 50% of all music streaming app downloads in their Asian markets. The number of music-streaming users in Hong Kong, Macau, Malaysia, Thailand, Myanmar and Indonesia was expected to reach 87 million by 2020. == Background == Before the emergence of Joox, Tencent owned QQ Music, one of the largest music streaming and download service in China. In 2015, they introduced Joox as their expansion of music services to overseas market instead of mainland China, starting first in Hong Kong. Instead of providing free services by playing audio ads to users like Spotify, another major music service, Joox focused on banner ads, splash ads and other advertising methods such as category playlists and in-app skins. They claimed it as a success. Joox offered their premium VIP access to DStv subscribers free of charge. DStv is the sister company to Tencent and is the primary pay-TV provider in South Africa. In November 2021, it was announced that Joox will stop streaming in South Africa in March 2022.
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Image formation

The study of image formation encompasses the radiometric and geometric processes by which 2D images of 3D objects are formed. In the case of digital images, the image formation process also includes analog to digital conversion and sampling. == Imaging == The imaging process is a mapping of an object to an image plane. Each point on the image corresponds to a point on the object. An illuminated object will scatter light toward a lens and the lens will collect and focus the light to create the image. The ratio of the height of the image to the height of the object is the magnification. The spatial extent of the image surface and the focal length of the lens determines the field of view of the lens. Image formation of mirror these have a center of curvature and its focal length of the mirror is half of the center of curvature. == Illumination == An object may be illuminated by the light from an emitting source such as the sun, a light bulb or a Light Emitting Diode. The light incident on the object is reflected in a manner dependent on the surface properties of the object. For rough surfaces, the reflected light is scattered in a manner described by the Bi-directional Reflectance Distribution Function (BRDF) of the surface. The BRDF of a surface is the ratio of the exiting power per square meter per steradian (radiance) to the incident power per square meter (irradiance). The BRDF typically varies with angle and may vary with wavelength, but a specific important case is a surface that has constant BRDF. This surface type is referred to as Lambertian and the magnitude of the BRDF is R/π, where R is the reflectivity of the surface. The portion of scattered light that propagates toward the lens is collected by the entrance pupil of the imaging lens over the field of view. == Field of view and imagery == The Field of view of a lens is limited by the size of the image plane and the focal length of the lens. The relationship between a location on the image and a location on the object is y = ftan(θ), where y is the max extent of the image plane, f is the focal length of the lens and θ is the field of view. If y is the max radial size of the image then θ is the field of view of the lens. While the image created by a lens is continuous, it can be modeled as a set of discrete field points, each representing a point on the object. The quality of the image is limited by the aberrations in the lens and the diffraction created by the finite aperture stop. == Pupils and stops == The aperture stop of a lens is a mechanical aperture which limits the light collection for each field point. The entrance pupil is the image of the aperture stop created by the optical elements on the object side of the lens. The light scattered by an object is collected by the entrance pupil and focused onto the image plane via a series of refractive elements. The cone of the focused light at the image plane is set by the size of the entrance pupil and the focal length of the lens. This is often referred to as the f-stop or f-number of the lens. f/# = f/D where D is the diameter of the entrance pupil. == Pixelation and color vs. monochrome == In typical digital imaging systems, a sensor is placed at the image plane. The light is focused on to the sensor and the continuous image is pixelated. The light incident on each pixel in the sensor will be integrated within the pixel and a proportional electronic signal will be generated. The angular geometric resolution of a pixel is given by atan(p/f), where p is the pitch of the pixel. This is also called the pixel field of view. The sensor may be monochrome or color. In the case of a monochrome sensor, the light incident on each pixel is integrated and the resulting image is a grayscale like picture. For color images, a mosaic color filter is typically placed over the pixels to create a color image. An example is a Bayer filter. The signal incident on each pixel is then digitized to a bit stream. == Image quality == The quality of an image is dependent upon both geometric and physical items. Geometrically, higher density of pixels across an image will give less blocky pixelation and thus a better geometric image quality. Lens aberrations also contribute to the quality of the image. Physically, diffraction due to the aperture stop will limit the resolvable spatial frequencies as a function of f-number. In the frequency domain, Modulation Transfer Function (MTF) is a measure of the quality of the imaging system. The MTF is a measure of the visibility of a sinusoidal variation in irradiance on the image plane as a function of the frequency of the sinusoid. It includes the effects of diffraction, aberrations and pixelation. For the lens, the MTF is the autocorrelation of the pupil function, so it accounts for the finite pupil extent and the lens aberrations. The sensor MTF is the Fourier Transform of the pixel geometry. For a square pixel, MTF(ξ) = sin(πξp)/πξp where p is the pixel width and ξ is the spatial frequency. The MTF of the combination of the lens and detector is the product of the two component MTFs. == Perception == Color images can be perceived via two means. In the case of computer vision the light incident on the sensor comprises the image. In the case of visual perception, the human eye has a color dependent response to light so this must be accounted for. This is important consideration when converting to grayscale. == Image formation in eye == The principal difference between the lens of the eye and an ordinary optical lens is that the former is flexible. The radius of the curvature of the anterior surface of the lens is greater than the radius of its posterior surface. The shape of the lens is controlled by tension in the fibers of the ciliary body. To focus on distant objects, the controlling muscles cause the lens to be relatively flattened. Similarly, these muscles allow the lens to become thicker in order to focus on objects near the eye. The distance between the center of the lens and the retina (focal length) varies from approximately 17 mm to about 14 mm, as the refractive power of the lens increases from its minimum to its maximum. When the eye focuses on an object farther away than about 3 m, the lens exhibits its lowest refractive power. When the eye focuses on a close object, the lens is most strongly refractive.
