(machines)

slot-machine, juke-box.

slot machine, one armed-bandit (informal).

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máquina tragaperras slot machine

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SF INV [gen] slot machine; [en bar] fruit-machine, one-armed bandit

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masculino o femenino (pl tragaperras) (Esp fam) slot machine

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= slot machine, fruit machine, one-arm(ed) bandit.

Ex. At Christmas, the only jingle bells heard in casinos were the noises of slot machines paying out.

Ex. Fruit machines are so profitable that US casinos are reported to make the bulk of their profits from their vast floors of machines.

Ex. Adults use these ' one arm bandits' for fun, a substitute for the games they engaged in as children.

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* máquina tragaperras = slot machine, fruit machine, one-arm(ed) bandit.

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masculino o femenino (pl tragaperras) (Esp fam) slot machine

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(pl tragaperras)

( Esp fam) slot machine

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◊ tragaperras) (Esp fam) slot machine

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tragaperras nf inv

slot machine, one-armed bandit

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f inv slot machine

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tragaperras n slot machine

SUBJECT AREA: Electronics and information technology

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George B.Grant was descended from families who came from Britain in the seventeenth century and was educated at the Bridgton (Maine) Academy, the Chandler Scientific School of Dartmouth College and the Lawrence Scientific School of Harvard College, where he graduated with the degree of BS in 1873. As an undergraduate he became interested in calculating machines, and his paper "On a new difference engine" was published in the American Journal of Science in August 1871. He also took out his first patents relating to calculating machines in 1872 and 1873. A machine of his design known as "Grant's Difference Engine" was exhibited at the Centennial Exposition in Philadelphia in 1876. Similar machines were also manufactured for sale; being sturdy and reliable, they did much to break down the prejudice against the use of calculating machines in business. Grant's work on calculating machines led to a requirement for accurate gears, so he established a machine shop for gear cutting at Charlestown, Massachusetts. He later moved the business to Boston and incorporated it under the name of Grant's Gear Works Inc., and continued to control it until his death. He also established two other gear-cutting shops, the Philadelphia Gear Works Inc., which he disposed of in 1911, and the Cleveland Gear Works Inc., which he also disposed of after a few years. Grant's commercial success was in connection with gear cutting and in this field he obtained several patents and contributed articles to the American Machinist. However, he continued to take an interest in calculating machines and in his later years carried out experimental work on their development.

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SUBJECT AREA: Mechanical, pneumatic and hydraulic engineering

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James N.Heald was the son of Leander S.Heald and was educated at the Worcester Polytechnic Institute, graduating with the degree of Bachelor of Science in 1884. He then joined the firm that had been established by his grandfather, Stephen Heald, in 1826; this was a machine shop and foundry then known as S.Heald \& Son. When his grandfather died in 1888, James Heald took over the management of the business, which then became known as L.S.Heald \& Son. He concentrated on the manufacture of grinding machines and in 1903 bought out his father's interest and organized the Heald Machine Company. James Heald then began the development of a series of grinding machines designed to meet the needs of the expanding automobile industry. Special machines were produced for grinding piston rings making use of the recently invented magnetic chuck, and for cylinder bores he introduced the planetary grinder. Heald was a member of the National Machine Tool Builders' Association and served as its Treasurer and on its Board of Directors. He was elected a member of the American Society of Mechanical Engineers in 1917 and was also a member of the Society of Automotive Engineers.

