process+context

 

контекст процесса
Совокупность факторов, задокументированных на выходе оценки процесса, которая влияет на суждение о рейтингах атрибутов оценки процесса, их понимание и сравнение.
[ ГОСТ Р ИСО/МЭК 15504-1-2009]

Тематики

• информационные технологии в целом

EN

• process context

3.38 контекст процесса (process context): Совокупность факторов, задокументированных на выходе оценки процесса, которая влияет на суждение о рейтингах атрибутов оценки процесса, их понимание и сравнение.

Источник: ГОСТ Р ИСО/МЭК 15504-1-2009: Информационные технологии. Оценка процессов. Часть 1. Концепция и словарь оригинал документа

см. тж. execution context, process

1) (от лат. contextus - соединение) текущий статус, режим работы или состояние системы; текущее содержимое регистров и флагов процессора; окружение, среда исполнения программы; текущая ситуация и т. п. Контекст ЦП должен быть сохранён при возникновении прерывания и переключении на другую задачу или процесс (см. context switching)

см. тж. context awareness, context diagram, context help, context-sensitive, execution context, help context, process context, security context

2) фрагмент текста, имеющий определённый смысл

3) прил. контекстный, контекстуальный

см. тж. contextual

1) процесс

2) обработка; технологический процесс, технология (способ) обработки

см. тж. compilation process, computational process, development process, event process, process line, test process

3) процесс, ход развития

см. тж. stochastic process

4) обрабатывать

1) коммутация процессов

см. тж. CEF, circuit switching, dCEF, message switching, packet switching, fast packet switching

2) переключение процессов

см. тж. context switching, task switching

 

процесс общего планирования
Высокоуровневый процесс развития планирования Игр в период деятельности ОКОИ с момента основания и до роспуска. Этапы планирования с указанием точных сроков каждого определяются в соответствии со спецификой конкретного ОКОИ.
[Департамент лингвистических услуг Оргкомитета «Сочи 2014». Глоссарий терминов]

EN

generic planning process
High-level process that describes the evolution in the Games planning during the lifecycle of the OCOG from foundation through to dissolution. The exact planning phases and timing of each phase are adapted to fit the context of the specific OCOG.
[Департамент лингвистических услуг Оргкомитета «Сочи 2014». Глоссарий терминов]

Тематики

• спорт (управление Играми)

EN

• generic planning process

   1) Programs and the Complexity of Human Mental Processes

   In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)

   2) Artificial Intelligence Is an Engineering Discipline

   Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)

   3) A Sceptical View of Artificial Intelligence

   Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....

   When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)

   4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, Eventually

   Just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)

   5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the Program

   Many problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)

   6) The Meaning of a Symbolic Description

   What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)

   7) The Principle of Artificial Intelligence

   [AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)

   8) Artificial Intelligence Recognizes the Need for Knowledge in Its Systems

   The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)

   9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract Form

   The basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)

    10) There Are Many Types of Reasoning

   There are many different kinds of reasoning one might imagine:

    Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."

    Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)

    11) Programs Are Beginning to Do Things That Critics Have Asserted to Be Impossible

   Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)

    12) The Synthesis of Man and Machine

   Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)

    13) The Thesis of Good Old-Fashioned Artificial Intelligence (GOFAI)

   The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)

    14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory Formation

   It is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)

    15) Four Kinds of Artificial Intelligence

   We might distinguish among four kinds of AI.

   ♦ Nonpsychological AI

   Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.

   ♦ Weak Psychological AI

   Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.

   ♦ Strong Psychological AI

... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)

   ♦ Suprapsychological AI

   Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)

    16) Determination of Relevance of Rules in Particular Contexts

   Even if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)

    17) Form and Content Are Not Fundamentally Different

   Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)

    18) The Assumption That the Mind Is a Formal System

   Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)

    19) A Statement of the Primary and Secondary Purposes of Artificial Intelligence

   The primary goal of Artificial Intelligence is to make machines smarter.

   The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)

    20) Mathematical Logic Provides the Basis for Theory in AI

   The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....

   AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)

    21) Perceptual Structures Can Be Represented as Lists of Elementary Propositions

   In artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)

    22) Definitions of Artificial Intelligence

   Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)

    23) The Computer Can Not Be a Model of the Mind

   Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)

    24) Computers Will Not Always Be Inferior to Human Brains

   The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)

   1) The Book of Nature Is Written in the Language of Mathematics

   Philosophy is written in that great book, the universe, which is always open, right before our eyes. But one cannot understand this book without first learning to understand the language and to know the characters in which it is written. It is written in the language of mathematics, and the characters are triangles, circles, and other figures. Without these, one cannot understand a single word of it, and just wanders in a dark labyrinth. (Galileo, 1990, p. 232)

   2) Arranging Speech so as to Reply Appropriately

   It never happens that it [a nonhuman animal] arranges its speech in various ways in order to reply appropriately to everything that may be said in its presence, as even the lowest type of man can do. (Descartes, 1970a, p. 116)

   3) No Other Animal Has the Language Capacity of the Human

   It is a very remarkable fact that there are none so depraved and stupid, without even excepting idiots, that they cannot arrange different words together, forming of them a statement by which they make known their thoughts; while, on the other hand, there is no other animal, however perfect and fortunately circumstanced it may be, which can do the same. (Descartes, 1967, p. 116)

   4) Human Beings Do Not Live Only in the World of Objects

   Human beings do not live in the object world alone, nor alone in the world of social activity as ordinarily understood, but are very much at the mercy of the particular language which has become the medium of expression for their society. It is quite an illusion to imagine that one adjusts to reality essentially without the use of language and that language is merely an incidental means of solving specific problems of communication or reflection. The fact of the matter is that the "real world" is to a large extent unconsciously built on the language habits of the group.... We see and hear and otherwise experience very largely as we do because the language habits of our community predispose certain choices of interpretation. (Sapir, 1921, p. 75)

