mental programming

1) программирование ( разработка программного обеспечения)

2) программирование (прошивка информации в ПЗУ, ПЛМ и пр.)

3) планирование

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- absolute programming

- client/server programming

- compositional programming

- defensive programming

- direct programming

- object-oriented programming

- opportunistic N-version programming

   1) Theories of Human Mental Processes Can Be Expressed in Programming Languages

   It [the information-processing revolution] has introduced computer programming languages as formal ["mathematical"] languages for expressing theories of human mental processes; and it has introduced the computers themselves as a device to simulate these processes and thereby make behavioral predictions for testing of the theories. (Simon, 1979, p. ix)

   2) The Advantages of LISP

   LISP is now the second oldest programming language in present widespread use (after FORTRAN).... Its core occupies some kind of local optimum in the space of programming languages given that static friction discourages purely notational changes. Recursive use of conditional expressions, representation of symbolic information externally by lists and internally by list structure, and representation of program in the same way will probably have a very long life. (McCarthy, quoted in Barr & Feigenbaum, 1982, p. 5)

   3) When a Machine Might Begin to Have a Mind of Its Own

   Although it sounds implausible, it might turn out that above a certain level of complexity, a machine ceased to be predictable, even in principle, and started doing things on its own account, or, to use a very revealing phrase, it might begin to have a mind of its own. (Lucas, quoted in Hand, 1985, p. 4)

   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)

masturbation, self-pollution, onanism, self-abuse.

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► nombre femenino

1 masturbation

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SF masturbation

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femenino masturbation

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= masturbation, wank.

Ex. Specific Question and Answer pages supply answers to standard topics including: 'Arguing over how much sex'; 'Answers about masturbation'; 'Women and orgasm'.

Ex. Channel 4 has postponed transmission of its 'wank week' programming in a bid to avoid further controversy.

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* masturbación mental = mental masturbation.

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femenino masturbation

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masturbation

* * *

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masturbación nf

masturbation

* * *

f masturbation

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masturbación nf, pl - ciones : masturbation

1 straw (hierba, caña).

2 wank (British), jerkoff (United States) (very informal) (masturbation).

hacerse la paja to jerk off (Am), to have a wank (British)

hacerse una paja to jerk off (Am), to have a wank (British)

3 light stuff, waffle, padding.

4 faucet, spigot.

5 garbage, insubstantial talk, rubbish, trash.

* * *

► nombre femenino

1 straw

2 figurado (relleno) waffle

3 tabú (masturbación) wank

\

hacerse una paja tabú to wank, US jerk off

meter paja to waffle

por un quítame allá esas pajas for no reason at all

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1) (Agr) straw; [de beber] straw; LAm (=leña) dried brushwood

- lo hizo en un quitarme las pajas

- riñeron por un quítame allá esas pajas

- ver la paja en el ojo ajeno y no la viga en el propio

2) (fig) trash, rubbish, garbage (EEUU); [en libro, ensayo] padding, waffle *

3) *** (=masturbación)

4) And, Chile

5) And, CAm

6) Cono Sur ** (=droga) dope **

7) CAm ** (=mentira) lie, fib *

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adjetivo (Per fam) great (colloq)

1) (Agr, Bot) straw

2) ( para beber) tb

3)

a) (fam) (en texto, discurso) padding, waffle (BrE colloq)

b) (Col fam)

4) (AmC) ( grifo) faucet (AmE), tap (BrE)

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adjetivo (Per fam) great (colloq)

1) (Agr, Bot) straw

2) ( para beber) tb

3)

a) (fam) (en texto, discurso) padding, waffle (BrE colloq)

b) (Col fam)

4) (AmC) ( grifo) faucet (AmE), tap (BrE)

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paja¹

¹ = straw, chaff, hay.

paja²

² = wank.

