AI Assistant In Teams

AI Assistant In Teams — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Piranesi (software)

    Piranesi (software)

    Piranesi is an interactive paint system that enables the user to create artistic images from 3D scenes created using conventional modeling applications. == Image format == Piranesi uses the proprietary EPix file format. For every pixel, additional information is stored, such as distance from the viewer and material settings. EPix files can be rendered from 3D scenes using a fixed viewpoint by Piranesi's companion software, Vedute.

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  • List of broadband over power line deployments

    List of broadband over power line deployments

    This is a list of broadband over power line deployments. In this sense, "broadband" usually refers to Internet access using power line communication technology. == BPL pilot projects - 1st Gen (UPA) == === Inactive pilot projects === North America: United States: The United Telecom Council publishes the Federal Communications Commission (FCC)-mandated BPL Interference Resolution website, which provides a list of all BPL deployments in the US. Canada: Quebec: As of 2005, PLC communication technology developed by Ariane Controls is being installed inside and outside existing buildings to control lights and other energy-hungry devices. The cheap devices allow energy consumption to be better managed, and so save much energy and bring a clear return on investment. Western Europe: Sweden: Vattenfall is using PLC technology at 1200 baud for automatic meter reading based on an Iskraemeco product. Central and Eastern Europe, and Eurasia: Russian Federation: Electro-com has deployed widely BPL/PLC technology and offers internet access service in Moscow, Nizhny Novgorod, Ryazan, Kaluga and Rostov-on-Don, planning to extend coverage to main Russian cities. Currently the company does not provide other services, though plans to start providing telephone, and television services someday. Base equipment is a DefiDev modem with a DS2 chipset. The company had 35,000 subscribers and an annual growth of 15-20%. The company has, however, halted operations in Moscow in September, 2008, having sold its client network to an IDSL internet provider. Romania: In January, 2006, the Ministry of Communications and Information Technology introduced a PLC trial in the rural locality of Band, Mureș County, offering phone and broadband internet access for €7 per month. The technology was introduced to 50 households. Montenegro: In March, 2002, the Internet Crna Gora biggest internet provider in Montenegro launched a pilot project in town of Cetinje. Serbia: In August 2002, the Star Engineering from Niš launched a pilot project to show a completely new way to access the Internet, which is a new in that time in most countries around the world. Hungary: The first powerline service in Hungary was realized in September, 2003, in the Riverside apartment house in Budapest by 23Vnet Ltd. The PLC equipment was supplied by ASCOM Powerline. After four months the service was counting 100 users from 450 apartment owners. The bandwidth is 4.5 Mbit/s. Asia, Pacific, and Oceania: Indonesia: PT Kejora Gemilang Internusa "KEJORA", under their banner PLANET BROADBAND, is currently rolling out broadband over power line, with over 300,000 homes expected to be enabled by August 2010. PT. Kejora Gemilang Internusa signed an 8-year Joint Venture concession agreement with ICON+ a division of PT. Perusahaan Listrik Negara (Indonesia electricity company). Under the terms of the agreement PLAnet Broadband are to supply BPL/PLC to Jakarta West and West Java. Another company, PT. Broadband Powerline Indonesia, has been developing broadband over power line in apartment buildings since 2006. PT. BPI also produces data couplers to make broadband over powerline possible in three phases (R, S, T) with a single master. India : In India IIIT Allahabad has completed a project in co-operation with Corinex Communications Canada to implement a prototype of BPL for University campus and nearby villages. Africa and the Middle East: Egypt: The Engineering Office for Integrated Projects (EOIP) has deployed PLC technology widely in Alexandria, Fayed, and Tanta. Based on a locally developed system, the company provides AMR for electricity utilities. Currently, the company has about 70,000 subscribers. South Africa: Goal Technology Solutions (GTS) trialled the technology and is offering service in the suburbs of Pretoria, and plans to extend it to other areas. The tests were done with Mitsubishi equipment using a DS2 chipset, and the company claims a maximum throughput of 90 Mbit/s although initially only "512 Kbits/s ADSL equivalent speeds" are available. Now it uses DefiDev's equipment, and according to GTS's website, it will expand available bandwidth up to 5-20 Mbit/s. Ghana: Cactel Communications, Ltd. successfully deployed an MV solution pilot project in the Graphic Communications Group in Accra in June, 2005. A Cactel Remote Energy Management System (REMS) pilot project for the Electricity Company of Ghana (ECG) is running a 40-user pilot project at the University of Ghana in Legon. The current project combines fiber, radio link, Wi-Fi and PLC to provide broadband internet access and telephony. It showcases the interoperability of PLC technology and the company's expertise in emerging market design and deployment. Cactel hopes to deploy nationally, and is in deliberations with the national stakeholders and with Ghana's Ministry of Communications (MoC). AllTerra Communications successfully implemented a pilot test of broadband over power lines in Akosombo. In partnership with VRA, this test involves demonstrating transmission of broadband from medium to low voltage signals. AllTerra is working with VRA to expand the pilot project to include essential grid management utilities that will help balance and manage the current electricity transmission throughout their various substations. Using IT as a catalyst for economic development, AllTerra is expanding into numerous areas throughout Ghana. Vobiss Solutions Ltd successfully implemented a Hybrid Fibre BPL pilot network within EMEFS Hillview Estate in collaboration with ECG. Saudi Arabia: ElectroNet has been working with the Saudi Electric Company since 2005 on a pilot project using broadband over power lines over medium voltage cables and linking into low voltage distribution within a shopping mall. The pilot project also integrates automatic meter readers. Powerlines Communications Co. Ltd. implemented an AMR pilot project for Saudi Electricity Company in 2006. The project was located in the city of Jeddah on the west coast of Saudi Arabia. Digital KWh meters were installed in parallel with analog KWh meters. Readings taken by the Saudi Electricity Company showed variations of less than 1%. A BPL pilot project was included. Saudi Arabian Computer Management Consultants (SACMAC) has signed a deal to become an official system integrator and distributor for Mitsubishi PLC. It is expected to become a great success, because the existing broadband service, monopolized by the Saudi Telecom Company, is expensive and has poor customer service (some clients report that company techs arrive months after ordering). SACMAC has declined to talk about specifics of availability and price but says it will start rolling out the service in a few months (as of May 2006) and its price will be lower than current broadband providers. === Concluded pilot projects === The following pilot projects have ended: Australia, Tasmania: In November 2007, electricity retailer Aurora Energy ended its involvement with BPL and announced it was switching to Optical Fiber. This ended their commercial trial begun in September 2005, offering BPL services to 500 homes in the suburb of Tolmans Hill near Hobart, which had followed a successful technological trial earlier that year. Portugal ended BPL/PLC deployments in the country in October 2006, reportedly for economic reasons., Russian Federation: In September 2008, Russia's only BPL provider Electro-com ended deployments in Moscow for economic reasons. Spain: In May 2007 Iberdrola and Endesa (the main power companies in Spain) ended their projects to deploy PLC. United States: As of July 2010, the City of Manassas, VA has shut down their BPL deployment, which was the largest in the country. As of April 2007, Motorola has shuttered its Powerline LV Access BPL and reportedly plans to re-purpose the technology to a new system called Powerline MU, which is for use within multiple-unit dwellings. Motorola's system uses only residential-side low-voltage power lines for transmission to reduce the antenna effect, and successfully demonstrated frequency-notching for reduced potential for interference over the Amperion Inc. and Current Technologies LLC systems. Motorola invited the American Radio Relay League to participate with these tests, and even installed the Motorola system at their headquarters. Preliminary results were very positive with regard to interference, because the Motorola system does not use BPL on the powerlines leading up to the neighborhood. The BPL carrier is only used for the last leg of the trip from the pole to the house, and gets the signal to the pole via radio. This limits the interference to the area surrounding the last leg to the house. === Dismantled pilot projects === The following other BPL trials in the US are dismantled as of May 2008:

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  • Social media use in hiring

