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technological+processes

  • 1 tehnološki procesi

    * * *
    • technological processes

    Hrvatski-Engleski rječnik > tehnološki procesi

  • 2 подсистема управления технологическими процессами

    Универсальный русско-английский словарь > подсистема управления технологическими процессами

  • 3 Rammler, Erich

    [br]
    b. 9 July 1901 Tirpersdorf, near Oelsnitz, Germany
    d. 6 November 1986 Freiberg, Saxony, Germany
    [br]
    German mining engineer, developer of metallurgic coke from lignite.
    [br]
    A scholar of the Mining Academy in Freiberg, who in his dissertation dealt with the fineness of coal dust, Rammler started experiments in 1925 relating to firing this material. In the USA this process, based on coal, had turned out to be very effective in large boiler furnaces. Rammler endeavoured to apply the process to lignite and pursued general research work on various thermochemical problems as well as methods of grinding and classifying. As producing power from lignite was of specific interest for the young Soviet Union, with its large demand from its new power stations and its as-yet unexploited lignite deposits, he soon came into contact with the Soviet authorities. In his laboratory in Dresden, which he had bought from the freelance metallurgist Paul Otto Rosin after his emigration and under whom he had been working since he left the Academy, he continued his studies in refining coal and soon gained an international reputation. He opened up means of producing coke from lignite for use in metallurgical processes.
    His later work was of utmost importance after the Second World War when several countries in Eastern Europe, especially East Germany with its large lignite deposits, established their own iron and steel industries. Accordingly, the Soviet administration supported his experiments vigorously after he joined Karl Kegel's Institute for Briquetting in Freiberg in 1945. Through his numerous books and articles, he became the internationally leading expert on refining lignite and Kegel's successor as head of the Institute and Professor at the Bergakademie. Six years later, he produced for the first time high-temperature coke from lignite low in ash and sulphur for smelting in low-shaft furnaces. Rammler was widely honoured and contributed decisively to the industrial development of his country; he demonstrated new technological processes when, under austere conditions, economical and ecological considerations were neglected.
    [br]
    Bibliography
    Rammler, whose list of publications comprises more than 600 titles on various matters of his main scientific concern, also was the co-author (with E.Wächtler) of two articles on the development of briquetting brown coal in Germany, both published in 1985, Freiberger Forschungshefte, D 163 and D 169, Leipzig.
    Further Reading
    E.Wächtler, W.Mühlfriedel and W.Michel, 1976, Erich Rammler, Leipzig, (substantial biography, although packed with communist propaganda).
    M.Rasch, 1989, "Paul Rosin—Ingenieur, Hochschullehrer und Rationalisierungsfachmann". Technikgeschichte 56:101–32 (describes the framework within which Rammler's primary research developed).
    WK

    Biographical history of technology > Rammler, Erich

  • 4 Автоматизация технологических процессов

    Универсальный русско-английский словарь > Автоматизация технологических процессов

  • 5 САПР-Т

    Универсальный русско-английский словарь > САПР-Т

  • 6 мониторинг потенциально опасных химико-технологических процессов

    Универсальный русско-английский словарь > мониторинг потенциально опасных химико-технологических процессов

  • 7 оборудование для контроля технологических процессов

    Универсальный русско-английский словарь > оборудование для контроля технологических процессов

  • 8 отдельные узлы технологических процессов

    Универсальный русско-английский словарь > отдельные узлы технологических процессов

  • 9 подсистема управления ТП

    Универсальный русско-английский словарь > подсистема управления ТП

  • 10 расчёт параметров технологических процессов подземной добычи руд

    Универсальный русско-английский словарь > расчёт параметров технологических процессов подземной добычи руд

  • 11 система проектирования технологических процессов

    Универсальный русско-английский словарь > система проектирования технологических процессов

