AI Email Response Generator Free

AI Email Response Generator Free — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Dailyhunt

    Dailyhunt

    Dailyhunt (formerly Newshunt) is an Indian content and news aggregator application based in Bangalore, India that provides local language content in 14 Indian languages from multiple content providers. Viru serves as Founder of Dailyhunt with Co-founder Umang Bedi. == History == Dailyhunt, earlier called Newshunt, was created as a Symbian app in 2009 by two ex-Nokia employees Umesh Kulkarni and Chandrashekhar Sohoni. Later in 2011, Newshunt became available on the Android platform. It was by that time that Virendra Gupta, founder of Verse acquired the application. Virendra Gupta, better known as Viru, had started Verse in 2007 as a value-added service (VAS) company. In 2011, he acquired Newshunt from its owners Umesh and Chandrashekhar. Umesh became the CTO and stayed on to oversee its transition towards the smartphone era. In 2015, Viru renamed Newshunt as Dailyhunt. In early 2018, Viru roped in Umang Bedi, to be the President of Dailyhunt and lead the business with him while focusing on making the benefits of the platform available to a larger audience. Umang was elevated to co-founder in 2020. == Funding == In September 2014, Dailyhunt (then known as Newshunt) closed its Series B funding of INR 1 billion ( or approx $12 million in 2014) from Sequoia Capital India. The Series C funding round was led by Falcon Capital and was closed with $40 million in February 2015. In October 2016, the company received its Series D funding of $25 million from ByteDance and a Series E funding of $6.39 million from Falcon Edge Capital in September 2018. Additionally, Dailyhunt raised $3 Mn (INR 21.75 Cr) in a Series F funding round from Stonebridge Capital in August 2019. Other investors of Dailyhunt include Matrix Partners India, Omidyar Network, Goldman Sachs and Sofina. == Tie-ups and partnerships == In January 2021, Dailyhunt partnered with Twitter to bring ‘Twitter Moments’ to the Indian social app. Dailyhunt app now has a dedicated tab called “Twitter Moments India” to showcase curated tweets pertaining to news and other events. In January 2021, Dailyhunt announced the premiere of Season 2 of the popular show QuoteUnquote with KK (Kapil Khandelwal) on the app. It was the first podcast to have been launched on the Dailyhunt app. In September 2020, Dailyhunt signed up as an Associate Sponsor with Star Sports for Dream 11 IPL 2020. In May 2020, Snapdeal partnered with Dailyhunt to add new content on marketplace. In March 2019, Discovery Communications India, the factual entertainment network, entered into a multi-year partnership with Dailyhunt to showcase short-form content.

    Read more →
  • Web developer

    Web developer

    A web developer is a programmer who develops World Wide Web applications using a client–server model. The applications typically use HTML, CSS, and JavaScript in the client, and any general-purpose programming language in the server. HTTP is used for communications between client and server. A web developer may specialize in client-side applications (Front-end web development), server-side applications (back-end development), or both (full-stack development). == Prerequisite == There are no formal educational or license requirements to become a web developer. However, many colleges and trade schools offer coursework in web development. There are also many tutorials and articles which teach web development, often freely available on the web - for example, on JavaScript. Even though there are no formal requirements, web development projects require web developers to have knowledge and skills such as: Using HTML, CSS, and JavaScript Programming/coding/scripting in one of the many server-side languages or frameworks Understanding server-side/client-side architecture and communication of the kind mentioned above Ability to utilize a database

    Read more →
  • Power cycling

    Power cycling

    Power cycling is the act of turning a piece of equipment, usually a computer, off and then on again. Reasons for power cycling include having an electronic device reinitialize its set of configuration parameters or recover from an unresponsive state of its mission critical functionality, such as in a crash or hang situation. Power cycling can also be used to reset network activity inside a modem. It can also be among the first steps for troubleshooting an issue. == Overview == Power cycling can be done manually, usually using the power switch on the device, or remotely, through some type of external device connected to the power input. In the data center environment, remote control power cycling can usually be done through a power distribution unit, over the network. In the home environment, this can be done through home automation powerline communications. Most Internet service providers publish a "how-to" on their website showing their customers the correct procedure to power cycle their devices. Power cycling is a common diagnostic procedure usually performed first when a computer system freezes. However, frequently power cycling a computer can cause thermal stress. Reset has an equal effect on the software but may be less problematic for the hardware as power is not interrupted. == Historical uses == On all Apollo missions to the moon, the landing radar was required to acquire the surface before a landing could be attempted. But on Apollo 14, the landing radar was unable to lock on. Mission control told the astronauts to cycle the power. They did, the radar locked on just in time, and the landing was completed. During the Rosetta mission to comet 67P/Churyumov–Gerasimenko, the Philae lander did not return the expected telemetry on awakening after arrival at the comet. The problem was diagnosed as "somehow a glitch in the electronics", engineers cycled the power, and the lander awoke correctly. During the launch of the billion dollar AEHF-6 satellite on 26 March 2020 by an Atlas V rocket from Cape Canaveral Space Force Station in Florida, a hold was called at T-46 seconds due to hydraulic system not responding as expected. The launch crew turned it off and back on, and the launch proceeded normally. In 2023 the Interstellar Boundary Explorer spacecraft stopped responding to commands after an anomaly. When gentler techniques failed, NASA resorted to rebooting the spacecraft with the remote equivalent of a power cycle.

