ceie undergraduate programme obligatory courses – … · theorem, passive two-terminal...

CEIE UNDERGRADUATE PROGRAMME

OBLIGATORY COURSES – SUBJECT SYLLABI

Undergaduate obligatory courses - subject syllabi

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Subject: Algebra and Analytic Geometry Code: CEIE_S1_11

Level of studies: BSc Semester(s): 1,2

Teacher: dr. Iwona Nowak

Pre-requisite qualification:

The knowledge and skills (on average level) in mathematics on the secondary school level are required

Course objectives:

The aim of education is efficient use of the basic mathematical apparatus (related to the com-plex numbers, matrix and vector calculus, vector spaces and linear transformations) necessary for the further study, the ability to formulate problems and their description in the language of algebra and interpretation of results.

Teaching modes and hours (Lecture/Seminar/Class/Project/Laboratory):

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Syllabus description:

Lectures:

Complex Numbers (def., operations in C, polar form, roots of complex numbers, exponential form); Polynominals; Matrices and Determinants; System of Linear Equations (Gaussian Elimi-nation, Cramer Rule, homogenous systems, rank, Kronecer-Capelli Theorem,); Analytical Ge-ometry (calculus of vectors, Line and plane In 3D space, curves of third degree); Vector Spaces (def.+examples, subspaces of vector space, spanning sets, linear dependence and independ-ence, basis and dimension); Inner Product Spaces (def., length and distance in inner product spaces, complex vector space, complex inner product space, angle and orthogonality, orthogo-nal basis, the Gram-Schmith orthonormalization process); Linear Transformations (transfor-mation defined by matrix, kernel and range, standard matrix, composition of transformations, inverse transformation, matrix of nonstandard basis, transition matrix and similarity); Eigen-values and Eigenvectors (def., eigenspases, diagonalization, orthogonal diagonalization, Jordan canonical form)

Classes:

During classes students solve practical tasks related to the topic introduced in the lecture.

References:

• Larson, Edwards: Elementary Linear Algebra, D.C. Heath and Company, 1991. • Fraleigh, Beauregard: Linear Algebra, Addison-Wesley Publishing Company,1999


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Number of ECTS credits: 5 + 4 = 9

Subject: Calculus and Differential Equations Code: CEIE_S1_12


Teacher: dr. Ewa Łobos


Mathematics from the secondary school (average knowledge is sufficient).

Course objectives:

The objective of the course is to give theoretical bases of mathematical analysis and its applica-tions. Students should be able to formulate problems, describe them in the language of mathe-matics, and interpret obtained results.


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Lectures

The real number system – the real line – the absolute value.

The concept of a function; examples. Metric on a set – metric spaces. One-to-one onto functions; composite functions, inverse functions. Review of elementary functions; hyperbolic and inverse trigonometric functions.

Sequences (of real numbers, complex numbers, plane points). Convergence in a metric space. Properties of convergent sequences. Limits of some numerical sequences.

The limit of a function defined on a metric space (real- and complex-valued functions of one or several variables). Properties of limits. Some important limits. Continuity – discontinuity – properties of continuous functions. Asymptotes.

The derivative of a function – definition, interpretations. Tangent line. Differentiation formulas and rules. Higher derivatives. Differentials – definition, applications. Parametric equations, the derivative of a function given by parametric equations.

Fermat’s Theorem. Rolle’s Theorem. The Lagrange Theorem. Cauchy’s Theorem. L’Hospital’s rules and indeterminate forms. Taylor’s formula. Approximation by the Taylor polynomials. Critical points and extreme values – the First Derivative Test. Concavity and inflections – the Second Derivative Test. Sketching the graph of a function.


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Antiderivatives and indefinite integrals. Techniques of integrations – integration by parts, the method of substitution. Integration of rational functions by partial fractions. Rationalizing substitutions.

The definite integral – definition, properties. Fundamental Theorems of Calculus. Applications (area between two curves, arc length). Improper integrals.

Ordinary differential equations. A solution (general, particular, singular). Initial-value and boundary-value problems. Separable equations. First order linear differential equations. Linear independence of functions and Wronskian. Second order linear differential equations with constant coefficients. The characteristic equation. The method of undetermined coefficients, the method of variation of parameters. The Laplace transformation – properties, computations, application in differential equations.

Functions of several variables. Partial derivatives. Tangent plane. The total differential – definition, applications, differentiability. Chain rules. Implicit Function Theorem. Directional derivative and gradient vector. Extreme values (of functions of two variables).

Double integral – definitions, properties, basic theorems and applications. Change of variables (polar coordinates).

Infinite series. The sum of infinite series. Series of nonnegative terms – the comparison, ratio and root tests. Alternating series. Absolute and conditional convergence.

Classes: practical problems, the interpretation of obtained results

References:

S. R. Lay, Analysis with an Introduction to Proof

B. Sikora, E. Łobos, A First Course in Calculus

E. Łobos, B. Sikora, Advanced Calculus – Selected Topics

E. Łobos, B. Sikora, Calculus and Differential Equations in Exercises

R. A. Adams, Calculus: a Complete Course

Number of ECTS credits: 5 + 5 =10

Subject: Circuit Theory Code: CEIE_S1_13

Level of studies: BSc Semester(s):1,2

Teacher: dr. Damian Grzechca


Course attendants are supposed to have general knowledge concerning mathematics (includ-ing the ability to solve algebraic equations, operations on complex numbers, differentiation and


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integration of basic functions), physics (elementary concepts and laws such as the electrostatic field, familiarity with the basic electrical units).

Course objectives:

CT1: The main objective of the course is to provide the students with basic and advanced knowledge concerning linear and nonlinear direct current (DC) and time domain circuits. During the course the students should develop the skills concerning the analysis methods of DC circuits as well as time domain circuits.

CT2: The main objective of the course is to provide the students with basic and advanced knowledge concerning alternating current (AC) circuits, time domain circuits, transmission line and 3-phase circuits. The students should understand differences between these cir-cuits, know how to analyze a circuit and possess skills of dealing with these circuits.


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Lectures:

CT1:

1. Introduction to circuit theory, circuit variables - basic terms and definitions, classification of circuit theory problems, dc analysis, circuit elements, classification.

2. Passive two-terminal elements: resistor, voltmeter, ammeter, active two-terminal elements, voltage source, current source, circuit diagram and Kirchhoff’s laws, circuit diagram, Kirch-hoff’s laws.

3. Analysis of complex circuits, generalized Kirchhoff’s analysis, node voltage (nodal) analysis. 4. Energy and power conservation principle, two-terminal subcircuit, Thevenin’s/Norton’s

theorem, passive two-terminal subcircuit, series connection of resistors, voltage divider, parallel connection of resistors, current divider. Active two-terminal subcircuit. Thevenin’s theorem. Norton’s theorem. Practical sources. Maximum power transfer theorem.

5. Transfer function. Superposition principle. Transfer function. One-dimensional case, multi-dimensional case. Separation principle (source substitution theorem).

6. Multi-terminal elements. Element description – conductance matrix. Passive multi-terminal element. Two-terminal element (one-port). Three-terminal element. Two-port. Active mul-ti-terminal element. Other matrices of multi-terminal element. Analysis of circuits with multi-terminal element(s).

7. Dependent (controlled) elements. Arbitrary dependent element – description. Controlled sources – description. Use of controlled sources to element modeling. Transistor. Opera-tional amplifier. Arbitrary three-terminal or two-port element. Analysis of circuits contain-ing controlled sources. Design tolerances, sensitivity analysis. Designation of the maximum design deviation of circuit variable. Worst case analysis. Sensitivity analysis. Designation of parameter design tolerances.


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8. Analysis of nonlinear circuits. Graphical analysis. Series connection of elements. Parallel connection of elements. Single-loop circuit. Circuit with one nonlinear element. Analysis based on PWL approximation. Analysis based on Newton-Raphson iteration scheme.

9. Network analogies – magnetic circuits. 10. Transient analysis. Kirchhoff’s laws and passive element laws. Kirchhoff’s laws. Passive el-

ement laws: Resistor, capacitor, coil (inductor). Passive elements – summary. 11. Transient analysis in circuits with step excitation. Forced response. 1st order circuit – time-

domain method. 12. 1st order circuit – s-domain method. 1st order circuit – boundary values based method. 13. 2nd order circuit – s-domain method. Natural response. Complete response: natural re-

sponse + forced response. 14. Transient analysis in circuits with arbitrary excitation. Transfer function – properties and

selected examples. Properties. Transfer functions of selected circuits. Integrator. Differenti-ator.

15. Higher order circuits. Natural response and forced response.

CT2:

1. Transfer function based transient analysis – examples. Practical step. Practical pulse. 2. Laplace transform, Heaviside formula, Laplace transform dictionary. 3. AC steady-state analysis. Alternating current – RMS value, phasor notation. Complex num-

bers. 4. Phasor analysis. Kirchhoff’s laws. Element laws: resistor, inductor, capacitor. General two-

terminal phasor circuit, phasor impedance. Algorithm of ac steady-state analysis. 5. AC steady-state power. Measures of power. Instantaneous power. Average or real power.

Apparent power. Reactive power. Complex power. Maximum power transfer. 6. Frequency characteristics of two-terminal subcircuit. Ideal elements – summary. Resistor.

Inductor. Capacitor. Practical coil and practical capacitor. 7. Resonant circuits. Series-resonant circuit RLC. Parallel-resonant circuit RLC. Complex-

resonant circuit. 8. Transfer function approach - frequency response. Bode (logarithmic) plot. Filters. Low-pass

filter – LPF. High-pass filter – HPF. Band-pass filter – BPF. Band-stop filter – BSF. 9. Analysis of circuit response when one circuit constant varies. 10. Mutual inductance and transformers. Mutual inductance – basic transformer. Ideal trans-

former. Practical iron-core transformer. 11. Three-phase circuits. Wye-wye systems. Delta-delta and wye-delta systems. Combinational

systems. Power in three-phase systems. 12. Circuits with distributed parameters. Introduction. 13. Transient analysis in transmission line. 14. AC analysis – standing waves. Matched load line. Arbitrary termination. Open-circuited line.

Short-circuited line. Transmission line as circuit element, input impedance. 15. Summary and exemplary practical problems.


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Classes:

CT1:

1. Simple linear circuit analysis, Ideal voltage and current sources. Application of the Ohm’s and Kirchhoff’s laws.

2. DC circuit with practical sources, ideal and real ammeter and voltmeter 3. Nodal analysis method 4. Thevenin’s and Norton’s theorems. Superposition principle. Maximum Power transfer The-

orem. 5. Multi-terminal elements. 6. Nonlinear circuit analysis.

CT2:

1. Transients in the first order circuits 2. Transients in the higher order circuits. Heaviside formula. 3. Transients in circuits with non-zero initial conditions. 4. Arbitrary non-periodic excitation. 5. AC domain circuits. Phasors. 6. Power in AC domain circuits. 7. Frequency response of AC circuit. Resonant circuits and filters. 8. Transformers. Mutual inductance. 9. Circuits with distributed parameters. Time domain analysis. 10. AC steady state analysis of transmission line (standing wave) 11. Three phase systems. Laboratory

CT2:

1. Introduction to laboratory and to work with oscilloscope 2. Transient in first order circuits with zero initial conditions switched on a DC source 3. Transient in higher order circuits with zero initial conditions switched on a DC source 4. Transient in circuits with non-zero initial conditions 5. Resonance and frequency response 6. Transmission lines

References:

1. Rutkowski J., Circuit Theory, Wydawnictwo Politechniki Śląskiej, Gliwice 2006. 2. Allan H. Robbins and Wilhelm C Miller, Circuit Analysis: Theory and Practice, Delmar Cen-

gage Learning; 4 edition (July 19, 2006)



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Subject: Fundamentals of Computer Programming Code: CEIE_S1_14

Level of studies: BSc Semester(s): 1

Teacher: dr. Piotr Fabian


It is assumed, that the student has an elementary knowledge of mathematics at the secondary level and logical thinking skills, including abstract thinking.

Course objectives:

The course provides the knowledge required to understand, design and write computer pro-grams in the C language. The aim of the course is to lay a solid foundation of good software en-gineering and programming language practice. The program contains: introduction to impera-tive programming in C language (basic knowledge required to create and understand programs as well as skills essential for good software engineering and programming practice), basic algo-rithms and data structures and some advanced problems and techniques essential for pro-grammers. Lectures are illustrated with slides with many sample programs. They are support-ed by laboratories, which give students an opportunity to create programs on their own.


