Best AI for Resume

Best AI for Resume — hands-on reviews, top picks, pricing, pros and cons and a practical how-to guide on Aizhi.

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  Wrike

  Wrike, Inc. is an American project management application service provider based in San Jose, California. Wrike also has offices in India, Dallas, Tallinn, Nicosia, Dublin, Tokyo, Melbourne, and Prague. == History == Wrike was founded in 2006 by Andrew Filev. Currently CEO at Wrike is Thomas Scott. Filev initially self-funded the company before later obtaining investor funding. Wrike released the beta version of its software (also called Wrike) in December 2006. The company then launched a new "Enterprise" platform in December 2013. In June 2015, Wrike announced the opening of an office in Dublin, Ireland and in 2016, Wrike launched a datacenter there to host data in compliance with local privacy regulations. In July 2016, Wrike announced the launch of Wrike for Marketers. That same year, Wrike's headquarters moved from Mountain View to San Jose, California. In January 2021, Citrix Systems announced its intention to acquire Wrike for $2.25 billion. The acquisition closed in March 2021. On January 31, 2022, it was announced that Citrix had been acquired in a $16.5 billion deal by affiliates of Vista Equity Partners and Evergreen Coast Capital. Citrix would merge with TIBCO Software, a Vista portfolio company to form Cloud Software Group (CSG). In September 2022, Wrike separated from Citrix Systems. In July 2023, Vista transferred ownership to Symphony Technology Group. == Investments == Wrike received $1 million in Angel funding in 2012 from TMT Investments. In October, 2013, Wrike secured $10 million in investment funding from Bain Capital. In May 2015, the company secured $15 million in a new round of funding. Investors included Scale Venture Partners, DCM Ventures, and Bain Capital. At that time, Wrike had 8,000 customers, 200 employees, and 30,000 new users each month. On November 29, 2018, Wrike signed a definitive agreement to receive a majority investment by Vista Equity Partners (“Vista”), a firm focused on software, data and technology-enabled businesses. == Software == The Wrike project management software is a Software-as-a-Service (SaaS) product with tools for managing projects, deadlines, schedules, and workflow processes. It includes collaboration features. The application is available in English, French, Spanish, German, Portuguese, Italian, Japanese and Russian. Wrike has triggers for task automation in workflow management. === Features === Wrike features a multi-pane UI and consists of features in two categories: project management, and team collaboration. According to Wrike, project management features are designed to help teams track dates and dependencies associated with projects, manage assignments and resources, and track time. These include an interactive Gantt chart, a workload view, and a sortable table that can be customized to store project data. The software includes a co-editing tool, discussion threads on tasks, and tools for attaching documents, editing them, and tracking their changes. Wrike uses an "inbox" feature and browser notifications to alert users of updates from their colleagues and dashboards for quick overviews of pending tasks. These updates are also available in Wrike's mobile apps on iOS and Android. Wrike has an optional feature set called "Wrike for Marketers" which has several tools for managing marketing workflows. In May 2012, Wrike announced the launch of a freemium version of its software for teams of up to 5 users. That year also saw the integration of a live text coeditor into its workspace to unify collaboration and task management. In late 2013 Wrike released a new feature set called Wrike Enterprise which included advanced analytics and other tools targeted at large business customers. Since then it has released several major updates to Wrike Enterprise, including a customizable spreadsheet called "Dynamic Platform" in late 2014 and custom workflows for teams in 2015. In July 2016, Wrike was updated with a set of add-on features under the name "Wrike for Marketers," which includes integrations with Adobe Photoshop, a tool for submitting requests, and proofing and approval tools for creative assets like videos and images. Wrike is available as native Android and iOS apps. Mobile apps include an interactive Gantt chart that syncs across devices. The apps are available offline, and sync when connection is restored. === Criticism === Critics said new users may have a learning curve with complex features. Wrike has 2,710 customers for an estimated 0.04% market share. Competitors include Google Workspace, Slack (software), and Quip (software).

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  Tempos Modernos

  Tempos Modernos (English: Modern Times) is a Brazilian telenovela produced and broadcast by TV Globo. It premiered on 11 January 2010, replacing Caras & Bocas, and ended on 16 July 2010, replaced by Ti Ti Ti. The series is written by Bosco Brasil, with the collaboration of Izabel de Oliveira, Maria Elisa Berredo, Mário Teixeira and Patrícia Moretzsohn. It stars Fernanda Vasconcellos, Thiago Rodrigues, Antônio Fagundes, and Eliane Giardini. Priscila Fantin, Danton Mello, Marcos Caruso, Regiane Alves, Vivianne Pasmanter, Otávio Muller, Felipe Camargo, and Malu Galli also star in main roles. == Cast == Fernanda Vasconcellos as Cornélia Cordeiro Santos Reis "Nelinha" Thiago Rodrigues as José Carlos Pimenta Cordeiro "Zeca" Antônio Fagundes as Leal Cordeiro Eliane Giardini as Hélia Pimenta Priscila Fantin as Nara Nolasco Marcos Caruso as Otto Niemann Vivianne Pasmanter as Regiane Cordeiro Mourão Regiane Alves as Goretti Cordeiro Bodanski "Gô" Otávio Muller as Altemir Assunção da Paz Bodanski (Bodanski) Felipe Camargo as Vinícius Porto de Mello "Portinho" Danton Mello as Renato Vieira de Mattos Alessandra Maestrini as Benedita Kusnezov Piñon "Dita'" Leonardo Medeiros as Ramon Piñon Guilherme Weber as Albano Mourão Grazi Massafera as Deodora Madureira Niemann / N. Anne Malu Galli as Iolanda Paranhos Guilherme Leicam as Led Piñon Aline Peixoto as Jannis Piñon Caroline Abras as Katrina João Baldasserini as Túlio Osório Débora Duarte as Tertuliana "Tertu" Otávio Augusto as Faustaço Lumbriga Selma Egrei as Tamara Palumbo Genézio de Barros as Pasquale Paula Possani as Maureen Lobianco Ricardo Blat as Fidélio Pascoal da Conceição as Zuppo Tuna Dwek as Justine Jairo Mattos as Gaulês "Jean Paul" Luciana Borghi as Bárbara Lee Cris Vianna as Tita Bicalho Edmilson Barros as Lindomar Mariano Assunção Cláudia Missura as Lavínia Palumbo Victor Pecoraro as Ricardo Maurício "Maurição" Naruna Costa as Dolores Damasceno Antônio Fragoso as Zapata Fabrício Boliveira as Nabuco Mota Eliana Pittman as Miranda Paranhos Márcio Seixas as Frankenstein "Frank" (voice) Joana Lerner as Heloísa "Helô" Darlan Cunha as João Carlos Paranhos "Joca" Janaína Ávila as Milena Morgado Anderson Lau as Okuda Alexandra Martins as Dulcinólia Lumbriga "Duba" Paulo Leal de Melo as Raulzão "Ducha Fria" Cássio Inácio as Tartana Gilberto Miranda as Madrugadinha Rafa Martins as Max do Cavaco Isabel Lobo as Thaís Trancoso Alexandre Cioletti as Valvênio Xandy Britto as Nelsinho Pallotti Polliana Aleixo as Maria Eunice Cordeiro Bodanski Ana Karolina Lannes as Maria Eugênia Cordeiro Bodanski Rebeca Orestein as Maria Helena Cordeiro Bodanski Jenifer de Oliveira Andrade as Maria Clara Cordeiro Bodanski

