Discipline annotation “Systems Engineering”

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Discipline Objectives
2 hours of lectures and 2 hours of workshops.
Prior Requirements
Recommended Literature
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Course Aims
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Be familiarized
Discipline annotation
Tasks of the course
Numerical Methods in Information
Численные методы.
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Be familiarized with
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Methods of control
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Grades distribution
Recommended literature
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DISCIPLINE ANNOTATION

Mathematical Methods of Operations Research

Lecturer: Andriy Volodymyrovych Gakhov, PhD (Physics and Mathematics), Associate Professor.

The aim of studying a course in “Mathematical Methods of Operations Research (MMOR)” is providing students with theoretical knowledge and practical skills in applying operations research methods while preparing and crucial decision-making in business and industrial systems.

Discipline Objectives:

- to familiarize students with various areas and methodology of operations research;

- to teach future specialists to apply mathematical, i.e. quantitative methods both theoretically and practically for argumentation at the decision-making process in various branches of economy.

Knowledge, Skills and Abilities:

Abilities that supposed to be acquired by a student:

have a notion of:

applying the methods of operations research in solving new practical problems;

know:

theoretical foundations of the mathematical methods of operations research;
basic methods applied in solving problems within the operations research theory;
application areas and features of the mathematical methods of operations research.

be able to:

construct mathematical models on the basis of an economic problem statement;
select a class from a range of classes in the mathematical methods of operations research for set practical problems solving;
apply the mathematical methods of operations research;
analyze the obtained results and give their economic interpretation.

Course Duration and Activities:

A course in “Mathematical Methods of Operations Research” is delivered during the seventh semester according to the following schedule of classes per week (18 weeks in total):

2 hours of lectures and 2 hours of workshops.

During the lectures the following theoretical foundations of the discipline are given: basic concepts and definitions, theorems and algorithms of computational methods and examples of their application for solving certain classes of problems.

During the workshops students hone their problem-solving skills and come to grips with applying their theoretical knowledge for practical problems solving within the operations research theory.

Prior Requirements:

For mastering the course it is desirable that students should have basic knowledge in the following studies:

“Higher Mathematics” (chapters – “Linear Algebra”, “Analytic Geometry” and “Mathematical Analysis”);

“Discrete Mathematics”;

“Optimization Methods”;

“The Probability Theory”.

The total grade is the sum of points including the factors listed in the table below.

№	Factor	Commentary	%
1.	Handing in laboratory works and individual tasks before the deadline	For each additional week	± 10%
2.	Working activity at the lessons	Required minimum – one performance at the blackboard solving a problem	± 10%
3.	Attendance	Penalty points for missing more than 80% of classes	- 10 points
4.	Additional information	Solving problems of high complexity, learning extra materials etc.	+ 10%

At the examination students are given four tasks – two theoretical tasks based on the lecture material and two practical tasks. The maximum number of points for the right answer to the theoretical task is 5 points, for the practical one – 15 points. In total, the maximum number of points a student can get at the exam is 40 points.

The mark itself depends on the total number of points, it is given according to the following assessment scale:

Recommended Literature

1. Таха Х. А. Введение в исследование операций, 7-е издание. Пер. с англ. (Operations Research: An Introduction, 7^th Edition. Translated from English)– М.: Издательский дом «Вильямс», 2005 – 912с.

2. Конюховский П. В. Математические методы исследования операций в экономике (Mathematical Methods of Operations Research in Economics)– СПб.:Питер, 2000 – 208с.

3. Костюкова О.И. Исследование операций: Учеб. пособие для студ. (Operations Research: a Study Guide for Students) – Минск: БГУИР, 2003 – 94 с.

4. Волков И.К., Загоруйко Е.А. Исследование операций: Учеб. для вузов (Operations Research: a Study Guide for Higher Educational Establishments) / Под ред. B.C. Зарубина, А.П. Крищенко. – М.: Изд-во МГТУ им. Н.Э. Баумана, 2000. – 436 с.

5. Перельман М.А. Дослідження операцій в задачах автомобільного траспорту: Учб. посібник (Operations Research in Auto Traffic Problems: a Study Guide). – Х.: ІСДО, ХДАДТУ, 1995. – 135с.

6. Мулен Э. Теория игр с примерами из математической экономики: Пер. с франц. (The Game Theory with Examples from Mathematical Economics: Translated from French) – М.: Мир, 1985. – 200с.

Supplementary

1. Банди Б. Основы линейного программирования / Пер. с англ. (Basic Linear Programming / Translated from English) – М.: Радио и связь, 1989.

2. Схрейвер А. Теорія линейного и целочисленного программирования. (The Theory of Linear and Integer Programming) – М.: Мир, 1991.

3. Ху Т. Целочисленное программирование и потоки в сетях (Integer Programming and Network Dataflows). – М.: Мир, 1974.

4. Акулич И.Л. Математическое программирование в примерах и задачах: Учеб. пособие для студентов (Mathematical Programming. Examples and Problems: a Study Guide for Students). – Минск: Высшая школа, 1986.

5. Кремер Н.Ш. Исследование операций в экономике (Operations Research in Economics). – М., 1997.

Professional Applied Software Packages

TORA (ссылка скрыта)

DISCIPLINE ANNOTATION

The Control Theory

Lecturer: Vitaliy Ivanovych Iesin, PhD in Engineering, Associate Professor.

Prior Requirements: studying “The Control Theory” discipline requires preliminary knowledge of the following disciplines: “Higher Mathematics”, “Physics”, “Accuracy and Precision”, “Systems Analysis”, “Algorithmic Languages and Programming”, “Computer Basics”.

Course Aims: to lay theoretical foundations, to teach students to conduct control systems analysis and design, to familiarize them with control techniques of engineering systems and facilities, information technologies and projects.

