Реферат: Discipline annotation “Systems Engineering”

DISCIPLINE ANNOTATION

“Systems Engineering”


Course of Humanitarian and Socio-Economic Subjects

Hours

Credits

ECTS

Division in Semesters

Credits

Exams

1

Philosophy

108

3




3

2

History of Ukrainian Literature

72

2




2

3

Foreign Language

216

6

1-3

4

4

History of Ukraine

108

3




1

5

Ukrainian language (according to the professional orientation)

108

3

3-4

5

^ Course of Natural Science (Fundamental ) Training Subjects

1

Higher Mathematics

513

14




1-4

2

Physics

405

11

1,3,4

2

3

Discrete Mathematics

162

5

1

2

4

Theory of Probability and Mathematical Statistics

162

5

3

4

5

Engineering and Computer Graphics

108

3

4




6

Numerical Analysis

135

4

6




7

Ecology

54

2

7




8

Electric and Magnetic Circuit Theory

162

5




4

9

Metrology and Measurement

108

3

5




^ Course of General Vocational and Practical Training

1

APLs and Programming

216

6

1

2

2

Object-Oriented Programming

189

5




3

3

System Programming and Operating Systems

216

6

5

6

4

Data Base and Knowledge Organization

162

6

6




5

Electronics and Microcircuitry

108

3




3

6

Computer Basics

108

3

2




7

Computer System Architecture

108

3

4




8

Economics and Organization of Production

108

3

4




9

Management

81

2

8




10

Introduction to Specialty

81

2




1

11

Information Theory (IT)

108

3

5




12

Graphic Data and Text Processing

54

2

2




13

Control Theory

108

3




5

14

Mathematical Methods of Data Research

144

4




7

15

Physical Education

378

11

2,6,7




16

Life Safety and Labor Safety

108

3

4




^ Selective Subjects

1

System Analysis

126

4




5

2

Microprocessors and Their Usage

135

4




5

3

Information Security

162

5

8




4

Computer Networks

108

3




6

5

AI Systems

162

5




8

6

Application Software Package

162

5

2,3




7

Optical Informatics

72

2

5




8

Specialized Programming Languages

144

4

7




^ Optional Subjects

1

Military Training

1044

4

7




^ Courses of General Vocational and Practical Training

1

Mathematical Simulation of Complex Networks

149

4




7

2

General Theories of Information Transfer

176

5




6

3

Parallel Systems and Calculus

108

3

8




4

Components of Complex Computer Network

254

7

6,7

8

5

Control of Complex Computer Network

243

7

7

8

6

Basis of Complex Computer Networks Exploitation

54

2

7






PHYSICS


Lecturer: Hirka Volodymyr Oleksandrovych, Full Professor


^ Prior Requirements: Educational Course in Vocational Education Institutes


Aims of the Course: to create students’ scientific point of view on physical processes in the world, ensure students’ acquisition of the theoretical basis of classical mechanics and molecular physics, general methods of experimental research of mechanical movement characteristics, let them master theoretical basis of molecular physics. To teach students principal methods of solving problems in classical mechanics and molecular physics using fundamental methods of differential and integral calculus and also basic methods of experimental research of mechanical movement characteristics and processes in thermodynamic system. To create general and thematic competence in branches of mechanics and molecular physics.


Task:

To form the scientific world view of a specialist in the sphere of computer science on the basis of theoretical knowledge of mechanic and molecular physics laws, practical skills in solving problems and bringing about experimental parameter measurements of mechanical and thermodynamical processes;

Because of a mathematical instrument of above mentioned parts of mechanic and molecular physics is well developed, their study is very important from the point of view of consolidation of knowledge of mathematical analysis bases and vector algebra in practical solution of certain problems that describe mechanical and thermodynamical processes.

To demonstrate the interrelation between laws of mechanics and molecular physics. This, from the point of broad usage of analog method, is very useful for studying other parts of classical physics, and also from the point of view of similarity of mathematical methods that describe physical processes.

