Discipline annotation “Systems Engineering”

Вид материала

Документы

Содержание Discipline annotation Discipline Description Discipline annotation Prior Requirements Assessment forms Discipline annotation Aims and tasks of the course Course annotation Prior Requirements Discipline annotation Prior Requirements Discipline annotation Amount of hours Course description (content, aims, structure)

Подобный материал:

• Общая теория систем критический обзор, 712.51kb.
• Автоматизация онтологического инжиниринга в системах извлечения знаний из текста automatization, 142.32kb.
• Engineering Fracture Mechanics Структура статьи Предисловие Некоторые общие комментарии, 127.46kb.
• Государственный стандарт союза СССР информационная технология Комплекс стандартов, 428.01kb.
• Компании Cisco Systems, Intel и landesk Software, в лице своего представителя в России, 84.58kb.
• A practical guide to business process re-engineering, 2179.62kb.
• Lecture 3 Typology of morphological systems, 55.03kb.
• Gost r certification System. Register of Quality Systems. Certification procedure, 830.31kb.
• Manual for the Design and Implementation of Recordkeeping Systems (dirks), 1279.81kb.
• Решения компании cisco systems по обеспечению безопасности корпоративных сетей, 147.77kb.

Language of instruction: Ukrainian, Russian, English (within the scope of micro- and macroeconomics terminology that is of English origin).


List of Recommended Literature


1. Экономическая теория (политэкономия) (Economics theory (Political Economics)): Учебник / Под общей ред. заслуженных деятелей науки Российской Федерации, профессоров В.И. Видяпина, Г.П. Журавлевой. – М.: Изд-во Рос. экон. акад., 2000. – 529 с.

2. Курс экономической теории (Course of Economics Theory): учебник / Под общей редакцией проф. Чепурина М.Н., проф. Киселевой Е.А. – Киров: «АСА», 2000. – 752 с.

3. Основи економічної теорії: політекономічний аспект (Principles of economics theory: politico-economic aspect): Підручник / Відп. ред. Г.Н. Климко. – К.: Знання-Прес, 2002. – 615 с.

4. Політична економія (Political Economics): Навч. посібник / К.Т. Кривенко, В.С. Савчук, О.О. Бєляєв та ін.; За ред. д-ра екон. наук, проф. К.Т. Кривенка. – К.: КНЕУ, 2001. – 508 с.

5. Економічна теорія: Політекономія (Economics theory: Political Economics): Підручник / За ред. В.Д. Базилевича. – 3-тє вид., перероб. і доп. – К.: Знання-Прес, 2004. – 615 с.

6. Иохин В.Я. Экономическая теория (Economics Theory): Учебник. – М.: Экономистъ, 2004. – 861 с.

7. Політична економія. (Political economics). За ред. В.О. Рибалкіна, В.Г. Бодрова. – К.: Академвидав, 2004. – 672 с.

8. Бутук А.И. Экономическая теория (Economics Theory): Учеб. пособие. – 2-е изд., перераб. и доп. – К.: Вікар, 2003. – 668 с.

9. Економічна теорія. Посібник вищої школи (Economics Theory. High School Manual). (Воробйов Є.М., Грищенко А.А., Лісовицький В.М., Соболєв В.М.) / Під загальною редакцією Воробйова Є.М. – Харків-Київ, 2003. – 704 с.

10. Киреев А.П. Международная экономика (. В 2-х ч. – Ч. I. Международная экономика: движение товаров и факторов производства. Учебное пособие для вузов (International Economics. In 2 parts. Part I. International economics: movement of goods and factors of production. University Manual). – М.: Междунар. отношения, 2000. – 416 с.

11. Киреев А.П. Международная экономика. В 2-х ч. – Ч. II. Открытая экономика и макроэкономическое программирование. Учебное пособие для вузов (International Economics. In 2 parts. Part II. Open economics and macroeconomic programming) – М.: Междунар. отношения, 2000. – 488 с.

DISCIPLINE ANNOTATION

Economics and Management


Lecturer: Kuklin Volodymyr Mykhaylovych Doctor of science (Physics and Mathematics)

1. TO KNOW
   

Principles of organization and production management; manufacturing process, its organization and structure, types of manufacture; structure and peculiarities of production facilities; mechanisms of price formation; forms of ownership and their influence on the organization and functioning of an enterprise; mechanisms and principles of production distribution and material and technical resources supply; principles of elaborating of an enterprise financial plan; principles of enterprise accountancy; methods of planning and analyzing of business activity; legislative regulation of an enterprise activity; principles of fiscal system activity; financial interrelation between an enterprise and a budget; to distinguish business processes, to know principles of transfer price calculation, to organize budgeting.