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Digital on-screen graphics by country

Digital on-screen graphics by country are the varying logos and differences of digital on-screen graphics in different countries and regions. == Overview == Digital on-screen graphics (DOGs; also called a digitally originated graphic, bug, network bug, on-screen bug, or screenbug) are almost always placed in one of four corners: the top left, the top right, the bottom left, or the bottom right. There are few exceptions to this rule: most notably, Saturday! in Russia, which places their DOG in the top center. Many news broadcasters, as well as a few television networks, also place a clock alongside their bug. In the United States, Canada, Australia, and New Zealand, DOGs may also include the show's parental guideline rating. In Australia, this is known as a Program Return Graphic (PRG). It has become common to place text above the station's logo advertising other programs on the network. In many countries, some TV networks insert the word "live" near the DOG to advise viewers that the program is live, rather than pre-recorded. During televised sports events, a DOG may also display game-related statistics such as the current score. This has led people in Canada and the United States to refer to such a DOG as a score bug. In many countries, DOGs are removed in non-program sections such as commercials and program trailers, but TV channels in some other countries have retained in full color or instead replaced them in either of these sections or in both sections (like Turkey, Indonesia, Italy, the entirety of South Asia, Vietnam, Taiwan, and Russia). == MENA == === Arab world === Arabic TV logos are placed in the top-right and top-left except for Al-Jazeera, whose logo appears on the bottom-right of the screen. Some Arabian TV stations hide their logos during commercial breaks and promos/trailers, such as Dubai TV, Dubai One, Funoon, the Egyptian CBC and Nile TV networks, ART Hekayat, ART Hekayat 2, Iqraa, and Al-Jazeera. Abu Dhabi TV and MBC1 initially had their logos at the bottom-right corner from their launch until the mid-2000s, when they were moved to the top-right corner. === Iran === Iranian broadcaster IRIB introduced DOGs in early 2000s. Unlike other Middle Eastern nations that introduced DOGs on their TV networks in 1990s, Iran was very late in this practice. Almost all Iranian TV channels display DOGs at top-left corner of the screen. The few exception is IRIB-owned channels remove DOGs during news broadcasts. === Israel === In Israel, Television DOGs were first introduced in 1991. Israeli channel watermarks most often appear on the top left or the top right corner since Israeli cable and satellite-based services often have the channel description and programming (OSD) on the bottom of the screen. Most channels have an opaque, full-color watermark, though exceptions exist, for example Channel 9, which displays a blue-tinted semi-transparent logo. In ad breaks, it is required to replace the channel watermark with another symbol – sometimes on the other edge of the screen – indicating there are ads at the moment. The Israel Broadcasting Authority, whose channels placed their logos in the top left corner, ceased broadcasting in May 2017. The new public broadcaster, the Israeli Public Broadcasting Corporation, displays its logos at the top right instead. The erstwhile Channel 2 as well as its successors, Keshet 12 and Reshet 13, also use the top right corner. However, Channel 10 used the top left corner before rebranding to Eser (Literally "Ten") in 2017 and simultaneously moving its logo to the top right (Not long after, in January 2019, it ceased broadcasting as it merged with Reshet 13). Channel 14 as well as its predecessor Channel 20 use the top right corner as well. The Knesset Channel, however, uses the top left corner. === Morocco === The SNRT and 2M And Al-Aoula Uses permanent on-screen DOGs for their TV channels. In contrast, other channels such as Medi 1 TV hide their DOGs during commercial breaks. == Asia == === Brunei === Radio Television Brunei introduced DOGs in 1994. Like TV channels from neighbouring Malaysia, all DOGs are removed during advertisement breaks. === Cambodia === Cambodian TV channels introduced DOGs in 1995. Like Thailand, all logos are full-color and displayed on the top-right corner of the screen. Some channels such as TV5 hide their logos during commercial breaks. Hang Meas HDTV Logo on the top-left corner of the screen, CTN (Cambodian Television Network), MyTV, Bayon TV, PNN, Logo on the top-right corner of the screen. === China === TV stations in mainland China always place their logo (usually semi-transparent and sometimes animated) in the top-left corner of the screen in full-color or grey-scale. Regardless of the content being broadcast (program or advertisements), some channels like Phoenix Television hide their logos during commercial breaks; although in some rare cases, the DOG may be placed elsewhere to avoid covering the score bug during the broadcast of a sporting event. China introduced logos in 1983 on the bottom-left corner of the screen, but they were used only during commercial breaks and clock idents. Later China Central Television (CCTV) introduced permanent DOGs for all programs in 1992, on the top-left corner of the screen. China also displays a clock on top-right corner of the screen for 1 minute between 59:30–00:30 & 29:30–30:30 time in transition between programs. === Hong Kong === Hong Kong TV introduced DOGs in 1994. Hong Kong DOGs can be either of full color or semi-transparent and (except for RTHK 31) always be hidden during commercial breaks. Television Broadcasts Limited (TVB) placed their logos at the top-right corner of the screen while now-defunct Asia Television and other channels placed their logos at the top-left corner of the screen. Sometimes, weather information, date, and time clocks had been used alongside DOGs in news programs, continuity & live broadcasts. === India === The first on-screen logo in India was introduced in 1984 by DD2 Metro (now DD News). It was white and slightly transparent. All Indian TV channels have on-screen logos. They are always full-colors, never transparent, and they are almost never removed during commercial breaks (though the channels of the South Indian Sun TV Network did so until 2015). The great majority of Indian TV channels place their logos in the top right corner of the screen, though there are exceptions. The corner used may be broadcaster-dependent. Among the big national broadcasters: Channels from the Sony network always use the top right corner, without exception. Star channels also use the top right, with the exception of National Geographic and Nat Geo Wild, which use the top left corner in line with their international counterparts. Past exceptions include The History Channel, whose logo was placed in the top left until it rebranded to Fox History & Entertainment in 2008; the now-defunct Channel V, which used the top left between 2013 and 2016; and Nat Geo People, Nat Geo Music and BabyTV, were withdrawn from India in June 2019. TV18 and Viacom18 channels use the top right corner as well, with the exceptions of regional-language movie channels (e.g., Colors Kannada Cinema and Colors Gujarati Cinema) as well as Colors Super, which have shown their logos at the top left corner since 2018; and VH1, which has always used the bottom right corner. Also, CNBC-TV18, CNBC Awaaz and CNBC Bajar use the bottom right. Moreover, MTV showed its logo in the top left corner until 23 April 2018, when it was moved to the top right (its HD version, launched in 2017, has always used the top right). Unlike most other major networks, the Zee Network's non-news channels containing 'Zee' in their name display their logos at the top left corner and not the top right. This has been the case since 15 October 2017, when almost all the Zee-branded TV channels of the Zee network rebranded with a new logo and, in many cases, a new graphics package and look. Before then, the logos were shown at the top right, as with other broadcasters. (News channels' logos—i.e., logos of channels owned by Zee Media Corporation—stayed put at the top right corner, with the exception of WION, which uses the bottom left.) All the major Zee-branded channels—such as Zee TV, Zee Cinema, Zee Café and the regional-language channels like Zee Tamil, Zee Telugu, Zee Marathi and Zee Bangla—show their logos at the top left; moreover, the Odia-language channel Sarthak TV rebranded to Zee Sarthak and moved its logo to the top left. Among the Zee channels not containing the word 'Zee' that moved their logos to the top left during the big rebrand in 2017 was English movie channel Zee Studio; when it was renamed to &flix on 3 June 2018, the logo remained at the top left. Moreover, Hindi movie channel &pictures has always shown its logo at the top left since its launch in 2013. However, &privé HD, Zee's other English movie channel, and Hindi entertainment channel &TV place the
