QuickPar is a computer program that creates parchives used as verification and recovery information for a file or group of files, and uses the recovery information, if available, to attempt to reconstruct the originals from the damaged files and the PAR volumes. Designed for the Microsoft Windows operating system, in the past it was often used to recover damaged or missing files that have been downloaded through Usenet. QuickPar may also be used under Linux via Wine. There are two main versions of PAR files: PAR and PAR2. The PAR2 file format lifts many of its previous restrictions. QuickPar is freeware but not open-source. It uses the Reed-Solomon error correction algorithm internally to create the error correcting information. == Replacement == Since QuickPar hasn't been updated in 21 years, it is considered abandonware. Currently, MultiPar is accepted as the software that replaces QuickPar. MultiPar is actively being developed by Yutaka Sawada. == 64-bit versions == At present the command line version of QuickPar for Linux command line is available as a 64-bit version. None of the GUI versions available presently offer a 64-bit version.
Statistical learning theory
Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data. Statistical learning theory has led to successful applications in fields such as computer vision, speech recognition, and bioinformatics. == Introduction == The goals of learning are understanding and prediction. Learning falls into many categories, including supervised learning, unsupervised learning, online learning, and reinforcement learning. From the perspective of statistical learning theory, supervised learning is best understood. Supervised learning involves learning from a training set of data. Every point in the training is an input–output pair, where the input maps to an output. The learning problem consists of inferring the function that maps between the input and the output, such that the learned function can be used to predict the output from future input. Depending on the type of output, supervised learning problems are either problems of regression or problems of classification. If the output takes a continuous range of values, it is a regression problem. Using Ohm's law as an example, a regression could be performed with voltage as input and current as an output. The regression would find the functional relationship between voltage and current to be R {\displaystyle R} , such that V = I R {\displaystyle V=IR} Classification problems are those for which the output will be an element from a discrete set of labels. Classification is very common for machine learning applications. In facial recognition, for instance, a picture of a person's face would be the input, and the output label would be that person's name. The input would be represented by a large multidimensional vector whose elements represent pixels in the picture. After learning a function based on the training set data, that function is validated on a test set of data, data that did not appear in the training set. == Formal description == Take X {\displaystyle X} to be the vector space of all possible inputs, and Y {\displaystyle Y} to be the vector space of all possible outputs. Statistical learning theory takes the perspective that there is some unknown probability distribution over the product space Z = X × Y {\displaystyle Z=X\times Y} , i.e. there exists some unknown p ( z ) = p ( x , y ) {\displaystyle p(z)=p(\mathbf {x} ,y)} . The training set is made up of n {\displaystyle n} samples from this probability distribution, and is notated S = { ( x 1 , y 1 ) , … , ( x n , y n ) } = { z 1 , … , z n } {\displaystyle S=\{(\mathbf {x} _{1},y_{1}),\dots ,(\mathbf {x} _{n},y_{n})\}=\{\mathbf {z} _{1},\dots ,\mathbf {z} _{n}\}} Every x i {\displaystyle \mathbf {x} _{i}} is an input vector from the training data, and y i {\displaystyle y_{i}} is the output that corresponds to it. In this formalism, the inference problem consists of finding a function f : X → Y {\displaystyle f:X\to Y} such that f ( x ) ∼ y {\displaystyle f(\mathbf {x} )\sim y} . Let H {\displaystyle {\mathcal {H}}} be a space of functions f : X → Y {\displaystyle f:X\to Y} called the hypothesis space. The hypothesis space is the space of functions the algorithm will search through. Let V ( f ( x ) , y ) {\displaystyle V(f(\mathbf {x} ),y)} be the loss function, a metric for the difference between the predicted value f ( x ) {\displaystyle f(\mathbf {x} )} and