processing+context

   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)

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 ■ Rumelhart, D. E., P. Smolensky, J. L. McClelland & G. E. Hinton (1986). Schemata and sequential thought processes in PDP models. In J. L. McClelland, D. E. Rumelhart & the PDP Research Group (Eds.), Parallel Distributed Processing (Vol. 2, pp. 7-57). Cambridge, MA: MIT Press.

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 ■ Salthouse, T. A. (1992). Expertise as the circumvention of human processing limitations. In K. A. Ericsson & J. Smith (Eds.), Toward a general theory of expertise: Prospects and limits (pp. 172-194). Cambridge: Cambridge University Press.

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   1) The Discovery of Truth Depends on the Thoughtful Reading of Authoritative Texts

   For the Middle Ages, all discovery of truth was first reception of traditional authorities, then later-in the thirteenth century-rational reconciliation of authoritative texts. A comprehension of the world was not regarded as a creative function but as an assimilation and retracing of given facts; the symbolic expression of this being reading. The goal and the accomplishment of the thinker is to connect all these facts together in the form of the "summa." Dante's cosmic poem is such a summa too. (Curtius, 1973, p. 326)

   2) The Many Functions of Reading

   The readers of books... extend or concentrate a function common to us all. Reading letters on a page is only one of its many guises. The astronomer reading a map of stars that no longer exist; the Japanese architect reading the land on which a house is to be built so as to guard it from evil forces; the zoologist reading the spoor of animals in the forest; the card-player reading her partner's gestures before playing the winning card; the dancer reading the choreographer's notations, and the public reading the dancer's movements on the stage; the weaver reading the intricate design of a carpet being woven; the organ-player reading various simultaneous strands of music orchestrated on the page; the parent reading the baby's face for signs of joy or fright, or wonder; the Chinese fortune-teller reading the ancient marks on the shell of a tortoise; the lover blindly reading the loved one's body at night, under the sheets; the psychiatrist helping patients read their own bewildering dreams; the Hawaiian fisherman reading the ocean currents by plunging a hand into the water; the farmer reading the weather in the sky-all these share with book-readers the craft of deciphering and translating signs....

   We all read ourselves and the world around us in order to glimpse what and where we are. We read to understand, or to begin to understand. We cannot do but read. Reading, almost as much as breathing, is our essential function. (Manguel, 1996, pp. 6-7)

   3) Theories of Language Processing during Reading

   There is a pitched battle between those theorists and modellers who embrace the primacy of syntax and those who embrace the primacy of semantics in language processing. At times both schools have committed various excesses. For example, some of the former have relied foolishly on context-free mathematical-combinatory models, while some of the latter have flirted with versions of the "direct-access hypothesis," the idea that skilled readers process printed language directly into meaning without phonological or even syntactic processing. The problems with the first excess are patent. Those with the second are more complex and demand more research. Unskilled readers apparently do rely more on phonological processing than do skilled ones; hence their spoken dialects may interfere with their reading-and writing-habits. But the extent to which phonological processing is absent in the skilled reader has not been established, and the contention that syntactic processing is suspended in the skilled reader is surely wrong and not supported by empirical evidence-though blood-flow patterns in the brain are curiously different during speaking, oral reading, and silent reading. (M. L. Johnson, 1988, pp. 101-102)