    Social media use in hiring

    Social media use in hiring refers to the examination by employers of job applicants' (public) social media profiles as part of the hiring assessment. For example, the vast majority of Fortune 500 companies use social media as a tool to screen prospective employees and as a tool for talent acquisition. This practice raises ethical questions. Employers and recruiters note that they have access only to information that applicants choose to make public. Many Western-European countries restrict employer's use of social media in the workplace. States including Arkansas, California, Colorado, Illinois, Maryland, Michigan, Nevada, New Jersey, New Mexico, Utah, Washington, and Wisconsin protect applicants and employees from surrendering usernames and passwords for social media accounts. Use of social media has caused significant problems for some applicants who are active on social media. A 2013 survey of 17,000 young people in six countries found that one in ten people aged 16 to 34 claimed to have been rejected for a job because of social media activity. Social media services have been reported to affect deception in resumes. While these services do not affect deception frequency, it does increase deception about interests and hobbies. == Ethical implications == This issue raises many ethical questions that some consider an employer's right and others consider discrimination. As of 2016, except in the states of California, Maryland, and Illinois, there are no laws that prohibit employers from using social media profiles as a basis of whether or not someone should be hired. Title VII also prohibits discrimination during any aspect of employment including hiring or firing, recruitment, or testing. Social media has been integrating into the workplace, and this has led to conflicts within employees and employers.[107] Particularly, Facebook has been seen as a popular platform for employers to investigate in order to learn more about potential employees. This conflict first started in Maryland when an employer requested and received an employee's Facebook username and password. State lawmakers first introduced legislation in 2012 to prohibit employers from requesting passwords to personal social accounts in order to get a job or to keep a job. This led to Canada, Germany, the U.S. Congress and 11 U.S. states to pass or propose legislation that prevents employers' access to private social accounts of employees.[108] Many Western European countries have already implemented laws that restrict the regulation of social media in the workplace. States including Arkansas, California, Colorado, Illinois, Maryland, Michigan, Nevada, New Jersey, New Mexico, Utah, Washington, and Wisconsin have passed legislation that protects potential employees and current employees from employers that demand them to give forth their username or password for a social media account. Laws that forbid employers from disciplining an employee based on activity off the job on social media sites have also been put into act in states including California, Colorado, Connecticut, North Dakota, and New York. Several states have similar laws that protect students in colleges and universities from having to grant access to their social media accounts. Eight states have passed the law that prohibits post secondary institutions from demanding social media login information from any prospective or current students and privacy legislation has been introduced or is pending in at least 36 states as of July 2013. As of May 2014, legislation has been introduced and is in the process of pending in at least 28 states and has been enacted in Maine and Wisconsin. In addition, the National Labor Relations Board has been devoting a lot of their attention to attacking employer policies regarding social media that can discipline employees who seek to speak and post freely on social media sites. Use of social media by young people has caused significant problems for some applicants who are active on social media when they try to enter the job market. A survey of 17,000 young people in six countries in 2013 found that 1 in 10 people aged 16 to 34 have been rejected for a job because of online comments they made on social media websites. A 2014 survey of recruiters found that 93% of them check candidates' social media postings. Moreover, professor Stijn Baert of Ghent University conducted a field experiment in which fictitious job candidates applied for real job vacancies in Belgium. They were identical except in one respect: their Facebook profile photos. It was found that candidates with the most wholesome photos were a lot more likely to receive invitations for job interviews than those with the more controversial photos. In addition, Facebook profile photos had a greater impact on hiring decisions when candidates were highly educated. These cases have created some privacy implications as to whether or not companies should have the right to look at employee's Facebook profiles. In March 2012, Facebook decided they might take legal action against employers for gaining access to employee's profiles through their passwords. According to Facebook Chief Privacy Officer for policy, Erin Egan, the company has worked hard to give its users the tools to control who sees their information. He also said users shouldn't be forced to share private information and communications just to get a job. According to the network's Statement of Rights and Responsibilities, sharing or soliciting a password is a violation of Facebook policy. Employees may still give their password information out to get a job, but according to Erin Egan, Facebook will continue to do their part to protect the privacy and security of their users. == Impacts == Use of social media by young people has caused significant problems for some applicants who are active on social media when they try to enter the job market. A survey of 17,000 young people in six countries in 2013 found that 1 in 10 people aged 16 to 34 have been rejected for a job because of online comments they made on social media websites. A 2014 survey of recruiters found that 93% of them check candidates' social media postings. Moreover, in 2015 professor Stijn Baert of Ghent University conducted a field experiment in which fictitious job candidates applied for real job vacancies in Belgium. They were identical except in one respect: their Facebook profile photos. It was found that candidates with the most wholesome photos were a lot more likely to receive invitations for job interviews than those with the more controversial photos. In addition, Facebook profile photos had a greater impact on hiring decisions when candidates were highly educated. These cases have created some privacy implications as to whether or not companies should have the right to look at employee's Facebook profiles. In March 2012, Facebook decided they might take legal action against employers for gaining access to employee's profiles through their passwords. According to Facebook Chief Privacy Officer for policy, Erin Egan, the company has worked hard to give its users the tools to control who sees their information. He also said users shouldn't be forced to share private information and communications just to get a job. According to the network's Statement of Rights and Responsibilities, sharing or soliciting a password is a violation of Facebook policy. Employees may still give their password information out to get a job, but according to Erin Egan, Facebook will continue to do their part to protect the privacy and security of their users. == Policy Responses == 26 US states now have laws against an employer requiring a current or potential employee to give the employer their username and password.

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  • Social media use in hiring

    Social media use in hiring

    Social media use in hiring refers to the examination by employers of job applicants' (public) social media profiles as part of the hiring assessment. For example, the vast majority of Fortune 500 companies use social media as a tool to screen prospective employees and as a tool for talent acquisition. This practice raises ethical questions. Employers and recruiters note that they have access only to information that applicants choose to make public. Many Western-European countries restrict employer's use of social media in the workplace. States including Arkansas, California, Colorado, Illinois, Maryland, Michigan, Nevada, New Jersey, New Mexico, Utah, Washington, and Wisconsin protect applicants and employees from surrendering usernames and passwords for social media accounts. Use of social media has caused significant problems for some applicants who are active on social media. A 2013 survey of 17,000 young people in six countries found that one in ten people aged 16 to 34 claimed to have been rejected for a job because of social media activity. Social media services have been reported to affect deception in resumes. While these services do not affect deception frequency, it does increase deception about interests and hobbies. == Ethical implications == This issue raises many ethical questions that some consider an employer's right and others consider discrimination. As of 2016, except in the states of California, Maryland, and Illinois, there are no laws that prohibit employers from using social media profiles as a basis of whether or not someone should be hired. Title VII also prohibits discrimination during any aspect of employment including hiring or firing, recruitment, or testing. Social media has been integrating into the workplace, and this has led to conflicts within employees and employers.[107] Particularly, Facebook has been seen as a popular platform for employers to investigate in order to learn more about potential employees. This conflict first started in Maryland when an employer requested and received an employee's Facebook username and password. State lawmakers first introduced legislation in 2012 to prohibit employers from requesting passwords to personal social accounts in order to get a job or to keep a job. This led to Canada, Germany, the U.S. Congress and 11 U.S. states to pass or propose legislation that prevents employers' access to private social accounts of employees.[108] Many Western European countries have already implemented laws that restrict the regulation of social media in the workplace. States including Arkansas, California, Colorado, Illinois, Maryland, Michigan, Nevada, New Jersey, New Mexico, Utah, Washington, and Wisconsin have passed legislation that protects potential employees and current employees from employers that demand them to give forth their username or password for a social media account. Laws that forbid employers from disciplining an employee based on activity off the job on social media sites have also been put into act in states including California, Colorado, Connecticut, North Dakota, and New York. Several states have similar laws that protect students in colleges and universities from having to grant access to their social media accounts. Eight states have passed the law that prohibits post secondary institutions from demanding social media login information from any prospective or current students and privacy legislation has been introduced or is pending in at least 36 states as of July 2013. As of May 2014, legislation has been introduced and is in the process of pending in at least 28 states and has been enacted in Maine and Wisconsin. In addition, the National Labor Relations Board has been devoting a lot of their attention to attacking employer policies regarding social media that can discipline employees who seek to speak and post freely on social media sites. Use of social media by young people has caused significant problems for some applicants who are active on social media when they try to enter the job market. A survey of 17,000 young people in six countries in 2013 found that 1 in 10 people aged 16 to 34 have been rejected for a job because of online comments they made on social media websites. A 2014 survey of recruiters found that 93% of them check candidates' social media postings. Moreover, professor Stijn Baert of Ghent University conducted a field experiment in which fictitious job candidates applied for real job vacancies in Belgium. They were identical except in one respect: their Facebook profile photos. It was found that candidates with the most wholesome photos were a lot more likely to receive invitations for job interviews than those with the more controversial photos. In addition, Facebook profile photos had a greater impact on hiring decisions when candidates were highly educated. These cases have created some privacy implications as to whether or not companies should have the right to look at employee's Facebook profiles. In March 2012, Facebook decided they might take legal action against employers for gaining access to employee's profiles through their passwords. According to Facebook Chief Privacy Officer for policy, Erin Egan, the company has worked hard to give its users the tools to control who sees their information. He also said users shouldn't be forced to share private information and communications just to get a job. According to the network's Statement of Rights and Responsibilities, sharing or soliciting a password is a violation of Facebook policy. Employees may still give their password information out to get a job, but according to Erin Egan, Facebook will continue to do their part to protect the privacy and security of their users. == Impacts == Use of social media by young people has caused significant problems for some applicants who are active on social media when they try to enter the job market. A survey of 17,000 young people in six countries in 2013 found that 1 in 10 people aged 16 to 34 have been rejected for a job because of online comments they made on social media websites. A 2014 survey of recruiters found that 93% of them check candidates' social media postings. Moreover, in 2015 professor Stijn Baert of Ghent University conducted a field experiment in which fictitious job candidates applied for real job vacancies in Belgium. They were identical except in one respect: their Facebook profile photos. It was found that candidates with the most wholesome photos were a lot more likely to receive invitations for job interviews than those with the more controversial photos. In addition, Facebook profile photos had a greater impact on hiring decisions when candidates were highly educated. These cases have created some privacy implications as to whether or not companies should have the right to look at employee's Facebook profiles. In March 2012, Facebook decided they might take legal action against employers for gaining access to employee's profiles through their passwords. According to Facebook Chief Privacy Officer for policy, Erin Egan, the company has worked hard to give its users the tools to control who sees their information. He also said users shouldn't be forced to share private information and communications just to get a job. According to the network's Statement of Rights and Responsibilities, sharing or soliciting a password is a violation of Facebook policy. Employees may still give their password information out to get a job, but according to Erin Egan, Facebook will continue to do their part to protect the privacy and security of their users. == Policy Responses == 26 US states now have laws against an employer requiring a current or potential employee to give the employer their username and password.