    Read more →
  • Digital citizen

    Digital citizen

    The term digital citizen is used with different meanings. According to the definition provided by Karen Mossberger, one of the authors of Digital Citizenship: The Internet, Society, and Participation, digital citizens are "those who use the internet regularly and effectively". In this sense, a digital citizen is a person who uses information technology (IT) to engage in society, politics, and government. More recent elaborations of the concept define digital citizenship as the self-enactment of people’s role in society through the use of digital technologies, stressing the empowering and democratizing characteristics of the citizenship idea. These theories aim at taking into account the ever-increasing datafication of contemporary societies (symbolically linked to the Snowden leaks), which has called into question the meaning of “being (digital) citizens in a datafied society”. This condition is also referred to as the “algorithmic society”, characterised by the increasing datafication of social life and the pervasive presence of surveillance practices – see surveillance and surveillance capitalism, the use of artificial intelligence, and Big Data. Datafication presents crucial challenges for the very notion of citizenship, so that data collection can no longer be seen as an issue of privacy alone so that:We cannot simply assume that being a citizen online already means something (whether it is the ability to participate or the ability to stay safe) and then look for those whose conduct conforms to this meaning Instead, the idea of digital citizenship shall reflect the idea that we are no longer mere “users” of technologies since they shape our agency both as individuals and as citizens. Digital citizenship refers to the responsible and respectful use of technology to engage online, evaluate information, and protect human rights. It encompasses skills for communication, collaboration, empathy, privacy protection, and security to prevent data breaches and identity theft. == Digital citizenship in the "algorithmic society" == In the context of the algorithmic society, the question of digital citizenship "becomes one of the extents to which subjects are able to challenge, avoid or mediate their data double in this datafied society”. These reflections put the emphasis on the idea of the digital space (or cyberspace) as a political space where the respect of fundamental rights of the individual shall be granted (with reference both to the traditional ones as well as to new specific rights of the internet [see “digital constitutionalism”]) and where the agency and the identity of the individuals as citizens is at stake. This idea of digital citizenship is thought to be not only active but also performative, in the sense that “in societies that are increasingly mediated through digital technologies, digital acts become important means through which citizens create, enact and perform their role in society.” In particular, for Isin and Ruppert this points towards an active meaning of (digital) citizenship based on the idea that we constitute ourselves as digital citizen by claiming rights on the internet, either by saying or by doing something. == Types of digital participation == People who characterize themselves as digital citizens often use IT extensively—creating blogs, using social networks, and participating in online journalism. Although digital citizenship begins when any child, teen, or adult signs up for an email address, posts pictures online, uses e-commerce to buy merchandise online, and/or participates in any electronic function that is B2B or B2C, the process of becoming a digital citizen goes beyond simple internet activity. According to Thomas Humphrey Marshall, a British sociologist known for his work on social citizenship, a primary framework of citizenship comprises three different traditions: liberalism, republicanism, and ascriptive hierarchy. Within this framework, the digital citizen needs to exist in order to promote equal economic opportunities and increase political participation. In this way, digital technology helps to lower the barriers to entry for participation as a citizen within a society. They also have a comprehensive understanding of digital citizenship, which is the appropriate and responsible behavior when using technology. Since digital citizenship evaluates the quality of an individual's response to membership in a digital community, it often requires the participation of all community members, both visible and those who are less visible. A large part in being a responsible digital citizen encompasses digital literacy, etiquette, online safety, and an acknowledgement of private versus public information. The development of digital citizen participation can be divided into two main stages. The first stage is through information dissemination, which includes subcategories of its own: static information dissemination, characterized largely by citizens who use read-only websites where they take control of data from credible sources in order to formulate judgments or facts. Many of these websites where credible information may be found are provided by the government. dynamic information dissemination, which is more interactive and involves citizens as well as public servants. Both questions and answers can be communicated, and citizens have the opportunity to engage in question-and-answer dialogues through two-way communication platforms The second stage of digital citizen participation is citizen deliberation, which evaluates what type of participation and role that they play when attempting to ignite some sort of policy change. static citizen participants can play a role by engaging in online polls as well as through complaints and recommendations sent up, mainly toward the government who can create changes in policy decisions. dynamic citizen participants can deliberate amongst others on their thoughts and recommendations in town hall meetings or various media sites. One potential advantage of online participation through digital citizenship is increased social inclusion. In a report on civic engagement, citizen-powered democracy can be initiated either through information shared through the web, direct communication signals made by the state toward the public, and social media tactics from both private and public companies. In fact, it was found that the community-based nature of social media platforms allow individuals to feel more socially included and informed about political issues that peers have also been found to engage with, otherwise known as a "second-order effect." Understanding strategic marketing on social media would further explain social media customers’ participation. Two types of opportunities rise as a result, the first being the ability to lower barriers that can make exchanges much easier. In addition, they have the chance to participate in transformative disruption, giving people who have a historically lower political engagement to mobilize in a much easier and convenient fashion. Nonetheless, there are several challenges that face the presence of digital technologies in political participation. Both current as well as potential challenges can create significant risks for democratic processes. Not only is digital technology still seen as relatively ambiguous, it was also seen to have "less inclusivity in democratic life." Demographic groups differ considerably in the use of technology, and thus, one group could potentially be more represented than another as a result of digital participation. Another primary challenge consists in the ideology of a "filter bubble" effect. Alongside a tremendous spread of false information, internet users could reinforce existing prejudices and assist in polarizing disagreements in the public sphere. This can lead to misinformed voting and decisions based on exposure rather than on pure knowledge. A communication technology director, Van Dijk, stated, "Computerized information campaigns and mass public information systems have to be designed and supported in such a way that they help to narrow the gap between the 'information rich' and 'information poor' otherwise the spontaneous development of ICT will widen it." Access and equivalent amounts of knowledge behind digital technology must be equivalent in order for a fair system to put into place. Alongside a lack of evidenced support for technology that can be proven to be safe for citizens, the OECD has identified five struggles for the online engagement of citizens: Scale: To what extent can a society allow every individual's voice to be heard, but also not be lost in the mass debate? This can be extremely challenging for the government, which may not effectively know how to listen and respond to each individual contribution. Capacity: How can digital technology offer citizens more information on public policy-making? The opportunity for citizens to debate with one another is lacking for acti