1) язык

а) естественный язык, средство человеческого общения

б) система знаков, жестов или сигналов для передачи или хранения информации

в) стиль

г) речь

д) язык программирования

2) языкознание, лингвистика

•

- abstract machine language

- algebraic logic functional language

- algorithmic language

- amorhic language

- axiomatic architecture description language

- basic combined programming language

- block-structured language

- boundary scan description language

- business-oriented language

- categorical abstract machine language

- cellular language

- computer hardware description language

- computer-independent language

- configuration language

- context-free language

- data definition language

- data description language

- data manipulation language

- document style semantics and specification language

- domain-specific language

- dynamic hypertext markup language

- dynamic simulation language

- extensible hypertext markup language

- extensible markup language

- fabricated language

- fifth-generation language

- first-generation language

- formal language

- fourth-generation language

- frame language

- function graph language

- geometrical layout description language

- graphics language

- hardware description language

- Hewlett-Packard graphics language

- Hewlett-Packard printer control language

- high-level language

- hypertext markup language

- hypertext markup language plus

- interactive set language

- intermediate language

- Java interface definition language

- Java language

- job control language

- Jules' own version of the international algorithmic language

- knowledge query and manipulation language

- left-associative language

- man-machine language

- mathematical markup language

- matrix-based programming language

- my favorite toy language

- native language

- network control language

- network description language

- noninteractive language

- page description language

- parallel object-oriented language

- partial differential equation language

- pattern-matching language

- practical extraction and report language

- prescriptive language

- second-generation language

- sense language

- server-parsed hypertext markup language

- set language

- simulation language

- specification and assertion language

- stack-based language

- standard generalized markup language

- statically scoped language

- string-oriented symbolic language

- string-processing language

- structural design language

- structured query language

- subset language

- symbolic layout description language

- synchronized multimedia integration language

- target language

- third-generation language

- threaded language

- very-high-speed integrated circuit hardware description language

- Vienna definition language

- virtual reality modeling language

- visual language

- wireless markup language

1) язык

а) естественный язык, средство человеческого общения

б) система знаков, жестов или сигналов для передачи или хранения информации

в) стиль

г) речь

д) язык программирования

2) языкознание, лингвистика

•

- a hardware programming language

1) язык || языковой

2) машинный язык; набор символов ( машины)

•

- algorithmic language

   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)

1) информация

а) вчт данные

б) сведения; факты; новости

2) количество информации

3) информирование

4) информационная служба; служба новостей; сотрудник информационной службы или службы новостей

•

- accounting information

- meta-information

- misleading information

- program chain information

- protocol control information

1) информация

а) вчт. данные

б) сведения; факты; новости

2) количество информации

3) информирование

4) информационная служба; служба новостей; сотрудник информационной службы или службы новостей

•

- accounting information

- disable the protection

- protection against compromising emanation

- protection against eavesdropping

- protection during processing

- access protection

- acoustic protection

- add-on protection

- adequate protection

- anti-burglar protection

- antihacker protection

- antivirus protection

- application protection

- asset protection

- barrier protection

- blanket protection

- boot protection

- boundary protection

- built-in protection

- bypass protection

- callback protection

- capability-based protection

- communication protection

- complex protection

- compromise protection

- confidentiality protection

- context-oriented protection

- controlled access protection

- copy protection

- copyright protection

- counterfeit protection

- critical-area protection

- cryptographic protection

- data communication protection

- data content protection

- data-dependent protection

- data processing asset protection

- DES protection

- dial-up port protection

- discretionary protection

- disincentive protection

- diskette boot protection

- emanations protection

- EMC protection

- encryption protection

- end-to-end protection

- entrance protection

- error protection

- fault protection

- fetch protection

- file-level protection

- hardware protection

- guaranteed protection

- impervious protection

- indirect disclosure protection

- information privacy protection

- inherent software protection

- integrated protection

- intellectual property protection

- interchange protection

- key protection

- key lock protection

- labeled security protection

- legal protection

- limited protection

- lock-and-key protection

- logical protection

- mandatory protection

- memory protection

- message content protection

- message stream protection

- message stream modification protection

- national security protection

- need-to-know protection

- art-card security protection

- passive protection

- password protection

- patent protection

- perimeter protection

- physical protection

- point protection

- port protection

- power protection

- power failure protection

- power loss protection

- privacy protection

- protocol-based protection

- read protection

- read-out protection

- reliable protection

- replay protection

- security protection

- security fetch protection

- fetch protection

- selective field protection

- sensitive data protection

- session protection

- signature protection

- short-term protection

- short time protection

- site protection

- software protection

- software copyright protection

- storage protection

- strategic protection

- structured protection

- tactical protection

- tamper protection

- tap protection

- target protection

- technical protection

- TEMPEST protection

- two-tiered protection

- verified protection

- very important person protection

- VIP protection

- virus protection

- volume protection

- warning protection

- weak protection

- write protection

- absolute language

 

вселенная
—
[А.С.Гольдберг. Англо-русский энергетический словарь. 2006 г.]

Тематики

• энергетика в целом

EN

• system

 

вычислительная система
ЭВМ
—
[Е.С.Алексеев, А.А.Мячев. Англо-русский толковый словарь по системотехнике ЭВМ. Москва 1993]

Тематики

• информационные технологии в целом

Синонимы

• ЭВМ

EN

• computer system
• system

 

механическая система
система
Любая совокупность материальных точек.
Примечание. В механике материальное тело рассматривается как механическая система, образованная непрерывной совокупностью материальных точек.
[Сборник рекомендуемых терминов. Выпуск 102. Теоретическая механика. Академия наук СССР. Комитет научно-технической терминологии. 1984 г.]

