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program+complexity

  • 1 показатель сложности программы

    Русско-английский словарь по вычислительной технике и программированию > показатель сложности программы

  • 2 сложность программы

    Information technology: program complexity, program difficulty

    Универсальный русско-английский словарь > сложность программы

  • 3 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, Eventually
       Just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)
       Many problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)
       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 Form
       The basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)
       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 Formation
       It is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)
       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 Contexts
       Even if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)
       Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)
        18) The Assumption That the Mind Is a Formal System
       Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)
        19) A Statement of the Primary and Secondary Purposes of Artificial Intelligence
       The primary goal of Artificial Intelligence is to make machines smarter.
       The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)
       The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....
       AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)
        21) Perceptual Structures Can Be Represented as Lists of Elementary Propositions
       In artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)
       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

  • 4 Schwierigkeit

    f difficulty; (Schwierigkeitsgrad) level (of difficulty); eine Aufgabe mittlerer Schwierigkeit a moderately difficult question; eine Kür von großer Schwierigkeit / mit vielen Schwierigkeiten a very difficult (free) program(me) / a (free) program(me) with many difficulties; Schwierigkeiten haben, etw. zu tun have difficulty ( oder trouble) (in) doing s.th.; jemandem Schwierigkeiten machen oder bereiten Sache: be a problem for s.o., cause s.o. problems; Person: make things difficult for s.o.; das Gehen machte ihm Schwierigkeiten auch he found it difficult to walk, he had trouble walking; sie haben wegen des Visums Schwierigkeiten gemacht they made difficulties over the visa; unnötige Schwierigkeiten machen complicate matters unnecessarily; bitte machen Sie keine Schwierigkeiten! please don’t make difficulties ( oder cause problems); das bereitete ihm keinerlei Schwierigkeiten it was no trouble at all for him, he took it all in his stride; auf Schwierigkeiten stoßen run into difficulty ( oder difficulties, problems); in Schwierigkeiten geraten run into trouble; in finanziellen Schwierigkeiten sein oder stecken have financial problems; mit jemandem Schwierigkeiten haben have problems with s.o.; Schwierigkeiten bekommen get into trouble; (Unannehmlichkeiten) have trouble ( wegen because of); es ist nicht ohne Schwierigkeiten it’s not without (its) problems
    * * *
    die Schwierigkeit
    difficulty; problem; trouble; complicacy; arduousness; snag
    * * *
    Schwie|rig|keit
    f -, -en
    difficulty

    in Schwíérigkeiten geraten or kommen — to get into difficulties or trouble

    auf Schwíérigkeiten stoßen — to meet with difficulties

    jdm Schwíérigkeiten machen — to make trouble for sb

    es macht mir überhaupt keine Schwíérigkeiten — it won't be at all difficult for me

    warum musst du bloß immer Schwíérigkeiten machen! — why must you always be difficult!

    mach keine Schwíérigkeiten! (inf) — don't be difficult, don't make any trouble

    ohne Schwíérigkeiten — without any difficulty

    ohne große Schwíérigkeit(en) — without any great difficulty

    Schwíérigkeiten haben, etw zu tun — to have difficulties doing sth

    * * *
    die
    2) (something complex.) complexity
    3) (the state or quality of being hard (to do) or not easy: I have difficulty in understanding him.) difficulty
    4) (an obstacle or objection: He has a habit of foreseeing difficulties.) difficulty
    5) (an unexpected problem or delay: The job was completed without a hitch.) hitch
    * * *
    Schwie·rig·keit
    <-, -en>
    f
    1. kein pl (Problematik) difficulty; eines Falles problematical nature; einer Lage, eines Problems complexity; einer Situation trickiness
    mit [einiger] \Schwierigkeit with [some] difficulty
    2. pl (Probleme) problems pl
    finanzielle \Schwierigkeiten financial difficulties pl
    jdn in \Schwierigkeiten bringen to get sb into trouble
    in \Schwierigkeiten geraten [o kommen] to get into difficulties [or trouble] [or fam hot water]
    [jdm] \Schwierigkeiten machen [o bereiten] to make trouble [for sb], to give sb trouble
    [jdm] keine \Schwierigkeiten machen [o bereiten] to be no trouble [for sb]
    ohne \Schwierigkeiten without any difficulty [or problems]
    * * *
    die; Schwierigkeit, Schwierigkeiten difficulty