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  • Information extraction

    Information extraction

    Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents and other electronically represented sources. Typically, this involves processing human language texts by means of natural language processing (NLP). Recent activities in multimedia document processing like automatic annotation and content extraction out of images/audio/video/documents could be seen as information extraction. Recent advances in NLP techniques have allowed for significantly improved performance compared to previous years. An example is the extraction from newswire reports of corporate mergers, such as denoted by the formal relation: MergerBetween ⁡ ( c o m p a n y 1 , c o m p a n y 2 , d a t e ) {\displaystyle \operatorname {MergerBetween} (\mathrm {company} _{1},\mathrm {company} _{2},\mathrm {date} )} , from an online news sentence such as: "Yesterday, New York based Foo Inc. announced their acquisition of Bar Corp." A broad goal of IE is to allow computation to be done on the previously unstructured data. A more specific goal is to allow automated reasoning about the logical form of the input data. Structured data is semantically well-defined data from a chosen target domain, interpreted with respect to category and context. Information extraction is the part of a greater puzzle which deals with the problem of devising automatic methods for text management, beyond its transmission, storage and display. The discipline of information retrieval (IR) has developed automatic methods, typically of a statistical flavor, for indexing large document collections and classifying documents. Another complementary approach is that of natural language processing (NLP) which has solved the problem of modelling human language processing with considerable success when taking into account the magnitude of the task. In terms of both difficulty and emphasis, IE deals with tasks in between both IR and NLP. In terms of input, IE assumes the existence of a set of documents in which each document follows a template, i.e. describes one or more entities or events in a manner that is similar to those in other documents but differing in the details. An example, consider a group of newswire articles on Latin American terrorism with each article presumed to be based upon one or more terroristic acts. We also define for any given IE task a template, which is a(or a set of) case frame(s) to hold the information contained in a single document. For the terrorism example, a template would have slots corresponding to the perpetrator, victim, and weapon of the terroristic act, and the date on which the event happened. An IE system for this problem is required to "understand" an attack article only enough to find data corresponding to the slots in this template. == History == Information extraction dates back to the late 1970s in the early days of NLP. An early commercial system from the mid-1980s was JASPER built for Reuters by the Carnegie Group Inc with the aim of providing real-time financial news to financial traders. Beginning in 1987, IE was spurred by a series of Message Understanding Conferences. MUC is a competition-based conference that focused on the following domains: MUC-1 (1987), MUC-3 (1989): Naval operations messages. MUC-3 (1991), MUC-4 (1992): Terrorism in Latin American countries. MUC-5 (1993): Joint ventures and microelectronics domain. MUC-6 (1995): News articles on management changes. MUC-7 (1998): Satellite launch reports. Considerable support came from the U.S. Defense Advanced Research Projects Agency (DARPA), who wished to automate mundane tasks performed by government analysts, such as scanning newspapers for possible links to terrorism. == Present significance == The present significance of IE pertains to the growing amount of information available in unstructured form. Tim Berners-Lee, inventor of the World Wide Web, refers to the existing Internet as the web of documents and advocates that more of the content be made available as a web of data. Until this transpires, the web largely consists of unstructured documents lacking semantic metadata. Knowledge contained within these documents can be made more accessible for machine processing by means of transformation into relational form, or by marking-up with XML tags. An intelligent agent monitoring a news data feed requires IE to transform unstructured data into something that can be reasoned with. A typical application of IE is to scan a set of documents written in a natural language and populate a database with the information extracted. == Tasks and subtasks == Applying information extraction to text is linked to the problem of text simplification in order to create a structured view of the information present in free text. The overall goal being to create a more easily machine-readable text to process the sentences. Typical IE tasks and subtasks include: Template filling: Extracting a fixed set of fields from a document, e.g. extract perpetrators, victims, time, etc. from a newspaper article about a terrorist attack. Event extraction: Given an input document, output zero or more event templates. For instance, a newspaper article might describe multiple terrorist attacks. Knowledge Base Population: Fill a database of facts given a set of documents. Typically the database is in the form of triplets, (entity 1, relation, entity 2), e.g. (Barack Obama, Spouse, Michelle Obama) Named entity recognition: recognition of known entity names (for people and organizations), place names, temporal expressions, and certain types of numerical expressions, by employing existing knowledge of the domain or information extracted from other sentences. Typically the recognition task involves assigning a unique identifier to the extracted entity. A simpler task is named entity detection, which aims at detecting entities without having any existing knowledge about the entity instances. For example, in processing the sentence "M. Smith likes fishing", named entity detection would denote detecting that the phrase "M. Smith" does refer to a person, but without necessarily having (or using) any knowledge about a certain M. Smith who is (or, "might be") the specific person whom that sentence is talking about. Coreference resolution: detection of coreference and anaphoric links between text entities. In IE tasks, this is typically restricted to finding links between previously extracted named entities. For example, "International Business Machines" and "IBM" refer to the same real-world entity. If we take the two sentences "M. Smith likes fishing. But he doesn't like biking", it would be beneficial to detect that "he" is referring to the previously detected person "M. Smith". Relationship extraction: identification of relations between entities, such as: PERSON works for ORGANIZATION (extracted from the sentence "Bill works for IBM.") PERSON located in LOCATION (extracted from the sentence "Bill is in France.") Semi-structured information extraction which may refer to any IE that tries to restore some kind of information structure that has been lost through publication, such as: Table extraction: finding and extracting tables from documents. Table information extraction : extracting information in structured manner from the tables. This task is more complex than table extraction, as table extraction is only the first step, while understanding the roles of the cells, rows, columns, linking the information inside the table and understanding the information presented in the table are additional tasks necessary for table information extraction. Comments extraction : extracting comments from the actual content of articles in order to restore the link between authors of each of the sentences Language and vocabulary analysis Terminology extraction: finding the relevant terms for a given corpus Audio extraction Template-based music extraction: finding relevant characteristic in an audio signal taken from a given repertoire; for instance time indexes of occurrences of percussive sounds can be extracted in order to represent the essential rhythmic component of a music piece. Note that this list is not exhaustive and that the exact meaning of IE activities is not commonly accepted and that many approaches combine multiple sub-tasks of IE in order to achieve a wider goal. Machine learning, statistical analysis and/or natural language processing are often used in IE. IE on non-text documents is becoming an increasingly interesting topic in research, and information extracted from multimedia documents can now be expressed in a high level structure as it is done on text. This naturally leads to the fusion of extracted information from multiple kinds of documents and sources. == World Wide Web applications == IE has been the focus of the MUC conferences. The proliferation of the Web, however, intensified the need for developing IE systems that help people