the actual value y {\displaystyle y} . The expected risk is defined to be I [ f ] = ∫ X × Y V ( f ( x ) , y ) p ( x , y ) d x d y {\displaystyle I[f]=\int _{X\times Y}V(f(\mathbf {x} ),y)\,p(\mathbf {x} ,y)\,d\mathbf {x} \,dy} The target function, the best possible function f {\displaystyle f} that can be chosen, is given by the f {\displaystyle f} that satisfies f = argmin h ∈ H I [ h ] {\displaystyle f=\mathop {\operatorname {argmin} } _{h\in {\mathcal {H}}}I[h]} Because the probability distribution p ( x , y ) {\displaystyle p(\mathbf {x} ,y)} is unknown, a proxy measure for the expected risk must be used. This measure is based on the training set, a sample from this unknown probability distribution. It is called the empirical risk I S [ f ] = 1 n ∑ i = 1 n V ( f ( x i ) , y i ) {\displaystyle I_{S}[f]={\frac {1}{n}}\sum _{i=1}^{n}V(f(\mathbf {x} _{i}),y_{i})} A learning algorithm that chooses the function f S {\displaystyle f_{S}} that minimizes the empirical risk is called empirical risk minimization. == Loss functions == The choice of loss function is a determining factor on the function f S {\displaystyle f_{S}} that will be chosen by the learning algorithm. The loss function also affects the convergence rate for an algorithm. It is important for the loss function to be convex. Different loss functions are used depending on whether the problem is one of regression or one of classification. === Regression === The most common loss function for regression is the square loss function (also known as the L2-norm). This familiar loss function is used in Ordinary Least Squares regression. The form is: V ( f ( x ) , y ) = ( y − f ( x ) ) 2 {\displaystyle V(f(\mathbf {x} ),y)=(y-f(\mathbf {x} ))^{2}} The absolute value loss (also known as the L1-norm) is also sometimes used: V ( f ( x ) , y ) = | y − f ( x ) | {\displaystyle V(f(\mathbf {x} ),y)=|y-f(\mathbf {x} )|} === Classification === In some sense the 0-1 indicator function is the most natural loss function for classification. It takes the value 0 if the predicted output is the same as the actual output, and it takes the value 1 if the predicted output is different from the actual output. For binary classification with Y = { − 1 , 1 } {\displaystyle Y=\{-1,1\}} , this is: V ( f ( x ) , y ) = θ ( − y f ( x ) ) {\displaystyle V(f(\mathbf {x} ),y)=\theta (-yf(\mathbf {x} ))} where θ {\displaystyle \theta } is the Heaviside step function. == Regularization == In machine learning problems, a major problem that arises is that of overfitting. Because learning is a prediction problem, the goal is not to find a function that most closely fits the (previously observed) data, but to find one that will most accurately predict output from future input. Empirical risk minimization runs this risk of overfitting: finding a function that matches the data exactly but does not predict future output well. Overfitting is symptomatic of unstable solutions; a small perturbation in the training set data would cause a large variation in the learned function. It can be shown that if the stability for the solution can be guaranteed, generalization and consistency are guaranteed as well. Regularization can solve the overfitting problem and give the problem stability. Regularization can be accomplished by restricting the hypothesis space H {\displaystyle {\mathcal {H}}} . A common example would be restricting H {\displaystyle {\mathcal {H}}} to linear functions: this can be seen as a reduction to the standard problem of linear regression. H {\displaystyle {\mathcal {H}}} could also be restricted to polynomial of degree p {\displaystyle p} , exponentials, or bounded functions on L1. Restriction of the hypothesis space avoids overfitting because the form of the potential functions are limited, and so does not allow for the choice of a function that gives empirical risk arbitrarily close to zero. One example of regularization is Tikhonov regularization. This consists of minimizing 1 n ∑ i = 1 n V ( f ( x i ) , y i ) + γ ‖ f ‖ H 2 {\displaystyle {\frac {1}{n}}\sum _{i=1}^{n}V(f(\mathbf {x} _{i}),y_{i})+\gamma \left\|f\right\|_{\mathcal {H}}^{2}} where γ {\displaystyle \gamma } is a fixed and positive parameter, the regularization parameter. Tikhonov regularization ensures existence, uniqueness, and stability of the solution. == Bounding empirical risk == Consider a binary classifier f : X → { 0 , 1 } {\displaystyle f:{\mathcal {X}}\to \{0,1\}} . We can apply Hoeffding's inequality to bound the