Discipline Objectives: to provide students with theoretical knowledge and practical skills in applying control techniques of engineering systems and facilities, information technologies and projects.

Abilities that supposed to be acquired by a student:

KNOW:

basic concepts of the control theory;
methods for dynamic processes estimation (Kalman filter);
methods for classical variational calculus;
the Pontryagin maximum principle;
the dynamic programming method;
methods for information technology control;
theoretical foundations of project control.

BE ABLE TO:

analyze the controllability and observability of control systems;
study dynamic systems robustness;
analyze optimization problem-solving procedures;
solve optimization problems;
construct optimal control algorithms;
follow the world standards for information technology control;
create software designs.

Discipline Description: The optimal control theory. Information technology control. Project control.

Assessment Forms: two module papers and one test paper are to be held within the course of study, the final assessment is to be conducted in the form of an examination paper.

Supportive Materials:

1. Texts of lectures (printed and electronic variants).

2. Workshops schedule (printed and electronic variants).

3. Syllabus.

4. Tasks for the test paper and two module papers.

5. Examination questions.

Recommended Literature

Basic

1. Михайлов В. С. Теория управления (The Control Theory). — К.: Выща шк. Головное изд-во, 1988. — 312 с; 26 табл., 80 ил.

2. Основы теории управления : учеб. пособие (An Introduction to the Control Theory: a Study Guide) /Ю.Ю. Громов, В.О. Драчёв, О. Г. Иванова, Ю.С. Сербулов, К.А. Набатов. – Тамбов : Изд-во Тамб. гос.техн. ун-та, 2008. – 240 с.

3. Певзнер Л. Д. Теория систем управления (The Control Systems Theory). — М.: Издательство Московского государственного горного университета, 2002. — 472 с.

Supplementary

1. Александров А. Г. Оптимальные и адаптивные системы: Учеб. Пособие для вузов по спец. "Автоматика и упр. в техн. системах" (Optimal and Adaptive Systems: a Study Guide for Higher Educational Establishments Specialized in Automatation and Management in Engineering Systems). - М.: Высш.шк.,1989.-263 с.: ил.

2. Достаточно общая теория управления (Basic Control Theory)/ Постановочные материалы учебного курса факультета прикладной математики — процессов управления Санкт-Петербургского государственного университета (1997 — 2003 гг.)

3. Основы теории оптимального управления: Учеб. Пособие для экон. вузов (An Introduction to the Optimal Control Theory: Manual. A Study Guide for Economic Higher Educational Establishments) / В.Ф. Кротов, Б.А. Лагоша, С.М. Лобанов и др.; Под ред. В.Ф. Кротова.- М.: Высш.шк.,1990.- 430 с.: ил.

4. Сотсков А.И., Колесник Г.В. Оптимальное управление в примерах и задачах (Optimal Control. Examples and Problems). – М.: Российская экономическая школа, 2002 – 58 с.

5. Теория управления: Учебник (The Control Theory: Textbook)/ Под общ. ред. А. Л. Гапоненко, А. П. Панкрухина.- М.: Изд-во РАГС, 2003.-558с.

Information Resources

1. Справочник по прикладной статистике. В 2-х т. Т.2: Пер. с англ.(A Directory on Practical Statistics. 2-volumed Edition. Volume 2: Translated from English) / Под ред. Э. Ллойда, У. Ледермана, С.А. Айвазяна, Ю.Н. Тюрина. – М.: Финансы и статистика, 1990. – 526 с.: ил.

2. Справочник по теории автоматического управления (A Directory on the Automatic Control Theory) / Под ред. А.А. Красовского .- М.: Наука, Гл. ред физ.-мат. Лит., 1987.- 712 с.

3. CobiT 4.1 Российское издание. Методология. Цели контроля. Руководство по управлению. Модели зрелости процессов. (CobiT 4.1 Russian Edition. Methodology. Control Aims. Management Manual. Capability Maturity Model) - М.: Аудит и контроль информационных систем, 2008

4. С. Гузик Стандарт CobiT. Управление и аудит информационных технологий. Особенности проведения внешнего аудита ИТ. (CobiT Standard. Control and Audit in Information Technologies. External Audit Features in IT)/ nis.nnov.su/consulting/standart_cobit/

5. Ефремов В.С. Проектное управление: модели и методы принятия решений (Project Control: Decision-Making Models and Methods)/ ru/press/management/1998-6/11.shtml

DISCIPLINE ANNOTATION

Theory of Information

Lecturer. Leonid Stepanovych Soroka, Doctor of Science, Full Professor

Aim: To teach students to measure quantitative characteristic of the process of information transmission, storage and processing in data-transmission systems, as well as to make students master up-to-date information methods of signal transformation means analysis.

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

KNOW:

Mathematical models of signals, obstructions and communication channels.
The basics of the information interchange principle in the data-transmission systems.
Coordination of signals and channels characteristics principles under the condition of rigid constraint of a physical resource.
Methods of increasing the authenticity of the discrete information with the help of anti-noise coding and feedback data-transmission systems.

BE ABLE TO:

Calculate basic information characteristic of a message source.
Calculate basic information and engineering data of data-transmission systems.
Use up-to-date information methods of analyzing transmission and processing information means.
Calculate the coordination of the channel capacity and the informational capacity of the source.
Apply basic provisions of the theory of information to estimate the information

and engineering data of the elements of control and communication systems.

Implement of encoding and decoding appliances of anti-noise codes.