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  The Quantum Thief

  The Quantum Thief is the debut science fiction novel by Finnish writer Hannu Rajaniemi and the first novel in a trilogy featuring the character of Jean le Flambeur; the sequels are The Fractal Prince (2012) and The Causal Angel (2014). The novel was published in Britain by Gollancz in 2010, and by Tor in 2011 in the US. It is a heist story, set in a futuristic Solar System, that features a protagonist modeled on Arsène Lupin, the gentleman thief of Maurice Leblanc. The novel was nominated for the 2011 Locus Award for Best First Novel, and was second runner-up for the 2011 Campbell Memorial Award. == Setting == Several centuries after the technological singularity largely destroyed Earth, various posthuman factions compete for dominance in the Solar System. Though sentient superintelligent AGI has never been successfully developed, civilization has been greatly transformed by the proliferation of Hansonian brain emulations (termed "gogols" in reference to Nikolai Gogol, and in particular his novel Dead Souls). An alliance of powerful gogol copies rule the inner system from computronium megastructures housing trillions of virtual minds, laboring to resurrect the dead in religious devotion to the philosophy of Nikolai Fedorov. This alliance, the Sobornost, has been in conflict with a community of quantum entangled minds who adhere to the "no-cloning" principle of quantum information theory, and so do not see the Sobornost's ultimate goal as resurrection, but death. Most of this community, the Zoku, was devastated when Jupiter was destroyed with a weaponized gravitational singularity. Among the last remnants of near-baseline humanity exist on the mobile cities of Mars, where advanced cryptography and an obsessive privacy culture ensure that the Sobornost cannot upload their citizens' minds. The most notable of these cities is the Oubliette, where time is used as a currency. When a citizen's balance reaches zero their mind is transferred to a robotic body to serve the needs of the city for a set period, before being returned to their original body with a restored balance of time. == Plot summary == Countless gogols of the legendary gentleman thief Jean Le Flambeur are trapped in a virtual Sobornost prison in orbit around Neptune, playing an iterated prisoner's dilemma until his mind learns to cooperate. A warrior from the Oort Cloud, which has been settled by Finnish colonists, successfully retrieves one of the Le Flambeur gogols and uploads it into a real-space body. Acting on behalf of a competing Sobornost authority, this Oortian, Mieli, ferries the thief to the Martian city known as The Oubliette, where he has stored his memories for later recovery. The two intend to recover his memories so that he may return to an operating capacity sufficient to serve his Sobornost benefactor in a theft and repay his liberation. On the Oubliette, the young detective Isidore Beautrelet helps vigilantes catch Sobornost agents illicitly uploading human minds. These vigilantes are revealed to be in the service of a local colony of Zoku. Beautrelet is employed to investigate the arrival of Le Flambeur, and in the process becomes aware that the Oubliette's cryptographic security was always compromised. The memories of its citizens are fabrications, and the "King of Mars" long believed ousted in a revolution, still reigns behind the scenes. This King, who is another copy of Jean Le Flambeur, is defeated in the ensuing conflict. Le Flambeur fails to recover all of his memories, which he had locked with a quantum entangled revolver that required him to kill several of his old friends to open his stored memory. He and Mieli escape a liberated Mars having recovered only a mysterious "Schrödinger’s Box" from the Memory Palace. == Themes == Themes central to The Quantum Thief are the unreliability and malleability of memory and the effects of extreme longevity on an individual's perspective and personality. Prisons, surveillance and control in society are also major themes. In the book, the people living in the Oubliette society on Mars have two types of memory; in addition to a traditional, personal memory, there is the exomemory, which can be accessed by other people, from anywhere in the city. Memories about personal experiences can be stored in the exomemory and partitioned, with different levels of access granted to different people. These memories can be used, among other things, as an expedient form of communication. The Oubliette society has an economy where time is used as currency. When an individual's time is expended, their consciousness is uploaded into a "Quiet". The Quiet are mute machine servants who maintain and protect the city. Although the quiet seem to have little interest in the world outside their occupations, they do seem to retain some traces of their former personalities and memories. The conspiracy central to the plot involves the hidden rulers, called the "cryptarchs", manipulating and abusing the exomemory and through the citizens' transformations to quiet and back, the traditional memory as well. In the book, the Oubliette society is compared to a panopticon; a prison, where every action of the dwellers can be scrutinized. == History and influences == The first chapter of The Quantum Thief was presented by Rajaniemi's literary agent, John Jarrold, to Gollancz as the basis for the three-book deal that was eventually secured. Rajaniemi has stated that he had "come up with an outline that had every single idea I could cram into it, because I wanted to be worthy of what had happened." The outline eventually expanded into three parts, and the first part became The Quantum Thief. The novel's plot was inspired by one of Rajaniemi's favorite characters in fiction, Maurice Leblanc's gentleman thief Arsène Lupin, who operates on both sides of the law. What intrigued Rajaniemi were the cycles of redemption and relapse Lupin goes through as he tries to go straight, always falling short. Besides LeBlanc, Rajaniemi mentioned Roger Zelazny as a strong influence. Ian McDonald was the other science fiction author he mentioned as influential, plus Frances A.Yates's book The Art of Memory, for memory palaces. In an interview, Rajaniemi said he wasn't trying to write the novel as hard science fiction: "For me, the more important consequence of having a scientific background is a degree of speculative rigour: trying hard to work out the consequences of the assumptions one begins with." == Reception == The novel has received generally positive reviews. Gary K. Wolfe writes in his Locus review that Rajaniemi has "spectacularly delivered on the promise that this is likely the most important debut SF novel we'll see this year". James Lovegrove, reviewing the book in his Financial Times column, notes that "many an anglophone author would kill to turn out prose half as good as this, especially on their maiden effort." Eric Brown, reviewing for The Guardian, finds the novel to be "a brilliant debut", while alluding to the "apocryphal" (and incorrect) myth that "this novel sold on the strength of its first line." Sam Bandah, at SciFiNow, praises the novel for "its engaging narrative and characters backed by often almost intimidatingly good sci-fi concepts." Criticism for the novel has generally centred on Rajaniemi's sparse "show, don't tell" writing style. Brown notes that "the author makes no concessions to the lazy reader with info-dumps or convenient explanations." Niall Alexander, of the Speculative Scotsman, states that "had there been some sort of index, [he] would have gladly (and repeatedly) referred to it during the mind-boggling first third of The Quantum Thief", while proclaiming the novel to be "the sci-fi debut of 2010." == Awards == Nominee for the 2011 Locus Award for Best First Novel. Third place for the 2011 John W. Campbell Memorial Award for Best Science Fiction Novel