^ Following the completion of the course a student must:

know laws of classical mechanics and molecular physics, be able to use them for solving theoretical tasks, to use these laws for setting procedures of physical parameters measurement, which mechanics and molecular physics operate, to explain experimental results, achieved during his/her laboratory research.

Be able to: measure principle physical parameters during laboratory research.


Subject Description: the subject of the discipline is laws of classical mechanics and molecular physics. This deals with the fact that physics is the main natural science in the vocational education of a computer science professional, without knowing of which a conscious and qualitative usage of knowledge in mathematical and merely social computer disciplines, that are the basis of an education of a future computer science specialist, is impossible. During the first two semesters two branches of physics are studied: mechanics and molecular physics, which are fundamental components of classical physics.




^ Assessment Forms: written following the end of thematic modules; current control of independent work; written reports on laboratory researches; final written test (credit) in the first semester and written exam in the second semester.


List of Recommended Literature

Basic

Савельев И.В. Куpс общей физики (Course of General Physics). - М.: Hаука, 1966. -т.1.

Ландау Л.Д., Ахиезеp А.И., Лифшиц Е.М. Механика и молекуляpная физика (Mechanics and Molecular Physics). -М.: Hаука, 1965.

Дущенко В.П., Кучерук І.М. Загальна фізика: Фізичні основи механіки. Молекулярна фізика і термодинаміка.(General Physics: Physical Basis of Mechanics. Molecular Physics and Thermodymamics) - К.: Вища школа, 1993.- 431 с.

Дутчак Я.Й. Молекулярна фізика. (Molecular Physics) - Видавництво Львівського університету, 1973. С. 264.

Савельев И.В. Сбоpник вопросов и задач по общей физике (Collected Questions and Problems on General Physics). -М.: Hаука, 1982.

Волькенштейн В.С. Сбоpник задач по общему курсу физики (Collected Problems in General physics). -М.: Hаука, 1985.

Иpодов И.Е. Задачи по общей физике (Problems in General Physics). -М.: Hаука, 1988.

Гірка В.О., Гірка І.О., Кондратенко А.М., Методичні поради до розв'язання домашніх завдань з курсу “Фізика” для студентів першого курсу факультету комп'ютерних наук (Methodological recommendations for solving homework Physics problems for the first year students of the Computer Science Department). – Харків.: Просвіта, 2005.

Гірка В.О., Гірка І.О., Кондратенко А.М., Методичні вказівки до виконання лабораторних робіт з курсу “Механіка” для студентів першого курсу факультету комп’ютерних наук (Methodological recommendations for laboratory research in “Mechanics” for the first year students of the Computer Science Department). – Харків.: Просвіта, 2004.

Гірка В.О., Гірка І.О., Кондратенко А.М., Методичні вказівки до виконання лабораторних робіт з курсу “Молекулярна фізика” для студентів першого курсу факультету комп’ютерних наук (Molecular Physics for the first year students of the Computer Science Department). – Харків.: Просвіта, 2004.

Гірка В.О., Гірка І.О., Кіндратенко А.М. Методичні поради до виконання фізичного практикуму студентами першого курсу Інституту високих технологій (Methodological recommendations for workshop in Physics for the first year students of the High Technology Institute). Харків, 2005.

Supplementary

Біленко І.І. Фізичний словник (Dictionary of Physical Terms).-К.: Вища школа, 1993.

Телеснин Р.В. Молекуляpная физика (Molecular Physics). -М.: Высш. школа, 1973.

Кучерук І.М., Горбачук І.Т., Луцик П.П. Механіка. Молекулярна фізика і термодинаміка. Том 1 (Mechanics. Molecular Physics and Thermodynamics. Volume 1). -К.: Техніка, 1999.

Иpодов И.Е., Савельев И.В., Замша О.И. Сборник задач по общей физике (Collected problems in General Physics).