Тематики

• теоретическая механика

Синонимы

• система

EN

• system

DE

• materielles System
• Punktsystem

FR

• système mécanique

 

операция MS DOS копирует системные файлы
—
[Е.С.Алексеев, А.А.Мячев. Англо-русский толковый словарь по системотехнике ЭВМ. Москва 1993]

Тематики

• информационные технологии в целом

EN

• system
• SYS

 

система
Группа взаимодействующих объектов, выполняющих общую функциональную задачу. В ее основе лежит некоторый механизм связи.
[ ГОСТ Р МЭК 61850-5-2011]

система
Набор элементов, которые взаимодействуют в соответствии с проектом, в котором элементом системы может быть другая система, называемая подсистемой; система может быть управляющей системой или управляемой системой и включать аппаратные средства, программное обеспечение и взаимодействие с человеком.
Примечания
1 Человек может быть частью системы. Например, человек может получать информацию от программируемого электронного устройства и выполнять действие, связанное с безопасностью, основываясь на этой информации, либо выполнять действие с помощью программируемого электронного устройства.
2 Это определение отличается от приведенного в МЭС 351-01-01.
[ ГОСТ Р МЭК 61508-4-2007]

система
Множество (совокупность) материальных объектов (элементов) любой, в том числе различной физической природы, а также информационных объектов, взаимосвязанных и взаимодействующих между собой для достижения общей цели.
[ ГОСТ Р 43.0.2-2006]

система
Совокупность элементов, объединенная связями между ними и обладающая определенной целостностью.
[ ГОСТ 34.003-90]

система
Совокупность взаимосвязанных и взаимодействующих элементов.
[ ГОСТ Р ИСО 9000-2008]

система
-
[IEV number 151-11-27]

система
Набор связанных элементов, работающих совместно для достижения общей Цели. Например: • Компьютерная система, состоящая из аппаратного обеспечения, программного обеспечения и приложений. • Система управления, состоящая из множества процессов, которые планируются и управляются совместно. Например, система менеджмента качества. • Система управления базами данных или операционная система, состоящая из множества программных модулей, разработанных для выполнения набора связанных функций.
[Словарь терминов ITIL версия 1.0, 29 июля 2011 г.]

