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101 conservation scientists and foresters
эк. тр., амер. специалисты по охране окружающей среды и лесоводы* (по SOC включают в себя следующие группы профессий: "специалисты по охране окружающей среды" и "лесоводы"; входят в подраздел "научные сотрудники в биологических науках" в разделе "профессии в биологических, физических и общественных науках")See:Англо-русский экономический словарь > conservation scientists and foresters
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102 board
комитет; совет; комиссия; планшет; доска; пульт; борт; совершать посадку (на) ; садиться (напр. на корабль, машину) ; разг. «комиссовать, увольнять по состоянию здоровья; пропускать через комиссию; см. тж. committeeArmy (Central) Physical Evaluation board — (центральная) комиссия СВ по оценке уровня физической подготовки ЛС
Army Airborne, Electronics and Special Warfare board — комитет СВ по авиационным бортовым электронным системам и специальным методам ведения боевых действий
— on board— target status board -
103 scientist
nounWissenschaftler, der/Wissenschaftlerin, die; (in physical or natural science) Naturwissenschaftler, der/-wissenschaftlerin, diebiological/social/computer scientists — Biologen/Soziologen/Informatiker
* * ** * *sci·en·tist[ˈsaɪəntɪst]he is employed as a research \scientist at NASA er arbeitet als Forscher bei der NASA* * *['saIəntɪst]n(Natur)wissenschaftler( in) m(f)* * *1. (Natur)Wissenschaftler(in)* * *nounWissenschaftler, der/Wissenschaftlerin, die; (in physical or natural science) Naturwissenschaftler, der/-wissenschaftlerin, diebiological/social/computer scientists — Biologen/Soziologen/Informatiker
* * *n.Forscher - m.Wissenschaftler m.Wissenschaftlerin f. -
104 Noyce, Robert
SUBJECT AREA: Electronics and information technology[br]b. 12 December 1927 Burlington, Iowa, USA[br]American engineer responsible for the development of integrated circuits and the microprocessor chip.[br]Noyce was the son of a Congregational minister whose family, after a number of moves, finally settled in Grinnell, some 50 miles (80 km) east of Des Moines, Iowa. Encouraged to follow his interest in science, in his teens he worked as a baby-sitter and mower of lawns to earn money for his hobby. One of his clients was Professor of Physics at Grinnell College, where Noyce enrolled to study mathematics and physics and eventually gained a top-grade BA. It was while there that he learned of the invention of the transistor by the team at Bell Laboratories, which included John Bardeen, a former fellow student of his professor. After taking a PhD in physical electronics at the Massachusetts Institute of Technology in 1953, he joined the Philco Corporation in Philadelphia to work on the development of transistors. Then in January 1956 he accepted an invitation from William Shockley, another of the Bell transistor team, to join the newly formed Shockley Transistor Company, the first electronic firm to set up shop in Palo Alto, California, in what later became known as "Silicon Valley".From the start things at the company did not go well and eventually Noyce and Gordon Moore and six colleagues decided to offer themselves as a complete development team; with the aid of the Fairchild Camera and Instrument Company, the Fairchild Semiconductor Corporation was born. It was there that in 1958, contemporaneously with Jack K. Wilby at Texas Instruments, Noyce had the idea for monolithic integration of transistor circuits. Eventually, after extended patent litigation involving study of laboratory notebooks and careful examination of the original claims, priority was assigned to Noyce. The invention was most timely. The Apollo Moon-landing programme announced by President Kennedy in May 1961 called for lightweight sophisticated navigation and control computer systems, which could only be met by the rapid development of the new technology, and Fairchild was well placed to deliver the micrologic chips required by NASA.In 1968 the founders sold Fairchild Semicon-ductors to the parent company. Noyce and Moore promptly found new backers and set up the Intel Corporation, primarily to make high-density memory chips. The first product was a 1,024-bit random access memory (1 K RAM) and by 1973 sales had reached $60 million. However, Noyce and Moore had already realized that it was possible to make a complete microcomputer by putting all the logic needed to go with the memory chip(s) on a single integrated circuit (1C) chip in the form of a general purpose central processing unit (CPU). By 1971 they had produced the Intel 4004 microprocessor, which sold for US$200, and within a year the 8008 followed. The personal computer (PC) revolution had begun! Noyce eventually left Intel, but he remained active in microchip technology and subsequently founded Sematech Inc.