^ DISCIPLINE ANNOTATION

Theory of Probability and Mathematical Statistics


Lecturer: Kabalyants Petro Stepanovych, Assistant Professor of Mathematical Modeling and Software Development Department

Status: normative

Course, semester: I and II courses, 2 and 3 semesters.

Amount of Credits: 5, in total 162 academic hours; 52 hours of lectures, 52 hours of workshops, 58 hours of independent work.

1 semester—2.5 credits: chapters 1,2,3—written test + credit;

2 semester—2.5 credits: chapters 4,5,6—written test + exam;

Prior Requirements: disciplines “Discrete Mathematics”, “Mathematical Analysis”.

Discipline Description (subject, aims, structure): the subject of the discipline is theoretically probabilistic methods and methods of mathematical statistics. Methods of construction of probability experiment model, simulation of random variable, methods of estimation theory, correlation and regression analysis are studied in details. Asymptotic probabilistic methods of analysis are surveyed.

Aim of the course: to provide future specialists with knowledge in the area of modern theory of probability and mathematical statistics, and usage of its methods in modeling and analysis of real objects and processes.

The program of the discipline consists of a schedule, thematic plan, containing 6 chapters and list of supportive materials.

^ Methods of Teaching: lectures, workshops, independent work.

Elements of topical lectures, individual tasks for independent work.

Assessment Forms: written control of individual tasks; written tests; written credit and written exam in the 2 and 3 semesters respectively.



Assessment criteria:


Only those students who have got 35 % of the total amount of credits according to all forms of current control are admitted to an exam; students who have got no less than 91 % of the total amount of credits are free from the exam.


^ Supportive Materials:

Program

Discipline schedule

Textbooks

Department manuals

Collected problems manuals

Set of individual tasks for current control

Tasks for rector tests

Examination cards

Language of Instruction: Russian

List of Recommended Literature


Basic Literature


Гихман И.И., Скороход А.В., Ядренко М.И. Теория вероятностей и математическая статистика (Theory of Probability and Mathematical Statistics). К., Выща школа, 1979.

Климов Г.П.. Теория вероятностей и математическая статистика (Theory of Probability and Mathematical Statistics). М., Издательство Московского университета, 1983.

Коваленко И.Н., Гнеденко Б.В. Теория вероятностей (Theory of Probability). К., Выща школа ,1990.

Розанов Ю.А. Теория вероятностей случайные процессы и математическая статистика (Theory of Probability, Casual Processes and Mathematical Statistics). М., Наука, 1985.

Крамер Г. Математические методы статистики (Mathematical Methods of Statistics). М., Мир, 1975.

Шметтерер Л. Введение в математическую статистику (Introduction to Mathematical Statistics). М., Наука, 1976.

Закс Ш. Теория статистических выводов (Theory of Statistical Conclusions) . М., Мир,1975.

Кендалл М.Д., Стюарт А. Статистические выводы и связи (Statistical Conclusions and Correlation). М., Наука, 1973.

Боровков А.А. Математическая статистика (Mathematic Statistics). М., Наука, 1984.

Леман Э. Проверка статистических гипотез (Check-up of the Statistical Hypotheses). М., Наука, 1979.

Бикел П., Доксам К. Математическая статистика (Mathematic Statistics). М., Финансы и статистика, 1983.

Ермаков С.М., Михайлов Г.А. Курс статистического моделирования (Course of Statistical Modeling). М., Наука, 1976.

Сборник задач по теории вероятностей математической статистике и теории случайных функций (Collected Problems in Theory of Probability and Theory of Casual Functions). Под ред. А.А. Свешникова, М., Наука,1970.


Manuals and Methodological guidance

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

^ DISCIPLINE ANNOTATION

Mathematical Analysis and Differential Equations


Lecturer: Nikolenko Iryna Hennadiivna PhD (Physics and Mathematics), Associate Professor

Status: Normative


Courses, semesters: 1-2 courses, 1-3 semesters


^ Aim of the Course: is in providing future specialists with knowledge in the area of mathematical analysis and differential equations.