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Lectures:

· Introduction. The first program. · Development environments · Variables, basic types. · operators and expressions. · Instructions and program control. · The structure of a program · Functions · Memory management. · Arrays and pointers, memory allocation. · Structures and unions · Dynamic data structures. · The preprocessor, separate compilation. · Header files and libraries Laboratory:

Small programming exercises and one individual programming assignment.


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References:

• B. W. Kernighan, D.M. Ritchie, The C Programming Language (ANSI C), Prentice-Hall. • B. Stroustrup, The C++ Programming Language. Addison-Wesley, Reading, MA.

Number of ECTS credits: 5

Subject: Theory of Logic Circuits Code: CEIE_S1_15


Teacher: dr. Piotr Czekalski


Course objectives:

Theory of Logic Circuits presents to the audience a complete course covering wide aspects of modern digital system design (combinational, sequential, microprogrammable, programma-ble), it’s analysis and review. Student are presented step-by-step course on general two-value logic, numeric systems, algebra and arithmetic of digital devices, various synthesis and analysis methods related to the digital circuits along with review of digital devices and it’s utility.


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Lectures:

• Numeric systems. • Converting numbers between different numeric systems. • Binary forms of numbers and it’s representation in digital systems. • Fixed point arithmetic. • Information and communication – digital vs analogue world. • Digital devices, circuits and systems. • Boolean algebra, gates and binary operators. • System functionally complete. • Digital systems classification. • Combinational circuits design. • Synthesis and analysis of combinational circuits. • Iterative circuits.


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• Sequential digital systems. • Asynchronous sequential systems design. • Synchronous sequential systems design. • Dynamics of sequential systems. • Microprogrammable circuits design. • Programmable logic devices.

Classes:

Classroom exercises cover practice of the subjects that are closely related to the lecture, par-ticularly insisting on real problem analysis and solution. Laboratory:

Laboratory course covers systems design on digital systems and computer systems. Students are creating and analyzing real digital systems, build of various operators and medium scale integration devices(including sequential-related components and microprogrammable related memory components).


Subject: Social Sciences I Code: CEIE_S1_16


Teacher: prof. Waldemar Czajkowski


none

Course objectives:

There are two main goals to be achieved in this course. First - to discuss the importance of social knowledge/science for the citizens' participation in democracy. Second - to analyze the most important global social (technological, economic, cultural etc.) processes and to demonstrate their challenging character.


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1. The notion of politics and democracy. Various types of democracy.


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2. The importance of knowledge for contemporary societies. Social sciences as a form of collective self-knowledge.

3. The relevance of social sciences for democracy. The peculiarities of social sciences. 4. Globalization and its various interpretations. The importance of the studying globalization. 5. Globalization in historical perspective. Models of global historical process. 6. Great historical transformations (neolithic revolution, the rise of civilization, industrial revolu-

tion....) 7. Material basis of globalization (from telegraph and steamship to Internet and jet) 8. Institutional/organizational infrastructure of globalization (UN, World Bank etc.) 9. Ideological debates on globalization

References:

1. Jan Aart Scholte; Globalization. A critical introduction; Palgrave, New York 2005 2. Anthony Giddens, Sociology; Sociology, Polity Press, London 2001


Subject: Physics Code: CEIE_S1_21


Teacher: prof. Jacek Szuber


Course attendants are supposed to have general knowledge concerning physics and mathemat-ics at the level of secondary school, which allows the understanding of main physical phenom-ena in the nature.

Course objectives:

The aim of the course is explain the fundamental physical phenomena in the nature, combined with their mathematical description, for application in modern automatics, electronics and computer sciences.


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Lectures:

Semester 2: Introduction to physical universe Fundamentals of kinematics and dynamics of material point and rigid body Motion in inertial and non-inertial frames Conservation principles in mechanics Mechanical vibrations Wave motion and sound propagation Thermal physics Thermal gas processes Thermodynamics of gases Semester 3: Gravitational field Electrostatic field including dielectric phenomena Magnetic field including electromagnetic induction Electromagnetic radiation and wave optics Quantum optics and wave properties of matter Classical atomic models Fundamentals of quantum mechanics and quantum theory of one-electron atoms Band structure of solids including semiconductors. Classes:

Semester 2: Physical quantities, vectors and fundamentals of mathematical analysis ? Kinematics and dynamics of material point and rigid body Conservation principles for material point and rigid body Mechanical vibrations Wave propagation and sound waves Gas transitions and kinetic theory of gases Thermodynamics of ideal gas Semester 3: Grawitational field Electrostatic field Magnetic field Wave optics Quantum optics Atomistic nature of mater


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Laboratories:

Determination of the following physical parameters: gravitational acceleration g, moment of inertia of rigid body, coefficient of viscosity, focus of lenses, constant of diffractive mesh by light diffraction, work fuction of metals, lifetime of carriers in semiconductors, carrier concentration by Hall effect, absorption of beta radiation, spectral characteristics of excited atoms. References:

1. R. Resnick, D. Halliday, J. Walker: Fundamentals of Physics, Wiley and Sons Inc. New York, 2001.

2. M.Mansfield, C.O'Sulivan: Understanding Physics, Wiley and Sons, Inc., New York, 1998.


Subject: Computer Programming Code: CEIE_S1_22

Level of studies: BSc Semester(s):



Course: Findamentals of Computer Programming

Course objectives:

The aim of the course is to teach understanding, designing and writing programs in high level languages, particularly in C and C++. The course should give students a strong foundation of both theory and practice in the field of software development. It also introduces object orient-ed programming. Laboratory classes give student the opportunity to test their programming skills by writing sample programs and solving programming tasks. Practical examples require analyzing of source code and designing object oriented structure of programs.


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Lectures:

Introduction: The first sample program. Variables, types, operators, expressions. Instructions and flow control. Functions, the structure of a programs. Arrays, pointers, dynamic memory


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allocation. Structures, unions, dynamic data structures. The preprocessor, header files and li-braries. Object-oriented techniques, C++. Object-oriented programming paradigm. Classes, objects, methods (member functions). Friend functions and classes. Constructors and destruc-tors. The life cycle of objects. Overloaded operators and user-defined conversions. Inheritance. Polymorphism. Abstract classes. Multiple inheritance and virtual classes. Streams. Exceptions. Templates. Run time type information (RTTI). Elements of the standard C++ library (STL).

Laboratories:

Data types, operators, statements. Array types and pointers. Libraries and library functions. Working with files. Structures and unions. Non-OO C++ elements. Classes, constructors and destructors, overloaded operators, inheritance, multiple inheritance, polymorphism, RTTI, streams, exceptions, templatess.

References:

• B. W. Kernigan, D.M.Ritche, ANSI C, • B. Stroustroup, C++, • International Standard for Information Systems—Programming Language C++, ANSI


Subject: Discrete Mathematics Code: CEIE_S1_23


Teacher: dr. Edyta Hetmaniok


Knowledge of mathematics at the secondary school level is required

Course objectives:

Goal of this subject is to present the basic fields in mathematics concerning the discrete struc-tures, mathematical logic, techniques of theorem proving, which makes an important supple-ment for mathematical analysis, algebra and analytical geometry.


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Lectures:


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ELEMENTS OF COMBINATORICS – permutations, function of n-factorial (n!), combinations, binomial coefficient, binomial formula. LOGIC – calculus of logic sentences, truth-tables, tautol-ogies and contradictions, quantifiers. METHODS OF THEOREMS PROVING – direct proof, mo-dus ponens, modus tollens, proof by contradiction and contrapositive, proof of equivalence, proof by mathematical induction. SETS – definition and notation, operations on sets, Venn dia-grams, Cartesian product, size (the cardinality) of the set, countable and uncountable sets. RELATIONS – definition and properties, graph of the relation, equivalence relation, relation of partial and total (linear) order. FUNCTION AS A RELATION – function in the sense of relation, surjective, injective, bijective function. INTRODUCTION TO GRAPH THEORY – definition and operation on graphs, graph isomorphism, walk, trail, path, trees. Z TRANSFORM AND DIFFERENCE EQUATIONS – recurrence relation and methods of its solving: iteration method, by using the generating functions, by using the z transform.

Classes:

1. Elements of combinatorics – solving tasks by using the combinatoric constructions. 2. Mathematical logic – determining the logic value of statements, giving the converse, inverse and contrapositive of the statement. Examples of theorems proving and mathematical induc-tion. 3. Sets – testing properties of sets, constructing the generalized union and intersection of the given indexed family of sets, checking whether the given set is countable or uncountable. 4. Relations – testing properties of relations and drawing its graph, identifying the equivalence and the order relations, constructing the equivalence classes, finding the extremal elements of ordered set. 5. Function as a relation –constructing the image and contraimage, verifying whether the func-tion is surjective, injective or bijective. 6. Introduction to graph theory – solving tasks concerning the special kinds of graphs, walks, trails and paths, identifying the Eulerian and Hamiltonian graphs, trees constructing. 7. Difference equations and z transform – solving the recurrence relations by using the generat-ing function and z transform.

References:

1. “An Introduction to Discrete Mathematics”, S.Roman, CBS College Publishing, 1986. 2. “Discrete Mathematics with Applications”, H.F.Matheson Jr., John Wiley & Sons Inc., 1996. 3. “Discrete mathematics”, J.L. Kulikowski [i in.], Warszawa, PWN, 1982. 4. “Difference equations : an introduction with applications”, Walter G. Kelley, Allan C. Peterson. -

Boston : Academic Press, Inc., 1991.


Subject: Optimization and decision making Code: CEIE_S1_31



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Teacher: prof. Jarosław Śmieja


Calculus and differentia equations, Algebra and analytic geometry, Fundamentals of computer programming. Prior to this course, students should learn how to calculate derivatives, solve linear differential equations, perform calculations using matrix notation and develop simple software given the algorithm.

Course objectives:

Introduction of various types of practical optimization problems and analytical methods for solving them. Development of skills necessary for application of basic numerical algorithms. Introduction of mathematically based decision making in multistage decision processes.

Laboratory exercises aim at teaching how to implement theoretical results and standard algo-rithms to find solutions of real life optimization problems


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Lectures:

• Examples of optimization problems; defining optimality criteria • Modeling of decision processes • Unconstrained extrema • Examples of using necessary conditions • Constrained optimization • Necessary conditions for constrained minimum • Inequality constraints • Convex programming • Linear programming and simplex algorithm • Dynamic programming • Zero- and nonzero sum games • Decision trees

Laboratory:

• Analytical methods of solving constrained and unconstrained static optimization prob-lems

• Optimization of functions of one variable • Multivariable optimization • Linear programming, simplex method • Quadratic programming


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• Direct methods of dynamic optimization, gradient methods • Dynamic programming • Decision trees/game theory

References:

• Świerniak, A. Gałuszka, Optimization Methods and Decision Making. Lecture Notes. Wyd. Politechniki Śląskiej, Gliwice 2003.

• Z. Ogonowski, J. Smieja, Optimization Methods and Decision Making. (Handbook for students) Art&Kolor, Gliwice, 2001. (available for download at http://www.platforma.polsl.pl/rau1/)


Subject: Probability and Statistics Code: CEIE_S1_32


Teacher: prof. Joanna Polanska, prof. Marek Kimmel


Courses: Algebra and Analytic Geometry, Calculus and Differential Equations

Course objectives:

The objective of this course is to give a theoretical basis of probability theory and statistics in very general context and to demonstrate the possible applications of this theory to applied models in system engineering, in operation research, and time series.


