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Topic Review
Converse (Logic)
In logic and mathematics, the converse of a categorical or implicational statement is the result of reversing its two constituent statements. For the implication P → Q, the converse is Q → P. For the categorical proposition All S are P, the converse is All P are S. Either way, the truth of the converse is generally independent from that of the original statement.
  • 1.3K
  • 27 Oct 2022
Topic Review
Weights and Measures Acts (UK)
Weights and measures acts are acts of the British Parliament determining the regulation of weights and measures. It also refers to similar royal and parliamentary acts of the Kingdoms of England and Scotland and the medieval Welsh states. The earliest of these were originally untitled but were given descriptive glosses or titles based upon the monarch under whose reign they were promulgated. Several omnibus modern acts are entitled the Weights and Measures Act and are distinguished by the year of their enactment. There have been many laws concerned with weights and measures in the United Kingdom or parts of it over the last 1000 or so years. The acts may catalogue lawful weights and measures, prescribe the mechanism for inspection and enforcement of the use of such weights and measures and may set out circumstances under which they may be amended. Modern legislation may, in addition to specific requirements, set out circumstances under which the incumbent minister may amend the legislation by means of statutory instruments. Prior to the Weights and Measures Act 1985, weights and measures acts were only concerned with trade law where the weight or size of the goods being traded was important. The 1985 act, however, had a broader scope, encompassing all aspects covered by the European Economic Community (EEC) European Commission directive 80/181/EEC. As of 25 April 2012, the current primary legislation in the United Kingdom is the 1985 Act, which was last amended by statutory instrument in 2011. Statutory instruments made under the authority of the Act do not amend the Act per se, but regulate particular areas covered by the Act. The Act is currently enforced by the 200 Trading Standards Offices managed by local authorities around the country. Definitions of units of measurements and the technical equipment relating to weights and measures are provided by the National Measurement Office, an agency of the Department for Business, Innovation and Skills.
  • 1.3K
  • 14 Oct 2022
Topic Review
Unique Prime
In recreational number theory, a unique prime or unique period prime is a certain kind of prime number. A prime p ≠ 2, 5 is called unique if there is no other prime q such that the period length of the decimal expansion of its reciprocal, 1 / p, is equal to the period length of the reciprocal of q, 1 / q. For example, 3 is the only prime with period 1, 11 is the only prime with period 2, 37 is the only prime with period 3, 101 is the only prime with period 4, so they are unique primes. In contrast, 41 and 271 both have period 5; 7 and 13 both have period 6; 239 and 4649 both have period 7; 73 and 137 both have period 8; 21649 and 513239 both have period 11; 53, 79 and 265371653 all have period 13; 31 and 2906161 both have period 15; 17 and 5882353 both have period 16; 2071723 and 5363222357 both have period 17; 19 and 52579 both have period 18; 3541 and 27961 both have period 20. Therefore, none of these is a unique prime. Unique primes were first described by Samuel Yates in 1980. The above definition is related to the decimal representation of integers. Unique primes may be defined and have been studied in any numeral base.
  • 1.3K
  • 20 Oct 2022
Topic Review
Office 365
Office 365 is a line of subscription services offered by Microsoft as part of the Microsoft Office product line. The brand encompasses plans that allow use of the Microsoft Office software suite over the life of the subscription, as well as cloud-based software-as-a-service products for business environments, such as hosted Exchange Server, Skype for Business Server, and SharePoint, among others. All Office 365 plans include automatic updates to their respective software at no additional charge, as opposed to conventional licenses for these programs—where new versions require purchase of a new license. After a beta test that began in October 2010, Microsoft launched Office 365 on 28 June 2011, aimed originally at corporate users as a successor to Microsoft Business Productivity Online Suite (BPOS). With the release of Microsoft Office 2013, Microsoft expanded Office 365 to include new plans aimed at different types of businesses, along with new plans aimed at general consumers, including benefits tailored towards Microsoft consumer services such as OneDrive (whose integration with Office was a major feature of the 2013 suite). On 21 April 2020, the consumer and small business plans of Office 365 were renamed Microsoft 365, which emphasizes productivity features and services outside of the core Microsoft Office software suite. All products that were called Office 365 were renamed as Microsoft 365 on the same day. In the fourth quarter of fiscal year 2017, Office 365 revenue exceeded that of conventional license sales of Microsoft Office software for the first time.
