词汇 | example_english_computer-science |
释义 | Examples of computer scienceThese examples are from corpora and from sources on the web. Any opinions in the examples do not represent the opinion of the Cambridge Dictionary editors or of Cambridge University Press or its licensors. The book is self-contained and the text is accessible to any graduate or undergraduate student of computerscience or engineering. We think also that some problems of confidentiality in computerscience involve the construction of a relative corner homology. The "meeting type" column shows that most of the teams have studied meetings in their domain of research, that is, computerscience or software design. Our work contributes to several areas of computerscience and engineering. It introduced to computerscience the important concept of declarative-as opposed to procedural-programming. This book is distinctly on the computerscience side of the middle of this range. It includes advanced programming, computerscience theory, databases, hardware and logic design and business applications. The authors make very few assumptions indeed about the computerscience knowledge and programming skills of their readers. As a discipline of computerscience, term rewriting has two main application areas: functional languages and their semantics; and equational reasoning and mechanical inference. He had a wide range of interests and was accomplished in areas outside of computerscience. The book is intended for graduate students, researchers, and practitioners in diverse areas of computerscience. There is other work in mainstream computerscience appears to be of relevance for multi-agent system specification and verification. Time-series analysis is routinely found in physics, electronics, geophysics, astrophysics, climatology, computerscience and biometric applications. This book discusses recent research in the theoretical foundations of several subjects of importance for the design hardware, and for computerscience in general. Faculty colleagues (inside and outside of computerscience) often have an emotional preference for a specific language in the introductory course. In theoretical computerscience, machine models and characterizations have been the basis for quantitative reasoning about the use of computational resources. It can be used as an introductory textbook or as a general reference for professionals in computerscience and logic. In law, in computerscience, in mathematics, in economics, in politics, there are many things that have nothing to do with game theory. The notion of event-based systems is used in many areas of computerscience. His areas of interest include evolutionary computation, quantum computation, and the intersections between computerscience, cognitive science, evolutionary biology, and the arts. Intensional logics of various types have already proven useful in different areas of computerscience, but mainly in artificial intelligence and verification (temporal logics). The above historical definitions record how the term ontology is more and more concrete and applicable in computerscience. But how unfair it would be to reduce computerscience to these archaic mistakes. But the distinction is crucial in computerscience. However, it is much less a limitation when dealing with objects of computerscience. The design and analysis of protocols is an area where traditionally computerscience has helped to supply standards. In computerscience they are much less popular. This model has been studied for decades and applied in diverse fields such as computerscience, biology, and statistics. Reurning to computerscience, we can apply the same reasoning to those formalisations that interpret mathematical entities as direct statements about the physical world. In the category theoretic semantics for computerscience, to any functor there corresponds a category of coalgebras of that functor. Because this paper was primarily written with an audience of computer scientists in mind, we tend to use computerscience notation instead of physics notation. Every step needs engineering rigour, based on sound computerscience and supported by formal quality control. In the second period, functional programming and parallelism are together trying to offer a solution to the big challenges in computerscience. It will provide an excellent tutorial text for computerscience, and a reference resource which will be valuable for practitioners writing programs in this field. The authors give several examples of this and it is also apparent from the computerscience theory of communicating systems, mentioned above. Search trees are fundamental data structures in computerscience. There is an extensive computerscience literature on multiway trees. Directions for further research, including just about every aspect of computerscience, are outlined. These classes consisted of computerscience students as well as students from other disciplines. Some students wish to learn what computerscience is about; others have three years of programming experience. From a computerscience perspective, the linear term calculus is interesting for several reasons. The notations the authors use in the various sections will be difficult for nonlinguists without background in computerscience to work through. Freely generated structures play a fundamental role in mathematics and computerscience. It is now a basic paradigm in denotational semantics in particular and in theoretical computerscience in general. Abstraction is the essence of computerscience and the key to software development. But one of the things that makes computerscience so much fun is that elegance and speed often go hand in hand. If it