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Database

In computing, a database is an organized collection of data or a type of data store based on the use of a database management system (DBMS), the software that interacts with end users, applications, and the database itself to capture and analyze the data. The DBMS additionally encompasses the core facilities provided to administer the database. The sum total of the database, the DBMS and the associated applications can be referred to as a database system. Often the term "database" is also used loosely to refer to any of the DBMS, the database system or an application associated with the database. Before digital storage and retrieval of data became widespread, index cards were used for data storage in a wide range of applications and environments: in the home to record and store recipes, shopping lists, contact information and other organizational data; in business to record presentation notes, project research and notes, and contact information; in schools as flash cards or other visual aids; and in academic research to hold data such as bibliographical citations or notes in a card file. Professional book indexers used index cards in the creation of book indexes until they were replaced by indexing software in the 1980s and 1990s. Small databases can be stored on a file system, while large databases are hosted on computer clusters or cloud storage. The design of databases spans formal techniques and practical considerations, including data modeling, efficient data representation and storage, query languages, security and privacy of sensitive data, and distributed computing issues, including supporting concurrent access and fault tolerance. Computer scientists may classify database management systems according to the database models that they support. Relational databases became dominant in the 1980s. These model data as rows and columns in a series of tables, and the vast majority use SQL for writing and querying data. In the 2000s, non-relational databases became popular, collectively referred to as NoSQL, because they use different query languages. == Terminology and overview == Formally, a "database" refers to a set of related data accessed through the use of a "database management system" (DBMS), which is an integrated set of computer software that allows users to interact with one or more databases and provides access to all of the data contained in the database (although restrictions may exist that limit access to particular data). The DBMS provides various functions that allow entry, storage and retrieval of large quantities of information and provides ways to manage how that information is organized. Because of the close relationship between them, the term "database" is often used casually to refer to both a database and the DBMS used to manipulate it. Outside the world of professional information technology, the term database is often used to refer to any collection of related data (such as a spreadsheet or a card index) as size and usage requirements typically necessitate use of a database management system. Existing DBMSs provide various functions that allow management of a database and its data which can be classified into four main functional groups: Data definition – Creation, modification and removal of definitions that detail how the data is to be organized. Update – Insertion, modification, and deletion of the data itself. Retrieval – Selecting data according to specified criteria (e.g., a query, a position in a hierarchy, or a position in relation to other data) and providing that data either directly to the user, or making it available for further processing by the database itself or by other applications. The retrieved data may be made available in a more or less direct form without modification, as it is stored in the database, or in a new form obtained by altering it or combining it with existing data from the database. Administration – Registering and monitoring users, enforcing data security, monitoring performance, maintaining data integrity, dealing with concurrency control, and recovering information that has been corrupted by some event such as an unexpected system failure. Both a database and its DBMS conform to the principles of a particular database model. "Database system" refers collectively to the database model, database management system, and database. Physically, database servers are dedicated computers that hold the actual databases and run only the DBMS and related software. Database servers are usually multiprocessor computers, with generous memory and RAID disk arrays used for stable storage. Hardware database accelerators, connected to one or more servers via a high-speed channel, are also used in large-volume transaction processing environments. DBMSs are found at the heart of most database applications. DBMSs may be built around a custom multitasking kernel with built-in networking support, but modern DBMSs typically rely on a standard operating system to provide these functions. Since DBMSs comprise a significant market, computer and storage vendors often take into account DBMS requirements in their own development plans. Databases and DBMSs can be categorized according to the database model(s) that they support (such as relational or XML), the type(s) of computer they run on (from a server cluster to a mobile phone), the query language(s) used to access the database (such as SQL or XQuery), and their internal engineering, which affects performance, scalability, resilience, and security. == History == The sizes, capabilities, and performance of databases and their respective DBMSs have grown in orders of magnitude. These performance increases were enabled by the technology progress in the areas of processors, computer memory, computer storage, and computer networks. The concept of a database was made possible by the emergence of direct access storage media such as magnetic disks, which became widely available in the mid-1960s; earlier systems relied on sequential storage of data on magnetic tape. The subsequent development of database technology can be divided into three eras based on data model or structure: navigational, SQL/relational, and post-relational. The two main early navigational data models were the hierarchical model and the CODASYL model (network model). These were characterized by the use of pointers (often physical disk addresses) to follow relationships from one record to another. The relational model, first proposed in 1970 by Edgar F. Codd, departed from this tradition by insisting that applications should search for data by content, rather than by following links. The relational model employs sets of ledger-style tables, each used for a different type of entity. Only in the