BE FAMILIARIZED:

With up-to-date directions of development of the theory of information and its practical usage. Description of the course:

Information, messages, signal, communication channel, communication system. Information transmission systems classification. Basic characteristic of the data-transmission system. Obstructions and distortions in communication channels. Amount of information and entropy. Entropy of a random experiment with equiprobable and unequal-probability consequences. Conditional entropy. Federated systems entropy. Discrete message source entropy. Entropy of a source of continuous messages. Excessiveness of the message sources. Determined and random signals (processes). Stationary random process. Elements of Furier spectral theory of transformation. Energy spectrum. Signal quantization by time. Kotelnykov theorem. Signal quantization by level. Correlation function of a stationary random process. Wiener-Khintchin theorem. Communication channels classification. A model of a continuous communication channel. A model of a discrete communication channel. Shannon theorem for a communication channel without interference. Effective encoding. Throughput capacity of a discrete communication channel. Shannon theorem for a channel with interference. Throughout capacity of a continuous communication channel. Coordination of message sources with communication channels. Means of increasing authenticity of information. Feedback data-transmission systems. Principles of anti-noise encoding. Anti-noise codes classification. Basic characteristic of anti-noise codes. Major anti-noise codes. Methods of making encoders and decoders of major anti-noise codes. Features of application of encoding and decoding anti-noise codes appliance.

Assessment Forms: monitoring of students' work is realized at workshops in the form of a quiz. Final assessment takes the form of an end-of-term test.

Supportive Materials:

"The Theory of Information" course, electronic version.
Power Point presentations "The Theory of Information"
Methodological instructions to workshops and self-study.

Recommended Literature:

Basic:

Сорока Л.С. Основи теорії інформації (Basics of the Theory of Information): Навчальний посібник. X.: ХНУ ім. В.Н. Каразіна, 2007.-264 с
Краснобаев В.А., Фурман LA. Теорія інформації (The Theory of Information): Підручник для ВНЗ / М-во освіти і науки України. - К., 2005. - 160 с
Сорока Л.С. Основы теории минимально-избыточных сигналов. Математические методы и средства обработки (Basics of the Theory of Minimally-Excess Signals): Монография.- X.: МОУ ОНИИ ВС, 2005.- 280 с.

Supplementary

A.H. Колмогоров Избранные труды. III том: Теория информации и теория алгоритмов (The Theory of Information and the Theory of Algorithms) M., "Наука", 1987, - 303 с.
Блейхут Р. Теория и практика кодов, контролирующих ошибки (Theory and Practice of Mistakes-Controlling Codes) / Пер. с англ. - M.: Мир, 1986. - 576 c.

Кузьмин И.В. Основы теории информации и кодирования (Basics of the
Theory of Information and Encoding)/ И.В. Кузьмин, В.А. Кедрус - К.: Вища школа, 1986. - 238 с.
Лосев Ю.И. Основы теории передачи данных. (Basics of the Theory of Data Transmission.: ВИРТА, 1992.-233 с
Никитин Г. И. Помехоустойчивые циклические коды: Учеб. пособие. (Anti-noise Cyclic Coding: Turorial)- Санкт-Петербург. – СП б ГУАП, 2003. -33 с.
Питерсон У. Коды, исправляющие ошибки (Mistakes Correcting Codes)/ У. Питерсон, Э. Уэлдон.: Пер. с англ. - М.: Мир, 1976. - 600 с.
Шульгин В.И. Основы теории передачи информации. Ч. 2. Помехоустойчивое кодирование: Учеб. пособие. (Basics of the Information Transmission Theory. Part 2. Anti-noise Coding: Tutorial) - Харьков: Нац. аэрокосм, ун-т «Харьк. авиац. институт», 2003. - 87 с.

DISCIPLINE ANNOTATION

Numerical Methods in Information

Lecturer: A. V. Hakhov, PhD , Associate Professor

Aim of the course: to form theoretical knowledge and practical skills of using numerical methods in solving various applied problems, as well as to teach students to assess accuracy of the results. Tasks of the course:

Familiarization with various directions and methodology of calculus mathematics.
Teaching future specialists theory and practice of implementation of numerical
methods and assessing final results' accuracy.

List of obtained knowledge and skills

Following the completion of the course students must:

Have a notion about:

- ways of solving new applied problems with the help of computer-based calculations.

Know:

-theoretical basis for numerical methods,

-basic methods (method classes) and algorithms used in solving applied problems.

-areas and peculiarities of using numerical methods in computer-based calculations.

Be able to:

-choose computational approach class to numerically solve assigned problem

-use numerical methods

-analyze obtained data and assess their accuracy.

Duration and activities

The course of Numerical Methods in Information is taught in semester 5 by the following schedule of teacher-guided classes per week (16 weeks): 2 hours of lectures and 2 hours of teacher-guided classes.

During the lectures the theoretical basis for the course is taught: basic notions and definitions, theorems and algorithms of computational approach, examples of their

application to solve certain classes of problems are provided.

During the teacher-guided classes students train solving algorithms and get to know the peculiarities of application of the theoretical knowledge of numerical realization of the algorithms and solving practical tasks they have obtained.

Preliminary knowledge

To successfully master the course students must have basic knowledge of the following courses:

"Higher Mathematics" (sections - "Linear Algebra", "Analytic Geometry", "Mathematical Analysis")

"Object-oriented Programming"

Students get a maximum of 40 points for the final test. The grade is given depending on the total sum of points according to the following scale:

Basic literature:

B.M. Вержбицкий Численные методы: Линейная алгебра и нелинейные уравнения: Учебное пособие для вузов. (Numerical Methods: Linear Algebra and Non-Linear Equations)- M.: Высшая школа , 2000 - 266 с.

H.C. Бахвалов, Н.П. Жидков, Г.М. Кобельков Численные методы. (Numerical Methods)- M.: БИНОМ, 2008. - 640 с.

