Обучение чтению литературы на английском языке по специальности «Автономные информационные и управляющие системы»

Московский государственный технический университет 
имени Н.Э. Баумана 

Е. А. Яковлева 

ОБУЧЕНИЕ ЧТЕНИЮ ЛИТЕРАТУРЫ  
НА АНГЛИЙСКОМ ЯЗЫКЕ  
ПО СПЕЦИАЛЬНОСТИ  
«АВТОНОМНЫЕ ИНФОРМАЦИОННЫЕ  
И УПРАВЛЯЮЩИЕ СИСТЕМЫ» 

Учебно-методическое пособие 

М о с к в а 
Издательство МГТУ им. Н.Э. Баумана 
2 0 0 7 

УДК 802.0 
ББК 81.2 Англ-923 
Я-474 

Рецензент И.В. Стасенко 

Яковлева Е.А.  
Я-474  
Обучение чтению литературы на английском языке по спе- 
циальности «Автономные информационные и управляющие системы»: Учеб.-метод. пособие. – М.: Изд-во МГТУ 
им. Н.Э. Баумана, 2007. – 28 с.  
 

Пособие содержит оригинальные тексты из английской и американской научно-технической литературы, а также упражнения и 
задания, позволяющие освоить и закрепить лексико-грамматический материал, необходимый для понимания и перевода иностранных изданий по специальности. 
Для студентов старших курсов, обучающихся по специальности 
«Автономные информационные и управляющие системы». 
Ил. 1. Библиогр. 6 назв. 

 
УДК 802.0 
 
ББК 81.2 Англ-923 

 Учебное издание 

Екатерина Александровна Яковлева 

Обучение чтению литературы на английском языке  
по специальности «Автономные информационные  
и управляющие системы» 

Редактор Н.М. Маслова 
Корректор Р.В. Царева 
Компьютерная верстка А.Ю. Ураловой 

Подписано в печать 12.03.2007. Формат 60×84/16. Бумага офсетная. 
Печ. л. 1,75. Усл. печ. л. 1,63. Уч.-изд. л. 1,45. 
Тираж 100 экз. Изд. № 137. Заказ 

Издательство МГТУ им. Н.Э. Баумана 
105005, Москва, 2-я Бауманская ул., 5 

 
© МГТУ им. Н.Э. Баумана, 2007 

ПРЕДИСЛОВИЕ 

Пособие содержит оригинальные тексты из английской и американской научно-технической литературы (с элементами адаптации лишь в особенно трудных для перевода случаях) как для самостоятельной работы студентов, так и для аудиторных занятий под 
руководством преподавателя. 
Каждый из трех разделов включает лексические и грамматические упражнения и задания, выполняя которые, студенты овладевают навыками перевода с английского языка на русский и с 
русского на английский, а также развивают навыки устного обсуждения вопросов, связанных с изучаемой тематикой. 
Овладение терминологией в рамках специальности и необходимой общеупотребительной лексикой позволяет студентам и будущим специалистам получать из иностранных источников информацию, нужную им в исследовательской и другой работе. 
Пособие предназначено для студентов старших курсов, обучающихся по специальности «Автономные информационные и 
управляющие системы» на факультете «Специальное машиностроение». 
 

UNIT I 

1. Learn the new words and word combinations: 

adaptability n  
 адаптивность 
adoptable a 
 приемлемый 
artilicial intelligence (AI) 
 искусственный интеллект 
assertion n 
 утверждение, суждение 
 
boom n 
 звуковой удар; быстрое развитие 
bridge v  
 преодолевать препятствие 
claim v  
 претендовать 
cognitive a 
 познавательный 
consciousness n  
 сознание  
core n 
 сущность, ядро 
disregard v 
 игнорировать, пренебрегать 
emulate v 
 имитировать  
encode v 
 кодировать 
feasibility n  
 возможность 
for the time being  
 в данный момент 
gap n 
 брешь, разрыв 
 
 
heavy parallelism 
 значительный параллелизм 
 
ingenious a  
 изобретательный, искусный, оригинальный 
intentionality n 
 умысел 
magnitude n  
 величина 
multistrategy approach  
 зд. комплексный подход 
neural network  
 нейронная сеть 
predominant a 
 преобладающий 
 
 
query n 
 вопрос 
real-life a 
 реалистический 
reasoning n  
 логическое мышление; доводы 
tie v 
 обязывать; ограничивать 

2. Match Russian and English equivalents. 

(1) artificial intelligence 
(a) навязать свой взгляд 
(2) to produce a boom  
(b) сравнение доводов «за» и 
«против» 
(3) to bridge the gap  
(c) широкий выбор логических устройств 
(4) to launch a project   
(d) создать системы 
(5) to give on-line answers  
(e) заявить права на … 

(6) a wide range of reasoning facilities  
(f) ликвидировать разрыв 

(7) comparison of pros and cons 
(g) дать ответ в режиме реального времени 
(8) order of magnitude 
(h) искусственный интеллект 
(9) to adopt an approach 
(i) обеспечить быстрый рост 
(10) to claim one’s rights  
(j) принять научный метод 
(11) to establish a system  
(k) придерживаться одностороннего подхода 
(12) to rely on one-sided approach (l) начать работу над проектом 
(13) to impose its own view  
(m) порядок величины 

