AI Chat Free Online

AI Chat Free Online — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Hugging Face

    Hugging Face

    Hugging Face, Inc., is an American company based in New York City that develops computation tools for building applications using machine learning. Its transformers library built for natural language processing applications and its platform allow users to share machine learning models and datasets and showcase their work. == History == === Founding === The company was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf in New York City, originally as a company that developed a chatbot app targeted at teenagers. The company was named after the U+1F917 🤗 HUGGING FACE emoji. After open sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning. === AI boom === On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters. In February 2023, the company announced partnership with Amazon Web Services (AWS) which would allow Hugging Face's products to be available to AWS customers to use them as the building blocks for their custom applications. The company also said the next generation of BLOOM will be run on Trainium, a proprietary machine learning chip created by AWS. In June 2024, the company announced, along with Meta and Scaleway, their launch of a new AI accelerator program for European startups. The initiative aimed to help startups integrate open foundation models into their products, accelerating the EU AI ecosystem. The program, based at STATION F in Paris, ran from September 2024 to February 2025. Selected startups received mentoring, and access to AI models and tools and Scaleway's computing power. On September 23, 2024, to further the International Decade of Indigenous Languages, Hugging Face teamed up with Meta and UNESCO to launch a new online language translator. It was built on Meta's No Language Left Behind open-source AI model, enabling free text translation across 200 languages, including many low-resource languages. In April 2025, Hugging Face announced that they acquired a humanoid robotics startup, Pollen Robotics, based in France and founded by Matthieu Lapeyre and Pierre Rouanet in 2016. In an X tweet, Delangue shared his vision to "make Artificial Intelligence robotics Open Source". === Cyberattacks === In early 2026, hackers hijacked the Hugging Face platform to launch Android-targeted attacks involving "powerful malware" which could completely take over a compromised target.

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  • List of cryptosystems

    List of cryptosystems

    A cryptosystem is a set of cryptographic algorithms that map ciphertexts and plaintexts to each other. == Private-key cryptosystems == Private-key cryptosystems use the same key for encryption and decryption. Caesar cipher Substitution cipher Enigma machine Data Encryption Standard Twofish Serpent Camellia Salsa20 ChaCha20 Blowfish CAST5 Kuznyechik RC4 3DES Skipjack Safer IDEA Advanced Encryption Standard, also known as AES and Rijndael. == Public-key cryptosystems == Public-key cryptosystems use a public key for encryption and a private key for decryption. Diffie–Hellman key exchange RSA encryption Rabin cryptosystem Schnorr signature ElGamal encryption Elliptic-curve cryptography Lattice-based cryptography McEliece cryptosystem Multivariate cryptography Isogeny-based cryptography

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  • Communications security

    Communications security

    Communications security is the discipline of preventing unauthorized interceptors from accessing telecommunications in an intelligible form, while still delivering content to the intended recipients. In the North Atlantic Treaty Organization culture, including United States Department of Defense culture, it is often referred to by the abbreviation COMSEC. The field includes cryptographic security, transmission security, emissions security and physical security of COMSEC equipment and associated keying material. COMSEC is used to protect both classified and unclassified traffic on military communications networks, including voice, video, and data. It is used for both analog and digital applications, and both wired and wireless links. Voice over secure internet protocol VOSIP has become the de facto standard for securing voice communication, replacing the need for Secure Terminal Equipment (STE) in much of NATO, including the U.S.A. USCENTCOM moved entirely to VOSIP in 2008. == Specialties == Cryptographic security: The component of communications security that results from the provision of technically sound cryptosystems and their proper use. This includes ensuring message confidentiality and authenticity. Emission security (EMSEC): The protection resulting from all measures taken to deny unauthorized persons information of value that might be derived from communications systems and cryptographic equipment intercepts and the interception and analysis of compromising emanations from cryptographic equipment, information systems, and telecommunications systems. Transmission security (TRANSEC): The component of communications security that results from the application of measures designed to protect transmissions from interception and exploitation by means other than cryptanalysis (e.g. frequency hopping and spread spectrum). Physical security: The component of communications security that results from all physical measures necessary to safeguard classified equipment, material, and documents from access thereto or observation thereof by unauthorized persons. == Related terms == ACES – Automated Communications Engineering Software AEK – Algorithmic Encryption Key AKMS – the Army Key Management System CCI – Controlled Cryptographic Item - equipment which contains COMSEC embedded devices CT3 – Common Tier 3 DTD – Data Transfer Device ICOM – Integrated COMSEC, e.g. a radio with built in encryption KEK – Key Encryption Key KG-30 – family of COMSEC equipment KOI-18 – Tape Reader General Purpose KPK – Key production key KYK-13 – Electronic Transfer Device KYX-15 – Electronic Transfer Device LCMS – Local COMSEC Management Software OTAR – Over the Air Rekeying OWK – Over the Wire Key SKL – Simple Key Loader SOI – Signal operating instructions STE – Secure Terminal Equipment (secure phone) STU-III – (obsolete secure phone, replaced by STE) TED – Trunk Encryption Device such as the WALBURN/KG family TEK – Traffic Encryption Key TPI – Two person integrity TSEC – Telecommunications Security (sometimes referred to in error transmission security or TRANSEC) Types of COMSEC equipment: Authentication equipment Crypto equipment: Any equipment that embodies cryptographic logic or performs one or more cryptographic functions (key generation, encryption, and authentication). Crypto-ancillary equipment: Equipment designed specifically to facilitate efficient or reliable operation of crypto-equipment, without performing cryptographic functions itself. Crypto-production equipment: Equipment used to produce or load keying material == DoD Electronic Key Management System == The Electronic Key Management System (EKMS) is a United States Department of Defense (DoD) key management, COMSEC material distribution, and logistics support system. The National Security Agency (NSA) established the EKMS program to supply electronic key to COMSEC devices in securely and timely manner, and to provide COMSEC managers with an automated system capable of ordering, generation, production, distribution, storage, security accounting, and access control. The Army's platform in the four-tiered EKMS, AKMS, automates frequency management and COMSEC management operations. It eliminates paper keying material, hardcopy Signal operating instructions (SOI) and saves the time and resources required for courier distribution. It has 4 components: LCMS provides automation for the detailed accounting required for every COMSEC account, and electronic key generation and distribution capability. ACES is the frequency management portion of AKMS. ACES has been designated by the Military Communications Electronics Board as the joint standard for use by all services in development of frequency management and crypto-net planning. CT3 with DTD software is in a fielded, ruggedized hand-held device that handles, views, stores, and loads SOI, Key, and electronic protection data. DTD provides an improved net-control device to automate crypto-net control operations for communications networks employing electronically keyed COMSEC equipment. SKL is a hand-held PDA that handles, views, stores, and loads SOI, Key, and electronic protection data. == Key Management Infrastructure (KMI) Program == KMI is intended to replace the legacy Electronic Key Management System to provide a means for securely ordering, generating, producing, distributing, managing, and auditing cryptographic products (e.g., asymmetric keys, symmetric keys, manual cryptographic systems, and cryptographic applications). This system is currently being fielded by Major Commands and variants will be required for non-DoD Agencies with a COMSEC Mission.