  • 12 производствен

    production (attr.)
    производствен план a production plan
    производствени отношения relations of production
    производствен процес a process of produc-tion; a production process
    производствени разходи costs. of production, production cost, working expenses
    производствена практика practical training
    производствен стаж length of service; industrial record/experience
    производствено съвещание a conference on production, a conference on current problems of work/production
    производствена травма an industrial injury
    * * *
    произво̀дствен,
    прил. production (attr.); \производствен график load chart; \производствен стаж length of service; industrial record/experience; \производствена практика practical training, in-the-job practice; \производствена травма industrial injury; \производствени мощности production facilities; \производствени отношения relations of production; \производствени процеси industrial and technological processes; \производствени разходи costs of production, production cost, working expenses; \производствено време job time; \производствено съвещание conference on production, conference on current problems of work/production.
    * * *
    industrial: производствен injury - производствена травма; production: a process of производствен - производствен процес, производствен costs - производствени разходи
    * * *
    1. production (attr.) 2. ПРОИЗВОДСТВЕН а практика practical training 3. ПРОИЗВОДСТВЕН план a production plan 4. ПРОИЗВОДСТВЕН процес a process of produc-tion;a production process 5. ПРОИЗВОДСТВЕН стаж length of service;industrial record/experience 6. ПРОИЗВОДСТВЕНa травма an industrial injury 7. ПРОИЗВОДСТВЕНo съвещание a conference on production, a conference on current problems of work/production 8. ПРОИЗВОДСТВЕНи отношения relations of production 9. ПРОИЗВОДСТВЕНи разходи costs. of production, production cost, working expenses

    Български-английски речник > производствен

  • 13 drvno tehnološki procesi

    • timber technological processes

    Hrvatski-Engleski rječnik > drvno tehnološki procesi

  • 14 совершенствование

    improvement, perfection, improving

    совершенствование государственного аппарата — improvement / perfection of the state machinery / apparatus

    Russian-english dctionary of diplomacy > совершенствование

  • 15 Pliny the Elder (Gaius Plinius Secundus)

    SUBJECT AREA: Metallurgy
    [br]
    b. c. 23 AD Como, Italy
    d. 25 August 79 AD near Pompeii, Italy
    [br]
    Roman encyclopedic writer on the natural world.
    [br]
    Pliny was well educated in Rome, and for ten years or so followed a military career with which he was able to combine literary work, writing especially on historical subjects. He completed his duties c. 57 AD and concentrated on writing until he resumed his official career in 69 AD with administrative duties. During this last phase he began work on his only extant work, the thirty-seven "books" of his Historia Naturalis (Natural History), each dealing with a broad subject such as astronomy, geography, mineralogy, etc. His last post was the command of the fleet based at Misenum, which came to an end when he sailed too near Vesuvius during the eruption that engulfed Pompeii and he was overcome by the fumes.
    Pliny developed an insatiable curiosity about the natural world. Unlike the Greeks, the Romans made few original contributions to scientific thought and observation, but some made careful compilations of the learning and observations of Greek scholars. The most notable and influential of these was the Historia Naturalis. To the ideas about the natural world gleaned from earlier Greek authors, he added information about natural history, mineral resources, crafts and some technological processes, such as the extraction of metals from their ores, reported to him from the corners of the Empire. He added a few observations of his own, noted during travels on his official duties. Not all the reports were reliable, and the work often presents a tangled web of fact and fable. Gibbon described it as an immense register in which the author has "deposited the discoveries, the arts, and the errors of mankind". Pliny was indefatigable in his relentless note-taking, even dictating to his secretary while dining.
    During the Dark Ages and early Middle Ages in Western Europe, Pliny's Historia Naturalis was the largest known collection of facts about the natural world and was drawn upon freely by a succession of later writers. Its influence survived the influx into Western Europe, from the twelfth century, of translations of the works of Greek and Arab scholars. After the invention of printing in the middle of the fifteenth century, Pliny was the first work on a scientific subject to be printed, in 1469. Many editions followed and it may still be consulted with profit for its insights into technical knowledge and practice in the ancient world.
    [br]
    Bibliography
    The standard Latin text with English translation is that edited by H.Rackham et al.(1942– 63, Loeb Classical Library, London: Heinemann, 10 vols). The French version is by A.
    Ernout et al. (1947–, Belles Lettres, Paris).
    Further Reading
    The editions mentioned above include useful biographical and other details. For special aspects of Pliny, see K.C.Bailey, 1929–32, The Elder Pliny's Chapters on Chemical Subjects, London, 2 vols.
    LRD

    Biographical history of technology > Pliny the Elder (Gaius Plinius Secundus)

  • 16 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

  • 17 aprendizaje a través de la red

    (n.) = electronic learning [e-learning]
    Ex. The age of e-learning is already here and the interplay of technological developments and socio-economic change which has had such an impact on the commercial sector has already begun to change the processes of teaching and learning.
    * * *
    (n.) = electronic learning [e-learning]

    Ex: The age of e-learning is already here and the interplay of technological developments and socio-economic change which has had such an impact on the commercial sector has already begun to change the processes of teaching and learning.