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( Per fam) great ( colloq)

A ( Agr, Bot) straw

sombrero de paja straw hat

techo de paja thatched roof

correrse una or la paja (Chi, Per vulg); to jerk off ( vulg), to wank ( BrE vulg)

hacerse pajas mentales ( vulg); to indulge in mental masturbation

hacerse una or la paja ( vulg); to jerk off ( vulg), to wank ( BrE vulg), to have a wank ( BrE vulg)

quítame allá esas pajas ( fam): arma un escándalo por cualquier quítame allá esas pajas she kicks up a fuss over the slightest little thing ( colloq)

ver la paja en el ojo ajeno y no la viga en el propio to see the mote in one's neighbor's eye and not the beam in one's own

tener (el) rabo (Col, Ven) or ( RPl) (la) cola de paja to have a guilty conscience

B (para beber) tb

pajita straw, drinking straw

(de) color paja straw-colored*

1 ( fam) (en un escrito, discurso) padding, waffle ( BrE colloq)

tiene unos capítulos interesantes pero también hay mucha paja it has some interesting chapters but there's a lot of padding o waffle too

ha escrito siete páginas pero es pura paja she's written seven pages but it's pure padding

( Col fam): hablar or echar paja (decir mentiras) to tell lies; (charlar) to chat, gab ( colloq)

E (AmC, Ven) (del agua) faucet ( AmE), tap ( BrE)

agua de la paja tap water

* * *

a) (Agr, Bot) straw;

◊ sombrero de paja straw hat;

b) ( para beber) (drinking) straw

a) (fam) (en texto, discurso) padding, waffle (BrE colloq)

b) (Col fam): hablar or echar paja ( decir mentiras) to tell lies;

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paja¹ nf

1. [hierba, caña] straw;

casa con techo de paja thatched house, house with a thatched roof;

por un quítame allá esas pajas over nothing, over some silly little thing;

separar la paja del grano to separate o sort out the wheat from the chaff;

no ser paja de coco to be no easy task;

ver la paja en el ojo ajeno y no la viga en el propio to see the mote in one's neighbour's eye and not the beam in one's own

2. [para beber] (drinking) straw

3. Fam [relleno] waffle, padding;

has metido mucha paja en el trabajo your essay's got too much waffle o padding in it

4. muy Fam [masturbación] Br wank, US jerkoff;

hacerse una o Am [m5] la paja to jerk off, Br to have a wank

no son más que pajas mentales it's just mental masturbation;

deja de hacerte pajas mentales y decídete quit o stop jerking around and make your mind up

5. Col, Ven Fam [palabrería] blather, waffle;

deja ya de hablar paja stop blathering o Br wittering on

paja² adj

* * *

f straw;

hacerse una o L.Am.

la paja vulg jerk off vulg ;

por un quítame allá esas pajas over nothing

* * *

paja nf

1) : straw

2) fam : trash, tripe

* * *

paja n

1. (en general) straw

2. (relleno) waffle

[ˈprɔbləm]