3. Translate the following sentences paying attention to contextual 
meanings of the italicized words. 

1. The artificial satellite launched was manufactured in Russia. The 
fifth generation project was launched in Japan. A launch of a space vehicle is a complicated process. 
2. Ferrous metals are subject to corrosion. Artificial intelligence is 
probably the subject to challenge human interest forever. Data were 
subjected to thorough verification. 
3. Reasoning is done through argumentation, comparison and pro 
and con arguments. The power of reasoning belongs to “homo 
sapiens”. 
4. Both projects have adopted the computationally strong-AI approach. Tsiolkovsky’s ideas were adopted by his followers. 
5. AI technology is undergoing a boom. Aircraft manufacturers 
strive to make the boom of aircraft lower. 
6. To bridge a gap between the two theories scientists worked more 
than a decade. The arches of the bridge were high enough to let a tall 
ship pass. 

4. Translate the following words stating the part of speech they 
belong to. 

Regard – disregard – regardless; general – generality; adopt – 
adoption – adoptability; conscious – consciousness – unconscious; intend – intention – intentionality – unintended; execute – 
executive – execution. 

5. Read and translate the text. 

Text IA. Artificial Intelligence 

To understand current trends in artificial intelligence, the history of 
AI can be of great help. 
The first AI era was impressed by the fact that human brains are 
several orders of magnitude slower than computers (in transmission as 
well as coupling speed). Therefore, making a copy of a human brain on 
a computer would have to result in something ingeniously better. Three 
subjects were predominant: (1) learning without knowledge, (2) neural 
modeling (self organizing systems and decision space techniques), and 
(3) evolutionary learning. 
Major AI projects have not resulted in intelligent or commercially 
successful products. But intelligence cannot be easily achieved on 
digital computers with existing approaches. Today’s computers as 
well as existing approaches basically do not differ much from those of 
30 years ago (apart from being faster and having better storing capacities) and, therefore, are very unlikely to approach not only human 
level but also any level of intelligence established by biological intelligent systems. 
Several other projects were started, based on logic programming 
(LP). The project was heavily based on logic programming to bridge 
the gap between applications and machines. 
Japan has already launched the Sixth Generation project, based on 
real-life domains, neural networks, optical connections, and heavy 
parallelism. This project addresses the tremendous task of codifying  
a vast quantity of knowledge possessed by a typical human into  
a workable system. General assertions have been put into CYC’s 
knowledge base, using a vocabulary with approximately 10³ atomic 
terms. CYC (cyclic computer) is intended to be able to give on-line 
sensible answers to all sensible queries. CYC includes a wide range of 
reasoning facilities, including general deduction and analogical inference. Reasoning is done through argumentation, through comparison 
of pros and cons.  
CYC is the first project of this magnitude. All knowledge in CYC is 
encoded in the form of logical sentences, and not in diagrams, procedures, semantic nets, or neural networks. 
The two projects mentioned could not produce intelligent systems 
at all. They have adopted the computationally strong AI approach instead of at least combining it with others, e.g. cognitive weak-AI. Both 
projects relied on a one-sided approach, disregarding the new school of 

AI. This new approach claims that to design an intelligent system, none 
has to give it all properties of intelligent creatures: unity (i.e. multiple 
knowledge and multistrategy approach), intentionality, consciousness 
and autonomy along with generality and adaptability. 
One algorithm executed on a single processor cannot emulate intelligence. The process must consist of many interleaving and intensively communicating sub processes. The general approach seems 
promising, yet it is not clear in which particular direction the discovery of true intelligence lies. For the time being it seems that new AI is 
strongly related to interdisciplinary sciences, especially biological and 
cognitive sciences. 
The strong thesis of multiple knowledge states that multiple semantic models are an integral and necessary part of intelligence in any 
machine or being in real-life domains. A single model cannot achieve 
as good performance as multiple models because each model ties to 
fit data and noise according to its own structure and therefore ties to 
impose its own view. In other words, although multiple models can be 
at any time transformed into one single model with the same performance as a set of models, in general it is not possible to construct such  
a single model in the process of learning without designing multiple 
models. 
Integration of models after they are designed seems not only feasible but also sensible because of reduction in storage and classification time. 
99% of all existing computer systems and most current AI orientations are based of a single model. Intelligent systems seem to have special properties, e.g. multiplicity. 
(3500 characters) 

6. Answer the following questions. 

1. What three subjects were predominant in making a copy of  
a human brain? 
2. What was logic programming aimed at? 
3. What is the sixth generation project based on? 
4. What does the CYC project address? 
5. What facilities is reasoning done through? 
6. How is knowledge encoded in CYC projects? 
7. What are the characteristic properties of intelligent creatures? 
8. Which are weak and strong points of AI modeling? 