    Read more →
  • Explanation-based learning

    Explanation-based learning

    Explanation-based learning (EBL) is a form of machine learning that exploits a very strong, or even perfect, domain theory (i.e. a formal theory of an application domain akin to a domain model in ontology engineering, not to be confused with Scott's domain theory) in order to make generalizations or form concepts from training examples. It is also linked with Encoding (memory) to help with Learning. == Details == An example of EBL using a perfect domain theory is a program that learns to play chess through example. A specific chess position that contains an important feature such as "Forced loss of black queen in two moves" includes many irrelevant features, such as the specific scattering of pawns on the board. EBL can take a single training example and determine what are the relevant features in order to form a generalization. A domain theory is perfect or complete if it contains, in principle, all information needed to decide any question about the domain. For example, the domain theory for chess is simply the rules of chess. Knowing the rules, in principle, it is possible to deduce the best move in any situation. However, actually making such a deduction is impossible in practice due to combinatoric explosion. EBL uses training examples to make searching for deductive consequences of a domain theory efficient in practice. In essence, an EBL system works by finding a way to deduce each training example from the system's existing database of domain theory. Having a short proof of the training example extends the domain-theory database, enabling the EBL system to find and classify future examples that are similar to the training example very quickly. The main drawback of the method—the cost of applying the learned proof macros, as these become numerous—was analyzed by Minton. === Basic formulation === EBL software takes four inputs: a hypothesis space (the set of all possible conclusions) a domain theory (axioms about a domain of interest) training examples (specific facts that rule out some possible hypothesis) operationality criteria (criteria for determining which features in the domain are efficiently recognizable, e.g. which features are directly detectable using sensors) == Application == An especially good application domain for an EBL is natural language processing (NLP). Here a rich domain theory, i.e., a natural language grammar—although neither perfect nor complete, is tuned to a particular application or particular language usage, using a treebank (training examples). Rayner pioneered this work. The first successful industrial application was to a commercial NL interface to relational databases. The method has been successfully applied to several large-scale natural language parsing systems, where the utility problem was solved by omitting the original grammar (domain theory) and using specialized LR-parsing techniques, resulting in huge speed-ups, at a cost in coverage, but with a gain in disambiguation. EBL-like techniques have also been applied to surface generation, the converse of parsing. When applying EBL to NLP, the operationality criteria can be hand-crafted, or can be inferred from the treebank using either the entropy of its or-nodes or a target coverage/disambiguation trade-off (= recall/precision trade-off = f-score). EBL can also be used to compile grammar-based language models for speech recognition, from general unification grammars. Note how the utility problem, first exposed by Minton, was solved by discarding the original grammar/domain theory, and that the quoted articles tend to contain the phrase grammar specialization—quite the opposite of the original term explanation-based generalization. Perhaps the best name for this technique would be data-driven search space reduction. Other people who worked on EBL for NLP include Guenther Neumann, Aravind Joshi, Srinivas Bangalore, and Khalil Sima'an.

    Read more →
  • Radio code

    Radio code

    A radio code is any code that is commonly used over a telecommunication system such as Morse code, brevity codes and procedure words. == Brevity code == Brevity codes are designed to convey complex information with a few words or codes. Specific brevity codes include: ACP-131 Aeronautical Code signals ARRL Numbered Radiogram Multiservice tactical brevity code Ten-code Phillips Code NOTAM Code === Operating signals === Brevity codes that are specifically designed for use between communications operators and to support communication operations are referred to as "operating signals". These include: Prosigns for Morse code 92 Code, Western Union telegraph brevity codes Q code, initially developed for commercial radiotelegraph communication, later adopted by other radio services, especially amateur radio. Used since circa 1909. QN Signals, published by the ARRL and used by Amateur radio operators to assist in the transmission of ARRL Radiograms in the National Traffic System. R and S brevity codes, published by the British Post Office in 1908 for coastal wireless stations and ships, superseded in 1912 by Q codes X code, used by European military services as a wireless telegraphy code in the 1930s and 1940s Z code, also used in the early days of radiotelegraph communication. == Other == Morse code is commonly used in amateur radio. Morse code abbreviations are a type of brevity code. Procedure words used in radiotelephony procedure, are a type of radio code. Spelling alphabets, including the ICAO spelling alphabet, are commonly used in communication over radios and telephones. == Other meanings == Many car audio systems (car radios) have a so-called 'radio code' number which needs to be entered after a power disconnection. This was introduced as a measure to deter theft of these devices. If the code is entered correctly, the radio is activated for use. Entering the code incorrectly several times in a row will cause a temporary or permanent lockout. Some car radios have another check which operates in conjunction with car electronics. If the VIN or another vehicle ID matches the previously stored one, the radio is activated. If the radio cannot verify the vehicle, it is considered to be moved into another vehicle. The radio will then request for the code number or simply refuse to operate and display an error message such as "CANCHECK" or "SECURE".