Prior Requirements: “Higher Algebra”, 1 semester, “Analytical Geometry”, 1 semester.


Tasks of the Discipline: following the completion of the course students must:


KNOW:

Features of infinitely small consecutive orders or functions;

Rules of differentiation;

Theories of Roll, Langrage, L’Hopital;

Necessary and sufficient conditions for extremum of functions;

Features of the anti-derivative and indefinite integral;

Rules of calculus of the Riemann integral;

Formulae for calculus of a shape area, quantities of lines, volumes of solids;

Formulae of differential of bivariate function, derivative of composite function;

LS method (least square method);

Linear operations on series;

Conditions of similarity and difference of numerical series;

the Leibniz's Theorem, Abel's theorem, Taylor and Maclaurin series;

Euler’s formula, a Fourier series for periodic function and Fourier integrals, Laplace formula;

Formulae for contour, double, triple integral calculus;

Green formulae;

Formulae of vector field current through the surface;

Taylor series;

Methods of solving the first-order equations;

Defining of discriminating polynomial of differential equation; application of the Wronskian, assignment and definition of Cauchy function;

Technology of reduction of the first degree linear equations system to the second degree equation;

Theorems about the existence of Laplace transform;

Formulae of figuring of derivative, convolution integral of originals;

Euler-Poisson equations, Ostrogradsky method;

Reasoning of heuristic formula of natural function according to the method of mathematical induction;

Verifying of the fundamental theorems.


BE ABLE TO:


Calculate borders and derivatives of simple and composite functions with one or a number of variables;

To trace functions, set distinctly, tacitly or with the help of parameters, to plot their graphs;

To find indefinite and defined integrals according to Riemann;

To calculate area of figures, length of lines, volume of solids;

To solve differential equations and systems of differential equations;

To apply differential or integral calculus to solving physical problems;

To trace numerical, consecutive and unusual integral conformity;

To explicate functions of vrai variable in Taylor, Maclaurin and Fourier series;

To find extremum of most functions variables;

To calculate contour; double and triple integrals;

To find the current of vector field through the surface;

To apply Stocks and Gauss-Ostrogradsky formulae;

To calculate integrals with the help of Euler beta and gamma functions.


Discipline Annotation:

Theory of limits: limit of sequence, limit of function, partial, superior and minimum limit of function. Continuity of function: local property of continuous functions, properties of continuous functions on interval. Differential calculus of one-variable function: derivatives and differentials of random order, properties of differential functions; Taylor’s function; extremum examination and plotting of function graphs. Indefinite integral: primary and indefinite integral, their properties; change of variable and integrating by parts; tabular interval; methods of integrating: rational functions; Ostrogradsky method; irrationalities, rational functions from trigonometric; some transcendental functions. Riemann integral: properties of integral functions; geometrical and physical application of integral; Riemann improper integral. Improper integrals; from infinite interval and from unbounded function on finite interval; convergence properties of improper integrals; absolute and conditional convergence. Numerical series; convergence properties of series, absolute and conditional convergence. Space ; metric space, open and closed sets, their properties; compact sets in metric space and in ; arrays in , their convergence; properties of compactedness. Differential calculus of multivariable functions: variables and differentials of random order, properties of differential functions; Taylor function; the implicit function theorem; extremum examinations and extremum conditions. Functional consequence and series; conditions of proportional convergence of functional series; theorems about term-by-term differentiation and integration of functional series; formal power series and Taylor series. Riemann integrals depending on parameter: Euler’s integrals; Laplace method. Riemann multiple integral; properties of integral functions on sets, calculated by Jordan method; Fubini’s and change of variable theorem. Improper integrals; geometrical and physical application of multiple integral. Contour and surface integral: calculus of the first kind surface integrals and their properties, calculus of the second kind surface integrals; General Stock’s theorem and classic specific cases; elements of field theory. Fourier series: Fourier series relating to orthogonal vector system; trigonometrical Fourier series and their point convergence. Fourier integral: Fourier properties of change and point convergence of Fourier integral. Differential equations of n-power: Coachi’s differential equation; geometrical interpretation of the first-degree differential equation; normal system of differential equation; reduction of differential equation to normal system; Linear differential equations: first degree linear differential equations; methods of integrating factor and variations of arbitrary constant ; equations in total differentials; linear differential equations of higher order; linear differential equations with constant coefficients; Euler equation; method of certain constant variations; linear systems of differential equations: linear systems of differential equations with variable coefficients; linear systems of differential equations with constant coefficients. Laplace transform and application of operational calculus for differential equations.