  • 1.3K
  • 30 Nov 2022
Topic Review
Eucalyptus
Eucalyptus is a paid and open-source computer software for building Amazon Web Services (AWS)-compatible private and hybrid cloud computing environments, originally developed by the company Eucalyptus Systems. Eucalyptus is an acronym for Elastic Utility Computing Architecture for Linking Your Programs To Useful Systems. Eucalyptus enables pooling compute, storage, and network resources that can be dynamically scaled up or down as application workloads change. Mårten Mickos was the CEO of Eucalyptus. In September 2014, Eucalyptus was acquired by Hewlett-Packard and then maintained by DXC Technology. After DXC stopped developing the product in late 2017, AppScale Systems forked the code and started supporting Eucalyptus customers.
  • 1.3K
  • 09 Nov 2022
Topic Review
Computer Emergency Response Team
A computer emergency response team (CERT) is an expert group that handles computer security incidents. Alternative names for such groups include computer emergency readiness team and computer security incident response team (CSIRT).
  • 1.3K
  • 31 Oct 2022
Topic Review
Google Book Search Settlement Agreement
The Google Book Search Settlement Agreement was a proposal between the Authors Guild, the Association of American Publishers, and Google in the settlement of Authors Guild et al. v. Google, a class action lawsuit alleging copyright infringement on the part of Google. The settlement was initially proposed in 2008, but ultimately rejected by the court in 2011. In November 2013, the presiding U.S. Circuit Judge dismissed Authors Guild et al. v. Google. On April 18, 2016, the Supreme Court turned down an appeal.
  • 1.3K
  • 14 Nov 2022
Topic Review
IBM Tivoli Storage Productivity Center
IBM Tivoli Storage Productivity Center (TPC) is a Storage Resource Management (SRM) software offering that provides a centralized point of control for managing large-scale, complex heterogeneous storage environments. IBM Tivoli Storage Productivity Center V5.2.x (5608-PC1) was renamed in V5.2.8 to IBM Spectrum Control Standard Edition V5.2.x (5608-PC1).
  • 1.3K
  • 20 Oct 2022
Topic Review
High-frequency analysis, Model Validation and Intraday risk metrics
Despite the growing amount of research in the field of high frequency financial data analysis, few studies have focused on model validation and high-frequency risk measures. This study contributes to the literature in the following ways: A rigorous model validation, both in terms of in-sample fit and out-sample performance for the MC-GARCH model under five error distributions is provided. Statistical and graphical tests are conducted to validate the models. One component of the MC-GARCH model is the daily variance forecast. For this purpose, the GARCH(1,1) and EGARCH(1,1) under the five error distributions are compared and the best model among the 10 GARCH models is used to forecast the daily variance. The modelling and forecasting performance of the MC-GARCH model under different distributional assumptions is assessed in this study. The 99% intraday VaR is forecasted and three backtesting procedures are used. This is the first study to assess the VaR predictive ability of the MC-GARCH models by using an asymmetric VaR loss function. This is the first study to forecast the intraday expected shortfall under different distributional assumptions for the MC-GARCH model. Again, three backtests are used including the recently proposed ES regression backtest. Due to the high importance of risk management, the results of this study may contribute in many fields. This study is highly relevant to the banking industry since banks are required to calculate risk metrics on a daily basis for internal control purposes and for determining their capital requirements. Risk measurement is also essential to the insurance industry from the pricing of insurance contracts to determining the Solvency Capital Requirement (SCR) and therefore the results of this study might be useful. Any other organisation having an exposure to some kind of financial risk might benefit from this study. 