   5) Language Powerfully Conditions All Our Thinking

   It powerfully conditions all our thinking about social problems and processes.... No two languages are ever sufficiently similar to be considered as representing the same social reality. The worlds in which different societies live are distinct worlds, not merely the same worlds with different labels attached. (Sapir, 1985, p. 162)

   6) A List of Language Games

   [A list of language games, not meant to be exhaustive:]

   Giving orders, and obeying them- Describing the appearance of an object, or giving its measurements- Constructing an object from a description (a drawing)Reporting an eventSpeculating about an eventForming and testing a hypothesisPresenting the results of an experiment in tables and diagramsMaking up a story; and reading itPlay actingSinging catchesGuessing riddlesMaking a joke; and telling it

   Solving a problem in practical arithmeticTranslating from one language into another

   LANGUAGE Asking, thanking, cursing, greeting, and praying-. (Wittgenstein, 1953, Pt. I, No. 23, pp. 11 e-12 e)

   7) Language Constrains Certain Modes of Interpretation

   We dissect nature along lines laid down by our native languages.... The world is presented in a kaleidoscopic flux of impressions which has to be organized by our minds-and this means largely by the linguistic systems in our minds.... No individual is free to describe nature with absolute impartiality but is constrained to certain modes of interpretation even while he thinks himself most free. (Whorf, 1956, pp. 153, 213-214)

   8) We Dissect Nature in Accordance with Our Native Languages

   We dissect nature along the lines laid down by our native languages.

   The categories and types that we isolate from the world of phenomena we do not find there because they stare every observer in the face; on the contrary, the world is presented in a kaleidoscopic flux of impressions which has to be organized by our minds-and this means largely by the linguistic systems in our minds.... We are thus introduced to a new principle of relativity, which holds that all observers are not led by the same physical evidence to the same picture of the universe, unless their linguistic backgrounds are similar or can in some way be calibrated. (Whorf, 1956, pp. 213-214)

   9) The Forms of a Person's Thoughts Are Controlled by Unperceived Patterns of His Own Language

   The forms of a person's thoughts are controlled by inexorable laws of pattern of which he is unconscious. These patterns are the unperceived intricate systematizations of his own language-shown readily enough by a candid comparison and contrast with other languages, especially those of a different linguistic family. (Whorf, 1956, p. 252)

    10) The Analysis of Certain Types of Utterances

   It has come to be commonly held that many utterances which look like statements are either not intended at all, or only intended in part, to record or impart straightforward information about the facts.... Many traditional philosophical perplexities have arisen through a mistake-the mistake of taking as straightforward statements of fact utterances which are either (in interesting non-grammatical ways) nonsensical or else intended as something quite different. (Austin, 1962, pp. 2-3)

    11) The Dictionary of a Language Is a System of Concepts

   In general, one might define a complex of semantic components connected by logical constants as a concept. The dictionary of a language is then a system of concepts in which a phonological form and certain syntactic and morphological characteristics are assigned to each concept. This system of concepts is structured by several types of relations. It is supplemented, furthermore, by redundancy or implicational rules..., representing general properties of the whole system of concepts.... At least a relevant part of these general rules is not bound to particular languages, but represents presumably universal structures of natural languages. They are not learned, but are rather a part of the human ability to acquire an arbitrary natural language. (Bierwisch, 1970, pp. 171-172)

    12) Talk about the Evolution of the Language Capacity is Beside the Point

   In studying the evolution of mind, we cannot guess to what extent there are physically possible alternatives to, say, transformational generative grammar, for an organism meeting certain other physical conditions characteristic of humans. Conceivably, there are none-or very few-in which case talk about evolution of the language capacity is beside the point. (Chomsky, 1972, p. 98)

    13) The Development of Language

   [It is] truth value rather than syntactic well-formedness that chiefly governs explicit verbal reinforcement by parents-which renders mildly paradoxical the fact that the usual product of such a training schedule is an adult whose speech is highly grammatical but not notably truthful. (R. O. Brown, 1973, p. 330)

    14) Sentential and Conceptual Levels in Language

   he conceptual base is responsible for formally representing the concepts underlying an utterance.... A given word in a language may or may not have one or more concepts underlying it.... On the sentential level, the utterances of a given language are encoded within a syntactic structure of that language. The basic construction of the sentential level is the sentence.

   The next highest level... is the conceptual level. We call the basic construction of this level the conceptualization. A conceptualization consists of concepts and certain relations among those concepts. We can consider that both levels exist at the same point in time and that for any unit on one level, some corresponding realizate exists on the other level. This realizate may be null or extremely complex.... Conceptualizations may relate to other conceptualizations by nesting or other specified relationships. (Schank, 1973, pp. 191-192)

    15) Linguistic Realities Have Not Yet Been Captured by Theoretical Models

   The mathematics of multi-dimensional interactive spaces and lattices, the projection of "computer behavior" on to possible models of cerebral functions, the theoretical and mechanical investigation of artificial intelligence, are producing a stream of sophisticated, often suggestive ideas.

