Context Modeling
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Context Modeling
A context model (or context modeling) defines how context data are structured and maintained (It plays a key role in supporting efficient context management). It aims to produce a formal or semi-formal description of the context information that is present in a context-aware system. In other words, the context is the surrounding element for the system, and a model provides the mathematical interface and a behavioral description of the surrounding environment. It is used to represent the reusable context information of the components (The top level classes consist of Operating system, component container, hardware requirement and Software requirement). A key role of context model is to simplify and introduce greater structure into the task of developing context-aware applications. Examples of context models The Unified Modeling Language as used in systems engineering defines a context model as the physical scope of the system being designed, which could include the user as well as ...
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Context Awareness
Context awareness refers, in information and communication technologies, to a capability to take into account the ''situation'' of ''entities'', which may be users or devices, but are not limited to those. ''Location'' is only the most obvious element of this ''situation''. Narrowly defined for mobile devices, context awareness does thus generalize location awareness. Whereas location may determine how certain processes around a contributing device operate, context may be applied more flexibly with mobile users, especially with users of smart phones. Context awareness originated as a term from ubiquitous computing or as so-called pervasive computing which sought to deal with linking changes in the environment with computer systems, which are otherwise static. The term has also been applied to business theory in relation to contextual application design and business process management issues. Qualities of context Various categorizations of context have been proposed in the past. ...
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Deterministic
Determinism is a philosophical view, where all events are determined completely by previously existing causes. Deterministic theories throughout the history of philosophy have developed from diverse and sometimes overlapping motives and considerations. The opposite of determinism is some kind of indeterminism (otherwise called nondeterminism) or randomness. Determinism is often contrasted with free will, although some philosophers claim that the two are compatible.For example, see Determinism is often used to mean ''causal determinism'', which in physics is known as cause-and-effect. This is the concept that events within a given paradigm are bound by causality in such a way that any state of an object or event is completely determined by its prior states. This meaning can be distinguished from other varieties of determinism mentioned below. Debates about determinism often concern the scope of determined systems; some maintain that the entire universe is a single determinate ...
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Virtual Environment
A virtual environment is a networked application that allows a user to interact with both the computing environment and the work of other users. Email Electronic mail (email or e-mail) is a method of exchanging messages ("mail") between people using electronic devices. Email was thus conceived as the electronic ( digital) version of, or counterpart to, mail, at a time when "mail" meant ..., chat, and web-based document sharing applications are all examples of virtual environments. Simply put, it is a networked common operating space. Once the fidelity of the virtual environment is such that it "creates a psychological state in which the individual perceives himself or herself as existing within the virtual environment" (Blascovich, 2002, p. 129) then the virtual environment (VE) has progressed into the realm of immersive virtual environments (IVEs). References * Blascovich, J. (2002).Social Influence within Immersive Virtual Environments In R. Schroeder (Ed.), T ...
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Semantic Analysis (knowledge Representation)
Semantic analysis is a method for eliciting and representing knowledge about organisations. Liu Kecheng, (2000Semiotics in information systems engineering Cambridge University Press. Initially the problem must be defined by domain experts and passed to the project analyst(s). The next step is the generation of candidate affordances. This step will generate a list of semantic units that may be included in the schema. The candidate grouping follows where some of the semantic units that will appear in the schema are placed in simple groups. Finally the groups will be integrated together into an ontology chart. Semantic analysis always starts from the problem definition which if not clear, require the analyst to employ relevant literature, interviews with the stakeholders and other techniques towards collecting supplementary information. All assumptions made must be genuine and not limiting the system. See also * Semantic analysis (machine learning) * Ontology chart An ontol ...
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Ontology (information Science)
In computer science and information science, an ontology encompasses a representation, formal naming, and definition of the categories, properties, and relations between the concepts, data, and entities that substantiate one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of concepts and categories that represent the subject. Every academic discipline or field creates ontologies to limit complexity and organize data into information and knowledge. Each uses ontological assumptions to frame explicit theories, research and applications. New ontologies may improve problem solving within that domain. Translating research papers within every field is a problem made easier when experts from different countries maintain a controlled vocabulary of jargon between each of their languages. For instance, the definition and ontology of economics is a primary concern in Marxist econo ...
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Gene Sequence
In biology, the word gene (from , ; "...Wilhelm Johannsen coined the word gene to describe the Mendelian units of heredity..." meaning ''generation'' or ''birth'' or ''gender'') can have several different meanings. The Mendelian gene is a basic unit of heredity and the molecular gene is a sequence of nucleotides in DNA that is transcribed to produce a functional RNA. There are two types of molecular genes: protein-coding genes and noncoding genes. During gene expression, the DNA is first copied into RNA. The RNA can be directly functional or be the intermediate template for a protein that performs a function. The transmission of genes to an organism's offspring is the basis of the inheritance of phenotypic traits. These genes make up different DNA sequences called genotypes. Genotypes along with environmental and developmental factors determine what the phenotypes will be. Most biological traits are under the influence of polygenes (many different genes) as well as gene– ...