    in Schwierigkeiten (Akk.) geraten — get into difficulties

    jemanden/sich in Schwierigkeiten (Akk.) bringen — get somebody/oneself into trouble

    * * *
    Schwierigkeit f difficulty; (Schwierigkeitsgrad) level (of difficulty);
    eine Aufgabe mittlerer Schwierigkeit a moderately difficult question;
    eine Kür von großer Schwierigkeit/mit vielen Schwierigkeiten a very difficult (free) program(me)/a (free) program(me) with many difficulties;
    Schwierigkeiten haben, etwas zu tun have difficulty ( oder trouble) (in) doing sth;
    bereiten Sache: be a problem for sb, cause sb problems; Person: make things difficult for sb;
    das Gehen machte ihm Schwierigkeiten auch he found it difficult to walk, he had trouble walking;
    sie haben wegen des Visums Schwierigkeiten gemacht they made difficulties over the visa;
    unnötige Schwierigkeiten machen complicate matters unnecessarily;
    bitte machen Sie keine Schwierigkeiten! please don’t make difficulties ( oder cause problems);
    das bereitete ihm keinerlei Schwierigkeiten it was no trouble at all for him, he took it all in his stride;
    auf Schwierigkeiten stoßen run into difficulty ( oder difficulties, problems);
    in Schwierigkeiten geraten run into trouble;
    stecken have financial problems;
    mit jemandem Schwierigkeiten haben have problems with sb;
    Schwierigkeiten bekommen get into trouble; (Unannehmlichkeiten) have trouble (
    wegen because of);
    es ist nicht ohne Schwierigkeiten it’s not without (its) problems
    * * *
    die; Schwierigkeit, Schwierigkeiten difficulty

    in Schwierigkeiten (Akk.) geraten — get into difficulties

    jemanden/sich in Schwierigkeiten (Akk.) bringen — get somebody/oneself into trouble

    * * *
    f.
    arduousness n.
    difficulty n.
    problem n.
    severity n.
    trouble n.

