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1 опробование скважины на приток
Русско-английский словарь по нефти и газу > опробование скважины на приток
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2 опробование скважины на приток
Oil&Gas technology production-well testingУниверсальный русско-английский словарь > опробование скважины на приток
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3 метод испытаний в эксплуатируемой скважине
Русско-английский словарь нормативно-технической терминологии > метод испытаний в эксплуатируемой скважине
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4 эксплуатационные испытания
1) Aviation: field tests, in-service testing, operation tests2) Military: actual tests, employment testing3) Engineering: actual test, beta test, commercial test, development and operational testing, field test, in-service test, operational test, operational trials, performance test, real-life test, service test, use test4) Construction: service trial5) Railway term: tests on the line, service testing6) Economy: field trials, service trials7) Insurance: running tests8) Automobile industry: driving test (автомобиля)9) Information technology: operation testing10) Oil: OT (operation test), ST (service test), field proving, real-life test, running test, service test, well test, well testing11) Mechanics: working test12) Coolers: pilot case13) Business: driving test, field trial, performance tests, tests under normal working conditions14) Sakhalin energy glossary: real-life tests, service tests15) Programming: operational testings16) Automation: performance testing17) Quality control: operation test18) Cables: operational tests19) General subject: performance test (машины)20) Makarov: commissioning test, maintenance test21) oil&gas: liquid production testУниверсальный русско-английский словарь > эксплуатационные испытания
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5 освоение скважины
2) Sakhalin energy glossary: stimulation, well production testing3) Oilfield: finishing the well4) oil&gas: well testing, well tests -
6 пробная эксплуатация скважины
1) Oil: well testing2) Sakhalin energy glossary: production testing of a well3) Oil&Gas technology well testУниверсальный русско-английский словарь > пробная эксплуатация скважины
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7 гидродинамические исследования
1) Naval: hydrodynamic research2) Oil: Well Testing (ГДИ), flow test, flowing test, hydrodynamical study3) Sakhalin energy glossary: well test4) oil&gas: pressure transient analysis, production testУниверсальный русско-английский словарь > гидродинамические исследования
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8 исследования в эксплуатируемой скважине
Oil&Gas technology producing-well testing, production-well loggingУниверсальный русско-английский словарь > исследования в эксплуатируемой скважине
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9 метод испытаний в эксплуатируемой скважине
Универсальный русско-английский словарь > метод испытаний в эксплуатируемой скважине
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10 метод исследования в эксплуатируемой скважине
Универсальный русско-английский словарь > метод исследования в эксплуатируемой скважине
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11 пробная эксплуатация
1) General subject: test operation2) Geology: exploration4) Mining: pilot production (10-4)5) Oil: burn-in, production test (скважины), production test flowing (испытание на приток), production test, gas lift (скважины), production test, pumping (скважины), production test, swabbing (скважины), production testing, production testing (of a well - скважины), trial development, producing test6) Sakhalin energy glossary: test production7) oil&gas: trial productionУниверсальный русско-английский словарь > пробная эксплуатация
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12 prova
"test;Probe;prova"* * *f ( esame) test( tentativo) attempt( testimonianza) proofdi abito fittingsports heatprova di laboratorio lab testa prova di bomba bombproofsalvo prova contraria unless otherwise statedper insufficienza di prove for lack of evidencemettere alla prova put to the test* * *prova s.f.1 ( dimostrazione) proof; ( elemento, mezzo di prova) evidence [U]: ne abbiamo le prove, we have evidence of it; diede prova di essere un vero amico, he proved to be a real friend; è una prova della sua innocenza, this is a proof of (o this proves) his innocence; voglio la prova di quanto hai detto, I want proof of what you said // dare prova di, to give proof of: ha dato prova di eccellente preparazione, he showed excellent preparation // (dir.): prova diretta, direct evidence; prova indiziaria, indiretta, circumstantial (o indirect) evidence; prova a carico, a discarico, evidence for the prosecution, for the defence; prova per sentito dire, de auditu, hearsay evidence; prova illecita, illegally obtained evidence; prova