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organized+matter

  • 81 zaakje

    1 [handeltje] little matter/business/affair/thing; 〈 transactie〉 small deal; 〈 karwei〉 job
    2 [ding] affair
    3 [eufemistisch] [voornamelijk geslachtsdelen] works ⇒ business
    ♦voorbeelden:
    1   dat is een vies zaakje • that is a nasty/dirty business
         zijn zaakjes geregeld hebben • have got things (well) organized
         ik vertrouw het zaakje niet • I don't trust the set-up
    ¶   zijn zaakje goed/zaakjes kennen • he knows his stuff/a thing or two

    Van Dale Handwoordenboek Nederlands-Engels > zaakje

  • 82 sort

    A n
    1 (kind, type) sorte f, genre m ; this sort of novel/fabric ce genre de roman/tissu ; this sort of rabbit/person ce genre de lapin/personne ; all sorts of reasons/people/colours toutes sortes de raisons/gens/couleurs ; machines of all sorts des machines de toutes sortes ; different sorts of cakes différentes sortes de gâteaux ; I like board games, backgammon, that sort of thing j'aime les jeux de société, le jaquet, ce genre de jeu ; books, records-that sort of thing des livres, des disques, ce genre de choses ; that's my sort of holiday GB ou vacation US c'est le genre de vacances que j'aime ; I'm not that sort of person ce n'est pas mon genre ; it's some sort of computer c'est une sorte d'ordinateur ; there must by some sort of mistake il doit y avoir une erreur ; this must be some sort of joke ça doit être une plaisanterie ; he must be some sort of madman ce doit être un fou ; I need a bag of some sort j'ai besoin d'un sac quelconque ; you must have some sort of idea tu dois avoir une idée ; an odd ou strange sort of chap un drôle de type ; radiation of any sort is harmful toutes les sortes de radiation sont dangereuses ; any sort of knife will do n'importe quel couteau fera l'affaire ; what sort of person would do such a thing? qui pourrait faire une chose pareille? ; what sort of person does she think I am? pour qui me prend-elle? ; what sort of thing does she like/read? qu'est-ce qu'elle aime/lit? ; what sort of a reply/an excuse is that? qu'est-ce que c'est que cette réponse/excuse? ; you know the sort of thing (I mean) tu vois ce que je veux dire ; the same sort of thing la même chose ; a liar of the worst sort un menteur de la pire or de la plus belle espèce ; in an embarrassed sort of way d'une façon plutôt embarrassée ; something of that ou the sort quelque chose comme ça ; I didn't say anything of the sort! je n'ai jamais dit une chose pareille! ; nothing of the sort ( not in the least) pas du tout ; ‘this milk is off’-‘it's nothing of the sort!’ ‘ce lait est tourné’-‘mais non, pas du tout!’ ; ‘I'll pay’-‘you'll do nothing of the sort!’ ‘je vais payer’-‘il n'en est pas question!’ ; ‘you're being awkward’-‘I'm being nothing of the sort’ ‘tu es vraiment exigeant’-‘ce n'est pas vrai du tout!’ ;
    2 ( in vague description) espèce f, sorte f ; some sort of bird une sorte or espèce d'oiseau ; a sort of blue uniform une sorte or espèce d'uniforme bleu ; a sort of elephant without a trunk une sorte or espèce d'éléphant sans trompe ;
    3 ( type of person) I know your/his sort je connais les gens de votre/son espèce ; people of her sort les gens de son espèce ; he's not the sort to betray his friends ce n'est pas le genre à trahir ses amis ; she's the sort who would cheat c'est le genre or elle est du genre à tricher ; we see all sorts here on voit toutes sortes de gens ici ; he's a good sort c'est un brave type ; she's a good sort c'est une brave fille ;
    4 Comput tri m.
