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problem+statement

  • 121 Aufgabenstellung

    Aufgabenstellung f TECH aim, aims pl (figurativ; angestrebtes Ziel); statement of problem, type of problem

    Deutsch-Englisch Wörterbuch Engineering > Aufgabenstellung

  • 122 ampararse

    1 (protegerse) to take shelter, protect oneself
    2 (acogerse) to avail oneself of the protection (en, of), seek protection (en, in)
    ————————
    1 (proteger) to protect, shelter
    2 (ayudar) to help; (favorecer) to favour (US favor)
    1 (protegerse) to take shelter, protect oneself
    2 (acogerse) to avail oneself of the protection (en, of), seek protection (en, in)
    * * *
    * * *
    VPR
    1) (=buscar protección) to seek protection, seek help

    ampararse con o de o en — to seek the protection of

    2) [de la lluvia] to shelter
    * * *
    (v.) = seek + shelter
    Ex. Problem patrons include, but are not limited to, illiterates simply seeking shelter, alcoholics, the homeless, the mentally disturbed, aggressive young people, and those with offensive odours.
    * * *
    (v.) = seek + shelter

    Ex: Problem patrons include, but are not limited to, illiterates simply seeking shelter, alcoholics, the homeless, the mentally disturbed, aggressive young people, and those with offensive odours.

    * * *

    ■ampararse verbo reflexivo to seek protection
    ' ampararse' also found in these entries:
    Spanish:
    amparar
    * * *
    vpr
    1. [en ley]
    ampararse en una ley to have recourse to a law;
    se amparó en su condición de diputado para no declarar he used his parliamentary immunity to avoid making a statement;
    se ampara en la excusa de que no sabía nada she uses her ignorance as an excuse
    2. [cobijarse]
    ampararse de to (take) shelter from;
    se ampararon de la lluvia en una cabaña they sheltered from the rain in a hut;
    cuando pasó por aquella crisis se amparó en su familia her family were a great support to her at that difficult time
    * * *
    v/r seek shelter (de from);
    ampararse en algo seek protection in sth
    * * *
    vr
    1)
    ampararse de : to take shelter from
    2)
    ampararse en : to have recourse to
    * * *
    1. (refugiarse) to shelter
    2. (apoyarse) to seek protection [pt. & pp. sought]

    Spanish-English dictionary > ampararse

  • 123 oximorón

    m.
    oxymoron, seemingly-contradictory statement.
    Un silencio ensordecedor A deafening silence...
    * * *
    * * *
    Ex. The author argues that the 'digital library' is not an oxymoron, pointing to the fact that libraries face the problem of differentiating between the product that is managed in libraries, information, and the familiar container for that product (the book).
    * * *

    Ex: The author argues that the 'digital library' is not an oxymoron, pointing to the fact that libraries face the problem of differentiating between the product that is managed in libraries, information, and the familiar container for that product (the book).