2. TO BE ABLE TO:
   

To calculate assets price, product prime cost and its price, to evaluate quality of a product and its competitiveness; to use the system of indices of production financial effectiveness; to make quantitative and qualitative analyses of enterprise effectiveness; to calculate income, funds, effectiveness, cost effectiveness, returns on assets, capital coefficient, intensity of use; make forecasts of production development; to define necessity in material and labor resources; to use the methods of calculus of labor productivity; to work out an enterprise financial plan; to analyze book entry during the accounts of business activity; to work out a plan of economic and social development of an enterprise; to work out a plan calendar of an enterprise; to be able to calculate taxes.

3. Discipline Description: studying of enterprise accounting; methods of planning and analyzing of business activity; legislative regulation of an enterprise activity; principles of the fiscal system functioning; enterprise-budget financial interrelations; to distinguish business processes.
   
4. Methods of Teaching: lectures, workshops, independent work.
   

Elements of problematic lectures, individual tasks for independent work.

5. Assessment Forms: written control by means of individual tasks; written tests; written credit.
   

DISCIPLINE ANNOTATION


Mathematical Statistics in Computerized Systems


Lecturer: Podtsykin Mykola Serafymovych, Associate Professor of the Department of Mathematical Modelling and Software Development of the Mathematics and Mechanical Engineering School.


Prior Requirements: To know courses: “Mathematical Analysis”, “Theory of Measurement and Lebesgue Integral”. “Theory of Probability”.


Description (content, aims, structure,): Modeling of casual parameters, distribution. Interval parameter assessment. Checking of statistics. Line regression. Application of statistics methods in stochastic mathematical models.

Assessment forms: credit


Aim of the Discipline: The aim of the course is in providing future specialists with knowledge in the sphere of modern Theory of Probability and Mathematical Statistics, and applying its methods in modeling and analyzing of the real objects and processes.


Tasks of the Course:

Following a completion of the course students must:


KNOW:

• The fundamental laws of the probability theory and mathematical statistics;
  
• The definition of empirical distribution, moments;
  
• To plot block diagrams;
  
• To model (image) random variable;
  
• Characteristics of point estimations;
  
• Methods of obtaining of point estimations;
  
• Methods of obtaining of interval estimation;
  
• To check statistic hypotheses;
  
• Elements of regression analysis.
  

TO BE ABLE TO:

• To apply the fundamental laws of the probability theory and mathematical statistics for the analysis of real stochastic objects and processes;
  
• To image random variables and real stochastic objects.
  

Description of the discipline: Problems of mathematical statistics. Statistical structure. Definition of the empirical distribution. The Glivenko-Cantelli theorem. The sample curve. Block diagram plot. Imaging of the discrete random variable. Proportional actuator. Imaging of the continuous random variable. Method of the moments of derivation estimate. Probability function. Method of maximum probability of point estimations. Estimation comparison. The Cramer-Rao inequality. Super effective estimations. Sufficient statistic. The Fisher-Neyman theorem. Interval estimation of the ND parameters. Plotting of the interval estimations on big samples. Simple and complex hypotheses. Statistical criteria for the hypotheses examination. Criteria of ² transactions. The Neyman-Pearson theorem. Two simple hypotheses examination. Linear regression. Regression parameters estimation according to the least-squares method.


List of Recommended Literature

Basic:

1. Гихман И.И., Скороход А.В., Ядренко М.И. Теория вероятностей и математическая статистика (Theory of Probability and Mathematical Statistics). К., Выща школа, 1979.
   
2. Климов Г.П.. Теория вероятностей и математическая статистика (Theory of Probability and Mathematical Statistics)М., Издательство Московского университета, 1983.
   
3. Коваленко И.Н., Гнеденко Б.В. Теория вероятностей (Theory of Probabilities). К., Выща школа ,1990.
   
4. Розанов Ю.А. Теория вероятностей, случайные процессы и математическая статистика. (Theory of Probability (Theory of Probability, Casual Processes and Mathematic Statistics).М., Наука, 1985.
   
5. Крамер Г. Математические методы статистики (Mathematical Methods of Statistics). М., Мир, 1975.
   
6. Закс Ш. Теория статистических выводов (Theory of Statistical Conclusions). М., Мир,1975.
   