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SUBJECT AREA: Agricultural and food technology

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A farmer's son, at the age of 17 McKay developed modifications to the existing stripper harvester and created a machine that would not only strip the seed from standing corn, but was able to produce a threshed, winnowed and clean sample in one operation. The prototype was produced in 1884 and worked well on the two acres of wheat that had been set aside on the family farm. By arrangement with a Melbourne plough maker, five machines were made and sold for the 1885 season. In 1886 the McKay Harvester Company was formed, with offices at Ballarat, from which the machines, built by various companies, were sold. The business expanded quickly, selling sixty machines in 1888, and eventually rising to the production of nearly 2,000 harvesters in 1905. The name "Sunshine" was given to the harvester, and the "Sun" prefix was to appear on all other implements produced by the company as it diversified its production interests. In 1902 severe drought reduced machinery sales and left 2,000 harvesters unsold. McKay was forced to look to export markets to dispose of his surplus machines. By 1914 a total of 10,000 machines were being exported annually. During the First World War McKay was appointed to the Business Board of the Defence Department. Increases in the scale of production resulted in the company moving to Melbourne, where it was close to the port of entry of raw materials and was able to export the finished article more readily. In 1909 McKay produced one of the first gas-engined harvesters, but its cost prevented it from being more than an experimental prototype. By this time McKay was the largest agricultural machinery manufacturer in the Southern hemisphere, producing a wide range of implements, including binders. In 1916 McKay hired Headlie Taylor, who had developed a machine capable of harvesting fallen crops. The jointly developed machine was a major success, coming as it did in what would otherwise have been a disastrous Australian harvest. Further developments included the "Sun Auto-header" in 1923, the first of the harvesting machines to adopt the "T" configuration to be seen on modern harvesters. The Australian market was expanding fast and a keen rivalry developed between McKay and Massey Harris. Confronted by the tariff regulations with which the Australian Government had protected its indigenous machinery industry since 1906, Massey Harris sold all its Australian assets to the H.V. McKay company in 1930. Twenty-three years later Massey Ferguson acquired the old Sunshine works and was still operating from there in the 1990s.

Despite a long-running history of wage disputes with his workforce, McKay established a retiring fund as well as a self-help fund for distressed cases. Before his death he created a charitable trust and requested that some funds should be made available for the "aerial experiments" which were to lead to the establishment of the Flying Doctor Service.

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SUBJECT AREA: Domestic appliances and interiors, Textiles

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The son of a millwright, Singer was employed as an unskilled labourer at the age of 12, but later gained wide experience as a travelling machinist. He also found employment as an actor. On 16 May 1839, while living at Lockport, Illinois, he obtained his first patent for a rock-drilling machine, but he soon squandered the money he made. Then in 1849, while at Pittsburgh, he secured a patent for a wood-and metal-carving machine that he had begun five years previously; however, a boiler explosion in the factory destroyed his machine and left him penniless.

Near the end of 1850 Singer was engaged to redesign the Lerow \& Blodgett sewing machine at the Boston shop of Orson C.Phelps, where the machine was being repaired. He built an improved version in eleven days that was sufficiently different for him to patent on 12 August 1851. He formed a partnership with Phelps and G.B. Zieber and they began to market the invention. Singer soon purchased Phelps's interest, although Phelps continued to manufacture the machines. Then Edward Clark acquired a one-third interest and with Singer bought out Zieber. These two, with dark's flair for promotion and marketing, began to create a company which eventually would become the largest manufacturer of sewing machines exported worldwide, with subsidiary factories in England.

However, first Singer had to defend his patent, which was challenged by an earlier Boston inventor, Elias Howe. Although after a long lawsuit Singer had to pay royalties, it was the Singer machine which eventually captured the market because it could do continuous stitching. In 1856 the Great Sewing Machine Combination, the first important pooling arrangement in American history, was formed to share the various patents so that machines could be built without infringements and manufacture could be expanded without fear of litigation. Singer contributed his monopoly on the needle-bar cam with his 1851 patent. He secured twenty additional patents, so that his original straight-needle vertical design for lock-stitching eventually included such refinements as a continuous wheel-feed, yielding presser-foot, and improved cam for moving the needle-bar. A new model, introduced in 1856, was the first to be intended solely for use in the home.

