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21 число
count, figure, number, numeral* * *число́ с.1. (совокупность предметов и т. п.) count, number2. ( математическое представление исчислимого количества) numberвводи́ть число́ (в счё́тную маши́ну) — key [enter] a number into (a calculator)изобража́ть число́ — represent a numberобознача́ть число́ — express a numberчисло́ о́бщее — total of …округли́ть число́ — round off a numberпредставля́ть число́ в дополни́тельном ко́де вчт. — cast a number in true complement formпредставля́ть число́ в обра́тном ко́де вчт. — cast a number in base [radix] minus ones complement formпредставля́ть число́ в прямо́м ко́де вчт. — cast a number in sign-and-magnitude [in sign-and-absolute value] formпредставля́ть двои́чное число́ в дополни́тельном ко́де вчт. — cast a binary number in 2's complement formпредставля́ть двои́чное число́ в обра́тном ко́де вчт. — cast a binary number in 1's complement formпредставля́ть десяти́чное число́ в дополни́тельном ко́де вчт. — cast a decimal number in 10's complement formпредставля́ть десяти́чное число́ в обра́тном ко́де вчт. — cast a decimal number in 9's complement formсбра́сывать чи́сла (на счё́тной маши́не) — clear the calculatorсоставля́ть ( такое-то) [m2]число́ — be in (such and such number)число́ кана́лов (составля́ет) четы́ре — the channels are four in numberусека́ть число́ — truncate a number4. ( количество) quantityпроверя́ть число́, напр. болто́в — check, e. g., the bolts for correct countчисло́ А́ббе — Abbe numberчисло́ Авога́дро — Avogadro numberарифмети́ческое число́ — arithmetic number, absolute numberа́томное число́ — atomic numberацето́новое число́ — acetone numberчисло́ без зна́ка вчт. — unsigned numberбезразме́рное число́ — dimensionless [nondimensional, pure] numberчисло́ Берну́лли — Bernoulli numberчисло́ Ве́бера — Weber numberвеще́ственное число́ — real numberвзаи́мно-просты́е чи́сла — coprime numbers, relatively prime numbersводоро́дное число́ — hydrogen numberводяно́е число́ ( калориметра) — water equivalentволново́е число́ — wave numberгидрокси́льное число́ — hydroxyl numberчисло́ Грасго́фа — Grashoff numberчисло́ Гре́ца — Graetz numberдвои́чно-десяти́чное число́ — binary coded decimal [BCD] numberдвои́чное число́ — binary numberдвои́чно-пятери́чное число́ — biquinary numberчисло́ двойны́х ходо́в в мину́ту — strokes per minute, s.p.m.десяти́чное число́ — decimal (number)десяти́чное, двои́чно-коди́рованное число́ — binary coded decimal [BCD] numberдокрити́ческое число́ мех. — subcritical numberдро́бное число́ — fraction, fractional [broken] numberзакрити́ческое число́ мех. — beyond-critical [supercritical] number
n-зна́чное число́ — n -digit numberзолото́е число́ — the golden numberизотопи́ческое число́ — isotopic numberимено́ванное число́ — denominate(d) numberиррациона́льное число́ — irrational (number), surd (number)ио́дное число́ — iodine number, iodine valueчисло́ кавита́ции — cavitation numberкардина́льное число́ — cardinality, cardinal numberчисло́ Карма́на — Karman numberква́нтовое число́ — quantum numberква́нтовое, азимута́льное число́ — azimuthal quantum numberква́нтовое, вну́треннее число́ — inner quantum numberква́нтовое, гла́вное число́ — first [principal] quantum numberква́нтовое, магни́тное число́ — magnetic quantum numberква́нтовое, спи́новое число́ — spin quantum numberкислоро́дное число́ — oxygen numberкисло́тное число́ — acid numberко́мплексное число́ — complex numberкоординацио́нное число́ — coordination numberкра́тное число́ — multipleкру́глое число́ — round numberчисло́ Ло́кка — Lock numberчисло́ Лошми́дта — Loschmidt numberчисло́ Лью́иса — Lewis numberчисло́ М — Mach (number), M numberс число́м М — triplesonicма́ссовое число́ яд. физ. — mass [nucleon] numberчисло́ Ма́ха — Mach (number), M numberчисло́ Ма́ха, гиперзвуково́е — hypersonic M numberчисло́ Ма́ха, дозвуково́е — subsonic M numberчисло́ Ма́ха, околозвуково́е — transonic M numberчисло́ Ма́ха, сверхзвуково́е — supersonic [over-one] M numberчисло́ мест (в транспортном средстве, зрительном зале и т. п.) — seating capacityмни́мое число́ — imaginary (number)многозна́чное число́ — multidigit [multiplace] numberнатура́льное число́ — natural numberчисло́ нейтрализа́ции — neutralization numberчисло́ нейтро́нов ( в ядре) — neutron numberненормализо́ванное число́ — nonnormalized numberнеотрица́тельное число́ — nonnegative numberнечё́тное число́ — odd numberнормализо́ванное число́ — standard [normalized] number, a number in normal formчисло́ Ну́ссельта — Nusselt numberчисло́ оборо́тов — rotational speedчисло́ оборо́тов в мину́ту — revolutions per minute, r.p.m.