accounting problem бухгалтерская задача activity-analysis problem задача анализа операций algorithmic problem алгоритмическая проблема all integer problem вчт. полностью целочисленная задача allocation problem задача распределения approximating problem приближенная задача assignment problem задача о назначениях assignment problem задача о распределении auxiliary problem вспомогательная задача bargaining problem задача о торгах benchmark problem вчт. эталонная тестовая задача bottleneck problem вчт. проблема узких мест bottleneck problem проблема узких мест bounded-variable problem вчт. задача с ограниченными переменными bulk queueing problem задача о групповом обслуживании business problem коммерческая задача classical optimization problem классическая задача оптимизации congestion problem вчт. задача массового обслуживания convex programming problem задача выпуклого программирования cut problem задача о раскрое data-set problem задача обработки совокупности данных decision problem задача принятия решений define a problem сформулировать задачу define a problem формулировать задачу delivery problem задача о доставке drug problem проблема наркомании dual problem двойственная задача equilibrium problem задача о равновесии error minimization problem задача минимизации ошибок estimation problem задача оценивания extremal problem экстремальная задача finite horizon problem задача о конечном интервале forecasting problem задача прогнозирования game-theoretic problem задача теории игр general decision problem общая задача принятия решений general transportation problem общая транспортная задача harmonization problem эк. проблема согласования ill-defined problem плохо структурированная задача ill-posed problem некорректная задача inference problem проблема логического вывода infinite horizon problem задача о бесконечном интервале information retrieval problem информационно-поисковая задача intractable problem трудноразрешимая задача legal problem правовая проблема legal problem правовой вопрос linear programming problem задача линейного программирования longest-path problem задача о максимальном пути management problem управленческая задача market analysis problem вчт. задача анализа рынка maximization problem задача максимизации mental problem умственные трудности minimal path problem задача о минимальном пути minimization problem задача минимизации minimum problem задача на минимум multi-objective problem многоцелевая задача multifacility problem вчт. задача для многоканальной системы nonlinear programming problem задача нелинейного программирования optimal kit problem задача об оптимальном комплекте optimal path problem задача о выборе оптимального пути optimization problem задача оптимизации optimum problem задача оптимизации ordering problem задача упорядочения primal problem прямая задача probabilistic problem вероятностная задача problem вопрос problem мат., шахм. задача problem задача problem проблема; вопрос; задача problem проблема problem проблемный problem сложная ситуация problem трудный случай problem attr. проблемный; problem novel проблемный роман problem child трудный ребенок problem of waiting вчт. задача об обслуживании с ожиданием programming problem вчт. задача программирования programming problem вчт. проблема программирования psychiatric problem психиатрическая проблема queuing problem задача массового обслуживания real-time problem вчт. задача решаемая в реальном времени real-world problem практическая задача real-world problem реальная задача saddle-point problem задача нахождения седловой точки scaling problem проблема размерности scheduling problem задача планирования sequential decision problem задача последовательного принятия решений servicing problem задача массового обслуживания set the problem поставить задачу set the problem ставить задачу shortest path problem задача о кратчайшем пути shortest route problem задача о кратчайшем пути smoothing problem задача о сглаживании social problem социальная проблема software problem проблема программного обеспечения sojourn time problem задача о времени пребывания solder-ball problem проблема шарика припоя solvable problem разрешимая задача solve a problem решать проблему stale data problem проблема устаревших данных statistical problem статистическая задача symmetric problem симметричная задача symmetrical problem симметричная задача system analysis problem задача системного анализа test problem тестовая задача toy problem искусственная задача trade-off problem проблема компромиссных решений transportation problem транспортная задача transshipment problem транспортная задача промежуточных пунктов traveling salesman problem задача коммивояжера trim problem задача о раскрое trouble-shooting problem вчт. диагностическая задача unsymmetrical problem несимметричная задача urgent problem неотложная проблема waiting-line problem вчт. задача массового обслуживания waiting-line problem задача массового обслуживания waiting-time problem вчт. задача о времени ожидания warehouse problem задача о рациональном использовании склада warehouse storage problem задача о рациональном использовании склада weak bridge problem проблема слабой связки well-structured problem хорошо сформулированная задача

² = wank.

Ex. Channel 4 has postponed transmission of its 'wank week' programming in a bid to avoid further controversy.

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* hacerle una paja a un muerto = flog + a dead horse, beat + a dead horse, fart + in the wind.

* hacerse una paja = wank, jerk + Reflexivo + off.

* paja mental = mental masturbation.

1) Компьютерная техника: Multiple Original Printout

2) Военный термин: JCS Memorandum of Policy, Measures Of Performance, Memorandum of Policy, manner of performance, manual operations panel, manual override panel, measure of performance, medical outpatient, message output processing, method of preparation, mission operations plan, mobility operating procedure, mode of operation, model operational plan, monitor panel, mustering-out pay, Ministry of Defense Industry (FSU), боеприпас большой мощности заглубляющегося типа (для поражения высокопрочных заглубленных целей, напр., бункеров; сокр. от "massive ordnance penetrator")

3) Техника: main oil pump, maintenance operational procedures, maintenance operations program, maintenance outline procedure, manual optical picture analysis, minimum output power, modification of procedure, monthly operating plan

4) Шутливое выражение: Mashed Out Posse

5) Химия: Muriate Of Potash

6) Математика: многоцелевое программирование (multiobjective programming)

7) Юридический термин: Mash Out Posse

8) Страхование: manufacturers output policy

9) Биржевой термин: Maximum Offering Price

10) Грубое выражение: Make Out Party

11) Сокращение: Macau Pataca, Magnetic Orange Pipe, manned orbital platform, Meeting of the Parties, Measure Of Performance (Critical and essential aspect of all sorts of business activities (training, delegation, planning anything, product development etc.))

