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• Zdorovoe TV
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• Основи медсестринства 3 страница. E Порцію А В С відправити в лабораторію
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ПОСМОТРИТЕ ВИДЕО ПО ТЕМЕ: Как делают шунтирование

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Because most of this introduction is non-technical and yet I want you to believe me, I feel compelled to offer you my credentials. I want you to be convinced that I know what I am talking about. Here is one such fact:. Science is hated because its mastery requires too much hard work, and, by the same token, its practitioners, the scientists, are hated because of their power they derive from it.

I should repeat it a third time because whatever I say three times is true. Deem that done. Archemedes was murdered by the Romans, Hypatia was murdered by the Christians, the Moslims burned down the library of Alexandria, and in , Lavoisier lost his head on the guillotine because of the verdict of the populace that the French Revolution had no use for scientists. Less than a decade later, France had its next dictator, but the rabble never made the connection.

So slow, as a matter of fact, that in the first decade of this century, Albert Einstein developed the theory of Brownian motion because of the large number of chemists that still refused to believe in the atomicity of matter.

When the science of chemistry eventually emerged, alchemy had already all but disappeared. Chemically speaking, there has been an intellectual interregnum, but I invite you to join me for a short while in the thought experiment of envisaging chemistry with alchemy still in existence. Needless to say, almost all the funding goes to the alchemists, who, in their effort to make gold from cheap base materials, at least attack a problem of the highest social relevance, viz.

The chemists are derided because none of their work has contributed anything to the central problem of gold-making. When chemistry then makes assumptions about matter that would exclude gold-making, it is accused of being counterproductive, demoralizing, and harmful to the national interest.

Well, I think that that is enough for our thought experiment: phantasy has already come too close to reality. Well, we all know what happened.

Chemistry is accepted as a science: we hate it for its pollution and our dependency on its products, but we no longer blame it for not trying to make gold. Medicine has been accepted as a science: we hate it for the overpopulation and the soaring medical bill but no longer blame it for not producing the Elixir that gives eternal youth. They are accepted as sciences; at the same time, the flourishing business in Healing Gems and Crystals, the horoscopes in otherwise respectable magazines, and governments relying on astrologers are a healthy reminder that Science as such remains rejected and that the old dreams linger on.

Finally, one general remark about how sciences emerge: sciences become respectable by confining themselves to the feasible and successful by allowing themselves to be opportunity-driven rather than mission-oriented. This, by the way, is why managers hate successful science: because it is not mission-oriented, they cannot manage it. Let us now turn our attention to computing science. It is hated, of course, like any other science.

In order to understand the specific distaste it evokes, and along with it all the pressures exerted on it, we should be aware of all the unrealistic dreams it failed to realize, for, unrealistic as they might be, the dreams linger on.

The dreams have been so many, that I must restrict myself to the major ones. Surely, our computers would unscramble all the secret code of all our enemies and guide our missiles with unfailing precision right on their targets. Robots would take over the tedium of production, guaranteeing a positive balance of trade for all nations. Office automation would multiply the productivity of the white-collar worker, information systems would enable management to avoid waste and to make the right strategic decisions, and finally, the giant brains would not only relieve us from the tedium but also from the obligation to think about hard problems and from the painful responsibility to take difficult decisions.

In short: computers were tolerated because they promised a well protected and prosperous paradise for the lazy, the incompetent, and the cowardly. I cannot repeat often enough that, unrealistic as they are, these dreams continue to be dreamt. Their lure is too strong. So much for the unrealistic dreams. But even the majority of at face-value feasible projects went awry. As said before, sciences become respectable by confining themselves to the feasible, and that is precisely what computing science did: it focussed its attention on the intellectual challenge of how to specify and design reliable software systems of great sophistication.

In doing so, it came to a few unescapable conclusions, all clarifying and inspiring for the computing scientists involved, and each of them unacceptable to the world at large, that refused to part from its cherished dreams.

For instance, an early conclusion was that the only effective way of winning the battle against unmastered complexity requires that one prevents the latter from entering the design in the first place, or, in more technical terms: mathematical elegance is not a dispensable luxury but a factor that decides between success and failure. Mathematical elegance, conceptual simplicity, and their companion, brevity of an unambiguous reference manual, are a condition sine qua non for any product reliable enough to attain stability.

Needless to say, this sober message is unacceptable. Simplicity requires hard work to be obtained and education for its appreciation, and complexity sells much better. I quickly learned this about twenty years ago when I presented orderly program design techniques for the first time in a foreign country.

My audience was the personnel of a software house and, in my innocence, I expected for economic reasons this audience to be highly receptive for techniques for making flawless software.

I gave a beautiful lecture, which fell flat on its face. The managers were horrified at the suggestion that flawless software should be delivered since company derived its stability from the subsequent maintenance contracts. The programmers were horrified too: they derived their intellectual excitement from not quite understanding what they were doing and their professional satisfaction from finding weird bugs they had first introduced in their daring irresponsibility.

Teaching the competence to program boils down to the training of misfits. A more technical finding of computing science was that the reliable design of sophisticated digital systems requires much more formal manipulation than any design task faced before. Moreover, the job requires a degree of formalization in comparison to which classical mathematical reasoning becomes slipshod handwaving.

Unavoidably, programming is becoming applied logic, but this time applied on a scale that was never envisaged by the logicians. So, computing science found itself faced with the task of figuring out how to apply logic effectively on an unprecedented scale.

By now, the competent computing scientist has greatly improved his insight in how to exploit his powers of abstraction for the effective disentanglement of his formal derivations and knows how to design his notations so that his formulae are geared to his manipulative needs and he can let the symbols do the work. So what does the world-at-large do? Quite predictably, it tries to ignore the message, and each time the message raises its ugly head it desperately tries to argue that the message is false or irrelevant.