Assessment Forms: calculus, tests, examination.


Supportive Materials: handbooks, methodological manuals and credit tasks.


List of Recommended Literature:


Карташев А.П., Рождественский Б.Л. Математический анализ (Mathematical Analysis). - М.: Наука, 1984.

Кудрявцев Л.Д. Краткий курс математического анализа (Brief Course of Mathematical Analysis). - М.: Наука, 1989.

Зорич В.А. Математический анализ (Mathematical Analysis). - М.: Наука, 1984 (I, II т.).

Фихтенгольц Г.М. Основы математического анализа (Principles of Mathematical Analysis) . - М.: Наука, 1964 (I, II т.).

Кудрявцев Л.Д., Кутасов А.Д., Чехлов В.И., Шабунин М.И. Сборник задач по математическому анализу (Collected Problems in Mathematical Analysis). - М.: Наука, 1984. - I т. (Предел, непрерывность, дифференцируемость).

Кудрявцев Л.Д., Кутасов А.Д., Чехлов В.И., Шабунин М.И. Сборник задач по математическому анализу ( Collected Problems in Mathematical Analysis). - М.: Наука, 1984. - II т. (Интегралы, ряды).

Демидович Б.П. Сборник задач и упражнений по математическому анализу (Collected Problems in Mathematical Analysis). - М.: Наука, 1966.

Петровский И.Г. Лекции по теории обыкновенных дифференциальных уравнений (Lectures in the Theory of Simple Differential Equations). М., Изд-во Моск. Ун-та, 1984.

Степанов В.В. Курс дифференциальных уравнений (Course of Differential Equations). - М.: Гостехиздат, 1953.

Понтрягин Л.С. Обыкновенные дифференциальные уравнения (Simple Differential Equations). - М.: Наука, 1974.

Филиппов А.Ф. Сборник задач по дифференциальным уравнениям (Collected Problems in Differential Equations). - М.: Наука, 1973(1979).



^ DISCIPLINE ANNOTATION


Discrete Mathematics


Lecturer: Kabalyants Petro Stepanovych, Assistant Professor of Mathematical Modeling and Software Development Department

Status: normative

Course, semester: I course, 1and 2 semesters.

Amount of Credits: 5, in total 162 academic hours; 52 hours of lectures, 52 hours of workshops, 58 hours of independent work.

1 semester—2,5 credits: chapters 1,2,3—written test + credit;

2 semester—2,5 credits: chapters 4,5,—written test + exam;

Prior Requirements: school mathematics base

Discipline Description (subject, aims, structure): the subject of the discipline is in methods of discrete mathematics: methods of the theory of sets, graph theory, combinatorics, logic, theory of numbers and theory of coding. Theory of sets and graph theory are studied in detail. Methods of the theory of sets and the theory of coding are studied throughout. A separate chapter is dedicated to the combinatorial analysis.

Aim of the course: to study principle methods of discrete mathematics: graph theory, the theory of sets, combinatorics, logic, the theory of automata and the theory of grammar. Great attention is paid to matrix, numerical and common algebraic methods which are effective in computer realization.

The program of the discipline consists of a schedule, thematic plan, containing 4 chapters which contain 45 topics and list of supportive materials.

^ Methods of Teaching: lectures, workshops, independent work.

Elements of topical lectures, individual tasks for independent work.