[br]Principal Honours and DistinctionsFranklin Institute Stuart Ballantine Medal 1966. National Academy of Engineering 1969. National Academy of Science. Institute of Electrical and Electronics Engineers Medal of Honour 1978; Cledo Brunetti Award (jointly with Kilby) 1978. Institution of Electrical Engineers Faraday Medal 1979. National Medal of Science 1979. National Medal of Engineering 1987.Bibliography1955, "Base-widening punch-through", Proceedings of the American Physical Society.30 July 1959, US patent no. 2,981,877.Further ReadingT.R.Reid, 1985, Microchip: The Story of a Revolution and the Men Who Made It, London: Pan Books.KF -
105 Clarke, Arthur Charles
[br]b. 16 December 1917 Minehead, Somerset, England[br]English writer of science fiction who correctly predicted the use of geo-stationary earth satellites for worldwide communications.[br]Whilst still at Huish's Grammar School, Taunton, Clarke became interested in both space science and science fiction. Unable to afford a scientific education at the time (he later obtained a BSc at King's College, London), he pursued both interests in his spare time while working in the Government Exchequer and Audit Department between 1936 and 1941. He was a founder member of the British Interplanetary Society, subsequently serving as its Chairman in 1946–7 and 1950–3. From 1941 to 1945 he served in the Royal Air Force, becoming a technical officer in the first GCA (Ground Controlled Approach) radar unit. There he began to produce the first of many science-fiction stories. In 1949–50 he was an assistant editor of Science Abstracts at the Institution of Electrical Engineers.As a result of his two interests, he realized during the Second World War that an artificial earth satellite in an equatorial orbital with a radius of 35,000 km (22,000 miles) would appear to be stationary, and that three such geo-stationary, or synchronous, satellites could be used for worldwide broadcast or communications. He described these ideas in a paper published in Wireless World in 1945. Initially there was little response, but within a few years the idea was taken up by the US National Aeronautics and Space Administration and in 1965 the first synchronous satellite, Early Bird, was launched into orbit.In the 1950s he moved to Ceylon (now Sri Lanka) to pursue an interest in underwater exploration, but he continued to write science fiction, being known in particular for his contribution to the making of the classic Stanley Kubrick science-fiction film 2001: A Space Odyssey, based on his book of the same title.[br]Principal Honours and DistinctionsClarke received many honours for both his scientific and science-fiction writings. For his satellite communication ideas his awards include the Franklin Institute Gold Medal 1963 and Honorary Fellowship of the American Institute of Aeronautics and Astronautics 1976. For his science-fiction writing he received the UNESCO Kalinga Prize (1961) and many others. In 1979 he became Chancellor of Moratuwa University in Sri Lanka and in 1980 Vikran Scrabhai Professor at the Physical Research Laboratory of the University of Ahmedabad.Bibliography1945. "Extra-terrestrial relays: can rocket stations give world wide coverage?", Wireless World L1: 305 (puts forward his ideas for geo-stationary communication satellites).1946. "Astronomical radar: some future possibilities", Wireless World 52:321.1948, "Electronics and space flight", Journal of the British Interplanetary Society 7:49. Other publications, mainly science-fiction novels, include: 1955, Earthlight, 1956, TheCoast of Coral; 1958, Voice Across the Sea; 1961, Fall of Moondust; 1965, Voicesfrom the Sky, 1977, The View from Serendip; 1979, Fountain of Paradise; 1984, Ascent to Orbit: A Scientific Autobiography, and 1984, 2010: Odyssey Two (a sequel to 2001: A Space Odyssey that was also made into a film).Further Reading1986, Encyclopaedia Britannica.1991, Who's Who, London: A. \& C.Black.See also: Pierce, John RobinsonKF -
106 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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107 astronomers
эк. тр., амер. астрономы* (по SOC: наблюдают, изучают и интерпретируют небесные и астрономические явления с целью увеличения фундаментальных знаний и приложения этой информации к решению практических проблем; входит в подраздел "астрономы и физики" в разделе "профессии в биологических, физических и общественных науках")See: -