reale, tangible evidence; prova non rilevante, irrelevant evidence; regole di prova, rules of evidence; il valore ( probante) della prova, the weight of evidence; prova in contrario, evidence to the contrary; la prova riguarda..., the evidence relates to... // fino a prova contraria, until one has proof to the contrary2 ( controllo, esperimento) test; trial; ( di dipendente) probation: superare una prova, to pass a test; mettere qlcu. alla prova, to put s.o. to the test (o to test s.o.); sembra buono ma bisogna vederlo alla prova, it looks good on paper but we'll need to see it tested // assumere qlcu. in prova, to take s.o. on for a trial period; il periodo di prova è di tre mesi, the trial period is three months; il nuovo impiegato è ancora in prova, the new clerk is still on probation // (comm.): prova del prodotto, product test; prova di vendita, sales test // (econ.): prova di mercato, market test; prova su zona, area test; prova di produzione, production test3 (tecn.) test, trial: prova a fatica, fatigue test; prova all'urto, shock (o impact) test; prova a trazione, tensile test; prova conclusiva, crucial test; prova di affidabilità, reliability test; prova di collaudo, acceptance test; prova di durata, endurance (o life) test; prova di durezza, hardness test; prova di elasticità, elasticity test; prova di laboratorio, laboratory test; prova di pressione, pressure test; prova di sicurezza, safety test; apparecchiatura di prova, test set; banco di prova, testing bench; mettere una macchina in prova, to test a machine // (mecc.): prova al banco, bench test; prova al freno, brake test // (elettr.): prova ad alta tensione, high-voltage test; prova di isolamento, insulation test; prova di rigidità dielettrica, electric strength test // (chim.) prova alla fiamma, flame test // (tess.) prova dei filati, yarn testing // (mar.): prova agli ormeggi, quay trial; prova a tutta forza, full-power trial // (aer.): prova a terra, ground test; prova di volo, flight trial; volo di prova, trial flight // (aut.): prova di consumo, fuel consumption test; prova di velocità, speed test; prova su strada, road test; targa di prova, temporary plate // (mil.) prova di tiro, range trial // (sport) prova di durata, long-distance trial // (inform.): prova del programma, programme checkout; prova automatica, self-test4 a prova di, proof (attr.): a prova di bomba, bombproof; a prova di cannone, shellproof; a prova di ruggine, rustproof; a prova di umidità, wetproof5 ( scolastica) test, examination: prova orale, oral test (o examination); prova scritta, written test (o examination); sostenere una prova, to take (o to do o to sit for) an examination6 (fig.) trial, ordeal: fu una dura prova, it was a severe trial (o ordeal); la sua vita fu piena di prove, his life was full of trials7 ( tentativo) try: farò una prova, I shall try; prima di cambiarlo facciamo un'ultima prova, before changing it let's have another try9 (di abito, durante la confezione) fitting: ho fatto tre prove per questo abito, I've had three fittings for this dress; mettere in prova un abito, to make a dress ready for a fitting10 (teatr., mus.) rehearsal: prova generale, dress rehearsal, (mus.) final rehearsal; ogni giorno facciamo tre ore di prova, every day we rehearse for three hours11 (tip.) proof: foglio di prova, ( di stampa) specimen page; prima prova, foul (o flat) proof; seconda prova, revise; terza prova, second revise; prova in colonna, galley proof; correggere una prova, to correct a proof; tirare una prova, to pull a proof12 (mat.) proof: fa' la prova di questa addizione, check this sum; prova del nove, casting out nines: fare la prova del nove, to cast out nines13 ( sportiva) trials (pl.): la prova dei 100 metri, the 100 metres trials; le prove del Gran Premio inizieranno alle 13, the Grand Prix trials will begin at 1 p.m.* * *['prɔva]sostantivo femminile1) (dimostrazione) proof U, evidence Udare prova di — to show [fermezza, coraggio]
essere la prova di — to testify to, to bear testimony to [fatto, ostilità]
dare buona prova di sé — to give a good account of oneself, to acquit oneself well
2) dir. evidence U, proof; (documento) exhibit3) mat. (operazione di verifica) proof4) aut. ind. tecn. (collaudo) trial (run)prova su strada — road test, test drive
volo, giro di prova — test flight, run
5) (esperimento) testfare delle -e — to do o run tests, to test
6) (verifica) test; (di persona) trial, testassumere qcn. in prova — to give sb. a trial, to try sb. (out)
periodo di prova — trial o probational period
essere all'altezza della prova — to rise to o meet the challenge
"uno, due, tre, prova" — "one, two, three, testing"
mettere alla prova — to (put to the) test, to try [persona, capacità, resistenza]
mettere a dura prova — to put a strain on, to strain o try [sth.] to the limit [pazienza, rapporto]
ho bisogno di un lavoro che mi metta alla prova — I need a job that stretches o challenges me
"mettimi alla prova!" — "try me!"