7. Кендалл М.Д., Стюарт А. Статистические выводы и связи (Statistical Conclusions and Correlation). М., Наука, 1973.
   
8. Боровков А.А. Математическая статистика (Mathematical Statistics) . М., Наука, 1984.
   
9. Леман Э. Проверка статистических гипотез (Examination of Statistical Hypotheses). М., Наука, 1979.
   
10. Бикел П., Доксам К. Математическая статистика (Mathematical Statistics). М., Финансы и статистика, 1983.
    
11. Ермаков С.М., Михайлов Г.А. Курс статистического моделирования (Course of Statistical Modelling). М., Наука, 1976.
    
12. Сборник задач по теории вероятностей математической статистике и теории случайных функций (Collected Problems in Theory of Probability and Casual Functions Theory). Под ред. А.А. Свешникова, М., Наука,1970.
    

Supportive materials

1. Учебно-методическое пособие “Теория вероятностей и математическая статистика” (The manual “Theory of Probability and Mathematical Statistics “). Сост. Рофе-Бекетов Ф.С., Подцыкин Н.С. – Харьков, 2001.
   

DISCIPLINE ANNOTATION

Systems modeling


Lecturer: Podtsykin Mykola Serafimovych, Associate Professor of Mathematical analysis department, School of Mathematics and Mechanical Engineering.


Course, semester: 4^th year, 8^th semester

Prior requirements: knowledge of courses: mathematical analysis. Theory of probability and mathematical statistics


Course description (content, aims, structure): modeling of deterministic and stochastic systems. Aims and tasks of modeling. Modeling of service systems, modeling of small homogeneous and heterogeneous systems. Modeling of engineering systems reliability. Simulation modeling AIMS AND TASKS OF THE COURSE:

The aim of Systems modeling course is to study different types of mathematical models, modeling methods and methods of model analysis for optimization problems and production, social and economic process control.

Tasks of the course

• Study the basic concepts of modeling, classification of models, common modeling methods;
  
• Revise and study mathematical classes facilities for object modeling;
  
• Study and acquire of practical skills in algorithmization of complex systems functioning for simulation models;
  
• Study certainty criteria of modeling and acquirement of corresponding practical skills;
  
• Make models with service systems means; estimation of average big stochastic dynamic systems characteristics.
  

Following the completion of the course a student must: KNOW:

• Existing modeling methods of deterministic and stochastic systems.
  
• Generation of Kolmogorov equation for state probability of stochastic objects.
  
• Service systems modeling methods.
  
• Average dynamic method for estimation of big stochastic systems characteristics.
  

BE ABLE TO:

• Build deterministic and stochastic objects models.
  
• Use simulation modeling for analysis of complex stochastic systems.
  

• Use dynamic method of average for estimation of big stochastic systems characteristics.


Assessment Forms: exam


Supportive Materials:

1. Бусленко Н.П. Моделирование систем.(System modeling) - М.: Наука, 1978.
   
2. Бусленко Н.П. Метод статистического моделирования Method of statistical modeling) - M.: Статистика, 1970.
   
3. Полляк Ю.Г. Вероятностное моделирование на ЭВМ.( Probabilistic computer modeling) - М.: Статистика, 1971.
   
4. Снапелев Ю.М., Старосельский В.А. Моделирование и управление в сложных системах. (Modeling and complex systems administration) - M.: Советское радио, 1974.
   
5. Срагович В.Г. Теория адаптивных систем.(Adaptive system theory) - М.: Наука, 1976.
   
6. Варшавский В.И. Коллективное поведение автоматов. (Automatic machine cooperative behavior); - M.: Наука, 1973.
   
7. Клейнрок Л. Теория массового обслуживания.( Theory of waiting lines )M.: Машиностроение, 1979. 432 с.
   
8. Саати Т.Л. Элементы теории массового обслуживания и ее приложения.( Elements of the theory of waiting lines and its applications ) М.:Сов. радио, 1971. 520 с.
   
9. Вентцель Е.С. Теория вероятностей. ( Probability theory) M.: Наука, 1969. 576 с.
   

10. Вентцель Е.С. Исследование операций. ( Operations research) M.: Сов. радио, 1972. 552 с.
    
11. Смирнов Б.Я., Дунин-Барковский И.В. Краткий курс математической статистики для технических предложений. ( Short course of mathematical statistics and technical suggestions) -M.,: Физматгиз, 1959.- 436 с.
    