    Spanish-English dictionary > aprendizaje a través de la red

  • 18 aprendizaje virtual

    (n.) = electronic learning [e-learning], virtual learning
    Ex. The age of e-learning is already here and the interplay of technological developments and socio-economic change which has had such an impact on the commercial sector has already begun to change the processes of teaching and learning.
    Ex. In other words, an essential element of adequate preparation and adaptability is to foster within students a positive attitude towards computers and virtual learning.
    * * *
    (n.) = electronic learning [e-learning], virtual learning

    Ex: The age of e-learning is already here and the interplay of technological developments and socio-economic change which has had such an impact on the commercial sector has already begun to change the processes of teaching and learning.

    Ex: In other words, an essential element of adequate preparation and adaptability is to foster within students a positive attitude towards computers and virtual learning.

    Spanish-English dictionary > aprendizaje virtual

  • 19 enseñanza virtual

    (n.) = electronic learning [e-learning]
    Ex. The age of e-learning is already here and the interplay of technological developments and socio-economic change which has had such an impact on the commercial sector has already begun to change the processes of teaching and learning.
    * * *
    (n.) = electronic learning [e-learning]

    Ex: The age of e-learning is already here and the interplay of technological developments and socio-economic change which has had such an impact on the commercial sector has already begun to change the processes of teaching and learning.

    Spanish-English dictionary > enseñanza virtual

  • 20 examinar

    v.
    1 to examine.
    El científico examinó la evidencia The scientist examined the evidence.
    El médico examinó al paciente The doctor examined the patient.
    Ricardo examinó el libro Richard examined=perused the book.
    2 to interrogate.
    La policía examinó al testigo The police interrogated the witness.
    * * *
    1 (gen) to examine
    2 (investigar) to consider, inspect, go over
    1 to take an examination, sit an examination
    * * *
    verb
    •
    * * *
    1. VT
    1) [+ alumno] to examine
    2) [+ producto] to test
    3) [+ problema] to examine, study
    4) [+ paciente] to examine
    2.
    See:
    * * *
    1.
    verbo transitivo
    1) <alumno/candidato> to examine
    2) (mirar detenidamente, estudiar) < objeto> to examine, inspect; <documento/proyecto/propuesta> to examine, study; <situación/caso> to study, consider; < enfermo> to examine
    2.
    examinarse v pron (Esp) to take an exam