В.М. Вержбицкий Основы численных методов: Учеб. пособие для вузов.

(Basic Principles of Numerical Methods) - M.: Высшая школа, 2002. - 840 с. B.M. Вержбицкий Численные методы. Математический анализ и

обыкновенные дифференциальные уравнения. (Numerical Methods.

Mathematical Analysis and Ordinary Differential Equations) - M. Высшая

школа, 2001.-382 с.

Дж. Форсайт, К. Моллер Численное решение систем линейных алгебраических уравнений. (Numerical Solution of a System of Linear Equations)- M.: Мир, 1969. - 166 с.

Сборник задач (Collected problems) под ред. П.И. Монастырного. - М.: Наука,

1994.

Supplementary literature

Д.К. Фадеев, В.Н. Фадеева Вычислительные методы линейной алгебры. (Computational Approaches to Linear Algebra)- М.:Лань, 2002. - 736 с.

Ч. Лоусон, Р. Хенсон Численное решение задач метода наименьших квадратов. (Numerical Way of Solving Problems on Technique Least-Squares Method)- M.: Наука, 1986. - 232 с.

Дж. Ортега, В. Рейнболдт Итерационные методы решения нелинейных систем уравнений со многими неизвестными. (Iterative Methods of Solving Non-Linear Equation Systems with Many Unknown Quantities)- M.: Мир, 1975.

A.A. Самарский, А.В. Гулин Численные методы. (Numerical Methods) - М.:Наука, 1978

Professional application software package

Scilab (ссылка скрыта)

DISCIPLINE ANNOTATION

Principles of the Theory of Operating Complex Systems

Lecturer: Volodymyr Mykhailovych Kuklin, PhD, Full Professor Aim and tasks of the course

Aim of the course: to form basic notions and categories of the theory of electronics reliability, its service properties, principles of index choice and grounds for necessary reliability, reliability calculation methods, ensuring the necessary level of reliability of such appliance, basic principles of the theory of operation, essence of the main operating actions: technical service, repairs, diagnosis supervision, material and technical support. To teach basic methods of planning technical service. To give practical skills of calculating basic indicators of reliability, control's influence on reliability indicators, analyzing and interpretation of the results of planning technical service and reliability calculations.

Following the completion of the course students must:

KNOW:

Basic notions, terms, and the reliability indicators system of electronics.

Basic models of lifetime distribution and recovery time of electronics.

Methodological principles of calculation and ensuring electronics reliability.

Principles of choosing indicators and grounds for necessary reliability of electronics.

Kinds of technical service and their characteristic, methods of planning and operating

this service.

Principles of the theory of electronics technical state and diagnostics control.

Be able to:

Calculate faults of electronic elements.

Calculate single and integrated reliability index of electronics.

Define assessment of reliability index of redundant systems with updating.

Analyze control influence on electronics reliability index.

Build network models of technical service and analyze them.

Be familiarized with:

Electronics reliability impact factors.

List of preliminary courses:

The "Principles of the Theory of Operating Complex Systems" course is taught in semester 7 and consists of lectures, workshops and independent work. All technical equipment is provided.

The course study grounds on theoretical and practical knowledge obtained by students from the following courses: Physics, Higher Mathematics, Probability Theory and Mathematical Statistics, Circuit Theory and Magnetic Theory, Electronics and Microcircuitry, Systems Analysis, Complex Compute Network Components.

DISCIPLINE ANNOTATION

Introduction to the Major

Lecturer: Associate Professor of the chairs of Theoretical and Applied Systems Engineering, PhD, Sergii Ihorovych Shmatkov

Aims and tasks of the course Aim of the course

To give students general idea of the major, concerning basic principles of informatics and systems analysis, creation history and structure principles of computer systems and networks.

Tasks of the course

Following the completion of the course students must:

Know:

basic notions and terms of informatics and the theory of complex systems.
creation history of the computer and computer networks
computer views of information

- hardware tools structure and software

basic principles of computer network structure
networks standardization methods

Be able to:

classify existing and perspective complex systems
use the rules of binary arithmetic

-analyze structure and principles of computer systems

Syllabus of the course Module 1

Topic 1. Basic principles of informatics

Topic 2. Basic principles of systems analysis

Topic 3. Basic principles of computer systems structure

Module 2

Topic 4. Evolution of computer networks

Topic 5. General principles of computer systems structure

Topic 6. Network standardization

Methods of instruction

Basic material of the course is introduces to students in the form of lectures. Much attention is paid to explaining physical sense of the processes under study. Visual methods are used via multimedia equipment. Laboratory work contribute to deepening the knowledge obtained at the lectures.

Methods of control

Students' work is controlled at workshops and during laboratory work in the form of tests. The final control is presented if the form of a test and an examination.

Recommended literature

Basic

Г.Н. Жолткевич и др. Інформатика для инженеров. (Informatics for Engineers) - X.: Издательство «Факт», 2005, - 423 с.
Ф.И. Перегудов, Ф.П.Тарасенко. Введение в системный анализ. (Introduction to the Systems Analysis) - M.: «Высшая школа», 1989, - 367 с.
В.Г.Олифер, Н.А.Олифер. Компьютерные сети. (Computer Networks) - Питер, 2008, - 957 с.

Supplementary

В.А.Краснобаєв та ін. Методологія системного аналізу технічних систем. (Methodology of Systems Analysis of Engineering Systems ) - X.: «Факт», 2009, - 297 с.
В.В.Корнеев. Вычислительные системы. (Computer Systems)- M.: «Гелиос», 2004,-510 с.

DISCIPLINE ANNOTATION

Systems of Artificial Intelligence

Lecturer: Associate Professor of the chairs of Theoretical and Applied Systems Engineering, PhD, Sergii Ihorovych Shmatkov

Aim of the course.