  • 1.3K
  • 30 Oct 2020
Topic Review
Training, Validation, and Test Sets
In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function by making data-driven predictions or decisions, through building a mathematical model from input data. These input data used to build the model are usually divided in multiple data sets. In particular, three data sets are commonly used in different stages of the creation of the model: training, validation and test sets. The model is initially fit on a training data set, which is a set of examples used to fit the parameters (e.g. weights of connections between neurons in artificial neural networks) of the model. The model (e.g. a naive Bayes classifier) is trained on the training data set using a supervised learning method, for example using optimization methods such as gradient descent or stochastic gradient descent. In practice, the training data set often consists of pairs of an input vector (or scalar) and the corresponding output vector (or scalar), where the answer key is commonly denoted as the target (or label). The current model is run with the training data set and produces a result, which is then compared with the target, for each input vector in the training data set. Based on the result of the comparison and the specific learning algorithm being used, the parameters of the model are adjusted. The model fitting can include both variable selection and parameter estimation. Successively, the fitted model is used to predict the responses for the observations in a second data set called the validation data set. The validation data set provides an unbiased evaluation of a model fit on the training data set while tuning the model's hyperparameters (e.g. the number of hidden units—layers and layer widths—in a neural network). Validation datasets can be used for regularization by early stopping (stopping training when the error on the validation data set increases, as this is a sign of over-fitting to the training data set). This simple procedure is complicated in practice by the fact that the validation dataset's error may fluctuate during training, producing multiple local minima. This complication has led to the creation of many ad-hoc rules for deciding when over-fitting has truly begun. Finally, the test data set is a data set used to provide an unbiased evaluation of a final model fit on the training data set. If the data in the test data set has never been used in training (for example in cross-validation), the test data set is also called a holdout data set. The term "validation set" is sometimes used instead of "test set" in some literature (e.g., if the original data set was partitioned into only two subsets, the test set might be referred to as the validation set). Deciding the sizes and strategies for data set division in training, test and validation sets is very dependent on the problem and data available.
  • 1.3K
  • 17 Oct 2022
Topic Review
3DNow!
3DNow! is a deprecated extension to the x86 instruction set developed by Advanced Micro Devices (AMD). It adds single instruction multiple data (SIMD) instructions to the base x86 instruction set, enabling it to perform vector processing of floating-point vector-operations using Vector registers, which improves the performance of many graphic-intensive applications. The first microprocessor to implement 3DNow was the AMD K6-2, which was introduced in 1998. When the application was appropriate, this raised the speed by about 2–4 times. However, the instruction set never gained much popularity, and AMD announced on August 2010 that support for 3DNow would be dropped in future AMD processors, except for two instructions (the PREFETCH and PREFETCHW instructions). The two instructions are also available in Bay-Trail Intel processors.
  • 1.3K
  • 03 Nov 2022
Topic Review
Recursively Enumerable Set
In computability theory, traditionally called recursion theory, a set S of natural numbers is called recursively enumerable, computably enumerable, semidecidable, provable or Turing-recognizable if: Or, equivalently, The first condition suggests why the term semidecidable is sometimes used; the second suggests why computably enumerable is used. The abbreviations r.e. and c.e. are often used, even in print, instead of the full phrase. In computational complexity theory, the complexity class containing all recursively enumerable sets is RE. In recursion theory, the lattice of r.e. sets under inclusion is denoted [math]\displaystyle{ \mathcal{E} }[/math].
  • 1.3K
  • 21 Oct 2022
Topic Review
Information Assurance
Information assurance (IA) is the practice of assuring information and managing risks related to the use, processing, storage, and transmission of information. Information assurance includes protection of the integrity, availability, authenticity, non-repudiation and confidentiality of user data. IA encompasses not only digital protections but also physical techniques. These protections apply to data in transit, both physical and electronic forms, as well as data at rest . IA is best thought of as a superset of information security (i.e. umbrella term), and as the business outcome of information risk management.
  • 1.3K
  • 21 Nov 2022
Topic Review
Applications of Multi-Connectivity in 5G Networks and Beyond
To manage a growing number of users and an ever-increasing demand for bandwidth, future 5th Generation (5G) cellular networks will combine different radio access technologies (cellular, satellite, and WiFi, among others) and different types of equipment (pico-cells, femto-cells, small-cells, macro-cells, etc.). Multi-connectivity is an emerging paradigm aiming to leverage this heterogeneous architecture. To achieve that, multi-connectivity proposes to enable each User Equipment to simultaneously use component carriers from different and heterogeneous network nodes: base stations, WiFi Access Points, etc. This could offer many benefits in terms of Quality of Service, energy efficiency, fairness, mobility, spectrum and interference management. That is why this survey aims to present an overview of multi-connectivity in 5G networks and Beyond. To do so, a comprehensive review of existing standards and enabling technologies is proposed. Then, a taxonomy is defined to classify the different elements characterizing multi-connectivity in 5G and future networks. Thereafter, existing research works using multi-connectivity to improve Quality of Service, energy efficiency, fairness, mobility management and spectrum and interference management are analyzed and compared. In addition, lessons common to these different contexts are presented. Finally, open challenges for multi-connectivity in 5G networks and Beyond are discussed.