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  • Backdoor (computing)

    Backdoor (computing)

    A backdoor is a typically covert method of bypassing normal authentication or encryption in a computer, product, embedded device (e.g. a home router), or its embodiment (e.g. part of a cryptosystem, algorithm, chipset, or even a "homunculus computer"—a tiny computer-within-a-computer such as that found in Intel's AMT technology). Backdoors are most often used for securing remote access to a computer, or obtaining access to plaintext in cryptosystems. From there it may be used to gain access to privileged information like passwords, corrupt or delete data on hard drives, or transfer information within compromised networks. In the United States, the 1994 Communications Assistance for Law Enforcement Act forces internet providers to provide backdoors for government authorities. In 2024, the U.S. government realized that China had been tapping communications in the U.S. using that infrastructure for months, or perhaps longer; China recorded presidential candidate campaign office phone calls—including employees of the then-vice president of the nation, and of the candidates themselves. A backdoor may take the form of a hidden part of a program, a separate program (e.g. Back Orifice may subvert the system through a rootkit), code in the firmware of the hardware, or parts of an operating system such as Windows, for example, device drivers. Trojan horses can be used to create vulnerabilities in a device. A Trojan horse may appear to be an entirely legitimate program, but when executed, it triggers an activity that may install a backdoor. Although some are secretly installed, other backdoors are deliberate and widely known. These kinds of backdoors have "legitimate" uses such as providing the manufacturer with a way to restore user passwords. Many systems that store information within the cloud fail to create accurate security measures. If many systems are connected within the cloud, hackers can gain access to all other platforms through the most vulnerable system. Default passwords (or other default credentials) can function as backdoors if they are not changed by the user. Some debugging features can also act as backdoors if they are not removed in the release version. In 1993, the United States government attempted to deploy an encryption system, the Clipper chip, with an explicit backdoor for law enforcement and national security access. The chip was unsuccessful. Recent proposals to counter backdoors include creating a database of backdoors' triggers and then using neural networks to detect them. == Overview == The threat of backdoors surfaced when multiuser and networked operating systems became widely adopted. Petersen and Turn discussed computer subversion in a paper published in the proceedings of the 1967 AFIPS Conference. They noted a class of active infiltration attacks that use "trapdoor" entry points into the system to bypass security facilities and permit direct access to data. The use of the word trapdoor here clearly coincides with more recent definitions of a backdoor. However, since the advent of public key cryptography the term trapdoor has acquired a different meaning (see: Trapdoor function), and thus the term "backdoor" is now preferred, only after the term trapdoor went out of use. More generally, such security breaches were discussed at length in a RAND Corporation task force report published under DARPA sponsorship by J.P. Anderson and D.J. Edwards in 1970. While initially targeting the computer vision domain, backdoor attacks have expanded to encompass various other domains, including text, audio, ML-based computer-aided design, and ML-based wireless signal classification. Additionally, vulnerabilities in backdoors have been demonstrated in deep generative models, reinforcement learning (e.g., AI GO), and deep graph models. These broad-ranging potential risks have prompted concerns from national security agencies regarding their potentially disastrous consequences. A backdoor in a login system might take the form of a hard coded user and password combination which gives access to the system. An example of this sort of backdoor was used as a plot device in the 1983 film WarGames, in which the architect of the "WOPR" computer system had inserted a hardcoded password-less account which gave the user access to the system, and to undocumented parts of the system (in particular, a video game-like simulation mode and direct interaction with the artificial intelligence). Although the number of backdoors in systems using proprietary software (software whose source code is not publicly available) is not widely credited, they are nevertheless frequently exposed. Programmers have even succeeded in secretly installing large amounts of benign code as Easter eggs in programs, although such cases may involve official forbearance, if not actual permission. == Examples == === Worms === Many computer worms, such as Sobig and Mydoom, install a backdoor on the affected computer (generally a PC on broadband running Microsoft Windows and Microsoft Outlook). Such backdoors appear to be installed so that spammers can send junk e-mail from the infected machines. Others, such as the Sony/BMG rootkit, placed secretly on millions of music CDs through late 2005, are intended as DRM measures—and, in that case, as data-gathering agents, since both surreptitious programs they installed routinely contacted central servers. A sophisticated attempt to plant a backdoor in the Linux kernel, exposed in November 2003, added a small and subtle code change by subverting the revision control system. In this case, a two-line change appeared to check root access permissions of a caller to the sys_wait4 function, but because it used assignment = instead of equality checking ==, it actually granted permissions to the system. This difference is easily overlooked, and could even be interpreted as an accidental typographical error, rather than an intentional attack. In January 2014, a backdoor was discovered in certain Samsung Android products, like the Galaxy devices. The Samsung proprietary Android versions are fitted with a backdoor that provides remote access to the data stored on the device. In particular, the Samsung Android software that is in charge of handling the communications with the modem, using the Samsung IPC protocol, implements a class of requests known as remote file server (RFS) commands, that allows the backdoor operator to perform via modem remote I/O operations on the device hard disk or other storage. As the modem is running Samsung proprietary Android software, it is likely that it offers over-the-air remote control that could then be used to issue the RFS commands and thus to access the file system on the device. === Object code backdoors === Harder to detect backdoors involve modifying object code, rather than source code—object code is much harder to inspect, as it is designed to be machine-readable, not human-readable. These backdoors can be inserted either directly in the on-disk object code, or inserted at some point during compilation, assembly linking, or loading—in the latter case the backdoor never appears on disk, only in memory. Object code backdoors are difficult to detect by inspection of the object code, but are easily detected by simply checking for changes (differences), notably in length or in checksum, and in some cases can be detected or analyzed by disassembling the object code. Further, object code backdoors can be removed (assuming source code is available) by simply recompiling from source on a trusted system. Thus for such backdoors to avoid detection, all extant copies of a binary must be subverted, and any validation checksums must also be compromised, and source must be unavailable, to prevent recompilation. Alternatively, these other tools (length checks, diff, checksumming, disassemblers) can themselves be compromised to conceal the backdoor, for example detecting that the subverted binary is being checksummed and returning the expected value, not the actual value. To conceal these further subversions, the tools must also conceal the changes in themselves—for example, a subverted checksummer must also detect if it is checksumming itself (or other subverted tools) and return false values. This leads to extensive changes in the system and tools being needed to conceal a single change. As object code can be regenerated by recompiling (reassembling, relinking) the original source code, making a persistent object code backdoor (without modifying source code) requires subverting the compiler itself—so that when it detects that it is compiling the program under attack it inserts the backdoor—or alternatively the assembler, linker, or loader. As this requires subverting the compiler, this in turn can be fixed by recompiling the compiler, removing the backdoor insertion code. This defense can in turn be subverted by putting a source meta-backdoor in the compiler, so that when it detects that it is compiling itself