    Deutsch-Englisch Wörterbuch > Schwierigkeit

  • 5 Empire, Portuguese overseas

    (1415-1975)
       Portugal was the first Western European state to establish an early modern overseas empire beyond the Mediterranean and perhaps the last colonial power to decolonize. A vast subject of complexity that is full of myth as well as debatable theories, the history of the Portuguese overseas empire involves the story of more than one empire, the question of imperial motives, the nature of Portuguese rule, and the results and consequences of empire, including the impact on subject peoples as well as on the mother country and its society, Here, only the briefest account of a few such issues can be attempted.
       There were various empires or phases of empire after the capture of the Moroccan city of Ceuta in 1415. There were at least three Portuguese empires in history: the First empire (1415-1580), the Second empire (1580-1640 and 1640-1822), and the Third empire (1822-1975).
       With regard to the second empire, the so-called Phillipine period (1580-1640), when Portugal's empire was under Spanish domination, could almost be counted as a separate era. During that period, Portugal lost important parts of its Asian holdings to England and also sections of its colonies of Brazil, Angola, and West Africa to Holland's conquests. These various empires could be characterized by the geography of where Lisbon invested its greatest efforts and resources to develop territories and ward off enemies.
       The first empire (1415-1580) had two phases. First came the African coastal phase (1415-97), when the Portuguese sought a foothold in various Moroccan cities but then explored the African coast from Morocco to past the Cape of Good Hope in South Africa. While colonization and sugar farming were pursued in the Atlantic islands, as well as in the islands in the Gulf of Guinea like São Tomé and Príncipe, for the most part the Portuguese strategy was to avoid commitments to defending or peopling lands on the African continent. Rather, Lisbon sought a seaborne trade empire, in which the Portuguese could profit from exploiting trade and resources (such as gold) along the coasts and continue exploring southward to seek a sea route to Portuguese India. The second phase of the first empire (1498-1580) began with the discovery of the sea route to Asia, thanks to Vasco da Gama's first voyage in 1497-99, and the capture of strong points, ports, and trading posts in order to enforce a trade monopoly between Asia and Europe. This Asian phase produced the greatest revenues of empire Portugal had garnered, yet ended when Spain conquered Portugal and commanded her empire as of 1580.
       Portugal's second overseas empire began with Spanish domination and ran to 1822, when Brazil won her independence from Portugal. This phase was characterized largely by Brazilian dominance of imperial commitment, wealth in minerals and other raw materials from Brazil, and the loss of a significant portion of her African and Asian coastal empire to Holland and Great Britain. A sketch of Portugal's imperial losses either to native rebellions or to imperial rivals like Britain and Holland follows:
       • Morocco (North Africa) (sample only)
       Arzila—Taken in 1471; evacuated in 1550s; lost to Spain in 1580, which returned city to a sultan.
       Ceuta—Taken in 1415; lost to Spain in 1640 (loss confirmed in 1668 treaty with Spain).
       • Tangiers—Taken in 15th century; handed over to England in 1661 as part of Catherine of Braganza's dowry to King Charles II.
       • West Africa
       • Fort/Castle of São Jorge da Mina, Gold Coast (in what is now Ghana)—Taken in 1480s; lost to Holland in 1630s.
       • Middle East
       Socotra-isle—Conquered in 1507; fort abandoned in 1511; used as water resupply stop for India fleet.
       Muscat—Conquered in 1501; lost to Persians in 1650.
       Ormuz—Taken, 1505-15 under Albuquerque; lost to England, which gave it to Persia in the 17th century.
       Aden (entry to Red Sea) — Unsuccessfully attacked by Portugal (1513-30); taken by Turks in 1538.
       • India
       • Ceylon (Sri Lanka)—Taken by 1516; lost to Dutch after 1600.
       • Bombay—Taken in 16th century; given to England in 1661 treaty as part of Catherine of Braganza's dowry for Charles II.
       • East Indies
       • Moluccas—Taken by 1520; possession confirmed in 1529 Saragossa treaty with Spain; lost to Dutch after 1600; only East Timor remaining.
       After the restoration of Portuguese independence from Spain in 1640, Portugal proceeded to revive and strengthen the Anglo- Portuguese Alliance, with international aid to fight off further Spanish threats to Portugal and drive the Dutch invaders out of Brazil and Angola. While Portugal lost its foothold in West Africa at Mina to the Dutch, dominion in Angola was consolidated. The most vital part of the imperial economy was a triangular trade: slaves from West Africa and from the coasts of Congo and Angola were shipped to plantations in Brazil; raw materials (sugar, tobacco, gold, diamonds, dyes) were sent to Lisbon; Lisbon shipped Brazil colonists and hardware. Part of Portugal's War of Restoration against Spain (1640-68) and its reclaiming of Brazil and Angola from Dutch intrusions was financed by the New Christians (Jews converted to Christianity after the 1496 Manueline order of expulsion of Jews) who lived in Portugal, Holland and other low countries, France, and Brazil. If the first empire was mainly an African coastal and Asian empire, the second empire was primarily a Brazilian empire.