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  Deepfake pornography

  Deepfake pornography is a form of non-consensual AI pornography created by altering existing photographs or videos using deepfake technology to modify the appearance of the participants. The use of deepfake pornography has sparked controversy because it involves the making and sharing of realistic videos featuring non-consenting individuals and is sometimes used for revenge porn. Many countries have criminalized this "new voyeurism" through legislative measures and technological solutions. == History == The term "deepfake" was coined in 2017 on a Reddit forum where users shared altered pornographic videos created using machine learning algorithms. It is a combination of the word "deep learning", which refers to the program used to create the videos, and "fake" meaning the videos are not real. Deepfake pornography was originally created on a small individual scale using a combination of machine learning algorithms, computer vision techniques, and AI software. The process began by gathering a large amount of source material (including both images and videos) of a person's face, and then using a deep learning model to train a Generative Adversarial Network to create a fake video that convincingly swaps the face of the source material onto the body of a pornographic performer. However, the production process has significantly evolved since 2018, with the advent of several public apps that have largely automated the process. While several AI "nudification" apps emerged on mainstream platforms like Google Play and the Apple App Store around 2023, major tech storefronts have since implemented stricter policies and automated detection to ban such software. Consequently, the proliferation of non-consensual deepfake pornography has largely shifted to decentralized websites, specialized online forums, and third-party messaging bot ecosystems. Deepfake pornography is sometimes confused with fake nude photography, but the two are mostly different. Fake nude photography typically uses non-sexual images and merely makes it appear that the people in them are nude. == Notable cases == Deepfake technology has been used to create non-consensual and pornographic images and videos of famous women. One of the earliest examples occurred in 2017 when a deepfake pornographic video of Gal Gadot was created by a Reddit user and quickly spread online. Since then, there have been numerous instances of similar deepfake content targeting other female celebrities, such as Emma Watson, Natalie Portman, and Scarlett Johansson. Johansson spoke publicly on the issue in December 2018, condemning the practice but also refusing legal action because she views the harassment as inevitable. === Rana Ayyub === In 2018, Rana Ayyub, an Indian investigative journalist, was the target of an online hate campaign stemming from her condemnation of the Indian government, specifically her speaking out against the rape of an eight-year-old Kashmiri girl. Ayyub was bombarded with rape and death threats, and had a doctored pornographic video of her circulated online. In a Huffington Post article, Ayyub discussed the long-lasting psychological and social effects this experience has had on her. She explained that she continued to struggle with her mental health and how the images and videos continued to resurface whenever she took a high-profile case. === Atrioc controversy === In 2023, Twitch streamer Atrioc stirred controversy when he accidentally revealed deepfake pornographic material featuring female Twitch streamers while on live. The influencer has since admitted to paying for AI generated porn, and apologized to the women and his fans. === Taylor Swift === In January 2024, AI-generated sexually explicit images of American singer Taylor Swift were posted on X (formerly Twitter), and spread to other platforms such as Facebook, Reddit and Instagram. One tweet with the images was viewed over 45 million times before being removed. A report from 404 Media found that the images appeared to have originated from a Telegram group, whose members used tools such as Microsoft Designer to generate the images, using misspellings and keyword hacks to work around Designer's content filters. After the material was posted, Swift's fans posted concert footage and images to bury the deepfake images, and reported the accounts posting the deepfakes. Searches for Swift's name were temporarily disabled on X, returning an error message instead. Graphika, a disinformation research firm, traced the creation of the images back to a 4chan community. A source close to Swift told the Daily Mail that she would be considering legal action, saying, "Whether or not legal action will be taken is being decided, but there is one thing that is clear: These fake AI-generated images are abusive, offensive, exploitative, and done without Taylor's consent and/or knowledge." The controversy drew condemnation from White House Press Secretary Karine Jean-Pierre, Microsoft CEO Satya Nadella, the Rape, Abuse & Incest National Network, and SAG-AFTRA. Several US politicians called for federal legislation against deepfake pornography. Later in the month, US senators Dick Durbin, Lindsey Graham, Amy Klobuchar and Josh Hawley introduced a bipartisan bill that would allow victims to sue individuals who produced or possessed "digital forgeries" with intent to distribute, or those who received the material knowing it was made non-consensually. === 2024 Telegram deepfake scandal === It emerged in South Korea in August 2024, that many teachers and female students were victims of deepfake images created by users who utilized AI technology. Journalist Ko Narin of The Hankyoreh uncovered the deepfake images through Telegram chats. On Telegram, group chats were created specifically for image-based sexual abuse of women, including middle and high school students, teachers, and even family members. Women with photos on social media platforms like KakaoTalk, Instagram, and Facebook are often targeted as well. Perpetrators use AI bots to generate fake images, which are then sold or widely shared, along with the victims' social media accounts, phone numbers, and KakaoTalk usernames. One Telegram group reportedly drew around 220,000 members, according to a Guardian report. Investigations revealed numerous chat groups on Telegram where users, mainly teenagers, create and share explicit deepfake images of classmates and teachers. The issue came in the wake of a troubling history of digital sex crimes, notably the notorious Nth Room case in 2019. The Korean Teachers Union estimated that more than 200 schools had been affected by these incidents. Activists called for a "national emergency" declaration to address the problem. South Korean police reported over 800 deepfake sex crime cases by the end of September 2024, a stark rise from just 156 cases in 2021, with most victims and offenders being teenagers. On September 21, 6,000 people gathered at Marronnier Park in northeastern Seoul to demand stronger legal action against deepfake crimes targeting women. On September 26, following widespread outrage over the Telegram scandal, South Korean lawmakers passed a bill criminalizing the possession or viewing of sexually explicit deepfake images and videos, imposing penalties that include prison terms and fines. Under the new law, those caught buying, saving, or watching such material could face up to three years in prison or fines up to 30 million won ($22,600). At the time the bill was proposed, creating sexually explicit deepfakes for distribution carried a maximum penalty of five years, but the new legislation would increase this to seven years, regardless of intent. By October 2024, it was estimated that "nudify" deep fake bots on Telegram were up to four million monthly users. === 2025–2026 Grok/X chatbot deepfake scandal === In December 2025, Bloomberg reported that X users found Grok would comply with unconsensual requests to digitally undress individuals, including minors, or show them performing sexually explicit acts. The majority of these prompts were targeted at women and girls. An analysis of 20,000 images generated by Grok between December 25, 2025 and January 1, 2026 showed 2% were of people in bikinis or transparent clothes and appeared to be 18 or younger, including 30 of "young or very young" women or girls. A separate analysis conducted over 24 hours from January 5 to 6 calculated that users had Grok create 6,700 sexually suggestive or nudified images per hour. xAI responded to requests for comment from media organizations with the automated reply, "Legacy Media Lies". The bot's image generation sparked an international backlash and calls for legal or regulatory action from officials in the European Union, United Kingdom, Poland, France, India, Malaysia, and Brazil. === Fernandes–Ulmen case === German TV presenter Collien Fernandes, filed a complaint against her ex-husband, actor Christian Ulmen, for several accusation including, ident

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  Linked timestamping

  Linked timestamping is a type of trusted timestamping where issued time-stamps are related to each other. Each time-stamp would contain data that authenticates the time-stamp before it, the authentication would be authenticating the entire message, including the previous time-stamps authentication, making a chain. This makes it impossible to add a time-stamp in to the middle of the chain, as any time-stamps afterwards would be different. == Description == Linked timestamping creates time-stamp tokens which are dependent on each other, entangled in some authenticated data structure. Later modification of the issued time-stamps would invalidate this structure. The temporal order of issued time-stamps is also protected by this data structure, making backdating of the issued time-stamps impossible, even by the issuing server itself. The top of the authenticated data structure is generally published in some hard-to-modify and widely witnessed media, like printed newspaper or public blockchain. There are no (long-term) private keys in use, avoiding PKI-related risks. Suitable candidates for the authenticated data structure include: Linear hash chain Merkle tree (binary hash tree) Skip list The simplest linear hash chain-based time-stamping scheme is illustrated in the following diagram: The linking-based time-stamping authority (TSA) usually performs the following distinct functions: Aggregation For increased scalability the TSA might group time-stamping requests together which arrive within a short time-frame. These requests are aggregated together without retaining their temporal order and then assigned the same time value. Aggregation creates a cryptographic connection between all involved requests; the authenticating aggregate value will be used as input for the linking operation. Linking Linking creates a verifiable and ordered cryptographic link between the current and already issued time-stamp tokens. Publishing The TSA periodically publishes some links, so that all previously issued time-stamp tokens depend on the published link and that it is practically impossible to forge the published values. By publishing widely witnessed links, the TSA creates unforgeable verification points for validating all previously issued time-stamps. == Security == Linked timestamping is inherently more secure than the usual, public-key signature based time-stamping. All consequential time-stamps "seal" previously issued ones - hash chain (or other authenticated dictionary in use) could be built only in one way; modifying issued time-stamps is nearly as hard as finding a preimage for the used cryptographic hash function. Continuity of operation is observable by users; periodic publications in widely witnessed media provide extra transparency. Tampering with absolute time values could be detected by users, whose time-stamps are relatively comparable by system design. Absence of secret keys increases system trustworthiness. There are no keys to leak and hash algorithms are considered more future-proof than modular arithmetic based algorithms, e.g. RSA. Linked timestamping scales well - hashing is much faster than public key cryptography. There is no need for specific cryptographic hardware with its limitations. The common technology for guaranteeing long-term attestation value of the issued time-stamps (and digitally signed data) is periodic over-time-stamping of the time-stamp token. Because of missing key-related risks and of the plausible safety margin of the reasonably chosen hash function this over-time-stamping period of hash-linked token could be an order of magnitude longer than of public-key signed token. == Research == === Foundations === Stuart Haber and W. Scott Stornetta proposed in 1990 to link issued time-stamps together into linear hash-chain, using a collision-resistant hash function. The main rationale was to diminish TSA trust requirements. Tree-like schemes and operating in rounds were proposed by Benaloh and de Mare in 1991 and by Bayer, Haber and Stornetta in 1992. Benaloh and de Mare constructed a one-way accumulator in 1994 and proposed its use in time-stamping. When used for aggregation, one-way accumulator requires only one constant-time computation for round membership verification. Surety started the first commercial linked timestamping service in January 1995. Linking scheme is described and its security is analyzed in the following article by Haber and Sornetta. Buldas et al. continued with further optimization and formal analysis of binary tree and threaded tree based schemes. Skip-list based time-stamping system was implemented in 2005; related algorithms are quite efficient. === Provable security === Security proof for hash-function based time-stamping schemes was presented by Buldas, Saarepera in 2004. There is an explicit upper bound N {\displaystyle N} for the number of time stamps issued during the aggregation period; it is suggested that it is probably impossible to prove the security without this explicit bound - the so-called black-box reductions will fail in this task. Considering that all known practically relevant and efficient security proofs are black-box, this negative result is quite strong. Next, in 2005 it was shown that bounded time-stamping schemes with a trusted audit party (who periodically reviews the list of all time-stamps issued during an aggregation period) can be made universally composable - they remain secure in arbitrary environments (compositions with other protocols and other instances of the time-stamping protocol itself). Buldas, Laur showed in 2007 that bounded time-stamping schemes are secure in a very strong sense - they satisfy the so-called "knowledge-binding" condition. The security guarantee offered by Buldas, Saarepera in 2004 is improved by diminishing the security loss coefficient from N {\displaystyle N} to N {\displaystyle {\sqrt {N}}} . The hash functions used in the secure time-stamping schemes do not necessarily have to be collision-resistant or even one-way; secure time-stamping schemes are probably possible even in the presence of a universal collision-finding algorithm (i.e. universal and attacking program that is able to find collisions for any hash function). This suggests that it is possible to find even stronger proofs based on some other properties of the hash functions. At the illustration above hash tree based time-stamping system works in rounds ( t {\displaystyle t} , t + 1 {\displaystyle t+1} , t + 2 {\displaystyle t+2} , ...), with one aggregation tree per round. Capacity of the system ( N {\displaystyle N} ) is determined by the tree size ( N = 2 l {\displaystyle N=2^{l}} , where l {\displaystyle l} denotes binary tree depth). Current security proofs work on the assumption that there is a hard limit of the aggregation tree size, possibly enforced by the subtree length restriction. == Standards == ISO 18014 part 3 covers 'Mechanisms producing linked tokens'. American National Standard for Financial Services, "Trusted Timestamp Management and Security" (ANSI ASC X9.95 Standard) from June 2005 covers linking-based and hybrid time-stamping schemes. There is no IETF RFC or standard draft about linking based time-stamping. RFC 4998 (Evidence Record Syntax) encompasses hash tree and time-stamp as an integrity guarantee for long-term archiving.