система
Множество элементов, находящихся в отношениях и связях друг с другом, которое образует определенную целостность, единство. Следует отметить, что это определение (взятое нами из Большой Советской Энциклопедии) не является ни единственным, ни общепризнанным. Есть десятки определений понятия “С.”, которые с некоторой условностью можно поделить на три группы. Определения, принадлежащие к первой группе, рассматривают С. как комплекс процессов и явлений, а также связей между ними, существующий объективно, независимо от наблюдателя. Его задача состоит в том, чтобы выделить эту С. из окружающей среды, т.е. как минимум определить ее входы и выходы (тогда она рассматривается как “черный ящик”), а как максимум — подвергнуть анализу ее структуру (произвести структуризацию), выяснить механизм функционирования и, исходя из этого, воздействовать на нее в нужном направлении. Здесь С. — объект исследования и управления. Определения второй группы рассматривают С. как инструмент, способ исследования процессов и явлений. Наблюдатель, имея перед собой некоторую цель, конструирует (синтезирует) С. как некоторое абстрактное отображение реальных объектов. При этом С. (“абстрактная система”) понимается как совокупность взаимосвязанных переменных, представляющих те или иные свойства, характеристики объектов, которые рассматриваются в данной С. В этой трактовке понятие С. практически смыкается с понятием модели, и в некоторых работах эти два термина вообще употребляются как взаимозаменяемые. Говоря о синтезе С., в таких случаях имеют в виду формирование макромодели, анализ же С. совпадает в этой трактовке с микромоделированием отдельных элементов и процессов. Третья группа определений представляет собой некий компромисс между двумя первыми. С. здесь — искусственно создаваемый комплекс элементов (например, коллективов людей, технических средств, научных теорий и т.д.), предназначенный для решения сложной организационной, экономической, технической задачи. Следовательно, здесь наблюдатель не только выделяет из среды С. (и ее отдельные части), но и создает, синтезирует ее. С. является реальным объектом и одновременно — абстрактным отображением связей действительности. Именно в этом смысле понимает С. наука системотехника. Между этими группами определений нет непроходимых границ. Во всех случаях термин “С.” включает понятие о целом, состоящем из взаимосвязанных, взаимодействующих, взаимозависимых частей, причем свойства этих частей зависят от С. в целом, свойства С. — от свойств ее частей. Во всех случаях имеется в виду наличие среды, в которой С. существует и функционирует. Для исследуемой С. среда может рассматриваться как надсистема, соответственно, ее части — как подсистемы, а также элементы С., если их внутренняя структура не является предметом рассмотрения. С. делятся на материальные и нематериальные. К первым относятся, например, железная дорога, народное хозяйство, ко вторым — С. уравнений в математике, математика как наука, далее — С. наук. Автоматизированная система управления включает как материальные элементы (ЭВМ, документация, люди), так и нематериальные — математические модели, знания людей. Разделение это тоже неоднозначно: железную дорогу можно рассматривать не только как материальную С., но и как нематериальную С. взаимосвязей, соотношений, потоков информации и т.д. Закономерности функционирования систем изучаются общей теорией систем, оперирующей понятием абстрактной С. Наибольшее значение среди абстрактных С. имеют кибернетические С. Есть два понятия, близкие понятию С.: комплекс, совокупность (множество объектов). Они, однако, не тождественны ему, как нередко утверждают. Их можно рассматривать как усеченные, неполные понятия по отношению к С.: комплекс включает части, не обязательно обладающие системными свойствами (в том смысле, как это указано выше), но эти части сами могут быть системами, и элементы последних такими свойствами по отношению к ним способны обладать. Совокупность же есть множество элементов, не обязательно находящихся в системных отношениях и связях друг с другом. В данном словаре мы стремимся по возможности последовательно различать понятия С. и модели, рассматривая С. как некий объект (реальной действительности или воображаемый — безразлично), который подвергается наблюдению и изучению, а модель — как средство этого наблюдения и изучения. Разумеется, и модель, если она сама оказывается объектом наблюдения и изучения, в свою очередь рассматривается как С. (в частности, как моделируемая С.) — и так до бесконечности. Все это означает, что такие, например, понятия, как переменная или параметр, мы (в отличие от многих авторов) относим не к С., а к ее описанию, т.е. к модели (см. Параметры модели, Переменная модели), численные же их значения, характеризующие С., — к С. (например, координаты С.). • Системы математически описываются различными способами. Каждая переменная модели, выражающая определенную характеристику С., может быть задана множеством конкретных значений, которые эта переменная может принимать. Состояние С. описывается вектором (или кортежем, если учитываются также величины, не имеющие численных значений), каждая компонента которого соответствует конкретному значению определенной переменной. С. в целом может быть описана соответственно множеством ее состояний. Например, если x = (1, 2, … m) — вектор существенных переменных модели, каждая из которых может принять y значений (y = 1, 2, …, n), то матрица S = [ Sxy ] размерностью m ? n представляет собой описание данной С. Широко применяется описание динамической С. с помощью понятий, связанных с ее функционированием в среде. При этом С. определяется как три множества: входов X, выходов Y и отношений между ними R. Полученный “портрет системы” может записываться так: XRY или Y = ®X. Аналитическое описание С. представляет собой систему уравнений, характеризующих преобразования, выполняемые ее элементами и С. в целом в процессе ее функционирования: в непрерывном случае применяется аппарат дифференциальных уравнений, в дискретном — аппарат разностных уравнений. Графическое описание С. чаще всего состоит в построении графа, вершины которого соответствуют элементам С., а дуги — их связям. Существует ряд классификаций систем. Наиболее известны три: 1) Ст. Бир делит все С. (в природе и обществе), с одной стороны, на простые, сложные и очень сложные, с другой — на детерминированные и вероятностные; 2) Н.Винер исходит из особенностей поведения С. (бихевиористский подход) и строит дихотомическую схему: С., характеризующиеся пассивным и активным поведением; среди последних — нецеленаправленным (случайным) и целенаправленным; в свою очередь последние подразделяются на С. без обратной связи и с обратной связью и т.д.; 3) К.Боулдинг выделяет восемь уровней иерархии С., начиная с простых статических (например, карта земли) и простых кибернетических (механизм часов), продолжая разного уровня сложности кибернетическими С., вплоть до самых сложных — социальных организаций. Предложены также классификации по другим основаниям, в том числе более частные, например, ряд классификаций С. управления. См. также: Абстрактная система, Адаптирующиеся, адаптивные системы, Большая система, Вероятностная система, Выделение системы, Входы и выходы системы, Детерминированная система, Динамическая система, Дискретная система, Диффузная система, Замкнутая (закрытая) система, Иерархическая структура, Имитационная система, Информационная система, Информационно-развивающаяся система, Кибернетическая система, Координаты системы, Надсистема, Нелинейная система, Непрерывная система, Открытая система, Относительно обособленная система, Память системы, Подсистема, Портрет системы, Разомкнутая система, Рефлексная система, Решающая система, Самонастраивающаяся система, Самообучающаяся система, Самоорганизующаяся система, Сложная система, Состояние системы, Статическая система, Стохастическая система, Структура системы, Структуризация системы, Управляющая система, Устойчивость системы, Целенаправленная система, Экономическая система, Функционирование экономической системы..
[ http://slovar-lopatnikov.ru/]