12) Физиология: Mental Or Physical

13) Электроника: Modify Operating Procedures

14) Вычислительная техника: Maintenance Operation Protocol, Multiple Original Prints, Meta Object Protocol (CLOS), Maintenance Operations Protocol (DEC)

15) Нефть: margin of overpull, monthly oil production, movable oil plot

16) Экология: оперативная программа "Метеосат", МОП

17) Деловая лексика: Major Opportunity Planning, Measuring Organizational Performance

18) Пластмассы: Modern Organic Products

19) Часовое производство: mother-of-pearl, перламутровый (Например - MOP dial - перламутровый циферблат часов)

20) Сахалин Ю: maximum operating pressure

21) Химическое оружие: maintenance operating procedure

22) Ювелирное дело: Перламутр (Mother of pearl)

23) Безопасность: Means Of Production

24) Расширение файла: Maintenance Operations Protocol, Multiple On-line Programming

25) Аэропорты: Mt. Pleasant Airport, Mount Pleasant, Michigan USA

26) НАСА: Memorandum Of Procedure

27) Программное обеспечение: Meta Object Protocol

28) ГОСТ: means of protection (IEC 60601-1, ed. 3.0 (2005-12))

1) Компьютерная техника: Multiple Original Printout

2) Военный термин: JCS Memorandum of Policy, Measures Of Performance, Memorandum of Policy, manner of performance, manual operations panel, manual override panel, measure of performance, medical outpatient, message output processing, method of preparation, mission operations plan, mobility operating procedure, mode of operation, model operational plan, monitor panel, mustering-out pay, Ministry of Defense Industry (FSU), боеприпас большой мощности заглубляющегося типа (для поражения высокопрочных заглубленных целей, напр., бункеров; сокр. от "massive ordnance penetrator")

3) Техника: main oil pump, maintenance operational procedures, maintenance operations program, maintenance outline procedure, manual optical picture analysis, minimum output power, modification of procedure, monthly operating plan

4) Шутливое выражение: Mashed Out Posse

5) Химия: Muriate Of Potash

6) Математика: многоцелевое программирование (multiobjective programming)

7) Юридический термин: Mash Out Posse

8) Страхование: manufacturers output policy

9) Биржевой термин: Maximum Offering Price

10) Грубое выражение: Make Out Party

11) Сокращение: Macau Pataca, Magnetic Orange Pipe, manned orbital platform, Meeting of the Parties, Measure Of Performance (Critical and essential aspect of all sorts of business activities (training, delegation, planning anything, product development etc.))

12) Физиология: Mental Or Physical

13) Электроника: Modify Operating Procedures

14) Вычислительная техника: Maintenance Operation Protocol, Multiple Original Prints, Meta Object Protocol (CLOS), Maintenance Operations Protocol (DEC)

15) Нефть: margin of overpull, monthly oil production, movable oil plot

16) Экология: оперативная программа "Метеосат", МОП

17) Деловая лексика: Major Opportunity Planning, Measuring Organizational Performance

18) Пластмассы: Modern Organic Products

19) Часовое производство: mother-of-pearl, перламутровый (Например - MOP dial - перламутровый циферблат часов)

20) Сахалин Ю: maximum operating pressure

21) Химическое оружие: maintenance operating procedure

22) Ювелирное дело: Перламутр (Mother of pearl)

23) Безопасность: Means Of Production

24) Расширение файла: Maintenance Operations Protocol, Multiple On-line Programming

25) Аэропорты: Mt. Pleasant Airport, Mount Pleasant, Michigan USA

26) НАСА: Memorandum Of Procedure

27) Программное обеспечение: Meta Object Protocol

28) ГОСТ: means of protection (IEC 60601-1, ed. 3.0 (2005-12))

1) модель; модификация

2) модель (образец; уменьшенная, упрощенная копия)

3) модель (абстрактная схема; концепция)

•

- abstract model

- business model

- camera model

- digital terrain model

- domain model

- pull model

- push model

- qualitative model

1) General subject: adjustment, aligner, arrangement, assembling, assembly, bump-in, establishment, fitting, fixing (предмета), guidepost, installation, line, mounting, orientation, placing, plant, policy, prescription, set, setting, setup, directive, precept, tenet