    Read more →
  • Electronics (journal)

    Electronics (journal)

    Electronics is a peer-reviewed, scientific journal that covers the study of electronics, including the design, development, and application of electronic devices, systems, and circuits. The journal is published by MDPI and was established in 2012. The editor-in-chief is Flavio Canavero 'Politecnico di Torino). The journal covers a wide range of topics related to electronics, including: electronic devices, electronic materials, electronic circuits, electronic systems, communication electronics, power electronics, and biomedical electronics. The journal also includes articles on the application of electronics in various fields, such as consumer electronics, industrial electronics, automotive electronics, and military electronics. The journal publishes original research articles, review articles, and short communications. == Abstracting and indexing == EBSCO databases ProQuest databases Scopus According to the Journal Citation Reports, the journal has a 2021 impact factor of 2.690.

    Read more →
  • DBOS

    DBOS

    DBOS (Formerly Database-Oriented Operating System, now just DBOS) is an open source durable workflow execution software library written for the Python, TypeScript, Java, and Go programming languages. DBOS arose from a joint open source project from MIT and Stanford, after a discussion between Michael Stonebraker and Matei Zaharia on how to scale and improve scheduling and performance of millions of Apache Spark tasks. Today it is a commercial company that offers an open source system to add durable computing to any software, built on concepts derived from the joint research project. == History == === 2020: Academic R&D Project === DBOS originated in 2020 as a joint open source project between MIT, Stanford, and Carnegie Mellon. The project explored the idea of operating system services built atop a distributed database - a database-oriented operating system meant to simplify and improve the scalability, security and resilience of large-scale distributed applications. The basic concept was to run a multi-node multi-core, transactional, highly-available distributed database, such as VoltDB, as the only application for a microkernel, and then to implement scheduling, messaging, file systems and other operating system services on top of the database. The architectural philosophy is described by this quote from the abstract of their initial preprint: All operating system state should be represented uniformly as database tables, and operations on this state should be made via queries from otherwise stateless tasks. This design makes it easy to scale and evolve the OS without whole-system refactoring, inspect and debug system state, upgrade components without downtime, manage decisions using machine learning, and implement sophisticated security features. A prototype was built with competitive performance to existing systems. ==

    Read more →
  • Find It, Fix It

    Find It, Fix It

    Find It, Fix It is a mobile app developed by the city of Seattle to report non-emergency issues. == History == The City of Seattle launched Find It, Fix It in 2013 for Android and iOS phones to let citizens report potholes, graffiti, and other problems they observe to the city. The app did not support Windows Phone, making it inaccessible to Microsoft employees in the city who used the company's then-supported mobile operating system. In 2015, Mayor Ed Murray led a Find It, Fix It walk with about 100 other people, including police officers, in the University District. Participants were encouraged to use the app to report problems they observed in the neighborhood. Later Find It, Fix It walks have taken place in neighborhoods including Crown Hill, First Hill, Belltown, Wallingford, and Highland Park. In 2020, Find It, Fix It added support for reporting issues with the dockless bicycle sharing systems in the city. Citing the success of Seattle’s app, the nearby city of Kent, Washington, announced that it would create a similar customer service app. == Usage == Users of Find It, Fix It can submit reports about graffiti, potholes, parking violations, broken street signs, and other issues. The app is designed to use a smartphone’s camera and GPS features to make it easier for users to file reports. The Atlantic reported in 2018 that Find It, Fix It was being used by neighborhood groups to report homeless encampments with the intention of having authorities remove them, citing examples of campaigns in Ravenna and Ballard. The executive director of Ballard Alliance, a local chamber of commerce for businesses in the neighborhood, used a private Facebook group to encourage business owners to use the app to report homeless encampments. In response to a poster campaign in the summer of 2019 with the slogan “See a tent? Report a tent”, a representative for the mayor’s office and two Seattle City Council members said that it was inappropriate to encourage use of Find It, Fix It to displace homeless people. As a backlash to these campaigns, people living far from Seattle filed hoax complaints using the app, such as by using photos of tents on display at REI stores. According to the Seattle Times, between January 1, 2020, and November 15, 2021, the city had received over 230,000 service requests, of which 77% were submitted via Find It, Fix It. The largest category of these, numbering over 55,000, concerned illegal dumping. Of complaints categorized as "parking", 3,000 had comments explicitly mentioning issues around homelessness. The ZIP code 98134, covering an industrial area south of Pioneer Square and north of Georgetown, had 5,559 service requests per 1,000 residents, by far the highest in the city.