mid-1980s did computing hardware become powerful enough to allow the wide deployment of relational systems (DBMSs plus applications). By the early 1990s, however, relational systems dominated in all large-scale data processing applications, and as of 2018 they remain dominant: IBM Db2, Oracle, MySQL, and Microsoft SQL Server are the most searched DBMS. The dominant database language, standardized SQL for the relational model, has influenced database languages for other data models. Object databases were developed in the 1980s to overcome the inconvenience of object–relational impedance mismatch, which led to the coining of the term "post-relational" and also the development of hybrid object–relational databases. The next generation of post-relational databases in the late 2000s became known as NoSQL databases, introducing fast key–value stores and document-oriented databases. A competing "next generation" known as NewSQL databases attempted new implementations that retained the relational/SQL model while aiming to match the high performance of NoSQL compared to commercially available relational DBMSs. === 1960s, navigational DBMS === The introduction of the term database coincided with the availability of direct-access storage (disks and drums) from the mid-1960s onwards. The term represented a contrast with the tape-based systems of the past, allowing shared interactive use rather than daily batch processing. The Oxford English Dictionary cites a 1962 report by the System Development Corporation of California as the first to use the term "data-base" in a specific technical sense. As computers grew in speed and capability, a number of general-purpose database systems emerged; by the mid-1960s a number of such systems had come into commercial use. Interest in a standard began to grow, and Charles Bachman, author of one such product, the Integrated Data Store (IDS), founded the Database Task Group within CODASYL, the group responsible for the creation and standardization of COBOL. In 1971, the Database Task Group delivered their standard, which generally became known as the CODASYL approach, and soon a number of commercial products based on this approach entered the market. The CODASYL approach of
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Outline of computer security

The following outline is provided as an overview of and topical guide to computer security: Computer security (also cybersecurity, digital security, or information technology (IT) security) is a subdiscipline within the field of information security. It focuses on protecting computer software, systems, and networks from threats that can lead to unauthorized information disclosure, theft, or damage to hardware, software, or data, as well as to the disruption or misdirection of the services they provide. The growing significance of computer security reflects the increasing dependence on computer systems, the Internet, and evolving wireless network standards. This reliance has expanded with the proliferation of smart devices, including smartphones, televisions, and other components of the Internet of things (IoT). (yes) == Essence of computer security == Computer security can be described as all of the following: a branch of security Network security application security == Areas of computer security == Access control – selective restriction of access to a place or other resource. The act of accessing may mean consuming, entering, or using. Permission to access a resource is called authorization. Computer access control – includes authorization, authentication, access approval, and audit. Authentication Knowledge-based authentication Integrated Windows Authentication Password Password length parameter Secure Password Authentication Secure Shell Kerberos (protocol) SPNEGO NTLMSSP AEGIS SecureConnect TACACS Cyber security and countermeasure Device fingerprint Physical security – protecting property and people from damage or harm (such as from theft, espionage, or terrorist attacks). It includes security measures designed to deny unauthorized access to facilities, (such as a computer room), equipment (such as your computer), and resources (like the data storage devices, and data, in your computer). If a computer gets stolen, then the data goes with it. In addition to theft, physical access to a computer allows for ongoing espionage, like the installment of a hardware keylogger device, and so on. Data security – protecting data, such as a database, from destructive forces and the unwanted actions of unauthorized users. Information privacy – relationship between collection and dissemination of data, technology, the public expectation of privacy, and the legal and political issues surrounding them. Privacy concerns exist wherever personally identifiable information or other sensitive information is collected and stored – in digital form or otherwise. Improper or non-existent disclosure control can be the root cause for privacy issues. Internet privacy – involves the right or mandate of personal privacy concerning the storing, repurposing, provision to third parties, and displaying of information pertaining to oneself via the Internet. Privacy can entail either Personally Identifying Information (PII) or non-PII information such as a site visitor's behavior on a website. PII refers to any information that can be used to identify an individual. For example, age and physical address alone could identify who an individual is without explicitly disclosing their name, as these two factors relate to a specific person. Mobile security – security pertaining to smartphones, especially with respect to the personal and business information stored on them. Network security – provisions and policies adopted by a network administrator to prevent and monitor unauthorized access, misuse, modification, or denial of a computer network and network-accessible resources. Network security involves the authorization of access to data in a network, which is controlled by the network administrator. Network Security Toolkit Internet security – computer security specifically related to the Internet, often involving browser security but also network security on a more general level as it applies to other applications or operating systems on a whole. Its objective is to establish rules and measures to use against attacks over the Internet. The Internet represents an insecure channel for exchanging information leading to a high risk of intrusion or fraud, such as phishing. Different methods have been used to protect the transfer of data, including encryption. World Wide Web Security – dealing with the vulnerabilities of users who visit websites. Cybercrime on the Web can include identity theft, fraud, espionage and intelligence gathering. For criminals, the Web has become the preferred way to spread malware. == Computer security threats == Methods of Computer Network Attack and Computer Network Exploitation Social engineering is a frequent method of attack, and can take the form of phishing, or spear phishing in the corporate or government world, as well as counterfeit websites. Password sharing and insecure password practices Poor patch management Computer crime – Computer criminals – Hackers – in the context of computer security, a hacker is someone who seeks and exploits weaknesses in a computer system or computer network. Password cracking – Software cracking – Script kiddies – List of computer criminals – Identity theft – Computer malfunction – Operating system failure and vulnerabilities Hard disk drive failure – occurs when a hard disk drive malfunctions and the stored information cannot be accessed with a properly configured computer. A disk failure may occur in the course of normal operation, or due to an external factor such as exposure to fire or water or high magnetic fields, or suffering a sharp impact or environmental contamination, which can lead to a head crash. Data