    B of sorts, of a sort adv phr a duck of sorts ou of a sort une sorte de canard ; a hero of sorts une sorte de héros ; progress of sorts un semblant de progrès ; an answer of sorts un semblant de réponse.
    1 ( a bit) sort of cute/eccentric/embarrassed plutôt mignon/excentrique/gêné ; to sort of understand/sympathize comprendre/compatir plus ou moins ; ‘is it hard?-‘sort of’ ‘est-ce que c'est difficile?’-‘plutôt, oui’ ; ‘did you enjoy the film?’-‘sort of’ ‘est-ce que le film t'a plu?’-‘oui, c'était pas mal’ ;
    2 ( approximately) sort of blue-green dans les bleu-vert ; it just sort of happened c'est arrivé comme ça ; he was just sort of lying there il était étendu par terre comme ça.
    D vtr
    1 (classify, arrange) classer [data, files, stamps] ; trier [letters, apples, potatoes] ; to sort books into piles ranger des livres en piles ; to sort buttons by colour ranger des boutons par couleur ; to sort the apples according to size classer les pommes selon leur taille ;
    2 ( separate) séparer ; to sort the good potatoes from the bad séparer les bonnes pommes de terre des mauvaises ; to sort the old stock from the new séparer les vieux stocks des nouveaux.
    to be ou feel out of sorts ( ill) ne pas être dans son assiette ; ( grumpy) être de mauvais poil ○ ; it takes all sorts (to make a world) Prov il faut de tout pour faire un monde Prov.
    ■ sort out:
    ▶ sort [sth] out, sort out [sth]
    1 ( resolve) régler [problem, matter] ; to sort out the confusion dissiper un malentendu ; it will take me hours to sort this mess out il va me falloir des heures pour remettre de l'ordre dans tout ça ; I'll sort it out je m' en occuperai ; they have sorted out their differences ils ont réglé leurs différends ; go and sort it out elsewhere allez vous expliquer ailleurs ; it's time to sort this thing out il est temps de tirer cette affaire au clair ;
    2 ( organize) s'occuper de [details, arrangements] ; clarifier [ideas] ; I'll sort something out with Tim j'arrangerai quelque chose avec Tim ; Rex will sort something out for you Rex arrangera quelque chose pour vous ; I'll sort out with him what I have to do je verrai avec lui ce que j'ai à faire ;
    3 (tidy up, put in order) ranger [cupboard, desk] ; classer [files, documents] ; mettre de l'ordre dans [finances, affairs] ; to sort out one's life mettre de l'ordre dans sa vie ;
    4 ( select) trier [photos, clothes] ;
    5 ( find) trouver [replacement, stand-in] ;
    6 ( mend) réparer [clutch, fault] ;
    ▶ sort out [sth]
    1 ( separate) to sort out the clean socks from the dirty séparer les chaussettes propres des chaussettes sales ; to sort out the truth from the lies démêler le vrai du faux ;
    2 ( establish) to sort out who is responsible établir qui est responsable ; we're still trying to sort out what happened nous essayons toujours de comprendre ce qui s'est passé ;
    ▶ sort [sb] out ○
    1 ( punish) régler son compte à qn ○ ;
    2 ( help) [representative, receptionist, organizer] aider [person] ; the doctor will soon sort you out le médecin te remettra sur pied ;
    ▶ sort [oneself] out ( get organized) s'organiser ; ( in one's personal life) résoudre ses problèmes ; to get oneself sorted out s'organiser ; things will sort themselves out les choses vont s'arranger d'elles-mêmes ; the problem sorted itself out le problème s'est résolu de lui-même.
    ▶ sort through [sth] regarder, passer [qch] en revue [files, invoices] ; sort through the cards until you find the ace of clubs regarde toutes les cartes une par une pour trouver l'as de trèfle.