   But it is, I believe, fair to say that nothing put forward until now in either theoretic design or mechanical mimicry comes even remotely in reach of the most rudimentary linguistic realities. (Steiner, 1975, p. 284)

    16) The Final Steps to Human Language

   The step from the simple tool to the master tool, a tool to make tools (what we would now call a machine tool), seems to me indeed to parallel the final step to human language, which I call reconstitution. It expresses in a practical and social context the same understanding of hierarchy, and shows the same analysis by function as a basis for synthesis. (Bronowski, 1977, pp. 127-128)

    17) The Inadequacy of Formal Linguistic Models for Ordinary Language Usage

    t is the language donn eґ in which we conduct our lives.... We have no other. And the danger is that formal linguistic models, in their loosely argued analogy with the axiomatic structure of the mathematical sciences, may block perception.... It is quite conceivable that, in language, continuous induction from simple, elemental units to more complex, realistic forms is not justified. The extent and formal "undecidability" of context-and every linguistic particle above the level of the phoneme is context-bound-may make it impossible, except in the most abstract, meta-linguistic sense, to pass from "pro-verbs," "kernals," or "deep deep structures" to actual speech. (Steiner, 1975, pp. 111-113)

    18) When a Language Is an Abstract Machine

   A higher-level formal language is an abstract machine. (Weizenbaum, 1976, p. 113)

    19) Metaphor and Metonymy Underpin the Formation of Linguistic Signs

   Jakobson sees metaphor and metonymy as the characteristic modes of binarily opposed polarities which between them underpin the two-fold process of selection and combination by which linguistic signs are formed.... Thus messages are constructed, as Saussure said, by a combination of a "horizontal" movement, which combines words together, and a "vertical" movement, which selects the particular words from the available inventory or "inner storehouse" of the language. The combinative (or syntagmatic) process manifests itself in contiguity (one word being placed next to another) and its mode is metonymic. The selective (or associative) process manifests itself in similarity (one word or concept being "like" another) and its mode is metaphoric. The "opposition" of metaphor and metonymy therefore may be said to represent in effect the essence of the total opposition between the synchronic mode of language (its immediate, coexistent, "vertical" relationships) and its diachronic mode (its sequential, successive, lineal progressive relationships). (Hawkes, 1977, pp. 77-78)

    20) Language and the Analysis of Nature

   It is striking that the layered structure that man has given to language constantly reappears in his analyses of nature. (Bronowski, 1977, p. 121)

    21) Correspondence Rules for Mapping Old Theory into Subsets of New Theory

   First, [an ideal intertheoretic reduction] provides us with a set of rules"correspondence rules" or "bridge laws," as the standard vernacular has it-which effect a mapping of the terms of the old theory (T o) onto a subset of the expressions of the new or reducing theory (T n). These rules guide the application of those selected expressions of T n in the following way: we are free to make singular applications of their correspondencerule doppelgangers in T o....

   Second, and equally important, a successful reduction ideally has the outcome that, under the term mapping effected by the correspondence rules, the central principles of T o (those of semantic and systematic importance) are mapped onto general sentences of T n that are theorems of Tn. (P. Churchland, 1979, p. 81)

    22) The Inclusion of Non- linguistic Factors in a Theory of Grammar

   If non-linguistic factors must be included in grammar: beliefs, attitudes, etc. [this would] amount to a rejection of the initial idealization of language as an object of study. A priori such a move cannot be ruled out, but it must be empirically motivated. If it proves to be correct, I would conclude that language is a chaos that is not worth studying.... Note that the question is not whether beliefs or attitudes, and so on, play a role in linguistic behavior and linguistic judgments... [but rather] whether distinct cognitive structures can be identified, which interact in the real use of language and linguistic judgments, the grammatical system being one of these. (Chomsky, 1979, pp. 140, 152-153)

    23) Language Is Inevitably Influenced by Specific Contexts of Human Interaction

   Language cannot be studied in isolation from the investigation of "rationality." It cannot afford to neglect our everyday assumptions concerning the total behavior of a reasonable person.... An integrational linguistics must recognize that human beings inhabit a communicational space which is not neatly compartmentalized into language and nonlanguage.... It renounces in advance the possibility of setting up systems of forms and meanings which will "account for" a central core of linguistic behavior irrespective of the situation and communicational purposes involved. (Harris, 1981, p. 165)

    24) The Genetic Blueprints of Language

   By innate [linguistic knowledge], Chomsky simply means "genetically programmed." He does not literally think that children are born with language in their heads ready to be spoken. He merely claims that a "blueprint is there, which is brought into use when the child reaches a certain point in her general development. With the help of this blueprint, she analyzes the language she hears around her more readily than she would if she were totally unprepared for the strange gabbling sounds which emerge from human mouths. (Aitchison, 1987, p. 31)

    25) Languages Are Machines

   Looking at ourselves from the computer viewpoint, we cannot avoid seeing that natural language is our most important "programming language." This means that a vast portion of our knowledge and activity is, for us, best communicated and understood in our natural language.... One could say that natural language was our first great original artifact and, since, as we increasingly realize, languages are machines, so natural language, with our brains to run it, was our primal invention of the universal computer. One could say this except for the sneaking suspicion that language isn't something we invented but something we became, not something we constructed but something in which we created, and recreated, ourselves. (Leiber, 1991, p. 8)

   1) All Human Complex Problem Solving Is Creativity

   Put in this bald way, these aims sound utopian. How utopian they areor rather, how imminent their realization-depends on how broadly or narrowly we interpret the term "creative." If we are willing to regard all human complex problem solving as creative, then-as we will point out-successful programs for problem solving mechanisms that simulate human problem solvers already exist, and a number of their general characteristics are known. If we reserve the term "creative" for activities like discovery of the special theory of relativity or the composition of Beethoven's Seventh Symphony, then no example of a creative mechanism exists at the present time. (Simon, 1979, pp. 144-145)

   2) Artificial Intelligence Models of Creative Association

   Among the questions that can now be given preliminary answers in computational terms are the following: how can ideas from very different sources be spontaneously thought of together? how can two ideas be merged to produce a new structure, which shows the influence of both ancestor ideas without being a mere "cut-and-paste" combination? how can the mind be "primed," so that one will more easily notice serendipitous ideas? why may someone notice-and remember-something fairly uninteresting, if it occurs in an interesting context? how can a brief phrase conjure up an entire melody from memory? and how can we accept two ideas as similar ("love" and "prove" as rhyming, for instance) in respect of a feature not identical in both? The features of connectionist AI models that suggest answers to these questions are their powers of pattern completion, graceful degradation, sensitization, multiple constraint satisfaction, and "best-fit" equilibration.... Here, the important point is that the unconscious, "insightful," associative aspects of creativity can be explained-in outline, at least-by AI methods. (Boden, 1996, p. 273)