7) (tentativo) try8) (esame) test, exam(ination)- e scritte — written proof o examinations
9) tip.10) (momento difficile) ordeal, hardship11) (manifestazione)12) sport event; (prestazione) performance- e eliminatorie — heats
prova di velocità, a cronometro — speed, time trial
13) teatr. mus. rehearsalfare le -e — to rehearse, to practise
14) sart. fittingcabina o camerino di prova — changing o fitting room
15) a prova dia prova di bomba — [ rifugio] shell-proof; fig. [pazienza, solidità] bombproof
a prova di scasso — burglar-proof, tamper-proof
•prova a carico — dir. evidence for the prosecution
prova a discarico — dir. evidence for the defence
prova d'esame — examination o exam paper
prova generale — teatr. dress rehearsal, trial run
prova del nove — mat. casting out nines; fig. litmus test, acid test
prova di resistenza — sport mil. endurance test
••a tutta prova — [ coraggio] unflinching
* * *prova/'prɔva/sostantivo f.1 (dimostrazione) proof U, evidence U; dare prova di to show [fermezza, coraggio]; essere la prova di to testify to, to bear testimony to [fatto, ostilità]; è la prova che it's a sure sign that; dare buona prova di sé to give a good account of oneself, to acquit oneself well; fino a prova contraria until proved otherwise2 dir. evidence U, proof; (documento) exhibit; una prova a piece of evidence; insufficienza di -e insufficient evidence3 mat. (operazione di verifica) proof4 aut. ind. tecn. (collaudo) trial (run); fare delle -e to run trials; il nuovo modello è in prova the new model is undergoing trials; prova su strada road test, test drive; volo, giro di prova test flight, run5 (esperimento) test; fare delle -e to do o run tests, to test; prova di laboratorio laboratory test6 (verifica) test; (di persona) trial, test; assumere qcn. in prova to give sb. a trial, to try sb. (out); periodo di prova trial o probational period; essere all'altezza della prova to rise to o meet the challenge; "uno, due, tre, prova" "one, two, three, testing"; mettere alla prova to (put to the) test, to try [persona, capacità, resistenza]; mettere a dura prova to put a strain on, to strain o try [sth.] to the limit [pazienza, rapporto]; ho bisogno di un lavoro che mi metta alla prova I need a job that stretches o challenges me; "mettimi alla prova!" "try me!"7 (tentativo) try; fare una prova to have a try8 (esame) test, exam(ination); prova orale oral examination; - e scritte written proof o examinations9 tip. prova di stampa proof10 (momento difficile) ordeal, hardship; superare una prova to go through an ordeal11 (manifestazione) prova d'amore demonstration of love; come prova della sua amicizia as a pledge of her friendship12 sport event; (prestazione) performance; - e eliminatorie heats; prova di velocità, a cronometro speed, time trial13 teatr. mus. rehearsal; fare le -e to rehearse, to practise14 sart. fitting; cabina o camerino di prova changing o fitting room15 a prova di a prova di bomba [ rifugio] shell-proof; fig. [pazienza, solidità] bombproof; a prova di scasso burglar-proof, tamper-proofa tutta prova [ coraggio] unflinching\prova d'acquisto proof of purchase; prova a carico dir. evidence for the prosecution; prova a discarico dir. evidence for the defence; prova d'esame examination o exam paper; prova generale teatr. dress rehearsal, trial run; prova del nove mat. casting out nines; fig. litmus test, acid test; prova di resistenza sport mil. endurance test. -
13 Artificial Intelligence
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)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)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, EventuallyJust 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 ProgramMany 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)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)[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)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 FormThe 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)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)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)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)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 FormationIt 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)We might distinguish among four kinds of 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.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.... 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)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 ContextsEven 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)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)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 IntelligenceThe 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)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 PropositionsIn 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)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)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)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)Historical dictionary of quotations in cognitive science > Artificial Intelligence