probability that the empirical risk deviates from the true risk to be a Sub-Gaussian distribution. P ( | R ^ ( f ) − R ( f ) | ≥ ϵ ) ≤ 2 e − 2 n ϵ 2 {\displaystyle \mathbb {P} (|{\hat {R}}(f)-R(f)|\geq \epsilon )\leq 2e^{-2n\epsilon ^{2}}} But generally, when we do empirical risk minimization, we are not given a classifier; we must choose it. Therefore, a more useful result is to bound the probability of the supremum of the difference over the whole class. P ( sup f ∈ F | R ^ ( f ) − R ( f ) | ≥ ϵ ) ≤ 2 S ( F , n ) e − n ϵ 2 / 8 ≈ n d e − n ϵ 2 / 8 {\displaystyle \mathbb {P} {\bigg (}\sup _{f\in {\mathcal {F}}}|{\hat {R}}(f)-R(f)|\geq \epsilon {\bigg )}\leq 2S({\mathcal {F}},n)e^{-n\epsilon ^{2}/8}\approx n^{d}e^{-n\epsilon ^{2}/8}} where S ( F , n ) {\displaystyle S({\mathcal {F}},n)} is the shattering number and n {\displaystyle n} is the number of samples in your dataset. The exponential term comes from Hoeffding but there is an extra cost of taking the supremum over the whole cla
ISO/IEC 11801
International standard ISO/IEC 11801 Information technology — Generic cabling for customer premises specifies general-purpose telecommunication cabling systems (structured cabling) that are suitable for a wide range of applications (analog and ISDN telephony, various data communication standards, building control systems, factory automation). It is published by ISO/IEC JTC 1/SC 25/WG 3 of the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). It covers both balanced copper cabling and optical fibre cabling. The standard was designed for use within commercial premises that may consist of either a single building or of multiple buildings on a campus. It was optimized for premises that span up to 3 km, up to 1 km2 office space, with between 50 and 50,000 persons, but can also be applied for installations outside this range. A major revision was released in November 2017, unifying requirements for commercial, home and industrial networks. == Classes and categories == The standard defines several link/channel classes and cabling categories of twisted-pair copper interconnects, which differ in the maximum frequency for which a certain channel performance is required: Class A: Up to 100 kHz using Category 1 cable and connectors Class B: Up to 1 MHz using Category 2 cable and connectors Class C: Up to 16 MHz using Category 3 cable and connectors Class D: Up to 100 MHz using Category 5e cable and connectors Class E: Up to 250 MHz using Category 6 cable and connectors Class EA: Up to 500 MHz using category 6A cable and connectors (Amendments 1 and 2 to ISO/IEC 11801, 2nd Ed.) Class F: Up to 600 MHz using Category 7 cable and connectors Class FA: Up to 1 GHz (1000 MHz) using Category 7A cable and connectors (Amendments 1 and 2 to ISO/IEC 11801, 2nd Ed.) Class BCT-B: Up to 1 GHz (1000 MHz) using with coaxial cabling for BCT applications. (ISO/IEC 11801-1, Edition 1.0 2017-11) Class I: Up to 2 GHz (2000 MHz) using Category 8.1 cable and connectors (ISO/IEC 11801-1, Edition 1.0 2017-11) Class II: Up to 2 GHz (2000 MHz) using Category 8.2 cable and connectors (ISO/IEC 11801-1, Edition 1.0 2017-11) The standard link impedance is 100 Ω. (The older 1995 version of the standard also permitted 120 Ω and 150 Ω in Classes A−C, but this was removed from the 2002 edition.) The standard defines several classes of optical fiber interconnect: OM1: Multimode, 62.5 μm core; minimum modal bandwidth of 200 MHz·km at 850 nm OM2: Multimode, 50 μm core; minimum modal bandwidth of 500 MHz·km at 850 nm OM3: Multimode, 50 μm core; minimum modal bandwidth of 2000 MHz·km at 850 nm OM4: Multimode, 50 μm core; minimum modal bandwidth of 4700 MHz·km at 850 nm OM5: Multimode, 50 μm core; minimum modal bandwidth of 4700 MHz·km at 850 nm and 2470 MHz·km at 953 nm OS1: Single-mode, maximum attenuation 1 dB/km at 1310 and 1550 nm OS1a: Single-mode, maximum attenuation 1 dB/km at 1310, 1383, and 1550 nm OS2: Single-mode, maximum attenuation 0.4 dB/km at 1310, 1383, and 1550 nm Grandfathered === OM5 === OM5 fiber is designed for wideband applications using SWDM multiplexing of 4–16 carriers (40G=4λ×10G, 100G=4λ×25G, 400G=4×4λ×25G) in the 850–953 nm range. === Category 7 === Class F channel and Category 7 cable are backward compatible with Class D/Category 5e and Class E/Category 6. Class F features even stricter specifications for crosstalk and system noise than Class E. To achieve this, shielding was added for individual wire pairs and the cable as a whole. Unshielded