   3) Creative Innovation and Social Independence

   There thus appears to be an underlying similarity in the process involved in creative innovation and social independence, with common traits and postures required for expression of both behaviors. The difference is one of product-literary, musical, artistic, theoretical products on the one hand, opinions on the other-rather than one of process. In both instances the individual must believe that his perceptions are meaningful and valid and be willing to rely upon his own interpretations. He must trust himself sufficiently that even when persons express opinions counter to his own he can proceed on the basis of his own perceptions and convictions. (Coopersmith, 1967, p. 58)

   4) Ego Strength and Emotional Stability among Creative Geniuses

   he average level of ego strength and emotional stability is noticeably higher among creative geniuses than among the general population, though it is possibly lower than among men of comparable intelligence and education who go into administrative and similar positions. High anxiety and excitability appear common (e.g. Priestley, Darwin, Kepler) but full-blown neurosis is quite rare. (Cattell & Butcher, 1970, p. 315)

   5) Its Mundane Character

   he insight that is supposed to be required for such work as discovery turns out to be synonymous with the familiar process of recognition; and other terms commonly used in the discussion of creative work-such terms as "judgment," "creativity," or even "genius"-appear to be wholly dispensable or to be definable, as insight is, in terms of mundane and well-understood concepts. (Simon, 1989, p. 376)

   6) Mozart's Musical Ideas Came to Him in Polished Form

   From the sketch material still in existence, from the condition of the fragments, and from the autographs themselves we can draw definite conclusions about Mozart's creative process. To invent musical ideas he did not need any stimulation; they came to his mind "ready-made" and in polished form. In contrast to Beethoven, who made numerous attempts at shaping his musical ideas until he found the definitive formulation of a theme, Mozart's first inspiration has the stamp of finality. Any Mozart theme has completeness and unity; as a phenomenon it is a Gestalt. (Herzmann, 1964, p. 28)

   7) Scientific Theories and Works of Art Alike Originate in Fantasy

   Great artists enlarge the limits of one's perception. Looking at the world through the eyes of Rembrandt or Tolstoy makes one able to perceive aspects of truth about the world which one could not have achieved without their aid. Freud believed that science was adaptive because it facilitated mastery of the external world; but was it not the case that many scientific theories, like works of art, also originated in phantasy? Certainly, reading accounts of scientific discovery by men of the calibre of Einstein compelled me to conclude that phantasy was not merely escapist, but a way of reaching new insights concerning the nature of reality. Scientific hypotheses require proof; works of art do not. Both are concerned with creating order, with making sense out of the world and our experience of it. (Storr, 1993, p. xii)

   8) Self- Esteem and Creative Expression

   The importance of self-esteem for creative expression appears to be almost beyond disproof. Without a high regard for himself the individual who is working in the frontiers of his field cannot trust himself to discriminate between the trivial and the significant. Without trust in his own powers the person seeking improved solutions or alternative theories has no basis for distinguishing the significant and profound innovation from the one that is merely different.... An essential component of the creative process, whether it be analysis, synthesis, or the development of a new perspective or more comprehensive theory, is the conviction that one's judgment in interpreting the events is to be trusted. (Coopersmith, 1967, p. 59)

   9) Stages in Creative Problem- Solving

   In the daily stream of thought these four different stages [preparation; incubation; illumination or inspiration; and verification] constantly overlap each other as we explore different problems. An economist reading a Blue Book, a physiologist watching an experiment, or a business man going through his morning's letters, may at the same time be "incubating" on a problem which he proposed to himself a few days ago, be accumulating knowledge in "preparation" for a second problem, and be "verifying" his conclusions to a third problem. Even in exploring the same problem, the mind may be unconsciously incubating on one aspect of it, while it is consciously employed in preparing for or verifying another aspect. (Wallas, 1926, p. 81)

    10) The Bisociative Pattern of the Creative Synthesis

   he basic, bisociative pattern of the creative synthesis [is] the sudden interlocking of two previously unrelated skills, or matrices of thought. (Koestler, 1964, p. 121)

    11) The Earliest Stages in the Creative Process Involve a Commerce with Disorder

   Even to the creator himself, the earliest effort may seem to involve a commerce with disorder. For the creative order, which is an extension of life, is not an elaboration of the established, but a movement beyond the established, or at least a reorganization of it and often of elements not included in it. The first need is therefore to transcend the old order. Before any new order can be defined, the absolute power of the established, the hold upon us of what we know and are, must be broken. New life comes always from outside our world, as we commonly conceive that world. This is the reason why, in order to invent, one must yield to the indeterminate within him, or, more precisely, to certain illdefined impulses which seem to be of the very texture of the ungoverned fullness which John Livingston Lowes calls "the surging chaos of the unexpressed." (Ghiselin, 1985, p. 4)

    12) The Inner Life of the Creative Process

   New life comes always from outside our world, as we commonly conceive our world. This is the reason why, in order to invent, one must yield to the indeterminate within him, or, more precisely, to certain illdefined impulses which seem to be of the very texture of the ungoverned fullness which John Livingston Lowes calls "the surging chaos of the unexpressed." Chaos and disorder are perhaps the wrong terms for that indeterminate fullness and activity of the inner life. For it is organic, dynamic, full of tension and tendency. What is absent from it, except in the decisive act of creation, is determination, fixity, and commitment to one resolution or another of the whole complex of its tensions. (Ghiselin, 1952, p. 13)

    13) The Problem of What Impels the Creative Person

   [P]sychoanalysts have principally been concerned with the content of creative products, and with explaining content in terms of the artist's infantile past. They have paid less attention to examining why the artist chooses his particular activity to express, abreact or sublimate his emotions. In short, they have not made much distinction between art and neurosis; and, since the former is one of the blessings of mankind, whereas the latter is one of the curses, it seems a pity that they should not be better differentiated....