число́ оборо́тов дви́гателя — engine speedчисло́ оборо́тов дви́гателя на холосто́м ходу́ — idling speedчисло́ оборо́тов, уде́льное — specific speedчисло́ обраще́ний, допусти́мое ( в электростатических запоминающих трубках) — selection ratioчисло́ обраще́нии ме́жду регенера́циями ( в электростатическом запоминающем устройстве) — read-around number, read-around ratioчисло́ окисле́ния — oxidation numberокта́новое число́ — octane number, octane value, octane ratingчисло́ омыле́ния — saponification number, saponification valueордина́льное число́ — ordinal (number)отвлечё́нное число́ — dimensionless [nondimensional, pure] numberотноси́тельные чи́сла — directed [signed, algebraic] numbersотрица́тельное число́ — negative numberчисло́ Пекле́ — Peclet numberпереводно́е число́ ( в физической химии) — transference numberпереда́точное число́1. мех. gear ratioпереда́точное число́ ме́жду зубча́тыми колё́сами А и Б равно́ 60: [m2]1 — gears A and B are geared by 60 to 1переда́точное число́ от А к Б составля́ет 1:n ( в сервомеханизмах) — A is geared 1: n to B2. эл. gainпереда́точное число́ два к одному́ — two-to-one ratio, two-to-one gearчисло́ переда́ч — number of gearsпе́рекисное число́ — peroxide numberчисло́ перено́са1. ( в физической химии) transport number2. мат. carry quantityпермангана́тное число́ ( целлюлозы) — permanganate numberпифаго́ровы чи́сла — Pythagorean numbers, Pythagorean triplesподкоренно́е число́ — radicandпоря́дковое число́ — ordinal; ordinal [serial] numberчисло́ Пра́ндтля — Prandtl numberчисло́ проду́ба кож. — tanning numberпросто́е число́ — prime numberравнооста́точные чи́сла — congruent numbersчисло́ разря́дов в реги́стре — register lengthрациона́льное число́ — rational (number)число́ Рейно́льдса — Reynolds numberчисло́ Рейно́льдса, крити́ческое — transition Reynolds numberчисло́ Ре́йхерта—Ме́йссля — Reichert-Meissl numberрода́новое число́ — thiocyanogen number, thiocyanogen valueслуча́йные чи́сла — random numbersвыраба́тывать случа́йные чи́сла вчт. — generate random numbersсоставно́е число́ — composite numberспиртово́е число́ — alcohol numberчисло́ с пла́вающей запято́й — floating-point numberчисло́ Строуха́ла — Strouhal numberчисло́ Стэ́нтона — Stanton numberчисло́ с фикси́рованной запято́й — fixed-point numberчисло́ твё́рдости — hardness numberчисло́ твё́рдости по Брине́ллю — Brinell (hardness) numberчисло́ твё́рдости по Ви́ккерсу — Vickers (hardness) numberчисло́ твё́рдости по Моо́су — Moos (hardness) numberчисло́ твё́рдости по Ро́квеллу — Rockwell (hardness) numberчисло́ теорети́ческих таре́лок — theoretical plate numberчисло́ Фараде́я — Faraday constant, faradayфигу́рные чи́сла — figurate numbersфле́гмовое число́ хим. — reflux ratioчисло́ Фру́да — Froude numberце́лое число́ — integer, integral [whole] numberце́лое, ко́мплексное число́ — complex [Gaussian] integerцета́новое число́ — cetane numberчё́тное число́ — even numberчи́сто мни́мое число́ — pure imaginary (number)число́ Ше́рвуда — Sherwood numberчисло́ Шми́дта — Schmidt numberчисло́ Э́йлера — Euler numberэфи́рное число́ — ester number, ester value -
22 вычислительный центр
1) General subject: computation centre, computer centre, computer centre (внутри организации), central computing facility3) Engineering: computation center, computer center, computer facility (внутри организации), computer installation, computer shop, computing center, computing machine centre, computing shop, electronic data processing center, service center4) Law: calculation centre, computing centre5) Polygraphy: data processing center6) Information technology: EDP center, computer bureau, computer service bureau, computing services office (Система, обеспечивающая поиск по компьютерному справочнику учащихся и преподавателей