12. Голенко Д.И. Моделирование и статистический анализ'псевдослучайных чисел на ЭВМ. - М.: Наука, 1965. - 228 с. Computer modeling and statistical analysis of pseudorandom numbers)
    
13. Советов Б.Я. Моделирование систем. ( System modeling) - M.: Высшая школа, 1985.
    

COURSE ANNOTATION

Basic concepts of mathematical optimization methods


Lecturer: Smortsova Tetyana Ivanivna, Assistant Professor

Aim of the course: to teach future specialists basic concepts of mathematical optimization methods.

Prior Requirements: studying of the course "Basic concepts ef mathematical optimization methods" is based on knowledge of the course "Mathematical analysis".

Tasks of the course:

Following the completion of the course a student must:

KNOW: different problems of calculus of variations and simplest numerical optimization procedures

BE ABLE TO: use studied types of problems and methods for solving specific problems

Course Description. Subject and aims of th course. Examples. A simplest calculus of variations problem. First variation, its calculation and application. Euler Equation. First Euler integral equation in different cases. Examples. Brachistochrone problem. Newton's aerodynamic problem. Weierstrass - Erdmann condition. Regular functional. Second variation, its calculation and application. Legendre necessary condition. Jacobi necessary condition. Euler critical load problem. Jacobi sufficient condition. Vectorial variational calculus problem. Free point Bolza problem. Transversability condition. Higher derivative problem. Isoperimetric problem. Form of rope equilibrium problem, Dido problem. Numerical methods of solving nonlinear algebroid equation. Numerical methods of minimization of function with one variable.

Assessment Forms: during the whole semester students take the following assessment forms:

• Module control
  
• Final control (exam)
  

Supportive Materials:

1. Ахиезер Н.И. Вариационное исчисление (Variations calculus)

2. Еельфанд, Фомин. Вариационное исчисление. (Variations calculus)
   
3. Эльсгольц. Дифференциальные уравнения и вариационное исчисление (Variations calculus and differential equation)
   
4. Еилл, Мюррей, Райт. Практическая оптимизация. (Practical optimization)
   
5. Сухарев, Тимохов, Фёдоров. Курс методов оптимизации. (Optimization method course)
   

DISCIPLINE ANNOTATION

Optimal static solving of simulation and control problems.


Lecturer: Podtsykin Mykola Serafimovych, Associate Professor of Mathematical analysis department, School of Mathematics and Mechanical Engineering.


Aims and tasks of the course:to teach future specialists the theory of making optimal static decisions in stochastic control systems: economic, technical etc.


Prior Requirements: knowledge of courses: mathematical analysis. Theory of probability and mathematical statistics.


Tasks of the course:

Following the completion of the course a student must: KNOW:

• Classical and Bayesian approach to assessment of parameter in statistics.
  
• Construction and analysis of utility function.
  
• Estimation of the Bayesian risk and solution.
  
• The rule of constructing in the Bayesian decision function in statistical problems.
  
• Determination and constructing of conjugate distributions families.
  
• Convergence of posterior distributions.
  

BE ABLE TO:

• Construct and analyse utility function in case of cash income.
  

• Calculate the Bayesian decision function in problems with observation and with the
  known observation value.
  

• Find conjugate distributions families parameters for different observation distributions.
  
• Use the statistical decision theory in economy, psychology and engineering.
  

Supportive Materials:

1. Де Гроот М. Оптимальные статистические решения.( Optimal statistical decisions) M., Мир. 1974.
   
2. Ширяев А.Н. Статистический последовательный анализ. ( Statistical sequential analysis) М., Наука. 1969.
   
3. Чжоу Й., Роббинс X. Об оптимальных правилах остановки. ( About best stopping rules ) Математика. 9:3, 1965.
   
4. Чернов Г., Мозес Л. Элементарная теория статистических решений. ( The elementary theory of statistical decisions) M. 1962.
   
5. Ченцов Н.Н. Статистические решающие правила и оптимальные выводы. (Statistical decision rules and optimal methods) M., Наука, 1972.
   
6. Управление риском: Риск. Устойчивое развитие. ( Sustainable development) M., Наука, 2002.
   
7. Городецкий А.Я. Информационные системы. Вероятностные модели и статистические решения. ( Information systems. Probabilistic models and statistical decisions) СПб, изд-во СПбГПУ, 2003.
   