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  • Morphobank

    Morphobank

    MorphoBank is a web application for collaborative evolutionary research, specifically phylogenetic systematics or cladistics, on the phenotype. Historically, scientists conducting research on phylogenetic systematics have worked individually or in small groups employing traditional single-user software applications such as MacClade, Mesquite and Nexus Data Editor. As the hypotheses under study have grown more complex, large research teams have assembled to tackle the problem of discovering the Tree of Life for the estimated 4-100 million living species(Wilson 2003, pp. 77–80) and the many thousands more extinct species known from fossils. Because the phenotype is fundamentally visual, and as phenotype-based phylogenetic studies have continued to increase in size, it becomes important that observations be backed up by labeled images. Traditional desktop software applications currently in wide use do not provide robust support for team-based research or for image manipulation and storage. MorphoBank is a particularly important tool for the growing scientific field of phenomics. The development of MorphoBank, which began in 2001, has been funded by the National Science Foundation's Directorates for Geosciences, Biological Sciences and Computer and Information Science and Engineering. The significance of the scientific work on MorphoBank has been featured in the New York Times(here and here), among other publications. == Advantages == Teams of scientists studying phylogenetics to build the Tree of Life assemble large spreadsheets of observations about species (referred to as "matrices"). These teams require simultaneous access by each team member to a single and secure copy of the team's data during a scientific research project. This single copy of the data also changes with great frequency during the data collection phase. Images that can be very helpful for documenting homology statements must be displayed, labeled and shared as homology statements develop. This cannot be accomplished elegantly with a desktop software package alone because in a desktop environment each collaborator is working on his own private copy of project data. Changes made by one participant cannot automatically propagate to others, preventing collaborators from seeing each other's data edits until they are manually (and due to the effort involved, often only periodically) merged into a single "true" dataset. In all but the smallest and most disciplined of teams, file version control and the reconciliation of changes made on multiple copies of the data emerge quickly as significant drags on productivity. MorphoBank is an attempt to address these issues by leveraging the ubiquity of the web and modern web-based application techniques, including Ajax, web service layers, and rich web applications to provide a full-featured, net-accessible collaborative workspace for phylogenetic research. In particular, MorphoBank makes it easy to: Share all kinds of data with geographically separated team members, including taxonomy, character and specimen data, media (including images, video and audio), phylogenetic matrices (including data in the widely used NEXUS and TNT format) and other data such as documents and genetic sequences. Label high-resolution images using a web-based image annotation application. Collaboratively edit project data such as phylogenetic matrices using a built-in web-based matrix editor. The editor allows the linking of labeled images to individual cells of a matrix. Manage access to project data. Access ranges from full-access for team members to anonymous read-only access for potential reviewers. Publish completed project data on the web in support of a published paper with a persistent URL. Search The Encyclopedia of Life for taxon exemplar images. Store high resolution CT data Create ontologies for updating and populating matrix cells. These tasks are difficult or impossible in most existing software applications. == History == In 2001 the National Science Foundation (NSF) sponsored a workshop, at the American Museum of Natural History in New York to develop the outlines of a web-based system for a collaborative, media-rich research tool for morphological phylogenetics. An application prototype presented at the workshop was later refined with feedback from the workshop and became MorphoBank version 1.0. A grant from the US National Oceanic and Atmospheric Administration funded further revisions resulting in version 2.0, released in 2005. Current support from the NSF is funding current feature enhancements to MorphoBank. MorphoBank was hosted by Stony Brook University until late October 2021 and received back up support from the American Museum of Natural History. The current version is 3.0. Rationale for the software was described in the journal Cladistics. MorphoBank has also received support from NESCENT and the San Diego Supercomputer Center. Since 2018, MorphoBank has been supported in part by Phoenix Bioinformatics, a non-profit company founded to sustain databases for the basic sciences. A permanent move of MorphoBank from Stony Brook University to Phoenix Bioinformatics was complete in late October 2021. The San Diego Supercomputer Center has previously provided technical and hosting resources to the MorphoBank project. == Usage == MorphoBank hosts the products of peer-reviewed scientific research on phenotypes. An increasing volume of systematics data is "born digital" and MorphoBank is well suited to handle this type of material. On August 24, 2007, 62 active research projects were hosted by MorphoBank, as well as 6 completed (and published) projects. By 2017 over 2000 scientists and their students were registered content builders (users are not required to register and are even more numerous) and has more than 500 publicly available projects with approximately 80,000 images that are the products of scientific research. Over 1,500 active research projects are hosted by MorphoBank. The software has been used to assemble phylogenetic research on such groups as mammals, from bats to whales, bivalve molluscs, arachnids, fossil plants and living and extinct amniotes. It has also been used more broadly in evolutionary and paleontological research to host curated images associated with published research on lacewing insects geckos, raptor birds, dinosaurs, frogs and nematodes. MorphoBank is increasingly used in conjunction with the Paleobiology Database. Example published projects: Project 1097: Blank CE, 2013 Origin and early evolution of photosynthetic eukaryotes in freshwater environments – reinterpreting proterozoic paleobiology and biogeochemical processes in light of trait evolution Project 2520: Carvalho, T. P., R. E. Reis, and J. P. Friel, 2017 A new species of Hoplomyzon (Siluriformes: Aspredinidae) from Maracaibo Basin, Venezuela: osteological description using high-resolution Project 2651: Baron, M. G., Norman, D. B., Barrett, P. M., 2017 A new hypothesis of dinosaur relationships and early dinosaur evolution MorphoBank has been particularly important to the Assembling the Tree of Life initiative sponsored by the National Science Foundation. MorphoBank is well-suited to such projects because of its tools for merging taxonomic, character and matrix-based data, as well as its collaborative features. Highlights of this research include a collaborative matrix on mammal evolution published in Science that included over 4,000 phenomic characters scored for over 80 species, a matrix on extant baleen whales featuring nearly 600 images, and more.