   Psychoanalysis, being fundamentally concerned with drive and motive, might have been expected to throw more light upon what impels the creative person that in fact it has. (Storr, 1993, pp. xvii, 3)

    14) Theories of Creative Thinking

   A number of theoretical approaches were considered. Associative theory, as developed by Mednick (1962), gained some empirical support from the apparent validity of the Remote Associates Test, which was constructed on the basis of the theory.... Koestler's (1964) bisociative theory allows more complexity to mental organization than Mednick's associative theory, and postulates "associative contexts" or "frames of reference." He proposed that normal, non-creative, thought proceeds within particular contexts or frames and that the creative act involves linking together previously unconnected frames.... Simonton (1988) has developed associative notions further and explored the mathematical consequences of chance permutation of ideas....

   Like Koestler, Gruber (1980; Gruber and Davis, 1988) has based his analysis on case studies. He has focused especially on Darwin's development of the theory of evolution. Using piagetian notions, such as assimilation and accommodation, Gruber shows how Darwin's system of ideas changed very slowly over a period of many years. "Moments of insight," in Gruber's analysis, were the culminations of slow long-term processes.... Finally, the information-processing approach, as represented by Simon (1966) and Langley et al. (1987), was considered.... [Simon] points out the importance of good problem representations, both to ensure search is in an appropriate problem space and to aid in developing heuristic evaluations of possible research directions.... The work of Langley et al. (1987) demonstrates how such search processes, realized in computer programs, can indeed discover many basic laws of science from tables of raw data.... Boden (1990a, 1994) has stressed the importance of restructuring the problem space in creative work to develop new genres and paradigms in the arts and sciences. (Gilhooly, 1996, pp. 243-244; emphasis in original)

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a technique that requires the use of a scenario in the process of strategic planning to aid the development of corporate strategy in the face of uncertainty about the future. Scenario planning was developed in a military context during the 1940s. Its use in a business context was pioneered at Royal Dutch Shell during the 1960s and increased after the 1972 oil crisis. The process of identifying alternative scenarios of the future, based on a variety of differing assumptions, can help managers anticipate changes in the business environment and raise awareness of the frame of reference within which they are operating. The scenarios are then used to assist in both the development of strategies for dealing with unexpected events and the choice between alternative strategic options.

 

зависимости
—
[ http://slovarionline.ru/anglo_russkiy_slovar_neftegazovoy_promyishlennosti/]

Тематики

• нефтегазовая промышленность

EN

• function

 

мн. должностные обязанности
—
[А.С.Гольдберг. Англо-русский энергетический словарь. 2006 г.]

Тематики

• энергетика в целом

EN

• function
• func
• function

 

направления деятельности системы управления
Пять основных направлений в командной системе по устранению последствий инцидента, то есть командование, действия, планирование, логистика и финансово-административное управление.
Примечание
Термин "функционирование" также используют при описании сопутствующей активности, например планирования.
[ ГОСТ Р 53389-2009]

Тематики

• защита морской среды

Обобщающие термины

• система управления в случае инцидента

EN

• function

 

функционирование
Корректное выполнение предназначения – «компьютер функционирует».
[Словарь терминов ITIL версия 1.0, 29 июля 2011 г.]

EN

function
To perform the intended purpose correctly, as in «The computer is functioning».
[Словарь терминов ITIL версия 1.0, 29 июля 2011 г.]

Тематики

• информационные технологии в целом

EN

• function

 

функция
Команда или группа людей, а также инструментарий или другие ресурсы, которые они используют для выполнения одного или нескольких процессов или деятельности. Например, служба поддержки пользователей. Этот термин также имеет другое значение: предназначение конфигурационной единицы, человека, команды, процесса или ИТ-услуги. Например, одна из функций услуги электронной почты может заключаться в сохранении и пересылке исходящей почты, тогда как функция бизнес-процесса может заключаться в отправке товаров заказчикам.
[Словарь терминов ITIL версия 1.0, 29 июля 2011 г.]

функция
Синоним термина функциональное направление деятельности.
[Департамент лингвистических услуг Оргкомитета «Сочи 2014». Глоссарий терминов]

функция
1. Зависимая переменная величина; 2. Соответствие y=f(x) между переменными величинами, в силу которого каждому рассматриваемому значению некоторой величины x (аргумента или независимой переменной) соответствует определенное значение другой величины y (зависимой переменной или Ф. в значении 1.). Ф. задана, если известен закон, определяющий такое соответствие. На практике она задается формулой, таблицей или графиком (есть и другие способы, например, алгоритмический — см. Алгоритм). При построении графика функции анализируются такие ее свойства, как четность или нечетность, нулевые значения, периодичность (см. Периодическая функция), монотонность (см. Монотонная функция), наличие асимптоты и другие. Важны еще два часто употребляемых понятия: функция, заданная в виде уравнения f(x,y) =0, неразрешенного относительно y, называется неявной; функция, заданная в виде y= f(g(x), то есть функция функции, называется сложной Ф. или, иначе, суперпозицией функций g и f. (См. также Функционал). Сложную функцию часто записывают в виде y=f(u), где u=g(x), при этом u называют промежуточным аргументом. Множество значений аргументов функции X (x ? X) называется областью определения функции, а, соответственно, множество Y — областью значений функции или областью изменения функции. См. также Отображение. В различных экономических приложениях применяются (и рассматриваются в словаре), следующие функции: Взвешивающие, Дифференцируемые, Гладкие, Кусочно-линейные, Кусочно-непрерывные, Линейные, Нелинейные, Непрерывные, Сепарабельные, Экспоненты и др. См. также: Вектор-функция, Гессиан, Мультипликативная форма представления функции, Производная, Рекурсия, Частная производная, Эластичность функции, Якобиан, Интеграл.
[ http://slovar-lopatnikov.ru/]