EN

system
set of interrelated elements considered in a defined context as a whole and separated from their environment
NOTE 1 – A system is generally defined with the view of achieving a given objective, e.g. by performing a definite function.
NOTE 2 – Elements of a system may be natural or man-made material objects, as well as modes of thinking and the results thereof (e.g. forms of organisation, mathematical methods, programming languages).
NOTE 3 – The system is considered to be separated from the environment and the other external systems by an imaginary surface, which cuts the links between them and the system.
NOTE 4 – The term "system" should be qualified when it is not clear from the context to what it refers, e.g. control system, colorimetric system, system of units, transmission system.
Source: 351-01-01 MOD
[IEV number 151-11-27]

system
A number of related things that work together to achieve an overall objective. For example: • A computer system including hardware, software and applications • A management system, including the framework of policy, processes, functions, standards, guidelines and tools that are planned and managed together – for example, a quality management system • A database management system or operating system that includes many software modules which are designed to perform a set of related functions.
[Словарь терминов ITIL версия 1.0, 29 июля 2011 г.]

FR

système, m
ensemble d'éléments reliés entre eux, considéré comme un tout dans un contexte défini et séparé de son environnement
NOTE 1 – Un système est en général défini en vue d'atteindre un objectif déterminé, par exemple en réalisant une certaine fonction.
NOTE 2 – Les éléments d'un système peuvent être aussi bien des objets matériels, naturels ou artificiels, que des modes de pensée et les résultats de ceux-ci (par exemple des formes d'organisation, des méthodes mathématiques, des langages de programmation).
NOTE 3 – Le système est considéré comme séparé de l'environnement et des autres systèmes extérieurs par une surface imaginaire qui coupe les liaisons entre eux et le système.
NOTE 4 – Il convient de qualifier le terme "système" lorsque le concept ne résulte pas clairement du contexte, par exemple système de commande, système colorimétrique, système d'unités, système de transmission.
Source: 351-01-01 MOD
[IEV number 151-11-27]

Тематики

• автоматизированные системы
• информационные технологии в целом
• релейная защита
• системы менеджмента качества
• экономика

EN

• system

DE

• System

FR

• système

 

система
Любой объект, который одновременно рассматривается и как единое целое, и как совокупность разнородных объектов, объединенных для достижения определенного результата. [http://www.rol.ru/files/dict/internet/#P].
[ http://www.morepc.ru/dict/]

Тематики

• информационные технологии в целом

EN

• system

 

система
Объект, представляющий собой совокупность элементов, обладающую свойством целостности при данном рассмотрении.
[Сборник рекомендуемых терминов. Выпуск 107. Теория управления.
 Академия наук СССР. Комитет научно-технической терминологии. 1984 г.]

Тематики

• автоматизация, основные понятия

EN

• system

 

система (в экологическом менеджменте)
Совокупность взаимосвязанных или взаимодействующих элементов.
[ http://www.14000.ru/glossary/main.php?PHPSESSID=25e3708243746ef7c85d0a8408d768af]

EN

system
Set of interrelated or interacting elements.
[ISO 9000:2000]

Тематики

• управление окружающей средой

EN

• system

 

система (в электроэнергетике)
Означает любые транспортные сети, распределительные сети, комплексы СПГ и/или хранилища, принадлежащие и/или эксплуатируемые предприятием природного газа, включая хранилища в трубопроводе и объекты, поставляющие вспомогательные услуги, а также подобные же подразделения связанных предприятий, необходимые для обеспечения доступа к транспортировке, распределению и СПГ (Директива 2003/55/ЕС).
[Англо-русский глосcарий энергетических терминов ERRA]

EN

system
Means any transmission networks, distribution networks, LNG facilities and/or storage facilities owned and/or operated by a natural gas undertaking, including linepack and its facilities supplying ancillary services and those of related undertakings necessary for providing access to transmission, distribution and LNG (Directive 2003/55/EC).
[Англо-русский глосcарий энергетических терминов ERRA]

Тематики

• энергетика в целом

EN

• system

 

система
Отложения, образовавшиеся в течение геологического периода.
[ Словарь геологических терминов и понятий. Томский Государственный Университет]

Тематики

• геология, геофизика

Обобщающие термины

• геохронология

EN

• system

4.48 система (system): Комбинация взаимодействующих элементов, организованных для достижения одной или нескольких поставленных целей.