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  • Social media marketing

    Social media marketing

    Social media marketing is the use of social media platforms and websites to promote a product or service. Although the terms e-marketing and digital marketing are still dominant in academia, social media marketing is becoming more popular for practitioners and researchers. Social media platforms such as Facebook, LinkedIn, Instagram, and Twitter, among others, have built-in data analytics tools that companies can use to track the progress, success, and engagement of social media marketing campaigns. Companies address a range of stakeholders through social media marketing, including current and potential customers, current and potential employees, journalists, bloggers, and the general public. On a strategic level, social media marketing includes the management of a marketing campaign, governance, setting the scope (e.g. more active or passive use) and the establishment of a firm's desired social media "culture" and "tone". Firms that use social media marketing can allow customers and Internet users to post user-generated content (e.g., online comments, product reviews, etc.), also known as "earned media", rather than use marketer-prepared advertising copy. == Purposes and tactics == Social media may be employed in marketing as a communications tool that makes companies accessible to those who are interested in their product and visible to those who are not familiar with their products. It is used by companies to create buzz, learn from customers, and target them. Of the top 10 factors that correlate with a strong Google organic search, seven are social media-dependent. This means that if brands with little to no social media presence tend to show up less on Google searches. While platforms such as Twitter, Facebook and—in the past—Google+ have a larger number of monthly users, the visual media-sharing-based mobile platforms garner a higher interaction rate in comparison, and have registered the fastest growth, and have changed the ways in which consumers engage with brand content. Instagram has an interaction rate of 1.46% with an average of 130 million users monthly as opposed to Twitter, which has a .03% interaction rate with an average of 210 million monthly users. Unlike traditional media that are often cost-prohibitive to many companies, a social media strategy does not require significant financial investment. To this end, companies make use of platforms such as Facebook, Twitter, YouTube, TikTok and Instagram to reach audiences much wider than through traditional print, television, or radio advertisements alone at a fraction of the cost, as most social networking sites can be used at little or no cost (however, some websites charge companies for premium services). This has changed the ways that companies approach and interact with customers, as a substantial percentage of consumer interactions are now being carried out over online platforms with much higher visibility. Customers can post reviews of products and services, rate customer service, and ask questions or voice concerns directly to companies through social media platforms. According to Measuring Success, over 80% of consumers use the web to research products and services. Thus social media marketing is also used by businesses in order to build relationships of trust with consumers. To this aim, companies may hire personnel to specifically handle these social media interactions, who usually report under the title of online community managers. Handling these interactions in a satisfactory manner can result in an increase of consumer trust. To both this aim and to fix the public's perception of a company, three steps are taken in order to address consumer concerns: Identifying the extent of the social chatter Engaging the influencers to help Developing a proportional response == Strategies == === Passive approach === Social media can be a useful source of market information and a way to hear customers' perspectives. Blogs, content communities, and forums are platforms where individuals share their reviews and recommendations of brands, products, and services. Businesses are able to tap into and analyze customer voices and feedback generated in social media for marketing purposes. In this sense, social media is a relatively inexpensive source of market intelligence which can be used by marketers and managers to track and respond to consumer-identified problems and detect market opportunities. === Active approach === Social media can be used as a public relations tool, a direct marketing tool, and a communication channel to target very specific audiences, with social media influencers and social media personalities as effective customer engagement tools. This tactic is widely known as influencer marketing, which gives brands the opportunity to reach their target audience via a group of selected influencers advertising their product or service. Brands were projected to spend up to $15 billion on influencer marketing by 2022, per Business Insider Intelligence estimates, based on Mediakix data. The use of customer influencers, such as popular bloggers, can be an efficient and cost-effective method to launch new products or services. == Engagement == Engagement with the social web means that customers and stakeholders are active participants rather than passive spectators. An example of these are consumer advocacy groups and groups that criticize companies (e.g., lobby groups or advocacy organizations). The use of Social media in a business or political context allows people to express and share opinions about a company's products, services or business practices, or a government's actions. On social media, each participant becomes part of the marketing department (or a challenge to the marketing effort) as other customers read their comments or reviews. The effectiveness of social media marketing campaigns is dependent on the promotion of online engagement. With the advent of social media marketing, it has become increasingly important to gain customer interest in products and services, which can eventually be translated into buying behavior, or voting and donating behavior in a political context. New online marketing concepts of engagement and loyalty have emerged which aim to build customer participation and brand reputation. Engagement in social media for the purpose of a social media strategy is divided into two parts. The first is proactive, regular posting of new online content, which can be seen through digital photos, digital videos, text, and conversations. It is also represented through sharing of content and information from others via weblinks. The second part is reactive conversations, with social media users responding to those who reach out to others' social media profiles through comments or messages. == Campaigns == === Local businesses === Small businesses use social networking sites as a promotional technique. Businesses can follow individuals' social media usage in their local area and advertise specials and deals, which can be exclusive and in the form of "get a free drink with a copy of this tweet". This type of message encourages other locals to follow the business on their official websites in order to obtain the promotional deal. The business's brand visibility is enhanced in the process. Social networking sites are also used by small businesses to develop their own market research on new products and services. By encouraging their customers to give feedback on new product ideas, businesses can gain insights on whether or not a product may be accepted by their target market enough to merit full production. In addition, customers will feel the company has engaged them in the process of co-creation—the process in which the business uses customer feedback to create or modify a product or service to fill a need of the target market. Such feedback can be presented in various forms, such as surveys, contests, and polls. Social networking sites such as LinkedIn, also provide opportunities for small businesses to find candidates to fill staff positions. Review sites such as Yelp help small businesses build their reputation beyond brand visibility. Positive customer peer reviews help influence new prospects to purchase goods and services more than company advertising. == Benefits == Social Media Marketing allows companies to promote themselves to large, diverse audiences that could not be reached through traditional marketing such as phone and email-based advertising. Marketing on most social media platforms also comes at little to no cost, making it accessible to virtually any size business. Social Media Marketing accommodates personalized and direct marketing that targets specific demographics and markets. Companies can engage with customers directly, allowing them to obtain feedback and resolve issues almost immediately. Another advantage of social media marketing is that it's an ideal environment for a company to conduct market research. It can be used

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  • Cognos ReportNet

    Cognos ReportNet

    Cognos ReportNet (CRN) was a web-based software product for creating and managing ad hoc and custom-made reports. ReportNet was developed by the Ottawa-based company Cognos (formerly Cognos Incorporated), an IBM company. The web-based reporting tool was launched in September 2003. Since IBM's acquisition of Cognos, ReportNet has been renamed IBM Cognos ReportNet like all other Cognos products. ReportNet uses web services standards such as XML and Simple Object Access Protocol and also supports dynamic HTML and Java. ReportNet is compatible with multiple databases including Oracle, SAP, Teradata, Microsoft SQL server, DB2 and Sybase. The product provides interface in over 10 languages, has Web Services architecture to meet the needs of multi-national, diversified enterprises and helps reduce total cost of ownership. Multiple versions of Cognos ReportNet have since been released by the company. Cognos ReportNet was awarded the Software and Information Industry Association (SIIA) 2005 Codie awards for the "Best Business Intelligence or Knowledge Management Solution" category. CRN's capabilities have been further used in IBM Cognos 8 BI (2005), the latest reporting tool. CRN comes with its own software development kit (SDK). == Launch == Early adopters of Cognos ReportNet for their corporate reporting needs included Bear Stearns, BMW and Alfred Publishing. Around this same time of launch, Cognos competitor Business Objects released version 6.1 of its enterprise reporting tool. Cognos ReportNet has been successful since its launch, raising revenues in 2004 from licensing fees. == Controversy == Cognos rival Business Objects announced in 2005 that BusinessObjects XI significantly outperformed Cognos ReportNet in benchmark tests conducted by VeriTest, an independent software testing firm. The tests performed showed Cognos ReportNet performed poorly when processing styled reports, complex business reports and combination of both. The tests reported a massive 21 times higher report throughput for BusinessObjects XI than Cognos ReportNet at capacity loads. Cognos soon dismissed the claims by stating Business Objects dictated the environment and testing criteria and Cognos did not provide the software to participate in benchmark test. Cognos later performed their own test to demonstrate Cognos ReportNet capabilities. == Components == Cognos Report Studio – A Web-based product for creating complex professional looking reports. Cognos Query Studio - A Web-based product for creating ad-hoc reports. Cognos Framework Manager – A metadata modeling tool to create BI metadata for reporting and dashboard applications. Cognos Connection – Main portal used to access reports, schedule reports and perform administrator activities. == Versions == Cognos ReportNet 1.1 – Java EE-style professional web-based authoring tool. (base version) Cognos ReportNet IBM Special Edition – comes with an embedded version of IBM WebSphere as its application server and IBM DB2 as its data store. Cognos Linux – for Intel-based Linux platforms.

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  • Open Data-Link Interface

    Open Data-Link Interface

    The Open Data-Link Interface (ODI) is an application programming interface (API) for network interface controllers (NICs) developed by Apple and Novell. The API serves the same function as Microsoft and 3COM's Network Driver Interface Specification (NDIS). Originally, ODI was written for NetWare and Macintosh environments. Like NDIS, ODI provides rules that establish a vendor-neutral interface between the protocol stack and the adapter driver. It resides in Layer 2, the Data Link layer, of the OSI model. This interface also enables one or more network drivers to support one or more protocol stacks.