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The course consists of two parts: probability theory and applied statistics. The probability part starts with set theoretic concepts such as sigma-algebras, and denumerable operations on sets. Then, probability is introduced as a denumerably additive nonnegative normed set function. Properties of probabilities, including conditional probability follow. Random variables are in-troduced as measurable maps from the probability space in to the set of real numbers with Borel sigma-algebra. Distribution functions are discussed, including important examples of continuous and discrete distributions binomial/Poisson, geometric, uniform, exponential, normal, multivariate normal, gamma and chisquare). Independence of events is shown to lead


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to strong results such as Borel-Cantelli theorems and Kolmogorov 0-1 law. Expected values are defined as Lebesgue integrals of random variables. Monotone and Dominated Convergence theorems follow. Law of Large Numbers and Central Limit Theorem are discussed. The second part starts with the survey of the methods of basic statistical testing where special emphasis is put on the hypothesis tests for the mean and variance of a normal population. Then the nonparametric methods are introduced followed by the ANOVA algorithms. Next we focus on the way of describing the relations among random variables. We introduce the measures of correlation (for both Gaussian and non – Gaussian random variables) and basic statistical tests. We give a general introduction to linear regression and consider the estimation problem for unknown parameters of probability distribution. Here we discuss the following three main methods: maximum likelihood method, the least squares method and the method of moments. Finally we present the basis of the analysis of frequencies. All the theoretical material is broadly illustrated by the examples whose purpose is to help un-derstanding the theoretical concepts and to show the possibility of applications of the probabil-ity methods in engineering practice

1. Probability theory, part 1 – total and conditional probability 2. Probability theory, part 2 – distribution functions 3. Descriptive statistics 4. Graphical representation 5. Elements of theory of estimation. Point and interval estimators 6. Parametric tests, part 1 – testing for population mean, 7. Parametric tests, part 2 – testing for population variance 8. Goodness of fit tests 9. Nonparametric tests - unpaired measurements 10. Nonparametric tests – paired measurements 11. Inference for proportions – testing for population proportion 12. Inference for proportions – odds ratio, test of independence 13. Measures of correlation, linear regression

References:

1. Feller W: An Introduction to Probability Theory and Its Applications, Vol. 1, Wiley, 3rd

edition or later

2. Sokal RR, Rohlf JF: Biometry WH Freeman, 3rd

edition or later

3. Zar JH: Biostatistical Analysis, Prentice Hall, 4th

edition or later


Subject: Introduction to Electronics Code: CEIE_S1_33


Teacher: prof. Zdzisław Filus


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Course attendants have to possess basic knowledge in calculus, algebra, physics and circuit theory.

Course objectives:

The objective of the course is to provide basic understanding of the operating principles of semiconductor devices and an introduction to the theory and operation of electronic circuits


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Lectures:

Introduction: definitions and basic features of analog and digital signals and circuits. Resistors, capacitors, inductors and transformers. Logarithmic scale and Bode plots. Basic RC circuits. Intrinsic and extrinsic semiconductors. P-N junction: charge density, electric field and voltage distribution, contact potential, capacitance of the junction, V-I characteristics, switching char-acteristics. Various types of diodes: Zener and avalanche effects, varicaps, Schottky diodes. Bi-polar transistors: principle of operation, basic characteristics and parameters, Ebers-Moll model, linear piecewise models, small-signal equivalent circuits, switching characteristics, bias-ing circuits, basic amplifiers: CE, CB and CC, current sources, current mirror. Field-effect tran-sistors: operation of JFETs and MOSFETs, voltage-to-current characteristics, biasing circuits, basic amplifiers (CS, CG, CD), current sources, analog switches, NMOS and CMOS gates. Optoe-lectronic devices: photoresistor, photodiode, light emitting diode, optocouplers, displays. Sim-plified theory of feedback: types of feedback systems, influence of negative feedback on gain, input and output impedances, bandwidth, noise reduction, stability, gain and phase margins. Power amplifiers: class A, B, C, D amplifiers, principle of operation, efficiency. Differential am-plifier: large and small-signal analysis. Operational amplifiers: ideal and non-ideal amplifier, basic applications. Integrators and differentiators. Analogue comparators. Sine wave oscilla-tors. Square wave and ramp oscillators. Rectifier systems. Regulated power supplies: IC voltage regulators, switching regulators. Sample & hold circuits. Analogue-to-digital and digital-to-analogue converters: basic methods of conversion and their comparison.

Classes:

Frequency response of simple RC networks. Diode applications. Simple linear voltage regula-tors. Quiescent point of simple transistor amplifiers and its thermal stabilisation. Small-signal analysis of amplifiers: equivalent circuit. Ideal operational amplifier and its basic applications. Voltage regulators. Sine wave oscillators. Square wave oscillators. Non-linear circuits with op-erational amplifiers.

Laboratory:

1. Introduction to measurement instruments


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2. Semiconductor diodes 3. Bipolar transistors 4. Unipolar transistors 5. Optoelectronic devices 6. Rectifier circuits 7. Linear voltage regulators 8. Sine wave oscillators 9. Applications of operational amplifiers 10. Square wave and ramp oscillators 11. Power amplifiers

References:

1. Horowitz P., Hill W., The Art Of Electronics. Cambridge University Press, 2001 2. Tietze U., Schenk Ch.: Electronic circuits. Springer-Verlag Berlin Heidelberg, 2008 3. Cooke M.J.: Semiconductor Devices. Prentice-Hall, 1990 4. Savant C.J., Roden M.S., Carpenter G.L.: Electronic Design: Circuits and Systems. Benja-

min/Cummings, 1991


Subject: Introduction to System Dynamics Code: CEIE_S1_34


Teacher: prof. Andrzej Polański


Algebra and analytic geometry, Calculus and differential equations, Physics

Course objectives:

The aim of the course is making students familiar with problem and methods related to model-ing phisical dynamical systems and dynamical systems as engineering constructions.


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Lectures:


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Introduction, mathematical modeling, what for?, approaches, problems, software projects. Mathematical modeling in physics, chemistry, engineering, biology, economy. Derivation of mathematical models by using the method of balances. Balances of mass, volume, energy, force, momentum, current, voltage. Collection of mathematical models obtained by using the method of balances. Short introduction to variational calculus. Derivation of mathematical models of physical systems by using variational principles. The method of Lagrange equations. Collection of models obtained by using the method of Lagrange equations. Miscellaneous topics. Lagrange equations for the case of mechanical systems with constraints. Hamilton equations. Electro-mechanical analogies of type I and II. Basics of methodology of analysis of systems of linear differential equations. State, input. Modes, modal forms, eigenvalues and eigenvectors of the state matrix. Stability, aperiodicity. Basics of the methodology of the analysis of nonlinear systems. State space. Isoclines. Elements of chaotic dynamics. Classes:

Modeling physical and engineering systems by using the method of balances. Lagrange equations I Lagrange equations II Electromechanical analogies I Electromechanical analogies II Linear systems Nonlinear systems and state space

References:

Cannon RH, Dynamics of Physical Systems, McGraw Hill, 1980 Luenberger DG, Introduction to Dynamic Systems, Wiley, 1979 Ginsberg JH, Advanced Engineering Dynamics, Cambridge University Press, 1995


Subject: Numerical Methods Code: CEIE_S1_41


Teacher: dr. Janusz Wyrwał



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Mathematics. It is assumed that before starting to attend this course student has adequate knowledge in the field related to linear algebra, calculus and differential equations.

Course objectives:

The aim of the course is to teach basic terms related to numerical analysis and numerical methods used for approximate solving fundamental engineering problems. After completing the course students should be ready on his own to choose proper numerical method for solving fundamental engineering problems.


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Lectures:

Basic notions: convergence rate, conditionnning, stability of algorithm, computational efficien-cy. Sources of errors. Absolute and relative error. Truncation and round-off error. Positional numeral systems.

Numbers representation in computer. Two’s complements representation. Floating point rep-resentation. Floating point errors – Loss of significance. Errors of algebraic computations.

Computation of function values. Horner’s scheme and its applications: evaluating polynomial values, dividing polynomial by binomial, determining interval of real roots, evaluating values of polynomial derivatives, determining decimal representation of numbers of different positional numeral systems, expanding polynomial in terms of powers of binomial, determining coeffi-cients of polynomial after change of variable.

Continued fractions. Convergents of the continued fractions. Continued fraction expression of a real number. Convergence of continued fractions. Definition of analytical function of real varia-ble. Taylor and Maclaurin series expansions. Errors of series expansions.

Interpolation. Formulation of the interpolation problem. Geometric interpretation. Basis func-tions. Lagrange’s interpolating polynomial. Newton’s interpolating polynomial. Divided differ-ences. Linear difference operators, their properties and computations schemes. Relationships between divided differences and difference operators. Newton’s interpolation polynomial with divided differences and difference operators. Errors of interpolation. Relationships between different interpolation polynomials. Examples.

Numerical differentiation. Differential operators and their relationship with difference opera-tors. Formulas for numerical differentiation. Examples.

Numerical integration. Formulation of numerical integration. Newton-Cotes formula for nu-merical integration. Other numerical integration methods – Gauss formula, Chebyshev formula. Relationships between different integration methods. Examples.


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Approximation. Formulation of the approximation problem. Different types of approximation. Space of square integrable functions. Least square approximation method. Examples of orthog-onal and orthonormal bases. Point approximation. Uniform approximation in the space of con-tinuous functions. Weierstrass Theorem. Chebyshev polynomials and their application in uni-form approximation. Examples.

Solution of systems of linear equations. Conditioning of systems of linear equations. Direct methods. Algorithm of Gauss elimination method with full and partial pivoting. Inverse matrix determination. LU factorization. Cholevsky method. Examples. Iterative methods.

Eigenvalues and eigenfunctions. Definitions of eigenvalues and eigenvectors. Finding the great-est real eigenvalue and corresponding eigenvector – Power method. Matrix reduction. Inverse iteration. Jacobi method. Examples. Approximate solution of nonlinear equations. Bisection method. Regula falsi method. Newton's method. Secand method. Comparison of convergence rates. Bernoulli method. Examples.

Approximate solution of ordinary differential equations. Newton’s method and its modifica-tions. Runge-Kutty method. Taylor’s method. Piccard’s method. Examples.

Laboratory:

1. Theory of Errors 2. Calculation of Function Value 3. Interpolation 4. Numerical Differentiation 5. Numerical Integration 6. Approximation 7. Solving Systems of Linear Equations 8. Determining Eigenvalues And Eigenvectors of Matrix 9. Approximate Solving of Non-Linear Equations 10. Approximate Solving of Ordinary Differential Equations 11. Approximate Solving of Partial Differential Equations 12. Approximate Solving of Integral Equations

References:

1. Klamka J., Pawełczyk M., Wyrwał J.: “Numerical Methods”, students’ book, Gliwice, 2001 2. Kincaid D., Cheney W.: “Numerical Analysis: mathematics of scientific computing”, Pacific

Grove: Books/Cole Publ. Co., 2002 3. Ralston A.: „A First Course In Numerical Analysis”, McGraw-Hill, 1965. 4. Burden R., Faires J.: „Numerical Analysis” , Boston: PWS-KENT Publ. Co, 1985. 5. Demidowicz B. P., Maron I.: „Computational mathematics”, Moscow: Mir Publ., 1987. 6. Press W. H. [et al.]: „Numerical recipes : the art of scientific computing”, Cambridge Universi-

ty Press, 2007


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Subject: Digital Circuits Code: CEIE_S1_42


Teacher: dr. Wojciech Sakowski


Course attendants are supposed to have general knowledge concerning Boolean Algebra and Automata Theory that enable design of combinational and sequential logical circuits. It is as-sumed that students passed the course: Theory of Logical Circuits.

Course objectives:

Course is a part of specialized curriculum content and covers basics of digital hardware design. The course objectives include having the students got acquainted with available hardware component base, methods of implementing a specified functionality in hardware and related design methodologies and tools.


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Lectures:

Basic information about digital signals: quantization and coding, binary codes, binary coded decimal numbers (BCD), fixed point positive and negative numbers, symbolic data represen-tation. General description of digital integrated circuits: scale of integration, digital circuits families.

TTL family: structures and parameters of basic gates, immunity to interference – noise mar-gins, comparison of TTL integrated circuits with ECL, CMOS and BiCMOS devices; basic op-eration and static and dynamic characteristics of TTL and CMOS gates.

Combinational circuits: complex gates, multiplexors, decoders.

Sequential circuits: flip-flops, registers, shift registers with feedback, counters.

Arithmetic circuits: adders and subtractors for binary and BCD Excess 3 numbers, number comparators, multipliers, floating point arithmetic.


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Memories: static and dynamic RAMs, ROMs, UVEPROMs, EEPROMs, Flash memories. Pro-grammable logic devices: simple PLDs, basic knowledge of FPGA.

Control unit design: hardwired control units, microprogrammed control units. Introduction to PLD/FPGA and ASIC design methodologies and hardware description languages (ABEL, VHDL).

Devices for data input: keys, keyboards, touchscreens. Data output: LED and LCD displays, display control. General rules of data transmission: structure of digital system, asynchro-nous serial and parallel data transmission, handshaking, bus protocols. Long transmission line effects and line terminators.

Classes:

• Basics of interfacing digital gates with analogue elements • Register & Counters • Arithmetic circuits • Microprogrammable Logic Circuits • FPLA Devices Laboratory:

• Static and Dynamic Gate Characteristics • Arithmetic Circuits • Microprogrammable Logic Circuits • Digital Frequency Meter • FPLA Devices

References:

Jerry D. Daniels, Digital Design from Zero to One, John Wiley & Sons, 1996 John P. Hayes, Digital Logic Design, Addison Wesley, 1993


Subject: Measurement Systems Code: CEIE_S1_43


Teacher: prof. Jerzy Frączek


Circuit Theory, Physics, Probability and Statistics.