    * * *
    oxymoron

    Spanish-English dictionary > oximorón

  • 124 условие

    clause, condition, criterion
    * * *
    усло́вие с.
    condition
    в [при] таки́х усло́виях … — under such conditions …
    из усло́вия, что́бы … — such that …
    выбира́ть, напр. величину́ сопротивле́ния из усло́вия, что́бы … — choose, e. g., the value of a resistor such that …
    имити́ровать, напр. усло́вия невесо́мости — simulate, e. g., zero-g [zero gravity] conditions
    наруша́ть усло́вие — violate a condition
    при усло́вии, что … — subject to the restriction that …, given that …, provided that …, on condition that …, subject to the condition that …, with the proviso that …
    при про́чих ра́вных усло́виях — other conditions [other things] being equal
    при схо́дных усло́виях — under similar conditions
    ста́вить усло́вием — stipulate, condition, postulate
    удовлетворя́ть усло́виям — satisfy conditions
    авари́йные усло́вия — emergency
    в авари́йных усло́виях — in an emergency
    атмосфе́рные усло́вия — atmospheric conditions, atmospheric environment
    безразли́чное усло́вие вчт. — don't care condition
    усло́вие Ву́льфа—Брэ́гга физ. — Bragg equation, Bragg law
    высо́тные усло́вия — high-altitude environment
    усло́вие гармони́ческого бала́нса элк. — Barkhausen criterion for oscillation
    грани́чные усло́вия — boundary conditions
    установи́ть грани́чные усло́вия — establish boundary conditions
    доста́точное усло́вие — sufficient [sufficiency] condition
    усло́вия зада́чи — statement of a problem
    по усло́виям зада́чи — under the conditions of the problem
    климати́ческие усло́вия ( в технических данных) — environmental conditions
    коне́чное усло́вие — terminal condition
    усло́вия контра́кта — terms of the contract
    по усло́виям контра́кта — under the terms of the contract
    усло́вия косми́ческого простра́нства — space environment
    краевы́е усло́вия — boundary conditions
    усло́вие максима́льности мат. — maximum [ascending chain] condition
    метеорологи́ческие усло́вия — weather conditions
    метеорологи́ческие, просты́е усло́вия ав. — visual meteorological conditions, VMC, visual flight rules [VFR] weather conditions
    метеорологи́ческие, сло́жные усло́вия ав. — instrument meteorological conditions, lMC, instrument flight rules [IFR] weather conditions
    усло́вие минима́льности мат. — minimum [descending chain] condition
    усло́вия нагруже́ния — conditions of loading
    наиху́дшие усло́вия — worst-case conditions
    нача́льное усло́вие — initial condition
    нача́льное усло́вие по … — the initial condition on …
    усло́вие непреры́вности — continuity condition
    усло́вие неразры́вности — continuity condition
    нерасчё́тные усло́вия — off-design conditions
    норма́льные усло́вия — normal conditions
    приводи́ть к норма́льным усло́виям — reduce to normal conditions
    усло́вие нормиро́вки — normality condition
    ограни́чивающее усло́вие — constraint
    окружа́ющие усло́вия — the environment
    усло́вия о́пыта — experimental conditions, experimental arrangement
    усло́вие ортогона́льности — orthogonality condition
    преде́льное усло́вие — limiting condition
    произво́дственные усло́вия — working conditions
    рабо́чие усло́вия — working [service] conditions; (оборудования, прибора) operating environment
    усло́вия соглаше́ния — terms of the contract
    техни́ческие усло́вия [ТУ] — specifications, Specs
    техни́ческие, вре́менные усло́вия — tentative specifications
    техни́ческие усло́вия на испыта́ния — test specifications
    установи́вшиеся усло́вия — steady-state conditions
    фа́зовое усло́вие для генера́ции в ОКГ — phase relationship for lasing action
    усло́вия хране́ния — storage conditions
    усло́вия эксплуата́ции — service, [operating] conditions; (для красок, лаков и т. п.) exposure
    в усло́виях эксплуата́ции — in the field, under field conditions
    прибо́р не тре́бует регулиро́вок в усло́виях эксплуата́ции — the instrument calls for no adjustment in the field
    усло́вия эксплуата́ции, обы́чные — regular service conditions

    Русско-английский политехнический словарь > условие

  • 125 рассматривать

    в данной статье рассматривается задача - the paper examines the problem of

    в статье рассматривается общая постановка - the paper addresses the general statement A будем рассматривать как B - A will be considered B Рассмотрим обзор некоторых работ по исследованию чего-л., выполненных в институте за последние несколько лет. - We will survey some of the research conducted at the institute in the last several years on Однако поставленная задача в известных ранее публикациях не рассматривались - The stated problem has not been addressed, however, in previous known publications Задачи рассмотрены в [2] - The problems are addressed in [2]

    Русско-английский словарь по прикладной механике > рассматривать

  • 126 διορισμός

    A division, distinction, Pl.Ti. 38c, Arist.EN 1134b33, Porph.Abst.3.20.
    II logical distinction, Pl.Plt. 282c; definition, Arist.SE 168a23, al.
    III Math., particular enunciation of a problem, Procl. in Euc.p.203 F.
    2 statement of limits of possibility of a problem, Apollon.Perg.Con.Praef., Archim.Sph.Cyl.2.4, Phld.Acad.Ind.p.17 M.

    Greek-English dictionary (Αγγλικά Ελληνικά-λεξικό) > διορισμός

  • 127 πρόβλημα

    A anything thrown forward or projecting, πόντου π. ἁλίκλυστον sea-washed promontory, S.Aj. 1219 (lyr.).
    2 hindrance, obstacle, Hp.Nat.Mul.67, Mul.1.20, Ael. NA2.13.
    II anything put before one as a defence, bulwark, barrier,

    προβλήματα ἀντ' ἀσπίδων ἐποιεῦντο γεράνων δοράς Hdt.7.70

    , cf.4.175;

    τῶν.. π. τὰ μὲν πρὸς τὸν πόλεμον ὁπλίσματα, τὰ δὲ φράγματα Pl.Plt. 279d

     sq., cf. Sph. 261a; σώματος π., of a shield, A.Th. 540; νεῶν προβλήματα, of a wall, E.Rh. 213; χαλκᾶ προβλήματα the brazen armour of horses, X.Cyr.6.1.51.
    2 c.gen. objecti, defence against a thing,

    αἰχμῆς καὶ πέτρων A.Th. 676

    ;