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  • Security information management

    Security information management

    Security information management (SIM) is an information security industry term for the collection of data such as log files into a central repository for trend analysis. == Overview == SIM products generally are software agents running on the computer systems that are monitored. The recorded log information is then sent to a centralized server that acts as a "security console". The console typically displays reports, charts, and graphs of that information, often in real time. Some software agents can incorporate local filters to reduce and manipulate the data that they send to the server, although typically from a forensic point of view you would collect all audit and accounting logs to ensure you can recreate a security incident. The security console is monitored by an administrator who reviews the consolidated information and takes action in response to any alerts issued. The data that is sent to the server to be correlated and analyzed are normalized by the software agents into a common form, usually XML. Those data are then aggregated in order to reduce their overall size. == Terminology == The terminology can easily be mistaken as a reference to the whole aspect of protecting one's infrastructure from any computer security breach. Due to historic reasons of terminology evolution; SIM refers to just the part of information security which consists of discovery of 'bad behavior' or policy violations by using data collection techniques. The term commonly used to represent an entire security infrastructure that protects an environment is commonly called information security management (InfoSec). Security information management is also referred to as log management and is different from SEM (security event management), but makes up a portion of a SIEM (security information and event management) solution. == Regulatory compliance == Security information management systems support compliance with regulatory frameworks that require centralized collection and analysis of security data. The Health Insurance Portability and Accountability Act (HIPAA) Security Rule requires covered entities to implement audit controls that record and examine activity in information systems containing electronic protected health information (45 CFR 164.312(b))."45 CFR § 164.312 - Technical safeguards". Legal Information Institute. Retrieved April 1, 2026. SIM platforms aggregate these audit records to support the required regular review of information system activity records (45 CFR 164.308(a)(1)(ii)(D)). The December 2024 HIPAA Security Rule NPRM proposed requiring regulated entities to deploy automated systems capable of monitoring and recording access to ePHI, including the ability to detect unauthorized access attempts in near real-time."HIPAA Security Rule To Strengthen the Cybersecurity of Electronic Protected Health Information". Federal Register. January 6, 2025. Retrieved April 1, 2026. The Payment Card Industry Data Security Standard (PCI DSS) similarly requires centralized log management and daily review of security events (Requirements 10.4 and 10.6)."PCI DSS v4.0" (PDF). PCI Security Standards Council. March 2022. Retrieved April 1, 2026. NIST Special Publication 800-53 addresses security information management through the AU (Audit and Accountability) control family, which specifies requirements for audit event generation, content, storage, and analysis."NIST SP 800-53 Rev. 5: Security and Privacy Controls". National Institute of Standards and Technology. September 2020. Retrieved April 1, 2026.

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  • Multiple encryption

    Multiple encryption

    Multiple encryption is the process of encrypting an already encrypted message one or more times, either using the same or a different algorithm. It is also known as cascade encryption, cascade ciphering, cipher stacking, multiple encryption, and superencipherment. Superencryption refers to the outer-level encryption of a multiple encryption. Some cryptographers, like Matthew Green of Johns Hopkins University, say multiple encryption addresses a problem that mostly doesn't exist: Modern ciphers rarely get broken... You’re far more likely to get hit by malware or an implementation bug than you are to suffer a catastrophic attack on Advanced Encryption Standard (AES). However, from the previous quote an argument for multiple encryption can be made, namely poor implementation. Using two different cryptomodules and keying processes from two different vendors requires both vendors' wares to be compromised for security to fail completely. == Independent keys == Picking any two ciphers, if the key used is the same for both, the second cipher could possibly undo the first cipher, partly or entirely. This is true of ciphers where the decryption process is exactly the same as the encryption process (a reciprocal cipher) – the second cipher would completely undo the first. If an attacker were to recover the key through cryptanalysis of the first encryption layer, the attacker could possibly decrypt all the remaining layers, assuming the same key is used for all layers. To prevent that risk, one can use keys that are statistically independent for each layer (e.g. independent RNGs). Ideally each key should have separate and different generation, sharing, and management processes. == Independent Initialization Vectors == For en/decryption processes that require sharing an Initialization Vector (IV) / nonce these are typically, openly shared or made known to the recipient (and everyone else). Its good security policy never to provide the same data in both plaintext and ciphertext when using the same key and IV. Therefore, its recommended (although at this moment without specific evidence) to use separate IVs for each layer of encryption. == Importance of the first layer == With the exception of the one-time pad, no cipher has been theoretically proven to be unbreakable. Furthermore, some recurring properties may be found in the ciphertexts generated by the first cipher. Since those ciphertexts are the plaintexts used by the second cipher, the second cipher may be rendered vulnerable to attacks based on known plaintext properties (see references below). This is the case when the first layer is a program P that always adds the same string S of characters at the beginning (or end) of all ciphertexts (commonly known as a magic number). When found in a file, the string S allows an operating system to know that the program P has to be launched in order to decrypt the file. This string should be removed before adding a second layer. To prevent this kind of attack, one can use the method provided by Bruce Schneier: Generate a random pad R of the same size as the plaintext. Encrypt R using the first cipher and key. XOR the plaintext with the pad, then encrypt the result using the second cipher and a different (!) key. Concatenate both ciphertexts in order to build the final ciphertext. A cryptanalyst must break both ciphers to get any information. This will, however, have the drawback of making the ciphertext twice as long as the original plaintext. Note, however, that a weak first cipher may merely make a second cipher that is vulnerable to a chosen plaintext attack also vulnerable to a known plaintext attack. However, a block cipher must not be vulnerable to a chosen plaintext attack to be considered secure. Therefore, the second cipher described above is not secure under that definition, either. Consequently, both ciphers still need to be broken. The attack illustrates why strong assumptions are made about secure block ciphers and ciphers that are even partially broken should never be used. == The Rule of Two == The Rule of Two is a data security principle from the NSA's Commercial Solutions for Classified Program (CSfC). It specifies two completely independent layers of cryptography to protect data. For example, data could be protected by both hardware encryption at its lowest level and software encryption at the application layer. It could mean using two FIPS-validated software cryptomodules from different vendors to en/decrypt data. The importance of vendor and/or model diversity between the layers of components centers around removing the possibility that the manufacturers or models will share a vulnerability. This way if one components is compromised there is still an entire layer of encryption protecting the information at rest or in transit. The CSfC Program offers solutions to achieve diversity in two ways. "The first is to implement each layer using components produced by different manufacturers. The second is to use components from the same manufacturer, where that manufacturer has provided NSA with sufficient evidence that the implementations of the two components are independent of one another." The principle is practiced in the NSA's secure mobile phone called Fishbowl. The phones use two layers of encryption protocols, IPsec and Secure Real-time Transport Protocol (SRTP), to protect voice communications. The Samsung Galaxy S9 Tactical Edition is also an approved CSfC Component.