Course objectives:


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Objectives of the course is to acquaint the students with measurement systems. A measure-ment system is recognized as an information system which presents an observer with numeri-cal value corresponding to the variable being measured. The course is intended as a reference for users of sensors, sensors systems, transducers and transducers systems. The scope of this course presents the basic principles of advanced sensor and transducers systems.


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Lectures:

Introduction: scope of lectures, literature; integration of intrinsically safe field instrumentation into industrial communication networks; intelligent sensors; institutions: IMEKO, IFAC, EUROSENSORS, PSST – Polish Society of Sensors Technology, COE – Optoelectronic and Elec-tronic Sensors.

Smart sensors: Measurement of fluid flow by means of pressure differential devices - orifice plates and Venturi tubes. Smart interface. The essential sub-systems; list some of the main sen-sor defects. Zener Barriers (Ex).

The general measurement system: purpose, general structure,. elements of system. Definition of sensor; sensor classifications. Example: “Weight measurement system” – elements of system; strain gauges (conventional and silicon).

Vocabulary of Basic and General Terms in Metrology: static characteristics - range, span, zero, zero drift, sensitivity, resolution, response, linearity, hysteresis, calibration, accuracy… ; dy-namic characteristics.

Specialized measurement system: gas chromatography – column, carrier gas, solid particles, thin layer of liquid composition, HETP – Height Equivalent to a Theoretical Plate, chromato-gram, retention time. Detectors: TCD – Thermal Conductivity Detector (katharometer), FID – Flame Ionisation Detector, ECD – Electron Capture Detector.

Non–Dispersive Infra-Red (NDIR) gas analyser: IR transmission characteristics, one path sys-tem, two path system, IR emitters, rotating chopper disc, reference cell, sample cell, radiation detectors (selective or non-selective), transfer equation

ITS-90 – The International Temperature Scale of 1990: triple points, freezing points, melting points, interpolation instruments – platinum resistance thermometer, gas and vapour ther-mometers, radiation pyrometer; interpolation equations; thermodynamic (Kelvin) and empiri-cal (Celsius) scales.

Thermal radiation measurement system: high temperatures, moving body, temperature distri-bution over a surface; “black body”, Planck’s law, emissivity of real body, characteristics of transmission medium; general form of thermal radiation measurement system, optical focus-


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ing system without and with lens, transmission characteristics, detectors – thermopiles, bo-lometers; total detected power, output signal.

Pressure (pneumatic) measurement system: elements of system; metal resistance Strain Gauge - tensile stress, compressive stress, longitudinal strain, transverse strain, elastic modulus, Young’s modulus, Poisson’s ratio, GF – Gage Factor; characteristics of system.

Review of sensors: conventional, thick, thin and semiconductor technologies; Strain Gages, Zir-conia Cell (ZrO2), magnetic (mechanical) sensors, electromagnetic sensors, chemical sensors, gas sensors, resistance and thermocouple sensors.

Reliability of measurement systems: reliability, unreliability, MTBF - Mean Time Between Fail-ures, failure rate, variation of failure rate during lifetime of equipment – “bathtub” curve, relia-bility of a system of n elements in series or cascade, availability, methods of improving the re-liability of measurement systems.

Laboratory:

Practical works in laboratories concerning instrumentation as a coherent , integrated subject of measurement systems. Examples of exercises:

1. LabVIEW The introduction to the National Instruments graphical environment – LabVIEW. Front and block diagram (source code) creation, application debugging, array and matrix operation, graphical presentation of measurement/calculation results. Equipment: PC with LabVIEW graphical environment. 1. LabVIEW + DAQ Functional overview of the Data Acquisition boards architecture. Signal generation and acquisi-tion with LabVIEW application – close look at how the signal is generated and acquired by the DAQ board. Equipment: PC with DAQ board and LabVIEW graphical environment, HP33120 arbitrary waveform generator, HP56003B digital oscilloscope. 2. Digital to analog converters Investigation of the metrological characteristic of the D/A converters (zero and gain errors, differential and integral linearity, sensitivity to temperature, dynamic properties). Equipment: DAC tester, voltmeter, analogue oscilloscope,muffle furnace. 3. Strain gauges Investigation of the strain gauge factor for conventional and piezoresistive strain gauges. 4. Flow measurements Familiarize with the properties of some of the measurement sensors used in flow measure-ments (turbine, electromagnetic, ultrasonic and orifice plate flowmeters)


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5. Gas chromatography Familiarize with the gas chromatography. Investigation of column temperature and flow rate of carrier gas on chromatogram. Equipment: gas chromatograph wit TCD (thermo-conductive) detector 6. Temperature measurements Familiarize with the widely used in industry temperature sensors – RTDs and thermocouples. Calibration of temperature sensor in one of the fixed point of the ITS-90 (freezing point of tin). 7. GPIB Interface Familiarize with the modern measuring instruments used as test equipment in laboratories and industry, equipped with dedicated measuring interface – GPIB. 8. Profibus DP Investigation of the metrological parameters of chosen measuring modules. System configura-tion, sensors connection (2, 3 and 4 wire RTD measurements, thermocouple cold junction compensation, current loop operation with HART protocol).

References:

Bentley J. P.: Principles of Measurement Systems; Longman, London and New York 1985. Fraden J.: AIP Handbook of Modern Sensors; Physics, Design and Applications. American Institute of Phys-ics, 3rd ed., Springer-Verlag, New York, Berlin, Heidelberg, 2004. International Vocabulary of Basic and General Terms in Metrology. ISO 1993. Guide to the Expression of Uncertainty in Measurement. ISO 1993


Subject: Theory of Computer Science Code: CEIE_S1_44

Level of studies: BSc Semester(s): 4, 5

Teacher: dr. Robert Brzeski


none

Course objectives:

The aim of the lecture is to delivery to students the information in the range of the basic notions of

computer science. The aim of the classes and laboratory is to purchase by the students the skill in the


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range of creating the algorithms, low-level programming, understanding of works of microprocessors

and introduction with the basic structures of the data.


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Lectures

1. Algorithms 2. Turing machine 3. Introduction to formal grammars 4. Formal grammars - examples 5. Basic components of a computer 6. Introduction to architecture of a computer 7. Von Neumann's architecture, introduction to machine W 8. Designing an instruction set for machine W 9. Program control unit for machine W 10. Programming in assembly language of machine W 11. Advance programming in assembly language of machine W 12. Input / Output functionality 13. Interrupts 14. Introduction to operating systems 15. Problems of management of resources and synchronization

Classes

1. Algorithms, 2. Turing machine 3. Formal grammars 4. Designing instructions for machine W 5. Programming in assembly language of machine W 6. Management of resources and synchronization

Laboratories

1. Designing instructions for machine W, 2. Programming in assembly language of machine W 3. Machine W - Input/Output 4. Machine W - Interrupts 5. Data access methods 6. Turing machine

References:


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1. Tanenbaum, Andrew S.: "Structured Computer Organization"

2. Hennessy, John L., Patterson, David A.and Goldberg, David: "Computer Architecture: A Quantitative Approach"


Subject: Social Sciences II Code: CEIE_S1_45




The basic knowledge of Social Sciences I

Course objectives:

The main objective of the course is to present an outline of the development of technology and science, including the feedback beween S&T and economy, politics and culture. Emphasis will be given to the 20th century development, in particular to the computer/Internet revolution and the development of information/knowledge civilization/society.


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1. Introductory remarks on history of science&technology nad global history 2. Technologies of information/knowledge: language, writing, print, 3. Mythology - Philosophy - Science 4. Outline of the history of mathematics, physics and chemistry 5. Outline of the history of geology, biology and medicine 6. Outline of the history of computers hardawre and software 7. Social, cultural and political history of computers and Internet

References:

1. Jacob BronowskiI, The Ascent of Man, Science Horizons, London 1973 2. Paul Levinson, The Soft Edge: A natural history and future of the information revolution, Routledge,

London 1997


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3. Paul Levinson, Cellphone: The Story of World's Most Mobile Medium and How Palgrave, New York 2004


Subject: Control Fundamentals Code: CEIE_S1_51

Level of studies: BSc Semester(s): 5, 6

Teacher: prof. Ryszard Gessing


Mathematics, Physics, Introduction to system dynamics. It is assumed that the student has the basic knowledge concerning linear differential equations, Laplace and Z transform, as well as the models of the systems, especially their dynamical properties.

Course objectives:

The objective of the lectures is to give basic control knowledge in the fields of analysis and design of linear control systems, continuous and discrete-time, single and multivariable. The objective of classes and laboratory exercises is to acquire some practice in control system analysis and design using ad-vanced CAD environment, like MATLAB-SIMULINK


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Lectures:

Introduction to the course. Watt centrifugal governor Feedback Control Systems-basic notions, dy-namic and static elements, block diagrams. Control system classification.

Models of physical systems. Differential equations, state space models, linearization, transfer func-tion for single – and multivariable elements. State space versus transfer function description. Fre-quency responses: Nyquist, Bode plots.

Basic elements and their responses. Time and frequency responses of the basic elements: first order lag, second order, ideal integrator and differentiator, system with delay.

Dynamic system properties. Fundamental matrix derivation. Canonical form. Controllability – defi-nition, conditions. Observability – definition conditions. Stability, Hurwitz criterion.


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Feedback control systems. Voltage stabilization system. Closed-loop (CL) system description. CL frequency response – Nichols chart. Feedback system properties. Control system structure. Block diagrams transformation.

Closed-Loop system stability. Characteristic equation of the CL system. Applying of Hurwitz criteri-on. Nyquist criterion, derivation and calculation usage. Stability analysis using Bode plots. Stability of the systems with delay.

Quality of the control. Steady-state analysis – system of type 0 and type I. Account of nonlinearities. Method based on root placement. Root locus method. Methods based on integral indices. Methods based on frequency responses.

Compensators and controllers. Lead, lag, lead-lag compensators. Recommendation for compensator choice. PID controller. Regulator implementations. Regulator parameters tuning. Ziegler-Nichols rules.

Multivariable systems. Matrix transfer function. Stability analysis. Characteristic equation using state space and transfer function models. Applying of Hurwitz criterion. Design using the method of successive closing of control loops.

Discrete-time systems. Z-transform. Sampling data system. Digital control systems. Discrete-time transfer function. Ideal sampler, zero-order hold, first order hold. CL system description. Stability analysis. Design.

Classes

1. Dynamic systems description 2. Frequency responses 3. Hurwitz stability criterion 4. Nyquist stability criterion 5. Nyquist stability criterion - systems with time delay 6. Steady state analysis 7. Root locus method 8. Stability degree and resonance degree 9. Systems quality - frequency domain methods 10. Sampled data systems

Laboratories

1. CAD of control systems – Matlab introduction 2. Stability of linear systems 3. Static accuracy 4. Phase-lead and phase-lag compensation 5. Attenuation index and tracking index 6. PID controllers 7. Root locus method 8. Sampled-data systems

References:


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1. Gessing R.: Control Fundamentals, Wydawnictwo Politechniki Śl., Gliwice 2004. 2. Franklin G.F, J.D. Powell and Emani-Naeini: Feedback control of Dynamic Systems, (Third Edition)

Addison-Wesley, 1994.


Subject: Artificial Intelligence Code: CEIE_S1_52


Teacher: prof. Ewa Straszecka


Course attendants are supposed to have general knowledge concerning computers and computer appli-cations. They have either be able to use at least one high level programming language or an advanced numerical tool like e.g. Matlab. It is assumed that students passed the following courses: Fundamentals of Computer Programming, Theory of Computer Science.

Course objectives:

Aim of the study is to give a definition and a review of AI, together with more careful investigation in se-lected areas. A student has a chance to learn among others about knowledge representation, reasoning, fuzzy sets, neural networks and genetic algorithms and practice an implementation of the methods dur-ing laboratory work


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Lectures

Definition of artificial intelligence. Methods of AI problems representation. Representation of knowledge – classical and new methods. Schemes of reasoning. Reasoning with certainty measures. Fuzzy reasoning. Chaining rules. Expert systems in technical and medical diagnosis support. A review of AI computer languages. Natural language processing and its use in databases. Fuzzy sets in signal iden-tification and control. Neural networks in signal processing. Clustering methods. Genetic algorithms in solving problems. Emotion modelling – aim and methods.