Примечание 1 - Система может рассматриваться как продукт или предоставляемые им услуги.

Примечание 2 - На практике интерпретация данного термина зачастую уточняется с помощью ассоциативного существительного, например, «система самолета». В некоторых случаях слово «система» может заменяться контекстно-зависимым синонимом, например, «самолет», хотя это может впоследствии затруднить восприятие системных принципов.

Источник: ГОСТ Р ИСО/МЭК 12207-2010: Информационная технология. Системная и программная инженерия. Процессы жизненного цикла программных средств оригинал документа

4.17 система (system): Комбинация взаимодействующих элементов, организованных для достижения одной или нескольких поставленных целей.

Примечания

1. Система может рассматриваться как продукт или как совокупность услуг, которые она обеспечивает.

2. На практике интерпретация данного термина зачастую уточняется с помощью ассоциативного существительного, например, система самолета. В некоторых случаях слово «система» может заменяться контекстным синонимом, например, самолет, хотя это может впоследствии затруднять восприятие системных принципов.

Источник: ГОСТ Р ИСО/МЭК 15288-2005: Информационная технология. Системная инженерия. Процессы жизненного цикла систем оригинал документа

4.44 система (system): Комплекс процессов, технических и программных средств, устройств, обслуживаемый персоналом и обладающий возможностью удовлетворять установленным потребностям и целям (3.31 ГОСТ Р ИСО/МЭК 12207).

Источник: ГОСТ Р ИСО/МЭК 15910-2002: Информационная технология. Процесс создания документации пользователя программного средства оригинал документа

3.31 система (system): Комплекс, состоящий из процессов, технических и программных средств, устройств и персонала, обладающий возможностью удовлетворять установленным потребностям или целям.

Источник: ГОСТ Р ИСО/МЭК 12207-99: Информационная технология. Процессы жизненного цикла программных средств оригинал документа

3.36 система (system): Совокупность взаимосвязанных и взаимодействующих объектов. [ ГОСТ Р ИСО 9000, статья 3.2.1]

Источник: ГОСТ Р 51901.6-2005: Менеджмент риска. Программа повышения надежности оригинал документа

3.2 система (system): Совокупность взаимосвязанных и взаимодействующих элементов. [ ГОСТ Р ИСО 9000 - 2001]

Примечания

1 С точки зрения надежности система должна иметь:

a) определенную цель, выраженную в виде требований к функционированию системы;

b) заданные условия эксплуатации.

2 Система имеет иерархическую структуру.

Источник: ГОСТ Р 51901.5-2005: Менеджмент риска. Руководство по применению методов анализа надежности оригинал документа

3.2.1 система (system): Совокупность взаимосвязанных и взаимодействующих элементов.

Источник: ГОСТ Р ИСО 9000-2008: Системы менеджмента качества. Основные положения и словарь оригинал документа

3. Система обработки

информации

СОИ

Information processing

system

Совокупность технических средств и программного обеспечения, а также методов обработки информации и действий персонала, обеспечивающая выполнение автоматизированной обработки информации

Источник: ГОСТ 15971-90: Системы обработки информации. Термины и определения оригинал документа

3.7 система (system): Совокупность взаимосвязанных или взаимодействующих элементов.

Примечания

1 Применительно к надежности система должна иметь:

a) определенные цели, представленные в виде требований к ее функциям;

b) установленные условия функционирования;

c) определенные границы.

2 Структура системы является иерархической.

Источник: ГОСТ Р 51901.12-2007: Менеджмент риска. Метод анализа видов и последствий отказов оригинал документа

2.39 система (system): Совокупность взаимосвязанных и взаимодействующих элементов.

Источник: ГОСТ Р 53647.2-2009: Менеджмент непрерывности бизнеса. Часть 2. Требования оригинал документа

3.20 система (system): Конфигурация взаимодействующих в соответствии с проектом составляющих, в которой элемент системы может сам представлять собой систему, называемую в этом случае подсистемой.

(МЭК 61513, статья 3.61)

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

3.61 система (system): Конфигурация взаимодействующих в соответствии с проектом составляющих, в которой элемент системы может сам представлять собой систему, называемую в этом случае подсистемой.

[МЭК 61508-4, пункт 3.3.1, модифицировано]

Примечание 1 - См. также «система контроля и управления».

Примечание 2 - Системы контроля и управления следует отличать от механических систем и электрических систем АС.

Источник: ГОСТ Р МЭК 61513-2011: Атомные станции. Системы контроля и управления, важные для безопасности. Общие требования оригинал документа

3.2.1 система (system): Совокупность взаимосвязанных и взаимодействующих элементов.