       Portugal's third overseas empire began upon the traumatic independence of Brazil, the keystone of the Lusitanian enterprise, in 1822. The loss of Brazil greatly weakened Portugal both as a European power and as an imperial state, for the scattered remainder of largely coastal, poor, and uncolonized territories that stretched from the bulge of West Africa to East Timor in the East Indies and Macau in south China were more of a financial liability than an asset. Only two small territories balanced their budgets occasionally or made profits: the cocoa islands of São Tomé and Príncipe in the Gulf of Guinea and tiny Macau, which lost much of its advantage as an entrepot between the West and the East when the British annexed neighboring Hong Kong in 1842. The others were largely burdens on the treasury. The African colonies were strapped by a chronic economic problem: at a time when the slave trade and then slavery were being abolished under pressures from Britain and other Western powers, the economies of Guinea- Bissau, São Tomé/Príncipe, Angola, and Mozambique were totally dependent on revenues from the slave trade and slavery. During the course of the 19th century, Lisbon began a program to reform colonial administration in a newly rejuvenated African empire, where most of the imperial efforts were expended, by means of replacing the slave trade and slavery, with legitimate economic activities.
       Portugal participated in its own early version of the "Scramble" for Africa's interior during 1850-69, but discovered that the costs of imperial expansion were too high to allow effective occupation of the hinterlands. After 1875, Portugal participated in the international "Scramble for Africa" and consolidated its holdings in west and southern Africa, despite the failure of the contra-costa (to the opposite coast) plan, which sought to link up the interiors of Angola and Mozambique with a corridor in central Africa. Portugal's expansion into what is now Malawi, Zambia, and Zimbabwe (eastern section) in 1885-90 was thwarted by its oldest ally, Britain, under pressure from interest groups in South Africa, Scotland, and England. All things considered, Portugal's colonizing resources and energies were overwhelmed by the African empire it possessed after the frontier-marking treaties of 1891-1906. Lisbon could barely administer the massive area of five African colonies, whose total area comprised about 8 percent of the area of the colossal continent. The African territories alone were many times the size of tiny Portugal and, as of 1914, Portugal was the third colonial power in terms of size of area possessed in the world.
       The politics of Portugal's empire were deceptive. Lisbon remained obsessed with the fear that rival colonial powers, especially Germany and Britain, would undermine and then dismantle her African empire. This fear endured well into World War II. In developing and keeping her potentially rich African territories (especially mineral-rich Angola and strategically located Mozambique), however, the race against time was with herself and her subject peoples. Two major problems, both chronic, prevented Portugal from effective colonization (i.e., settling) and development of her African empire: the economic weakness and underdevelopment of the mother country and the fact that the bulk of Portuguese emigration after 1822 went to Brazil, Venezuela, the United States, and France, not to the colonies. These factors made it difficult to consolidate imperial control until it was too late; that is, until local African nationalist movements had organized and taken the field in insurgency wars that began in three of the colonies during the years 1961-64.
       Portugal's belated effort to revitalize control and to develop, in the truest sense of the word, Angola and Mozambique after 1961 had to be set against contemporary events in Europe, Africa, and Asia. While Portugal held on to a backward empire, other European countries like Britain, France, and Belgium were rapidly decolonizing their empires. Portugal's failure or unwillingness to divert the large streams of emigrants to her empire after 1850 remained a constant factor in this question. Prophetic were the words of the 19th-century economist Joaquim Oliveira Martins, who wrote in 1880 that Brazil was a better colony for Portugal than Africa and that the best colony of all would have been Portugal itself. As of the day of the Revolution of 25 April 1974, which sparked the final process of decolonization of the remainder of Portugal's third overseas empire, the results of the colonization program could be seen to be modest compared to the numbers of Portuguese emigrants outside the empire. Moreover, within a year, of some 600,000 Portuguese residing permanently in Angola and Mozambique, all but a few thousand had fled to South Africa or returned to Portugal.
       In 1974 and 1975, most of the Portuguese empire was decolonized or, in the case of East Timor, invaded and annexed by a foreign power before it could consolidate its independence. Only historic Macau, scheduled for transfer to the People's Republic of China in 1999, remained nominally under Portuguese control as a kind of footnote to imperial history. If Portugal now lacked a conventional overseas empire and was occupied with the challenges of integration in the European Union (EU), Lisbon retained another sort of informal dependency that was a new kind of empire: the empire of her scattered overseas Portuguese communities from North America to South America. Their numbers were at least six times greater than that of the last settlers of the third empire.

