Table Of ContentМИНИСТЕРСТВО ОБРАЗОВАНИЯ И НАУКИ РОССИЙСКОЙ ФЕДЕРАЦИИ
НАЦИОНАЛЬНЫЙ ИССЛЕДОВАТЕЛЬСКИЙ ЯДЕРНЫЙ УНИВЕРСИТЕТ
«МИФИ»
Е.А. Гвоздева
COMPUTER SCIENCE
Учебно-методическое пособие
для аспирантов по специальности
«Вычислительная техника»
Рекомендовано к изданию
УМО «Ядерные физика и технологии»
Москва 2011
УДК 811.111(075)
ББК 81.2я7
Г 25
Гвоздева Е.А. Computer science. Учебно-методическое пособие для аспирантов
по специальности «Вычислительная техника». М.: НИЯУ МИФИ, 2011. – 52 с.
Учебное пособие предназначено для подготовки аспирантов, специализирую-
щихся в области вычислительной техники.
Цель данного учебного пособия – обучение свободному чтению специальной
литературы на английском языке без использования метода перевода.
Структура учебного пособия предполагает работу в парах и мини-группах, что
дает возможность совершенствования разговорной речи в рамках предлагаемого
материала.
Поставленные цели соответствуют современной концепции образовательного
процесса, смещающей акцент с усвоения готового знания, предлагаемого препо-
давателем, на самостоятельную, познавательную деятельность студента.
Подготовлено в рамках Программы создания и развития НИЯУ МИФИ.
ISBN 978-5-7262-1601-0 © Национальный исследовательский
ядерный университет «МИФИ», 2011
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2
TO THE TEACHER
The traditional system of education centered on the teacher is becoming obso-
lete. The world has developed a new education paradigm, which turns upside
down the situation in teaching. The modern conception of education revises the
proportions of its main components: the teacher, the text-book and the students,
putting new emphasis on the independent creative cognitive activity of the
learner. The new paradigm implies a shift from ‘teacher-centered learning’ to
‘student-centered learning.’ The postulate “Languages are learned, they are not
taught” (Seneca) is gaining momentum. Learning implies thinking. To learn to
think the learner needs to have a chance of finding things out for himself. That
is why the student’s independent work is very important. DIY – ‘do it yourself’
is not a home exercise, it’s a class one. Besides, group work and pair work are
welcomed because language is a social activity. The stimulus for the learner
here is not to lag behind the others.
Confucius, who was concerned with the problems of education 2500 years
ago, wrote: “I listen and I forget, I see (understand) and I remember, I do and I
learn. Any text is information. Reading the text is information processing by
the mind. Knowledge is the information which you can reproduce. To remem-
ber the information the learner has to understand it. Understanding implies pe-
netrating into the essence of the studied phenomenon. To penetrate into the
essence of the phenomenon the learner has first to analyze the text and then to
contract it. Translating texts is an unnecessary activity in the process of learn-
ing languages. Translation is done by the knower of the language for those who
don’t know it. By making the learner translate we don’t give him a chance to
stop and think, to remember and make notes. The teacher can use translation
only in case it is necessary to check up comprehension.
To bring the learner up to the level of comprehending information the teach-
er is to teach him the structure and the composition on the text and sentence
level; he is to teach him to differentiate between important and unimportant
information, facts and opinions. He is to teach him to follow cause and effect
relationship, he is to teach him how to analyze the information and how to cut it
down to the minimum.
The teacher gives the learner a chance to experiment with language. But the
teacher is no longer the dominant figure in the learning process, he directs, ra-
ther than commands or instructs. According to a new education paradigm it is
the student who learns; the teacher only helps, assists, trains the learners to be
more responsible, motivates, involves everybody in the learning process, en-
courages learners to speak and promotes discussion. He directs, rather than
commands or instructs.
3
INTRODUCTION
HOW EVERYTHING STARTED
Study the passage.
When the work is first done it is completely impractical. Nuclear
physics before the Second World War was like studying Greek poetry.
There were only a handful of people who studied nuclear physics and it
had no practical consequences. Computer technology was a spin off a
philosophical controversy about the foundations of mathematics:
whether mathematics has a firm foundation and how to make it firm.
One of the suggestions, about a hundred years ago, was made by a
famous mathematician David Hilbert. And Hilbert said that we should
formalize mathematics, make an artificial language for mathematical
reasoning. That project failed. But the notion of total formalization, of
a completely artificial language, where it is mechanical to see what
something means, is the most tremendous technological success of the
past century: the computer! These artificial languages are everywhere
now. But they are not artificial languages for mathematical reasoning
which Hilbert wanted. They are languages for calculating, for algo-
rithms, for programming.