Assessment Forms: written control of individual tasks; written tests; written credit and written exam in the 1 and 2 semesters respectively.


Assessment Criteria:


Only those students who got 35 % of the total amount of credits according to all forms of current control are admitted to an exam; students who got no less than 91 % of the total amount of credits are free from exam.


Supportive Materials:

Program

Discipline schedule

Textbooks

Department manuals

Collected problem textbooks (electronic copies for the chapter “Combinatorics)

Electronic version of the first semester notes

Set of individual tasks for current control

Tasks for rector tests

Examination cards

Language of Instruction: Russian

List of Recommended Literature


Basic Literature


Берж К. Теория графов и ее применение (Graph Theory and its Application). – М.: ИЛИ, 1962. – 320с.

Оре О. Теория графов (Graph Theory). – М.: Наука, 1968. – 352с.

Сешу С., Рид М.В. Линейные графы и электрические цепи (Linear graphs and Electric Circuits). – М.: Высшая школа,1971. – 448с.

Харари Ф. Теория графов (Graph Theory). – М.,Мир,1973. – 304с.

Басакер Р.,Саати Т. Конечные графы и сети (Finite Graphs and Networks). – М.:Наука,1974. – 336с.

Кристофидес Н. Теория графов (алгоритмический подход) (Graph Theory (Algorythmic Approach). – М.: Мир, 1978. – 432с.

Майника Э. Алгоритмы оптимизации на графах и сетях (Graphs and Networks Algorithms Optimization on). – М.: Мир, 1981. – 323с.

Свами М., Тхуласираман Н. Графы, сети и алгоритмы (Graphs, Networks and Algorithms). – М.: Мир, 1984. – 454с.

Филлипс Д., Гарсиа-Диас А. Методы анализа сетей (Methods of Networks Analysis). – М.: Мир, 1984. – 496с.

Кук Д., Бейз Г. Компьютерная математика (Computer Mathematics). – М.: Наука,1990. – 384с.

Колмогоров А.Н., Драгалин А.Г. Введение в математическую логику (Introduction into Logistics). Учеб. пособие для вузов. – М.: Изд.-во МГУ, 1982. – 120с.

Сигорский В.П. Математический аппарат инженера (Mathematical Apparatus of an Engineer). – Киев, Техника, 1977. – 766с.

Кузнецов ОЛ.П., Адельсон-Вельский Г.М. Дискретная математика для инженера (Discrete Mathematics for Engineers). – М.: Энергия, 1980. – 342с.

Яблонский С.В. Введение в дискретную математику (Introduction into Discrete Mathematics) . – М.: изд. МГУ, 1986. – 384с.

Виноградов И.М. Основы теории чисел (Principles of the Theory of Numbers). – М.: Наука 1965. – 172с.

Гускин В.М., Цейтлин Г.Е., Ющенко Е.Л. Алгебра, язык, программирование (Algebra, Language, Programming). – К.: Наукова думка, 1978. – 318с.


Manuals and Methodical Guidance


Руткас А.Г. Введение в теорию графов (Introduction into Graph Theory) . Учебное пособие . – Х.: ХГУ, 1993. – 63с.

Дюбко Г.Ф. Введение в формальные системы (Introduction into Formal Systems). – Х.: ХИРЭ, 1992. – 170с.

Бондаренко М.Ф., Білоус Н.В., Шубін І.Ю. Збірник тестових завдань з дискретної математики (Collected Tests in Discrete Mathematics) . – Х.: ХДТУРЕ, 2000. – 156с.

Бондаренко М.Ф., Білоус Н.В., Руткас А.Г. Комп'ютерна дискретна математика: Підручник для ВУЗів. (Computer Discrete Mathematics. High School Textbook) – Х.: Компания СМІТ, 2004. – 479с.



^ DISCIPLINE ANNOTATION


Economic theory


Lecturer: Shedyakova Tetyana Evheniivna, Associate Professor of the Economic Theory Department.,

Status: normative

Course, semester: I course, 2 semester

Amount of Credits: 3, 108 academic hours in total; 32 hours of lectures; 32 hours of seminars, 44 hours of independent work.