  • 1.3K
  • 24 Oct 2022
Topic Review
Flocking (Behavior)
thumb|200px|right|A swarm-like flock of starlings Flocking behavior is the behavior exhibited when a group of birds, called a flock, are foraging or in flight. There are parallels with the shoaling behavior of fish, the swarming behavior of insects, and herd behavior of land animals. During the winter months, Starlings are known for aggregating into huge flocks of hundreds to thousands of individuals, murmurations, which when they take flight altogether, render large displays of intriguing swirling patterns in the skies above observers. Computer simulations and mathematical models which have been developed to emulate the flocking behaviors of birds can also generally be applied to the "flocking" behavior of other species. As a result, the term "flocking" is sometimes applied, in computer science, to species other than birds. This article is about the modelling of flocking behavior. From the perspective of the mathematical modeller, "flocking" is the collective motion by a group of self-propelled entities and is a collective animal behavior exhibited by many living beings such as birds, fish, bacteria, and insects. It is considered an emergent behavior arising from simple rules that are followed by individuals and does not involve any central coordination. Flocking behavior was simulated on a computer in 1987 by Craig Reynolds with his simulation program, Boids. This program simulates simple agents (boids) that are allowed to move according to a set of basic rules. The result is akin to a flock of birds, a school of fish, or a swarm of insects.
  • 1.3K
  • 27 Oct 2022
Topic Review
Meaning-Text Theory
Meaning-text theory (MTT) is a theoretical linguistic framework, first put forward in Moscow by Aleksandr Žolkovskij and Igor Mel’čuk, for the construction of models of natural language. The theory provides a large and elaborate basis for linguistic description and, due to its formal character, lends itself particularly well to computer applications, including machine translation, phraseology, and lexicography.
  • 1.3K
  • 14 Oct 2022
Topic Review
Emotion Recognition
Emotion recognition is the process of identifying human emotion, most typically from facial expressions as well as from verbal expressions. This is both something that humans do automatically but computational methodologies have also been developed.
  • 1.3K
  • 10 Oct 2022
Topic Review
Reduction (Complexity)
In computability theory and computational complexity theory, a reduction is an algorithm for transforming one problem into another problem. A reduction from one problem to another may be used to show that the second problem is at least as difficult as the first. Intuitively, problem A is reducible to problem B if an algorithm for solving problem B efficiently (if it existed) could also be used as a subroutine to solve problem A efficiently. When this is true, solving A cannot be harder than solving B. "Harder" means having a higher estimate of the required computational resources in a given context (e.g., higher time complexity, greater memory requirement, expensive need for extra hardware processor cores for a parallel solution compared to a single-threaded solution, etc.). We write A ≤m B, usually with a subscript on the ≤ to indicate the type of reduction being used (m : mapping reduction, p : polynomial reduction). The mathematical structure generated on a set of problems by the reductions of a particular type generally forms a preorder, whose equivalence classes may be used to define degrees of unsolvability and complexity classes.
  • 1.3K
  • 30 Sep 2022
Topic Review
Operad Theory
Operad theory is a field of mathematics concerned with prototypical algebras that model properties such as commutativity or anticommutativity as well as various amounts of associativity. Operads generalize the various associativity properties already observed in algebras and coalgebras such as Lie algebras or Poisson algebras by modeling computational trees within the algebra. Algebras are to operads as group representations are to groups. An operad can be seen as a set of operations, each one having a fixed finite number of inputs (arguments) and one output, which can be composed one with others. They form a category-theoretic analog of universal algebra. Operads originate in algebraic topology from the study of iterated loop spaces by J. Michael Boardman and Rainer M. Vogt, and J. Peter May. The word "operad" was created by May as a portmanteau of "operations" and "monad" (and also because his mother was an opera singer). Interest in operads was considerably renewed in the early 90s when, based on early insights of Maxim Kontsevich, Victor Ginzburg and Mikhail Kapranov discovered that some duality phenomena in rational homotopy theory could be explained using Koszul duality of operads. Operads have since found many applications, such as in deformation quantization of Poisson manifolds, the Deligne conjecture, or graph homology in the work of Maxim Kontsevich and Thomas Willwacher.
  • 1.3K
  • 09 Oct 2022
Biography
Arun Sharma
Arun Sharma is an Indian Australian computer science professor and a noted leader within the Australian Higher education, research, innovation, and High Tech sectors. He is a distinguished emeritus professor at the Queensland University of Technology (QUT) where he was the Deputy Vice-Chancellor for Research and Commercialisation from 2004 to 2019.[1][2] He is the Council Chair of the QIMR Bergh
  • 1.3K
  • 09 Dec 2022
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