recovery from a failed hard disk is problematic and expensive. Backups are essential Computer and network surveillance – Man in the Middle Loss of anonymity – when one's identity becomes known. Identification of people or their computers allows their activity to be tracked. For example, when a person's name is matched with the IP address they are using, their activity can be tracked thereafter by monitoring the IP address. HTTP Cookie Local Shared Object Web bug Spyware Adware Cyber spying – obtaining secrets without the permission of the holder of the information (personal, sensitive, proprietary or of classified nature), from individuals, competitors, rivals, groups, governments and enemies for personal, economic, political or military advantage using methods on the Internet, networks or individual computers through the use of cracking techniques and malicious software including Trojan horses and spyware. It may be done online from by professionals sitting at their computer desks on bases in far away countries, or it may involve infiltration at home by computer trained conventional spies and moles, or it may be the criminal handiwork of amateur malicious hackers, software programmers, or thieves. Computer and network eavesdropping Lawful Interception War Driving Packet analyzer (aka packet sniffer) – mainly used as a security tool (in many ways, including for the detection of network intrusion attempts), packet analyzers can also be used for spying, to collect sensitive information (e.g., login details, cookies, personal communications) sent through a network, or to reverse engineer proprietary protocols used over a network. One way to protect data sent over a network such as the Internet is by using encryption software. Cyberwarfare – Exploit – piece of software, a chunk of data, or a sequence of commands that takes advantage of a bug, glitch or vulnerability in order to cause unintended or unanticipated behavior to occur on computer software, hardware, or something electronic (usually computerized). Such behavior frequently includes things like gaining control of a computer system, allowing privilege escalation, or a denial-of-service attack. Trojan Computer virus Computer worm Denial-of-service attack – an attempt to make a machine or network resource unavailable to its intended users, usually consisting of efforts to temporarily or indefinitely interrupt or suspend services of a host connected to the Internet. One common method of attack involves saturating the target machine with external communications requests, so much so that it cannot respond to legitimate traffic, or responds so slowly as to be rendered essentially unavailable. Distributed denial-of-service attack (DDoS) – DoS attack sent by two or more persons. Hacking tool Malware Computer virus Computer worm Keylogger – program that does keystroke logging, which is the action of recording (or logging) the keys struck on a keyboard, typically in a covert manner so that the person using the keyboard is unaware that their actions are being monitored. There are also HID spoofing hardware keyloggers, like a USB device inserting stored keystores when connected. Rootkit – stealthy type of software, typically malicious, designed to hide the existence of certain processes or programs from normal methods of detection and enable contin
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Aarogya Setu

Aarogya Setu (lit. 'The bridge to health') is an Indian COVID-19 "contact tracing, syndromic mapping and self-assessment" digital service, primarily a mobile app, developed by the National Informatics Centre under the Ministry of Electronics and Information Technology (MeitY). The app reached more than 100 million installs in 40 days. On 26 May, amid growing privacy and security concerns, the source code of the app was made public. == Full view == The stated purpose of this app is to spread awareness of COVID-19 and to connect essential COVID-19-related health services to the people of India. This app augments the initiatives of the Department of Health to contain COVID-19 and shares best practices and advisories. It is a tracking app which uses the smartphone's GPS and Bluetooth features to track COVID-19 cases. The app is available for Android and iOS mobile operating systems. With Bluetooth, it tries to determine the risk if one has been near (within six feet of) a COVID-19-infected person, by scanning through a database of known cases across India. Using location information, it determines whether the location one is in belongs to one of the infected areas based on the data available. This app is an updated version of an earlier app called Corona Kavach (now discontinued) which was released earlier by the Government of India. == Features and tools == Aarogya Setu has four sections: User Status (tells the risk of getting COVID-19 for the user) Self Assess (helps the users identify COVID-19 symptoms and their risk profile) COVID-19 Updates (gives updates on local and national COVID-19 cases) E-pass integration (if applied for E-pass, it will be available) See Recent Contacts option (allows the users to assess the risk level of their Bluetooth contacts) It tells how many COVID-19 positive cases are likely in a radius of 500 m, 1 km, 2 km, 5 km and 10 km from the user. The app is built on a platform that can provide an application programming interface (API) so that other computer programs, mobile applications, and web services can make use of the features and data available in Aarogya Setu. == Response == Aarogya Setu crossed five million downloads within three days of its launch, making it one of the most popular government apps in India. It became the world's fastest-growing mobile app, beating Pokémon Go, with more than 50 million installs 13 days after launching in India on 2 April 2020. It reached 100 million installs by 13 May 2020, that is in 40 days since its launch. In an order on 29 April 2020 the central government made it mandatory for all employees to download the app and use it – "Before starting for office, they must review their status on Aarogya Setu and commute only when the app shows safe or low risk". The Union Home Ministry also said that the application is mandatory for all living in the COVID-19 containment zone. The government gave the announcement along with the nationwide lockdown extension by two weeks from the 4 May with certain relaxations. On 21 May 2020, the Airport Authority of India issued a Standard Operating Procedure (SOP) stating that all departing passengers must compulsorily be registered with the Aarogya Setu app. It added that the app would not be mandatory for children below 14 years. However, the next day, Civil Aviation Minister Hardeep Singh Puri clarified that the app would not be mandatory for any passengers. On 26 May 2020, the Aarogya Setu app code was made open to developers across the globe to help other countries manage contact tracing in their fight against COVID-19 pandemic. In March 2021, Co-WIN portal was integrated with the app. This allowed users to schedule an appointment through the app for COVID-19 vaccine by registering their phone number and providing relevant documents. == Effectiveness == NITI Aayog CEO revealed that "the app has been able to identify more than 3,000 hotspots in 3–17 days ahead of time." However, users and experts in India and around the world say the app raises huge data security concerns. The app collects name, number, gender, travel history, and uses a phone's Bluetooth and location data to let users know if they have been near a person with COVID-19 by scanning a database of known cases of infection, and also share it with the government simultaneously. This is the major area of concern as the app's constant access to a phone's Bluetooth imposes a form of security threat. But it stood to clarify itself that the informations received are not going to be made public. Amidst all