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  • Private message

    Private message

    In computer networking, a private message (PM), or direct message (DM), refers to a private communication, often text-based, sent or received by a user of a private communication channel on any given platform. Unlike public posts, PMs are only viewable by the participants. Long a function present on IRCs and Internet forums, private channels for PMs have also been prevalent features on instant messaging (IM) and on social media networks. It may be either synchronous (e.g. on an IM) or asynchronous (e.g. on an Internet forum). The term private message (PM) originated as a feature on internet forums, while the term direct message (DM) originated as a feature on Twitter. Due to the popularity of the latter service, DM has since been appropriated by other platforms, such as Instagram, and is often genericized in popular usage. == Overview == There are two main types of private messages, and one obscure type: One type includes those found on IRCs and Internet forums, as well as on social media services like Twitter, Facebook, and Instagram, where the focus is public posting, PMs allow users to communicate privately without leaving the platform. The second type are those relayed through instant messaging platforms such as WhatsApp and Snapchat, where users join the networks primarily to exchange PMs. A third type, peer-to-peer messaging, occurs when users create and own the infrastructure used to transmit and store the messages; while features vary depending on application, they give the user full control over the data they transmit. An example of software that enables this kind of messaging is Classified-ads. Besides serving as a tool to connect privately with friends and family, PMs have gained momentum in the workplace. Working professionals use PMs to reach coworkers in other spaces and increase efficiency during meetings. Although useful, using PMs in the workplace may blur the boundary between work and private lives. Some common forms of private messaging today include Facebook messaging (sometimes referred to as "inboxing"), Twitter direct messaging, and Instagram direct messaging. These forms of private messaging provide a private space on a usually public site. For instance, most activity on Twitter is public, but Twitter DMs provide a private space for communication between two users. This differs from mediums like email, texting, and Snapchat, where most or all activity is always private. Modern forms of private messaging may include multimedia messages, such as pictures or videos. == History == Email was first developed to send messages between different computers on ARPANET in 1971. Access to ARPANET was primarily limited to universities and other research institutions. Starting in 1983 or 1984, FidoNet allowed home computer users to send and receive email via bulletin board systems. Information services such as CompuServe, America Online, and Prodigy also helped to popularizes online messaging. The advent of the public World Wide Web in 1993 increased access to email via internet service providers, and later via webmail. Instant messaging systems became popular in the mid 1990s, as Internet access improved and personal computers became more common. The introduction of Skype in 2003 popularized Internet-based voice and video messaging. Direct messaging is now a feature of all major social networking services. == Privacy concerns == In January 2014, Matthew Campbell and Michael Hurley filed a class-action lawsuit against Facebook for breaching the Electronic Communications Privacy Act. They alleged that private messages which contained URLs were being read and used to generate profit, through data mining and user profiling, and that it was misleading for Facebook to refer to the functionality as "private" with the implication that the communication was "free from surveillance". In 2012, some Facebook users misinterpreted a redesign of the Facebook wall as publicly sharing private messages from 2008–2009. These were found to be public wall posts from those years, made at a time when it was not possible to like or comment on a wall post, making the notes look like private messages.

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  • IWARP

    IWARP

    iWARP is a computer networking protocol that implements remote direct memory access (RDMA) for efficient data transfer over Internet Protocol networks. Contrary to some accounts, iWARP is not an acronym. Because iWARP is layered on Internet Engineering Task Force (IETF)-standard congestion-aware protocols such as Transmission Control Protocol (TCP) and Stream Control Transmission Protocol (SCTP), it makes few requirements on the network, and can be successfully deployed in a broad range of environments. == History == In 2007, the IETF published five Request for Comments (RFCs) that define iWARP: RFC 5040 A Remote Direct Memory Access Protocol Specification is layered over Direct Data Placement Protocol (DDP). It defines how RDMA Send, Read, and Write operations are encoded using DDP into headers on the network. RFC 5041 Direct Data Placement over Reliable Transports is layered over MPA/TCP or SCTP. It defines how received data can be directly placed into an upper layer protocols receive buffer without intermediate buffers. RFC 5042 Direct Data Placement Protocol (DDP) / Remote Direct Memory Access Protocol (RDMAP) Security analyzes security issues related to iWARP DDP and RDMAP protocol layers. RFC 5043 Stream Control Transmission Protocol (SCTP) Direct Data Placement (DDP) Adaptation defines an adaptation layer that enables DDP over SCTP. RFC 5044 Marker PDU Aligned Framing for TCP Specification defines an adaptation layer that enables preservation of DDP-level protocol record boundaries layered over the TCP reliable connected byte stream. These RFCs are based on the RDMA Consortium's specifications for RDMA over TCP. The RDMA Consortium's specifications are influenced by earlier RDMA standards, including Virtual Interface Architecture (VIA) and InfiniBand (IB). Since 2007, the IETF has published three additional RFCs that maintain and extend iWARP: RFC 6580 IANA Registries for the Remote Direct Data Placement (RDDP) Protocols published in 2012 defines IANA registries for Remote Direct Data Placement (RDDP) error codes, operation codes, and function codes. RFC 6581 Enhanced Remote Direct Memory Access (RDMA) Connection Establishment published in 2011 fixes shortcomings with iWARP connection setup. RFC 7306 Remote Direct Memory Access (RDMA) Protocol Extensions published in 2014 extends RFC 5040 with atomic operations and RDMA Write with Immediate Data. == Protocol == The main component in the iWARP protocol is the Direct Data Placement Protocol (DDP), which permits the actual zero-copy transmission. DDP itself does not perform the transmission; the underlying protocol (TCP or SCTP) does. However, TCP does not respect message boundaries; it sends data as a sequence of bytes without regard to protocol data units (PDU). In this regard, DDP itself may be better suited for SCTP, and indeed the IETF proposed a standard RDMA over SCTP. To run DDP over TCP requires a tweak known as marker PDU aligned (MPA) framing to guarantee boundaries of messages. Furthermore, DDP is not intended to be accessed directly. Instead, a separate RDMA protocol (RDMAP) provides the services to read and write data. Therefore, the entire RDMA over TCP specification is really RDMAP over DDP over either MPA/TCP or SCTP. All of these protocols can be implemented in hardware. Unlike IB, iWARP only has reliable connected communication, as this is the only service that TCP and SCTP provide. The iWARP specification omits other features of IB, such as Send with Immediate Data operations. With RFC 7306, the IETF is working to reduce these omissions. == Implementation == Because a kernel implementation of the TCP stack can be seen as a bottleneck, the protocol is typically implemented in hardware RDMA network interface controllers (rNICs). As simple data losses are rare in tightly coupled network environments, the error-correction mechanisms of TCP may be performed by software while the more frequently performed communications are handled strictly by logic embedded on the rNIC. Similarly, connections are often established entirely by software and then handed off to the hardware. Furthermore, the handling of iWARP specific protocol details is typically isolated from the TCP implementation, allowing rNICs to be used for both as RDMA offload and TCP offload (in support of traditional sockets based TCP/IP applications). The portion of the hardware implementation used for implementing the TCP protocol is known as the TCP Offload Engine (TOE). TOE itself does not prevent copying on the reception side, and must be combined with RDMA hardware for zero-copy results. The RDMA / TCP specification is a set of different wire protocols intended to be implemented in hardware (though it seems feasible to emulate it in software for compatibility but without the performance benefits). == Interfaces == iWARP is a protocol, not an implementation, but defines protocol behavior in terms of the operations that are legal for the protocol, known as Verbs. As such, iWARP does not have any single standard programming interface. However, programming interfaces tend to very closely correspond to the Verbs. Several programmatic interfaces have been proposed, including OpenFabrics Verbs, Network Direct, uDAPL, kDAPL, IT-API, and RNICPI. Implementations of some of these interfaces are available for different platforms, including Windows and Linux. == Services available == Networking services implemented over iWARP include those offered in the OpenFabrics Enterprise Distribution (OFED) by the OpenFabrics Alliance for Linux operating systems, and by Microsoft Windows via Network Direct. NVMe over Fabrics (NVMEoF) iSCSI Extensions for RDMA (iSER) Server Message Block Direct (SMB Direct) Sockets Direct Protocol (SDP) SCSI RDMA Protocol (SRP) Network File System over RDMA (NFS over RDMA) GPUDirect

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  • Social media coverage of the Olympics