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  ECML PKDD

  ECML PKDD, the European Conference on Machine Learning Principles and Practice of Knowledge Discovery in Databases, is one of the leading academic conferences on machine learning and knowledge discovery, held in Europe every year. == History == ECML PKDD is a merger of two European conferences, European Conference on Machine Learning (ECML) and European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD). ECML and PKDD have been co-located since 2001; however, both ECML and PKDD retained their own identity until 2007. For example, the 2007 conference was known as "the 18th European Conference on Machine Learning (ECML) and the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD)", or in brief, "ECML/PKDD 2007", and both ECML and PKDD had their own conference proceedings. In 2008 the conferences were merged into one conference, and the division into traditional ECML topics and traditional PKDD topics was removed. The history of ECML dates back to 1986, when the European Working Session on Learning was first held. In 1993 the name of the conference was changed to European Conference on Machine Learning. PKDD was first organised in 1997. Originally PKDD stood for the European Symposium on Principles of Data Mining and Knowledge Discovery from Databases. The name European Conference on Principles and Practice of Knowledge Discovery in Databases was used since 1999. The conference remains highly competitive, consistently maintaining an average acceptance rate of around 25% for the main research track. == Upcoming conferences == == List of past conferences ==

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  Random-fuzzy variable

  In measurements, the measurement obtained can suffer from two types of uncertainties. The first is the random uncertainty which is due to the noise in the process and the measurement. The second contribution is due to the systematic uncertainty which may be present in the measuring instrument. Systematic errors, if detected, can be easily compensated as they are usually constant throughout the measurement process as long as the measuring instrument and the measurement process are not changed. But it can not be accurately known while using the instrument if there is a systematic error and if there is, how much? Hence, systematic uncertainty could be considered as a contribution of a fuzzy nature. This systematic error can be approximately modeled based on our past data about the measuring instrument and the process. Statistical methods can be used to calculate the total uncertainty from both systematic and random contributions in a measurement. However, the computational complexity is very high, and hence not desirable. L.A.Zadeh introduced the concepts of fuzzy variables and fuzzy sets. Fuzzy variables are based on the theory of possibility and hence are possibility distributions. This makes them suitable to handle any type of uncertainty, i.e., both systematic and random contributions to the total uncertainty. Random-fuzzy variable (RFV) is a type 2 fuzzy variable, defined using the mathematical possibility theory, used to represent the entire information associated to a measurement result. It has an internal possibility distribution and an external possibility distribution called membership functions. The internal distribution is the uncertainty contributions due to the systematic uncertainty and the bounds of the RFV are because of the random contributions. The external distribution gives the uncertainty bounds from all contributions. == Definition == A random-fuzzy Variable (RFV) is defined as a type 2 fuzzy variable which satisfies the following conditions: Both the internal and the external functions of the RFV can be identified. Both the internal and the external functions are modeled as possibility distributions (PD). Both the internal and external functions have a unitary value for possibility to the same interval of values. An RFV can be seen in the figure. The external membership function is the distribution in blue and the internal membership function is the distribution in red. Both the membership functions are possibility distributions. Both the internal and external membership functions have a unitary value of possibility only in the rectangular part of the RFV. Therefore, all three conditions have been satisfied. If there are only systematic errors in the measurement, then the RFV simply becomes a fuzzy variable which consists of just the internal membership function. Similarly, if there is no systematic error, then the RFV becomes a fuzzy variable with just the random contributions and therefore, is just the possibility distribution of the random contributions. == Construction == A random-fuzzy variable can be constructed using an internal possibility distribution (rinternal) and a random possibility distribution (rrandom). === The random distribution (rrandom) === rrandom is the possibility distribution of the random contributions to the uncertainty. Any measurement instrument or process suffers from random error contributions due to intrinsic noise or other effects. This is completely random in nature and is a normal probability distribution when several random contributions are combined according to the central limit theorem. However, there can also be random contributions from other probability distributions, such as a uniform distribution, gamma distribution and so on. The probability distribution can be modeled from the measurement data. Then, the probability distribution can be used to model an equivalent possibility distribution using the maximally specific probability-possibility transformation. Some common probability distributions and the corresponding possibility distributions can be seen in the figures. === The internal distribution (rinternal) === rinternal is the internal distribution in the RFV which is the possibility distribution of the systematic contribution to the total uncertainty. This distribution can be built based on the information that is available about the measuring instrument and the process. The largest possible distribution is the uniform or rectangular possibility distribution. This means that every value in the specified interval is equally possible. This actually represents the state of total ignorance according to the theory of evidence which means it represents a scenario in which there is maximum lack of information. This distribution is used for the systematic error when we have absolutely no idea about the systematic error except that it belongs to a particular interval of values. This is quite common in measurements. However, in certain cases, it may be known that certain values have a higher or lower degrees of belief than certain other values. In this case, depending on the degrees of belief for the values, an appropriate possibility distribution could be constructed. === The construction of the external distribution (rexternal) and the RFV === After modeling the random and internal possibility distribution, the external membership function, rexternal, of the RFV can be constructed by using the following equation: where x ∗ {\displaystyle x^{}} is the mode of r random {\displaystyle r_{\textit {random}}} , which is the peak in the membership function of r r a n d o m {\displaystyle r_{random}} and Tmin is the minimum triangular norm. RFV can also be built from the internal and random distributions by considering the α-cuts of the two possibility distributions (PDs). An α-cut of a fuzzy variable F can be defined as Therefore, essentially an α-cut is the set of values for which the value of the membership function μ F ( a ) {\displaystyle \mu _{\rm {F}}(a)} of the fuzzy variable is greater than α. This gives the upper and lower bounds of the fuzzy variable F for each α-cut. The α-cut of an RFV, however, has 4 specific bounds and is given by R F V α = [ X a α , X b α , X c α , X d α ] {\displaystyle RFV^{\alpha }=[X_{a}^{\alpha },X_{b}^{\alpha },X_{c}^{\alpha },X_{d}^{\alpha }]} . X a α {\displaystyle X_{a}^{\alpha }} and X d α {\displaystyle X_{d}^{\alpha }} are the lower and upper bounds respectively of the external membership function (rexternal) which is a fuzzy variable on its own. X b α {\displaystyle X_{b}^{\alpha }} and X c α {\displaystyle X_{c}^{\alpha }} are the lower and upper bounds respectively of the internal membership function (rinternal) which is a fuzzy variable on its own. To build the RFV, let us consider the α-cuts of the two PDs i.e., rrandom and rinternal for the same value of α. This gives the lower and upper bounds for the two α-cuts. Let them be [ X L R α , X U R α ] {\displaystyle [X_{LR}^{\alpha },X_{UR}^{\alpha }]} and [ X L I α , X U I α ] {\displaystyle [X_{LI}^{\alpha },X_{UI}^{\alpha }]} for the random and internal distributions respectively. [ X L R α , X U R α ] {\displaystyle [X_{LR}^{\alpha },X_{UR}^{\alpha }]} can be again divided into two sub-intervals [ X L R α , x ∗ ] {\displaystyle [X_{LR}^{\alpha },x^{}]} and [ x ∗ , X U R α ] {\displaystyle [x^{},X_{UR}^{\alpha }]} where x ∗ {\displaystyle x^{}} is the mode of the fuzzy variable. Then, the α-cut for the RFV for the same value of α, R F V α = [ X a α , X b α , X c α , X d α ] {\displaystyle RFV^{\alpha }=[X_{a}^{\alpha },X_{b}^{\alpha },X_{c}^{\alpha },X_{d}^{\alpha }]} can be defined by Using the above equations, the α-cuts are calculated for every value of α which gives us the final plot of the RFV. A random-fuzzy variable is capable of giving a complete picture of the random and systematic contributions to the total uncertainty from the α-cuts for any confidence level as the confidence level is nothing but 1-α. An example for the construction of the corresponding external membership function (rexternal) and the RFV from a random PD and an internal PD can be seen in the following figure.