    Read more →
  • International Teletraffic Congress

    International Teletraffic Congress

    The International Teletraffic Congress (ITC) is the first international conference in networking science and practice. It was created in 1955 by Arne Jensen to initially cater to the emerging need to understand and model traffic in telephone networks using stochastic methodologies, and to bring together researchers with these considerations as a common theme. Up through World War II, teletraffic research was done mainly by engineers and mathematicians working in telephone companies. Most of their work was published in local or company journals. In 1955, however, the field acquired a formal, international, institutional structure, with the organization of the first International Teletraffic Congress (ITC). Over the years, it has broaden its scope to address a wide spectrum ranging from the mathematical theory of traffic processes, stochastic system modelling and analysis, traffic and performance measurements, network management, traffic engineering to network capacity planning and cost optimization, including network economics and reliability for various types of networks. ITC served as a forum for all theoretical fundamentals and engineering practices for large-scale deployment and operation of telecommunications networks. Since its inception, ITC witnessed the evolution of communications and networking: the influence of computer science on telecommunication, the advent of the Internet and the massive deployment of mobile communications and optics, the appearance of peer-to-peer networking and social networks, the ever increasing speed and flexibility of new communication technologies, networks, user devices, and applications, and the ever changing operation challenges arising from this development. ITC documented this evolution with contemporary measurement studies, performance analyses of new technologies, recommendations for provisioning and configuration, and greatly contributed to the methodological toolbox of network scientists. Today, with its conferences, specialist seminars, regional seminars, training courses and publications, the ITC aims at a worldwide forum for all questions related to network and service performance, management, and assessment, both present and futuristic. The notion of traffic is broadly used to encompass data traffic from the MAC layer all the way to application traffic in the application layer. The scope of ITC is thus ranging all issues embedding operations, design, planning, economics and performance analysis of current and emerging communication networks and services, to be addressed by applying a variety of tools from different fields, such as Stochastic Processes, Information theory, Control theory, Signal and Processing, Game theory and optimization techniques, Statistical methodologies and Artificial Intelligence techniques. The target audience of such issues is experts from research organizations, universities, equipment vendors and suppliers, network operators, service providers, system integrators and international technical organizations, guaranteeing a well-balanced contribution from theory, application, and practice. The general goal remains to bring researchers and practitioners together toward operational understanding of all types of current and future networks. The ITC is ruled by the International Advisory Council (IAC) which gathers a number of technical experts, from universities and the research arms of key corporations in the industry, from countries having a strong tradition in teletraffic development. The IAC responsibilities are to disseminate information on teletraffic which is of interest for the whole community and: to select the locations of Plenary Congresses and to ensure their high-level technical programme to support Specialist Seminars on specific topics of current interest to promote Regional Seminars for the dissemination of teletraffic concepts in developing countries to facilitate the liaison activity with the ITU through participation in the standardization process and in the Development Programme The technical program and the organization of each ITC event remains within the responsibilities of the hosting country, but with significant IAC support to guarantee that the event is consistent with the quality standards established during the previous congresses. The ITC Plenary Congresses were scheduled tri-annually from 1955 until 1995 when the interval became bi-annual to account for the ever-accelerating development of network technologies, products and services and the associated dramatic increases in network demands. Similarly, to better cover the impact of dramatic changes undergoing in the field of computer and communication systems, networks and usage, it has been decided to hold the Plenary Congress on an annual basis from 2009. == Content == Teletraffic science is the traditional term for all theoretical fundamentals and engineering practices to describe data flows in telecommunication networks, the performance of the usage of network resources, procedures for sizing of resources and engineering the networks for given traffic load and quality of service requirements. For more than 50 years of the 20th century, traffic or teletraffic has been identified primarily with telephone networks. With the huge development of computers, stored program control of network nodes and computer communication, the traditional teletraffic science field naturally extended to computer networks, mobile and wireless/optical networks, and for a wide spectrum of new applications. The convergence between the voice network, the Internet, the television and mobility raised new questions that request new models and tools to be developed. In addition, the development of community networks, home networking, multiple access networking technologies, and the advent of pervasive and ambient communications dictates new challenges to be addressed. Today, ITC addresses the emerging paradigms such as an increasing diversity of distributed applications and services over various media like mobile/optical networks, enabling new markets and economy. ITC has steered the evolutions in communications since its creation in 1955 and remains at the forefront of innovation regarding modeling and performance. The scientific roots of communications traffic are based on the theory of probability and stochastic processes, modelling and performance evaluation. Modelling is the key for the mathematical description and quantitative performance analysis. Traffic flows are described by stochastic processes with complex dependencies which have to be validated by traffic measurements. Modelling also includes operational properties of resource control reflected by service strategies such as queueing disciplines, admission control, and routing. The results of such performance analyses are used for resource dimensioning (sizing), resource management, and network optimization while providing targeted Quality of Service. Teletraffic science is closely related to methods of operation research (queueing theory, optimization, forecasting) and computational sciences (simulation technology distributed systems). In this context, ITC represents a wide community of researchers and practitioners and is regularly organizing events like Congresses, Specialist Seminars and Workshops in order to discuss the latest changes in the modelling, design and performance of communication systems, networks and services. === The evolution of technologies of the 20th century === ITC has been witnessing the change of communication and networking technologies which are reflected in the proceedings and programs of the congresses. The specialist seminars and the motto of the congresses thereby reflect the hot topics of that time and the evolution. Selected topics of the 70's, 80's and 90's were 1998: Traffic Issues related to Multimedia and Nomadic Communications 1995: Traffic Modeling and Measurement in Broadband and Mobile Communications 1990: Broadband Technologies: Architectures, Applications, Control and Performance 1986: ISDN Traffic Issues 1984: Fundamentals of Teletraffic Theory 1977: Modeling of SPC Exchanges and Data Networks === Recent topics in the 21st century === With the rise of the Internet, new networking paradigms and technologies but also new challenges emerged: 2020: Teletraffic in the era of beyond-5G and AI 2019: Networked Systems and Services 2018: Teletraffic in the Smart World 2017: Ubiquitous, software-based, and sustainable networks and services 2016: Digital Connected World 2015: Traffic, Performance and Big Data 2014: Towards a Sustainable World 2013: Energy Efficient and Green Networking 2010: Multimedia Applications - Traffic, Performance and QoE 2009: Network Virtualization - Concepts and Performance 2008: Future Internet Design and Experimental Facilities 2008: Quality of Experience 2002: Internet Traffic Engineering and Traffic Management == Arne Jensen Lifetime Achievement Awards == The Arne Jensen Lifetime A