Initially Phelps made all the machines for Singer. Then a works was established in New York where the parts were assembled by skilled workers through filing and fitting. Each machine was therefore a "one-off" but Singer machines were always advertised as the best on the market and sold at correspondingly high prices. Gradually, more specialized machine tools were acquired, but it was not until long after Singer had retired to Europe in 1863 that Clark made the change to mass production. Sales of machines numbered 810 in 1853 and 21,000 ten years later.

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   1) Programs and the Complexity of Human Mental Processes

   In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)

   2) Artificial Intelligence Is an Engineering Discipline

   Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)

   3) A Sceptical View of Artificial Intelligence

   Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....

   When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)

   4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, Eventually

   Just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)

   5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the Program

   Many problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)

   6) The Meaning of a Symbolic Description

   What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)

   7) The Principle of Artificial Intelligence

   [AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)

   8) Artificial Intelligence Recognizes the Need for Knowledge in Its Systems

   The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)

   9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract Form

   The basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)

    10) There Are Many Types of Reasoning

   There are many different kinds of reasoning one might imagine:

    Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."

    Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)

    11) Programs Are Beginning to Do Things That Critics Have Asserted to Be Impossible

   Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)

    12) The Synthesis of Man and Machine

   Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)

    13) The Thesis of Good Old-Fashioned Artificial Intelligence (GOFAI)

   The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)

    14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory Formation

   It is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)

    15) Four Kinds of Artificial Intelligence

   We might distinguish among four kinds of AI.

   ♦ Nonpsychological AI

   Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.

   ♦ Weak Psychological AI

   Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.

   ♦ Strong Psychological AI

... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)

   ♦ Suprapsychological AI

   Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)

    16) Determination of Relevance of Rules in Particular Contexts

   Even if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)

    17) Form and Content Are Not Fundamentally Different

   Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)

    18) The Assumption That the Mind Is a Formal System

   Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)

    19) A Statement of the Primary and Secondary Purposes of Artificial Intelligence

   The primary goal of Artificial Intelligence is to make machines smarter.

   The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)

    20) Mathematical Logic Provides the Basis for Theory in AI

   The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....

   AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)

    21) Perceptual Structures Can Be Represented as Lists of Elementary Propositions

   In artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)

    22) Definitions of Artificial Intelligence

   Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)

    23) The Computer Can Not Be a Model of the Mind

   Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)

    24) Computers Will Not Always Be Inferior to Human Brains

   The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)

   1) The Basic Idea of Cognitive Science

   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.... [P]eople and intelligent computers turn out to be merely different manifestations of the same underlying phenomenon. (Haugeland, 1981b, p. 31)

   2) Experimental Psychology, Theoretical Linguistics, and Computational Simulation of Cognitive Processes Are All Components of Cognitive Science

   I went away from the Symposium with a strong conviction, more intuitive than rational, that human experimental psychology, theoretical linguistics, and computer simulation of cognitive processes were all pieces of a larger whole, and that the future would see progressive elaboration and coordination of their shared concerns.... I have been working toward a cognitive science for about twenty years beginning before I knew what to call it. (G. A. Miller, 1979, p. 9)

   3) The Nature of Cognitive Science

    Cognitive Science studies the nature of cognition in human beings, other animals, and inanimate machines (if such a thing is possible). While computers are helpful within cognitive science, they are not essential to its being. A science of cognition could still be pursued even without these machines.

    Computer Science studies various kinds of problems and the use of computers to solve them, without concern for the means by which we humans might otherwise resolve them. There could be no computer science if there were no machines of this kind, because they are indispensable to its being. Artificial Intelligence is a special branch of computer science that investigates the extent to which the mental powers of human beings can be captured by means of machines.