continues, it will surely lead to cynicism on the part of the computerscience community at large. The authors of the chapters come from diverse disciplines such as computerscience, cognitive and social psychology, philosophy and sociology. Many of the domains studied in computerscience do not have enough minimal limit elements. Without computerscience, would there still be any room left for logic? The functoriality referred to above seems a novelty in computerscience applications of algebraic topology. Next we apply some of its ideas to the formalisation of computerscience languages. This idea of the purpose of mathematical entities is not exclusive to computerscience. As already noted, we assume that the authors have a computerscience background, but no previous experience in natural language generation. We will concentrate on the case where the authors have a computerscience background. In computerscience we have distributed computing, in which there are many different processors. However, they are not equivalent from a computerscience point of view. The number of women studying mechanical and electrical engineering (which includes computerscience) has not changed significantly. The latter model is part of the foundations of theoretical computerscience, whereas the model used in our approach to model micro-architectures is relatively unknown. We follow here a widespread convention in theoretical computerscience that considers ground types as being of order 1. From the early nineties the study of persuasion dialogues was taken up in several fields of computerscience. Symbolic coding proved to be important both theoretically, for example by providing models for dynamical systems, and practically, for example in computerscience. Perhaps it is time to consider modern developments in ethology, experimental psychology, and computerscience that supersede the traditional structure. His primary research interests lie where the fields of biology and computerscience intersect. The emphasis is on the discrete optimization problem of checkpoint placement rather than their implementation from a computerscience perspective. The innovative use of computerscience technologies enables a smooth link of visual typological knowledge with the design goals. This review is aimed at researchers from different disciplines - microbiology, biology, chemistry, physics, mathematics and computerscience. Instead, patterns have found unexpected success in computerscience. Rapid recent advances in molecular genetics, imaging, statistical modeling, and computerscience are bringing a new horizon of research into view. Firstly, the approaches offer alternatives for artificial teams, but the chapters dealing with computerscience do not explicitly explore the collectivist team reasoning model. In the next corollaries we provide a 'computerscience' view of the previous result. Binary trees are, of course, one of the most basic data structures in computerscience. In computerscience, we often find problems where the discrete version is extremely difficult but where relaxation of discreteness makes for far greater tractability. The book is written for upper-year undergraduates or beginning graduate students specializing in theoretical computerscience, software systems, or mathematics. Many computerscience programs require at least one course in software engineering, and some require more. Perhaps surprisingly, some of the partners who do the code review have minimal training in programming and computerscience. The result is a type system for static control of access (and interference) that is close to computerscience expectations. A number of papers were also submitted targeting typical computerscience applications, such as building parsers, programming environments, and executable specifications. Despite this potential underlying coherence, the book of essays is quite an eclectic mix touching on many different topics in the foundations of computerscience. To have some impact on the real world and to stay relevant to computerscience, our community must communicate to and with other language communities. That book gave me deeper insights into computer languages than either my long ago introductory course in computerscience or the primary text itself. My colleagues are uniformly pleased with the course, and are amazed that nonmajors are able to learn so much computerscience. By now, the course had found its definitive form, and was introduced for all computerscience students at the start of the 1991/92 curriculum. It is for anyone who has a need to understand computerscience. Several examples of such structures occurring in computerscience are given. It summarizes the advantages of ontologies for computerscience applications, and describes the issues relative to formal ontology development. As with many modern textbooks on computerscience, the book itself is not the only resource that the authors provide. This definition describes how the philosophical nature of ontologies could be incorporated into computerscience. The ideas of the event-based style are used in a wide range of computerscience areas, although terminology and meaning vary. The notions of function, set and algorithm were available "off-the-shelf" from mathematics and logic for use in computerscience. With this volume we are honouring a scientist who can truly be said to have built bridges between mathematics and theoretical computerscience. These examples are from corpora and from sources on the web. Any opinions in the examples do not represent the opinion of the Cambridge Dictionary editors or of Cambridge University Press or its licensors. |
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