    Read more →
  • Filter (social media)

    Filter (social media)

    Filters are digital image effects often used on social media. They initially simulated the effects of camera filters, and they have since developed with facial recognition technology and computer-generated augmented reality. Social media filters—especially beauty filters—are often used to alter the appearance of selfies taken on smartphones or other similar devices. While filters are commonly associated with beauty enhancement and feature alterations, there is a wide range of filters that have different functions. From adjusting photo tones to using face animations and interactive elements, users have access to a range of tools. These filters allow users to enhance photos and allow room for creative expression and fun interactions with digital content. == History == Beauty filters originate from Purikura ("print club"), a type of Japanese photographic arcade game machine conceived in 1994 by Sasaki Miho, a female employee at Atlus, and released in 1995 by Atlus and Sega primarily for female visitors at Japanese arcades. They allowed the manipulation of digital selfie photos with kawaii beauty filters similar to later Snapchat filters. Purikura filters included beautifying the image, cat whiskers, bunny ears, writing text, scribbling graffiti, selecting backdrops, borders, insertable decorations, icons, hair extensions, twinkling diamond tiaras, tenderized light effects, and predesigned decorative margins. To capitalize on the Purikura phenomenon in Japan during the late 1990s, Japanese mobile phones began including a front-facing camera, starting with the Kyocera Visual Phone VP‑210 in 1999. The Sanyo SCP-5300 released in 2002 was the first camera phone with filter effects, such as illumination, white‑balance control, sepia, black and white, and negative colors. Purikura-like beauty filters later appeared in smartphone apps such as Instagram and Snapchat in the 2010s. In 2010, Apple introduced the iPhone 4—the first iPhone model with a front-facing camera. It gave rise to a dramatic increase in selfies, which could be touched up with more flattering lighting effects with applications such as Instagram. The American photographer Cole Rise was involved in the creation of the original filters for Instagram around 2010, designing several of them himself, including Sierra, Mayfair, Sutro, Amaro, and Willow. However, the technology for virtual lens filters was invented and patented by Patrick Levy-Rosenthal in 2007. The patent received 100 citations, including Facebook, Nvidia, Microsoft, Samsung, and Snap. In September, 2011, the Instagram 2.0 update for the application introduced "live filters," which allowed the user to preview the effect of the filter while shooting with the application's camera. #NoFilter, a hashtag label to describe an image that had not been filtered, became popular around 2013. An update in 2014 allowed users to adjust the intensity of the filters as well as fine-tune other aspects of the image, features that had been available for years on applications such as VSCO and Litely. In 2014, Snapchat started releasing sponsored filters to monetize the participatory use of the application. In September 2015, Snapchat acquired Looksery and released a feature called "lenses," animated filters using facial recognition technology. Some of the early lenses available on Snapchat at the time were Heart Eyes, Terminator, Puke Rainbows, Old, Scary, Rage Face, Heart Avalanche. The Coachella filter released April 2016 was a popular early augmented reality filter. In April 2017, Facebook released the Camera Effects Platform, which is the first augmented reality platform that allows developers to create their own filters and effects on Facebook's Camera. In December 2017, Snapchat also launched their Lens Studio augmented reality developer tool that allows users and advertisers to do the same on the Snapchat application. In April 2022,TikTok joined the two, and launched their own augmented reality developer platform called Effect house. In February 2023, Effect House gave opened up the access to generative AI tools that allowed creators to change facial features in real time. In November 2023, TikTok released a feature where users no longer needed Effect House to create their own filters, as they are now able to create their own effects on the TikTok application. In August 2024, Meta announced that it would be removing third-party filter effects from its family of apps by January 14, 2025. The AR development software Meta Spark AR will also be retired at the same time; it was at one point the "world's largest mobile AR platform". Brand and creator effects represent the vast majority of filters available on Meta platforms, with over 2 million third-party filters available as of 2021. == Beauty filter == A beauty filter is a filter applied to still photographs, or to video in real time, to enhance the physical attractiveness of the subject. Typical effects of such filters include smoothing skin texture and modifying the proportions of facial features, for example enlarging the eyes or narrowing the nose. Filters may be included as a built-in feature of social media apps such as Instagram or Snapchat, or implemented through standalone applications such as Facetune. In 2020, the "Perfect Skin" filter for Snapchat and Instagram which was created by Brazilian augmented reality developer Brenno Faustino gained more than 36 million impressions in the first 24 hours of its release. In 2021, TikTok users pointed out how the default front-facing camera on the platform automatically applied the retouch and other feature-altering filters. Users noted that these filters slimmed down faces, smoothed skin, whitened teeth, and altered facial features such as nose and eye size, without the option to disable this feature through settings. In March 2023, the "Bold Glamour" filter was released on TikTok and instantly went viral with over 18 million videos created within its first week. This filter subtly enhances the user's facial features seamlessly, giving the illusion of fuller eyebrows, taller cheekbones, enhanced eye make up, a smaller nose, plumper lips, and clearer skin, giving off a natural yet distinct effect. As of May 2024, the filter has been used in over 220 million videos and has become a pivotal moment for beauty filters on digital platforms. Critics have raised concerns that the widespread use of such filters on social media may lead to negative body image, particularly among girls. Though Meta's intention of removing third-party filters will likely see all beauty filters removed, academics feel that the damage of beautifying filters is already done. === Background === The manipulation of photos to enhance attractiveness has long been possible using software such as Adobe Photoshop and, before that, analogue techniques such as airbrushing. However, such tools required considerable technical and artistic skill, and so their use was mostly limited to professional contexts, such as magazines or advertisements. By contrast, filters work in an automated fashion through the use of complex algorithms, requiring little or no input from the user. This ease of use, in combination with the increase in processing power of smartphones, and the rise of social media and selfie culture, have led to photographic manipulation occurring on a much wider scale than ever before. One of the earliest examples of a content-aware digital photographic filter is red-eye reduction. === Effects === Typical changes applied by beauty filters include: Smoothing skin texture; minimizing fine lines and blemishes Erasing under-eye bags Erasing naso-labial lines ("laugh lines") Application of virtual makeup, such as lipstick or eyeshadow Slimming the face; erasing double chins Enlarging the eyes Whitening teeth Narrowing the nose Increasing fullness of the lips Beauty filters most frequently target the face, though in some cases they may affect other body parts. For example, the app "Retouch Me" was reported to have a feature which allows users to superimpose visible abdominal muscles (a "six pack") onto photos featuring the subject's bare stomach. === Reception and psychological effects === Some commentators have expressed concern that beauty filters may create unrealistic beauty standards, particularly among girls, and contribute to rates of body dysmorphic disorder. A correlation has been established between negative body image and the use of beautifying filters, though the direction of causation is unknown. The inability to discern whether a particular image has been filtered is thought to exacerbate their negative psychological effects. Policymakers have advocated for social networks to disclose the use of filters; TikTok, Instagram, and Snapchat all label filtered photos and videos with the name of the filter applied. It has also been noted that beauty filters on social media tend to highlight Eurocentric features, like lighter eyes, a smaller nose, and flushed ch