    Social media coverage of the Olympics

    Over the years, television broadcast rights have distinguished what Olympic-related content can be accessed by fans online. By doing so, mobile-friendly social platforms began to integrate into the Olympics. Athletes and fans use these platforms to share live updates, special moments, and behind-the-scenes specials. Various social media platforms have been used for Olympic content, including Twitter and Facebook. Some marketers credit social media for prompting the official U.S. broadcasters, NBC, to live stream events, including early rounds. == Background == The Olympics is able to advertise to its viewers and its host country with the use of data it collects through Social media marketing. Prominent social media platforms include: Twitter, Facebook, Instagram, Tumblr, YouTube, Google, MSN, Yahoo and many more. Campaign Initiatives and Artificial Intelligence technologies have been used to analyze the social media content of users. Information from consumers such as their preferences, demographics, age and locality are all analyzed to gain consumer insight. Campaign initiatives and AI technologies were used for such purposes in the 2010 Vancouver Winter Olympics and are in use currently. Social media marketing of the Olympics is a new phenomena, beginning prior to the 2008 Beijing Olympics == Variations == There are two classifications of social media marketing recognized by the IOC: Officially sanctioned content from rights holders and sponsors that maximizes the use of Olympic content (imagery, hashtag) Unofficial content that is generated by brands that leverage the excitement of the Olympics == 2008 Beijing Summer Olympics == Social media marketing emerged as a phenomenon during the 2008 Beijing Olympics, which progressed as a marketing and an advertising tactic ever since. The Beijing Olympics became the test subject for social media marketing initiatives started by advertising agencies. In 2008, social media marketing began the transition from one-sided communication to mass communication of the Olympic Games. Although social media marketing of the Olympic Games began in 2008, the audience to the Olympics was still primarily reached through television–reaching an audience of 4.3 billion viewers. At the time, the viewers of the Olympic Games through Internet website platforms made up an audience of approximately 390 million individuals. What was the beginning of Olympic social media marketing, was also the beginning of a more globalized experience of the Olympic Games via social media. Twitter, now a prominent social media platform, began in 2006 and grew to three million active users by the beginning of the 2008 Beijing Olympics. Members of Facebook, another prominent social media platform, tracking the Olympic Games grew from approximately one million during the Olympic Games of Athens 2004 to 90 million during the 2008 Beijing Olympics. Social media use, in general, increased by 24 percent between 2007 and 2008–from 63 percent of U.S. adults to 87 percent of U.S. adults. == 2010 Vancouver Winter Olympics == The International Olympic Committee (IOC) deemed The Vancouver Winter Olympics as "the first social media games” based on its fan base through social media platforms. The IOC launched their Facebook page a month before the games began, attracting 1.5 million fans. Shifting to online viewing attracted a younger audience than past Olympic games with over 60 percent of Facebook fans being under 24 years of age. Athletes like Lindsey Vonn and Shaun White reached fans on social media as the platform posted behind-the-scenes coverage on their experiences. The IOC used social media to create competitions between athletes and fans streamed online. Its YouTube channel hosted a “Best of Us” challenge in which the public could compete in games with their favorite athletes, acquiring three million viewers. Photos spread across social media platforms, such as Flickr, which had 11,000 photos posted by 600 photographers, bringing a new perspective to the games. Twitter contributed constant live updates of the competitions. The IOC's Twitter following doubled to 12,000 followers during the Vancouver Olympics, creating a larger viewer population for the games. The IOC created social media guidelines as more athletes and fans got online to interact with the Olympics. Social media was still relatively new as a marketing platform, so these guidelines confused many individuals. == 2012 London Summer Olympics == The London 2012 Olympic Games succeeded in broadcasting, participation and marketing. For the first time, the IOC broadcast the Olympic Games live and on-demand through YouTube, allowing fans to access the Games anytime, anywhere through live streaming. The combination of conventional broadcasting and mobile platforms reached a global audience of 4.8 billion people. Social media soared with Facebook, Twitter and Google+, attracting 4.7 million followers. Athletes shared photographs, interacted online with fans and updated daily, either in person or via an agent. Instagram was established by 2012, making itself a premier photo-sharing platform perfect for athletes to capture their emotions. Lewis Wiltshire, head of sport for Twitter UK said, "Never before have fans had such direct access to their sporting heroes." Social media created conversation on fan opinions regarding athletes, including 962,756 total mentions of Usain Bolt, “Fastest Man in History,” who defended the 100 meter and 200 meter gold medals. Michael Phelps followed with 828,081 total mentions. Olympic sponsors were active on social media; created several campaigns to promote their brands; and inspired viewers with mass participation and personalized events. The Adidas “Take the Stage” Campaign recognized talent around the world, installing a photo booth and inviting the 550 Olympics athletes to take the stage. (IOC Marketing Report 2012). David Beckham surprised fans at the photo booth in Westfield shopping centre, gaining popularity in UK media. Coca-Cola, Acer Inc., McDonald's, Visa Inc. and several others used similar tactics of participation to attract viewers. == 2014 Sochi Winter Olympics == === Channels === The 2014 Winter Olympic Games were held in Sochi, a city in Krasnodar Krai, Russia, establishing the first “social media Olympics” for Russia. The most popular Russian social media and networking service, VK, created an Olympic page, similar to Facebook's. The Olympic VK page has 2.8 million fans and—the most popular official community on the platform. Throughout the games, VK had 54 million Olympic mentions, an average of 1.5 million per day. Numbers grew on other social media pages: more than 2 million fans joined the Olympic Facebook page, 168,101 followed the Olympic Twitter, 150,000 followed the Olympic Instagram and three million visited the Olympic website in February 2014. There were 90,000 total updates on social media by Sochi 2014 Olympians and teams. The United States was the most active country during the games logging 22,598 posts across Facebook, Twitter, and Instagram. === Engagement === With social media there is also hashtags. The most popular hashtag was #sochi2014 with almost 11,000 uses. The next top five hashtags were #wearewinter, #teamusa, #olympics, #goaus and #wirfuerD. Another popular hashtag was #Sochiproblems, depicting local struggles. Photos of the poor state of Sochi on all platforms made the games the number one trending topic one week before the opening ceremony. #SochiFail and #SochiProblems gave multiple reports of the poor living arrangements, incomplete construction, broken elevators, and polluted waters. This was one way that social media provided awareness to its users. === Media Perceptions === Media perceptions varied during the games; the Olympics was viewed as a confrontation between Eastern and Western Civilizations. The LGBT community took a stand against the games. Sponsors for the games including Coca-Cola, Mcdonald's, and P&G protested against Russian authorities and Russian anti-LGBT laws. Many protests took a stand against Russian laws, which created a discussion between human rights advocates. Advocates believed organizations should not promote certain values in western markets while supporting an anti-human rights government in another market. == 2016 Rio Summer Olympics == Social media marketing was an influential tool in the promotion and analysis of the 2016 Rio Olympics. Thomas Bach, President of the International Olympic Committee said that the power of sport demonstrates that diversity and interconnectedness can enlighten us all. With over 25,000+ sources of accredited media covering the games, the 2016 games were the most consumed Olympic games to date. Marketing for the Rio Olympics began in 2013 and ultimately lasted 3 years. There were 26 million visits to Olympic.org, the official website of the Olympic games, and over 7 billion views of official Olympic content on social media. There were o

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  • Confidential computing

    Confidential computing

    Confidential computing is a security and privacy-enhancing computational technique focused on protecting data in use. Confidential computing can be used in conjunction with storage and network encryption, which protect data at rest and data in transit respectively. It is designed to address software, protocol, cryptographic, and basic physical and supply-chain attacks, although some critics have demonstrated architectural and side-channel attacks effective against the technology. The technology protects data in use by performing computations in a hardware-based trusted execution environment (TEE). Confidential data is released to the TEE only once it is assessed to be trustworthy. Different types of confidential computing define the level of data isolation used, whether virtual machine, application, or function, and the technology can be deployed in on-premise data centers, edge locations, or the public cloud. It is often compared with other privacy-enhancing computational techniques such as fully homomorphic encryption, secure multi-party computation, and Trusted Computing. Confidential computing is promoted by the Confidential Computing Consortium (CCC) industry group, whose membership includes major providers of the technology. == Properties == Trusted execution environments (TEEs) "prevent unauthorized access or modification of applications and data while they are in use, thereby increasing the security level of organizations that manage sensitive and regulated data". Trusted execution environments can be instantiated on a computer's processing components such as a central processing unit (CPU) or a graphics processing unit (GPU). In their various implementations, TEEs can provide different levels of isolation including virtual machine, individual application, or compute functions. Typically, data in use in a computer's compute components and memory exists in a decrypted state and can be vulnerable to examination or tampering by unauthorized software or administrators. According to the CCC, confidential computing protects data in use through a minimum of three properties: Data confidentiality: "Unauthorized entities cannot view data while it is in use within the TEE". Data integrity: "Unauthorized entities cannot add, remove, or alter data while it is in use within the TEE". Code integrity: "Unauthorized entities cannot add, remove, or alter code executing in the TEE". In addition to trusted execution environments, remote cryptographic attestation is an essential part of confidential computing. The attestation process assesses the trustworthiness of a system and helps ensure that confidential data is released to a TEE only after it presents verifiable evidence that it is genuine and operating with an acceptable security posture. It allows the verifying party to assess the trustworthiness of a confidential computing environment through an "authentic, accurate, and timely report about the software and data state" of that environment. "Hardware-based attestation schemes rely on a trusted hardware component and associated firmware to execute attestation routines in a secure environment". Without attestation, a compromised system could deceive others into trusting it, claim it is running certain software in a TEE, and potentially compromise the confidentiality or integrity of the data being processed or the integrity of the trusted code. == Technical approaches == Technical approaches to confidential computing may vary in which software, infrastructure and administrator elements are allowed to access confidential data. The "trust boundary," which circumscribes a trusted computing base (TCB), defines which elements have the potential to access confidential data, whether they are acting benignly or maliciously. Confidential computing implementations enforce the defined trust boundary at a specific level of data isolation. The three main types of confidential computing are: Virtual machine isolation Application isolation, also known as process isolation Function isolation, also known as library isolation Virtual machine isolation removes the elements controlled by the computer infrastructure or cloud provider, but allows potential data access by elements inside a virtual machine running on the infrastructure. Application or process isolation permits data access only by authorized software applications or processes. Function or library isolation is designed to permit data access only by authorized subroutines or modules within a larger application, blocking access by any other system element, including unauthorized code in the larger application. == Threat model == As confidential computing is concerned with the protection of data in use, only certain threat models can be addressed by this technique. Other types of attacks are better addressed by other privacy-enhancing technologies. === In scope === The following threat vectors are generally considered in scope for confidential computing: Software attacks: including attacks on the host’s software and firmware. This may include the operating system, hypervisor, BIOS, other software and workloads. Protocol attacks: including "attacks on protocols associated with attestation as well as workload and data transport". This includes vulnerabilities in the "provisioning or placement of the workload" or data that could cause a compromise. Cryptographic attacks: including "vulnerabilities found in ciphers and algorithms due to a number of factors, including mathematical breakthroughs, availability of computing power and new computing approaches such as quantum computing". The CCC notes several caveats in this threat vector, including relative difficulty of upgrading cryptographic algorithms in hardware and recommendations that software and firmware be kept up-to-date. A multi-faceted, defense-in-depth strategy is recommended as a best practice. Basic physical attacks: including cold boot attacks, bus and cache snooping and plugging attack devices into an existing port, such as a PCI Express slot or USB port. Basic upstream supply-chain attacks: including attacks that would compromise TEEs through changes such as added debugging ports. The degree and mechanism of protection against these threats varies with specific confidential computing implementations. === Out of scope === Threats generally defined as out of scope for confidential computing include: Sophisticated physical attacks: including physical attacks that "require long-term and/or invasive access to hardware" such as chip scraping techniques and electron microscope probes. Upstream hardware supply-chain attacks: including attacks on the CPU manufacturing process, CPU supply chain in key injection/generation during manufacture. Attacks on components of a host system that are not directly providing the capabilities of the trusted execution environment are also generally out-of-scope. Availability attacks: confidential computing is designed to protect the confidentiality and integrity of protected data and code. It does not address availability attacks such as Denial of Service or Distributed Denial of Service attacks. == Use cases == Confidential computing can be deployed in the public cloud, on-premise data centers, or distributed "edge" locations, including network nodes, branch offices, industrial systems and others. === Data privacy and security === Confidential computing protects the confidentiality and integrity of data and code from the infrastructure provider, unauthorized or malicious software and system administrators, and other cloud tenants, which may be a concern for organizations seeking control over sensitive or regulated data. The additional security capabilities offered by confidential computing can help accelerate the transition of more sensitive workloads to the cloud or edge locations. === Multi-party analytics === Confidential computing can enable multiple parties to engage in joint analysis using confidential or regulated data inside a TEE while preserving privacy and regulatory compliance. In this case, all parties benefit from the shared analysis, but no party's sensitive data or confidential code is exposed to the other parties or system host. Examples include multiple healthcare organizations contributing data to medical research, or multiple banks collaborating to identify financial fraud or money laundering. Oxford University researchers proposed the alternative paradigm called "Confidential Remote Computing" (CRC), which supports confidential operations in Trusted Execution Environments across endpoint computers considering multiple stakeholders as mutually distrustful data, algorithm and hardware providers. === Confidential generative AI === Confidential computing technologies can be applied to various stages of a generative AI deployments to help increase data or model privacy, security, and regulatory compliance. TEEs and remote attestation can protect the integrity of data during AI model training, keep