    Historical dictionary of Portugal > Empire, Portuguese overseas

  • 6 разбивать на ряд

    Разбивать на ряд
     The complexity of implementing a large application program can be broken down into a number of almost independent software modules.
     The bed is divided into a set of N discrete horizontal sections.

    Русско-английский научно-технический словарь переводчика > разбивать на ряд

  • 7 объем работы

    The duration of such training was determined by the flight program, by the complexity and the volume of the work assigned to the crews.

    Русско-английский словарь по космонавтике > объем работы

  • 8 продолжительность определяется

    The duration of such training was determined by the flight program, by the complexity and the volume of the work assigned to the crews.

    Русско-английский словарь по космонавтике > продолжительность определяется

  • 9 гонорар

    Размер гонорара должен соответствовать сложности учебной программы и уровню подготовленности слушателей курса. Поэтому размер гонорара должен быть больше для программ старшего уровня. В то же время он не должен зависеть от педагогической квалификации преподавателя. — The honorarium must correspond to the complexity of training program and level of course participants. Therefore, the honorarium should be higher for senior-level programs. However, it must not depend on academic qualifications of trainer.

    Russian-English Dictionary "Microeconomics" > гонорар

  • 10 Caetano, Marcello José das Neves Alves

    (19061980)
       Marcello Caetano, as the last prime minister of the Estado Novo, was both the heir and successor of Antônio de Oliveira Salazar. In a sense, Caetano was one of the founders and sustainers of this unusual regime and, at various crucial stages of its long life, Caetano's contribution was as important as Salazar's.
       Born in Lisbon in 1906 to a middle-class family, Caetano was a member of the student generation that rebelled against the unstable parliamentary First Republic and sought answers to Portugal's legion of troubles in conservative ideologies such as integralism, Catholic reformism, and the Italian Fascist model. One of the most brilliant students at the University of Lisbon's Law School, Caetano soon became directly involved in government service in various ministries, including Salazar's Ministry of Finance. When Caetano was not teaching full-time at the law school in Lisbon and influencing new generations of students who became critical of the regime he helped construct, Caetano was in important government posts and working on challenging assignments. In the 1930s, he participated in reforms in the Ministry of Finance, in the writing of the 1933 Constitution, in the formation of the new civil code, of which he was in part the author, and in the construction of corporativism, which sought to control labor-management relations and other aspects of social engineering. In a regime largely directed by academics from the law faculties of Coimbra University and the University of Lisbon, Caetano was the leading expert on constitutional law, administrative law, political science, and colonial law. A prolific writer as both a political scientist and historian, Caetano was the author of the standard political science, administrative law, and history of law textbooks, works that remained in print and in use among students long after his exile and death.
       After his apprenticeship service in a number of ministries, Caetano rose steadily in the system. At age 38, he was named minister for the colonies (1944 47), and unlike many predecessors, he "went to see for himself" and made important research visits to Portugal's African territories. In 1955-58, Caetano served in the number-three position in the regime in the Ministry of the Presidency of the Council (premier's office); he left office for full-time academic work in part because of his disagreements with Salazar and others on regime policy and failures to reform at the desired pace. In 1956 and 1957, Caetano briefly served as interim minister of communications and of foreign affairs.