Chitin, American mathematician
Vocabulary Notes
1. a consequence – an implication – a result
2. a spin off – something useful that happens unexpectedly as a re-
sult of some other activities – a by-product
3. a controversy – a dispute
4. a suggestion – a proposal – an idea that is put forward
5. to reason – the ability to think in order to make an argument
6. to fail – not to be accepted
7. a notion – a concept
8. tremendous – great – important – impressive
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PART I
DATA PROCESSING
UNIT 1
MAN VS. MAN
PRE-READING TASK
Study some grammar points.
I. We use S seems to V – Russian – вроде бы; по-видимому; соз-
дается впечатление
We use both variants.
1. It seemed that there was no limit to what science could achieve.
2. There seemed to be no limit to what science could achieve.
1. It seems that touch-sensitive “smart” paper is an interesting new
I/O technology that can be used as an inexpensive remote control de-
vice.
2. Touch sensitive smart paper seems to be an interesting I/O tech-
nology that can be used as an inexpensive remote control device.
II. N + to Vo (active); N + to be V3 (passive)
An infinitive (to V) after a noun characterizes it and expresses an ac-
tion which must be done or could be done in the future.
Study the sentences.
1. Early computer pioneers make their programs play like people do
on the basis of knowledge-based searches (or heuristics) to choose the
best moves.
2. A new generation of researchers relied on increasingly fast hard-
ware to conduct searches of game trees.
3. IBM got interested in the challenge to build a system to defeat a
human player.
III. We use to V to talk about the purpose of doing something (why
someone does something.
Study the sentences.
1. In 1989, the members of the Deep Blue team were employed by
IBM to develop a computer to defeat World Chess Champion Garry
Kasparov.
2. To learn to think, a machine needs to have a chance of finding
things out for himself.
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IV. The participle
The verb changes in four forms.
V1 V2 V3 V4
to develop – developed – developed – developing
\ \
participles
Ving (ющий); Ved (нный)
The participle has two functions.
a. The participle following a noun N + Ving or N + Ved gives in-
formation about it.
The participle can be put together with other words to make an adjec-
tival participle clause (определительное придаточное предложение –
который).
Study the sentences.
1. A new generation of researchers conducted searches of game trees
allowing the evaluation of millions of chess positions.
2. The Java language is an interpretive language based on object-
oriented technology.
3. The Pentium microprocessor developed by Intel Corp. became the
workhorse of PCs.
4. Deep Blue ‘magic’ relied on human abilities hidden within a box.
b. When two things happen at the same time, you can use Ving
for one of the verbs.
These structures are used mainly in written English.
Study the sentences.
1. The team spent seven years refining the machine’s software and
adding more custom processors.
2. Kasparov also played along, proclaiming “playing such a match is
like defending humanity.”
V. When we imagine a situation we use would (could, might) + Vo
would – (Russian) бы
could, might – (Russian) мог бы
Study the sentence.
1. If a computer could play chess, then perhaps other problems that
require human intelligence might also be solved.
VI. Независимый причастный оборот
1. ………………… , S + Ving (Ved) = а, и, причём
2. ........................... , with S + Ving (Ved) = при этом
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Study the sentences.
1. The match was really about man vs. man, that is, Kasparov vs.
Deep Blue’s programmers, a view shared by most of them as well.
2. Windows NT come in both server and client versions, the latter
accounting for 80% of total units.
3. In numbers of units, the export of LAN and Web servers will be
largest, with millions of products sold each year.
Give Russian correspondence:
then (in this case), although (though), no + N, to make (to force some-
body to do something), a challenge (a task to be solved), in spite of (de-
spite), as (in the process), like, vs. (against), at all, in fact (really), that is
(that is to say), as well (too), within (inside)
Terminology
1. heuristics – a knowledge-based search
2. a game tree – древовидная схема, дерево игры
3. a custom processor – процессор, запрограммированный по
техническим условиям заказчика
“IN CERTAIN KINDS OF POSITIONS THE COMPUTER SEES
SO DEEPLY THAT IT PLAYS LIKE GOD”
(Kasparov)
Study the passage.
The emergence of an electronic computer in the late 1940s led to
much speculation about “thinking machines.” There seemed to be no
limit to what science could achieve, including building a machine that
could think. If a computer could play chess, then perhaps other prob-
lems that require human intelligence might also be solved. For example,
in a 1949 paper, Claude Shannon, a researcher at MIT, said of pro-
gramming a computer to play chess that, “Although of no practical im-
portance, the question is of theoretical interest, and it is hoped that this
problem will be helpful in attacking other problems of greater signific-
ance.”