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  • Data security

    Data security

    Data security or data protection is the process of securing digital information to protect it from online threats. Data security or protection means protecting digital data, such as those in a database, from destructive forces and from the unwanted actions of unauthorized users, such as a cyberattack or a data breach. Data security protects computer hardware, software, storage devices, and the data of user devices. Data security also protects the data of organizations, companies and administrative controls. Data security guarantees the protection of individual data, such as identity documents and bank data, and protects against unauthorized access, theft and loss of individual data. Data security also protects data breaches that occurs in companies and industries. Good security measures in industries reduce the probability of data breaches, and employees can rely on the company with their data and private information to be kept secured while companies can continue to maintain a stable reputation. The CIA Triad (Confidentiality, Integrity, and Availability) is what is used to practice what an information security is required to follow. Confidentiality, protects information from being accessed by unauthorized persons. Integrity, makes sure data is trustworthy; and Availability, meaning that data can be accessed by approved users when it is needed; are three goals for data security. Non-repudiation in data security definition, is a device/service that shows where the data originated from and the proof of integrity. == Technologies == === Disk encryption === Disk encryption refers to encryption technology that encrypts data on a hard disk drive. It takes data from a storage device and coverts it into an unreadable format. Disk encryption typically takes form in either software (see disk encryption software) or hardware (see disk encryption hardware) which can be used together. Disk encryption is often referred to as on-the-fly encryption (OTFE) or transparent encryption. Full disk encryption encrypts each individual sector of a disk volume. Files and user data are encrypted to hinder unauthorized users from accessing without a decryption key. A diversifier permits a plaintext of a specific disk sector to be encrypted into different ciphertexts, which does not require additional storage, such as an initialization vector (IV) or message authentication code (MAC). === Software versus hardware-based mechanisms for protecting data === Software-based security solutions encrypt the data to protect it from theft. However, a malicious program or a hacker could corrupt the data to make it unrecoverable, making the system unusable. Hardware-based security solutions prevent read and write access to data, which provides very strong protection against tampering and unauthorized access. Hardware-based security or assisted computer security offers an alternative to software-only computer security. Security tokens such as those using PKCS#11 or a mobile phone may be more secure due to the physical access required in order to be compromised. Access is enabled only when the token is connected and the correct PIN is entered (see two-factor authentication). However, dongles can be used by anyone who can gain physical access to it. Newer technologies in hardware-based security solve this problem by offering full proof of security for data. Working off hardware-based security: A hardware device allows a user to log in, log out and set different levels through manual actions. Many devices use biometric technology to prevent malicious users from logging in, logging out, and changing privilege levels. The current state of a user of the device is read by controllers in peripheral devices such as hard disks. Illegal access by a malicious user or a malicious program is interrupted based on the current state of a user by hard disk and DVD controllers making illegal access to data impossible. Hardware-based access control is more secure than the protection provided by the operating systems as operating systems are vulnerable to malicious attacks by viruses and hackers. The data on hard disks can be corrupted after malicious access is obtained. With hardware-based protection, the software cannot manipulate the user privilege levels. A hacker or a malicious program cannot gain access to secure data protected by hardware or perform unauthorized privileged operations. This assumption is broken only if the hardware itself is malicious or contains a backdoor. The hardware protects the operating system image and file system privileges from being tampered with. Therefore, a completely secure system can be created using a combination of hardware-based security and secure system administration policies. === Backups === Backup is the process of reproducing copies of essential data and storing in a separate, secured place. It is used to ensure data that is lost can be recovered from another source. Backups contains a minimum of one copy of the data that requires preservation. It is considered essential to keep a backup of any data in most industries and the process is recommended for any files of importance to a user. There are 3 types of backups; full backups, incremental backups, and differential backups. Full backups secure all data from a production system, such as a server, database, or other connected data source. It is impossible to lose all data in a full backup if a breach or corruption were to occur. Full backups require a significantly large amount of time to back up and may be time-consuming taking hours to days to complete. Incremental backups only secures changed data since last backup. While all backups are done in full backups, incremental backups only save data that is recently or frequently changed. Incremental backups require lower storage costs making it a prominent solution for growing datasets. === Data Privacy === Data privacy (or information privacy) is the right for individual's data to be secured to obstruct the use of unauthorized access. It gives individuals control over their data and how it can be shared to third parties. The U.S Privacy Protection Law (see Privacy laws of the United States) requires organizations to inform individuals of how their data is collected and when a data breach occurs. By implementing an encryption, it ensures that private data is unreadable to cybercriminals. === Data masking === Data masking of structured data is the process of obscuring (masking) specific data within a database table or cell to ensure that data security is maintained and sensitive information is not exposed to unauthorized personnel. This may include masking the data from users (for example so banking customer representatives can only see the last four digits of a customer's national identity number), developers (who need real production data to test new software releases but should not be able to see sensitive financial data), outsourcing vendors, etc. Data masking is a form of encryption, as it obscures data by modifying particular letters and numbers to keep data concealed and protected from potential hackers. The individual that has access to the code that decrypts the replaced characters are the only ones that can uncover the data. === Data erasure === Data erasure (or data deletion, data destruction) is a method of software-based overwriting that permanently clears all electronic data residing on a hard drive or other digital media to ensure that no sensitive data is lost when an asset is retired or reused. Article 17: Right to be Forgotten states that users have the right to permanently remove all of their private information from their old devices/services to give people more control over their data. Users are able to switch between devices efficiently. == Threats == === Malware === Malware (or malicious software) is designed to destroy, corrupt or gain unauthorized access to a computer for the purpose of stealing, or destroying data. Hackers who use malware typically utilize many types of malware, which includes computer virus, computer worms, ransomware, spyware and Trojan horse to create a vast system of disruption and cause easy data theft. One of the victims of the vast system of disruption includes healthcare workers, who are targeted by compromised systems by infections and then having their data attacked. === Phishing === Phishing is a type of scam that allows hackers to hoax people using psychological and social engineering (using human emotions such as their trust and fear) tactics into giving personal data through emails and messages, and install computer viruses if the individual were to click on a malicious link unknowingly. Attackers are able to create websites that are very similar to original websites, which makes it difficult to detect a fake website, causing individuals to fall for giving in information. Phishing attackers use human emotion to exploit them, such as making them feel fear, urgency, sympathy with the message

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  • Social recruiting

    Social recruiting

    Social recruiting (social hiring or social media recruitment) is recruiting candidates by using social platforms as talent databases or for advertising. Social recruiting uses social media profiles, blogs, and other Internet sites to find information on candidates. It also uses social media to advertise jobs either through HR vendors or through crowdsourcing where job seekers and others share job openings within their online social networks. Social recruiting's effectiveness and return on investment have been difficult to determine, since applicants do not usually apply through the social channels which first attracted them. In May 2013, Maximum Employment Marketing Group released the Social Recruitment Monitor, which ranks the reach, engagement, and interactivity of employers' social recruiting efforts around the world. == Social recruitment software == The social recruitment software market (a form of e-recruitment) is often included in the wider talent management software sector. Bersin & Associates valued the wider talent management market at over $2bn in 2007. Social recruitment increasingly sits at an intersection of a number of fast-moving areas including social networking, recruitment and now cloud computing. Additionally, mobile recruiting has become another hot topic, especially with the rise in tablet and smartphone usage. In 2012, there was a rise of tech companies using social recruiting applications to find and screen applicants. As more companies saw value in filling jobs by putting them on the social platforms where millions of people spend at least 37 minutes daily, there developed a much larger focus on social recruiting among the talent acquisition community. By mid-2013, many major enterprise companies such as Pepsi, Gap, AIG, and Oracle had begun effectively utilizing social recruiting software, making it clear that large corporations were open to automating or streamlining (and ultimately investing in) their social recruiting processes.