EN

function
A team or group of people and the tools or other resources they use to carry out one or more processes or activities – for example, the service desk. The term also has two other meanings: • An intended purpose of a configuration item, person, team, process or IT service. For example, one function of an email service may be to store and forward outgoing mails, while the function of a business process may be to despatch goods to customers.
[Словарь терминов ITIL версия 1.0, 29 июля 2011 г.]

function
Another term for functional area.
[Департамент лингвистических услуг Оргкомитета «Сочи 2014». Глоссарий терминов]

Тематики

• информационные технологии в целом
• спорт (управление Играми)
• экономика

EN

• feature
• function

 

функция (сети и системы связи)
Задача, выполняемая системой автоматизации подстанции, то есть прикладными функциями.
Примечание 1. Обычно функции обмениваются данными с другими функциями. Функции выполняются интеллектуальными электронными устройствами (физическими устройствами).
Примечание 2. Функция может быть разделена на части, которые резидентно находятся в интеллектуальных электронных устройствах, но сообщаются друг с другом и с частями других функций. Эти сообщающиеся части называются логическими узлами.
Примечание 3. В контексте стандартов серии "Сети и системы связи на подстанциях" декомпозиция функций или степень их детализации определяется только характером связи. Это означает, что все функции состоят из логических узлов, которые обмениваются данными.
[ ГОСТ Р 54325-2011 (IEC/TS 61850-2:2003)]

EN

function(s)
task(s) performed by the substation automation system i.e. by application functions. Generally, functions exchange data with other functions. Details are dependant on the functions involved. Functions are performed by IEDs (physical devices). A function may be split into parts residing in different IEDs but communicating with each other (distributed function) and with parts of other functions. These communicating parts are called logical nodes.

In the context of this standard, the decomposition of functions or their granularity is ruled by the communication behaviour only. Therefore, all functions considered consist of logical nodes that exchange data. Functions without an explicit reference to logical nodes mean only that in the actual context, the logical node modelling of these functions is of no importance to the standard
[IEC 61850-2, ed. 1.0 (2003-08)]

Тематики

• релейная защита

EN

• function

 

часть команды, определяющая действия адресуемого абонента (во время интерфейсной операции)
—
[Е.С.Алексеев, А.А.Мячев. Англо-русский толковый словарь по системотехнике ЭВМ. Москва 1993]

Тематики

• информационные технологии в целом

EN

• function

 

шина магистрали, несущая Информацию, определяющую действие во время интерфейсной операции
—
[Е.С.Алексеев, А.А.Мячев. Англо-русский толковый словарь по системотехнике ЭВМ. Москва 1993]

Тематики

• информационные технологии в целом

EN

• function

2.1 функция (function): Реализация в программе алгоритма, по которому пользователь или программа могут частично или полностью выполнять решаемую задачу.

Примечания

1 Пользователю нет необходимости вызывать функцию (например, автоматическое резервирование или сохранение данных).

2 Определение функции в настоящем стандарте уже, чем в ИСО/МЭК 2382-14 [9] (в части определений отказа, сбоя, эксплуатации и надежности), но шире аналогичных определений в ИСО 2382-2 [10] и ИСО 2382-15 [11].

Источник: ГОСТ Р ИСО/МЭК 12119-2000: Информационная технология. Пакеты программ. Требования к качеству и тестирование оригинал документа

3.7 функция (function): Конкретная цель или предназначенная для выполнения задача, которая может быть установлена или описана без ссылок на физические средства ее достижения.

Источник: ГОСТ Р МЭК 61226-2011: Атомные станции. Системы контроля и управления, важные для безопасности. Классификация функций контроля и управления оригинал документа

in accordance with 1. в соответствии с

in addition to that вместе с тем

in advance 1. заранее; заблаговременно

Supplier shall notify the Contractor sufficiently in advance of any fabricating operations Обо всех производственных операциях Поставщик заблаговременно извещает Подрядчика 2. авансом (т.е. "вперед", в отличие от in arrears- см.)

in all ways 1. во всех отношениях 2. с любой точки зрения

in ample time заблаговременно ( с оттенком задолго до, с большим запасом [ по времени])

in analysis based on limit load при расчете по предельным нагрузкам

in anticipation 1. исподволь 2. заблаговременно

in arrears по факту (т.е. по истечении какого-то времени, «потом», в отличие от in advance - см)

in attendance Those in attendance included Присутствовали:...

in basic terms вообще говоря; в общем и целом; как правило

in block letters печатными буквами

in the blueprint stage в стадии проектирования (перен. в стадии планирования, "на бумаге"; в отличие от in the hardware stage - см.)

in bulk quantities в товарных количествах

in case a (

the)

in case of eye contact при попадании в глаза (опасного / вредного вещества /материала)

in case of ingestion при попадании внутрь (опасного / вредного вещества /материала)

in case of inhalation при вдыхании (опасного / вредного вещества / материала)

in case of respiratory standstill при остановке дыхания

in case of skin contact при попадании на кожу (опасного /вредного вещества /материала)

in case of swallowing при проглатывании (опасного /вредного вещества /материала)

in the clear: be sure all personnel are in the clear убедиться в том, что весь персонал находится в безопасности (т.е. вне опасности, на безопасном расстоянии и т.д.)

in codex form в форме книги

in compliance with по (напр., нормам, ТУ и т.д.);

in conclusion, В заключение...

in a condensed form в сжатой форме

in conflict with: In conflict with this is... ( в начале предлож.) В то же время...; Вместе с тем...

in conformance to по (напр., нормам, ТУ и т.д.)