Work on computer chess continued mainly in universities. By the
1970s, a community of researchers emerged and began to share new
7
techniques and programs. At the same time, computers were doubling in
speed about every two years. Сomputer pioneers tried to make their pro-
grams play like people do on the basis of knowledge-based searches (or
heuristics) to choose the best moves. A new generation of researchers
included heuristics, but also conducted searches of game trees allowing
the evaluation of millions of chess positions – something no human can
do.
IBM got interested in the challenge. In 1989, the members of the
Deep Blue team graduated and were employed by IBM to develop a
computer to defeat World Chess Champion Garry Kasparov. The first
match took place at the New-York Academy of Science in 1989. Kaspa-
rov’s win was swift but the team learned many valuable lessons and
spent seven years refining the machine’s software and adding more cus-
tom processors.
A six-game rematch took place in Manhattan in 1997. Kasparov won
the first game but missed an opportunity in the second game and lost. In
the last game, he made a simple mistake and lost.
In spite of his loss, it is remarkable that a human could hold his own
against a machine that could evaluate 200 million positions per second.
But some conclusions were made. Kasparov’s typical psychological
strategy of intimidation had no effect on Deep blue. The machine never
got tired or frustrated, factors which began to affect Kasparov’s play as
the match progressed.
The popular media portrayed the match as a battle between “man and
machine.” Kasparov also played along, proclaiming “playing such a
match is like defending humanity.” In fact, it was not a battle of man vs.
machine at all. As philosopher John Searle suggests, the match was re-
ally about man vs. man, that is, Kasparov vs. Deep Blue’s programmers,
a view shared by most of them as well. Deep Blue ‘magic’ relied on
human abilities hidden within a box.
Vocabulary Notes
1. emergence – appearance
2. a speculation – a discussion
3. a significance – an importance
4. to share – if people share a task they do it together
5. to rely on – to be based on
6. a search – an attempt to find
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7. an evaluation – a decision about the significance of something
8. to defeat – if you defeat someone, you win a victory over him
9. swift – quick – rapid
10. remarkable – surprising – startling
11. to intimidate – to frighten
12. to proclaim − to say
POST-READING TASK
(To be done at home in writing)
I. Write a summary by answering the questions.
1. Why did the researchers start developing a computer chess pro-
gram although they were sure that it was of no practical importance?
2. What searches did a new generation of researchers conduct?
3. What is heuristics?
4. What does a game tree allow to do?
5. When and where did the first game between a human and a com-
puter take place?
6. Who did the computer play with?
7. Who won?
8. What is Kasparov’s typical psychological strategy?
9. What are the advantages of a machine over man?
10. Was it a man vs. machine game or a man vs. man one?
II. Make up simple sentences with the expressions. Follow the
passage.
1. to miss the opportunity 3. to make a conclusion
2. to have no effect on 4. to get tired
III. Give words close in meaning.
1. a task to be solved 4. to have an effect on
2. to appear 5. an attempt to find
3. a discussion 6. quick
CLASS EXERCISES
Exercise 1 (do it yourself)
Translate the sentences.
1. Cкорость компьютеров удваивалась каждые два года.
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2. Новое поколение исследователей проводило поиск древовид-
ной схемы игры.
3. Древовидная схема позволяла оценить миллионы шахматных
позиций.
4. Ни один человек не может сделать этого.
5. Создание компьютерной программы для игры в шахматы за-
интересовало IBM.
Exercise 2 (do it yourself)
Translate the sentences using: to be of importance, to be of inter-
est, to be of significance. Follow the passage.
1. Создание компьютерной программы для игры в шахматы не
имеет никакого практического значения.
2. Эта проблема представляет чисто теоретический интерес, но
она поможет решить более важные задачи.
UNIT 2
WHAT’S NEXT?
PRE-READING TASK
Study some grammar points.
I. We use to V to talk about the purpose of doing something (why
someone does something.
Study the sentences.
1. Grandmasters and World Champions use computer chess pro-
grams to train for play, both against machines and other humans.
2. Logic is not enough to correctly answer this question.
II. Gerund
Preposition (предлог) + N + Ving (active) or N + being V3 (pas-
sive) = Russian = то, что; gerunds are used only in written English.
Study the sentence.
In spite of the millions of positions per second being evaluated, com-
puters and humans are matched.
III. We use whether when talking about a doubt between two alter-
natives = Russian = V + ли
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