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  • Hexagonal sampling

    Hexagonal sampling

    A multidimensional signal is a function of M independent variables where M ≥ 2 {\displaystyle M\geq 2} . Real world signals, which are generally continuous time signals, have to be discretized (sampled) in order to ensure that digital systems can be used to process the signals. It is during this process of discretization where sampling comes into picture. Although there are many ways of obtaining a discrete representation of a continuous time signal, periodic sampling is by far the simplest scheme. Theoretically, sampling can be performed with respect to any set of points. But practically, sampling is carried out with respect to a set of points that have a certain algebraic structure. Such structures are called lattices. Mathematically, the process of sampling an N {\displaystyle N} -dimensional signal can be written as: w ( t ^ ) = w ( V . n ^ ) {\displaystyle w({\hat {t}})=w(V.{\hat {n}})} where t ^ {\displaystyle {\hat {t}}} is continuous domain M-dimensional vector (M-D) that is being sampled, n ^ {\displaystyle {\hat {n}}} is an M-dimensional integer vector corresponding to indices of a sample, and V is an N × N {\displaystyle N\times N} sampling matrix. == Motivation == Multidimensional sampling provides the opportunity to look at digital methods to process signals. Some of the advantages of processing signals in the digital domain include flexibility via programmable DSP operations, signal storage without the loss of fidelity, opportunity for encryption in communication, lower sensitivity to hardware tolerances. Thus, digital methods are simultaneously both powerful and flexible. In many applications, they act as less expensive alternatives to their analog counterparts. Sometimes, the algorithms implemented using digital hardware are so complex that they have no analog counterparts. Multidimensional digital signal processing deals with processing signals represented as multidimensional arrays such as 2-D sequences or sampled images.[1] Processing these signals in the digital domain permits the use of digital hardware where in signal processing operations are specified by algorithms. As real world signals are continuous time signals, multidimensional sampling plays a crucial role in discretizing the real world signals. The discrete time signals are in turn processed using digital hardware to extract information from the signal. == Preliminaries == === Region of Support === The region outside of which the samples of the signal take zero values is known as the Region of support (ROS). From the definition, it is clear that the region of support of a signal is not unique. === Fourier transform === The Fourier transform is a tool that allows us to simplify mathematical operations performed on the signal. The transform basically represents any signal as a weighted combination of sinusoids. The Fourier and the inverse Fourier transform of an M-dimensional signal can be defined as follows: X a ( Ω ^ ) = ∫ − ∞ + ∞ x a ( t ^ ) e − j Ω ^ T t ^ d t ^ {\displaystyle X_{a}({\hat {\Omega }})=\int _{-\infty }^{+\infty }\!x_{a}({\hat {t}})e^{-j{\hat {\Omega }}^{T}{\hat {t}}}d{\hat {t}}} x a ( t ^ ) = 1 2 π M ∫ − ∞ + ∞ X ( Ω ^ ) e ( j Ω ^ T t ^ ) d Ω ^ {\displaystyle x_{a}({\hat {t}})={\frac {1}{2\pi ^{M}}}\int _{-\infty }^{+\infty }\!X({\hat {\Omega }})e^{(j{\hat {\Omega }}^{T}{\hat {t}})}\,\mathrm {d} {\hat {\Omega }}} The cap symbol ^ indicates that the operation is performed on vectors. The Fourier transform of the sampled signal is observed to be a periodic extension of the continuous time Fourier transform of the signal. This is mathematically represented as: X ( ω ) = 1 | d e t ( V ) | ∑ k X a ( Ω ^ − U k ) {\displaystyle X(\omega )={\frac {1}{|det(V)|}}\sum _{k}\!X_{a}({\hat {\Omega }}-Uk)} where ω = V ~ Ω {\displaystyle \omega ={\tilde {V}}\Omega } and U = 2 π V ~ {\displaystyle U=2\pi {\tilde {V}}} is the periodicity matrix where ~ denotes matrix transposition. Thus sampling in the spatial domain results in periodicity in the Fourier domain. === Aliasing === A band limited signal may be periodically replicated in many ways. If the replication results in an overlap between replicated regions, the signal suffers from aliasing. Under such conditions, a continuous time signal cannot be perfectly recovered from its samples. Thus in order to ensure perfect recovery of the continuous signal, there must be zero overlap multidimensional sampling of the replicated regions in the transformed domain. As in the case of 1-dimensional signals, aliasing can be prevented if the continuous time signal is sampled at an adequate sufficiently high rate. === Sampling density === It is a measure of the number of samples per unit area. It is defined as: S . D = 1 | d e t ( V ) | = | d e t ( U ) | 4 π 2 {\displaystyle S.D={\frac {1}{|det(V)|}}={\frac {|det(U)|}{4\pi ^{2}}}} . The minimum number of samples per unit area required to completely recover the continuous time signal is termed as optimal sampling density. In applications where memory or processing time are limited, emphasis must be given to minimizing the number of samples required to represent the signal completely. == Existing approaches == For a bandlimited waveform, there are infinitely many ways the signal can be sampled without producing aliases in the Fourier domain. But only two strategies are commonly used: rectangular sampling and hexagonal sampling. === Rectangular and Hexagonal sampling === In rectangular sampling, a 2-dimensional signal, for example, is sampled according to the following V matrix: V r e c t = [ T 1 0 0 T 2 ] {\displaystyle V_{rect}={\begin{bmatrix}T1&0\\0&T2\end{bmatrix}}} where T1 and T2 are the sampling periods along the horizontal and vertical direction respectively. In hexagonal sampling, the V matrix assumes the following general form: V h e x = [ T 1 T 1 − T 2 T 2 ] {\displaystyle V_{hex}={\begin{bmatrix}T1&T1\\-T2&T2\end{bmatrix}}} The difference in the efficiency of the two schemes is highlighted using a bandlimited signal with a circular region of support of radius R. The circle can be inscribed in a square of length 2R or a regular hexagon of length 2 R 3 {\displaystyle {\frac {2R}{\sqrt {3}}}} . Consequently, the region of support is now transformed into a square and a hexagon respectively. If these regions are periodically replicated in the frequency domain such that there is zero overlap between any two regions, then by periodically replicating the square region of support, we effectively sample the continuous signal on a rectangular lattice. Similarly periodic replication of the hexagonal region of support maps to sampling the continuous signal on a hexagonal lattice. From U, the periodicity matrix, we can calculate the optimal sampling density for both the rectangular and hexagonal schemes. It is found that in order to completely recover the circularly band-limited signal, the hexagonal sampling scheme requires 13.4% fewer samples than the rectangular sampling scheme. The reduction may appear to be of little significance for a 2-dimensional signal. But as the dimensionality of the signal increases, the efficiency of the hexagonal sampling scheme will become far more evident. For instance, the reduction achieved for an 8-dimensional signal is 93.8%. To highlight the importance of the obtained result [2], try and visualize an image as a collection of infinite number of samples. The primary entity responsible for vision, i.e. the photoreceptors (rods and cones) are present on the retina of all mammals. These cells are not arranged in rows and columns. By adapting a hexagonal sampling scheme, our eyes are able to process images much more efficiently. The importance of hexagonal sampling lies in the fact that the photoreceptors of the human vision system lie on a hexagonal sampling lattice and, thus, perform hexagonal sampling.[3] In fact, it can be shown that the hexagonal sampling scheme is the optimal sampling scheme for a circularly band-limited signal. == Applications == === Aliasing effects minimized by the use of optimal sampling grids === Recent advances in the CCD technology has made hexagonal sampling feasible for real life applications. Historically, because of technology constraints, detector arrays were implemented only on 2-dimensional rectangular sampling lattices with rectangular shape detectors. But the super [CCD] detector introduced by Fuji has an octagonal shaped pixel in a hexagonal grid. Theoretically, the performance of the detector was greatly increased by introducing an octagonal pixel. The number of pixels required to represent the sample was reduced and there was significant improvement in the Signal-to-Noise Ratio (SNR) when compared with that of a rectangular pixel. But the drawback of using hexagonal pixels is that the associated fill factor will be less than 82%. An alternative method would be to interpolate hexagonal pixels in such a manner that we ultimately end up with a rectangular grid. The Spot 5 satellite incorporates a

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  • Manufacturing Automation Protocol

    Manufacturing Automation Protocol

    Manufacturing Automation Protocol (MAP) was a computer network standard released in 1982 for interconnection of devices from multiple manufacturers. It was developed by General Motors to combat the proliferation of incompatible communications standards used by suppliers of automation products such as programmable controllers. By 1985 demonstrations of interoperability were carried out and 21 vendors offered MAP products. In 1986 the Boeing corporation merged its Technical Office Protocol with the MAP standard, and the combined standard was referred to as "MAP/TOP". The standard was revised several times between the first issue in 1982 and MAP 3.0 in 1987, with significant technical changes that made interoperation between different revisions of the standard difficult. Although promoted and used by manufacturers such as General Motors, Boeing, and others, it lost market share to the contemporary Ethernet standard and was not widely adopted. Difficulties included changing protocol specifications, the expense of MAP interface links, and the speed penalty of a token-passing network. The token bus network protocol used by MAP became standardized as IEEE standard 802.4 but this committee disbanded in 2004 due to lack of industry attention.