108 astronomers and physicists
эк. тр., амер. астрономы и физики (по SOC включает в себя следующие группы профессий: "астрономы" и "физики"; входит в подраздел "научные сотрудники в физических науках" в разделе "профессии в биологических, физических и общественных науках")See:Англо-русский экономический словарь > astronomers and physicists
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109 biochemists and biophysicists
эк. тр., амер. биохимики и биофизики* (изучают химическое строение и физические принципы жизни клеток и организмов, их электрическую и механическую энергию и связанные с этим явления; проводят исследования с целью углубленного изучения сложных химических сочетаний и реакций, связанных с обменом веществ, репродукцией, ростом и наследственностью; могут изучать влияние пищи, сывороток, гормонов и других веществ на ткани и жизненные процессы в живых организмах; по SOC входят в подраздел "биологи" в разделе "профессии в биологических, физических и общественных науках")See:Англо-русский экономический словарь > biochemists and biophysicists
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110 conservation scientists
эк. тр., амер. специалисты по охране окружающей среды* (по SOC: занимаются усовершенствованием, защитой и управлением в области естественных ресурсов с целью их максимального использования без ущерба окружающей среде; могут изучать почвы и разрабатывать планы по устранению эрозии почв или защите природных пастбищ от огня или грызунов и т. д.; входят в подраздел "специалисты по охране окружающей среды" в разделе "профессии в биологических, физических и общественных науках")See:Англо-русский экономический словарь > conservation scientists
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111 economists
эк. тр., амер. экономисты (по SOC: ведут исследования, готовят отчеты или формируют планы, призванные помочь в решении экономических проблем, связанных с производством и распределением товаров и услуг; пользуясь эконометрическими и выборочными методами, могут собирать и обрабатывать экономические и статистические данные; входят в раздел "профессии в биологических, физических и общественных науках")See: -
112 forest and conservation technicians
эк. тр., амер. технологи-лесоводы и специалисты по защите леса* (по SOC: собирают данные относительно размера, содержания, условий и других характеристик лесных массивов; обучают и направляют лесных рабочих в сфере лесоводства и предотвращения и локализации пожаров; входят в подраздел "разные технические специалисты в биологических, физических и общественных науках" в разделе "профессии в биологических, физических и общественных науках")See:Англо-русский экономический словарь > forest and conservation technicians
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113 foresters
эк. тр., амер. лесоводы* (по SOC: занимаются управлением лесными площадями для экономических, рекреационных и консервационных целей; входят в подраздел "специалисты по охране окружающей среды и лесоводы" в разделе "профессии в биологических, физических и общественных науках")See: -
114 market and survey researchers
эк. тр., амер. исследователи рынка и массового поведения* (по SOC: включает в себя следующие группы профессий: "исследователи рынка" и "исследователи массового поведения"; входят в подраздел "научные сотрудники в общественных науках и родственные специальности" в разделе "профессии в биологических, физических и общественных науках")See:Англо-русский экономический словарь > market and survey researchers
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115 microbiologists
эк. тр., амер. микробиологи* (по SOC: изучают рост, структуру, развитие и другие характеристики микроскопических организмов, таких как бактерии; сюда входят микробиологи-медики, которые изучают взаимосвязь между организмами и болезнями и влияние на микроорганизмы антибиотиков; входят в подраздел "научные сотрудники в сельском хозяйстве и пищевой отрасли" в разделе "профессии в биологических, физических и общественных науках")See: -
116 miscellaneous social scientists and related workers
эк. тр., амер. разные специалисты в общественных науках и родственные специальности* (по SOC включает в себя следующие группы профессий: "антропологи и археологи", "географы", "историки", "политологи"; входят в подраздел "научные сотрудники в общественных науках и родственные специальности" в разделе "профессии в биологических, физических и общественных науках")See:Англо-русский экономический словарь > miscellaneous social scientists and related workers
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117 physicists