in conjunction with 1. параллельно с

in connection with 1. в свете... 2. в контексте чего-л. 3. in connection with Fig. 13... Если обратиться к рис. 13...

in consideration of 1. принимая во внимание 2. учитывая

in a conspicuous location на видном месте

in a conspicuous place на видном месте

in a conspicuous position на видном месте

in consultation with по согласованию с; по договоренности с

in contemplation of в преддверии чего-л.;

in the context of 1. в связи с; в свете; в плане 2. применительно к 3. если иметь в виду; с учетом 4. на примере 5. с точки зрения 6. в случае 7. в отношении 8. в области 9. в рамках

in continuation of в развитие чего-л.

in contradiction with противоречащий чему-л.

in contrast (npomueum.) 1. же

in contrast to в отличие от; в то время как; что же касается

in control не выходящий за установленные предельные значения (напр., о размерах, механических свойствах, технологических параметрах и т.д.)

in a controlled manner организованно

in a criss-cross pattern по перекрестной схеме ( затяжка болтов - для обеспечения равномерной затяжки)

in a customary manner обычным способом; по обычной схеме; тривиально

in a design situation при проектировании

in diction словами; на обычном языке; открытым текстом (т.е. не кодом)

in a direction parallel to по ходу (напр., трубопровода)

in document format отдельным изданием

in domestic experience в отечественной практике

in due time в установленные сроки; своевременно

in effect по существу

in either direction в любом направлении

in excess больше ( чем нужно);

in excess of 1. не укладывающийся в 2. сверх чего-л.

in an expedient manner оперативно

in fact более того,...

in force действующий (напр., законодательство, договор и т.д.)

in the field на монтаже ( а не па заводе или на производстве)

in the first place вообще

in foreseeable future в обозримом будущем

in formative stage в стадии становления

in free format в произвольном виде

in full detail исчерпывающе; исчерпывающим образом; исчерпывающе подробно; с исчерпывающей полнотой

in full standing полноправный

in full view в пределах прямой видимости (зд. «прямо» означает не впереди, перед, а незаслоненный, незагороженный)

in furtherance of в продолжение чего-л.;

in furtherance to в развитие чего-л.;

in furtherance to your letter dated01.15.2004 в развитие Вашего письма от 15.01.2004 г.

in ( the) future 1. со временем; впоследствии 2. в перспективе

in general: A does not in general correspond to В А не всегда соответствует В

in general terms вообще говоря

in the generic sense собирательно

in good order в полной исправности; в исправном рабочем состоянии;

in good standing полноправный

in a gradual manner плавно;

in greater detail намного / гораздо полнее

in hand (см. тж. on hand) наличный; имеющийся

in the hardware stage в стадии конструктивной сборки (в отличие от in the blueprint stage - см.)

in hidden form (матем.) в неявном виде; в неявной форме

in the initial stages на первых порах

in isolation автономно

in the judgment of по мнению

in line with 1. в увязке с

in the long run в перспективе

in a... manner: in a gradual and uniform manner плавно и равномерно

in a masterful way мастерски

in the mean в обычном смысле

in the melting-pot: be in the melting-pot находиться в стадии решения / принятия решения

in a modification в другом исполнении

in multiples of в количестве

in the near term в краткосрочной перспективе

in need of нуждающийся в чем-л.;

in no case ни при каких обстоятельствах

in a non-discriminative manner непредвзято

in no time в сжатые сроки

in no way никоим образом не

in operation задействованный;

in an orderly manner организованно; в организованном порядке

in outline в общих чертах

in one's own element в своей сфере

in one's own milieu в своей сфере

in particular в первую очередь; прежде всего

in passing заметим в скобках; заметим попутно; между прочим

in person лично

1) be in place 1. иметь наготове; представлять (документы, согласования и т.д.) 2. (описат.) используемый (реально, фактически)

2) have in place располагать (чем-л.)

3) put in place 1. внедрять; вводить в действие; внедрять в практику 2. реализовывать 3. выполнять ( фактически); осуществлять 4. задействовать; (перен..) запускать (напр., процесс перехода на новый материал)

1) case in point характерный пример; образчик; эпизод

2) tool in point подходящее / нужное / соответствующее средство

in the present circumstances 1. в данном случае 2. в этих условиях

in ( the) press готовится к печати

in progress быть ( пока) незавершенным

in pursuance of: 1. следуя (напр., нашему плану) 2. in pursuance of your letter dated01.15.2004 в связи с Вашим письмом от 15.01.2004 г.; в контексте Вашего письма от 15.01.2004 г. 3. in pursuance of your orders во исполнение Ваших указаний

in pursuance to в ответ на;

in question рассматриваемый

in receipt of: We are in receipt of your letter dated Мы получили Ваше письмо от...

in recent years в последние годы

in recognition of 1. отдавая должное 2. принимая во внимание 3. с учетом

in reference: in reference to your inquiry dated На Ваш запрос от...

in this regard (синон. in this context) в этой связи

in response of в соответствии с;

in response to в соответствии с;

in retaliation в отместку за что-л.

in retrospect задним числом

in routine use in: be in routine use in обычно используется в

in running order годный к пуску (напр., блок электростанции)

in a sense в известном смысле

in a short time в недалеком будущем

in situ на своем месте

in so doing ( в начале предлож.) При этом...