    Read more →
  • Fifth Estate

    Fifth Estate

    The Fifth Estate is a socio-cultural reference to groupings of outlier viewpoints in contemporary society, and is most associated with bloggers, journalists publishing in non-mainstream media outlets, and online social networks. The "Fifth" Estate extends the sequence of the three classical estates (clergy (first), nobility (second), commoners (third)) and the preceding Fourth Estate, essentially the common press. The use of "fifth estate" dates to the 1960s counterculture, and in particular the influential Fifth Estate, an underground newspaper first published in Detroit in 1965. Web-based technologies have enhanced the scope and power of the Fifth Estate far beyond the modest and boutique conditions of its beginnings. Nimmo and Combs asserted in 1992 that political pundits constitute a Fifth Estate. Media researcher Stephen D. Cooper argued in 2006 that bloggers are the Fifth Estate. In 2009, William Dutton argued that the Fifth Estate is not just the blogging community, nor an extension of the media, but "networked individuals" enabled by the Internet, e.g. social media, in ways that can hold the other estates accountable.

    Read more →
  • Eager learning

    Eager learning

    In artificial intelligence, eager learning is a learning method in which the system tries to construct a general, input-independent target function during training of the system, as opposed to lazy learning, where generalization beyond the training data is delayed until a query is made to the system. The main advantage gained in employing an eager learning method, such as an artificial neural network, is that the target function will be approximated globally during training, thus requiring much less space than using a lazy learning system. Eager learning systems also deal much better with noise in the training data. Eager learning is an example of offline learning, in which post-training queries to the system have no effect on the system itself, and thus the same query to the system will always produce the same result. The main disadvantage with eager learning is that it is generally unable to provide good local approximations in the target function.

