Khasi peopleThe Khasi people are an ethnic group of Meghalaya in north-eastern India with a significant population in the bordering state of Assam, and in certain parts of Bangladesh. Khasi people form the majority of the population of the eastern part of Meghalaya, that is Khasi Hills, constituting 78.3% of the region's population, and is the state's largest community, with around 48% of the population of Meghalaya. They are among the few Austroasiatic-speaking peoples in South Asia.
MeghalayaMeghalaya (ˌmeɪgəˈleɪə, or meɪˈgɑːləjə, meaning "abode of clouds"; from Sanskrit megha, "cloud" + ā-laya, "abode") is a state in northeast India. Meghalaya was formed on 21 January 1972 by carving out two districts from the state of Assam: (a) the United Khasi Hills and Jaintia Hills and (b) the Garo Hills. The population of Meghalaya as of 2014 is estimated to be 3,211,474. Meghalaya covers an area of approximately 22,429 square kilometres, with a length-to-breadth ratio of about 3:1.
Node.jsNode.js is a cross-platform, open-source server environment that can run on Windows, Linux, Unix, macOS, and more. Node.js is a back-end JavaScript runtime environment, runs on the V8 JavaScript engine, and executes JavaScript code outside a web browser. Node.js lets developers use JavaScript to write command line tools and for server-side scripting. The ability to run JavaScript code on the server is often used to generate dynamic web page content before the page is sent to the user's web browser.
Khasi languageKhasi (Ka Ktien Khasi) is an Austroasiatic language with just over a million speakers in north-east India, primarily the Khasi people in the state of Meghalaya. It has associate official status in some districts of this state. The closest relatives of Khasi are the other languages in the Khasic group of the Shillong Plateau; these include Pnar, Lyngngam and War. Khasi is written using the Latin and Bengali-Assamese scripts. Khasi is natively spoken by people in India (as of 2011).
Bayesian information criterionIn statistics, the Bayesian information criterion (BIC) or Schwarz information criterion (also SIC, SBC, SBIC) is a criterion for model selection among a finite set of models; models with lower BIC are generally preferred. It is based, in part, on the likelihood function and it is closely related to the Akaike information criterion (AIC). When fitting models, it is possible to increase the maximum likelihood by adding parameters, but doing so may result in overfitting.
Riemann integralIn the branch of mathematics known as real analysis, the Riemann integral, created by Bernhard Riemann, was the first rigorous definition of the integral of a function on an interval. It was presented to the faculty at the University of Göttingen in 1854, but not published in a journal until 1868. For many functions and practical applications, the Riemann integral can be evaluated by the fundamental theorem of calculus or approximated by numerical integration, or simulated using Monte Carlo Integration.
LinearityIn mathematics, the term linear is used in two distinct senses for two different properties: linearity of a function (or mapping ); linearity of a polynomial. An example of a linear function is the function defined by that maps the real line to a line in the Euclidean plane R2 that passes through the origin. An example of a linear polynomial in the variables and is Linearity of a mapping is closely related to proportionality. Examples in physics include the linear relationship of voltage and current in an electrical conductor (Ohm's law), and the relationship of mass and weight.
Microsoft OfficeMicrosoft Office, or simply Office, is a discontinued family of client software, server software, and services developed by Microsoft. It was first announced by Bill Gates on August 1, 1988, at COMDEX in Las Vegas. Initially a marketing term for an office suite (bundled set of productivity applications), the first version of Office contained Microsoft Word, Microsoft Excel, and Microsoft PowerPoint. Over the years, Office applications have grown substantially closer with shared features such as a common spell checker, Object Linking and Embedding data integration and Visual Basic for Applications scripting language.
Monotone convergence theoremIn the mathematical field of real analysis, the monotone convergence theorem is any of a number of related theorems proving the convergence of monotonic sequences (sequences that are non-decreasing or non-increasing) that are also bounded. Informally, the theorems state that if a sequence is increasing and bounded above by a supremum, then the sequence will converge to the supremum; in the same way, if a sequence is decreasing and is bounded below by an infimum, it will converge to the infimum.
Dominated convergence theoremIn measure theory, Lebesgue's dominated convergence theorem provides sufficient conditions under which almost everywhere convergence of a sequence of functions implies convergence in the L1 norm. Its power and utility are two of the primary theoretical advantages of Lebesgue integration over Riemann integration. In addition to its frequent appearance in mathematical analysis and partial differential equations, it is widely used in probability theory, since it gives a sufficient condition for the convergence of expected values of random variables.
Vitali convergence theoremIn real analysis and measure theory, the Vitali convergence theorem, named after the Italian mathematician Giuseppe Vitali, is a generalization of the better-known dominated convergence theorem of Henri Lebesgue. It is a characterization of the convergence in Lp in terms of convergence in measure and a condition related to uniform integrability. Let be a measure space, i.e. is a set function such that and is countably-additive. All functions considered in the sequel will be functions , where or .
Final value theoremIn mathematical analysis, the final value theorem (FVT) is one of several similar theorems used to relate frequency domain expressions to the time domain behavior as time approaches infinity. Mathematically, if in continuous time has (unilateral) Laplace transform , then a final value theorem establishes conditions under which Likewise, if in discrete time has (unilateral) Z-transform , then a final value theorem establishes conditions under which An Abelian final value theorem makes assumptions about the time-domain behavior of (or ) to calculate .