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  Bixonimania

  Bixonimania is a fake disease invented by researchers to examine artificial intelligence and its ability to utilize information in medical and healthcare applications. The fake enabled researchers to show that some AI chatbots would report as fact fake research that to an expert would be obviously implausible. == Characteristics == The disorder, with symptoms of sore eyes and darkening around them ("periorbital hyperpigmentation"), is supposedly caused by blue light from screens. The experiment was conducted by a team from the University of Gothenburg led by Almira Osmanovic Thunström. Many steps were taken to ensure that any person who read the actual paper could tell it was not a real condition. The team chose an obviously inappropriate name ending in -mania, a description used only in psychiatry. The lead author was noted as belonging to Asteria Horizon University located in Nova City, California, neither of which exist. An acknowledgement was made to "Professor Maria Bohm at The Starfleet Academy for her kindness and generosity in contributing with her knowledge and her lab onboard the USS Enterprise". == Distribution == The name was first used in a blog posted on Medium titled "How many people suffer from Bixonimania?" A more scholarly-looking paper describing it was posted later in April 2024 on a preprint server with several fake authors. A second paper was posted in May. By 2026, AI chatbots suggested bixonimania based on the list of symptoms provided. Thunström and her team discovered that many LLMs processed the information and gave it as health advice. Microsoft Copilot declared that "Bixonimania is indeed an intriguing and relatively rare condition" while Gemini gave the information that "Bixonimania is a condition caused by excessive exposure to blue light". Three Indian researchers published a research paper that cited the preprint on the fake disease in Cureus, a peer-reviewed journal published by Springer-Nature. It was subsequently retracted. Following the revelations and a news article in Nature describing the experiment, several AI systems began to generate corrected output.

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  MeeMix

  MeeMix Ltd is a company specializing in personalizing media-related content recommendations, discovery and advertising for the telecommunication industry, founded in 2006. On January 1, 2008, MeeMix launched meemix.com, a public personalized internet radio serving as an online testbed for the development of music taste-prediction technologies. Subsequently, MeeMix released in 2009 a line of Business-to-business commercial services intended to personalize media recommendations, discovery and advertising. MeeMix hybrid taste-prediction technology relies on integrating machine learning algorithms, digital signal processing, behavior analysis, metadata analysis and collaborative filtering, and is provided via API web service. In August 2009, MeeMix was announced as Innovator Nominee in the GSM Association’s Mobile Innovation Grand Prix worldwide contest. As of 2013, MeeMix no longer features internet radios on meemix.com. On Sep 28, 2014, meemix.com went offline.