эк. тр., амер. физики* (по SOC: ведут исследования в области физических явлений, развивают теории и раскрывают законы на основе наблюдений и экспериментов, а также разрабатывают методы приложения этих законов и теорий к сфере производства и другим областям; входят в подраздел "астрономы и физики" в разделе "профессии в биологических, физических и общественных науках")See: -
118 Sociologists
эк. тр., амер. социологи* (по SOC: изучают человеческое общество и социальное поведение, исследуя группы и социальные институты, которые формируют люди, а также различные общественные, религиозные, политические и коммерческие организации; могут изучать поведение и взаимодействие групп, прослеживать их происхождение и рост, а также анализировать влияние деятельности групп на отдельных их членов; входят в раздел "Профессии в биологических, физических и общественных науках")See: -
119 Soil and Plant Scientists
эк. тр., амер. специалисты по почвам и растениям* (по SOC: проводят исследования по размножению, физиологии, производству, урожаю и управлению в области сельскохозяйственных культур; изучают их внутрипочвенный рост и контроль за вредителями; могут изучать химическое, физическое, биологическое и минералогическое строение почв и его соотношение с растениями и их ростом; входят в подраздел "Некораблестроительные архитекторы" в разделе "Профессии в биологических, физических и общественных науках")See:Англо-русский экономический словарь > Soil and Plant Scientists
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120 urban and regional planners
эк. тр., амер. специалисты по городскому и региональному планированию* (по SOC: разрабатывают всесторонние планы и программы для использования земли и физических объектов городов, мегаполисов или стран; входят в раздел "профессии в биологических, физических и общественных науках")See:Англо-русский экономический словарь > urban and regional planners
См. также в других словарях:
physical science — physical scientist. 1. any of the natural sciences dealing with inanimate matter or with energy, as physics, chemistry, and astronomy. 2. these sciences collectively. [1835 45] * * * Introduction the systematic study of the inorganic world … Universalium
Physical science — is an encompassing term for the branches of natural science and science that study non living systems, in contrast to the biological sciences. However, the term physical creates an unintended, somewhat arbitrary distinction, since many branches… … Wikipedia
physical science — Science Sci ence, n. [F., fr. L. scientia, fr. sciens, entis, p. pr. of scire to know. Cf. {Conscience}, {Conscious}, {Nice}.] 1. Knowledge; knowledge of principles and causes; ascertained truth of facts. [1913 Webster] If we conceive God s sight … The Collaborative International Dictionary of English
physical science — n any of the natural sciences (as physics, chemistry, and astronomy) that deal primarily with nonliving materials physical scientist n … Medical dictionary
physical science — n [U] also the physical sciences [plural] the sciences, for example ↑chemistry and ↑physics, that are concerned with studying things that are not living … Dictionary of contemporary English
physical science — noun count sciences such as geography and physics that deal with things that are not alive. Sciences such as biology that deal with things that are alive are called life sciences … Usage of the words and phrases in modern English
physical science — n. any of the sciences that deal with inanimate matter or energy, as physics, chemistry, geology, astronomy, etc … English World dictionary
physical science — noun the physical properties, phenomena, and laws of something (Freq. 3) he studied the physics of radiation • Syn: ↑physics • Hypernyms: ↑natural science • Hyponyms: ↑acoustics * * * … Useful english dictionary
physical science — UK / US noun [countable] Word forms physical science : singular physical science plural physical sciences sciences such as geography and physics that deal with things that are not alive. Sciences such as biology that deal with things that are… … English dictionary
Physical Science for Christian Schools — (1974) is written by Emmett L. Williams and George Mulfinger, Jr. and was the first text book published by Bob Jones University Press. This book has been described as follows [in 1974] a full scale, Bible science textbook rolls off the Bob Jones… … Wikipedia
physical science — physical sciences N COUNT: usu pl The physical sciences are branches of science such as physics, chemistry, and geology that are concerned with natural forces and with things that do not have life. ...the rapid growth of interest in both the… … English dictionary