    me examiné de latín — I had o took my Latin exam

    * * *
    = analyse [analyze, -USA], assess, discuss, examine, go over, look at, look into, overhaul, study, survey, probe into, offer + an account of, go through, vet, test, look over, check out, check up on, keep + tabs on, review, question, peruse, screen, probe.
    Ex. With a clear objective, the next step is to analyse the concepts that are present in a search.
    Ex. Without such guidelines each document would need to be assessed individually, and inconsistencies would be inevitable.
    Ex. This review also illustrates some of the issues which cataloguers have discussed over the years, and demonstrates other solutions to standards in cataloguing than those embodied in modern cataloguing codes.
    Ex. The article 'Home schoolers: a forgotten clientele?' examines ways in which the library can support parents and children in the home schooling situation.
    Ex. The person assigned as coach goes over the work of the new abstractor, makes editorial changes, and discusses these changes with the new man.
    Ex. This article looks at three interrelated issues regarding on-line services based on the recent literature.
    Ex. The main concern is to look into current use of, and interest in, electronic information services, and also to gauge opinion on setting up a data base concerned solely with development issues.
    Ex. It is difficult to overhaul the basic structure of an enumerative scheme without complete revision of sections of the scheme.
    Ex. Each of the binders is portable and can be separately studied.
    Ex. Chapters 7 and 8 introduced the problems associated with author cataloguing and have surveyed the purpose of cataloguing codes.
    Ex. If one probes more deeply into the question of truth and falsehood, one gets into difficult philosophical issues, which we prefer to leave to others.
    Ex. This article offers an account of the processes shaping the professionalisation of college and research librarianship within the framework of 4 contemporary sociological theories.
    Ex. I believe Mr. Freedman hired about 11 student assistants to go through this intentionally dirty file and clean it up.
    Ex. All three types of material, when first received by DG XIII, are submitted to the Technological Information and Patents Division of DG XIII in order to vet items for possible patentable inventions.
    Ex. Inmate library workers often test a new librarian, but once he or she has passed the test, they usually become very protective and staunch promoters of the library.
    Ex. It would be of enormous help to us if you could put a few things together for us to look over.
    Ex. Where problems do arise it is sensible to check out the training programme before blaming the assistant for poor performance of duties.
    Ex. The physical effort of keeping tabs on people as well as the distasteful practice of checking up on staff output achieves nothing and may do considerable damage.
    Ex. The physical effort of keeping tabs on people as well as the distasteful practice of checking up on staff output achieves nothing and may do considerable damage.
    Ex. There is only space to review briefly the special problems associated with the descriptive cataloguing of nonbook materials.
    Ex. If this appears to be excessively difficult, maybe it is time to question whether the tool is too complex.
    Ex. A summary differs from an abstract in that it assumes that the reader will have the opportunity to peruse the accompanying text.
    Ex. Employers should take a preventive role in protecting women's general health, for example, screening women workers for cervical cancer.
    Ex. The librarian sometimes must probe to discover the context of the question and to be able to discuss various possible approaches and explore their merits.
    ----
    * al examinar Algo de cerca = on closer examination, on closer inspection.
    * examinar cómo = look at + ways in which.
    * examinar detenidamente = scrutinise [scrutinize, -USA], put + Nombre + under the spotlight, bring + Nombre + under the spotlight.
    * examinar el modo de = examine + way.
    * examinar el papel de Algo = investigate + role.
    * examinar la función de Algo = investigate + role.
    * examinar la posibilidad de (que) = examine + the possibility that/of.
    * examinar los conocimientos = test + knowledge.
    * examinar más detenidamente = look + closer, take + a closer look at, take + a close look.
    * examinar más minuciosamente = examine + in greater detail.
    * examinar minuciosamente = pull apart.
    * examinar + Posesivo + conciencia = search + Posesivo + conscience.
    * examinar rápidamente = scan.
    * examinar un tema = explore + theme.
    * sin examinar = unexamined.
    * * *
    1.
    verbo transitivo
    1) <alumno/candidato> to examine
    2) (mirar detenidamente, estudiar) < objeto> to examine, inspect; <documento/proyecto/propuesta> to examine, study; <situación/caso> to study, consider; < enfermo> to examine
    2.
    examinarse v pron (Esp) to take an exam

    me examiné de latín — I had o took my Latin exam

    * * *
    = analyse [analyze, -USA], assess, discuss, examine, go over, look at, look into, overhaul, study, survey, probe into, offer + an account of, go through, vet, test, look over, check out, check up on, keep + tabs on, review, question, peruse, screen, probe.

    Ex: With a clear objective, the next step is to analyse the concepts that are present in a search.