To teach students to use methods of artificial intelligence to analyze complex systems

Tasks of the course

Following the completion of the course students must: Know:

numeration of phrases and numeration of objects
search for solutions methods
principles of production systems
methods of representing knowledge
principles of expert systems structure
structure of neural networks and their types
features of genetic algorithms and artificial life algorithms.

Be able to:

design control algorithms based on predicate numeration
use systems based on rules of design and modification without knowledge
analyze structure and algorithms of neural networks instruction
solve problems of non-informed and heuristic search
use heuristic methods of the "ant algorithm" type for solving optimization tasks.

Syllabus of the course

Module 1

Topic 1. Introduction to artificial intelligence

Topic 2. Search in the space of the states

Module 2.

Topic 3. Knowledge presentation

Topic 4. Machine learning

Methods of instruction

Basic material of the course is introduces to students in the form of lectures. Much attention is paid to explaining physical sense of the processes under study. Visual methods are used via multimedia equipment. Laboratory work contribute to deepening the knowledge obtained at the lectures.

Methods of control

Students' work is controlled at workshops and during laboratory work in the form of tests. The final control is presented if the form of a test and an examination.

Grades distribution

Current test and individual student work				Final control		Total grade
Module I Module II
T1	T2	T3	T4	40	100
15	15	15	15

T1, T2, - topics of the modules.

Recommended literature

Basic

Д.Ф.Люгер. Искусственный интеллект. (Artificial Intelligence) - Вильяме, 2005, 863 c.
М.Т.Джонс. Программирование искусственного интеллекта в приложениях. (Artificial Intelligence Programming in Applications)- M.: ДМК, 2004, - 311 с

Supplementary

С.Рассел, П.Норвиг. Искусственный интеллект. (Artificial Intelligence)- Вильямс, 2006, - 1407 с.
А.Эндрю. Искусственный интеллект.(Artificial Intelligence) - М.: Мир, 1995,-221 с.
Б.Уитби. Искусственный интеллект. (Artificial Intelligence)- M,: Гранд, 2004,-221 с.

DISCIPLINE ANNOTATION

Application Packages

Lecturer: Associate Professor of the chairs of Theoretical and Applied Systems Engineering, PhD, Dmytro Oleksiiovych Bulavin

Aims and tasks of the course

Modern computer mathematics offers a wide range of integrated software systems and program packages to automatize mathematical calculations: Eureka, Gauss, TK Solver!, MatLab, Mathcad, Mathematica, Maple V and others.

Aim of the course

is to make students master theoretical and practical basic principles of working with

application packages, software realization of solvong a range of mathematical tasks.

Tasks of the course:

to learn basic terms and notions of application packages Mathcad, MatLab
to introduce students to the basic principles of representing information of various origin and principles of data entry in Mathcad, MatLab
to introduce students to the features of solving problems in vector and matrix algebra
to examine basic structure principles of two-dimensional and three-dimensional graphs and further work with them.
to give practical methods of solving simultaneous linear equations, approximation, optimization and other problems

Following the completion of the course a student must

Know:

basic terms and notions of application packages Mathcad, MatLab;
basic functions of working with vectors and matrixes
principles of building two-dimensional and three-dimensional graphs
algorithms of solving simultaneous linear equations
methods of solving approximation and optimization problems
main principles of working with basic toolboxes (Optimization, Simulink).

Be able to:

- solve vector and matrix algebra problems

-build two-dimensional and three-dimensional graphs

solve simultaneous linear equations
-solve approximation and optimization problems
solve problems with the help of basic toolboxes(Optimization, Simulink).

Methods of instruction

During the lectures and workshops of the course a complex of technical facilities is used, particularly computer video. Course books and manuals are provided.

Laboratory work is done in a computer class using modeling application package MathCAD, MatLab, relevant tasks and methodological recommendations on their fulfilment are provided.

Control tasks cover all main questions that define to what extent students are ready to solve practical problems.

Methods of control

Control of course mastering is performed in the way of:

current control during workshops
laboratory reports
tests after after each principle part of the course
written final control test

Grades Distribution.

Current test and individual work											Final semester control	Total grade
Module 1											30	100
T1	T2	T3	T4
20	20	20	10

				Module 2			Module 3
				T5	T6	T7	T8	T9	T10	T11
				10	10	10	10	10	10	10

Module 1 topics are tested by workshops #1, 2, 3 and the final test.

Module 2 topics are tested by workshops #4, 5 laboratory reports #1,2 and test #3

Module 3 topics are tested by laboratory reports #3, 4

Minima] points that a student should gain to accomplish their module: Module 1-100 points Module 2, 3 - 100 points

A student only is allowed to take the final semester test if their laboratory reports have been accepted and he has gained at least 30 points for current control.