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Hidden Markov Model
A hidden Markov model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process — call it X — with unobservable ("''hidden''") states. As part of the definition, HMM requires that there be an observable process Y whose outcomes are "influenced" by the outcomes of X in a known way. Since X cannot be observed directly, the goal is to learn about X by observing Y. HMM has an additional requirement that the outcome of Y at time t=t_0 must be "influenced" exclusively by the outcome of X at t=t_0 and that the outcomes of X and Y at t handwriting recognition, handwriting, gesture recognition, part-of-speech tagging, musical score following, partial discharges and bioinformatics. Definition Let X_n and Y_n be discrete-time stochastic processes and n\geq 1. The pair (X_n,Y_n) is a ''hidden Markov model'' if * X_n is a Markov process whose behavior is not directly observable ("hidden"); * \operatorname\bigl(Y_n \i ...
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Stochastic
Stochastic (, ) refers to the property of being well described by a random probability distribution. Although stochasticity and randomness are distinct in that the former refers to a modeling approach and the latter refers to phenomena themselves, these two terms are often used synonymously. Furthermore, in probability theory, the formal concept of a ''stochastic process'' is also referred to as a ''random process''. Stochasticity is used in many different fields, including the natural sciences such as biology, chemistry, ecology, neuroscience, and physics, as well as technology and engineering fields such as image processing, signal processing, information theory, computer science, cryptography, and telecommunications. It is also used in finance, due to seemingly random changes in financial markets as well as in medicine, linguistics, music, media, colour theory, botany, manufacturing, and geomorphology. Etymology The word ''stochastic'' in English was originally used as a ...
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Context-sensitive Grammar
A context-sensitive grammar (CSG) is a formal grammar in which the left-hand sides and right-hand sides of any production rules may be surrounded by a context of terminal and nonterminal symbols. Context-sensitive grammars are more general than context-free grammars, in the sense that there are languages that can be described by CSG but not by context-free grammars. Context-sensitive grammars are less general (in the same sense) than unrestricted grammars. Thus, CSG are positioned between context-free and unrestricted grammars in the Chomsky hierarchy. A formal language that can be described by a context-sensitive grammar, or, equivalently, by a noncontracting grammar or a linear bounded automaton, is called a context-sensitive language. Some textbooks actually define CSGs as non-contracting, although this is not how Noam Chomsky defined them in 1959. This choice of definition makes no difference in terms of the languages generated (i.e. the two definitions are weakly equivalent), ...
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Operating System
An operating system (OS) is system software that manages computer hardware, software resources, and provides common services for computer programs. Time-sharing operating systems schedule tasks for efficient use of the system and may also include accounting software for cost allocation of processor time, mass storage, printing, and other resources. For hardware functions such as input and output and memory allocation, the operating system acts as an intermediary between programs and the computer hardware, although the application code is usually executed directly by the hardware and frequently makes system calls to an OS function or is interrupted by it. Operating systems are found on many devices that contain a computer from cellular phones and video game consoles to web servers and supercomputers. The dominant general-purpose personal computer operating system is Microsoft Windows with a market share of around 74.99%. macOS by Apple Inc. is in second place (14.84%), and ...
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Lexical Item
In lexicography, a lexical item is a single word, a part of a word, or a chain of words ( catena) that forms the basic elements of a language's lexicon (≈ vocabulary). Examples are ''cat'', ''traffic light'', ''take care of'', ''by the way'', and ''it's raining cats and dogs''. Lexical items can be generally understood to convey a single meaning, much as a lexeme, but are not limited to single words. Lexical items are like semes in that they are "natural units" translating between languages, or in learning a new language. In this last sense, it is sometimes said that language consists of grammaticalized lexis, and not lexicalized grammar. The entire store of lexical items in a language is called its lexis. Lexical items composed of more than one word are also sometimes called ''lexical chunks'', ''gambits'', ''lexical phrases'', ''lexicalized stems'', or ''speech formulae''. The term ''polyword listemes'' is also sometimes used. Types Common types of lexical items/chunks ...
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Grammar
In linguistics, the grammar of a natural language is its set of structure, structural constraints on speakers' or writers' composition of clause (linguistics), clauses, phrases, and words. The term can also refer to the study of such constraints, a field that includes domains such as phonology, morphology (linguistics), morphology, and syntax, often complemented by phonetics, semantics, and pragmatics. There are currently two different approaches to the study of grammar: traditional grammar and Grammar#Theoretical frameworks, theoretical grammar. Fluency, Fluent speakers of a variety (linguistics), language variety or ''lect'' have effectively internalized these constraints, the vast majority of which – at least in the case of one's First language, native language(s) – are language acquisition, acquired not by conscious study or language teaching, instruction but by hearing other speakers. Much of this internalization occurs during early childhood; learning a language later ...
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