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  • Social media use in the financial services sector

    Social media use in the financial services sector

    Social media in the financial services sector refers to the use of social media by the financial services sector to promote and distribute financial services. Social media is used in various aspects of the financial industry including customer service, marketing, and product development. It has enabled financial institutions to extend their reach through direct and real-time communication with customers, fostering more personal connections. It also allows individuals to talk to other individuals creating lending and trading via social groups as well as developing new financial services by fintech startup companies. In terms of marketing, social media is utilized by both traditional financial companies as well as disruptive fintech companies such as peer-to-peer lending (P2P) companies. The financial industry has used information technology since its inception in the 1960s and social media fits in with this ongoing development. Larger, traditional financial firms have integrated social media into their marketing strategies. Companies in the financial sector are subject to strict regulations that include how they use social media. In the United States, the Financial Industry Regulatory Authority (FINRA) is a key regulator that sets rules how financial firms can interact with consumers. This includes ensuring that social media posts follow financial advertising rules, such as being fair and balanced and not providing misleading information, and that financial advice is not provided by unqualified personnel, such as influencers. == History == In 2003, at the beginning of social media development, MySpace was founded as a "social networking service." It allowed people to create a profile, connect with other people, and post videos, pictures, and songs. As MySpace grew in popularity, it attracted interest from companies wishing to promote their brands on the social platform. They were joined by Facebook and in 2010 by Instagram. Financial service firms were initially slow to adapt to promotion via social media but soon joined other big firms after they saw the success other industries had in engaging with younger people. == Uses == === Branding === While companies are able to connect with more people remotely through providing online financial services, their branding strategy has shifted from customized to standardized. Prior to the outbreak of technology, most banks used customized branding where they targeted only customers in their regions. Businesses can now use technology to operate beyond their geographic location and maintain a consistent image across multiple countries with standardized branding. By being able to extend a consistent brand reputation across a wider geographic location, financial services companies can take advantage of economies of scale in advertising cost, lower administrative complexity, lower entry into new markets, and improved cross-border learning within the company. === Customer engagement === Online banking reduced face-to-face interaction between customers and their banks. Most banking transactions can now be conducted online or through mobile devices, rather than at a local branch with a teller. Social media provides a channel for firms to maintain personal contact with customers, replicating some of the interaction that was previously available at local branches. For example, a bank's Facebook page may feature an employee profile describing their job duties, which serves to present a more human face for larger institutions. === Lending === Social media is a core marketing channel for online peer-to-peer lending as well as small business lenders. Since these companies operate exclusively online, it makes sense for them to market online through social media channels. They are able to grow and find new lenders and buyers by utilizing social networks. === Trading === Social trading is an alternative way of analyzing financial data by looking at what other traders are doing and comparing, copying and discussing their techniques and strategies. Prior to the advent of social trading, investors and traders were relying on fundamental or technical analysis to form their investment decisions. Using social trading investors and traders could integrate into their investment decision-process social indicators from trading data-feeds of other traders. Investors also use platform like Reddit, Signal messaging or WeChat to create social communities to discuss investments and finance. In some cases they use this to join together using meme stocks to move financial markets, such as the 2021 GameStop short squeeze incident. They can also use social groups to launch and promote new products such as cryptocurrencies. Investing application like WeBull incorporate a forum style messaging system on each stock that is available for trading. Financial brokers such as Fidelity Investments, Interactive Brokers, and E-Trade have moved to incorporate community features in their investment apps. == Regulations == The use of social media by investors and financial services professionals for business purposes is subject to regulatory oversight, in the United States this is done primarily by the Financial Industry Regulatory Authority (FINRA). FINRA's rules, designed to protect investors from misleading information in all communications and this also applies to social media communications. This includes ensuring that social media posts follow financial advertising rules, such as being fair and balanced and not providing misleading information, and that advice is not provided by unqualified personnel, such as influencers and bank staff acting in a personal capacity. Financial firms have to maintain books and records of all interaction with customers and this includes social media. == New products and services == Social media has created entirely new products for the financial services sector, revolutionizing products and developing new industries through the merging of social technology and financial services. Fintech startups use social media to promote products to get them established. Several developing nations have used social media to leapfrog traditional financial technology; for example, WeChat Pay, which developed from the Chinese WeChat social media platform, became a major payment system in China within a few years. In 2015, according to consulting firm Accenture, 390 million people in China had registered to use mobile banking. This figure is more than the population of the United States. In the United States, the fintech company Venmo combines technology and financial services on a social platform. Other financial technology companies that have used social media to develop or promote financial products include: Lending Club – One of the first peer-to-peer lending businesses OnDeck Capital – A US online-only lending business Funding Circle – A UK-based online lending company Wise – A global online money transfers company Kabbage – A US online unsecured loan company later acquired by American Express Avant – A US online unsecured loan company Zopa – A UK online neobank providing peer-to-peer lending == Risks == === Reputational damage === Due to the real-time nature of social media, financial services companies can be impacted by potential reputational issues. Any negative experience by customers can easily be shared online and could become a viral phenomenon, those comments could likely have a detrimental effect on the company’s stock price and reputation. On the other hand, any positive experience a customer has can also be shared online. However, positive experiences are much less likely to become viral. === Scams === The nature of social media makes it easy to target individuals without being seen by the wider community, this allows scammers to target individuals. Example include romance scams such as the pig butchering scam where an individual is tricked to transfer funds or assets to the scammer over social media making it hard for law enforcement to track them or recover funds. === Customer privacy === Customer privacy is important for the financial services industry. It is critical that customer information such as a bank account numbers and other personal information is kept private. However, this information can be leaked if for example, a customer is unhappy with a bank’s service, they may tweet at the bank expressing their frustrations and include their name and account number.