^ Prior requirements: “Higher Mathematics”, “Philosophy”.

Discipline description: The subject of the discipline is studying of the economic principles of social industry development, reasoning of a choice made by housekeeping individuals in optimal usage of limited resources aimed at a complete meeting of growing people’s needs.

^ Aim of the course is in forming the system of knowledge about economic relations in the society, problems of effective usage of scarce resources, functioning of basic components of the economic system, development of students’ economic thinking and also preparation for the further study of other economic disciplines’ backgrounds and potential implementation of economic knowledge in future profession.


To know: basic stages of economic thinking development, problems and principles of functioning and development of social industry, property relations, economic systems,
commodity-money relations, basis of offer and demand in market economy, rational consumer choice, firm operation, market resources and market structures, principles of national economy functioning, monetary and financial system, forming of macroeconomic equilibrium and forms of macroeconomic instability, principles of economic state regulation and international economic relations. The theoretical material which is studied is divided into 16 topics.


^ Methods of Teaching: lectures, workshops, independent work.


Assessment Forms: current control in the form of module tests, shotgun quizes on a covered theoretical material, final control in the form of written exam.


Assessment Criteria:


Students’ assessment is brought about according to the Bologna System requirements. In all forms of work a student can get a maximum of 100 credits (points), 60 of which is obtained due to a current work in the semester and 40 can be got in the final control. The course is divided into 3 modules, each allows to obtain 1/3 of the total amount of credits in a current work. Students’ assessment is carried out on the basis of an average credit calculus separately in each module and exam with a following reassessment of these rates into a sum of obtained credits through special coefficients as a relation of a maximum amount of credits which can be obtained in a module or an exam to a maximum of the scale through which average rates are calculated. Average rates are calculated on the basis of the five-grade scale. For students’ assessment during the workshops a scale from 0 to 5 with a 0.5 division value is used. For a current module tests assessment the five-grade scale is also used, but the mark is given as the ration from the division of points, received by the student during the test, into the coefficient of recalculation which is defined as the ratio from the division of the amount of questions, that were set for the test, into 5. Writing of all tests is compulsory. A student gets a “0” if he/she hasn’t written a test. The calculus of an average rating for the current work in the semester is brought about due to the formula of arithmetic mean with a weight number 2 – for the module test; 1 or 0.5 (it depends on the wok done by the student o his/her activity) for workshop. The exam is assessed as the arithmetic mean separately for each question in the exam card. So the average rating is recalculated into the amount of points got at the exam following the procedure described.


Supportive Materials:


The program;

Textbooks and manuals in economic theory;

Legal documents justifying the current economic processes in the country;

Collected problems on micro- and macroeconomics;

Electronic materials which are given to the student at the beginning of the semester;

Tasks for the current assessment;

Examination cards.


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)


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.


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.


^ 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.

Methods of Teaching: lectures, workshops, independent work.

Elements of problematic lectures, individual tasks for independent work.

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:

Гихман И.И., Скороход А.В., Ядренко М.И. Теория вероятностей и математическая статистика (Theory of Probability and Mathematical Statistics). К., Выща школа, 1979.

Климов Г.П.. Теория вероятностей и математическая статистика (Theory of Probability and Mathematical Statistics)М., Издательство Московского университета, 1983.

Коваленко И.Н., Гнеденко Б.В. Теория вероятностей (Theory of Probabilities). К., Выща школа ,1990.

Розанов Ю.А. Теория вероятностей, случайные процессы и математическая статистика. (Theory of Probability (Theory of Probability, Casual Processes and Mathematic Statistics).М., Наука, 1985.

Крамер Г. Математические методы статистики (Mathematical Methods of Statistics). М., Мир, 1975.

Закс Ш. Теория статистических выводов (Theory of Statistical Conclusions). М., Мир,1975.