these, the app hits a record of about one-hundred million downloads. == Reception == Rahul Gandhi, leader of the Congress party, termed the Aarogya Setu application a "sophisticated surveillance system" after the government announced that downloading the app would be mandatory for both government and private employees. Following this, others raised the same concerns about the Aarogya Setu app. The Ministry of Electronics and Information Technology (MeitY) responded to these concerns by asserting that Gandhi's claims were false, and that the app was being appreciated internationally. On 5 May, French ethical hacker Robert Baptiste, who goes by the name Elliot Alderson on Twitter, claimed that there were security issues with the app. The Indian government, as well as the app developers, responded to this claim by thanking the hacker for his attention, but dismissed his concerns. The developers of the app stated that the fetching of location data is a documented feature of the app, rather than a flaw, since the app is designed to track the distribution of the virus-infected population. They also asserted that no personal information of any user has been proven to be at risk. On 6 May, Robert Baptiste tweeted that security vulnerabilities in Aarogya Setu allowed hackers to "know who is infected, unwell, [or] made a self assessment in the area of his choice". He also gave details of how many people were unwell and infected at the Prime Minister's Office, the Indian Parliament and the Home Office. The Economic Times pointed out that a clause in the app's Terms and Conditions stated that the user "agrees and acknowledges that the Government of India will not be liable for ... any unauthorised access to your information or modification thereof". In response, several software developers called for the source code to be made public. On 12 May, former Supreme Court Judge Justice B.N. Srikrishna termed the government's push mandating the use of Aarogya Setu app "utterly illegal". He said so far it is not backed by any law and questioned "under what law, government is mandating it on anyone". MIT Technology Review gave 2 out of 5 stars to Aarogya Setu app after analyzing the COVID contact tracing apps launched in 25 countries. The app got stars only for the policy which suggests that data collected is deleted after a period of time and that the data collection, as far as user inputs go, is minimal. It also highlighted that India is the only democracy making its app mandatory for millions of people. The rating was further downgraded from 2 to 1 for collecting more information than the app needs to function. Following this, the MeitY made the source code of the Android app public on GitHub on 26 May, which will be followed by iOS and API documentation. Further, the Government has also launched a "bug bounty program". This was done to "promote transparency and ensure security and integrity of the app". However, experts stated that the server-side code had not yet been publicly released, which meant that public opinion on security and privacy was yet to be completely assuaged. Following this, ZDNet noted that the source code seemed to confirm the government's claim that user location data, if collected, would be anonymised and would be deleted after 45 days, or 60 days for high-risk individuals.
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Visible (mobile app)

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

In computer graphics, tessellation is the dividing of datasets of polygons (sometimes called vertex sets) presenting objects in a scene into suitable structures for rendering. Especially for real-time rendering, data is tessellated into triangles, for example in OpenGL 4.0 and Direct3D 11. == In graphics rendering == A key advantage of tessellation for realtime graphics is that it allows detail to be dynamically added and subtracted from a 3D polygon mesh and its silhouette edges based on control parameters (often camera distance). In previously leading realtime techniques such as parallax mapping and bump mapping, surface details could be simulated at the pixel level, but silhouette edge detail was fundamentally limited by the quality of the original dataset. In Direct3D 11 pipeline (a part of DirectX 11), the graphics primitive is the patch. The tessellator generates a triangle-based tessellation of the patch according to tessellation parameters such as the TessFactor, which controls the degree of fineness of the mesh. The tessellation, along with shaders such as a Phong shader, allows for producing smoother surfaces than would be generated by the original mesh. By offloading the tessellation process onto the GPU hardware, smoothing can be performed in real time. Tessellation can also be used for implementing subdivision surfaces, level of detail scaling and fine displacement mapping. OpenGL 4.0 uses a similar pipeline, where tessellation into triangles is controlled by the Tessellation Control Shader and a set of four tessellation parameters. == In computer-aided design == In computer-aided design the constructed design is represented by a boundary representation topological model, where analytical 3D surfaces and curves, limited to faces, edges, and vertices, constitute a continuous boundary of a 3D body. Arbitrary 3D bodies are often too complicated to analyze directly. So they are approximated (tessellated) with a mesh of small, easy-to-analyze pieces of 3D volume—usually either irregular tetrahedra, or irregular hexahedra. The mesh is used for finite element analysis. The mesh of a surface is usually generated per individual faces and edges (approximated to polylines) so that original limit vertices are included into mesh. To ensure that approximation of the original surface suits the needs of further processing, three basic parameters are usually defined for the surface mesh generator: The maximum allowed distance between the planar approximation polygon and the surface (known as "sag"). This parameter ensures that mesh is similar enough to the original analytical surface (or the polyline is similar to the original curve). The maximum allowed size of the approximation polygon (for triangulations it can be maximum allowed length of triangle sides). This parameter ensures enough detail for further analysis. The maximum allowed angle between two adjacent approximation polygons (on the same face). This parameter ensures that even very small humps or hollows that can have significant effect to analysis will not disappear in mesh. An algorithm generating a mesh is typically controlled by the above three and other parameters. Some types of computer analysis of a constructed design require an adaptive mesh refinement, which is a mesh made finer (using stronger parameters) in regions where the analysis needs more detail.
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Gooch shading

Gooch shading is a non-photorealistic rendering technique for shading objects. It is also known as "cool to warm" shading, and is widely used in technical illustration. == History == Gooch shading was developed by Amy Gooch et al. at the University of Utah School of Computing and first presented at the 1998 SIGGRAPH conference. It has since been implemented in shader libraries, software, and games released by Autodesk, Nvidia, and Valve. == Process == Gooch shading defines an additional two colors in conjunction with the original model color: a warm color (such as yellow) and a cool color (such as blue). The warm color indicates surfaces that are facing toward the light source while the cool color indicates surfaces facing away. This allows shading to occur only in mid-tones so that edge lines and highlights remain visually prominent. The Gooch shader is typically implemented in two passes: all objects in the scene are first drawn with the "cool to warm" shading, and in the second pass the object's edges are rendered in black.