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  • IBM remote batch terminals

    IBM remote batch terminals

    The IBM 2780 and the IBM 3780 are devices developed by IBM for performing remote job entry (RJE) and other batch functions over telephone lines; they communicate with the mainframe via Binary Synchronous Communications (BSC or Bisync) and replaced older terminals using synchronous transmit-receive (STR). In addition, IBM has developed workstation programs for the 1130, 360/20, 2922, System/360 other than 360/20, System/370 and System/3. == 2780 Data Transmission Terminal == The 2780 Data Transmission Terminal first shipped in 1967. It consists of: A line printer similar to the IBM 1443 that can print up to 240 lines per minute (lpm), or 300 lpm using an extremely restricted character set. A card reader/punch unit, similar to an IBM 1442, that can read up to 400 cards per minute (cpm) and can punch up to 355 cpm. A line buffer that stores data received or to be transmitted over the communications line. A binary synchronous adapter which controls the flow of data over the communications line. The 2780 is capable of local (offline) card to print operation. It comes in four models: Model 1: Can read punched cards and transmit the data to a remote host computer, and can receive and print data sent by the host. Model 2: Same as Model 1 but adds the ability to punch card data received from the host. Model 3: Can only print data received from the host, but not send data to it. Model 4: Can read and punch card data, but has no printing capabilities. The 2780 uses a dedicated communication line at speeds of 1200, 2000, 2400 or 4800 bits per second. It is a half duplex device, although full duplex lines can be used with some increase in throughput. It can communicate in Transcode (a 6-bit code), 8-bit EBCDIC, or 7-bit ASCII. == 2770 Data Communication System == The 2770, announced in 1969, "was said to surpass all other IBM terminals in the variety of available input-output devices." The 2770 was developed by the IBM General Products Division (GPD) in Rochester, MN. It comes standard with a desktop terminal with keyboard. The printer and other devices (any two in any combination) can be attached to the 2772 Multi-Purpose Control unit. Possible devices include: 50 Magnetic Data Inscriber 545 Card Punch Model 3 (non-printing) or Model 4 (printing) 1017 Paper Tape Reader 1018 Paper Tape Punch 1053 Printer Model 1 1255 Magnetic Character Reader Models 1, 2 or 3 2203 Printer Model A1 or A2 2213 Printer Model 1 or 2 2265 Display Station Model 2 2502 Card Reader Model A1 or A2 5496 Data Recorder == 3780 Data Communications Terminal == In May 1972, IBM announced the IBM 3780, an enhanced version of the 2780. The 3780 was developed by IBM's Data Processing Division (DPD). There is one model, with an optional card punch. The 3780 drops Transcode support and incorporates several performance enhancements. It supports compression of blank fields in data using run-length encoding. It provides the ability to interleave data between devices, introduces double buffering, and adds support for the Wait-before-transmit ACKnowledgement (WACK) and Temporary Text Delay (TTD) Binary Synchronous control characters. The integrated punched card unit can read cards at 600 cards per minute. The integrated printer is rated at 300, 350 or 425 lines per minute based on characters set (63, 52 or 39 characters). The 3781 Card Punch is an optional feature. It punches 160 columns per second, or 91 cards per minute if all 80 columns are punched. The IBM 2780 and 3780 were later emulated on various types of equipment, including eventually the personal computer. A notable early emulation was the DN60, by Digital Equipment Corporation in the late 1970s. == 3770 Data Communications System == In 1974 IBM Data Processing Division (DPD) offered a successor to the 3780, called the 3770 Data Communications System, supporting SDLC, BSC, BSC Multi-leaving and SNA, depending on the configuration. The 3770 is a family of desk console style terminals that offers a variety of keyboard and printer combinations as well as I/O equipment attachment and communications features. The terminals come built into a desk and include the following models: 3771 Communication Terminal (optional card reader, optional card punch, wire matrix printer) Models 1 (40 cps printer), 2 (80 cps printer), and 3 (120 cps printer). 3773 Communication Terminal (diskette, wire matrix printer) Models 1 (40 cps printer), 2 (80 cps printer), and 3 (120 cps printer). Each model has a P version which adds some programming features. 3774 Communication Terminal (optional card reader, optional card punch, optional belt printer, wire matrix printer) Models 1 (80 cps printer), and 2 (120 cps printer). Each model has a P version which adds some programming features, a 480-character display and a non-removable diskette. 3775 Communication Terminal (optional card reader, optional card punch, optional diskette, belt printer) Model 1 (120 lpm printer). The model P1 adds some programming features, a 480-character display and a non-removable diskette. 3776 Communication Terminal (optional card reader, optional card punch, optional diskette, belt printer) Models 1 (300 lpm printer) and 2 (400 lpm printer). Models 3 and 4 are similar to models 1 and 2. 3777 Communication Terminal (optional card reader, optional diskette, train printer) Model 1 (up to 1000 lpm printer depending on character set). Model 2 adds an optional card punch, model 3 adds an optional magnetic tape drive and model 4 replaces the train printer with a slower model called the IBM 3262. The model 4 also allows a second, optional, 3262. The following I/O devices can be attached to a 3770 terminal: IBM 2502 Card Reader: Models A1 (up to 150 card per minute), A2 (up to 300 cards per minute) or A3 (up to 400 cards per minute) IBM 3203 Printer Model 3: 1000 LPM using 48 character set IBM 3501 Card Reader: Up to 50 cards per minute desktop unit IBM 3521 Card Punch: Up to 50 cards per minute IBM 3782 Card Attachment unit, which allows the 2502 or 3521 to be attached to any terminal except the 3777 IBM 3784 Line Printer, can be attached to a 3774 as a second printer. Up to 155 LPM with 48 characters set print belt. == Workstation programs == IBM distributes workstation programs with systems software including OS/360 Attached Support Processor (ASP) Houston Automatic Spooling Priority (HASP and HASP II) Operating System/Virtual Storage 1 (OS/VS1) Operating System/Virtual Storage 2 (OS/VS2 MVS) Release 2 through 3.8 MVS versions from MVS/SP Version 1 through z/OS Priority Output Writers, Execution processors and input Readers (POWER) Remote Spooling Communications Subsystem (RSCS) Except for the RJE workstation programs in OS/360, these programs use a variation of BSC known as Multi-leaving. In addition, IBM provides separately ordered workstation programs using BSC. Systems Network Architecture (SNA) and TCP/IP. Workstation programs are available from IBM and third-party vendors to support all of these protocols: 2770/3770 2780/3780 Multileaving Network Job Entry (NJE) OS/360 RJE SNA TCP/IP

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