Recommended Literature

Дьяконов В.П. Справочник по Mathcad PLUS 6.0 PRO. (Mathcad PLUS 6.0 PRO Manual)- M.: «CK Пресс», 1997. - 336 с.
Дьяконов В. П. Справочник по Mathcad 7 Pro. (Mathcad 7 Pro. Manual) M. : «CK Прогресс», 1998
Дьяконов В.П., Абраменкова И.В. Mathcad 8 PRO в математике, физике и в Internet. (Mathcad 8 PRO in Mathematics, Physics and the Internet)- M.: «Нолидж», 1999.-512 c.
Дьяконов В. Mathcad 8/2000. Специальный справочник.( Mathcad 8/2000. Special Manual) - СПб: Питер, 2001. - 592 с.
Зимина О.В., Кириллов А.И., Сальникова Т.А. Высшая математика. (Higher Mathematics)- M.: Физико-математическая литература, 2000. - 368 с.
Мироненко Е.С. Высшая математика. Методические указания и контрольные задания для студентов-заочников инженерных специальностей вузов. (Higher Mathematics. Methodological Instruction and Tests for Correspondence Students of Engineering)- M.: Высшая школа, 1998. - 110 с.
Очков В.Ф. Mathcad PLUS 6.0 для инженеров и студентов. (Mathcad PLUS 6.0 for Engineers and Students)- M.: TOO фирма «КомпьютерПресс», 1996. – 238 с.
Плис А.И., Сливина Н.А. Mathcad: математический практикум для экономистов и инженеров: Учебное пособие. (Mathcad: Mathematical Practical Work for Economists and Engineers: Manual) - M.: Финансы и статистика, 1999. - 656 с.
Райхмист Р.Б. Графики функций: задачи и упражнения. (Function Graphs: Tasks and Exercises) - M.: Школа-Пресс, 1997. - 384 с.
Mathcad 6.0 PLUS . Финансовые, инженерные и научные расчеты в среде Windows 95. (Mathcad 6.0 PLUS Financial, Engineering and Scientific Calculation in Windows 95 Environment) - M.: Информационно-издательский дом «Филинъ», 1997. - 712 с.
Дьяконов В.П. MATLAB 6. Учебный курс .( MATLAB 6. Tutorial) - СПб.: Питер, 2001.-592 с.

Баженов В.А., Дащенко А.Ф., Коломиец Л.В., Оробей В.Ф. Строительная механика. Специальный курс. Применение метода граничных элементов. (Structural Mechanics. Special Course. Boundary Items Method Application) - Одесса: Астропринт, 2001. - 288 с.

Строительная механика. Динамика и устойчивость сооружений (Structural Mechanics. Structure Dynamics and Stability )/ Под ред. А.Ф. Смирнова. - М. : Стройиздат, 1984.-415 с.
Турчак Л.И. Основы численных методов. (Basics of Numerical Method) - M.: Наука, 1987.-320 с.
Мэтьюз Дж.Г., Финк К.Д. Численные методы. Использование MATLAB. (Numerical Methods. MATLAB Application. )Пер. с англ. - М.: Изд. Дом «Вильяме», 2001. - 720 с.
Дьяконов В., Круглов В. Математические пакеты расширения MATLAB. Специальный справочник. (MATLAB Mathematics Bump Packs ) - СПб.: Питер, 2001.-480 с.

DISCIPLINE ANNOTATION

Optoinformatics

Lecturer: Grygorii Mykolaiovych Dolia, Full Professor, Doctor of Science. Prelims:

Prior requirements:

Aim of the course is to teach students basic principles of photonics and optical technologies in informatics, as well as to train skills of calculating typical optoelectronic device characteristic.

Tasks of the course:

to introduce students to the principles of the structure of optoelectronic devices used in computer engineering
to form systematic conception of optical and optoelectronic devices of information processing
to practice engineering and calculation of basic setting of computer optical and optoelectronic devices.

Following the completion of the course a student must:

Know:

basic characteristic, structure and functioning principles of laser and optoelectronic computer devices
operating rules and safety measures at using laser and optoelectronic computer devices
Main areas of improvement, modernization and perspective development of laser
and optoelectronic computer devices.
capacity limiting factors of the above mentioned systems.

Be able to:

- ground and calculate main technical characteristics of laser and optoelectronic computer devices

- individually master equipment, study the structure of up-to-date, updated and perspective laser and optoelectronic computer devices

troubleshoot elements and devices of optoelectronic systems during operation, choose best performance mode.
Assess and analyze the possibility of using optical systems under different conditions.

Course description

Optical radiation receivers. Elements of laser-building. Laser radiation generation.

Optical modulators. Optical peripheral units of a PC. Optical disk storage devices. Holographic storage units. Analogue optical computers. Digital optical computers.

Supportive materials

Доля Г.Н. Чудовская Е.С. Методические материалы по учебной дисциплине «Оптоинформатика». Часть 1. «Основы фотоники». Харьков - 2008.
Доля Г.Н. Чудовская Е.С. Методические материалы по учебной дисциплине «Оптоинформатика». Часть 2. «Оптические технологии в вычислительной технике». Харьков - 2008

Recommended literature

Basic

Справочник по лазерной технике. (Laser Technology Reference Book) Киев, „Техника", 1978.
Г. Боухьюз и др. Оптические дисковые системы. (Optical Disc Systems) - М., Радио и связь, 1991.
Акаев А.А., Майоров С.А. Оптические методы обработки информации. (Optical Methods of Information Processing)- M.: Высшая школа, 1988.
Д. Гринфилд. Оптические сети. (Optical Networks)- К., ООО «ТИД ДС», 2002
М.Янг. Оптика и лазеры, включая волоконную оптику и оптические волноводы (Optics and Lasers, Including Fiber Optics and Optical Waveguides): Пер. с англ.- М.: Мир, 2005.

Supplementary

1.Новые физические принципы оптической обработки информации (New Phisical Principles of Optical Information Processing)/ Сборник статей под ред. С.А. Ахманова, 1990.

2.Р. Фриман. Волоконно- оптические систмы связи.(РіЬег-Оргісз Communication Systems) — М., Техносфера. 2004

Оптическая голография (Optical Holography) / Под ред. Г.Колфилда. - М., Мир, 1982
Справочник по лазерам (Lasers Reference Book)/ Под ред. A.M. Прохорова. В 2-х томах. - М. Сов радио, 1978.

DISCIPLINE ANNOTATION

DIRECTION “SYSTEN INGENEERING”

Graduate Level

Patents and Intellectual Property Rights

Lecturer: Head of the Laboratory of System Engineering, Junior Member of the Department Artyukh О.А.