Кендалл М.Д., Стюарт А. Статистические выводы и связи (Statistical Conclusions and Correlation). М., Наука, 1973.

Боровков А.А. Математическая статистика (Mathematical Statistics) . М., Наука, 1984.

Леман Э. Проверка статистических гипотез (Examination of Statistical Hypotheses). М., Наука, 1979.

Бикел П., Доксам К. Математическая статистика (Mathematical Statistics). М., Финансы и статистика, 1983.

Ермаков С.М., Михайлов Г.А. Курс статистического моделирования (Course of Statistical Modelling). М., Наука, 1976.

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

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: 4th year, 8th 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:

Бусленко Н.П. Моделирование систем.(System modeling) - М.: Наука, 1978.

Бусленко Н.П. Метод статистического моделирования^ Method of statistical modeling) - M.: Статистика, 1970.

Полляк Ю.Г. Вероятностное моделирование на ЭВМ.( Probabilistic computer modeling) - М.: Статистика, 1971.

Снапелев Ю.М., Старосельский В.А. Моделирование и управление в сложных системах. (Modeling and complex systems administration) - M.: Советское радио, 1974.

Срагович В.Г. Теория адаптивных систем.(Adaptive system theory) - М.: Наука, 1976.

Варшавский В.И. Коллективное поведение автоматов. (Automatic machine cooperative behavior); - M.: Наука, 1973.

Клейнрок Л. Теория массового обслуживания.( Theory of waiting lines )M.: Машиностроение, 1979. 432 с.

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.

Вентцель Е.С. Теория вероятностей. ( Probability theory) M.: Наука, 1969. 576 с.

Вентцель Е.С. Исследование операций. ( Operations research) M.: Сов. радио, 1972. 552 с.

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.

Голенко Д.И. Моделирование и статистический анализ'псевдослучайных чисел на ЭВМ. - М.: Наука, 1965. - 228 с. Computer modeling and statistical analysis of pseudorandom numbers)

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)

Еельфанд, Фомин. Вариационное исчисление. (Variations calculus)

Эльсгольц. Дифференциальные уравнения и вариационное исчисление (Variations calculus and differential equation)

Еилл, Мюррей, Райт. Практическая оптимизация. (Practical optimization)

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:


Де Гроот М. Оптимальные статистические решения.( Optimal statistical decisions) M., Мир. 1974.

Ширяев А.Н. Статистический последовательный анализ. ( Statistical sequential analysis) М., Наука. 1969.

Чжоу Й., Роббинс X. Об оптимальных правилах остановки. ( About best stopping rules ) Математика. 9:3, 1965.

Чернов Г., Мозес Л. Элементарная теория статистических решений. ( The elementary theory of statistical decisions) M. 1962.

Ченцов Н.Н. Статистические решающие правила и оптимальные выводы. (Statistical decision rules and optimal methods) M., Наука, 1972.

Управление риском: Риск. Устойчивое развитие. ( Sustainable development) M., Наука, 2002.

Городецкий А.Я. Информационные системы. Вероятностные модели и статистические решения. ( Information systems. Probabilistic models and statistical decisions) СПб, изд-во СПбГПУ, 2003.

Supplementary Materials:

Гихман И.И., Скороход А.В., Ядренко М.И. Теория вероятностей и математическая статистика. (Probability theory and the mathematical statistics) К., Выща школа, 1979.

Крамер Г. Математические методы статистики. (Mathematical methods of statistics) M., Мир, 1975.

Леман Э. Проверка статистических гипотез.( Checkup of statistical hypotheses) M., Наука, 1979.

Бикел П., Доксам К. Математическая статистика. (The mathematical statistics ) M., Финансы и статистика, 1983.

Ермаков СМ., Михайлов Г.А. Курс статистического моделирования. (The course of statistical modeling) M., Наука, 1976.

Зельнер Ф. Байесовские методы в эконометрике. (Bayesian methods in econometrics) M.,: Статистика, 1980.

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.

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: 4th year, 7th 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