It is really quite pathetic, but any argument, no matter how crooked, that we can do without VLSAL is so welcome that any snake oil merchant in programming methodology finds a ready market for his wares, no matter how ridiculous. I am not exaggerating. Let me give you a few examples of how expert we have become in sweeping the programming problem under the rug. Just when the computing science community has agreed that simplicity is an essential ingredient of reliability, the DoD adopts Ada!

What more can I say? When the late Andrei Ershov from Novosibirsk asked my opinion about Ada, I told him that I shuddered at the thought that Western security would depend on it and that I would feel much better if I knew that the Red Army had adopted Ada as well. Our own ACM is also great at skirting the programming problem.

Did you ever notice that there is no Special Interest Group on programming? Did you notice that the report on the CS curriculum that was recently published in the CACM carefully spent more space to arguing that the importance of programming should not be overemphasized than to arguing the need to include logic? Such a report, written by many people is, of course, a political compromise, but this compromise was very revealing. Also a bit sickening.

Another revealing phenomenon was the welcome with which the paper was greeted in which Lipton, Perlis and De Millo tried to argue why proving the correctness of programs was a misguided effort. Thank God that programming had nothing to do with Mathematics! In their eagerness to believe these authors, people failed to notice that the argument was based on the consensus model for informal classical mathematics, i. Program derivation is not a social process but a formal calculation. The paper was nonsensical.

A very different way of arguing the irrelevance of striving for flawless programs I learned the other month from Jim Gray. Well that need not deter us: their unashamed appeal to our base instincts makes sales talks at least as interesting as the average lecture. His great theme was that software correctness did not matter at all — and I must confess that this idea seemed very attractive to quite a number of our students.

His first argument was a familiar one: the fact that there is at least one known bug for every thousand lines of its software did not bother IBM at all. By this he meant that if something did not work as it should, you could either avoid using it or try again, for if malfunctioning was due to an unproperly resolved race condition, the error may not show up the second time.

Here the answer is that the theory of how to design systems without race conditions is well-known and that it is much more efficient —and cheaper! As long as your stuff was better than what an army of COBOL programmers would build on top of it, you were okay. By the time he made this remark I felt free to leave the lecture hall.

The best of these efforts just confuse composing with the physical act of writing the score, others are foolish at best, and some are criminal. How well did our departments of computing science educate? As I said before, the training of the competence to program boils down to the training of misfits, and under the circumstances sketched above it is only to be expected that our departments of computing science did not educate too well. I had in my audience the manager of software at a huge bank and I knew he was in trouble.

After three days he told me that, as far as he was concerned, I was teaching useless stuff, though he fully agreed that if their software had been developed in the way shown, most of the problems would not have emerged. Yet he rejected my recommendations because they would have required him to train his programmers better and he did not dare to do so for fear of losing them to the competition.

His conclusion is that programming does not require any sophistication because it should not, and this is the attitude that is faithfully reflected in many computing science curricula. Introducing programming courses have, in fact, become a prime target of curriculum infantilization and, instead of teaching the Very Large Scale Application of Logic, they give the student no more than the most primitive operational arguments for thinking about his programs.

Dealing in our curriculum with programming as a scientific challenge of high calibre is easier said than done: besides the resistance in the rest of the world, you would have to overcome the resistance in your own department. Firstly, the average computing science faculty member considers the problem of programming decently far below his dignity, while at the same time he has not the foggiest notion of how to do it.

It is a very shocking percentage, but you can take my word for it. This wide-spread incompetence is, of course, a severe problem for educating students may be hard, but, as we all know, educating faculty members is near to impossible. A second source of resistance within your department will be formed by those colleagues that have unwisely based their research efforts on the assumed dogma that competent programming is an illusion.

Really teaching how to program would dissolve their research topic and the significance of their expertise would evaporate. You cannot expect them to take kindly to that. Edsger W. EWD By way of introduction Because most of this introduction is non-technical and yet I want you to believe me, I feel compelled to offer you my credentials.

Here is one such fact: Science is hated because its mastery requires too much hard work, and, by the same token, its practitioners, the scientists, are hated because of their power they derive from it.

Let me repeat this, so as to help it to sink in: Science is hated because its mastery requires too much hard work, and, by the same token, its practitioners, the scientists, are hated because of their power they derive from it.

So much for the world in which we are supposed to educate young people in computing. Denning et al.

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It has a gray back, white belly, and orange markings behind its eyes and at the top of its chest. RANGE: The emperor penguin ranges throughout coastal Antarctica and may be seen up to 56 miles inland during the breeding season. Range Map. Near the beginning of summer, adult penguins and their chicks return to the sea and spend the rest of the summer feeding there. The female lays one egg in May or June, transfers the egg to the male, and returns to sea to feed while the male incubates the egg in his brood pouch for about 65 days. After the chick hatches, the male sets the chick on his feet and covers it with his pouch, feeding it a white, milky substance produced by a gland in his esophagus.

Biology is the study of living systems and of the processes, organisms, and environments that have shaped biological diversity on earth. Biology majors become part of a learning community in which students engage in courses that integrate information from the ever-expanding field of the life sciences, and share that intellectual journey with a broadly-trained group of committed faculty. Biology students at Wooster work closely with professional biologists who are dedicated and caring teachers as well as active scientists. The biology curriculum provides students with an engaging learning environment, one that fosters a mastery of the biological concepts required for independent and life-long learning. From introductory courses through upper-level classes, students are encouraged to make connections and to build on their skills in experimental design and hypothesis-testing.

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