cables rely on the quality of the twists to protect from EMI. This involves a tight twist and carefully controlled design. Cables with individual shielding per pair such as Category 7 rely mostly on the shield and therefore have pairs with longer twists. The Category 7 cable standard was ratified in 2002, and primarily introduced to support 10 gigabit Ethernet over 100 m of copper cabling. Like the earlier standards, it contains four twisted copper wire pairs rated for transmission frequencies of up to 600 MHz. However, in 2006, Category 6A was ratified for Ethernet to allow 10 Gbit/s while still using the conventional 8P8C connector. Care is required to avoid signal degradation by mixing cable and connectors not designed for that use, however similar. Most manufacturers of active equipment and network cards have chosen to support the 8P8C for their 10 gigabit Ethernet products on copper and not GG45, ARJ45, or TERA connectors as Class F would have originally called for. Therefore, the Category 6 specification was revised to Category 6A to permit this use; products therefore require a Class EA channel (ie, Cat 6A). As of 2019, some equipment has been introduced which has connectors supporting the Class F (Category 7) channel. Note, however, that Category 7 is not recognized by the TIA/EIA. === Category 7A === Class FA (Class F Augmented) channels and Category 7A cables, introduced by ISO 11801 Edition 2 Amendment 2 (2010), are defined at frequencies up to 1000 MHz. The intent of the Class FA was to possibly support the future 40 gigabit Ethernet: 40GBASE-T. Simulation results have shown that 40 gigabit Ethernet may be possible at 50 meters and 100 gigabit Ethernet at 15 meters. In 2007, researchers at Pennsylvania State University predicted that either 32 nm or 22 nm circuits would allow for 100 gigabit Ethernet at 100 meters. However, in 2016, the IEEE 802.3bq working group ratified the amendment 3 which defines 25GBASE-T and 40GBASE-T on Category 8 cabling specified to 2000 MHz. The Class FA therefore does not support 40G Ethernet. As of 2025, there is no equipment that has connectors supporting the Class FA (Category 7A) channel. Category 7A is not recognized in TIA/EIA. === Category 8 === Category 8 was ratified by the TR43 working group under ANSI/TIA 568-C.2-1. It is defined up to 2000 MHz and only for distances up to 30 m or 36 m, depending on the patch cords used. ISO/IEC JTC 1/SC 25/WG 3 developed the equivalent standard ISO/IEC 11801-1:2017/COR 1:2018, with two options: Class I channel (Category 8.1 cable): minimum cable design U/FTP or F/UTP, fully backward compatible and interoperable with Class EA (Category 6A) using 8P8C connectors; Class II channel (Category 8.2 cable): F/FTP or S/FTP minimum, interoperable with Class FA (Category 7A) using TERA or GG45. == Abbreviations for twisted pairs == Annex E, Acronyms for balanced cables, provides a system to specify the exact construction for both unshielded and shielded balanced twisted pair cables. It uses three letters—U for unshielded, S for braided shielding, and F for foil shielding—to form a two-part abbreviation in the form of xx/xTP, where the first part specifies the type of overall cable shielding, and the second part specifies shielding for individual cable elements. Common cable types include U/UTP (unshielded cable); U/FTP (individual pair shielding without the overall screen); F/UTP, S/UTP, or SF/UTP (overall screen without individual shielding); and F/FTP, S/FTP, or SF/FTP (overall screen with individual foil shielding). == 2017 edition == In November 2017, a new edition was released by ISO/IEC JTC 1/SC 25 "Interconnection of information technology equipment" subcommittee. It is a major revision of the standard which has unified several prior standards for commercial, home, and industrial networks, as well as data centers, and defines requirements for generic cabling and distributed building networks. The new series of standards replaces the former 11801 standard and includes six parts: == Versions == ISO/IEC 11801:1995 (Ed. 1) ISO/IEC 11801:2000 (Ed. 1.1) – Edition 1, Amendment 1 ISO/IEC 11801:2002 (Ed. 2) ISO/IEC 11801:2008 (Ed. 2.1) – Edition 2, Amendment 1 ISO/IEC 11801:2010 (Ed. 2.2) – Edition 2, Amendment 2 ISO/IEC 11801-1:2017, -1:2017/Cor 1:2018, -2:2017, -3:2017, -3:2017/Amd 1:2021, -3:2017/Cor 1:2018, -4:2017, -4:2017/Cor 1:2018, -5:2017, -5:2017/Cor 1:2018, -6:2017, -6:2017/Cor 1:2018 (As of September 2023, this set is current.)