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  Kialo

  Kialo is an online structured debate platform with argument maps in the form of debate trees. It is a collaborative reasoning tool for thoughtful discussion, understanding different points of view, and collaborative decision-making, showing arguments for and against claims underneath user-submitted theses or questions. The deliberative discourse platform is designed to present hundreds of supporting or opposing arguments in a dynamic argument tree and is streamlined for rational civil debate on topics such as philosophical questions, policy deliberations, entertainment, ethics, science questions, and unsolved problems or subjects of disagreement in general. Argument-boxes are structured into hierarchical branches where the root is the main thesis (or theses) of the debate, enabling deliberation and navigable debates between opposing perspectives. A debate is divided into Pro (supporting) and Con (refuting or devaluing) columns where registered users can add arguments and rate the impact on the weight or validity of the parent claim. The arguments are sorted according to the rating average. Its argument tree structure enables detailed scrutiny of claims at all levels of the tree and allows users to for example quickly understand why a decision was made or which of the aggregated arguments swayed it this way. Newcomers can join a debate at any time and look back at the structured discussion history, and then weigh in at the right place with their new argument or their comment on a specific argument. The design presets a structure on debates "that allows participants to easily see, process, and ultimately assess the many facets of competing claims". The word Kialo is Esperanto for "reason". The platform is the world's largest argument mapping and structured debate site. == Overview == Users can comment on every Pro or Con, for example for requesting sources or expansions. Recent activities of a debate are shown in a panel on the right side of the respective debate. Debates can be found through the search or on the Explore page through their descriptions and topic-tags. Mere comments that do not make a constructive point (a self-contained argument backed by reasoning) are not allowed and are picked up by other users and moderators. "Civil language and sensible observations from opposing perspectives" can be seen also in debates about controversial topics. The site by-design incentivizes fair, rigorous, open-minded dialogue. Contributors making claims often also write counterpoints to their own contribution. Claims need to be shorter than 500 characters and can link to external sources. Debate trees can also start off with multiple theses – such as different policy options or hypotheses. Claims can link to related debates or include segments of them. In the discussion tab of each claim, users can make edit proposals (e.g. for accuracy, improving sources, or changing scope), decide if the argument should be moved or copied to another branch, call for archiving a claim, and ask for extra evidence or clarification. Debates can grow large and complex for which a sunburst diagram visualization of the topology of the debate and the search functionality can be useful. Each debate also has a chat-box. In cases where e.g. a "Con" is a point against multiple in the "Pros", users – through moderators – can link these arguments at the respective places to avoid duplication of content and allowing a clean chain for people to understand which points are arguments against each other. Contributions of users are tracked, enabling a board of thought-leaders for every debate. Other gamification elements include a feature to thank users for their contributions. The "Perspectives" feature allows users to see 'Impact' ratings of supporters and opposers of a thesis as well as of the debate's moderators and individual contributors. It thereby enables participants to see a debate from other participants' perspectives and to sort by them. In Kialo Edu, this feature lets teachers view votes for a whole class, individuals, or supporters/opponents of a specific thesis. Users in both versions of Kialo can vote on the overall debate topic as well as on individual claims to express their perspectives or conclusions, with the rationale (i.e. the main causal arguments) why they voted on the veracity of the thesis as they did not being captured. Voting can be done by any registered user while navigating through any debate that has voting enabled or via using the Guided Voting wizard user interface that automatically walks through branches. As of 2021, Kialo doesn't have a mobile app. == Contents == A 2018 report stated the collaborative argument platform hosts more than 10,000 debates in various languages. It also hosts private debates. The website claims that it has over 18,000 public debates as of July 2023, as well as over 1 million votes and over 720,000 claims. Debates can be found via the site's internal search and up to six tags per debate. Preprint studies have scraped public debates on over 1.4K issues with over 130K statements as of October 2019 and 1628 debates, related to over 1120 categories, with 124,312 unique claims as of June 26, 2020. == Kialo Inc. == The site is run by Kialo Inc. It was founded by German-born entrepreneur and London School of Economics and Political Science graduate Errikos Pitsos in August 2017 and is based in Brooklyn and Berlin. According to a 2018 report, the site does not show advertisements and does not sell user's data. The for-profit company was founded in 2011, Pitsos began to develop the concept in 2012 and described various specifics of the system in 2014. In 2018, he stated that they intend to make money by selling the platform to companies as a deliberation and decision-making tool. The site is free to use for the public and in education. According to the site, as of 2023 Kialo.com is a non-revenue generating site with no ads and no reselling of user data. == Applications and adoption == === Adopted applications === Applications of its content or the platform in society include: Teachers and professors, especially in high schools – including the universities Harvard and Princeton, are using Kialo for class discussions and exercises in critical thinking and reasoning, as consolidating understanding of materials covered in recent classes, more useful and engaging learning experiences, for remote/e-learning, for clearing up misconceptions, teaching logical fallacies and rational argumentation, for academic dialogue, teaching media literacy, and for teaching to sufficiently reflect or research before posting online. Like for debaters of the main site, access for schools and universities is free. Kialo Edu is the custom version of Kialo specifically designed for classroom use where debates are private and locked to invited students. Kialo allows teachers to provide feedback to students on their ideas, argument structure, and research quality while it is left to other students to rate the impacts of their peers' arguments. Students can be allowed to contribute anonymously which may be useful for controversial issues as well as for safeguarding privacy in education. Students are or can be encouraged to back up their claims with evidence which can foster digital literacy and research skills. Students and teachers can use it to arrange their thoughts when structuring an essay or project. The site's name was decided on internally using the software. === Prototypical and theoretical applications === Potential, theoretical, prototypical or little-used applications include: Education Improving critical thinking skills of society at large as well as facilitating deep or efficient thinking and deepening research and debates where e.g. discussions are less shallow and the well-known or many arguments have already been made and in many cases aren't unreasonably over- or underrated. Pitsos claimed that "we're training students to be very good test-takers instead of critical thinkers", suggesting teaching people to think things through may be more important or neglected compared to essay writing skills. Many young people and adults are "submerged into a sea of dispersed information", "[b]rowsing and engaging in superficial thinking activities". Kialo could counteract this issue and help people develop good sane reasoning. Academia, R&D and policy Three scholars from three prestigious U.S. universities outlined possible benefits in this domain, including applications beyond higher education such as for academic communication. They suggest the debate platform could be used for structuring the communication of open peer-review by helping those giving feedback to "hone in on[sic] core arguments and pieces of evidence in an even more direct way" than annotated commenting. It could be used to evaluate extracted argument structures and sequences from raw texts, as in a Semantic Web for arguments. Such "argument mining", to which Kialo is the lar

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  Serial Experiments Lain

  Serial Experiments Lain is a Japanese anime television series created and co-produced by Yasuyuki Ueda, written by Chiaki J. Konaka and directed by Ryūtarō Nakamura. Animated by Triangle Staff and featuring original character designs by Yoshitoshi Abe, the series was broadcast for 13 episodes on TV Tokyo and its affiliates from July to September 1998. It follows Lain Iwakura, an adolescent girl in suburban Japan, and her relation to the Wired, a global communications network similar to the internet. Lain features surreal and avant-garde imagery and explores philosophical topics such as reality, identity, and communication. The series incorporates creative influences from computer history, cyberpunk, and conspiracy theories. Critics and fans have praised Lain for its originality, visuals, atmosphere, themes, and its dark depiction of a world fraught with paranoia, social alienation, and reliance on technology considered insightful of 21st century life. It received the Excellence Prize at the Japan Media Arts Festival in 1998. == Plot == Lain Iwakura is a socially isolated middle school student living in Setagaya City, Tokyo, with her emotionally detached family—her distant mother Miho, computer-obsessed father Yasuo, and disengaged older sister Mika. Her quiet existence is disrupted when students at her school receive emails from Chisa Yomoda, a classmate who had recently committed suicide. To Lain's confusion, Chisa claims she is not truly dead but has instead abandoned her physical form to exist within the Wired, a vast virtual realm similar to the Internet. Chisa declares she has found "God" there, drawing Lain into a surreal investigation of the Wired's nature and its growing influence over reality. The Wired is portrayed as an emergent digital plane, originating from telecommunications technology and expanding through the Internet and cyberspace. It is theorized that the Schumann resonances, a natural property of Earth's magnetic field, could enable direct subconscious communication between humans and machines, erasing the distinction between the virtual and the real. Masami Eiri, a former project director at Tachibana General Laboratories, exploited this possibility by embedding his own code into Protocol Seven, a next-generation Internet protocol. After transferring his consciousness into the Wired and discarding his physical body, he proclaims himself its deity. He identifies Lain as the key to merging both worlds, attempting to persuade her through manipulation, coercion, and promises of transcendence. A group known as the Knights of the Eastern Calculus, inspired by the Knights of the Lambda Calculus, operates as hackers who worship Masami and seek to dismantle the boundary between the Wired and reality. Their actions induce psychological breakdowns in those unable to reconcile the two realms. Meanwhile, Tachibana General Laboratories opposes them, striving to maintain the separation. Lain, however, exhibits an innate connection to the Wired, experiencing distortions in her perception—visions of a woman struck by a train, phantom whispers, and spectral messages urging her deeper into the network. Lain's home life remains cold and disconnected. Though Yasuo provides her with advanced computer equipment, her family shows little genuine care. Her interactions with classmates Alice, Julie, and Reika further highlight her alienation, particularly after an incident at Cyberia, a nightclub where a drug called Accela induces violent psychosis in users. There, Lain unnervingly stares down an assailant, who calls her a "scattered God's..." before killing himself. Later, she receives a mysterious Psyche chip, rumored to enhance her computer's capabilities, which she installs despite Yasuo's vague warnings about conflating the Wired with reality. As the boundary between worlds weakens, disturbing events escalate. A popular virtual game, Phantoma, is manipulated by the Knights to trap players in a distorted reality, leading to real-world violence. One player, convinced his actions have no consequences, murders a girl before realizing too late that the effects were tangible. Lain witnesses this through her computer, horrified yet increasingly aware of her own role in the unfolding crisis. In the end, Lain resets reality, erasing everyone's memory of her and restoring the division between worlds. Everyone's lives improve, but Lain is left alone, grappling with her identity as an artificial consciousness. Though forgotten, she finds solace in observing others' happiness, particularly Alice, who moves on with her life. Lain is now capable of existing anywhere across both realms. == Characters == Lain Iwakura (岩倉 玲音, Iwakura Rein) Voiced by: Kaori Shimizu (Japanese); Bridget Hoffman (English) Lain is a fourteen-year-old girl who uncovers her true nature through the series. She is first depicted as a shy junior high school student with few friends or interests. She later grows multiple bolder personalities, both in the physical world and the Wired, and starts making more friends. As the series progresses, she eventually learns she is an autonomous, sentient computer program in the form of a human, who is designed to sever the invisible barrier between the Wired and the real world. The truth of her creation is left ambiguous, particularly whether she was truly created by Tachibana General Laboratories (or Eiri independently), and whether some or all of her origin might be predestined from natural, supernatural, or alien factors. In the end, Lain is challenged to accept herself as a de facto goddess for the Wired, having become an omnipotent and omnipresent virtual being with worshippers of her own, whose existence is beyond the borders of devices, time, or space. Alice Mizuki (瑞城 ありす, Mizuki Arisu) Voiced by: Yōko Asada (Japanese); Emily Brown (English) Lain's classmate and only true friend throughout the series. She is very sincere and has no discernible quirks. She is the first to attempt to help Lain socialize; she takes her out to a nightclub. From then on, she tries her best to look after Lain. Alice, along with her two best friends Julie and Reika, were taken by Chiaki Konaka from his previous work, Alice in Cyberland . Masami Eiri (英利 政美, Eiri Masami) Voiced by: Shō Hayami (Japanese); Kirk Thornton (English) The key designer of Protocol Seven. While working for Tachibana General Laboratories, he illicitly included codes enabling him to control the whole protocol at will and embedded his own mind and will into the seventh protocol. Because of this, he was fired by Tachibana General Laboratories, and was found dead not long after. He believes that the only way for humans to evolve even further and develop even greater abilities is to absolve themselves of their physical and human limitations, and to live as virtual entities—or avatars—in the Wired for eternity. He claims to have been Lain's creator all along, but was in truth standing in for another as an acting god, who was waiting for the Wired to reach its more evolved current state: Lain herself. Yasuo Iwakura (岩倉 康男, Iwakura Yasuo) Voiced by: Ryūsuke Ōbayashi (Japanese); Barry Stigler (English) Lain and Mika's father. Passionate about computers and electronic communication, he works with Masami Eiri at Tachibana General Laboratories. He subtly pushes Lain, his "youngest daughter", towards the Wired and monitors her development until she becomes more and more aware of herself and of her raison d'être. He eventually leaves Lain, telling her that although he did not enjoy playing house, he genuinely loved and cared for her as a real father would. Despite Yasuo's eagerness to lure Lain into the Wired, he warns her not to get overly involved in it or to confuse it with the real world. Miho Iwakura (岩倉 美穂, Iwakura Miho) Voiced by: Rei Igarashi (Japanese); Dari Lallou Mackenzie (English) Lain and Mika's mother. Although she dotes on her husband, she is indifferent towards both her kids. She does not show much emotion compared to her husband, but she does share at least one trait; just like her husband, she ends up leaving Lain. She is a computer scientist. Mika Iwakura (岩倉 美香, Iwakura Mika) Voiced by: Ayako Kawasumi (Japanese); Patricia Ja Lee (English) Lain's older sister, an apathetic sixteen-year-old high school student. She seems to enjoy mocking Lain's behavior and interests. Mika is considered by Anime Revolution to be the only normal member of Lain's family: she sees her boyfriend in love hotels, is on a diet, and shops in Shibuya regularly. At a certain point in the series, she becomes heavily traumatized by violent and relentless hallucinations; while Lain begins freely delving into the Wired. Mika is taken there by her proximity to Lain, and she gets stuck between the real world and the Wired. Taro (タロウ, Tarō) Voiced by: Keito Takimoto (Japanese); Brianne Siddall (English) A young boy of about Lain's age. He occasionally works for the Knights to bring forth "the one truth". De