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CityEngine

ArcGIS CityEngine is a commercial 3D modeling program. Developed by Esri R&D Center Zurich (formerly Procedural Inc.), it specializes in the generation of 3D urban environments to support the creation of detailed large-scale 3D city models. Unlike traditional 3D modeling methodology, which uses computer-aided design (CAD) tools and techniques, CityEngine takes a procedural modeling approach which shapes generation via a rules-based system. Due to its integration with the wider ArcGIS platform, CityEngine can also be used with geographic information system (GIS) datasets. CityEngine can be used for urban planning and architecture, graphics visualization, game development, entertainment, and archeology. CityEngine can be used to visualize the building information modeling (BIM) data of buildings in a larger urban context, making for more realistic construction projects. == History and releases == === Software history === ArcGIS CityEngine, originally named Esri CityEngine, was developed at Swiss technology university ETH Zurich by Pascal Mueller, the co-founder and CEO of Procedural Inc. While researching for his PhD at the ETH Computer Vision Lab, Mueller invented a number of techniques for procedural modeling of 3D architecture that make up the foundation of CityEngine. CityEngine publically debuted at the 2001 SIGGRAPH conference; since then, additional research papers have been published that have contributed to CityEngine and its features. The first commercial version of CityEngine was released in 2008. In 2007, Procedural Inc. was founded and separated from ETH Zurich, the top-ranking technology university in Switzerland. In the summer of 2011, Procedural Inc. was acquired by Esri Inc., becoming Esri R&D Center Zurich. Esri CityEngine was renamed to ArcGIS CityEngine in June 2020 to offically make it a part of the ArcGIS software suite. === Releases === === Licensing and pricing === ArcGIS CityEngine is included in the Professional and Professional Plus tiers of ArcGIS Online. Pricing may vary by region and distributors. In the US, the professional tier costs US$2,200 per year; in the UK, it is £4,200 per year (excluding VAT). CityEngine can be purchased elsewhere via a local Esri partner. . Once purchased, users can download and obtain license details from the MyEsri portal. == Features == CGA (computer generated architecture) parametric modeling rules to control mass, geometry assets, proportions, or texturing of buildings or streets on a citywide scale Select a target location and import geo-referenced satellite imagery and 3D terrain of the location to more quickly build accurate urban environments through OpenStreetMap integration Interactively control specific street or building parameters, such as height or age Import/export geo-spatial/vector data with industry-standard formats such as Esri Shapefile, File Geodatabase, and OpenStreetMap, as well as file formats for WebGL, KMZ, Collada, Autodesk FBX, Autodesk Maya, 3DS, Wavefront OBJ, RenderMan RIB, Alembic, e-on software's Vue, Universal Scene Description USD, Khronos Group GLTF, Unreal Engine, and Unreal Datasmith Script and generate rules-based reports to show socioeconomic figures (e.g., Gross Floor Area (GFA) and Floor Area Ratio (FAR)) to analyze their urban design proposals. VR viewing of modeled environments with Samsung Gear VR Use a variety of materials through the Esri materials library == Procedural modeling == ArcGIS CityEngine uses a procedural modeling approach to automatically generate models through a predefined rule set. The rules are defined through a CGA shape grammar system, enabling the creation of complex parametric models. Users can change or add the shape grammar as needed. Urban environments can be modeled within CityEngine by starting with creating a street network (either from the street drawing tool or with data imported from map data). Then, lots may be subdivided as many times as specified, resulting in a map of multiple lots and streets. CityEngine can then be instructed to start generating the buildings using defined procedural modeling rules. At this point, the city model can be re-designed and adjusted by changing the parameters or the shape grammar. === Geodesign === Though CityEngine is not an analytical tool like GIS, discussions about geodesign often mention the use of ArcGIS CityEngine. As it can be used to enhance 3D shape generation in ArcGIS, ArcGIS CityEngine is a critical product to improve the applicability of geodesign by using geospatial information to design or analyze a city. == Applications == === Urban design and planning === Garsdale Design used ArcGIS CityEngine in the creation of city master plans in Iraq before 2013, both to model existing historic areas and also model future plans. Larger companies like Foster+Partners and HOK Architects have also used CityEngine in their urban planning projects. === Urban and environmental studies === Because its primary feature is building informative city models, some urban researchers use CityEngine to compare land-use planning schemes, for example in very dense global cities such as Hong Kong and Seoul. Environmental scientists can also utilize the instant 3D model generation in CityEngine, which can make for more convenient informative research than modeling a city by creating each building individually. === Game development === CityEngine can be used as a tool in the creation of video games that require detailed 3D environments to assign interactive scripts. === Movie industry === Zootopia (also known outside of the US as Zootopolis), which won the 2016 Academy Award for Best Animated Feature Film, used CityEngine to model the city in its movie. multi-scaling city, the designers used CityEngine due to its rule-based system. CityEngine was also used to create Big Hero 6's San-Fransokyo. === Military === Due to its integration with the Esri product suite and its ability to process geospatial data to create 3D scenes/maps, CityEngine can be used within military/defense organizations. == List of movies and TV shows using CityEngine == Studios and companies rarely state what software they use in their pipelines. When CityEngine is mentioned as a tool in production, it's often in a small reference in a larger article. Movies only claimed to use CityEngine by a single Esri employee Presented at FMX 2025 workshop == Ports == ArcGIS CityEngine is built on top of Eclipse IDE, and has therefore able to be used on Windows and Linux operating systems. Support for macOS was stopped in March 2021. == Plugins and extensions == ArcGIS CityEngine currently works with a number of third party 3D modeling, rendering, and analytical software products via its SDK and API; these currently are: ArcGIS CityEngine for ArcGIS Urban: ArcGIS Urban Suite Puma: ArcGIS CityEngine for Rhinoceros 3D Palladio: ArcGIS CityEngine for Houdini Serlio: ArcGIS CityEngine for Maya PyPRT: ArcGIS CityEngine for Python ArcGIS CityEngine provides a Python scripting interface built on Jython (current version 2.7.0) which allows users to create their own tools and functionality. == Publications ==
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Jeremy Renner Official