Enterprise social software
Enterprise social software (also known as or regarded as a major component of Enterprise 2.0), comprises social software as used in "enterprise" (business/commercial) contexts. It includes social and networked modifications to corporate intranets and other classic software platforms used by large companies to organize their communication. In contrast to traditional enterprise software, which imposes structure prior to use, enterprise social software tends to encourage use prior to providing structure. Carl Frappaolo and Dan Keldsen defined Enterprise 2.0 in a report written for Association for Information and Image Management (AIIM) as "a system of web-based technologies that provide rapid and agile collaboration, information sharing, emergence and integration capabilities in the extended enterprise". == Applications == === Functionality === Social software for an enterprise must (according to Andrew McAfee, Associate Professor, Harvard Business School) have the following functionality to work well: Search: allowing users to search for other users or content Links: grouping similar users or content together Authoring: including blogs and wikis Tags: allowing users to tag content Extensions: recommendations of users; or content based on profile Signals: allowing people to subscribe to users or content with RSS feeds McAfee recommends installing easy-to-use software which does not impose any rigid structure on users. He envisages an informal roll-out, but on a common platform to enable future collaboration between areas. He also recommends strong and visible managerial support to achieve this. In 2007 Dion Hinchcliffe expanded the list above by adding the following four functions: Freeform function: no barriers to authorship (meaning free from a learning curve or from restrictions) Network-oriented function, requiring web-addressable content in all cases Social function: stressing transparency (to access), diversity (in content and community members) and openness (to structure) Emergence function: requiring the provision of approaches that detect and leverage the collective wisdom of the community Enterprise search differs from a typical web search in its focus on "use within an organization by employees seeking information held internally, in a variety of formats and locations, including databases, document management systems, and other repositories". === Criticism === There has been recent criticism that the adaptation of the social paradigm (e.g. openness and altruistic behavior) does not always work well for the enterprise setting, which led some authors to question the proper functioning of enterprise social software. The findings from a novel study suggests that free and non-anonymous sharing of trusted information (beyond marketing or product information) is significantly influenced by concerns from business users.
ProjectExplorer
ProjectExplorer is a documentary short film series. The films, directed and produced by ProjectExplorer's Founder, Jenny M Buccos, focus on histories and cultures of foreign places and people using interviews with subject experts, artists, and public figures including Archbishop Desmond Tutu, Dr. John Kani, Greg Marinovich, and Sipho “Hotstix” Mabuse. Produced for a child and young adult audience, segments in each series depict everyday life and the challenges and concerns of those living in the locations and regions featured. Each film is 2–4 minutes in length, with each series containing approximately 40 films. The ProjectExplorer series is distributed internationally without charge via the web by ProjectExplorer, LTD. an American not-for-profit organization. Three series have been produced and distributed. In fall 2009, ProjectExplorer's third series, Jordan, received a GOLD level Parents' Choice Award for excellence in web programming. == Film series == === Shakespeare's England (2006) === The first series was filmed in London, Stratford-upon-Avon, and New York City. The series includes more than 30 film segments. United Kingdom locations and individuals include: The London Eye The Tower of London The Whitechapel Bell Foundry, which demonstrates the process of making a bell Simon Hughes, Member of Parliament and President of the Liberal Democrats The Old Vic The Royal Shakespeare Company The National Archives (UK) Segments filmed in New York City include: Michael Cumpsty discusses and performs monologues from Hamlet (while starring in the Classic Stage Company production) Michael Stuhlbarg discusses and performs a monologue from Macbeth === South Africa (2007) === Filmed in Johannesburg, Cape Town, and KwaZulu Natal, the series contains over 40 film segments