7. Translate the following sentences paying attention to the grammar. 

Object clause 
1. While it is not yet clear whether digital machines can achieve intelligence at all, it is becoming accepted that on digital computers, systems simulating human thought processes will be essentially different 
from humans. 
2. A procedure which determines whether it will stop or not, does 
not exist. 
3. The question remains whether this approach is applicable in all 
the cases. 
4. The problem is whether the results of the test could be recorded, 
whether successful or not. 
Complex subject 
1. Intelligent systems seem to have special properties, e.g. multiplicity. 
2. The new version has been formally proven to be wrong. 
3. The subject is likely to stimulate the reader’s interest. 
4. This change seems to have begun towards the end of the last 
century. 
5. However, the common practice of designing such devices has 
been shown to be inadequate. 
6. Such has indeed proved to be the case. 
7. The reaction could appear to involve a rearrangement. 
Participle I 
1. Today’s computers as well as existing approaches basically do 
not differ much from those of 30 years ago (apart from being faster and 
having better storing capacities) and, therefore, are very unlikely to approach not only human level but also any level of intelligence established by biological intelligent systems.  
2. CYC includes a wide range of reasoning facilities including general deduction and analogical inference.  
3. Both projects relied on a one-sided approach disregarding  
the new school of AI. 

8. Read and translate the text without a dictionary. Give your own 
title. Answer the questions. 

1. What new technologies are available to aerospace manufacturers? 
2. What are the applications of the new technologies? 

Text IB. New Generation of Computers 

New generation of powerful computers will soon be available to 
aerospace manufacturers. Neural networks, fly-by-speech advances1, 
smaller processors and integrated avionics will accelerate the process of 
automation. 
Neural networks are widely believed to be the next step in enhancing2 computer intelligence. Neurocomputers will be able to understand 
highly complex tasks which are extremely difficult to perform with current computers. Research is centering on image processing, target and 
feature recognition. Neural computing is also considered particularly 
suitable for speech recognition, enabling pilots to tell the aircraft to 
change course or arm missiles. Full voice control3 in combat aircraft 
may become a reality soon but it is unlikely to be introduced on commercial aircraft as crews do not fly hand-on-throttle4 stick as in combat 
aircraft. 
One major benefit of growing computer capacity will be the sophistication of monitoring systems, which detect and display error and 
damages requiring maintenance5. 
The latest programme is supposed to develop technologies for the 
new generation equipment using microwave integrated circuit technology based on one chip, incorporating the latest advances in parallel 
processing. New packaging6 and cooling techniques7 are certain to improve reliability. 
(1220 characters) 

9. Speak on the main trends of AI creation from the text below.  

А. Use the following words and word combinations: 
intelligent systems; commercially successful; cognitive; approach; to bridge a gap; applications; general assertions; reasoning; argumentation. 
B. Use the following starting phrases:  
I’d like to speak about…, I’ll begin with…, I shall speak in detail about…, to sum it up…, a major advance was made… 
                                                 
1 fly-by-speech advances – передовая технология управления голосом. 
2 enhance – усиливать, увеличивать. 
3 voice control – управление голосом. 
4 hand-on-throttle – в ручном режиме. 
5 maintenance – ремонт, обслуживание. 
6 packaging – компоновка, герметизация. 
7 cooling technique – криогенная технология. 

Text IC. Applications of AI  

Game playing  
You can buy machines that can play master level chess for a few 
hundred dollars. There is some AI in them, but they play well against 
people mainly through brute force computation—looking at hundreds 
of thousands of positions. To beat a world champion by brute force and 
known reliable heuristics requires being able to look at 200 million positions per second.  
Speech recognition  
In the 1990s, computer speech recognition reached a practical level 
for limited purposes. Thus United Airlines has replaced its keyboard 
tree for flight information by a system using speech recognition of 
flight numbers and city names. It is quite convenient. On the the other 
hand, while it is possible to instruct some computers using speech, most 
users have gone back to the keyboard and the mouse as still more convenient.  
Understanding natural language  
Just getting a sequence of words into a computer is not enough. 
Parsing sentences is not enough either. The computer has to be provided with an understanding of the domain the text is about, and this is 
presently possible only for very limited domains.  
Computer vision  
The world is composed of three-dimensional objects, but the inputs 
to the human eye and computers' TV cameras are two dimensional. 
Some useful programs can work solely in two dimensions, but full 
computer vision requires partial three-dimensional information that is 
not just a set of two-dimensional views. At present there are only limited ways of representing three-dimensional information directly, and 
they are not as good as what humans evidently use.  
Expert systems  
A «knowledge engineer» interviews experts in a certain domain and 
tries to embody their knowledge in a computer program for carrying out 
some task. How well this work depends on whether the intellectual 
mechanisms required for the task are within the present state of AI. 
When this turned out not to be so, there were many disappointing results. One of the first expert systems was MYCIN in 1974, which diagnosed bacterial infections of the blood and suggested treatments. It did 
better than medical students or practicing doctors, provided its limitations were observed. Namely, its ontology included bacteria, symptoms, and treatments and did not include patients, doctors, hospitals,