   There could be cognitive science without artificial intelligence but there could be no artificial intelligence without cognitive science. One final caveat: In the case of an emerging new discipline such as cognitive science there is an almost irresistible temptation to identify the discipline itself (as a field of inquiry) with one of the theories that inspired it (such as the computational conception...). This, however, is a mistake. The field of inquiry (or "domain") stands to specific theories as questions stand to possible answers. The computational conception should properly be viewed as a research program in cognitive science, where "research programs" are answers that continue to attract followers. (Fetzer, 1996, pp. xvi-xvii)

   4) The Nature of Cognitive Science

   What is the nature of knowledge and how is this knowledge used? These questions lie at the core of both psychology and artificial intelligence.

   The psychologist who studies "knowledge systems" wants to know how concepts are structured in the human mind, how such concepts develop, and how they are used in understanding and behavior. The artificial intelligence researcher wants to know how to program a computer so that it can understand and interact with the outside world. The two orientations intersect when the psychologist and the computer scientist agree that the best way to approach the problem of building an intelligent machine is to emulate the human conceptual mechanisms that deal with language.... The name "cognitive science" has been used to refer to this convergence of interests in psychology and artificial intelligence....

   This working partnership in "cognitive science" does not mean that psychologists and computer scientists are developing a single comprehensive theory in which people are no different from machines. Psychology and artificial intelligence have many points of difference in methods and goals.... We simply want to work on an important area of overlapping interest, namely a theory of knowledge systems. As it turns out, this overlap is substantial. For both people and machines, each in their own way, there is a serious problem in common of making sense out of what they hear, see, or are told about the world. The conceptual apparatus necessary to perform even a partial feat of understanding is formidable and fascinating. (Schank & Abelson, 1977, pp. 1-2)

   5) The New Field of Cognitive Science

   Within the last dozen years a general change in scientific outlook has occurred, consonant with the point of view represented here. One can date the change roughly from 1956: in psychology, by the appearance of Bruner, Goodnow, and Austin's Study of Thinking and George Miller's "The Magical Number Seven"; in linguistics, by Noam Chomsky's "Three Models of Language"; and in computer science, by our own paper on the Logic Theory Machine. (Newell & Simon, 1972, p. 4)

1 machine.

aparato de diálisis kidney machine

aparatos gimnásticos apparatus (en competición, escuela)

aparato de radio radio

aparato de televisión television set

aparato de vídeo video (cassette) recorder

2 plane.

3 aid (medicine) (prótesis).

4 system (anatomy).

aparato circulatorio circulatory system

aparato digestivo digestive system

aparato reproductor reproductive system

aparato respiratorio respiratory system

aparato urinario urinary tract

Aparato respiratorio Respiratory system.

5 machinery (politics).

6 pomp, ostentation.

7 appliance, gadget, mechanism, unit.

8 brace.

9 theatricality, exaggeration.

1^st person singular (yo) present indicative of spanish verb: aparatar.

* * *

► nombre masculino

1 (mecanismo) (piece of) apparatus, set; (eléctrico) appliance

■ aparatos eléctricos equipment

2 (dispositivo) device; (instrumento) instrument

3 (teléfono) telephone

■ está al aparato he's on the phone

4 (avión) plane

5 (exageración) exaggeration

6 (ostentación) pomp, display, show

■ con mucho aparato very pompously

7 (tormenta) flashes of lightning plural

■ una tormenta con gran aparato (eléctrico) a storm with tremendous flashes of lightning

\

aparato auditivo hearing aid

aparato de radio radio set

aparato de televisión television set

aparato digestivo ANATOMÍA digestive system

aparato ortopédico orthopedic aid

el aparato del estado the State apparatus

* * *

1) machine

2) apparatus

3) appliance, set

4) system

* * *

1) (Téc) machine

2) (Elec) (=electrodoméstico) appliance; (=televisor, radio) set

3) (Telec) phone, telephone

4) (Med)

5) (Gimnasia) (=máquina) exercise machine, fitness machine; (=anillas, barras) piece of apparatus

6) (Aer) aircraft, airplane (EEUU)

7) (=formalismo, artificio)

8) (Pol) (=estructura) [de base] machine; [de control] machinery

9) (Meteo)