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  • Sharenting

    Sharenting

    "Sharenting" is a portmanteau of "sharing" and "parenting", describing the practice of parents publicizing a large amount of potentially sensitive content about their children on internet platforms, most notably on social media. While the term was coined as recently as 2010, sharenting has become an international phenomenon with widespread presence in the United States, Spain, France, and the United Kingdom. Proponents of sharenting frame the practice as a natural expression of parental pride in their children and argue that critics take sharenting-related posts out of context. Detractors find that it violates child privacy and hurts a parent–child relationship. Academic research has been conducted over the potential social motivations for sharenting and legal frameworks to balance child privacy with this parental practice. Researchers have conducted several psychological surveys, outlining social media accessibility, parental self-identification with children, and social pressure as potential causes for sharenting. Legal scholars have identified international human rights laws, labor protections, and recent online child privacy statutes as potential legal standards to check sharenting abuses. == History == The origins of the term "sharenting" have been attributed to the Wall Street Journal, where they called it "oversharenting," a portmanteau of "oversharing" and "parenting." Priya Kumar suggests that recording life moments of children rearing is not a new practice: people have been using diaries, scrapbooks and baby log books as the media of documentation for centuries. Scholars assert that sharenting has become popular as a result of social media, which has made many people more comfortable with sharing their lives and those of their children online. The trend of oversharing on social media has raised public attention in the 2010s and become the focus of a number of editorials and academic research projects. It was also added to Times Word of the Day in February 2013 and Collins English Dictionary in 2016 given its influence. == Popularity == Several studies describe sharenting as an international phenomenon with widespread prevalence across households. In the United States, researchers at the University of Michigan C.S. Mott Children's Hospital found that almost 75% of American parents were familiar with someone who over-shared information about their child on social media, and an AVG survey determined that 92% of all American two-year-olds had some presence on the internet. In Australia, Fisher-Price conducted a survey which revealed that 90% of Australian parents admitted to over-sharing. In Spain and Czech Republic, a survey of approximately 1,500 parents found that 70-80% participated in sharenting. In the United Kingdom, France, Germany, and Italy, a Research Now report revealed that almost three-quarters of surveyed parents said that they were "willing to share images of their infants". Some claim that sharenting presents a violation of child privacy, and this backlash includes anti-sharenting sites and apps that block baby pictures. One particular outlet of protest was the blog STFU Parents, founded in 2009 to criticize parental oversharing on social media. Some parents felt that these criticisms of sharenting often took posts out of context and neglected some positive aspects of the practice, including advancing a stronger sense of online community. Others, while acknowledging the potential privacy violations of sharenting, suggested a more tailored approach that would only permit posting under certain conditions, notwithstanding audience and identification restrictions for social media posts. == Motivations == Research has suggested that sharenting is associated with a mix of parent self-identification with children, mothering pressures, and the accessibility of social media. Conducting 17 interviews with mothers in the United Kingdom, a London School of Economics study found that parent bloggers often re-explained their sharing practices in terms of expressing their own personal identity, representing their own child as part of themselves. In particular, the report surveyed the use of blogs as a networking vehicle to connect parents with similar family situations and found that sharenting parents, by filtering self-presentation through their parent-child relationship, adopted a more relational identity on social media websites. This included identifying oneself in terms of parental circumstances, whether it be raising a child with a disability or being a single mother. Alternatively, some have suggested that these online expressions indicate the infiltration of individual pride into the sphere of parenting, as family photography becomes a means to "show off" one's children to the others and strengthens a parent's sense of individuated self. Addressing the prevalence of mothers engaging in sharenting, those who purport this view argue that the rise of digital communication has pressured mothers into performing the role of a "good" parent on social media platforms. They claim that these developments may reinforce a dominant vision of a "normal" family, as sharenting posts could be motivated by the need to converge to a normative interpretation of family. == Controversy == While some people assert that online platforms enable parents to establish a community and seek parenting support, others are concerned about the children's data privacy and their lack of informed consent. Sharing content may not only embarrass children but also creates an initial digital footprint, a history of online activity, that the children themselves have no control over. This might bring some negative consequences, such as being ridiculed at school or leaving a negative impression on future employers. === Parental benefits === Many parents use social media to seek parenting advice and share information about their children. With the convenience of online platforms, parent bloggers can easily connect with other people in similar situations as well as those who are willing to contribute meaningful advice. By forming a community, parents can receive encouragement from empathetic peers and assistance from experts in children rearing. Parents whose children need special educational accommodations or have disabilities often found themselves detached from the mainstream parenting style. Therefore, they regard online blogs as a means to gain support from others and support back. Online blogging enables parents of children with disabilities and special needs to connect with other parents. The advice from similarly situated families can open up new possibilities that help the parents "negotiate the complexities of social services, health care, and schools". However, in some cases, posting online about a parent's struggles can cause a backlash, as advocates may accuse the parent of presenting people with that condition in a bad light, or wonder how the child will feel, if they later read these posts and see how much their parents struggled to care for them. Such advantages of social media are not limited to particular groups of parents. In general, most parents benefit from exchanging parenting experience. Statistically speaking, 72% of parents rate social media useful for emotional connection and affirmations, and 74% of them receive support about parenting from friends on social media. Sharenting also plays a role in fostering interpersonal relationships. As the images and words about children's lives initiate conversations, parents use sharenting to stay connected with distant friends and relatives. In particular, mothers, as a research study reveals, are willing to engage in sharenting since they believe that the positive contents can help avoid digital conflicts and maintain close relations with those in their social circles. Researchers also found that female participants in this study carefully chose photos and phrases to express love and present laudable behaviors of children in their updates, which indicates their intention to convey positive messages. These messages also promote a close social network for a child as the parents invites supportive family members and friends into daily life. === Children's privacy === Given the potential misuse of digital data, people are critical about sharenting, and the majority of parents are cautious about the wrongdoing with online posts. The disclosure of minors' personal information, such as geographic location, name, date of birth, pictures, and the schools they attend, might expose them to illegal practices by recipients with malicious intentions. Sharented information is often abused for "identity theft", when imposters manage to track, stalk, commit fraud against children, or even blackmail the family. According to Barclays, online fraud targeting the young generation will contribute to a loss of £670 million (approximately $790 million) by 2030, and two-thirds of identity fraud will be related to s

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  • Cryptographic Module Testing Laboratory

    Cryptographic Module Testing Laboratory

    Cryptographic Module Testing Laboratory (CMTL) is an information technology (IT) computer security testing laboratory that is accredited to conduct cryptographic module evaluations for conformance to the FIPS 140-2 U.S. Government standard. The National Institute of Standards and Technology (NIST) National Voluntary Laboratory Accreditation Program (NVLAP) accredits CMTLs to meet Cryptographic Module Validation Program (CMVP) standards and procedures. This has been replaced by FIPS 140-2 and the Cryptographic Module Validation Program (CMVP). == CMTL requirements == These laboratories must meet the following requirements: NIST Handbook 150, NVLAP Procedures and General Requirements NIST Handbook 150-17 Information Technology Security Testing - Cryptographic Module Testing NVLAP Specific Operations Checklist for Cryptographic Module Testing == FIPS 140-2 in relation to the Common Criteria == A CMTL can also be a Common Criteria (CC) Testing Laboratory (CCTL). The CC and FIPS 140-2 are different in the abstractness and focus of evaluation. FIPS 140-2 testing is against a defined cryptographic module and provides a suite of conformance tests to four FIPS 140 security levels. FIPS 140-2 describes the requirements for cryptographic modules and includes such areas as physical security, key management, self tests, roles and services, etc. The standard was initially developed in 1994 - prior to the development of the CC. The CC is an evaluation against a Protection Profile (PP), or security target (ST). Typically, a PP covers a broad range of products. A CC evaluation does not supersede or replace a validation to either FIPS 140-1, FIPS140-2 or FIPS 140-3. The four security levels in FIPS 140-1 and FIPS 140-2 do not map directly to specific CC EALs or to CC functional requirements. A CC certificate cannot be a substitute for a FIPS 140-1 or FIPS 140-2 certificate. If the operational environment is a modifiable operational environment, the operating system requirements of the Common Criteria are applicable at FIPS Security Levels 2 and above. FIPS 140-1 required evaluated operating systems that referenced the Trusted Computer System Evaluation Criteria (TCSEC) classes C2, B1 and B2. However, TCSEC is no longer in use and has been replaced by the Common Criteria. Consequently, FIPS 140-2 now references the Common Criteria. FIPS 140-2 or FIPS 140-3 validation efforts can be in some parts reused in Common Criteria evaluations, specifically in areas related to entropy source and cryptographic algorithms.