    χείματος προβλήματα E.Supp. 208

    ;

    π. χειμώνων Pl.Ti. 74b

    ;

    π. κακῶν Ar.V. 615

    ;

    κρύους π. ποιοῦνται τὴν ἐσθῆτα Plu.2.691d

    ; but,
    3 μηδὲν φόβου π. μηδ' αἰδοῦς ἔχειν to have neither fear nor reverence as a defence, S.Aj. 1076; τὸν ποταμὸν π. λαβεῖν, ποιήσασθαι, Plb.2.66.1, 3.14.5.
    III anything put forward as an excuse,

    π. τοῦ τρόπου D.45.69

    ; λαβὼν π. σαυτοῦ παῖδα making a screen of him, S.Ph. 1008.
    IV task. business, E.El. 985, Gal.11.250.
    2 problem in Geometry, etc., Pl.R. 530b, Tht. 180csq., Plu. Marc.14, 19, etc.;

    φυσικὰ π. Epicur.Ep.2p.36U.

    ; οἱ κατὰ πρόβλημα λόγοι (opp. τὰ ἐν τῷ βίῳ) theoretical, Phld.Lib.p.59 O.
    3 in the Logic of Arist., question as to whether a statement is so or not, Arist. Top. 101b28, cf. 104b1: τὰ π. title of work by Arist., cf. Mete. 363a24, PA 676a18, GA 747b5, cf. προβληματικός; also of the extant work wrongly ascribed to Arist.
    4 practical or theoretical problem,

    εἰς π. παμμέγεθες ἐνέπεσε Plb.28.13.9

    ;

    εὕροντο λύσιν τοῦ π. Id.30.19.5

    ;

    ἐν προβλήμασιν ἢ κρίνομεν ἢ βουλευόμεθα Hermog.Inv.1.1

    .
    5 riddle,

    π. προβάλλειν LXX Jd.14.12

    .

    Greek-English dictionary (Αγγλικά Ελληνικά-λεξικό) > πρόβλημα

  • 128 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

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  • Problem statement — A problem statement is a clear concise description of the issues that need to be addressed by a problem solving team and should be presented to them (or created by them) before they try to solve the problem. When bringing together a team to… …   Wikipedia

  • problem statement — uždavinio sąlyga statusas T sritis fizika atitikmenys: angl. problem statement vok. Voraussetzung der Aufgabe, f rus. условие задачи, n pranc. condition du problème, f …   Fizikos terminų žodynas

  • Problem solving — forms part of thinking. Considered the most complex of all intellectual functions, problem solving has been defined as higher order cognitive process that requires the modulation and control of more routine or fundamental skills (Goldstein Levin …   Wikipedia

  • Problem finding — means problem discovery. It is part of the larger problem process that includes problem shaping and problem solving. Problem finding requires intellectual vision and insight into what is missing. This involves the application of creativity.… …   Wikipedia

  • Problem shaping — means revising a question so that the solution process can begin or continue. It is part of the larger problem process that includes problem finding and problem solving. Problem shaping (or problem framing) often involves the application of… …   Wikipedia

  • Statement analysis — is a learned technique, utilised to examine a person s words todetect for concealed information, missing information and whether the information that person provided is true or false. Anytime someone who is lying or withholding sensitive… …   Wikipedia

  • Problem of Apollonius — In Euclidean plane geometry, Apollonius problem is to construct circles that are tangent to three given circles in a plane (Figure 1); two circles are tangent if they touch at a single point. Apollonius of Perga (ca. 262 BC ndash; ca. 190 BC)… …   Wikipedia

  • problem — n. unsettled question source of difficulty 1) to cause, create, pose, present a problem 2) to address, tackle; bring up, raise; resolve, settle, solve a problem 3) an acute, difficult, major, pressing, serious; insoluble, insurmountable problem… …   Combinatory dictionary

  • Statement Coverage — Die kontrollflussorientierten Testverfahren, auch Überdeckungstests genannt, gehören zu der Gruppe der strukturorientierten Testmethoden. Die kontrollflussorientierten Testverfahren orientieren sich am Kontrollflussgraphen des Programms. Es… …   Deutsch Wikipedia

  • problem — /prob leuhm/, n. 1. any question or matter involving doubt, uncertainty, or difficulty. 2. a question proposed for solution or discussion. 3. Math. a statement requiring a solution, usually by means of a mathematical operation or geometric… …   Universalium

  • Problem of future contingents — The problem of future contingents is a logical paradox first posed by Diodorus Cronus from the Megarian school of philosophy, under the name of the dominator , and then reactualized by Aristotle in chapter 9 of On Interpretation . It was later… …   Wikipedia

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