including: Ntate Thabong Phosa, a lesiba player from Lesotho. Due to the rarity of lesiba players globally, this is one of the only publicly available examples of the lesiba played on film. A Robben Island piece, filmed at the cell in which Nelson Mandela was held for 18 of his 27-year imprisonment. JSE Securities Exchange with Leigh Roberts, correspondent for CNBC Africa. A 3-part series on HIV/AIDS with amfAR Director of Research, Dr. Rowena Johnson. Dr. Johnson discusses high cost of anti-retroviral drugs and testing in South Africa. The June 16, 1976 Soweto Uprising, with archival film footage and photography from SABC and The Sowetan newspaper. Prominent South Africans featured in the series: Dr. John Kani, Chairperson of the Apartheid Museum and TONY Award Winning Actor Musician Sipho “Hotstix” Mabuse Former U.N. Ambassador Dave A. Steward, Executive Director of the FW de Klerk Foundation Director and producer, Duma Ndlovu Malcolm Purkey, Artistic Director of the Market Theatre === South Africa, Part II (2008) === Filmed in Johannesburg, Cape Town, and New York City, the series contains over 10 film segments. Prominent South Africans featured in the series: Archbishop Desmond Tutu, Nobel Peace Prize laureate Photojournalist Greg Marinovich, Pulitzer Prize winner and co-author of The Bang-Bang Club Vusi Mahlasela, musician Author, Max du Preez === Jordan (2008) === Filmed in Amman, Petra, Umm Qais, Jerash, Madaba, Bethany, the Dead Sea, and New York City, the series contains more than 45 film segments. Jordan series segments include: A tour of the throne room of King Abdullah II, at Raghadan Palace Sharing mansaf with a Bedouin family in the Wadi Rum desert The UNRWA Jabal Hussein refugee camp The Siq, Treasury, and Monastery at Petra The ruins of Gadara at Umm Qais Jerash, the capital and largest city of Jordan's Jerash Governorate Madaba, home of the Madaba Map and the mosaic capital of Jordan The archaeological site at Bethany Traditional clothing from Salt and Ma'an The reintroduction into the wild of the endangered Arabian Oryx The Desert Castles The science of the Dead Sea Her Royal Highness Princess Basma bint Ali and her Royal Botanic Garden
Altibase
Altibase is a hybrid database, relational database management system manufactured by the Altibase Corporation. The software's hybrid architecture allows it to access both memory-resident and disk-resident tables using single interface. It supports both synchronous and asynchronous replication and offers real-time ACID compliance. Support is also offered for a variety of SQL standards and programming languages. Other important capabilities include data import and export, data encryption for security, multiple data access command sets, materialized view and temporary tables, and others. == History == From 1991 through 1997 the Mr. RT project was an in-memory database research project, conducted by the Electronics and Telecommunications Research Institute a government-funded research organization in South Korea. Altibase was incorporated in 1999. Altibase acquired an in-memory database engine from the Electronics and Telecommunications Research Institute in February 2000, and commercialized the database in October of the same year. In 2001, Altibase changed the name of the in-memory database product from "Spiner" to "Altibase" in 2001. In 2004, Altibase integrated the in-memory database with a disk-resident database to create a hybrid DBMS, released version 4.0 and renamed it as ALTIBASE HDB. Altibase released version 5.5.1 and 6.1.1 in 2012, version 6.3.1 in November 2013, and 6.5.1 in May 2015. Altibase claims that this is the world's first hybrid DBMS. Altibase released its open source edition version 7.1, however, closed the source in 2023. In August 2023, Altibase released its cloud-optimized version 7.3. === Awards === In 2006, Received the Presidential Award at the Korea Software Awards In 2007, Selected as World-Class Product by the Ministry of Commerce, Industry and Energy In 2009, Awarded the Outstanding Product Award in China's Telecommunications Industry In 2009, Received Outstanding Product Award at the China Billing China 2009 Telecommunication Industry Awards In 2010, Commendation from the Minister of Knowledge Economy for Technological Practicalization In 2011, Received the Grand Prize at the 10th Software Enterprise Competitiveness Award In 2011, Selected as Top 10 Emerging Technologies and received Special Award at the Korea Technology Grand Prize In 2012, Awarded for Contributions to Military Manpower Administration In 2014~2016, Included in Gartner Magic Quadrant for Operational DBMS In 2015, Selected as Outstanding BSS by China Fujian Mobile. In 