       Caetano's opportunity to take Salazar's place and to challenge even more conservative forces in the system came in the 1960s. Portugal's most prominent law professor had a public falling out with the regime in March 1962, when he resigned as rector of Lisbon University following a clash between rebellious students and the PIDE, the political police. When students opposing the regime organized strikes on the University of Lisbon campus, Caetano resigned his rectorship after the police invaded the campus and beat and arrested some students, without asking permission to enter university premises from university authorities.
       When Salazar became incapacitated in September 1968, President Américo Tomás named Caetano prime minister. His tasks were formidable: in the midst of remarkable economic growth in Portugal, continued heavy immigration of Portuguese to France and other countries, and the costly colonial wars in three African colonies, namely Angola, Guinea- Bissau, and Mozambique, the regime struggled to engineer essential social and political reforms, win the wars in Africa, and move toward meaningful political reforms. Caetano supported moderately important reforms in his first two years in office (1968-70), as well as the drafting of constitutional revisions in 1971 that allowed a slight liberalization of the Dictatorship, gave the opposition more room for activity, and decentrali zed authority in the overseas provinces (colonies). Always aware of the complexity of Portugal's colonial problems and of the ongoing wars, Caetano made several visits to Africa as premier, and he sought to implement reforms in social and economic affairs while maintaining the expensive, divisive military effort, Portugal's largest armed forces mobilization in her history.
       Opposed by intransigent right-wing forces in various sectors in both Portugal and Africa, Caetano's modest "opening" of 1968-70 soon narrowed. Conservative forces in the military, police, civil service, and private sectors opposed key political reforms, including greater democratization, while pursuing the military solution to the African crisis and personal wealth. A significant perspective on Caetano's failed program of reforms, which could not prevent the advent of a creeping revolution in society, is a key development in the 1961-74 era of colonial wars: despite Lisbon's efforts, the greater part of Portuguese emigration and capital investment during this period were directed not to the African colonies but to Europe, North America, and Brazil.
       Prime Minister Caetano, discouraged by events and by opposition to his reforms from the so-called "Rheumatic Brigade" of superannuated regime loyalists, attempted to resign his office, but President Américo Tomás convinced him to remain. The publication and public reception of African hero General Antônio Spinola's best-selling book Portugal e Futuro (Portugal and the Future) in February 1974 convinced the surprised Caetano that a coup and revolution were imminent. When the virtually bloodless, smoothly operating military coup was successful in what became known as the Revolution of 25 April 1974, Caetano surrendered to the Armed Forces Movement in Lisbon and was flown to Madeira Island and later to exile in Brazil, where he remained for the rest of his life. In his Brazilian exile, Caetano was active writing important memoirs and histories of the Estado Novo from his vantage point, teaching law at a private university in Rio de Janeiro, and carrying on a lively correspondence with persons in Portugal. He died at age 74, in 1980, in Brazil.