Supplementary Materials:

1. Гихман И.И., Скороход А.В., Ядренко М.И. Теория вероятностей и математическая статистика. (Probability theory and the mathematical statistics) К., Выща школа, 1979.
   
2. Крамер Г. Математические методы статистики. (Mathematical methods of statistics) M., Мир, 1975.
   
3. Леман Э. Проверка статистических гипотез.( Checkup of statistical hypotheses) M., Наука, 1979.
   
4. Бикел П., Доксам К. Математическая статистика. (The mathematical statistics ) M., Финансы и статистика, 1983.
   
5. Ермаков СМ., Михайлов Г.А. Курс статистического моделирования. (The course of statistical modeling) M., Наука, 1976.
   
6. Зельнер Ф. Байесовские методы в эконометрике. (Bayesian methods in econometrics) M.,: Статистика, 1980.
   
7. Розен В.В. Цель, оптимальность, решение. Математические модели принятия оптимальных решений. ( The aim, optimality, decision. Mathematical models of acceptance of optimum decisions) M. Радио и связь. 1982.
   
8. Фишберн П. Теория полезности для принятия решений. (Utility theory for decision-making) M., Наука, 1978.
   

DISCIPLINE ANNOTATION

Ecology


Lecturer: Popov Hennadii Fedorovych, Associate Professor of Systems and Technologies Modeling Department.

Status: normative

Course , semester: 4^th year, 7^th semester.

Amount of hours: total - 54 academic hours; lectures - 24 hours, workshops - 8 hours, independent work- 18 hours. Module 1 - course of lectures, testing of current knowledge, which students get during lectures. Independent work. Exam.

Prior Requirements: eligible knowledge of physics, biology, higher mathematics and informatics.


Course description (content, aims, structure)

Radioecology is one of the most important branches of general ecology. Radioecology studies nature and radiation sources, influence of ionizing radiation on human beings and environment, migration of radionuclides in environment, radiation sensitivity of living organisms, aftereffects of radiation pollution on environment, radio-ecological problems of atomic power engineering, principle of radiation measurement, principle of radiation monitoring, radiation protection methods, radiation safety legislation.

Radiation is the most important natural and anthropogenic factor in life of biosphere and is the most critical factor for human being. Rapid development of atomic power engineering and widespread use of ionizing radiation sources in different fields of science, technology and national economy create a potential radiation hazard for people and environment radiation pollution.

Recently the question of environmental pollution by nuclear waste became very urgent. Accidents on nuclear power plants and atomic-powered vessels, nuclear waste processing plants have very huge influence in local areas, but they aren't safer in global scale, raising average radiation level in biosphere. Biosphere pollution was caused by nuclear tests. It should be noted, that in many places of the world there are certain areas with increased natural radiation level. Increased radiation background for some places on Earth is a permanent ecological factor, which has different impact on living organisms.

The course "Radioecology" will help to understand the influence of radiation on living things.

The aim of this course is to give an idea of ionizing emission effect as ecological factor on every unit of biosphere.

Tasks to learn:

• Physical nature and law of radioactive decay;
  

• physical-chemical processes during the influence of radiation on substance and living tissues;
  

• assessment of radiation hazard and basic concepts of radiation rationing;
  
• methods and ways of radiation control and protection;
  
• anthropogenic and natural sources of radiation;
  

• environmental conditions in areas where nuclear power plants and other full nuclear fuel cycle plants are located and also in areas with radiation pollution;
  

• protection and radiation pollution prophylaxis:
  

Following the completion of the course a student must know :

• the scheme of radioactive transformation and the unit of activity;
  
• natural and man-made sources of radiation and radiation composition;
  

• main mechanism of radionuclides' behavior in environment and ways of their inflow in plants, animal and human organisms;
  
• radiobiological effects and ecological changes caused by radiation;
  
• the character of influence of nuclear facilities on environment under their normal functioning and in case of emergency situation;
  
• main ecological problems of nuclear fuel cycle;
  
• ways of solving radiation waste problem;
  
• radiation standards.
  

Course program consists of 1 module, which covers 18 topics and a list of literature.

Module 1. The radioactive phenomenon. Nuclear reactions. Ionizing emission. Sources of ionizing emission. Interaction of ionizing emission with substance. Environmental radiation. Man-made sources of ionizing emission. Damage effects of nuclear weapons. Detectors and system in radiation monitoring of environment. Nuclear reactors. Atomic power engineering. Nuclear-power plants. Ecological problems of nuclear fuel cycle. Atomic force. Swimming nuclear-power plants. Nuclear fuel cycle. Problems of depleted radiation fuel. Decommissioning of nuclear-power plants and their preservation. Radiation disasters. Radiobiological effects. Radiation standards. Radiation doses.