    Ex: Without such guidelines each document would need to be assessed individually, and inconsistencies would be inevitable.
    Ex: This review also illustrates some of the issues which cataloguers have discussed over the years, and demonstrates other solutions to standards in cataloguing than those embodied in modern cataloguing codes.
    Ex: The article 'Home schoolers: a forgotten clientele?' examines ways in which the library can support parents and children in the home schooling situation.
    Ex: The person assigned as coach goes over the work of the new abstractor, makes editorial changes, and discusses these changes with the new man.
    Ex: This article looks at three interrelated issues regarding on-line services based on the recent literature.
    Ex: The main concern is to look into current use of, and interest in, electronic information services, and also to gauge opinion on setting up a data base concerned solely with development issues.
    Ex: It is difficult to overhaul the basic structure of an enumerative scheme without complete revision of sections of the scheme.
    Ex: Each of the binders is portable and can be separately studied.
    Ex: Chapters 7 and 8 introduced the problems associated with author cataloguing and have surveyed the purpose of cataloguing codes.
    Ex: If one probes more deeply into the question of truth and falsehood, one gets into difficult philosophical issues, which we prefer to leave to others.
    Ex: This article offers an account of the processes shaping the professionalisation of college and research librarianship within the framework of 4 contemporary sociological theories.
    Ex: I believe Mr. Freedman hired about 11 student assistants to go through this intentionally dirty file and clean it up.
    Ex: All three types of material, when first received by DG XIII, are submitted to the Technological Information and Patents Division of DG XIII in order to vet items for possible patentable inventions.
    Ex: Inmate library workers often test a new librarian, but once he or she has passed the test, they usually become very protective and staunch promoters of the library.
    Ex: It would be of enormous help to us if you could put a few things together for us to look over.
    Ex: Where problems do arise it is sensible to check out the training programme before blaming the assistant for poor performance of duties.
    Ex: The physical effort of keeping tabs on people as well as the distasteful practice of checking up on staff output achieves nothing and may do considerable damage.
    Ex: The physical effort of keeping tabs on people as well as the distasteful practice of checking up on staff output achieves nothing and may do considerable damage.
    Ex: There is only space to review briefly the special problems associated with the descriptive cataloguing of nonbook materials.
    Ex: If this appears to be excessively difficult, maybe it is time to question whether the tool is too complex.
    Ex: A summary differs from an abstract in that it assumes that the reader will have the opportunity to peruse the accompanying text.
    Ex: Employers should take a preventive role in protecting women's general health, for example, screening women workers for cervical cancer.
    Ex: The librarian sometimes must probe to discover the context of the question and to be able to discuss various possible approaches and explore their merits.
    * al examinar Algo de cerca = on closer examination, on closer inspection.
    * examinar cómo = look at + ways in which.
    * examinar detenidamente = scrutinise [scrutinize, -USA], put + Nombre + under the spotlight, bring + Nombre + under the spotlight.
    * examinar el modo de = examine + way.
    * examinar el papel de Algo = investigate + role.
    * examinar la función de Algo = investigate + role.
    * examinar la posibilidad de (que) = examine + the possibility that/of.
    * examinar los conocimientos = test + knowledge.
    * examinar más detenidamente = look + closer, take + a closer look at, take + a close look.
    * examinar más minuciosamente = examine + in greater detail.
    * examinar minuciosamente = pull apart.
    * examinar + Posesivo + conciencia = search + Posesivo + conscience.
    * examinar rápidamente = scan.
    * examinar un tema = explore + theme.
    * sin examinar = unexamined.

    * * *
    examinar [A1 ]
    vt
    A ‹alumno/candidato› to examine
    B (mirar detenidamente, estudiar)
    1 ‹objeto› to examine, inspect; ‹contrato/documento› to examine, study
    2 ‹situación/caso› to study, consider; ‹proyecto/propuesta› to study, examine
    3 ‹paciente/enfermo› to examine
    ( Esp) to take o ( BrE) sit an exam
    ayer nos examinamos de latín we had o took o ( BrE) sat our Latin exam yesterday
    * * *

    Multiple Entries:
    examinar    
    examinar algo
    examinar ( conjugate examinar) verbo transitivo
    to examine;
    ‹situación/caso› to study, consider
    examinarse verbo pronominal (Esp) to take an exam
    examinar verbo transitivo to examine: quisiera examinar las pruebas detenidamente, I'd like to thoroughly examine the evidence
    ' examinar' also found in these entries:
    Spanish:
    mirar
    - pensar
    - tantear
    - analizar
    - escudriñar
    - ver
    English:
    examine
    - inspect
    - look into
    - look over
    - paper
    - reassess
    - review
    - scrutinize
    - search
    - see into
    - study
    - test
    - trace
    - view
    - look
    - peruse
    - reexamine
    - survey
    - vet
    * * *
    ♦ vt
    1. [alumno] to examine
    2. [analizar] to examine;
    examinó detenidamente el arma he examined the weapon carefully;
    examinaremos su caso we shall examine her case;
    tienes que ir al médico a que te examine you must go and get the doctor to examine you
    * * *
    v/t examine
    * * *
    1) : to examine
    2) inspeccionar: to inspect
    * * *
    examinar vb to examine

    Spanish-English dictionary > examinar

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