Источник: ГОСТ ISO 9000-2011: Системы менеджмента качества. Основные положения и словарь

2.34 система (system): Специфическое воплощение ИТ с конкретным назначением и условиями эксплуатации.

[ИСО/МЭК 15408-1]

а) комбинация взаимодействующих компонентов, организованных для достижения одной или нескольких поставленных целей.

[ИСО/МЭК 15288]

Примечания

1 Система может рассматриваться как продукт или совокупность услуг, которые она обеспечивает.

[ИСО/МЭК 15288]

2 На практике интерпретация данного зачастую уточняется с помощью ассоциативного существительного, например, «система самолета». В некоторых случаях слово «система» допускается заменять, например, контекстным синонимом «самолет», хотя это может впоследствии затруднить восприятие системных принципов.

[ИСО/МЭК 15288]

Источник: ГОСТ Р 54581-2011: Информационная технология. Методы и средства обеспечения безопасности. Основы доверия к безопасности ИТ. Часть 1. Обзор и основы оригинал документа

3.34 система (system):

Совокупность связанных друг с другом подсистем и сборок компонентов и/или отдельных компонентов, функционирующих совместно для выполнения установленной задачи или

совокупность оборудования, подсистем, обученного персонала и технических приемов, обеспечивающих выполнение или поддержку установленных функциональных задач. Полная система включает в себя относящиеся к ней сооружения, оборудование, подсистемы, материалы, обслуживание и персонал, необходимые для ее функционирования в той степени, которая считается достаточной для выполнения установленных задач в окружающей обстановке.

Источник: ГОСТ Р 51317.1.5-2009: Совместимость технических средств электромагнитная. Воздействия электромагнитные большой мощности на системы гражданского назначения. Основные положения оригинал документа

3.2.6 система (system): Совокупность взаимосвязанных или взаимодействующих элементов.

Источник: ГОСТ Р 54147-2010: Стратегический и инновационный менеджмент. Термины и определения оригинал документа

3.12 система (system): Совокупность взаимосвязанных и взаимодействующих элементов

[ ГОСТ Р ИСО 9000-2008, ст. 3.2.1]

Источник: Р 50.1.069-2009: Менеджмент риска. Рекомендации по внедрению. Часть 2. Определение процесса менеджмента риска

3.136 система (system): Совокупность объектов реального мира, организованная для заданной цели.

Источник: ГОСТ Р 54136-2010: Системы промышленной автоматизации и интеграция. Руководство по применению стандартов, структура и словарь оригинал документа

1) Компьютерная техника: Primary Domain Controler

2) Медицина: пируват дегидрогеназный комплекс (Pyruvate dehydrogenase complex)

3) Американизм: Public Disclosure Commission

4) Спорт: Philip Derek Champion

5) Военный термин: Pacific Defense College, Per Diem, Travel and Transportation Allowance Committee, Polaris documentation control, Propaganda Development Center, parametric defense coverage, performance data computer, personnel data card, personnel dispatch center, personnel dispersal center, personnel distribution center, personnel distribution command, power distribution cabin, probability of detection and conversion, procurement document change, product data center, professional development center, proficiency data card, program data coordinator, publications distribution center, pyrotechnic devices checker

6) Техника: parallel data controller, preliminary design criterion, principal design criterion

7) Химия: Pretty Darn Confusing

8) Финансы: Public Debt Committee

9) Автомобильный термин: Park Distance Control

10) Грубое выражение: Pretty Dumb Criminal

11) Телевидение: (Programme Delivery Control System) Система программирования видеозаписи

12) Телекоммуникации: Personal Digital Cellular

13) Сокращение: Participatory Design Conference, Partido Democrata Cristiano (Chile), Parts Distribution Center (автомобильный термин), Postal Data Center (i.e. NYPDC, Minneapolis PDC), Processing and Distribution Center (180 in 2004)

14) Электроника: Passive data collection

15) Вычислительная техника: Power Disk Cartridge (ECMA), PROLOG Development Center (Hersteller, Daenemark, PROLOG), Primary DOMAIN Controller (MS, Windows, NT, BDC), Personal Digital Cellular (network, GSM), personal digital cellural, primary domain controller

16) Нефть: perforating depth control, polycrystalline diamond cutter, pressure differential controller, коронка, армированная поликристаллическими синтетическими алмазами (polycrystalline diamond compact), буровые долота PDC