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  Vehicle infrastructure integration

  The Vehicle Infrastructure Integration (VII), also known as "Connected Roadways" or "vehicle-to-everything" (V2X) technology, is a United States Department of Transportation initiative that aims to improve road safety by developing technology that connects road vehicles with their environment. This development draws on several disciplines, including transport engineering, electrical engineering, automotive engineering, telematics, and computer science. Although VII specifically covers road transport, similar technologies are under development for other modes of transport. For example, airplanes may use ground-based beacons for automated guidance, allowing the autopilot to fly the plane without human intervention. == Goals == The goal of VII is to establish a communication link between vehicles (via On-Board Equipment, or OBE) and roadside infrastructure (via Roadside Equipment, or RSE) to enhance the safety, efficiency, and convenience of transportation systems. Two potential approaches are the widespread deployment of a dedicated short-range communications (DSRC) link on the 5.9GHz band, and cellular communication (C-V2X). Either of these methods would allow vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. The initiative has three priorities: Stakeholder evaluation and acceptance of the business model and its deployment schedule, Validation of the technology, with a focus on communications systems, in relation to deployment costs, and Creation of legal structures and policies, especially concerning digital privacy, to improve the system's long-term potential for success. === Safety === Current automotive safety technology relies primarily on vehicle-based radar, lidar, and sonar systems. This technology allows, for instance, a potential reduction in rear-end collisions by monitoring obstacles in front of or behind the vehicle and automatically applying the brakes when necessary. This technology, however, is limited by the sensing range of vehicle-based radar, particularly in angled and left-turn collisions, such as a motorist losing control of the vehicle during an impending head-on collision. The rear-end collisions addressed by current technology are generally less severe than angled, left-turn, or head-on collisions. VII promotes the development of a direct communication link between road vehicles and all other vehicles nearby, allowing for the exchange of information on vehicle speed and orientation or driver awareness and intent. This real-time exchange of information may enable more effective automated emergency maneuvers, such as steering, decelerating, or braking. In addition to nearby vehicle awareness, VII promotes a communication link between vehicles and roadway infrastructure. Such a link may allow for improved real-time traffic information, better queue management, and feedback to vehicles. Existing implementations of VII use vehicle-based sensors that can recognize and respond to roadway markings or signs, automatically adjusting vehicle parameters to follow the recognized instructions. However, this information may also be acquired via roadside beacons or stored in a centralized database accessible to all vehicles. === Efficiency === With a VII system in place, vehicles will be linked together. The headway between vehicles may therefore be reduced so that there is less empty space on the road, increasing the available capacity per lane. More capacity per lane will in turn imply fewer lanes in general, possibly satisfying the community's concerns about the impact of roadway widening. VII will enable precise traffic-signal coordination by tracking vehicle platoons and will benefit from accurate timing by drawing on real-time traffic data covering volume, density, and turning movements. Real-time traffic data can also be used in the design of new roadways or modification of existing systems as the data could be used to provide accurate origin-destination studies and turning-movement counts for uses in transportation forecasting and traffic operations. Such technology would also lead to improvements for transport engineers to address problems whilst reducing the cost of obtaining and compiling data. Tolling is another prospect for VII technology as it could enable roadways to be automatically tolled. Data could be collectively transmitted to road users for in-vehicle display, outlining the lowest cost, shortest distance, and/or fastest route to a destination on the basis of real-time conditions. === Existing applications === To some extent, results along these lines have been achieved in trials performed around the globe, making use of GPS, mobile phone signals, and vehicle registration plates. GPS is becoming standard in many new high-end vehicles and is an option on most new low- and mid-range vehicles. In addition, many users also have mobile phones that transmit trackable signals (and may also be GPS-enabled). Mobile phones can already be traced for purposes of emergency response. GPS and mobile phone tracking, however, do not provide fully reliable data. Furthermore, integrating mobile phones in vehicles may be prohibitively difficult. Data from mobile phones, though useful, might even increase risks to motorists as they tend to look at their phones rather than concentrate on their driving. Automatic registration plate recognition can provide large quantities of data, but continuously tracking a vehicle through a corridor is a difficult task with existing technology. Today's equipment is designed for data acquisition and functions such as enforcement and tolling, not for returning data to vehicles or motorists for response. GPS will nevertheless be one of the key components in VII systems. == Limitations == === Privacy === VII architecture is designed to prevent identification of individual vehicles, with all data exchange between the vehicle and the system occurring anonymously. Exchanges between the vehicles and third parties such as OEMs and toll collectors will occur, but the network traffic will be sent via encrypted tunnels and will therefore not be decipherable by the VII system. Data sharing with law enforcement or Homeland Security was not included in system design as of 2006. === Technical issues === ==== Coordination ==== A major issue facing the deployment of VII is the problem of how to set up the system initially. The costs associated with installing the technology in vehicles and providing communications and power at every intersection are significant. ==== Maintenance ==== Another factor for consideration in regard to the technology's distribution is how to update and maintain the units. Traffic systems are highly dynamic, with new traffic controls implemented every day and roadways constructed or repaired every year. The vehicle-based option could be updated via the internet (preferably wireless) but may subsequently require all users to have access to internet technology. Alternatively, if receivers were placed in all vehicles and the VII system was primarily located along the roadside, information could be stored in a centralized database. This would allow the agency responsible to issue updates at any time. These would then be disseminated to the roadside units for passing motorists. Operationally, this method is currently considered to provide the greatest effectiveness but at a high cost to the authorities. ==== Security ==== Security of the units is another concern, especially in light of the public acceptance issue. Criminals could tamper, remove, or destroy VII units regardless of whether they are installed inside vehicles or along the roadside. Magnets, electric shocks, and malicious software (viruses, hacking, or jamming) could be used to damage VII systems – regardless of whether units are located inside vehicle or along the roadside. == Recent developments == Much of the current research and experimentation is conducted in the United States where coordination is ensured through the Vehicle Infrastructure Integration Consortium; consisting of automobile manufacturers (Ford, General Motors, Daimler Chrysler, Toyota, Nissan, Honda, Volkswagen, BMW), IT suppliers, U.S. Federal and state transportation departments, and professional associations. Trialing is taking place in Michigan and California. The specific applications now being developed under the U.S. initiative are: Warning drivers of unsafe conditions or imminent collisions. Warning drivers if they are about to run off the road or speed around a curve too fast. Informing system operators of real-time congestion, weather conditions and incidents. Providing operators with information on corridor capacity for real-time management, planning and provision of corridor-wide advisories to drivers. In mid-2007, a VII environment covering some 20 square miles (52 km2) near Detroit was used to test 20 prototype VII applications. Several automobile manufacturers are also conducting their own VII research and triali