Laboratories

1. KOHONEN NETWORKS – TP 2. ECG MODELLING BY GENETIC ALGORITHMS – part I- function optimisation 3. ECG MODELLING BY GENETIC ALGORITHMS – part II- ECG analysis


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4. NEURAL NETWORKS IN SIGNAL PROCESSING 5. MEDICAL DIAGNOSIS SUPPORT SYSTEM part I – basic probability assignment calculation 6. MEDICAL DIAGNOSIS SUPPORT SYSTEM part II – inference, incomplete data management 7. HEURISTIC CONCEPTS IN FUZZY SETS INTERPRETATION 8. EMOTION MODELING 9. EVOLUTIONARY STRATEGIES IN OPTIMIZATION PROBLEMS – part I – software preparation 10. EVOLUTIONARY STRATEGIES IN OPTIMIZATION PROBLEMS – part II – properties evaluation 11. ANT SYSTEMS - part I – software preparation 12. ANT SYSTEMS - part II – properties evaluation

References:

1. R.J. Schalkoff “Artificial Intelligence - An Engineering Approach”, McGraw-Hill Publishing Company 1990.

2. S. Russel, P. Norvig “Artificial Intelligence. A Modern Approach”, Pearson Education Inc. 2003.


Subject: Computer Networks Code: CEIE_S1_53


Teacher: dr. Jerzy Mościński


Course attendants are supposed to have general knowledge concerning computers and computer appli-cations, including using computer networks services. Students are also supposed to possess practical skills concerning computers and Internet usage as well as programming in at least one high level pro-gramming language. It is assumed that students passed the following courses: Fundamentals of Com-puter Programming, Theory of Computer Science.

Course objectives:

Course is part of specialized curriculum content and is related to education in areas of computer network technologies, Internet techniques and communication technologies. The course aims objec-tives include having the students got acquainted with hardware and software solutions in computer networks, benefits from computer networks based communication, usage and administration of network operating systems and network programming.


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Lectures

Overall objectives of the course include providing students with basic as well as advanced knowledge concerning components of computer network: communication methods, server comput-ers, client computers, network infrastructure. Types of services offered by computer network serv-ers are covered in detail as part of the course. Internet services, Internet and TCP/IP protocol suite, TCP/IP protocol structure, physical, data, network, transport and application layers tasks in com-puter network are also considered.

Specific topics covered during course lectures and laboratory exercises include the following: com-puter networks types and systems; local area network LAN and wide area network WAN; packets, frames, reliable and unreliable transmission; LAN cabling systems, physical topology, interfaces; Internet and TCP/IP protocol suite; network servers and types of services; Internet network proto-col, TCP/IP protocol family. TCP/IP protocol structure, tasks and services concerning the physical layer, data layer, network layer, transport and application layers in computer network; DNS system and its role in naming hosts in computer networks; WAN techniques, routing and tracing routes; internetworks, architecture and protocols; basic applications of computer networks services; using electronic mail systems; www pages and browsers; advanced elements of UNIX/Linux operating system using; multimedia networking applications; streaming audio and video with networks; quali-ty of Internet services – differentiated and aggregated services models; security in computer net-works; cryptography, authentication, certification, firewalls; Internet commerce; computer network management.

Laboratories

• UNIX/Linux operating system basics. • Bash shell programming. • DNS basics and configuration. • Advanced e-mail system configuration and administration. • Client/server programming. • Internet Protocol details, IP addressing, DHCP service. • DNS protocol, DNS server configuration. • Simple www server programming and configuration. • Security issues, firewall configuration. • Virtual LAN configuration. • Network protocols and applications analysis. • E-learning support system design and setup. • PHP programming, Internet based databases.

References:

1. J.F. Kurose, K.W. Ross, Computer Networking: A Top-down Approach, 5/e, Addison-Weesley, 2009.

2. D.E. Comer, Computer Networks and Internets, 5/e, Pearson Education, 2009

3. A.S. Tanenbaum, Computer Networks, 4/e, Pearson Education, 2003.



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Subject: Fundamentals of Signal Processing Code: CEIE_S1_54


Teacher: dr. Katarzyna Mościńska


Prerequisites: Algebra, Calculus, Circuit Theory. Course attendants should possess satisfactory knowledge of the following issues: complex numbers, derivatives and itegrals, AC circuits, frequency description of systems. Students are supposed to possess basic computer programming skills.

Course objectives:

The goal of the course is to make students acquainted with various methods of signals and systems rep-resentation. Course participants become familiar with fundamental methods of analog and digital signal processing. The course serves as foundation to more specialized courses, like digital signal processing and analog circuit design.


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Lectures

1. Introduction to signal processing: definition of signal. Signal properties. Some special signals of interest.

2. Periodic signals: orthogonality. Parseval’s theorem. Trigonometric Fourier series. Periodic sig-nals in linear, shift invariant systems. Equivalent forms of Fourier series. Discrete spectrum.

3. Frequency representation of aperiodic signals. Power and energy signals. Fourier transform: definition, properties.

4. Signal modulation: amplitude and frequency modulation – basic terms, description in time and frequency domain. Bandwidth and efficiency. Realization of modulation/demodulation.

5. Ideal and realizable filters. Relation of frequency characteristic to impulse response. Sampling and its implication: ideal sampling in the time and frequency domain. Shannon’s theorem. Alias-ing.

6. Discrete –time description of signals and systems: basic sequences, linear – time invariant sys-tems, convolution, causality criterion.

7. Fourier transform of discrete – time signals: definition, properties, use in signal processing.

8. Z transform: definition, region of convergence, properties. System function of a digital filter.

9. Representation of a digital circuit: difference equation, block diagram, system function, pole – zero pattern.

10. DFT and FFT. Definition and properties of DFT. Linear vs circular convolution. Linear convolu-tion with DFT. FFT decimation-in-time algorithm.


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Laboratories

1. Signal generation and basic operations on signals.

2. Transfer function of a filter.

3. Magnitude and phase spectral density. Signal convolution.

4. Measurement of signal spectrum.

5. Individual task – Fourier series expansion and reconstruction.

6. Rectifiers and amplitude modulation.

7. Pulse amplitude modulation.

8. Signal generation and convolution – LabVIEW environment.

9. Z Transform and system function H(z)

10. Discrete Fourier Transform

References:

Oppenheim A.V., Willsky A.S., Signals and Systems, Prentice-Hall, 1997

3. Lyons R. G., Understanding Digital Signal Processing, Addison-Wesley, 1997.


Subject: Microprocessor Systems Code: CEIE_S1_55


Teacher: dr. Adam Milik


Course attendants are supposed to have general knowledge of digital circuits operation and design, algorithm implementation, basics of programming languages and principles of computer operations.

Students are also supposed to possess practical skills concerning programming and algorithm imple-mentation with use of high level programming language. It is assumed that students passed the follow-ing courses: Fundamentals of Computer Programming, Theory of Logic Circuits, Theory of Computer Science, Digital Circuits

Course objectives:

….



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Lectures:

Introduction to microprocessor, Evolution from finite state machine through the microprogrammable device to microprocessor. Basic functional blocks of microprocessor and its feature are discussed. The influence to behavior and performance of computing system is shown.

Instruction execution. Harvard and Princeton (von Neumann) architectures. Sequential and pipelined execution concepts

Instruction set. Argument addressing model and addressing modes.

Bus architecture of computer system. Bus interface cycles. Controlling timing of cycles. Connecting memories and peripheral devices to microprocessor.

Interrupt system. Implementation concept. Classification of interrupt systems. Concept of vectorized interrupt system.

Serial interfaces RS232, 1-Wire, I2C, USB. Principles of data transmission and reception. Synchroniza-tion of receiver, asynchronous and synchronous modes. Data integrity check.

Arithmetic. Numeral systems. Integers signed and unsigned. Fixed point numbers. Floating point num-bers. Arithmetic operations. Numerical algorithms: line drawing (Bresenham’s), trigonometric calcula-tions and rotations (Cordic), Solving non-linear equation (Newton-Raphson)

Basics of automatic statement processing. BNF notation, Syntax diagram. Data flow graphs – intermedi-ate representation of statements.

Hardware Description Language (HDL) introduction to Verilog HDL. HDL vs Programming Language. Basic of automatic synthesis. Description of combinatorial blocks. Description of sequential blocks.

Laboratory:

Using C/C++ in embedded systems without operating system (OS). Controling resources of microcon-troller. Servicing interrupts. Interfacing real hardware. Handling: displays LED, LCD and graphic LCD, keyboards, sensors. Concurent operation of the program. Optimization of program for embedded sys-tems. Runing On Chip Debug with CAD EDA programming tools

Introduction to HDL logic synthesis and FPGA technology. Implementation of peripheral devices. Creat-ing and using bus functional models in verification. Binding the custom peripheral device with high lev-el programming language.

Project:

1. Implementation of mundane devices like advanced alarm clocks, timers, cycle computers etc. Stu-dents are supposed to implement software layer of the project that binds together simple hardware devices like displays, keyboards and other sensors into fully functional system. The attention is paid to simplicity of use and correct user interface simplicity.

2. Implementation of custom hardware device that supports operation of main design problem. Usually it is a specialized interface unit or arithmetic operation support device. Important part of the design concerns creating, modeling, synthesizing, implementing the device and linking it with microprocessor. The hardware component is linked with software operating by preparing appropriate declaration and drivers. Finally the component is used inside the design to proof its functionality.


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References:

1. Wayne Wolf Computers as Components: Principles of Embedded Computing Systems Design 2. M. Morris Mano, Charles R. Kime Logic and Computer Design Fundamentals. 3. Steve Furber ARM System-on-chip Architecture 4. Niklaus Wirth Algorithms + Data Structures = Programs 5. Samir Palnitkar Verilog HDL


Subject: Project Management Code: CEIE_S1_56


Teacher: dr. Seweryn Spałek


none

Course objectives:

The course of Project Management sets out to teach the basic theory and core methodologies one needs to successfully manage projects or participate in a project team


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The lectures include the following topics:

I. The definitions of the following are discussed: 1. Project 2. Project Life Cycle 3. Project Team 4. Project Manager 5. Project Sponsor 6. Stakeholders

II. The definition of the success of the project is given.

III. The key areas of managing the projects are discussed:

1. Project Integration Management


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2. Project Scope Management 3. Project Time Management 4. Project Cost Management 5. Project Resource Management 6. Project Communications Management 7. Project Risk Management 8. Project Procurement Management

Project will cover the following topics:

1. Project Charter 2. Work Breakedown Structure (WBS) 3. Crtical Path Method (CPM)

References:

1. “A Guide to the Project Management Body of Knowledge”, Project Management Institute, Newtown Square, 2008.

2. Caupin G. (red.), “ICB – IPMA Competence Baseline”, International Project Management Association, Nijkerk, Netherlands 2006.

3. Goldratt E. M. “Critical Chain“, The North River Press Publishing Corporation, Great Barrington, USA 1997. 4. Office of Government Commerce (OGC), “Managing Successful Projects with PRINCE2”, TSO (The Stationery

Office), 2005. 5. Scott B., “The Art of Project Management”, O’Reilly Media, Inc, New York 2005. 6. Spałek S., “Critical Success Factors in Project Management. To Fail or Not to Fail, That is a Question!”, Proceed-

ings of PMI Global Congress, Project Management Institute, Newtown Square, USA 2005. 7. US Def. Dept. - MIL-STD-881A 8. Verma V. K., “Organizing Projects for Success“, Project Management Institute, Newtown Square, 1995.


Subject: Social Sciences III Code: CEIE_S1_57




Basic knowledge presented in the courses: Social Sciences I, Social Scinces II

Course objectives:

The main objective of this course is to make students familiar with the vast field of application of for-mal/mathematical/computational methods in the domain of social sciences while stressing both the theoretical and the practical relevance of these applications.


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1. Challenges for social sciences in the time of globalization. How computers can help to overcome some barriers social sciences face.

2. Artificial intelligence and artifical life - ideas to be both applied in and adapted to social sciences. 3. Basic ideas of game theory. Prisonne's dilemmma. 4. Computer simulations in studying more complex forms of prisonner's dilemma. 5. The concept of artificial societies. 6. Raports to the Club of Rome as an example of computer modelling of global social processes

References:

1. Joshua Epstein, Robert Axtell; Artificial Societies. Social Science from the Bottom Up;The MIT Press, Cam-bridge (Mass.) 1996

2. William Poundstone; Prisoner's Dilemma; Doubleday, New York 1993 3. Peter Convey, Roger Highfield; Froniters of Complexity. The Search for Order in a Chaotic World; Ballantine

Books 1996


Subject: Computer Graphics Code: CEIE_S1_61


Teacher: prof. Konrad Wojciechowski


Computer Programing, Algebra and analytic geometry, Fundamentals of computer programming

Course objectives:

The course aims to provide the theoretical basis and the resulting 3D computer graphics algorithms,

and selected topics of 2D computer graphics as well as providing the necessary practical experience

acquired in result of the implementation of algorithms in the laboratory exercises. The lecture will ena-

ble students to get in touch with modern solutions in the field photo-realistic 3D graphics offered in

world literature, create their own solutions to the projects as well as understanding fundamental condi-

tions of modern computer animation


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Lecture:

• Basic math: vector space, Hilbert and affine. Frame, representation of the vector and the point. Representation in homogeneous coordinates. Transformations resulting from the choice of rep-resentation of the frame. The structure of the matrix transformation. Sample matrices for trans-lation, rotation, scaling of the frame.

