Theoretical computer

Xem 1-20 trên 125 kết quả Theoretical computer
  • Eric H. Glendinning is Director of the Institute of Applied Linguistics at the University of Edinburgh in the UK. He has worked in teaching English in Tanzania, Norway, Nepal, and the United Kingdom and former Research Director of the Edinburgh Language Organization. John McEwan is the computer staff at the Institute of Applied Linguistics, University of Edinburgh. He is an experienced mathematics and physics teacher and teaching study skills, computers, and learning computer languages ​​supported in the EFL language schools.

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  • Although much of its discovery process is descriptive and qualitative, chemistry is fundamentally a quantitative science. It serves a wide range of human needs, activities, and concerns. The mathematical sciences provide the language for quantitative science, and this language is growing in many directions as computational science in general continues its rapid expansion. A timely opportunity now exists to strengthen and increase the beneficial impacts of chemistry by enhancing the interaction between chemistry and the mathematical sciences.

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  • The book is intended for computer science students, programmers and professionals who have already got acquainted with the basic courses and background on discrete mathematics. It may be used as a textbook for graduate course on theoretical computer science. The book introduces a reader to the conceptual framework for thinking about computations with the objects. The several areas of theoretical computer science are covered, including the following: type free and typed -calculus and combinatory logic with applications, evaluation of expressions, computations in a category.

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  • For over ten years, Richard Deal has operated his own company, The Deal Group Inc., in Oviedo, Florida, east of Orlando. Richard has over 20 years of experience in the computing and networking industry including networking, training, systems administration, and programming. In addition to a BS in Mathematics from Grove City College, he holds many certifications from Cisco and has taught many beginning and advanced Cisco classes.

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  • Computational fluid dynamics (CFD) is concerned with the efficient numerical solution of the partial differential equations that describe fluid dynamics. CFD techniques are commonly used in the many areas of engineering where fluid behavior is an important factor. Traditional fields of application include aerospace and automotive design, and more recently, bioengineering and consumer and medical electronics.

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  • For quite a long time, computer security was a rather narrow field of study that was populated mainly by theoretical computer scientists, electrical engineers, and applied mathematicians. With the proliferation of open systems in general, and of the Internet and the World Wide Web (WWW) in particular, this situation has changed fundamentally. Today, computer and network practitioners are equally interested in computer security, since they require technologies and solutions that can be used to secure applications related to electronic commerce.

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  • Evolutionary computation has been widely used in computer science for decades. Even though it started as far back as the 1960s with simulated evolution, the subject is still evolving. During this time, new metaheuristic optimization approaches, like evolutionary algorithms, genetic algorithms, swarm intelligence, etc., were being developed and new fields of usage in artificial intelligence, machine learning, combinatorial and numerical optimization, etc., were being explored.

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  • An enumeration of a collection of items is a complete, ordered listing of all of the items in that collection. The term is commonly used in mathematics and theoretical computer science to refer to a listing of all of the elements of a set. In statistics the term categorical variable is used rather than enumeration. The precise requirements for an enumeration (for example, whether the set must be finite, or whether the list is allowed to contain repetitions) depend on the branch of mathematics and the context in which one is working....

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  • Harvester Studies in Cognitive Science is a new series which will explore the nature of knowledge by way of a distinctive theoretical approach one that takes account of the complex structures and interacting processes that make thought and action possible. Intelligence can be studied from the point of view of psychology, philosophy, linguistics, pedagogy and artificial intelligence, and all these different emphases will be represented within the series.

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  • This book is about how to construct and use computational models of specific parts of the nervous system, such as a neuron, a part of a neuron or a network of neurons. It is designed to be read by people from a wide range of backgrounds from the biological, physical and computational sciences. The word ‘model’ can mean different things in different disciplines, and even researchers in the same field may disagree on the nuances of its meaning.

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  • We ship printed books within 1 business day; personal PDFs are available immediately. Mathematical Challenges from Theoretical/Computational Chemistry Committee on Mathematical Challenges from Computational Chemistry, National Research Council ISBN: 0-309-56064-0, 144 pages, 8.5 x 11, (1995) This PDF is available from the National Academies Press at:

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  • It is by now well established that quantum machines can solve certain computational problems much faster than the best algorithms known in the standard Turing machine model. The complexity question of which problems can be feasibly computed by quantum machines has also been extensively investigated in recent years, both in the context of one machine models (quantum polynomial classes) and various flavors of multi-machine models (single and multiple prover quantum interactive proofs).

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  • We describe a new loss function, due to Jeon and Lin (2006), for estimating structured log-linear models on arbitrary features. The loss function can be seen as a (generative) alternative to maximum likelihood estimation with an interesting information-theoretic interpretation, and it is statistically consistent. It is substantially faster than maximum (conditional) likelihood estimation of conditional random fields (Lafferty et al., 2001; an order of magnitude or more).

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  • Allan BORRA Software Technology Department De La Salle University 2401 Taft Avenue, Manila, Philippines languages spoken in Southern Philippines. But as of yet, extensive research has already been done on theoretical linguistics and little is known for computational linguistics. In fact, the computational linguistics researches on Philippine languages are mainly focused on Tagalog.1 There are also notable work done on Ilocano.

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  • Much effort has been put into computational lexicons over the years, and most systems give much room to (lexical) semantic data. However, in these systems, the effort put on the study and representation of lexical items to express the underlying continuum existing in 1) language vagueness and polysemy, and 2) language gaps and mismatches, has remained embryonic.

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  • An important goal of ntodent linguistic theory is to characterize as narrowly as possible the class of natural !anguaooes. An adequate linguistic theory should be broad enough to cover observed variation iu human languages, and yet narrow enough to account for what might be dubbed "cognitive demands" -- among these, perhaps, the demands of lcarnability and pars,ability. If cognitive demands are to carry any real theoretical weight, then presumably a language may be a (theoretically) pos~ible human language, and yet be "inaccessible" because it is not leanmble or pa~able. ...

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  • Model-theoretic semantics provides a computationally attractive means of representing the semantics of natural language. However, the models used in this formalism are static and are usually infinite. Dynamic models are incomplete models that include only the information needed for an application and to which information can be added. Dynamic models are basically approximations of larger conventional models, but differ is several interesting ways. The difference discussed here is the possibility of inconsistent information being included in the model. ...

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  • We present a game-theoretic model of bargaining over a metaphor in the context of political communication, find its equilibrium, and use it to rationalize observed linguistic behavior. We argue that game theory is well suited for modeling discourse as a dynamic resulting from a number of conflicting pressures, and suggest applications of interest to computational linguists.

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  • A computational vehicle for lexicography was designed to keep to the constraints of meaningtext theory: sets of lexical correlates, limits on the form of definitions, and argument relations similar to lexical-functional grA--~-r. Relational data bases look like a natural framework for this. But linguists operate with a nonnormalized view. Mappings between semantic actants and grammatical relations do not fit actant fields uniquely. Lexical correlates and examples are polyvalent, hence denormalized. ...

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  • Several important tendencies have been emerging recently in the NLP community. First of all, work on corpora tends to become the norm, which constitutes a fruitful convergence area between taskdriven, computational approaches and descriptive linguistic ones. On corpora validation becomes more and more important for theoretical models, and the accuracy of these models can be evaluated either with regard to their ability to account for the reality of a given corpus (pursuing descriptive aims), either with regard to their ability to analyse it accurately (pursuing operational aims). ...

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