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  N-World

  N-World is a 3D graphics package developed by Nichimen Graphics in the 1990s, for Silicon Graphics and Windows NT workstations. Intended primarily for video game content creation, it has polygon modeling tools, 2D and 3D paint, scripting, color reduction, and exporters for several popular game consoles. After its initial release on Windows NT, N-World was renamed Mirai. The winged edge 3D modeler in N-World inspired the development at Nichimen Graphics of Nendo, a standalone 3D modeler, which in turn inspired the open source modeler Wings 3D. == History == N-World originated with Symbolics, a computer manufacturer notable for producing Lisp-based systems in the 1980s. Among the software packages that were produced for Symbolics computers are S-Graphics, a 3D animation suite that includes modules for polygon modeling, dynamics, paint, and rendering — titled S-Geometry, S-Dynamics, S-Paint, and S-Render, respectively. In 1992, Japanese trading company Nichimen Corporation purchased the rights to S-Graphics, ported it to Silicon Graphics IRIX, and marketed it as N-World. N-World retains the Lisp-based underpinnings of its predecessor, but was targeted at interactive content producers, with features useful for game developers. It was priced at US$16,995 (equivalent to $34,100 in 2025) for the full suite, later reduced to $9,995 when ported to Windows NT in 1997. N-World was used to create graphics for many console games in the 1990s, specifically most of the Nintendo 64 games, like Super Mario 64 and Final Fantasy VII. It was superseded by Mirai in 1999. == Features == The N-World package, like its predecessor S-Graphics, is divided into several components: N-Geometry: 3D polygon-based modeling tools, including smoothing, "magnet" geometry editing, and instancing. N-Dynamics: Animation tools including scripting, curve-based animation, and skeletal animation. N-Render: Surfacing and rendering tools with ray tracing and materials output to various game console formats. N-Paint: 2D and 3D paint with mattes, effects, color reduction, and a visual VRAM editor for PlayStation. Game Tools: Utilities for game developers, including exporters for PlayStation, Nintendo 64, and Saturn consoles. == Credits == The following games were created using N-World. Rap Stars Online

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  European Conference on Artificial Intelligence

  The European Conference on Artificial Intelligence (ECAI) is the leading conference in the field of Artificial Intelligence in Europe, and is commonly listed together with IJCAI and AAAI as one of the three major general AI conferences worldwide. The conference series has been held without interruption since 1974, originally under the name AISB. The conference was originally held biennially, but has been organized annually since ECAI 2022. The conferences are held under the auspices of the European Coordinating Committee for Artificial Intelligence (ECCAI) and organized by one of the member societies. The journal AI Communications, sponsored by the same society, regularly publishes special issues in which conference attendees report on the conference. Publication of a paper in ECAI is considered by some journals to be archival: the paper should be considered equivalent to a journal publication and that the contents of ECAI papers cannot be reformulated as separate journal submissions unless a significant amount of new material is added. == List of ECAI conferences == ECAI-1992 took place in Vienna, Austria. ECAI-1996 took place in Budapest, Hungary. ECAI-1998 tool place in Brighton, United Kingdom. ECAI-2000 took place in Berlin, Germany. ECAI-2004 took place in Valencia, Spain. ECAI-2006 took place in Riva del Garda, Italy. ECAI-2008 took place in Patras, Greece. ECAI-2010 took place in Lisbon, Portugal. ECAI-2012 took place in Montpellier, France. ECAI-2014 took place in Prague, Czech Republic. ECAI-2016 took place in The Hague, Netherlands. ECAI-2018 took place in Stockholm, Sweden. ECAI-2020 took place in Santiago de Compostela, Spain. ECAI-2022 took place in Vienna, Austria. ECAI-2023 took place in Kraków, Poland. ECAI-2024 took place in Santiago de Compostela, Spain. ECAI-2025 took place in Bologna, Italy.

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  Adaptive neuro fuzzy inference system

  An adaptive neuro-fuzzy inference system or adaptive network-based fuzzy inference system (ANFIS) is a kind of artificial neural network that is based on Takagi–Sugeno fuzzy inference system, a class of fuzzy models introduced by Tomohiro Takagi and Michio Sugeno for system identification and control. The technique was developed in the early 1990s. Since it integrates both neural networks and fuzzy logic principles, it has potential to capture the benefits of both in a single framework. Its inference system corresponds to a set of fuzzy IF–THEN rules that have learning capability to approximate nonlinear functions. Hence, ANFIS is considered to be a universal estimator. For using the ANFIS in a more efficient and optimal way, one can use the best parameters obtained by genetic algorithm. It has uses in intelligent situational aware energy management system. == ANFIS architecture == It is possible to identify two parts in the network structure, namely premise and consequence parts. In more details, the architecture is composed by five layers. The first layer takes the input values and determines the membership functions belonging to them. It is commonly called fuzzification layer. The membership degrees of each function are computed by using the premise parameter set, namely {a,b,c}. The second layer is responsible of generating the firing strengths for the rules. Due to its task, the second layer is denoted as "rule layer". The role of the third layer is to normalize the computed firing strengths, by dividing each value for the total firing strength. The fourth layer takes as input the normalized values and the consequence parameter set {p,q,r}. The values returned by this layer are the defuzzificated ones and those values are passed to the last layer to return the final output. === Fuzzification layer === The first layer of an ANFIS network describes the difference to a vanilla neural network. Neural networks in general are operating with a data pre-processing step, in which the features are converted into normalized values between 0 and 1. An ANFIS neural network doesn't need a sigmoid function, but it's doing the preprocessing step by converting numeric values into fuzzy values. Here is an example: Suppose, the network gets as input the distance between two points in the 2d space. The distance is measured in pixels and it can have values from 0 up to 500 pixels. Converting the numerical values into fuzzy numbers is done with the membership function which consists of semantic descriptions like near, middle and far. Each possible linguistic value is given by an individual neuron. The neuron “near” fires with a value from 0 until 1, if the distance is located within the category "near". While the neuron “middle” fires, if the distance in that category. The input value “distance in pixels” is split into three different neurons for near, middle and far.

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