какого-л. учебного заведения), digital arithmetic center, shop, site, computer bureaux7) Oil: computer service8) Astronautics: computer complex, data-processing center9) Mechanics: computing station10) Network technologies: DPC, glass house11) Automation: PC system, bureau service (по подготовке УП для станков с ЧПУ), center, centre, computation center (для централизованного использования и обслуживания вычислительной техники), computation office, computer center (для централизованного использования и обслуживания вычислительной техники), computer house, computing center (для централизованного использования и обслуживания вычислительной техники)12) Chemical weapons: computer center (ВЦ)13) SAP.tech. CCУниверсальный русско-английский словарь > вычислительный центр
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23 число
1. с. count, numberмах, число Маха, число M — Mach number
2. с. numberчисло общее — total of …
3. с. No. of …4. с. quantityСинонимический ряд:количество (сущ.) количество; численность -
24 σύνθετος
σύν-θετος, ον, also fem. συνθέτη (or συνθετή as in Lys.Fr.34, Arist.Ph. 265a21, Metaph. 1051b27, al.): ([etym.] συντίθημι):—A put together, compounded, composite, Pl.Phd. 78c, al.; of a centaur, διαιρετὸς.. καὶ πάλιν ς. X.Cyr.4.3.20, cf. Lys.l.c.; τὸ ς. the composite part of man, Arist.EN 1178a20;σ. ἐκ πολλῶν Pl.R. 611b
;ἐκ τῶν αὐτῶν Id.Phlb. 29e
; σ. ἀναγνώρισις complex, Arist.Po. 1455a12.2 σύνθετον, τό, compound, Id.Ph. 187b12; τὰ ς., opp. τὰ στοιχεῖα, Id.Cael. 306b20, cf. Metaph. 1070b8; so ἡ σύνθετος οὐσία ib. 1043a30; ἡ συνθέτη οὐσία ib. 1023b2, cf. de An. 412a16;αἱ μὴ σ. οὐσίαι Id.Metaph. 1051b27
; cf.σύγκειμαι 11.4
.3 in various technical senses,a in Grammar, φωνὴ ς. a. compound sound, i.e. a syllable, Id.Po. 1456b35; or a word, ib. 1457a11; φωνῶν αἱ μὲν ἁπλαῖ (e.g. Δίων) , αἱ δὲ ς. (e.g. Δίων περιπατεῖ) S.E.M.8.135; σ. ὀνόματα compound nouns, Arist.Rh.Al. 1434b34, Demetr.Eloc.91, Philomnest. 2;σ. σχῆμα D.T.635.21
; σ. προσηγορία (e. g. ὑπνώδης καταφορά) Gal.7.643. Adv.- τως Str.13.2.5
, Sor.2.26, Gal.6.549.b in Metre and Music, σ. ῥυθμός a compound foot, Pl.R. 400b; [διαστήματα] ς. Aristid.Quint.1.7, cf. Plu.2.1135b;ἁρμονίαν εἶναι σ. πρᾶγμα Pl.Phd. 92a
.c in Arithmetic, σ. ἀριθμός a number composed of several factors, Arist.Metaph. 1020b4, Euc.7 Def.14.d in Medicine, σύνθετα solid excrements, Hp.Coac. 109: also φάρμακον ς. compound drug,τὸ ξ. [φάρμακον] τὸ διὰ τῆς λιμνήστιδος καὶ εὐφορβίου καὶ πυρέθρου Aret.CD1.2
, cf. Hsch. s.v. φαρικόν.III metaph., agreed upon, covenanted, ὥσπερ ἐκ συνθέτου by agreement, Hdt.3.86.Greek-English dictionary (Αγγλικά Ελληνικά-λεξικό) > σύνθετος
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25 rate of return
Finan accounting ratio of the income from an investment to the amount of the investment, used to measure financial performance.EXAMPLEThere is a basic formula that will serve most needs, at least initially:[(Current value of amount invested – Original value of amount invested) / Original value of amount invested] × 100% = rate of returnIf $1,000 in capital is invested in stock, and one year later the investment yields $1,100, the rate of return of the investment is calculated like this:[(1100 – 1000) / 1000] × 100% = 100 / 1000 × 100% = 10% rate of returnNow, assume $1,000 is invested again. One year later, the investment grows to $2,000 in value, but after another year the value of the investment falls to $1,200. The rate of return after the first year is:[(2000 – 1000) / 1000] × 100% = 100%The rate of return after the second year is:[(1200 – 2000) / 2000] × 100% = – 40%The average annual return for the two years (also known as average annual arithmetic return) can be calculated using this formula:(Rate of return for Year 1 + Rate of return for Year 2) /2 = average annual returnAccordingly:(100% + – 40%) /2 = 30%The average annual rate of return is a percentage, but one that is accurate over only a short period, so this method should be used accordingly.The geometric or compound rate of return is a better yardstick for measuring investments over the long term, and takes into account the effects of compounding. This formula is more complex and technical.The real rate of return is the annual return realized on an investment, adjusted for changes in the price due to inflation. If 10% is earned on an investment but inflation is 2%, then the real rate of return is actually 8%. -