• Parameterization of the orientation, Euler angles, axis angle, quaternions. Equation of quaterni-ons,

• interpolation between quaternions, quaternion curves. The relationship between parameteriza-tions.

• Geometric modelling of volume and surface. Parametric curves and surfaces. Analytical and ge-ometric continuity. Bezier curves, B-spline, NURBS. Definitions, basic properties, determining the point on the curve, fold

• node, the weight of the control points. Parametric surfaces created from parametric curves. Pa-rameterization of the surface and texture. Junction patches of surface. Projecting the 3D to 2D. Types of projection. Projection matrix

• perspective. Volume / pyramid of vision. Classic trim to the pyramid of view. Pruning in homo-geneous coordinates. Shadowing algorithms.

• Rasterization algorithms.

• Texturing the basic concepts and application of textures, 2D texture and 3D texture procedure.

• Modelling of light using RGB representation. Components of the lighting heuristic approach. Techniques Gouraud'a and Phong, modelling of light including physics. Radiometry and its sub-sidiaries. BRDF and BSSRDF equation

• rendering versions of integrating the solid angle and the surface of the stage. Techniques solving the equation rendering. Monte Carlo method and its versions reduce variance estimate. Map a RGB colour to coordinate. Photon maps. Method energy balance.

• External devices used in computer graphics systems, the basic input devices, output devices to create a permanent copy machine displaying images, methods of storage and display.

• Modelling the colour used in computer graphics: RGB, CMY, CMYK, HSV, HLS, YUV, YCbCr.

Laboratory:

• Raster algorithms

• Clipping i windowing

• 3D Transformations

• Hidden surface removal

• Illumination models

• Raytracing


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• Object detection 1

• Object detection 2

• Bone animation

• Collision detection

• Particle effects

• Pixel and vertex shaders

References:

1. John F. Hughes, Andries van Dam, Morgan McGuire, David Sklar, James D. Foley: Computer Graphics:

Principles and Practice (3rd Edition) 2. Peter Shirley: Fundamentals of Computer Graphics


Subject: Embedded Systems Code: CEIE_S1_62


Teacher: dr. Krzysztof Tokarz


Theory of logic circuits, Digital circuits, Microprocessor systems

Course objectives:

Main goal of the course is to present elements of microprocessor and embedded systems like: micro-processors, memories, buses, peripheral devices. PC computer elements are also presented. The process of embedded system development is presented with attention on proper choice of hardware elements, operating system, programming methods. Methods of hardware-software design with co-design is pre-sented. Specification and documentation preparation according to IEEE standards is also presented as important part of system development process


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Lecture:

Introduction to microprocessor and embedded systems. Definition, classification and development methods of embedded systems. Elements of embedded system: microprocessor, microcontroller, mem-ories, peripheral devices.

Parallel and serial input and output devices, analog to digital and digital to analog converters, serial synchronous and asynchronous communication. Elements of microcontroller: processor unit, RAM, Flash, EEPROM memories, timers, watchdog, brownout detector, communication devices, ports. Con-necting external devices to microprocessor and microcontroller. Interrupt controllers, DMA controllers. Programmable logic devices, IP cores. Examples of modern microcontrollers.

Operating systems for embedded systems, RTOS, cooperative and preemptive multitasking. Writing applications without operating system, superloop, interrupt driven software, finite state machine, ex-amples of implementation.

Requirements for embedded system, IEEE standards for embedded system specification and documen-tation. Stages of system development: requirements analyze, general design, subsystem design, subsys-tem implementation, integration, testing, documentation, development errors.

Methods of hardware-software partitioning, co-design, selection of hardware elements. Hardware driv-ers.

Laboratory:

• In circuit emulators, debugging in embedded systems. Simulators. 8051 microcontroller.

• Serial synchronous data transmission. TWI, SPI.

• AVR microcontrollers, writting programs in assembler and C

• Simple programmable logic devices, Abel language.

• Interrupt controllers. Interrupt priorities.

• Digital signal processors.

• Example of cooperative real-time operating system

References:

1. Embedded systems : architecture, programming and design / Raj Kamal. - Boston [etc.]: McGraw Hill Higher Education, cop. 2008.

2. Handbook of real-time and embedded systems / ed. by Insup Lee, Joseph Y-T. Leung, Sang H. Son. - Boca Raton ; London ; New York : Chapman & Hall/CRC, cop. 2008.

3. Networking and internetworking with microcontrollers / by Fred Eady. - Burlington, Ma ; Oxford : Newnes, cop. 2004



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Subject: Databases Code: CEIE_S1_63


Teacher: dr. Paweł Kasprowski


Basic knowledge of any programming language.

Course objectives:

The purpose of the subject is to teach students how to develop and use modern database systems.


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Lectures

• Usage of databases – functions and architecture of Database Management System (DBMS).

• Relational model – relations, relationships, keys.

• Relational algebra – selections, projections, joins.

• Structured Query Language (SQL) - Data Definition Language (DDL), Data Manipulation Lan-guage (DML), Data Query Language (DQL).

• Searching in relational database using SELECT phrase.

• Advanced searching - grouping data, aggregations, views, outer joins, nested queries, correla-tions.

• Preserving database referential integrity - primary and foreign keys.

• Security in databases - users, roles, rights.

• Developing databases – functional dependencies, normal forms, ERD diagrams.

• Concurrent access to databases – locks, transactions, isolation levels.

• Programming in databases – stored procedures, functions, triggers.

• Architectures of modern database systems – client-server and 3-trier architectures.

Laboratories:

1. SQL language 2. Advanced SQL language – SELECT statement 3. SQL DDL/DCL – preparing users, rights, preserving referential integrity 4. Transactions and isolation levels 5. Constructing triggers and stored procedures


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6. Preparing Entity Relationship Diagrams

References:

…


Subject: Operating Systems Code: CEIE_S1_64


Teacher: dr. Przemysław Skurowski


Theory of computer science, Computer programming

Course objectives:

The goal of a course is to introduce students into the cotemporary operating systems which are consid-ered as environments of effective resource managing environment and user interface layer in modern computer systems. During the course students will get knowledge on configuring and administering of operating systems and on the solutions of classical resource management problems with special focus on processor and memory related tasks.


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Lectures:

Topics are related to the general purpose OS and to the general problems present in any kind of OS:

1. Basic concepts in OS topic: definition and fundamental roles, effectiveness criteria, processes, re-sources, types and architectures of OS

2. OS structure – kernel, drivers, tools, subsystems, interfaces and utilities. 3. Resource management and Inter process communication (IPC), concurrency, interference, mutual

exclusion, process synchronization and communication means, semaphores, mailboxes 4. Algorithms and mechanisms of a CPU time sharing 5. Memory organization and allocation, virtual ,memory, memory protection 6. I/O devices handling in the OS 7. File systems – physical and logical representation


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8. Hard disk head movement planning 9. Basics or realtime and distributed OS 10. Description of Windows and Linux OS

Laboratory topics

Windows 7 - Installation Windows 7 – Administrative scripts Windows 7 – Users, groups, permissions Windows 7 – Basic network Windows 7 – System services Windows 7 – Remote access Linux Ubuntu – Installation and configuration basics Linux Ubuntu - Users, groups, permissions Linux Ubuntu - Processes Linux Ubuntu - Basic network Linux Ubuntu – multi system collaboration Linux Ubuntu – Fundamentals of Bash programming

References:

1. A. Silberschatz, J.L. Peterson, G. Gagne, Operating Systems Concepts, Wiley 2. W. Stallings, Operating Systems. Pearson 3. A. S. Tanenbaum, Modern Operating Systems. ed 2, Prentice-Hall Inc., 2001. 4. W. R. Stevens, Advanced Programming in the UNIX Environment, Addison-Wesley, 1992


Subject: Algorithms and Data Structures Code: CEIE_S1_65




It is assumed, that the student has an elementary knowledge of mathematics at the secondary level and logical thinking skills, including abstract thinking. An additional requirement is knowledge of English and the ability to write and understand simple programs.

Course objectives:


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The aim of the course is to introduce students into advanced topics of algorithms and data structures. We present algorithms for sorting, searching, operating on graphs, trees. We discuss selected data structures: binary trees, heaps, priority queues. Students after this course should be able to analyze the complexity of algorithms, adapt known algorithms for new problems etc. Topics are illustrated with many examples. The course consists of lectures and classes (exercises). Classes are obligatory.


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Lectures

• Introduction, complexity of algorithms

• Simple sorting algorithms: selection sort, insertion sort

• Quick sort, k-selection

• Divide and conquere

• Heaps and their use: heap sort, priority queues

• Sorting with comparisons

• Sorting of specific data: integers, bucket sort, radix sort

• Binary Search Trees

• Hashing: chaining, open addressing, MPHF

• Exhaustive search

• Greedy algorithms

• Graphs, BFS, DFS

• The Dijkstra algorithm, the Floyd-Warshall algorithm

• Dynamic programming

• Pattern search

Laboratories:

Will follow the topics presented during the lectures.

References:

…



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Subject: Robotics Code: CEIE_S1_66


Teacher: dr. Aleksander Staszulonek


Before this course student should attend lectures on mathematical analysis, differential equations, al-gebra, physics and microcomputer programming. Strongly recommended is knowledge of assembly and C language programming. Knowledge of Lagrange equations is significant advantage as well. Additional-ly Mathematical analysis, Physics, Mechanics, Syste’s Dynamics.

Course objectives:

Course is part of specialized curriculum content and is related to education in areas of robotics, embed-ded systems, robot control systems and servomechanism control. The goal of this course is to provide students with the main elements of robot theory: mathematics, programming and control. The theory is complemented with laboratory exercises familiarizing students with practical aspects or robot control systems structure, control algorithms and programming.


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Lecture:

Program of the course includes: introduction to C and assembly language programming of embedded control systems, homogenous transformations, derivation of kinematic equations, kinematic equations solution, dynamics, control, trajectory execution and programming.

Section dedicated to homogenous transformations contains description of basic definitions like vectors, planes, coordinate frames, basic transformations, relative and inverse transformations, equivalent angle and axis of rotation. Section dedicated to derivation of kinematic equations deals with different coordi-nate systems, specification of A matrices for manipulator’s prismatic and rotational links, specification of T matrices in terms of A matrices. As the example, kinematic equations of Stanford and Elbow Ma-nipulators are derived. Methods leading to the solution of kinematic equations are described and solu-tions for Stanford and Elbow manipulators are presented. The dynamics of robot manipulators is then presented using Lagrangian equations. Requirements imposed on robot control systems are presented and set point and tracking control problems defined. Basic theory and methodology of robot control is presented on the examples of most frequently applied control structures. PID and sliding mode control-lers are discussed.

Laboratory:

The laboratory exercises include the following tasks:

1. Robot control system structure and servomechanism control


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2. Introductory aspects of C and assembly language programming of embedded controllers 3. Programming of communication between embedded system and servocontroller 4. Programming of single degree of freedom controller with digital PID algorithm 5. Implementation of desired trajectory specification 6. Programming of 6 degrees of freedom embedded controller and motion coordination 7. Synchronization of the robot.

References:

1. Richard P. Paul: “Robot Manipulators: Mathematics, Programming, And Control”

2. Itkis U.: Control Systems of Variable Structure


Subject: Mixed-signal circuits design Code: CEIE_S1_67


Teacher: dr. Jerzy Fiołka


Course attendants have to possess basic knowledge in algebra, physics, circuit theory, electronic, signal processing, digital circuits. Students are also supposed to possess practical skills concerning design, simulation and construction of electronic systems.

Course objectives:

The main purpose of this course is to provide theoretical and practical knowledge to the students about the design of mixed-signal circuits.