    Historical dictionary of Portugal > Caetano, Marcello José das Neves Alves

  • 11 оценивать

    гл.
    1. to judge; 2. to evaluate; 3. to assess; 4. to appraise; 5. to estimate; 6. to appreciate
    Русский глагол оценивать не конкретизирует, как и в результате него произведена оценка. В английском языке в зависимости от характера обстоятельств, при которых дана оценка, или от мнения оценивающих используются разные слова, предполагающие конкретные ситуации.
    1. to judge — оценивать ( что-либо), судить ( о чем-либо) ( предполагает личное мнение или суждение о чем-либо): to judge about/of smth — судить о чем-либо; to judge about smth or smb судить о чем-либо или о ком-либо/выказать свое мнение о чем-либо или о ком-либо/иметь о чем-либо или о ком-либо свое суждение; to judge smb, smth судить о ком-либо, о чем-либо It is difficult for us to judge of the situation because we don't really know enough about it. — Нам трудно оценивать эту ситуацию, так как мы мало что о ней знасм./Нам трудно судить об этой ситуации, так как мы мало что о ней знаем. I don't know much about it, so I can't judge whether you arc right or wrong. — Я мало что об этом знаю, и поэтому не могу оценить ваше мнение./Я мало что об этом знаю, и поэтому не могу судить, правы вы или нет. One should be judged by what he does not what he says. — О человеке надо судить по делам, а не по словам. She can judge people very well. — Она очень хорошо оценивает людей. Магу judged it best not to say anything to me. — Мэри рассудила, что лучше всего не надо ничего мне говорить. It is difficult to judge what kind of impression we made. — Трудно сказать/судить, какое мы произвели впечатление. Не judged that someone must have been in the house. — Он считал, что в доме кто-то побывал./У него сложилось такое мнение, что в доме кто-то побывал. I love it, but come along and judge for yourself. — Мне это очень нравится, но пойдем вместе, и ты оценишь сам. You may lose the ability to judge distance accurately. — Можно потерять способность правильно оценивать расстояние. I don't know the facts. How can I judge? — Как я могу судить, не зная фактов? Who is judging the contest (the match, the game)? — Кто судит конкурс (матч, игру)? Schools are judged on their results. — Школы оцениваются по их результатам./О школах судят по их результатам. Judging by modern standards, it was a cruel thing to do. — По современным меркам это было жестоко. The firm's success can be judged from its growing sales. — Успехи фирмы можно оценить по растущему количеству продаж. The water was judged to be of good guality. — Вода по полученной оценке была хорошего качсства./Качество воды получило хорошую оценку.
    2. to evaluate — оценивать, давать оценку (не носит официального характера, но предполагает тщательное рассмотрение ценности или полезности чего-либо): to evaluate the full significance — оценить все значение/оценивать всю важность We've arranged a meeting to evaluate their proposals. — Мы созвали совещание для оценки их предложений. We asked all ex-trainees to evaluate the courses they took. — Мы попросили всех, кто у нас учился, дать свою оценку степени эффективности этих курсов. The police have got to stop evaluating their employees performance by the number of arrests they have made. — Полиция должна перестать оценивать работу своих сотрудников по количеству произведенных ими арестов. I can't evaluate his ability without more information. — Я не могу оценить его способности, мне нужно больше информации. Не failed to evaluate the importance of the matter properly. — Он не смог правильно оценить важность этого вопроса./Он не смог должным образом оценить важность этого вопроса.
    3. to assess — оценивать, давать оценку (предполагает формирование заключения, суждения, вывода или мнения в результате обдумывания или рассмотрения чего-либо): to assess a personality — дать оценку личных качеств человека/оценить личные качества человека; to assess a speech at its true worth — определить истинную ценность какого-либо выступления There are many methods of assessing students. — Существует много способов оценки знаний студентов. The booklet aims to help parents to assess recent educational chances. — Цель брошюры — помочь родителям составить собственное суждение о том, какие возможности открывают последние общеобразовательные программы. This test provides an excellent way of assessing applicants' suitability. — Данный тест дает прекрасную возможность оценки пригодности тех, кто претендует на эту работу/Данный тест обеспечивает прекрасную возможность оценки пригодности поступающих на эту работу. She looked over the house and assessed its rough market value. — Она осмотрела дом и оценила его примерную рыночную стоимость. She prefers her taxes assessed separately from her husband's. — Она предпочитает, чтобы ее налоги исчислялись отдельно от налогов ее мужа. He can quickly assess a person's character. — Он может быстро оценить характер человека./Он способен быстро составить правильное мнение о характере человека. It is difficult to assess the effects of the new legislation just yet. — Пока еще трудно оценить насколько эффективно новое законодательство. We have tried to assess what went wrong. — Мы пытались оценить в чем был сбой./Мы пытались оценить где была допущена ошибка. They assessed the value of the painting at over one million dollars. — Они оценили стоимость картины более чем в миллион долларов.