26 Computers
The brain has been compared to a digital computer because the neuron, like a switch or valve, either does or does not complete a circuit. But at that point the similarity ends. The switch in the digital computer is constant in its effect, and its effect is large in proportion to the total output of the machine. The effect produced by the neuron varies with its recovery from [the] refractory phase and with its metabolic state. The number of neurons involved in any action runs into millions so that the influence of any one is negligible.... Any cell in the system can be dispensed with.... The brain is an analogical machine, not digital. Analysis of the integrative activities will probably have to be in statistical terms. (Lashley, quoted in Beach, Hebb, Morgan & Nissen, 1960, p. 539)It is essential to realize that a computer is not a mere "number cruncher," or supercalculating arithmetic machine, although this is how computers are commonly regarded by people having no familiarity with artificial intelligence. Computers do not crunch numbers; they manipulate symbols.... Digital computers originally developed with mathematical problems in mind, are in fact general purpose symbol manipulating machines....The terms "computer" and "computation" are themselves unfortunate, in view of their misleading arithmetical connotations. The definition of artificial intelligence previously cited-"the study of intelligence as computation"-does not imply that intelligence is really counting. Intelligence may be defined as the ability creatively to manipulate symbols, or process information, given the requirements of the task in hand. (Boden, 1981, pp. 15, 16-17)The task is to get computers to explain things to themselves, to ask questions about their experiences so as to cause those explanations to be forthcoming, and to be creative in coming up with explanations that have not been previously available. (Schank, 1986, p. 19)In What Computers Can't Do, written in 1969 (2nd edition, 1972), the main objection to AI was the impossibility of using rules to select only those facts about the real world that were relevant in a given situation. The "Introduction" to the paperback edition of the book, published by Harper & Row in 1979, pointed out further that no one had the slightest idea how to represent the common sense understanding possessed even by a four-year-old. (Dreyfus & Dreyfus, 1986, p. 102)A popular myth says that the invention of the computer diminishes our sense of ourselves, because it shows that rational thought is not special to human beings, but can be carried on by a mere machine. It is a short stop from there to the conclusion that intelligence is mechanical, which many people find to be an affront to all that is most precious and singular about their humanness.In fact, the computer, early in its career, was not an instrument of the philistines, but a humanizing influence. It helped to revive an idea that had fallen into disrepute: the idea that the mind is real, that it has an inner structure and a complex organization, and can be understood in scientific terms. For some three decades, until the 1940s, American psychology had lain in the grip of the ice age of behaviorism, which was antimental through and through. During these years, extreme behaviorists banished the study of thought from their agenda. Mind and consciousness, thinking, imagining, planning, solving problems, were dismissed as worthless for anything except speculation. Only the external aspects of behavior, the surface manifestations, were grist for the scientist's mill, because only they could be observed and measured....It is one of the surprising gifts of the computer in the history of ideas that it played a part in giving back to psychology what it had lost, which was nothing less than the mind itself. In particular, there was a revival of interest in how the mind represents the world