Aim:

To make students acquainted with basic notions of patent system, main objects and subjects of intellectual and industrial property, achieve skills of defining the technology level of on the basis of patent and technical information, achieve skills of patent work and certification.

Tasks:

Following the completion of the course a student must:

know:

classification of person’s rights which are part of industrial property, normative and legislative basis in the sphere of industrial property, main notion of objects and subjects of industrial property as parts of patent system, form of search of scientific and technical and patent information, stages of patent examining, order and methods of writing application for a patent, documents for objects of industrial property, system of international classification of objects of industrial property.

Be able to:

use normative and legislative basis in the sphere of industrial property and patent law, do patent search and write a report on patent research, write license agreements about the conveyance of industrial property and application for a title of protection.

Methods of teaching

The material is mostly given at lectures. The great attention at lectures is paid to all latest changes in legislation concerning protection of intellectual and industrial property. Multimedia equipment ensures the visuality of teaching.

Practical skills promote extending of knowledge obtained at lectures and achieving practical skills.

Assessment Forms

Assessment is realized at workshops via tests. Final assessment is realized via final written test.

Recommended Literature:

Basic

Кузнєцов Ю.М. Патентознавство та авторське право (Patents and Copyright). – Кондор, 2004, - 428с.
Дахно І.І. Право інтелектуальної власності (Intellectual Property Right). – Центр навчальної літератури, 2006, - 278с.
Патентные исследованя: Часть 1. Работа с патентной информацией (Patent Research. Part 1. Work with Patent Information) (методическое пособие)/ Под ред. Шаншурова Г.А. – Новосибирск: НГТУ, 2003.
Шаншуров Г.А. Патентные исследованя: Часть 2. Правила проведения патентных исследований (Patent Research. Part 2. Rules of Patent Research) (методическое пособие). - Новосибирск: НГТУ, 2003.

DISCIPLINE ANNOTATION

The Decision-Making Theory at Complex Computer Systems Management

Lecturer: Iuriy Ivanovych Losev, Full Professor, D.Sc. (Engineering).

Discipline Aims: To give the students the basic knowledge on decision-making methods while managing complex computer systems, methods for quality evaluation of the decisions made and development forecasting. Teach the basic decision-making techniques under uncertainty, choice of optimal alternatives in a fuzzy environment.

Discipline Objective:

Following the completion of the course students must:

know:

Characteristics of the computer management system. Network performance criteria and the impact of the network management system on them. Methodological basis of the decision-making process in network management. Characteristics of the preparation and decision-making processes. The conceptual model of decision-making in network management. The decision-making methods in network management. The situation assessment method. Situation planning and management. Merits and consequences evaluation techniques of the decision-making process in network management. Quality evaluation of the decisions made. Decision-making under uncertainty. Choice of optimal alternatives in a fuzzy environment. The basic functional connections in the theory of utility. Using artificial intelligence in network management. Simulation techniques for the preparation and decision-making processes in network management.

be able to:

Evaluate network performance and management system. Specify such network features as operativeness, capability and optimality. Consider the criterion for randomness, ambiguity of information at the decision-making process. Define the conceptual model of decision-making and its separate stages. Identify network elements connectivity at the decision-making process on network management, evaluate the merits of decision-making process and the decision-implementation consequences. Develop a frame-based knowledge model for an expert system used in network management.

Program of the course

Module 1 Phases of creation of computerized systems.

Topic 1. General information on projecting of management systems.

Topic 2. Content of the project documentation

Topic 3. Formulation of estimation at projecting of complex computerized systems..

Module 2. Implementation, exploitation and accompaniment of management systems.

Topic 4. Implementation, exploitation and accompaniment of management systems.

Topic 5. Computerizing of project works.

Topic 6. Management project on creation of computerized systems.

Training methods

Training of students is conducted trough lectures, at which a student may find out basic moments on organization and fulfillment of works, connected with projecting of management systems,and also with fundamental project documents. Availability of teaching is provided with multimedia equipment. Knowledge on projecting methods, skills in formulating of fundamental project documents, and fulfillment of project works are conducted at laboratory works. Knowledge and skills in formulating of project documents is provided during fulfillment of project work.

Control methods

Control is conducted trough concentration of attention of students on formulating of control questions and topic of a lecture.

The same is done during laboratory works.

Also the control is provided in accordance with explaining note, quality of fulfillment of illustrative material and skills to explain project decisions.

Discipline Description: Computer-aided systems management analysis. Methodological basis of the decision-making theory. The decision-making methods in network management. Decision-making under uncertainty. Network management using artificial intelligence.

Assessment Forms: Student performance in the discipline is assessed during workshops and laboratory experiments by means of shotgun quizzes. The final assessment is held by means of the course project and during an examination.

Supportive Materials

1. Multimedia equipment.

3. Slides. Presentation of “The Decision-Making Theory at Complex Computer Systems Management” discipline.

Recommended Literature

1. Проектирование и расчет структурированных кабельных систем и их компонентов( Projecting and evaluation of structured cable systems and their components), Семенов А.Б., изд. Компания АйТи, 2003г.

2. Проектирование и техническая эксплуатация систем передачи(Projecting and technical exploitation of transmission systems), Берганов И.Р., Гордиенко В.Н., Крухмалев В.В., изд. Москва, «Радио и связь», 1989г.

3. Проектирование сетей связи (Projecting of connection networks). Справочник, Р.Бесслер, А. Дойч, изд. Москва, «Радио и связь, 1988г.