    Read more →
  • Hashtag

    Hashtag

    A hashtag is a metadata tag operator that is prefaced by the hash symbol, #. On social media, hashtags are used on microblogging and photo-sharing services–especially Twitter and Tumblr–as a form of user-generated tagging that enables cross-referencing of content by topic or theme. For example, a search within Instagram for the hashtag #flowers returns all posts that have been tagged with that term. After the initial hash symbol, a hashtag may include letters, numerals or other punctuation. The use of hashtags was first proposed by American blogger and product consultant Chris Messina in a 2007 tweet. Messina made no attempt to patent the use because he felt that "they were born of the internet, and owned by no one". Hashtags became entrenched in the culture of Twitter and soon emerged across Instagram, Facebook, and YouTube. In June 2014, hashtag was added to the Oxford English Dictionary as "a word or phrase with the symbol # in front of it, used on social media websites and apps so that you can search for all messages with the same subject". == Origin and acceptance == The number sign or hash symbol, #, has long been used in information technology to highlight specific pieces of text. In 1970, the number sign was used to denote immediate address mode in the assembly language of the PDP-11 when placed next to a symbol or a number, and around 1973, '#' was introduced in the C programming language to indicate special keywords that the C preprocessor had to process first. The pound sign was adopted for use within IRC (Internet Relay Chat) networks around 1988 to label groups and topics. Channels or topics that are available across an entire IRC network are prefixed with a hash symbol # (as opposed to those local to a server, which uses an ampersand '&'). The use of the pound sign in IRC inspired Chris Messina to propose a similar system on Twitter to tag topics of interest on the microblogging network. He proposed the usage of hashtags on Twitter: How do you feel about using # (pound) for groups. As in #barcamp [msg]? According to Messina, he suggested use of the hashtag to make it easy for lay users without specialized knowledge of search protocols to find specific relevant content. Therefore, the hashtag "was created organically by Twitter users as a way to categorize messages". The first published use of the term "hash tag" was in a blog post "Hash Tags = Twitter Groupings" by Stowe Boyd, on August 26, 2007, according to lexicographer Ben Zimmer, chair of the American Dialect Society's New Words Committee. Messina's suggestion to use the hashtag was not immediately adopted by Twitter, but the convention gained popular acceptance when hashtags were used in tweets relating to the 2007 San Diego forest fires in Southern California. The hashtag gained international acceptance during the 2009–2010 Iranian election protests; Twitter users used both English- and Persian-language hashtags in communications during the events. Hashtags have since played critical roles in recent social movements such as #jesuischarlie, #BLM, and #MeToo. Beginning July 2, 2009, Twitter began to hyperlink all hashtags in tweets to Twitter search results for the hashtagged word (and for the standard spelling of commonly misspelled words). In 2010, Twitter introduced "Trending Topics" on the Twitter front page, displaying hashtags that are rapidly becoming popular, and the significance of trending hashtags has become so great that the company makes significant efforts to foil attempts to spam the trending list. During the 2010 World Cup, Twitter explicitly encouraged the use of hashtags with the temporary deployment of "hashflags", which replaced hashtags of three-letter country codes with their respective national flags. Other platforms such as YouTube and Gawker Media followed in officially supporting hashtags, and real-time search aggregators such as Google Real-Time Search began supporting hashtags. == Format == A hashtag must begin with a hash (#) character followed by other characters, and is terminated by a space or the end of the line. Some platforms may require the # to be preceded with a space. Most or all platforms that support hashtags permit the inclusion of letters (without diacritics), numerals, and underscores. Other characters may be supported on a platform-by-platform basis. Some characters, such as "&", are generally not supported as they may already serve other search functions. Hashtags are not case sensitive (a search for "#hashtag" will match "#HashTag" as well), but the use of embedded capitals (i.e., CamelCase) increases legibility and improves accessibility. Languages that do not use word dividers handle hashtags differently. In China, microblogs Sina Weibo and Tencent Weibo use a double-hashtag-delimited #HashName# format, since the lack of spacing between Chinese characters necessitates a closing tag. Twitter uses a different syntax for Chinese characters and orthographies with similar spacing conventions: the hashtag contains unspaced characters, separated from preceding and following text by spaces (e.g., '我 #爱 你' instead of '我#爱你') or by zero-width non-joiner characters before and after the hashtagged element, to retain a linguistically natural appearance (displaying as unspaced '我‌#爱‌你', but with invisible non-joiners delimiting the hashtag). === Etiquette and regulation === Some communities may limit, officially or unofficially, the number of hashtags permitted on a single post. Misuse of hashtags can lead to account suspensions. Twitter warns that adding hashtags to unrelated tweets, or repeated use of the same hashtag without adding to a conversation can filter an account from search results, or suspend the account. Individual platforms may deactivate certain hashtags either for being too generic to be useful, such as #photography on Instagram, or due to their use to facilitate illegal activities. === Alternate formats === In 2009, StockTwits began using ticker symbols preceded by the dollar sign (e.g., $XRX). In July 2012, Twitter began supporting the tag convention and dubbed it the "cashtag". The convention has extended to national currencies, and Cash App has implemented the cashtag to mark usernames. == Function == Hashtags are particularly useful in unmoderated forums that lack a formal ontological organization. Hashtags help users find content similar interest. Hashtags are neither registered nor controlled by any one user or group of users. They do not contain any set definitions, meaning that a single hashtag can be used for any number of purposes, and that the accepted meaning of a hashtag can change with time. Hashtags intended for discussion of a particular event tend to use an obscure wording to avoid being caught up with generic conversations on similar subjects, such as a cake festival using #cakefestival rather than simply #cake. However, this can also make it difficult for topics to become "trending topics" because people often use different spelling or words to refer to the same topic. For topics to trend, there must be a consensus, whether silent or stated, that the hashtag refers to that specific topic. Hashtags may be used informally to express context around a given message, with no intent to categorize the message for later searching, sharing, or other reasons. Hashtags may thus serve as a reflexive meta-commentary. This can help express contextual cues or offer more depth to the information or message that appears with the hashtag. "My arms are getting darker by the minute. #toomuchfaketan". AnoHashtags can also be used to express personal feelings and emotions. ther function of the hashtag can be used to express personal feelings and emotions. For example, with "It's Monday!! #excited #sarcasm" in which the adjectives are directly indicating the emotions of the speaker. Verbal use of the word hashtag is sometimes used in informal conversations. Use may be humorous, such as "I'm hashtag confused!" By August 2012, use of a hand gesture, sometimes called the "finger hashtag", in which the index and middle finger both hands are extended and arranged perpendicularly to form the hash, was documented. === Co-optation by other industries === Companies, businesses, and advocacy organizations have taken advantage of hashtag-based discussions for promotion of their products, services or campaigns. In the early 2010s, some television broadcasters began to employ hashtags related to programs in digital on-screen graphics, to encourage viewers to participate in a backchannel of discussion via social media prior to, during, or after the program. Television commercials have sometimes contained hashtags for similar purposes. The increased usage of hashtags as brand promotion devices has been compared to the promotion of branded "keywords" by AOL in the late 1990s and early 2000s, as such keywords were also promoted at the end of television commercials and series episodes. Organized real-world events have used hashta

    Read more →
  • Web engineering

    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

    Read more →