2) Geology: positioning

3) Aviation: deadheading, rigging up

4) Naval: building up, installation (инструмента)

5) Medicine: apparatus, facility, guideline, unit

6) Sports: stance

7) Military: (действие)(устройство) installation, mount (для орудия), (действие)(монтирование) mounting, (действие) placing, (силовая) plant, setting (данных), (действие)(устройство) unit

8) Engineering: complex, device, erecting work, erection, erection (машины), erection work, fixing, gear, incorporation, installation process, level (технологического параметра), machine (производственная), outfit, placement, range, rig, rigging, set-in, setup (регулируемой величины), site, startup, system

9) Agriculture: water conveyance and delivery efficiency

10) Construction: adjusting, building-up, erecting, thermostat setting, laying

11) Mathematics: aim, (детали на станок) loading, purpose, set (up)

12) Railway term: spacing (в определенном порядке или через отдельные интервалы)

13) Economy: fitting (оборудовани)

14) Accounting: installation (технологическая), process

15) Linguistics: attitude, background assumption

16) Automobile industry: making-ready, refitting, unit (величины)

17) Architecture: (технологическая) plant

18) Mining: mobile emergency winding equipment, rigging-up, setup (оборудования)

19) Diplomatic term: philosophy

20) Cinema: mental set

21) Forestry: assemblage, manifold, mill, planting

22) Metallurgy: contrivance

23) Polygraphy: stand (для испытания)

24) Psychology: (психологическая) attitude, mindset

25) Telecommunications: initialization (в исходное состояние), set-up

26) Electronics: bench, insertion (компонентов)

27) Information technology: install, set point, setting movement, situation

28) Oil: aggregate, equipment, holddown, installation (оборудования), landing (колонны труб в скважине), lay down, mounting (процесс), positioned operation, seating, setting up, setting-up, seek

29) Special term: tube

30) Astronautics: azimuth mount, fixture, installing, loading, set up, stand

31) Geophysics: array, circuit, configuration, layout, spread

32) Mechanic engineering: set hands square

33) Metrology: console, packaging

34) Mechanics: setting-out

35) Coolers: work

36) Ecology: mechanism, processor

37) Advertising: target

38) Business: operation

39) Drilling: instl (installation; оборудование)

40) Production: production plant

41) Microelectronics: tool

42) Solar energy: utility

43) Programming: (принудительная) coercion

44) Automation: docking (напр. фиксирующего пальца в отверстие), fitment, insertion (компонентов при сборке), (производственная) installation, interpretation, locating (заготовки или детали), location (заготовки или детали), register, registration

45) Quality control: bed, setup (заданной величины), station

46) Plastics: making true

47) Robots: insertion (компонентов в печатную плату), setting (в определённое состояние), setup (в определённое состояние), site (напр. вычислительная)

48) Sakhalin R: processing unit, unit (технологическая)

49) Cables: facilities, installation (действие), mounting (действие)

50) General subject: mount (механизм), positioning (угла поворотной шайбы)

51) Aviation medicine: disposition, preparatory set

52) Psychoanalysis: suggestion (в гипнозе)

53) Makarov: adjustment (процесс), adjustment (регулировка), adjustment (регулировка величины по прибору), app (apparatus), apparatus (устройство, прибор), assembly (процесс сборки, монтажа), erection (напр., машины), erection (процесс сборки, монтажа), facility (устройство, прибор), fit, fit (в проектное положение), fitting-up, fixation, frame, framework, installation (оборудование), installation (производственная), installation (процесс), installation (процесс сборки, монтажа), installation (устройство, прибор), interposition, maker, mounting (процесс сборки, монтажа), plant (агрегат), plant (в зависимости от производства, получения какого-л. продукта, материала и т.п.), plant (устройство, прибор), set (агрегат), set-up (конкретной величины), setting (конкретной величины), stage (процесс), unit (агрегат), unit (устройство, прибор)

54) Security: housing (оборудования), installation (объект), setting (параметров)

55) Gold mining: setup (приборов и т.д.)

56) SAP.tech. fetching

57) oil&gas: (напр. по очистке газа) plant

58) Combustion gas turbines: setting (чего-л.)