in so far as коль скоро

in some instances... and in others в одних случаях..., а в других случаях

in some locations..., in other (

in spurts скачкообразный (напр., о росте трещины)

in step with по мере (увеличения, уменьшения, роста, снижения, и т.д.];

in substitution to взамен чего-л. (напр., выдавать доработанный чертеж: проекта вместо другого, предыдущего)

in summary в общем (и целом)

in terms of (ЛДП) 1. в плане чего-л.; в части чего-л. 2. если говорить о 3. (матем.) относительно

in this instance А если это так, то; А раз это так, то

in a timely manner оперативно

in a tough spot: be in a tough spot находиться / оказаться в затруднительном положении

in a uniform manner равномерно

in unique cases в исключительных случаях

in unison параллельно; совместно; в связке

in use 1. принятый (в знач. находящийся в употреблении)

in a variety of[ different areas] в самых различных [ областях]

in the vicinity of в зоне чего-л.;

in view of 1. в связи с; коль скоро; в свете чего-л.; на основании чего-л. in view of the foregoing в связи с вышеизложенным; в свете вышеизложенного; на основании вышеизложенного 2. in view of the fact that в связи с тем, что

in which case и тогда...

in witness whereof в удостоверение чего...

in words прописью ( о цифрах)

in a workmanlike manner квалифицированно; мастерски; "классно"

in writing в письменном виде

in a wrong place 1. в неположенном месте 2. (разг.) не там

1) язык || языковой

2) машинный язык; набор символов ( машины)

•

- algorithmic language

SUBJECT AREA: Agricultural and food technology

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Robert Bakewell was the son of the tenant farming the 500-acre (200 hectare) Dishley Grange Farm, near Loughborough, where he was born. The family was sufficiently wealthy to allow Robert to travel, which he began to do at an early age, exploring the farming methods of the West Country, Norfolk, Ireland and Holland. On taking over the farm he continued the development of the irrigation scheme begun by his father. Arthur Young visited the farm during his tour of east England in 1771. At that time it consisted of 440 acres (178 hectares), 110 acres (45 hectares) of which were arable, and carried a stock of 60 horses, 400 sheep and 150 other assorted beasts. Of the arable land, 30 acres (12 hectares) were under root crops, mainly turnips.

Bakewell was not the first to pioneer selective breeding, but he was the first successfully to apply selection to both the efficiency with which an animal utilized its food, and its physical appearance. He always had a clear idea of the animal he wanted, travelled extensively to collect a range of animals possessing the characteristics he sought, and then bred from these towards his goal. He was aware of the dangers of inbreeding, but would often use it to gain the qualities he wanted. His early experiments were with Longhorn cattle, which he developed as a meat rather than a draught animal, but his most famous achievement was the development of the Improved Leicester breed of sheep. He set out to produce an animal that would put on the most meat in the least time and with the least feeding. As his base he chose the Old Leicester, but there is still doubt as to which other breeds he may have introduced to produce the desired results. The Improved Leicester was smaller than its ancestor, with poorer wool quality but with greatly improved meat-production capacity.

Bakewell let out his sires to other farms and was therefore able to study their development under differing conditions. However, he made stringent rules for those who hired these animals, requiring the exclusive use of his rams on the farms concerned and requiring particular dietary conditions to be met. To achieve this control he established the Dishley Society in 1783. Although his policies led to accusations of closed access to his stock, they enabled him to keep a close control of all offspring. He thereby pioneered the process now recognized as "progeny testing".

Bakewell's fame and that of his farm spread throughout the country and overseas. He engaged in an extensive correspondence and acted as host to all of influence in British and overseas agriculture, but it would appear that he was an over-generous host, since he is known to have been in financial difficulties in about 1789. He was saved from bankruptcy by a public subscription raised to allow him to continue with his breeding experiments; this experience may well have been the reason why he was such a staunch advocate of State funding of agricultural research.

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   1) Child Development and the Intellectual Life

   There is no mystery about it: the child who is familiar with books, ideas, conversation-the ways and means of the intellectual life-before he begins school, indeed, before he begins consciously to think, has a marked advantage. He is at home in the House of intellect just as the stableboy is at home among horses, or the child of actors on the stage. (Barzun, 1959, p. 142)

   2) Comparison of Sensory- Motor Intelligence and Conceptual Thought

   It is... no exaggeration to say that sensory-motor intelligence is limited to desiring success or practical adaptation, whereas the function of verbal or conceptual thought is to know and state truth. (Piaget, 1954, p. 359)

   3) The Epistemological and Heuristic Parts of Intelligence

   ntelligence has two parts, which we shall call the epistemological and the heuristic. The epistemological part is the representation of the world in such a form that the solution of problems follows from the facts expressed in the representation. The heuristic part is the mechanism that on the basis of the information solves the problem and decides what to do. (McCarthy & Hayes, 1969, p. 466)

   3. Contextual approaches. To qualify as a useful contextual construct, intelligence should be a source of individual differences in accomplishments in "real-world" performances. It is not enough just to account for performance in the laboratory. On [sic] the contextual view, what a person does in the lab may not even remotely resemble what the person would do outside it. Moreover, different cultures may have different conceptions of intelligence, which affect what would count as intelligent in one cultural context versus another.

   4. Systems approaches. Systems approaches attempt to understand intelligence through the interaction of cognition with context. They attempt to establish a link between the two levels of analysis, and to analyze what forms this link takes. (Sternberg, 1994, pp. 263-264)

   5) High Intelligence Combined with the Greatest Degrees of Persistence

   High but not the highest intelligence, combined with the greatest degrees of persistence, will achieve greater eminence than the highest degree of intelligence with somewhat less persistence. (Cox, 1926, p. 187)

   6) Intelligence Is Not Marked by Definitive Criteria

   There are no definitive criteria of intelligence, just as there are none for chairness; it is a fuzzy-edged concept to which many features are relevant. Two people may both be quite intelligent and yet have very few traits in common-they resemble the prototype along different dimensions.... [Intelligence] is a resemblance between two individuals, one real and the other prototypical. (Neisser, 1979, p. 185)

   7) Synthesis of Differential and Information- Processing Approaches to the Study of Intelligence

   Given the complementary strengths and weaknesses of the differential and information-processing approaches, it should be possible, at least in theory, to synthesise an approach that would capitalise upon the strength of each approach, and thereby share the weakness of neither. (Sternberg, 1977, p. 65)