    Big English-French dictionary > sort

  • 83 Gillette, King Camp

    [br]
    b. 5 January 1855 Fond du Lac, Wisconsin, USA
    d. 9 July 1932 Los Angeles, California, USA
    [br]
    American inventor and manufacturer, inventor of the safety razor.
    [br]
    Gillette's formal education in Chicago was brought to an end when a disastrous fire destroyed all his father's possessions. Forced to fend for himself, he worked first in the hardware trade in Chicago and New York, then as a travelling salesman. Gillette inherited the family talent for invention, but found that his successful inventions barely paid for those that failed. He was advised by a previous employer, William Painter (inventor of the Crown Cork), to look around for something that could be used widely and then thrown away. In 1895 he succeeded in following that advice of inventing something which people could use and then throw away, so that they would keep coming back for more. An idea came to him while he was honing an old-fashioned razor one morning; he was struck by the fact that only a short piece of the whole length of a cutthroat razor is actually used for shaving, as well as by the potentially dangerous nature of the implement. He "rushed out to purchase some pieces of brass, some steel ribbon used for clock springs, a small hand vise and some files". He thought of using a thin steel blade sharpened on each side, placed between two plates and held firmly together by a handle. Though coming from a family of inventors, Gillette had no formal technical education and was entirely ignorant of metallurgy. For six years he sought a way of making a cheap blade from sheet steel that could be hardened, tempered and sharpened to a keen edge.
    Gillette eventually found financial supporters: Henry Sachs, a Boston lamp manufacturer; his brother-in-law Jacob Heilbron; and William Nickerson, who had a considerable talent for invention. By skilled trial and error rather than expert metallurgical knowledge, Nickerson devised ways of forming and sharpening the blades, and it was these that brought commercial success. In 1901, the American Safety Razor Company, later to be renamed the Gillette Safety Razor Company, was set up. When it started production in 1903 the company was badly in debt, and managed to sell only fifty-one razors and 168 blades; but by the end of the following year, 90,000 razors and 12.4 million blades had been sold. A sound invention coupled with shrewd promotion ensured further success, and eight plants manufacturing safety razors were established in various parts of the world. Gillette's business experiences led him into the realms of social theory about the way society should be organized. He formulated his views in a series of books published over the years 1894 to 1910. He believed that competition led to a waste of up to 90 per cent of human effort and that want and crime would be eliminated by substituting a giant trust to plan production centrally. Unfortunately, the public in America, or anywhere else for that matter, were not ready for this form of Utopia; no omniscient planners were available, and human wants and needs were too various to be supplied by a single agency. Even so, some of his ideas have found favour: air conditioning and government provision of work for the unemployed. Gillette made a fortune from his invention and retired from active participation in the business in 1913, although he remained President until 1931 and Director until his death.
    [br]
    Bibliography
    "Origin of the Gillette razor", Gillette Blade (February/March).
    Further Reading
    Obituary, 1932, New York Times (11 July).
    J.Jewkes, D.Sawers and R.Stillerman, 1958, The Sources of Invention, London: Macmillan.
    LRD / IMcN

    Biographical history of technology > Gillette, King Camp

  • 84 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

  • 85 hareket

    ",-ti 1. motion, movement, action. 2. stir, activity. 3. act, action, deed; conduct, behavior. 4. departure. 5. movement, organized movement. 6. earthquake, tremor. 7. mus. tempo. 8. rail. traffic. 9. exercising, exercises, exercise. - cetveli rail. timetable. - dairesi rail. dispatcher´s office. - etmek 1. to move, stir, act. 2. to act, behave. 3. to set out, start; to depart. 4. /a/ to leave for. -e geçirmek /ı/ to set (someone) into action. -e geçmek to begin to act, begin, start. -e getirmek /ı/ 1. to set (something) in motion. 2. to stir up. - kolu starting handle; crank. - noktası 1. point of departure, departure. 2. starting point (of a matter, discussion, etc.)."

    Saja Türkçe - İngilizce Sözlük > hareket

  • 86 tertip

    "1. arrangement, setting up, setup; organizing; planning; contriving, contrivance; the manner in which something is arranged, set up, organized, planned, or contrived. 2. mil. disposition (of troops, artillery, etc.). 3. print. typesetting, setting (a page) in type. 4. way, manner: İşi bu tertip üzere hallettik. We solved the matter in this way. 5. fin. issue (all the bonds issued at one particular time). 6. group (of medicines which are taken together as a treatment for an illness). 7. arrangement (of words, phrases, or clauses) (in a sentence). - etmek /ı/ 1. to arrange, set up; to organize; to plan; to contrive. 2. mil. to dispose (troops, artillery, etc.). 3. print. to typeset, set (a page) in type."

    Saja Türkçe - İngilizce Sözlük > tertip

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