Jeremy Renner Official (or Jeremy Renner on the Google Play Store) was a mobile app created by American actor Jeremy Renner. He created the app in March 2017 to hear the input and comments of his fans. The app was shut down in September 2019 in part due to the frequent bullying and trolling that the platform had experienced. The app featured optional microtransactions, with some ranging up to roughly US$400 despite the app itself being free. Upon shutting down the app, Renner issued a mass-refund for the collectible "stars" in the app for purchases made within the last ninety days, from the day the announcement was posted. He then posted an apology to the app itself, and the app was deleted from both the Google Play Store and the App Store shortly after. == Usage == Upon downloading the app, the user was faced with a video of Renner speaking about his fans and superfans, regular giveaways, and real-life updates. While the app was active, Renner posted regular questions and comments for fans. Renner occasionally livestreamed about his work and day-to-day life. The community developed to include memes, selfies, and a "Happy Rennsday" event on Wednesdays. == History == === 2017–2019 === The app launched in March 2017 with a promotional contest. Renner's fans were encouraged to download the app and create comments about being Renner's biggest fan; Renner would then choose a winner and transport the winner and a guest to have lunch with him at the Calgary Expo. In the first few months Renner teased behind-the-scenes of projects he was working on, which he now sporadically does on Instagram. The app was similarly designed to Instagram as well, with a near identically styled layout. Around midway through 2019, a hoax account of Renner was made to mock the celebrity, joking about masturbating to porn and defending another hoax account of Casey Anthony. FastCompany wrote extensively about Renner's app in April 2019, calling it "a surprising new kind of social media". The Ringer stated "Jeremy Renner's Jeremy Renner app is the Jeremy Renner of apps." === After deletion (2019–2020) === After the shutdown of the app, a comedy-based pseudo-app with modular endings was released, called "The Jeremy Renner App Experience", in which the player plays as Jeremy Renner on the day of the Jeremy Renner Official app's shutdown. The app details several different choices on how Renner handles the situation. A six-part podcast was also created to mock the app's deletion, called The Renner Files, featuring Carolyn Goldfarb and Sarah Ramos. == Controversies == === Marketing === One of the main controversies of Renner's app was its marketing. The app's developers, Escapex, specialized in and grew famous for making similar monetized apps for celebrities. The marketing campaign was based on direct contact with Renner, whose chances were increased with regular payments for "stars", although very few encounters seemed to happen with Renner himself. The multiple problems with the app led the CEO of Escapex, Sephi Shapira, to call the app a "freak situation", and added "Am I concerned about this? Not more than I'm concerned about 50 other things I'm dealing with as a startup company." Along with the marketing failures, the app was seen as misrepresenting itself as seemingly erotic with some advertisements featuring Renner suggestively staring at the camera, despite the actual app being initially considered safe for children. === Harassment === After its release in 2017, the app was met with waves of harassment and bullying by many users on the app, most frequently by using impersonation — referenced in Renner's apology/deletion notice. Some death threats were made across the app by fraud accounts pretending to be several controversial celebrities, including O. J. Simpson and Casey Anthony. As early as October 2017, there were claims of censorship, bullying, and "contest-rigging". In September 2019, comedian Stefan Heck publicized his discovery of the fact that replies through the app appeared as if they were sent by Renner himself in push notifications. After several users abused this feature, Renner asked Escapex to shut down the app.
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Interlacing (bitmaps)

In computing, interlacing (also known as interleaving) is a method of encoding a bitmap image such that a person who has partially received it sees a degraded copy of the entire image. When communicating over a slow communications link, this is often preferable to seeing a perfectly clear copy of one part of the image, as it helps the viewer decide more quickly whether to abort or continue the transmission. Interlacing is supported by the following formats, where it is optional: GIF interlacing stores the lines in the order 0 , 8 , 16 , … , ( 8 n ) , 4 , 12 , … , ( 8 n + 4 ) , 2 , 6 , 10 , 14 , … , ( 4 n + 2 ) , 1 , 3 , 5 , 7 , 9 , … , ( 2 n + 1 ) . {\displaystyle 0,8,16,\dots ,(8n),\ 4,12,\dots ,(8n+4),\ 2,6,10,14,\dots ,(4n+2),\ 1,3,5,7,9,\dots ,(2n+1).} PNG uses the Adam7 algorithm, which interlaces in both the vertical and horizontal direction. TGA uses two optional interlacing algorithms: Two-way: 0 , 2 , 4 , … , ( 2 n ) , 1 , 3 , … , ( 2 n + 1 ) , {\displaystyle 0,2,4,\dots ,(2n),\ 1,3,\dots ,(2n+1),} And four-way: 0 , 4 , 8 , … , ( 4 n ) , 1 , 5 , … , ( 4 n + 1 ) , 2 , 6 , … , ( 4 n + 2 ) , 3 , 7 , … , ( 4 n + 3 ) . {\displaystyle 0,4,8,\dots ,(4n),\ 1,5,\dots ,(4n+1),\ 2,6,\dots ,\ (4n+2),3,7,\dots ,(4n+3).} JPEG, JPEG 2000, and JPEG XR (actually using a frequency decomposition hierarchy rather than interlacing of pixel values) PGF (also using a frequency decomposition) Interlacing is a form of incremental decoding, because the image can be loaded incrementally. Another form of incremental decoding is progressive scan. In progressive scan the loaded image is decoded line for line, so instead of becoming incrementally clearer it becomes incrementally larger. The main difference between the interlace concept in bitmaps and in video is that even progressive bitmaps can be loaded over multiple frames. For example: Interlaced GIF is a GIF image that seems to arrive on your display like an image coming through a slowly opening Venetian blind. A fuzzy outline of an image is gradually replaced by seven successive waves of bit streams that fill in the missing lines until the image arrives at its full resolution. Interlaced graphics were once widely used in web design and before that in the distribution of graphics files over bulletin board systems and other low-speed communications methods. The practice is much less common today, as common broadband internet connections allow most images to be downloaded to the user's screen nearly instantaneously, and interlacing is usually an inefficient method of encoding images. Interlacing has been criticized because it may not be clear to viewers when the image has finished rendering, unlike non-interlaced rendering, where progress is apparent (remaining data appears as blank). Also, the benefits of interlacing to those on low-speed connections may be outweighed by having to download a larger file, as interlaced images typically do not compress as well.
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