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Lecture:

Mixed signal circuits design lecture covers the following topics: 1) Definitions and basic features of mixed-signal circuits; 2) Hardware and software subsystems od mixed-signal systems; 3) CAD tools for circuits design and simulation; 4) Sampling of continuous-time signals; 5) Operational amplifiers: types, structures, operation, parameters, applications;


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6) Analog filters: fundamentals, design, simulation, realizations; 7) A/D converters: types, principle of operation, parameters; 8) D/A converters: types, principle of operation, parameters; 9) Sensor signal conditioning; 10) Phase-locked loop (PLL): principle of operation, parameters, applications; 11) Switched capacitor circuits (SC): principle of operation, parameters, applications; 12) Direct digital synthesis (DDS): principle of operation, parameters, applications; 13) Power supplies: types, structures, simulation, design 14) Interfacing Analog to Digital Circuits; 15) PCB Design for mixed-signal circuits;

Project:

Group of students (max. 3 people) choose project concerning design, simulation, construction and de-velopment of a mixed-signal circuit. The final result of the project is a working circuit and documenta-tion.

References:

1. Tietze U, Schenk Ch.: „Electronic Circuits: Handbook for Design and Application”, Springer; 2nd edi-tion

2. Hill W, Horowitz P.: „The Art of Electronics”, Cambridge University Press; 3 edition, 2011 3. Savant C.J, Roden M.S, Carpenter G.L .: „Electronic Design: Circuits and Systems”, Benja-

min/Cummings, 1991

4. Doboli A, E.H Currie, „Introduction to Mixed-Signal, Embedded Design”, Springer; 2011


Subject: CAD of control systems Code: CEIE_S1_71


Teacher: prof. Marian Błachuta


Algebra and Analytic Geometry, Introduction to System Dynamics, Control Fundamentals, Microproses-sor Systems

Course objectives:

The objective of the lectures is to give fundamentals of numerical procedures and programs used for Computer Aided Design in Control Systems, while laboratory aims at fast prototyping tools used to de-


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sign embedded controllers for selected laboratory plants. The theory is complemented with practical aspects of embedded control system.


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Lecture:

1. Introduction: History of CADCS, stages of design process, evolution of design tools, MATRIXx and MATLAB approaches to the design process.

2. Selected Problems of Linear Algebra: norms of vectors and matrices, typical norms, relation-ships between norms of vectors and matrices, typical induced norms. Particular types of matri-ces and their properties, orthogonal matrices and their properties, complex matrices, normal matrix, Hermitian matrix, unitary matrices and their properties, Schur matrix and eigenvalues of a matrix, unitary similarity transformation to a Schur matrix

3. Selected issues of numerical methods: sources of errors in numerical computations, floating point arithmetic and its precision, IEEE Standard 754, exceptions, overflow, underflow, round-ing errors. Backward stability and problem conditioning, condition numbers.

4. Selected numerical algorithms: LU factorization, solving systems of linear equations, condition number of a matrix. Hausholder transformation an QR factorization. Least-squares problem and its solution via QR factorization. Hessenberg form of a matrix. Eigenvalues computation via QR algorithm, generalized eigenvalues and QZ algorithm. Singular Value Decomposition, its proper-ties and applications. Computing matrix exponent and matrix logarithm. Overview of MATLAB matrix functions.

5. Numerical procedures for control: algorithms for conversion from state-space to transfer func-tion form, Markov parameters, canonical representations of state-space models and their rela-tionship with transfer function, transformations between continuous-time and discrete-time systems, δ - operator models, computation of frequency plots, van Dooren algorithm for investi-gation of the structure of controllability and observability, controllability and observability Gramians, balanced realizations, model approximation, Lyapunov equations and associated nu-merical algorithms

Laboratory:

1. Introduction. Configuration of environments Simulink and CodeWarrior. 2. Interface RS232. Fundamentals of programming. 3. Data transmission in CAN network. 4. PWM control method. Reading analog values. 5. Modeling of the DC motor dynamics. 6. PID discrete regulation. 7. Prototyping of control system.


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References:

1. P.Hr. Petkov, N.D. Christov, M.M. Konstantinov Computational methods for linear control systems, Pren-

tice Hall International, 1991;

2. G.W. Stewart: Matrix Algorithms, vol. 1. Basic Decompositions, SIAM, 1998;

3. Phillips CL., Harbor R.D.: Feedback Control Systems (Third Edition) Prentice Hall, 1996.

4. Goodwin G.C., Graebe S.F., Salgado M.E.: Control Systems Design, Prentice Hall, 2001

5. J. Maciejowski: Multivariable Feedback Design, Addison-Wesley, 1989


Subject: Hierarchical control Code: CEIE_S1_72


Teacher: prof. Krzysztof Fujarewicz


Students should have completed courses of: Mathematical analysis, Optimization and decision making, Control fundamentals.

Course objectives:

This course is addressed to students interested in systems analysis, control engineering, management and decision making. It covers basic methods used in solving control and optimization problems associ-ated with large-scale and complex systems. After completing the course student has basic knowledge in optimization and control of large scale systems. This knowledge consists of methods of analysis of com-posite systems, solving structured optimization problems and designing hierarchical and decentralized feedback systems.


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Lectures:

1. Introduction and the terminology. Large scale systems, complex systems, decomposition coordina-tion. Different types of hierarchical structures: multilayer structure and multilevel structure.


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2. Mathematical models of systems. Static models. Mathematical model of the planning problem for the oil refinery. Dynamical models. Concentrated-parameter models and distributed-parameter models.

3. Stirred-tank continuous-flow reactor. Types of variables in hierarchical structures: state variables, manipulated and input variables. Constraints. Description of complex systems, subsystems, the structure matrix. Static characteristics.

4. Multilayer systems. Decomposition. Stabilization layer and its structure: output and control varia-bles, assignment of variables. Multilayer structure of control and optimization for continuous-flow reactor.

5. Multilevel optimization systems. Simplex method. Decomposition of linear programming problems, Dantzig-Wolf method. Decomposition and coordination in nonlinear static optimization problems. Direct method of coordination. Induced constraints. Direct method with penalty function. The price method. Dynamic programming. Mixed methods.

6. Identification and optimization of nonlinear dynamical systems. Sensitivity analysis. Gradient derivation. Adjoint systems. Gradient calculation with the adjoint system. Neural models. Hybrid models. Gradient-based identification and optimization of complex nonlinear systems.

Laboratory:

1. Continuous-flow reactor. The aim of the exercise is modeling of a stirred-tank continuous-flow re-actor, finding its static characteristics, and designing control system for the reactor.

2. Oil refinery optimization. The aim of the exercise is to solve the problem of optimal production in an oil refinery. The problem is formulated as a linear programming (LP) problem which is solved using Matlab software.

3. Direct method of coordination. The aim of the laboratory exercise is to apply the direct method of coordination to a complex static system composed of three cross-coupled subsystems.

4. Price method of coordination. The aim of the laboratory exercise is to apply the price method of coordaination to a complex static system composed of three crosscoupled subsystems.

5. Dynamic programming. The aim of the exercise is to apply dynamic programming method in order to optimize an example of multistage process.

6. Identification of complex systems. Students make use of the sensitivity analysis to parameter esti-mation of nonlinear Hammerstein model.

7. Control of complex systems I. During the laboratory students perform gradient-based optimization of close-loop control system.

8. Control of complex systems. Students make use of the adjoint sensitivity analysis in order to gradi-ent-based optimization of a control signal for given non-linear system.

References:

1. L.S. Lasdon, Optimization theory for large systems, Mac-Millan, 1970.

2. H. Tamura, T Yoshikawa, (eds.) Large-scale systems. Control and decision making, Marcel Dekker, 1990.

3. J. Lunze, Feedback control of large-scale systems, Springer-Verlag, 1992.


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Subject: Applied digital signal processing Code: CEIE_S1_73


Teacher: prof. Marek Pawełczyk


Calculus and differential equations, Fundamentals of computer programming, Computer programming, Introduction to system dynamics, Numerical methods, Fundamentals of signal processing. It is assumed that students have basic knowledge on: differentiation, integration, Laplace transform, Z transform, Fourier transform, transfer function, dynamic system modeling, numerical algorithms, Matlab environ-ment.

Course objectives:

The aim of this lecture is to present issues in modern signal processing techniques with focus on appli-cations. It constitutes a pedagogical compilation of fundamentals, algorithm forms, behavioural insights, and application guidelines. The intertwining of theory and practice is demonstrated by numerous ex-amples and verified during project exercises.


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Lecture

In the era of rapid development of microprocessors, Digital Signal Processing (DSP) gains significant interest and finds applications in many fields of everyday life. DSP plays an increasingly central role in the development of telecommunications and information processing systems, and has a wide range of applications in multimedia technology, audio-visual systems, cellular mobile communications, adaptive network management, radar and ultrasonic systems, pattern analysis, medical signal processing, finan-cial data forecasting, decision making, etc.

The lecture touches the following subjects:

1. Sampling, analogue-to-digital and digital-to-analogue conversion, quantization

2. Correlation analysis

3. Fourier decomposition and Fourier transforms

4. Signal windowing and spectral analysis


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5. Conversion of sampling frequency and multi-rate signal processing

6. Finite and Infinite impulse response filters

7. Wiener and Kalman filters

8. Adaptive filters

9. Signal decomposition and forecasting

10. Fundamentals of electroacoustics

11. Active suppression of noise and vibration

12. Echo generation and cancellation

13. Speech intelligibility enhancement

14. Speech recognition and speaker identification

15. Ultrasonic signal processing

16. Vibration and acoustic signals processing for condition monitoring of working machines

Laboratory

Different project topics related to digital signal processing are offered each year. Some of them are per-formed individually, and some of them in groups of a few students. Students may suggest topics by themselves.

Exemplary topics are:

- Speech intelligibility enhancement

- Condition monitoring with audio or vibration signals

- EKG signal processing

- Active noise control

- Active vibration control

References:

1. B. S. Braun: Discover Signal Processing. An Interactive Guide for Engineers, Wiley, 2008

2. K. Shin, J.K. Hammond: Fundamentals of Signal Processing for Sound and Vibration Engineers, Wiley, 2008

3. V.K. Madisetti, D.B. Williams: The Digital Signal Processing Handbook, IEEE Press, 1998

4. S.K. Mitra, J.K. Kaiser: Handbook for Digital Signal Processing, J. Wiley & Sons, NY, 1993.

5. S.J. Elliott: Signal Processing for Active Control, Academic Press, 2001

6. J. Jan: Digital Signal Filtering, Analysis and Restoration, TJ Int. Ltd, 2000

7. J.S. Bendat, A.G. Piersol: Engineering Applications of Correlation and Spectral Analysis, Wiley, 1993.

8. S.W. Smith: The Scientist and Engineer's Guide to Digital Signal Processing, http://www.dspguide.com/.


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Subject: Computer architecture Code: CEIE_S1_74


Teacher: dr. Zghidi Hafed


Theory of Computer Science

Course objectives:

The lectures are to familiarize students with main concepts related to computer architecture. They pre-sent the main directions of development of computer architecture, provide representative examples of computer organization. The main part of the lecture is to present the architecture of modern processors and parallel computers. The purpose of the laboratory is practical and introduce students to various computer architectures, different operating systems and technologies of parallel and distributed pro-gramming. Students are familiarized with computers based on Sparc processors, PowerPC, x86, running under control of different operating systems (Windows, Linux, Sun Solaris, OS/400).


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Lectures

The history of the development of computer architectures: the first computers, the impact of electronic technology in computer architecture, subsequent generations of computers. Complex Instruction Set Computers (CISC). Reduced Instruction Set Computers (RISC): bases, implementation of RISC I comput-er. Pipelining, the problem of implementing jump instructions (jumps, delayed, branch prediction) and the problem of dependent data (changing the instruction order). Superscalar architecture and VLIW architecture. The specificity of the problems of pipelined instruction execution with dependent argu-ments in superscalar architecture. Renaming of registers. Examples of the superscalar processor archi-tectures: UltraSPARC, Motorola, PowerPC, POWER. Hardware support for multithreading: fine-grained multithreading, coarse and concurrent.