2023, Awarded as the Excellent Research and Development Institution by the Korean Ministry Science and ICT In 2023, Won the Global Premium Commercial Software Presidential Award at the 9th Global Commercial Software Grand Exhibition in Korea === Release === The first version, called Spiner, was released in 2000 for commercial use. It took half of the in-memory DBMS market share in South Korea. In 2002 the second version was released renamed to Altibase v2.0. By 2003, Altibase v3.0 was released and it entered the Chinese market. Released version 4.0 with hybrid architecture, combining RAM and disk databases, was released in 2004. In 2005 Altibase began working with Chinese telecommunications providers for billing systems, and some financial companies in Taiwan, China, for home trading systems. The software was certified by the Telecommunications Technology Association. The Ministry of Government Administration and Home Affairs gave it an award in 2006. Offices in China and United States opened in 2009. In 2011, version 5.5.1 was renamed it to HDB (for "hybrid database"). The Altibase Data Stream product for complex event processing was renamed DSM. The product received a Korean technology award. Altibase introduced certification services. In 2012, HDB Zeta and Extreme were announced, and DSM renamed to CEP. In 2013, yet another variant called XDB was announced, and the company received ISO/IEC 20000 certification. In 2018, Altibase went open source. Altibase went open source in February, 2018. Altibase Corp has made the decision to discontinue the Altibase 7.1 open source edition, effective March 17, 2023. As a result, the open-source edition of Altibase 7.1 will no longer be available for download or use. Altibase released version 7.3 in September, 2023, its notable feature is the world’s first hybrid partition, allowing data to be stored in both memory and on disk at the partition level. Version 7.3 also added parallel processing capabilities for high-speed performance in both partitioned and non-partitioned scenarios. Improving potential bottlenecks associated with Commit and logging that impact transaction performance, version 7.3 has achieved an approximately 490% enhancement in performance compared to previous versions. === Release history === == Clients == According to marketing research, Altibase have over 700 customers and more than 8,000 of installations and deployments, including 22 Fortune Global 500 Companies. Altibase's clients in the telecommunications, financial services, manufacturing, and utilities sectors include Bloomberg, AT&T, LG, Intel, LGU+, ETRADE, HP, UAT Inc., POSCO, SK Telecom, KT Corporation, Samsung Electronics, Shinhan Bank, Woori Bank, Canon(Toshiba), Hanhwa, The South Korean Ministry of Defense, G-Market, CJ, and Chung-Ang University. === Global clients === Japan FX Prime, a foreign exchange services company Retela Crea Securities United States AT&T Implemented Altibase for its PS-LTE Safety network, where the Presence service plays a vital role. This service handles the reception and storage of user information, conducting real-time checks for online presence and location as needed. Canada Telus One of the major telecommunication companies. Utilizes Altibase for its operations involving real-time user management, processing high volumes of dedicated terminal data, and managing real-time location information (GIS) for terminals. Altibase contributes to the company's in-house solution for maintaining uninterrupted services during national disasters or similar situations, ensuring efficiency and reliability. China China Mobile, China Unicom, China Telecom The three major telecommunications companies. Utilize ALTIBASE HDB in 29 of 31 Chinese provinces. Turkish Ziraat Bank, Halk Bank, Deniz Bank, Garanti BBVA, TEB, Oyak Bank, QNB, Burgan Bank, and others. In 2018, Altibase entered the market through a partnership with ATP-Tradesoft, a subsidiary of Ata Holdings. Collaborating with ATP-Tradesoft. Altibase integrated into the Online Trading System XFront. This integration was well-received by major financial institutions and securities firms in Turkey. Altibase is currently implemented in the XFront Online Trading System, used by 13 significant financial institutions and banks in the Turkey. Thailand Bualuang Securities Altibase has been supplied its DBMS to support the construction of the online stock trading platform. Mongolia MobiCom The Mongolian telecommunication giant, has adopted Altibase’s 7.0 version for its mobile platform for storing the infrequently used data. Azerbaijan M1 highway Altibase has been supplied as the Database Management System (DBMS) for the electronic toll collection