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14 Bakewell, Robert
SUBJECT AREA: Agricultural and food technology[br]b. 23 May 1725 Loughborough, Englandd. 1 October 1795 Loughborough, England[br]English livestock breeder who pioneered the practice of progeny testing for selecting breeding stock; he is particularly associated with the development of the Improved Leicester breed of sheep.[br]Robert Bakewell was the son of the tenant farming the 500-acre (200 hectare) Dishley Grange Farm, near Loughborough, where he was born. The family was sufficiently wealthy to allow Robert to travel, which he began to do at an early age, exploring the farming methods of the West Country, Norfolk, Ireland and Holland. On taking over the farm he continued the development of the irrigation scheme begun by his father. Arthur Young visited the farm during his tour of east England in 1771. At that time it consisted of 440 acres (178 hectares), 110 acres (45 hectares) of which were arable, and carried a stock of 60 horses, 400 sheep and 150 other assorted beasts. Of the arable land, 30 acres (12 hectares) were under root crops, mainly turnips.Bakewell was not the first to pioneer selective breeding, but he was the first successfully to apply selection to both the efficiency with which an animal utilized its food, and its physical appearance. He always had a clear idea of the animal he wanted, travelled extensively to collect a range of animals possessing the characteristics he sought, and then bred from these towards his goal. He was aware of the dangers of inbreeding, but would often use it to gain the qualities he wanted. His early experiments were with Longhorn cattle, which he developed as a meat rather than a draught animal, but his most famous achievement was the development of the Improved Leicester breed of sheep. He set out to produce an animal that would put on the most meat in the least time and with the least feeding. As his base he chose the Old Leicester, but there is still doubt as to which other breeds he may have introduced to produce the desired results. The Improved Leicester was smaller than its ancestor, with poorer wool quality but with greatly improved meat-production capacity.Bakewell let out his sires to other farms and was therefore able to study their development under differing conditions. However, he made stringent rules for those who hired these animals, requiring the exclusive use of his rams on the farms concerned and requiring particular dietary conditions to be met. To achieve this control he established the Dishley Society in 1783. Although his policies led to accusations of closed access to his stock, they enabled him to keep a close control of all offspring. He thereby pioneered the process now recognized as "progeny testing".Bakewell's fame and that of his farm spread throughout the country and overseas. He engaged in an extensive correspondence and acted as host to all of influence in British and overseas agriculture, but it would appear that he was an over-generous host, since he is known to have been in financial difficulties in about 1789. He was saved from bankruptcy by a public subscription raised to allow him to continue with his breeding experiments; this experience may well have been the reason why he was such a staunch advocate of State funding of agricultural research.[br]Further ReadingWilliam Houseman, 1894, biography, Journal of the Royal Agricultural Society. 1–31. H.C.Parsons, 1957, Robert Bakewell (contains a more detailed account).R.Trow Smith, 1957, A History of British Livestock Husbandry to 1700, London: Routledge \& Kegan Paul.—A History of British Livestock Husbandry 1700 to 1900 (places Bakewell within the context of overall developments).M.L.Ryder, 1983, Sheep and Man, Duckworth (a scientifically detailed account which deals with Bakewell within the context of its particular subject).AP -
15 вызов притока в скважину
1) Oil: stimulation of well2) Sakhalin energy glossary: well production testingУниверсальный русско-английский словарь > вызов притока в скважину
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16 пробная эксплуатация скважин(ы)
Karachaganak: well production testingУниверсальный русско-английский словарь > пробная эксплуатация скважин(ы)
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17 пробная эксплуатация скважин
Karachaganak: (ы) well production testingУниверсальный русско-английский словарь > пробная эксплуатация скважин
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18 реактор
kettle хим., reactor, ( гидротрансформатора) stator* * *реа́ктор м.