10) (=indicios) signs pl, symptoms pl ; (Med) symptoms pl ; (Psic) syndrome

11) (Literat)

12) ** (=pene) equipment *; (=vagina) pussy ***

* * *

1)

a) ( máquina)

b) ( de televisión) set; ( de radio) receiver

2) ( para gimnasia) piece of apparatus

3)

a) ( audífono) tb

b) (Odont) tb

4) ( teléfono) telephone

5) (frml) ( avión) aircraft

6) (estructura, sistema) machine

7) ( ceremonia) pomp

8) (fam & euf) ( pene) weenie (AmE colloq), willy (BrE colloq); ( genitales masculinos) equipment (euph)

•

- aparato circulatorio/digestivo/respiratorio

- aparato ortopédico

* * *

= apparatus, device, machine, whatchamacallit, gadget, widget, rig, appliance, unit, contraption.

Ex. The abstracts of research papers will typically represent the methodology employed, in particular, apparatus, equipment, tools, materials.

Ex. The extent of application of the synthetic devices will vary from one library to another.

Ex. Synonyms, related terms and other variants must now be collected, either by human selection, or with the aid of the machine.

Ex. In his book's section ' Watchamacallit' he forecasts that communication between user and machine will be through voice for entering text and a pen-like device for pointing.

Ex. The article is entitled 'Exhibits in the American Pavilion at the 1958 Brussels World's Fair: women's clothing, men's gadgets, hot dogs and haute couture'.

Ex. The term widget is taken from the 1963 movie, 'The Wheeler-Dealers'.

Ex. An adjustable seating rig was used to create the three-dimensional shape of a static lounge chair.

Ex. People want information available through the appliances they use in the mainstream of their daily lives.

Ex. Data-capture units are light pens, and such units can be made available at various locations in the library for public consultation.

Ex. If you are in cahoots with the circle of power, you get your projects approved in no time, and in some cases, you can build the most hideous and unsightly contraption.

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* aparato burocrático = bureaucratic apparatus.

* aparato de aire acondicionado = air conditioner.

* aparato de grabación = recorder.

* aparato de informática del tamaño de la palma de la mano = palm computing device.

* aparato de lectura = reading machine.

* aparato del partido = party machinery.

* aparato de medición = meter.

* aparato de radio = radio set.

* aparato de televisión = television set, TV set.

* aparato de vídeo = videocassette recorder (VCR), home video recorder, video recorder.

* aparato digestivo = gastrointestinal tract, digestive tract.

* aparato eléctrico = electrical apparatus, power appliance.

* aparato electrónico = electronic device.

* aparato motorizado = motorised device.

* aparato óptico = optical device.

* aparato para el uso de la información = information appliance.

* aparato para usar Internet = Internet appliance.

* aparato político = machine politics.

* aparato propagandista = propaganda machine.

* aparatos = gadgetry, mechanical equipment.

* aparatos de vídeo = video equipment.

* aparatos eléctricos = electrical equipment, electrical appliances, appliances, household appliances.

* aparatos eléctricos del hogar = home appliances, domestic appliances, home appliances.

* aparatos electrónicos = electronic(s) appliances.

* aparato urinario = urinary tract.

* zona con aparatos electrónicos = equipment area.

* * *

1)

a) ( máquina)

b) ( de televisión) set; ( de radio) receiver

2) ( para gimnasia) piece of apparatus

3)

a) ( audífono) tb

b) (Odont) tb

4) ( teléfono) telephone

5) (frml) ( avión) aircraft

6) (estructura, sistema) machine

7) ( ceremonia) pomp

8) (fam & euf) ( pene) weenie (AmE colloq), willy (BrE colloq); ( genitales masculinos) equipment (euph)