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  • Pixlr

    Pixlr

    Pixlr is a group of SaaS creative tools including Pixlr.com, Designs.ai and Vectr.com. Pixlr.com is a cloud-based set of image editing tools and utilities, including AI image generation and enhancements. The Pixlr suite targets users who require subjectively simple, or more advanced, photo editing as well as graphic design. It features a freemium business model with subscription plans—Plus, Premium and Teams. The platform can be used on desktop and also smartphones and tablets. Pixlr is compatible with various image formats such as JPEG, PNG, WEBP, GIF, PSD (Photoshop Document) and PXZ (native Pixlr document format). Designs.ai lets users create content using AI, with a goal of being within two minutes, across different media types including videos, text, banners and audio. Vectr.com was acquired in 2017 before being spun out into Pixlr Group in 2023. == History == Pixlr was founded in 2008 and built on Macromedia Flash. On 19 July 2011, Autodesk announced that they had acquired the Pixlr suite. In 2013, Time listed Pixlr as one of the top 50 websites of the year. In 2017, Pixlr was acquired from Autodesk. It was subsequently rebuilt and relaunched in HTML5 in 2019. In September 2023, Pixlr was awarded as the Top 13 GenAi Web Product by the world's top venture firm Andreessen Horowitz. In November 2023, Pixlr, Designs.ai and Vectr were combined as a new business group named Pixlr Group focusing on generative AI and creative software solutions. In May 2024, Pixlr was featured as one of the top 18 progressive web applications highlighted on Google I/O. == Versions == Pixlr.com rebranded itself as a full creative suite in 2019 by introducing Pixlr X, Pixlr E and Pixlr M. The platform introduced more features in December 2021 with a new logo and added tools which included: Brushes, the 'Heal tool', Animation, and Batch upload. The brush feature enables the creation of hand-drawn effects. The Heal tool allows users to remove unwanted objects from their images whereas the Animation feature can be used to include movements into their edits. Users can also utilize Batch upload to edit up to 50 images simultaneously. In November 2022, Pixlr 2023 was launched, adding more tools such as "AI smart resize", colorization, text wrapping and other additional effects. In November 2023, Pixlr 2024 was launched with Pixlr Designer and new AI-powered updates which includes AI image generation, AI infill, AI inpainting and more.

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  • Media intelligence

    Media intelligence

    Media intelligence uses data mining and data science to analyze public, social and editorial media content. It refers to marketing systems that synthesize billions of online conversations into relevant information. This allow organizations to measure and manage content performance, understand trends, and drive communications and business strategy. Media intelligence can include software as a service using big data terminology. This includes questions about messaging efficiency, share of voice, audience geographical distribution, message amplification, influencer strategy, journalist outreach, creative resonance, and competitor performance in all these areas. Media intelligence differs from business intelligence in that it uses and analyzes data outside company firewalls. Examples of that data are user-generated content on social media sites, blogs, comment fields, and wikis etc. It may also include other public data sources like press releases, news, blogs, legal filings, reviews and job postings. Media intelligence may also include competitive intelligence, wherein information that is gathered from publicly available sources such as social media, press releases, and news announcements are used to better understand the strategies and tactics being deployed by competing businesses. Media intelligence is enhanced by means of emerging technologies like ambient intelligence, machine learning, semantic tagging, natural language processing, sentiment analysis and machine translation. == Technologies used == Different media intelligence platforms use different technologies for monitoring, curating content, engaging with content, data analysis and measurement of communications and marketing campaign success. These technology providers may obtain content by scraping content directly from websites or by connecting to the API provided by social media, or other content platforms that are created for 3rd party developers to develop their own applications and services that access data. Technology companies may also get data from a data reseller. Some social media monitoring and analytics companies use calls to data providers each time an end-user develops a query. Others archive and index social media posts to provide end users with on-demand access to historical data and enable methodologies and technologies leveraging network and relational data. Additional monitoring companies use crawlers and spidering technology to find keyword references, known as semantic analysis or natural language processing. Basic implementation involves curating data from social media on a large scale and analyzing the results to make sense out of it.

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  • Cryptovirology

    Cryptovirology

    Cryptovirology refers to the study of cryptography use in malware, such as ransomware and asymmetric backdoors. Traditionally, cryptography and its applications are defensive in nature, and provide privacy, authentication, and security to users. Cryptovirology employs a twist on cryptography, showing that it can also be used offensively. It can be used to mount extortion based attacks that cause loss of access to information, loss of confidentiality, and information leakage, tasks which cryptography typically prevents. The field was born with the observation that public-key cryptography can be used to break the symmetry between what an antivirus analyst sees regarding malware and what the attacker sees. The antivirus analyst sees a public key contained in the malware, whereas the attacker sees the public key contained in the malware as well as the corresponding private key (outside the malware) since the attacker created the key pair for the attack. The public key allows the malware to perform trapdoor one-way operations on the victim's computer that only the attacker can undo. == Overview == The field encompasses covert malware attacks in which the attacker securely steals private information such as symmetric keys, private keys, PRNG state, and the victim's data. Examples of such covert attacks are asymmetric backdoors. An asymmetric backdoor is a backdoor (e.g., in a cryptosystem) that can be used only by the attacker, even after it is found. This contrasts with the traditional backdoor that is symmetric, i.e., anyone that finds it can use it. Kleptography, a subfield of cryptovirology, is the study of asymmetric backdoors in key generation algorithms, digital signature algorithms, key exchanges, pseudorandom number generators, encryption algorithms, and other cryptographic algorithms. The NIST Dual EC DRBG random bit generator has an asymmetric backdoor in it. The EC-DRBG algorithm utilizes the discrete-log kleptogram from kleptography, which by definition makes the EC-DRBG a cryptotrojan. Like ransomware, the EC-DRBG cryptotrojan contains and uses the attacker's public key to attack the host system. The cryptographer Ari Juels indicated that NSA effectively orchestrated a kleptographic attack on users of the Dual EC DRBG pseudorandom number generation algorithm and that, although security professionals and developers have been testing and implementing kleptographic attacks since 1996, "you would be hard-pressed to find one in actual use until now." Due to public outcry about this cryptovirology attack, NIST rescinded the EC-DRBG algorithm from the NIST SP 800-90 standard. Covert information leakage attacks carried out by cryptoviruses, cryptotrojans, and cryptoworms that, by definition, contain and use the public key of the attacker is a major theme in cryptovirology. In "deniable password snatching," a cryptovirus installs a cryptotrojan that asymmetrically encrypts host data and covertly broadcasts it. This makes it available to everyone, noticeable by no one (except the attacker), and only decipherable by the attacker. An attacker caught installing the cryptotrojan claims to be a virus victim. An attacker observed receiving the covert asymmetric broadcast is one of the thousands, if not millions of receivers, and exhibits no identifying information whatsoever. The cryptovirology attack achieves "end-to-end deniability." It is a covert asymmetric broadcast of the victim's data. Cryptovirology also encompasses the use of private information retrieval (PIR) to allow cryptoviruses to search for and steal host data without revealing the data searched for even when the cryptotrojan is under constant surveillance. By definition, such a cryptovirus carries within its own coding sequence the query of the attacker and the necessary PIR logic to apply the query to host systems. == History == The first cryptovirology attack and discussion of the concept was by Adam L. Young and Moti Yung, at the time called "cryptoviral extortion" and it was presented at the 1996 IEEE Security & Privacy conference. In this attack, a cryptovirus, cryptoworm, or cryptotrojan contains the public key of the attacker and hybrid encrypts the victim's files. The malware prompts the user to send the asymmetric ciphertext to the attacker who will decipher it and return the symmetric decryption key it contains for a fee. The victim needs the symmetric key to decrypt the encrypted files if there is no way to recover the original files (e.g., from backups). The 1996 IEEE paper predicted that cryptoviral extortion attackers would one day demand e-money, long before Bitcoin even existed. Many years later, the media relabeled cryptoviral extortion as ransomware. In 2016, cryptovirology attacks on healthcare providers reached epidemic levels, prompting the U.S. Department of Health and Human Services to issue a Fact Sheet on Ransomware and HIPAA. The fact sheet states that when electronic protected health information is encrypted by ransomware, a breach has occurred, and the attack therefore constitutes a disclosure that is not permitted under HIPAA, the rationale being that an adversary has taken control of the information. Sensitive data might never leave the victim organization, but the break-in may have allowed data to be sent out undetected. California enacted a law that defines the introduction of ransomware into a computer system with the intent of extortion as being against the law. == Examples == === Tremor virus === While viruses in the wild have used cryptography in the past, the only purpose of such usage of cryptography was to avoid detection by antivirus software. For example, the tremor virus used polymorphism as a defensive technique in an attempt to avoid detection by anti-virus software. Though cryptography does assist in such cases to enhance the longevity of a virus, the capabilities of cryptography are not used in the payload. The One-half virus was amongst the first viruses known to have encrypted affected files. === Tro_Ransom.A virus === An example of a virus that informs the owner of the infected machine to pay a ransom is the virus nicknamed Tro_Ransom.A. This virus asks the owner of the infected machine to send $10.99 to a given account through Western Union. Virus.Win32.Gpcode.ag is a classic cryptovirus. This virus partially uses a version of 660-bit RSA and encrypts files with many different extensions. It instructs the owner of the machine to email a given mail ID if the owner desires the decryptor. If contacted by email, the user will be asked to pay a certain amount as ransom in return for the decryptor. === CAPI === It has been demonstrated that using just 8 different calls to Microsoft's Cryptographic API (CAPI), a cryptovirus can satisfy all its encryption needs. == Other uses of cryptography-enabled malware == Apart from cryptoviral extortion, there are other potential uses of cryptoviruses, such as deniable password snatching, cryptocounters, private information retrieval, and in secure communication between different instances of a distributed cryptovirus.

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