17) Транспорт: Pre - Departure Clearance

18) Пищевая промышленность: Purina Dog Chow

19) Фирменный знак: Pressure Dynamic Consultants, Priority Dispatch Corporation

20) Бурение: polycrystalline diamond compact (with diamond inserts), кран трубного склада (pipe deck crane), поликристаллический алмазный композит, polycrystalline diamond compact, polycrystalline diamond composite

21) Сетевые технологии: Plugin Delay Compensation, Pointer To Device Context, Programme Delivery Control

22) Программирование: Processor Dependent Code, Professional Developers Conference

23) Автоматика: portable data collector, production data controller

24) Океанография: Pacific Disaster Center

25) Сахалин Ю: personnel development committee

26) Химическое оружие: Project Data Coordinator

27) Макаров: phase distribution chromatography

28) SAP.тех. сбор производственных данных

29) Нефть и газ: perforating depth control log, poly crystalline diamond composite, poly crystalline diamond cutter, power distribution cabinet, каротажная диаграмма для определения глубины интервала перфорации, поликристаллический алмазный резец, резец PDC

30) Маркетология: Product Discount Credit (в сетевых компаниях одна из опций перечисления премиальных на скидку на последующую приобретаемую продукцию)

31) Электротехника: power distribution control

32) Правительство: Prairie Du Chien, Wisconsin

33) НАСА: Planetary Data Center

1) Компьютерная техника: Primary Domain Controler

2) Медицина: пируват дегидрогеназный комплекс (Pyruvate dehydrogenase complex)

3) Американизм: Public Disclosure Commission

4) Спорт: Philip Derek Champion

5) Военный термин: Pacific Defense College, Per Diem, Travel and Transportation Allowance Committee, Polaris documentation control, Propaganda Development Center, parametric defense coverage, performance data computer, personnel data card, personnel dispatch center, personnel dispersal center, personnel distribution center, personnel distribution command, power distribution cabin, probability of detection and conversion, procurement document change, product data center, professional development center, proficiency data card, program data coordinator, publications distribution center, pyrotechnic devices checker

6) Техника: parallel data controller, preliminary design criterion, principal design criterion

7) Химия: Pretty Darn Confusing

8) Финансы: Public Debt Committee

9) Автомобильный термин: Park Distance Control

10) Грубое выражение: Pretty Dumb Criminal

11) Телевидение: (Programme Delivery Control System) Система программирования видеозаписи

12) Телекоммуникации: Personal Digital Cellular

13) Сокращение: Participatory Design Conference, Partido Democrata Cristiano (Chile), Parts Distribution Center (автомобильный термин), Postal Data Center (i.e. NYPDC, Minneapolis PDC), Processing and Distribution Center (180 in 2004)

14) Электроника: Passive data collection

15) Вычислительная техника: Power Disk Cartridge (ECMA), PROLOG Development Center (Hersteller, Daenemark, PROLOG), Primary DOMAIN Controller (MS, Windows, NT, BDC), Personal Digital Cellular (network, GSM), personal digital cellural, primary domain controller

16) Нефть: perforating depth control, polycrystalline diamond cutter, pressure differential controller, коронка, армированная поликристаллическими синтетическими алмазами (polycrystalline diamond compact), буровые долота PDC

17) Транспорт: Pre - Departure Clearance

18) Пищевая промышленность: Purina Dog Chow

19) Фирменный знак: Pressure Dynamic Consultants, Priority Dispatch Corporation

20) Бурение: polycrystalline diamond compact (with diamond inserts), кран трубного склада (pipe deck crane), поликристаллический алмазный композит, polycrystalline diamond compact, polycrystalline diamond composite

21) Сетевые технологии: Plugin Delay Compensation, Pointer To Device Context, Programme Delivery Control

22) Программирование: Processor Dependent Code, Professional Developers Conference

23) Автоматика: portable data collector, production data controller

24) Океанография: Pacific Disaster Center

25) Сахалин Ю: personnel development committee

26) Химическое оружие: Project Data Coordinator

27) Макаров: phase distribution chromatography

28) SAP.тех. сбор производственных данных

29) Нефть и газ: perforating depth control log, poly crystalline diamond composite, poly crystalline diamond cutter, power distribution cabinet, каротажная диаграмма для определения глубины интервала перфорации, поликристаллический алмазный резец, резец PDC

30) Маркетология: Product Discount Credit (в сетевых компаниях одна из опций перечисления премиальных на скидку на последующую приобретаемую продукцию)

31) Электротехника: power distribution control

32) Правительство: Prairie Du Chien, Wisconsin

33) НАСА: Planetary Data Center

- absolute language

- representation language

- requirement statement language