•

- aparato circulatorio/digestivo/respiratorio

- aparato ortopédico

* * *

* * *

(máquina): tiene la cocina llena de aparatos eléctricos the kitchen is full of electrical appliances

ese tipo de análisis requiere aparatos especiales that type of test requires special equipment

uno de esos aparatos para hacer zumo one of those juicer machines

el aparato para tomarte la tensión the apparatus for taking your blood pressure

2 (de televisión) set, receiver; (de radio) receiver

B (para gimnasia) piece of apparatus

los aparatos the apparatus, the equipment

rowing machine

1 (audífono) tb

aparato auditivo hearing aid

2 ( Odont) tb

aparatos braces (pl), brace ( BrE)

D (teléfono) telephone

ponerse al aparato to come to the phone

¡al aparato! speaking!

E ( frml) (avión) aircraft

F (estructura, sistema) machine

el aparato del partido the party machine

el aparato represivo montado por la dictadura the machinery of repression set up under the dictatorship

1 (ceremonia) pomp

fue recibido con mucho aparato he was received with great pomp (and ceremony)

todo el aparato que acompañó a la boda del príncipe all the pageantry which accompanied the prince's wedding

2 ( fam) (jaleo, escándalo) fuss ( colloq), to-do ( colloq)

H ( fam euf) (pene) thing ( colloq), weenie ( AmE colloq), willy ( BrE colloq); (genitales masculinos) equipment ( euph)

circulatory system

critical apparatus

digestive system

thunder and lightning

una fuerte tormenta acompañada de gran aparato eléctrico a heavy thunderstorm

surgical appliance

respiratory system

* * *

a) ( máquina):

◊ uno de esos aparatos para hacer pasta one of those pasta machines;

b) ( de televisión) set;

c) ( dispositivo) device;

◊ aparato ortopédico surgical appliance;

d) (Odont) tb

◊ aparatos braces (pl)

e) ( teléfono) telephone;

◊ ponerse al aparato to come to the phone

◊ los aparatos the apparatus, the equipment

◊ el aparato del partido the party machine;

* * *

aparato nm

1. [máquina] machine;

compró un aparato para medir el viento she bought a device to measure the wind speed

aparatos eléctricos electrical appliances;

aparatos electrónicos electronic devices;

aparatos de laboratorio laboratory apparatus;

aparato de radio radio;

aparato de televisión television set;

aparato de vídeo video recorder

2. [teléfono]

¡al aparato! speaking!

3. [avión] plane

4. [prótesis] aid;

5. [en gimnasia] [en competición, escuela] piece of apparatus;

aparato de remo rowing machine

6. Anat aparato circulatorio circulatory system;

aparato digestivo digestive system;

aparato excretor excretory system;

aparato genital genitalia, genitals;

aparato locomotor locomotor system;

aparato olfativo olfactory system;

aparato reproductor reproductive system;

aparato respiratorio respiratory system;

aparato urinario urinary tract;

aparato visual visual system

7. Pol

el aparato del partido [altos mandos] the party leadership;

el aparato represivo the machinery of repression

8. [ostentación] pomp, ostentation;

una boda con gran aparato a wedding with a lot of pomp and ceremony

9. Meteo aparato eléctrico thunder and lightning;

una tormenta con impresionante aparato eléctrico a storm with an impressive display of thunder and lightning

10. Fam [genitales de hombre] equipment, Br tackle

* * *

1 piece of equipment; doméstico appliance;

al aparato TELEC speaking

2 BIO, ANAT system

3 de partido político machine

* * *

aparato nm

1) : machine, appliance, apparatus

aparato auditivo: hearing aid

aparato de televisión: television set

2) : system

aparato digestivo: digestive system

3) : display, ostentation

sin aparato: without ceremony

4) aparatos nmpl

: braces (for the teeth)

* * *

aparato n

1. (mecanismo) device / thing

2. (doméstico) appliance

3. (televisión, radio) set

4. (conjunto de órganos) system

5. (de gimnasio) a piece of apparatus

6. (para los dientes) brace