Forms of Teaching: lectures and individual work.

Methods of teaching: lectures on which the main systematic material of the course is given, lectures are represented in the form of Power Point presentations on multimedia equipment, answering students' questions on every section of the topic, discussion of the most difficult questions of lectures, demonstration of films about principles of work of nuclear reactors, atomic-power plants, radiation equipment, atomic weapons; individual tasks for individual work. Individual work of the students includes work with academic and scientific books, with the Internet and ends in writing a summary.

Assessment Forms: current testing of students, final testing in the exam.

Evaluation criteria: students who complete their syllabus, videlicet: attended lectures, have their

lecture notes, have their summary concerning questions of individual work.

Supportive Materials:

• the program;
  
• schedule of course;
  
• electronic abstract of lectures;
  
• lectures in the form of Power Point presentation.
  
• theme film;
  
• list of tasks for individual work;
  
• list of literature and information sources;
  
• list of tasks foe the exam.
  

Language of Instruction: Russian (for the reason that groups contain many foreign students and in their contracts Russian is stated as the language of instruction).

List of Recommended Literature:

Basic

1. Коваленко Г.Д. Радиоэкология Украины. (Radioecology in Ukraine )Изд. ИНЖЭК. Харьков.2008.
   
2. Вальтер А.К., Залюбовский И.И. Ядерная физика. (Nuclear physics) Высшая школа. Харьков. 1974.
   
3. Ю. Одум. Основы экологии. (The basic foundations of ecology) Издательство "Мир", Москва. 1975.
   
4. Белозерский, Г. Н. Радиационная экология (Radioecology). - М. : Академия, 2008. - 384 с.
   
5. Безопасность жизнедеятельности. Защита населения и территорий в чрезвычайных ситуациях : учебное пособие для вузов. (Health and safety. Protection of the population and territories in emergency situations: the manual for high schools ) M. : Академия, 2008. - 297 с.
   
6. Прохоров, Б. Б. Социальная экология: учебник для вузов. (Social ecology, the textbook for high schools)M. : Академия, 2007. - 412 с.
   
7. 7 . Сапожников, Ю. А. Радиоактивность окружающей среды. Теория и практика : учебное пособие /( Environmental radioactivity. Theory and practice, the manual)2006. -286 с
   
8. Пивоваров, Ю. П. Радиационная экология : учебное пособие для вузов ( Radioecology: the textbook for high schools)/ M. : Академия, 2004. - 240 с.
   
9. Ярмоненко СП. "Радиобиология человека и животных",( Radiobiology of human and animals) ВШ, Москва. 1997г.
   
10. Лисовский Л.А. "Радиационная экология и радиационная безопасность", Мн. 1997. (Radiation ecology and safety)
    
11. Бабаев Н.С. В.Ф. Демин, Л.А. В.А. Легасов, Ю.В. Сивинцев. Ядерная энергетика, человек и окружающая среда.( Nuclear power engineering, humand and environment) M: «Энергоатомиздат», 1984.
    

Supplementary

1. Кудряшов Ю.Б. Радиационная биофизика. (Radiation biophysics) M.: Физматлит, 2004.
   
2. H. Г. Гусев, E. E. Ковалев, В. П. Машкович, А. П.Суворов. Защита от ионизирующих
   излучений. (Health physics) M.: "Энергоатомиздат", 1990.
   
3. Жабо В.В. Охрана окружающей среды на ТЭС и АЭС. ( Environmental protection
   onthermal and nuclear power plants ) - M.: Энергоатомиздат, 1992.
   
4. Изотопы: свойства, получение, применение. (Isotopes: properties, reception, application.) В 2-х томах. ФИЗМАТЛИТ. Москва. 2005.
   
5. Ковальський О.В. Лазар А.П., Людвинський Ю.С. та ін. Радіаційна медицина.
   (Radiation medicine) Київ. Здоров'я.-1993..
   

Informational resources

1. ergy.ru
   
2. http//raatom.ru ((Ат.электрост, яд.реакторы, яд.физика, яд.оружие )
   
3. http//nuclphys.sinp.msu.ru
   
4. http//atomas.ru
   
5. http//www.cpce.ru/tools/rtad_iocham_main.shtml
   
6. ссылка скрыта