reactorбиологи́ческий реа́ктор — fermenterреа́ктор гидротрансформа́тора — stator of a fluid torque converterтермоя́дерный реа́ктор — thermonuclear [fusion] reactorхими́ческий реа́ктор — reactor, reaction vesselвключа́ть [вводи́ть] (хими́ческий) реа́ктор в проце́сс — put a reactor on streamвыводи́ть (хими́ческий) реа́ктор из проце́сса — take a reactor off streamиспо́льзовать (хими́ческий) реа́ктор в за́мкнутом ко́нтуре с (други́м аппара́том) — operate a reactor in a closed circuit with …масштаби́ровать (хими́ческий) реа́ктор — scale up a reactorразгоня́ть (хими́ческий) реа́ктор — start up a reactorхими́ческий, диффузио́нный реа́ктор — dispersion reactorхими́ческий реа́ктор идеа́льного вытесне́ния — plug-flow reactorхими́ческий реа́ктор идеа́льного смеше́ния — perfect-mixing reactorхими́ческий, плё́ночный реа́ктор — film reactorхими́ческий, прото́чный реа́ктор с меша́лкой — well-stirred continuous reactor, WSCR, continuous stirred tank reactor, CSTRхими́ческий, секциони́рованный реа́ктор — section reactorхими́ческий реа́ктор с комбини́рованной структу́рой пото́ка — hybrid reactorхими́ческий реа́ктор с меша́лкой — stirred reactorхими́ческий, теплообме́нный реа́ктор — thermal exchange reactorхими́ческий, яче́ечный реа́ктор — cascade reactorэлектри́ческий, ано́дный реа́ктор — брит. anode reactor; амер. plate reactorэлектри́ческий, бето́нный реа́ктор — cast-in(-concrete) reactorэлектри́ческий, заземля́ющий реа́ктор — брит. earthing reactor; амер. grounding reactorэлектри́ческий, защи́тный реа́ктор — protective reactorэлектри́ческий, пусково́й реа́ктор — starting reactorэлектри́ческий, разря́дный реа́ктор — discharge coilэлектри́ческий, регулиро́вочный реа́ктор — regulating inductorэлектри́ческий реа́ктор с возду́шным серде́чником — air(-core) reactorэлектри́ческий, сгла́живающий реа́ктор — smoothing reactorэлектри́ческий реа́ктор с желе́зным серде́чником — iron-core(d) reactorэлектри́ческий, токоограни́чивающий реа́ктор — current-limiting reactorэлектри́ческий, ши́нный реа́ктор — bus reactorэлектри́ческий, шунти́рующий реа́ктор — shunt reactorя́дерный реа́ктор — nuclear reactorобеспе́чивать (я́дерный) реа́ктор защи́той — safeguard a reactorостана́вливать (я́дерный) реа́ктор — shut down a (nuclear) reactorостана́вливать я́дерный реа́ктор автомати́чески в авари́йной ситуа́ции — scram a reactorпуска́ть (я́дерный) реа́ктор — start up a reactorрегули́ровать (я́дерный) реа́ктор — control a reactorустана́вливать (я́дерный) реа́ктор в биозащи́ту — shield a reactor(я́дерный) реа́ктор вступа́ет в крити́ческий режи́м — the reactor goes criticalя́дерный, бассе́йновый реа́ктор — pool-type reactorя́дерный реа́ктор без отража́теля — bare reactorя́дерный, бы́стрый реа́ктор жарг. — fast reactorя́дерный, во́до-водяно́й реа́ктор — water-moderated [water-cooled] reactorя́дерный, гетероге́нный реа́ктор — heterogeneous reactorя́дерный, гомоге́нный реа́ктор — homogeneous reactorя́дерный реа́ктор для получе́ния я́дерного горю́чего — production [regenerative] reactorя́дерный, испыта́тельный реа́ктор — testing reactorя́дерный, иссле́довательский реа́ктор — research(-and-development) reactorя́дерный, ко́рпусный реа́ктор — shell-type reactorя́дерный реа́ктор на бы́стрых нейтро́нах — fast reactorя́дерный реа́ктор на ме́дленных нейтро́нах — thermal [slow] reactorя́дерный реа́ктор на обогащё́нном ура́не — enriched-uranium reactorя́дерный реа́ктор на тепловы́х нейтро́нах — thermal [slow] reactorя́дерный реа́ктор нулево́й мо́щности — zero-power reactorя́дерный реа́ктор о́бщего назначе́ния — general-purpose reactorя́дерный реа́ктор, охлажда́емый водо́й под давле́нием — pressurized water reactorя́дерный, промежу́точный реа́ктор — intermediate reactorя́дерный, регенерати́вный реа́ктор — regenerative reactorя́дерный реа́ктор с графи́товым замедли́телем — graphite-moderated reactorя́дерный реа́ктор с замедли́телем — moderated reactorя́дерный реа́ктор с кипя́щей водо́й — boiling water [water-boiler] reactorя́дерный, теплово́й реа́ктор — thermal [slow] reactorя́дерный, шла́мовый реа́ктор — slurry reactorя́дерный, энергети́ческий реа́ктор — power reactor
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