    4. to appraise — оценивать, давать оценку, определять качество, определять стоимость (носит официальный характер, как правило, употребляется при официальной и профессиональной оценке качества,полезности или стоимости чего-либо): to appraise a farm at a certain sum — оценить ферму в определенную сумму; to appraise the ability of one's students — дать оценку способностям своих учеников/определять уровень подготовки учащихся The company regularly appraises the performance of its employees. — Компания регулярно проводит оценку качества работы своих служащих. The officials were cautious in appraising the new aid program. — Должностные лица были очень осторожны при оценке новой программы помощи. The panel was asked to select and appraise this year's advertising. — Группу специалистов попросили оценить рекламу этого года и отобрать лучшую./Группу экспертов попросили оценить рекламу этого года и отобрать лучшую. They all appraised the house carefully before offering to buy it. — Они тщательно определили стоимость дома, прежде чем предложили его купить./Они осмотрели весь дом, прежде чем предложили его купить. The dealer came to appraise the furniture. — Посредник пришел, чтобы оценить предлагаемую на продажу мебель.
    5. to estimate — оценивать, определять ( примерно), определить: to estimate the distance (height) — примерно оценить расстояние (высоту)/прикинугь расстояние (высоту) The mechanic estimated the cost of repair at 200 dollars. — Механик оценил стоимость ремонта примерно в двести долларов. It is estimated that over 90 % crimes are committed in the day time. — По примерной оценке более девяноста процентов преступлений совершаются в дневное время. It is difficult to estimate how many deaths are caused by smoking each year. — Трудно даже определить, сколько человек каждый год умирает от курения. They estimated that the concert was watched by about five million people. — По их примерным подсчетам концерт по телевидению посмотрели около пять миллионов человек. It is difficult to estimate the cost of making your house safe. — Трудно подсчитать, сколько будет стоить работа по обеспечению безопасности вашего дома. The Antarctic ice is estimated to contain 90 % of the world's fresh water. — Льды Антарктики по имеющимся подсчетам содержат девяносто процентов пресной воды всей планеты. Can you estimate the distance to the forest from here? — Вы можете прикинуть расстояние отсюда до леса?
    6. to appreciate — оценивать, оценивать по достоинству, судить, понимать ( составить мнение о качестве чего-либо): to appreciate a joke — понять шутку; to appreciate the danger — правильно оценивать опасность/правильно судить об опасности Her abilities are not fully appreciated by her employer. — Ее хозяин не пенит се способностей по достоинству. I don't think you appreciate the difficulties his absence will cause. — Мне кажется, вы недооцениваете трудности, которые вызовет его отсутствие. I began to appreciate the difficulties my father had faced. — Я начал правильно оценивать трудности, с которыми столкнулся мой отец. I don't believe the Prime Minister fully appreciated the complexity ofthe problem. — Мне кажется, премьер-министр не полностью оценивает сложность этой проблсмы./Мне кажется, премьер-министр не до конин понимает сложность этой проблемы. She feels that her family does not really appreciate her. — Она чувствует, что семья ее недостаточно ценит. The restaurant is popular with people who appreciate food service and fine wines. — Этот ресторан пользуется популярностью у людей, которые пенят хорошее обслуживание и хорошие вина.

    Русско-английский объяснительный словарь > оценивать

  • 12 Programming Language

       1) Theories of Human Mental Processes Can Be Expressed in Programming Languages
       It [the information-processing revolution] has introduced computer programming languages as formal ["mathematical"] languages for expressing theories of human mental processes; and it has introduced the computers themselves as a device to simulate these processes and thereby make behavioral predictions for testing of the theories. (Simon, 1979, p. ix)
       LISP is now the second oldest programming language in present widespread use (after FORTRAN).... Its core occupies some kind of local optimum in the space of programming languages given that static friction discourages purely notational changes. Recursive use of conditional expressions, representation of symbolic information externally by lists and internally by list structure, and representation of program in the same way will probably have a very long life. (McCarthy, quoted in Barr & Feigenbaum, 1982, p. 5)
       Although it sounds implausible, it might turn out that above a certain level of complexity, a machine ceased to be predictable, even in principle, and started doing things on its own account, or, to use a very revealing phrase, it might begin to have a mind of its own. (Lucas, quoted in Hand, 1985, p. 4)

    Historical dictionary of quotations in cognitive science > Programming Language

См. также в других словарях:

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