internally to itself, by means of knowledge structures such as ideas, symbols, images, and inner narratives, all of which had been consigned to the realm of mysticism. (Campbell, 1989, p. 10)[Our artifacts] only have meaning because we give it to them; their intentionality, like that of smoke signals and writing, is essentially borrowed, hence derivative. To put it bluntly: computers themselves don't mean anything by their tokens (any more than books do)-they only mean what we say they do. Genuine understanding, on the other hand, is intentional "in its own right" and not derivatively from something else. (Haugeland, 1981a, pp. 32-33)he debate over the possibility of computer thought will never be won or lost; it will simply cease to be of interest, like the previous debate over man as a clockwork mechanism. (Bolter, 1984, p. 190)t takes us a long time to emotionally digest a new idea. The computer is too big a step, and too recently made, for us to quickly recover our balance and gauge its potential. It's an enormous accelerator, perhaps the greatest one since the plow, twelve thousand years ago. As an intelligence amplifier, it speeds up everything-including itself-and it continually improves because its heart is information or, more plainly, ideas. We can no more calculate its consequences than Babbage could have foreseen antibiotics, the Pill, or space stations.Further, the effects of those ideas are rapidly compounding, because a computer design is itself just a set of ideas. As we get better at manipulating ideas by building ever better computers, we get better at building even better computers-it's an ever-escalating upward spiral. The early nineteenth century, when the computer's story began, is already so far back that it may as well be the Stone Age. (Rawlins, 1997, p. 19)According to weak AI, the principle value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion than before. But according to strong AI the computer is not merely a tool in the study of the mind; rather the appropriately programmed computer really is a mind in the sense that computers given the right programs can be literally said to understand and have other cognitive states. And according to strong AI, because the programmed computer has cognitive states, the programs are not mere tools that enable us to test psychological explanations; rather, the programs are themselves the explanations. (Searle, 1981b, p. 353)What makes people smarter than machines? They certainly are not quicker or more precise. Yet people are far better at perceiving objects in natural scenes and noting their relations, at understanding language and retrieving contextually appropriate information from memory, at making plans and carrying out contextually appropriate actions, and at a wide range of other natural cognitive tasks. People are also far better at learning to do these things more accurately and fluently through processing experience.What is the basis for these differences? One answer, perhaps the classic one we might expect from artificial intelligence, is "software." If we only had the right computer program, the argument goes, we might be able to capture the fluidity and adaptability of human information processing. Certainly this answer is partially correct. There have been great breakthroughs in our understanding of cognition as a result of the development of expressive high-level computer languages and powerful algorithms. However, we do not think that software is the whole story.In our view, people are smarter than today's computers because the brain employs a basic computational architecture that is more suited to deal with a central aspect of the natural information processing tasks that people are so good at.... hese tasks generally require the simultaneous consideration of many pieces of information or constraints. Each constraint may be imperfectly specified and ambiguous, yet each can play a potentially decisive role in determining the outcome of processing. (McClelland, Rumelhart & Hinton, 1986, pp. 3-4)Historical dictionary of quotations in cognitive science > Computers
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