DISCIPLINE ANNOTATION

Technologies of elaboration of corporative systems

Lecturer: senior lecturer of the department of theoretical and applied system technique, candidate of technical sciences,senior lecturer Y.E. Duravkin

Aim and Tasks of the Discipline

Aim Creation of knowledge, ambitions and skills, which permit to rule the projects effectively in different branches of economy; provide the achievement of the results, which are determined in the project by structure and volume of work, time, number of members.

Task Introduction to problems of project management; study of methodology of elaboration and project management; study of abilities of project management methodology and its use in different banches of economy; study of informational technologies of project management using modern software.

Following the completion of the course students must

:

know

- stages of life cycle

- UML language of modelling- methodology of valuation of time and labour intensity of fulfillment

- methods of valuation of risks during elaboration

Be able to:

-perform the specification

- project the elaboration according to the life cycle.

- perform the evaluation of technical and economical indices during the elaboration

Subject Course

Module 1. General problems of the process of elaboration of corporative informational systems

Topic 1. Informational technologies: condition, role in business and tendencies of development.

Topic 2. problems of integration of information systems of the enterprise.

Topic 3. Method of construction of distributed systems

Module 2. Технології Technologies of Microsoft

Topic 4. Platform Microsoft .Net. Architecture, examination of possibilities

Topic5. Methods of Web-applications elaboration on the basis of the technology ASP.NET.

Recommended literature

Basic

1. Вендров А.М. Проектирование программного обеспечения экономических информационных систем ( Software Projecting of Informational Systems) М: «Финансы и статистика», 2000

2. Проектирование информационных систем (Projecting of Informational Systems) М: «КомпьютерПресс», №9, 2001 Колтунова Е.

3. Буч Г., Рамбо Д., Джекобсон А. Язык UML. Руководство пользователя:(UML Language. User`s Guide) Пер. с англ.

М.: ДМК, 2000

4. Смирнова Г.Н., Сорокин А.А., Тельнов Ю.Ф. Проектирование экономических информационных систем (Projecting of economic informational systems) М.: Финансы и статистика, 2002

5. Кондратьев В.В., Краснова В.Б. Модульная программа для менеджеров. Реструктуризация управления компанией (Modular program for managers. Restructing of company management) М.: Инфра-М, 2000

DISCIPLINE ANNOTATION

Management of Elaboration of Program Projects

Lecturer: senior lecturer of the department of theoretical and applied system technique, candidate of technical sciences,senior lecturer Y.E. Duravkin

Course description

Name of Indices	Branch of knowledge; training; educational level	Course Description
		Full-time course	Correspondence course
Credits – 4	Branch of knowledge 050201 «Automatics and management» (code and name)	Normative(by election)
	Training 6.050201 «System engineering» (code and name)
Modules – 3	Speciality (profession): 8.091401 «Systems of management and automatics»	Year of training:
		5-th	5-th
Individual Research Work ___________ (name)		Semester
Total number of hours - 144		9-th	9-th
		Lectures
Week hours for full-time course: lectures – 4 individual work -4	Educational level Master	36 h.
		Practical, seminars
		36 h
		Laboratory
		h	h.
		Individual work
		72 h
		ІНДЗ: год.
		Control: examination

Aim and Tasks of the Discipline

Aim Creation of knowledge, ambitions and skills, which permit to rule the projects effectively in different branches of economy;, provide the achievement of the results, which are determined in the project by structure and volume of work, time, number of members.

Tasks Introduction to problems of project management; study of methodology of elaboration and project management; study of abilities of project management methodology and its use in different banches of economy; study of informational technologies of project management using modern software.

Following the completion of the course students must

know:

- stages of life cycle

- UML language of modelling

- methodology of valuation of time and labour intensity of fulfillment

- methods of valuation of risks during elaboration

Be able to:

-perform the specification

- project the elaboration according to the life cycle.

- perform the evaluation of technical and economical indices during the elaboration

Recommended literature

Basic

1. Вендров А.М. Проектирование программного обеспечения экономических информационных систем ( Software Projecting of Informational Systems) М: «Финансы и статистика», 2000

2. Проектирование информационных систем . (Projecting of Informational Systems) М: «КомпьютерПресс», №9, 2001 Колтунова Е.

3. Буч Г., Рамбо Д., Джекобсон А. Язык UML. Руководство пользователя: :(UML Language. User`s Guide)Пер. с англ.

М.: ДМК, 2000

4. Смирнова Г.Н., Сорокин А.А., Тельнов Ю.Ф. Проектирование экономических информационных систем (Projecting of economic informational systems) М.: Финансы и статистика, 2002

5. Кондратьев В.В., Краснова В.Б. Модульная программа для менеджеров. Реструктуризация управления компанией (Modular program for managers. Restructing of company management) М.: Инфра-М, 2000

6. Калянов Г.Н. Структурный системный аналіз (Structural system analysis) М.: Лори, 1997

7. Марка Д.А., МакГоуэн К. SADT — методология структурного анализа и проектирования ( Methodology of structural analysis and projecting)М.: Метатехнология, 1993

8. Буч Г. Объектно-ориентированное проектирование с примерами применения (Object oriented projecting with examples of use) М.: Конкорд, 1992

Supportive Materials

Грекул В.И., Денищенко Г.Н., Коровкина Н.Л. Проектирование информационных систем ( Projecting of informational systems) Интернет-университет информационных технологий - ИНТУИТ.ру, 2008
Данилин А., Слюсаренко А. Архитектура и стратегия. "Инь" и "янь" информационных технологий (Architecture and Strategy) Интернет-университет информационных технологий - ИНТУИТ.ру, 2005

Informational Sources

ссылка скрыта

DISCIPLINE ANNOTATION

Methodology and organization of research work

Lecturer: senior lecturer of the department of theoretical and applied system technique, candidate of technical sciences S. I Shmatkov.,

Blog

Discipline annotation “Systems Engineering”