system. One of the most crucial transportation networks in the country. India State-owned Karur Vysya Bank In 2013, Altibase provided its hybrid database solution and was deployed for the online banking system === Industries === Telecommunications LGU+ SK Telecom KT Corporation AT&T Telus Financial services Shinhan Bank Woori Bank KakaoPay Securities Implemented Altibase in its stock trading system Leveraging Altibase's replication feature, along with offline replication through shared disk and adapter functionality, the system ensures a high level of availability and consistency, with a reliability rate of 99.999% even in the event of system failures. COREDAX Cryptocurrency market Altibase has entered into a strategic partnership by signing a database management system (DBMS) supply contract with the cryptocurrency exchange Bloomberg ETRADE Manufacturing Samsung Electronics LG POSCO Hanhwa Canon(Toshiba) Intel HP Utilities South Korean Ministry of Defense G-Market CJ UAT Inc. Chung-Ang University == Features == Altibase is a so-called "hybrid DBMS", meaning that it simultaneously supports access to both memory-resident and disk-resident tables via a single interface. It is compatible with Solaris, HP-UX, AIX, Linux, and Windows. It supports the complete SQL standard, features Multiversion concurrency control (MVCC), implements Fuzzy and Ping-Pong Checkpointing for periodically backing up memory-resident data, and ships with Replication and Database Link functionality. High performance, large -capacity service Fast real-time data processing and large amounts of data stable Provide parallel processing architecture for large data management Developed and provided Hybrid Partitioned Table function for efficiency according to data personality High stability
Paperless society
A paperless society is a society in which paper communication (written documents, email, letters, etc.) is replaced by electronic communication and storage. The concept was first introduced by Frederick Wilfrid Lancaster in 1978. Furthermore, libraries would no longer be needed to handle printed documents. "Librarians will, in time, become information specialists in a deinstitutionalized setting". Lancaster also stated that both computers and libraries will not always give us the information that other people and living life will. == Literature == Brodman, E. (1979). Review of Toward Paperless Information Systems. Bulletin of the Medical Library Association, 67(4), 437–439. Buckland, M. K. (1980). Review of Toward Paperless Information Systems. Journal of Academic Librarianship, 5(6), 349. Grosch, A. (1979). Review of Toward Paperless Information Systems. College & Research Libraries, 40(1), 88–89. Kohl, D. F. (2004). From the editor . . . The paperless society . . . Not quite yet. Journal of Academic Librarianship, 30(3), 177–178. Lancaster, F. W. (1978a). Toward paperless information systems. New York: Academic Press. Lancaster, F. W. (1980b). The future of the librarian lies outside of the library. Catholic Library World, 51, 388–391. Lancaster, F. W. (1982a). Libraries and librarians in an age of electronics. Arlington, VA: Information Resources Press. Lancaster, F. W. (1982b). The evolving paperless society and its implications for libraries. International Forum on Information and Documentation, 7(4), 3–10. Lancaster, F. W. (1983). Future librarianship: Preparing for an unconventional career. Wilson Library Bulletin, 57, 747–753. Lancaster, F. W. (1985). The paperless society revisited. American Libraries, 16, 553–555. Lancaster, F. W. (1993). Libraries and the future: Essays on the library in the twenty-first century. New York: Haworth Press. Lancaster, F. W. (1999). Second thoughts on the paperless society. Library Journal, 124(15), 48– 50. Lancaster, F. W., & Smith, L. C. (1980c). On-Line systems in the communication process: Projections. Journal of the American Society for Information Science, 31(3), 193–200. Miall, D. S. (2001). The library versus the Internet: Literary studies under siege? Proceedings of the Modern Language Association, 116(5), 1405–1414. Salton, G. (1979). Review of Toward Paperless Information Systems. Journal of Documentation, 35(3), 250–252. Sellen, A. J., & Harper, R. H. R. (2003). The myth of the paperless office. Cambridge, MA: MIT Press. Stevens, N. D. (2006). The fully electronic academic library. College & Research Libraries, 67(1),5–14. Young, Arthur P. (2008).Aftermath of a Prediction: F. W. Lancaster and the Paperless Society LIBRARY TRENDS, 56(4),(“The Evaluation and Transformation of Information Systems: Essays Honoring the Legacy of F. W. Lancaster,” edited by Lorraine J. Haricombe and Keith Russell), pp. 843–858.