Architecture of parallel computers. Classification of parallel systems - forms of parallelism: instruction-level parallelism and parallelism of processors, the Flynn classification, other classifications. Vector Computers: scalar and vector instructions - a vector computer concept, a review of vector instructions. Examples of vector computers, the use of vector computers. Array computers: the general approach, the


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model in the implementation of SIMD commands, interconnect network, examples of array computer. SIMD model in modern superscalar processors. Graphics Cards and the CUDA architecture. Multi-threaded - SIMT model. multiprocessor systems

: Systems with shared memory: cache coherence, MESI protocol different ways system elements con-nections - a common bus, multiple bus systems, cross-bar, multiport memory, multi-stage switch, non-blocking Clos network. NUMA architecture systems. Examples of commercial shared memory systems. Distributed memory systems: MPP model, connecting networks, the role of the processor in communi-cation and transmission - the first and second generation, the development of systems with distributed memory systems: example of Intel and IBM processors. MPP systems on the TOP500 list. Clusters: defi-nition and properties. Network connecting clusters: Topology "fat tree" network Infiniband. Beowulf Clusters. High-performance clusters. Physical construction of the clusters: rack and blade systems. Ex-amples of clusters. MPP clusters in Top 500 list. Clusters with high reliability. Factors constituting high reliability of the clusters: Redundant nodes, access to shared resources, mechanisms for controlling the operation of nodes. Heterogeneous computer systems - conventional CPU processors support by GPUs.

Laboratory

A detailed set of laboratory exercises:

AS/400 – Communication and data access on the AS/400 system

Sparc - Sparc processor low-level programming

CUDA - parallel programming of graphics processing units (GPUs) in C / C + + with corresponding ex-tensions

PVM - Parallel Programming with dynamic allocation of tasks using messages passing architecture us-ing the parallel virtual machine

Mosix – Use of a cluster of workstations for parallel computing and balance load

JavaSpaces – Parallel programming using shared and distributed memory in Java

References:

A.S. Tanenbaum, Structured Computer Organization


Subject: Digital circuits design Code: CEIE_S1_75


Teacher: dr. Tomasz Garbolino



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Course attendants are supposed to have general knowledge about the design of combinational and se-quential digital circuits. They must also have practical skills in assembling such systems. It is assumed that students have passed the following subjects: Theory of Logic Circuits, Digital Circuits.

Course objectives:

The main objective is to provide students with basic knowledge about the design of digital systems us-ing hardware description language VHDL. During the course students should acquire basic knowledge about VHDL data structures and language constructs used for modeling combinational and sequential digital circuits. They should also develop skills in modeling in VHDL simple digital systems as well as the ability to simulate, debug and synthesize models written in that language.


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Lectures

The main objective of the course is to familiarize students with the basic aspects of designing digital circuits using VHDL. The lecture includes - among others - data structures and language constructs that are useful in modeling for synthesis and verification of digital circuit design. During the course students acquire the basic knowledge of ASIC and FPGA circuits as well as the VLSI design methodology.

1. Basic information about ASIC and FPGA circuits.

2. Introduction to VLSI design methodology.

3. VHDL – overview and application field.

4. VHDL language and syntax: general language properties, identifiers, naming convention; structural elements; data types and operators; concurrent and sequential statements; subprograms; RTL-style; behavioral, dataflow and structural modeling.

5. Simulation: sequence of compilation; simulation flow; process execution; delay models

6. Introduction to design verification – writing simple testbenches

7. Synthesis: stages of the synthesis process, VHDL constructs used in the modeling for the synthesis, best practices for modeling for the synthesis.

8. Examples illustrating how to design VHDL models of typical digital components (e.g. multiplexers, coders/decoders, counters, shift registers, FSMs, etc.).

Laboratory

During laboratory classes students design models of typical components of digital systems. Then they simulate the behavior of the models to verify the correctness of their operation. In the next step, stu-dents carry out the synthesis of the models and their implementation in an FPGA device located on a demo board.


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1. Getting familiar with design tools and the demo board. 2. Multiplexers, coders / decoders, displaying characters on a 7-segment display. 3. Combinational circuits that perform binary-to-decimal (decimal-to-binary) number conversion and

binary-coded-decimal (BCD) addition. 4. Latches, Flip-flops, and Registers. 5. Counters. 6. Clocks and Timers. 7. Adders, Subtractors, and Multipliers. 8. Finite State Machines. 9. Memory Blocks.

References:

1. P. J. Ashenden, “The Student's Guide to VHDL, Second Edition (Systems on Silicon)”, Morgan Kaufmann Pub-

lishers, 2008

2. Sudhakar Yalamanchili, “VHDL Starters Guide”, Prentice Hall, 2005



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Subject: Design for manufacture Code: CEIE_S1_76


Teacher: prof. Zbigniew Rymarski


It has been assumed that student before attending this course have basic knowledge in designing ana-logue and digital microprocessor based devices.

Course objectives:

The main goal of the lectures is presenting to students the problems of the electronic devices designing taking in care the manufacturing requirements (the Design for Manufacture methodology) and appoint-ing

how to design the device to make possible to manufacture it in technologies granting the high yield with the reasonable cost simultaneously filling the assigned quality requirements.

The aim of the laboratory project is to make students familiar with creating the device documentation in the EDA environment (it was chosen Altium Designer) – the device scheme (CAE software), the print-ed circuit board design (CAD software) and files controlling the photoplotter (RS274X standard) and the numerically controlled drill (CAM software). During laboratory students design a simple micropro-cessor system that can be mounted in the standard 3U rack case using the proper design rules (concern-ing EMC, the tracks width, clearance and other design rules) and manufacturing rules of the chosen PCB manufacturers.


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Lecture

1. Introduction to the Design for Manufacture methodology

2. Design for Quality methodology, the Six Sigma program

3. The materials in the electronic devices manufacturing

3.1. Types of the PCB, their substrates, the solder mask and finishes

3.2. The controlled impedance PCB

3.3. The eutectic PbSn solder and lead free solder, RoHS requirements

3.4. The solder paste

3.5. Conducting adhesives

3.6. Fiducial marks


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3.7. The influence of the IC case type on the manufacturing technology

4. Technologies of electronic manufacturing

4.1. PCB manufacturing technology

4.2. Testing of the bare PCB

4.3 The solder paste printing on the PCB

4.3. Sticking SMDs to the PCB

4.4. How to avoid damaging the electronic devices by the ESD

4.5. Pick and place machines

4.6. Wave soldering and selective soldering

4.7. Reflow soldering

4.8. Typical soldering problems and defects

4.9. PCB cleaning

4.10. Conducting adhesives applications

4.11. Functional testing and inspection of the mounted PCB

4.12. Manufacturing Defects Analysis

4.13. PCB’s rework

5. Parameters of the basic passive components

6. Electric and mechanical components in the electronic manufacturing

7. PCB design methodology filling EMC requirements

8. Methodology of using CAE/CAD/CAM software in the design documentation creating and the nu-merically controlled devices for PCB manufacture programming.

Laboratory

Student creates the scheme and the 2 layer PCB layout design (in Altium Designer) of the simple micro-processor system that can be mounted in the standard 3U rack case using the proper design rules (con-cerning EMC, the tracks width and clearance standards) and manufacturing rules of the chosen PCB manufacturers. He generates the files for programming the photoplotter (RS274X files) and the numeri-cally controlled drill. Teacher begins each of the laboratory classes with the presentation of some basic actions in the EDA software. Teacher appoints the set of components that should be used in the design (all the necessary manuals of them are enclosed in the instruction). The PCB design (3U-160 standard) should fill requirements placed in the instruction. Student should finally discuss his design that has to fill the formal demands from the instruction. The grade of the project depends on EMC of the PCB and its overall quality.

References:



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Subject: Social and professional challenges of computer science Code: CEIE_S1_77


Teacher: dr. Jacek Frączek


none

Course objectives:

The aim of the course is to provide basic knowledge in the following areas:

1. Professional and Ethical Responsibility 2. Ethical Codes and Codes of Conduct 3. Computer Systems Risks and Responsibilities 4. Intellectual Property Rights: Legal Issues and Regulations, Patents 5. Fundamentals of Privacy


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Lecture topics:

1. Professional and Ethical Responsibility 2. Ethical Codes and Codes of Conduct 3. Computer Systems Risks and Responsibilities 4. Intellectual Property Rights: Legal Issues and Regulations, Patents 5. Fundamentals of Privacy

References:

1. Wikipedia portal: http://en.wikipedia.org 2. ACM Code of Ethics and Professional Conduct: http://www.acm.org/about/code-of-ethics



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Subject: Software engineering Code: CEIE_S1_78


Teacher: dr. Przemysław Szmal


Fundamentals of Computer Programming, Computer Programming

Course objectives:

The course is aimed at a presentation of selected topics falling within the scope of Software Engineering with particular attention to those that relate to the life cycle of limited size software units. Among other things, students become generally familiar with the design issues of information systems using modern methodologies and CASE tools


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Lectures

Introduction, origin and object of concern of Software Engineering. Software crisis, software life-cycle models. Outline of systems engineering, I(nformation) T(echnology) project management. Strategy phase. Requirements definition phase. Application of the CASE tools in the strategy and the require-ments definition phase. The analysis phase, the system design. Structural methodologies. Object meth-odologies (prior to UML). UML language and methodology. Implementation and testing. Software relia-bility.

Laboratory (List of laboratory classes):

I. Software effectiveness estimation and improvement.

II. Software development stages:

1. Requirements modeling. Introduction to project methodics. Introduction to a selected CASE tool. Elaboration of preliminary requirements specification.

2. Vocabulary and structure modeling. Vocabulary identification, elaboration of the project dictionary. Vocabulary integrity checking.

3. Use-case model. Use-case workshop. Use-cases against requirements matching. 4. Use-case implementation. Selecting a fragment for implementation. Interactions construction. 5. Code design and generation. Design of classes and interfaces for selected use-case implementation.

Code generator parameterization. Code generation. 6. Compilation and implementation. Compiled project template activation and debugging. Selected

interaction implementation.


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References:

1. Sommerville, I: Software Engineering, (8th Edition),

2. Booch, G., Rumbaugh, J., Jacobson, I., The Unified Modeling Language User Guide


Undergaduate optional courses - subject syllabi

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CEIE - UNDERGRADUATE PROGRAMME

OPTIONAL COURSES – SUBJECT SYLLABI

The minimum number of students required: 12 persons


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List of the courses offered in 2013/2014

6th semester of CEIE (Makrokierunek) BSc programme

Industrial measurements CEIE_S1_81

Design & Configuration of LAN infrastructure CEIE_S1_83

Industrial Process Visualization CEIE_S1_84

Constraint Logic Programming CEIE_S1_88

Object oriented programming CEIE_S1_92

Reliability and Intrinsic Safety CEIE_S1_93

802.11 Wireless local area networks CEIE_S1_95

Computer Networks II CEIE_S1_96

Fiber Optics CEIE_S1_97

Automotive Electronics CEIE_S1_98

STM32 family ARM microcontrollers programming CEIE_S1_99

Radio frequency identification systems CEIE_S1_100

Digital System Design in Verilog HDL CEIE_S1_101

Program-based digital control systems CEIE_S1_102

GPU programming and architecture CEIE_S1_103

7th semester of CEIE (Makrokierunek) BSc programme

Face recognition and biometric systems CEIE_S1_94

Industrial Control Systems Design CEIE_S1_90

Linux – advanced programming CEIE_S1_91

Electromechanical devices CEIE_S1_89

XML technologies CEIE_S1_87

Programming of mobile devices CEIE_S1_86

Programming LEGO Mindstorms NTX robots CEIE_S1_85

Robot vision CEIE_S1_82

Computer controlled systems CEIE_S1_80


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Subject: Computer controlled systems Code: CEIE_S1_80


Teacher: dr. Ryszard Jakuszewski


Computer Graphics, Computer Programming, Computer Networks, Operating Systems, Measurement Systems, Databases. It is assumed that the student knowns the basics of computer science. This lecture is suitable for students of all technical branches, which are interested in easy-to-use industrial automa-tion software.

Course objectives:

This course is designed primarily for students wanting to create advanced control and process monitor-ing systems. The students should obtain knowledge of theoretical fundamentals and of practical meth-ods used in modern SCADA systems and industrial automation software.


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Lecture

The world’s leading industrial automation software solutions, providing process visualization, data acquisition and supervisory control of plant floor operations are discussed and trained during labora-tory classes. This solutions give students the power to precisely monitor and control every aspect of manufacturing industry processes, as well as equipment and resources, resulting in faster response to production issues, less waste, improved quality, faster time-to-market with new products and in-creased profitability. The specialists who have acquired skills in SCADA systems are looked for in job market all over the world. The course teaches basic SCADA and HMI topics like: graphic design, data archiving, process database management, driver configuration, reporting, alarm strategies and securi-ty. The course is intended to provide the student a base level of proficiency using some of the Ameri-can software solutions and more advanced features. VBA scripting is covered primarily as a tool for automating tasks for the operator. The student will also become familiar with some of the tools and concepts available for optimizing and troubleshooting such software.

Basic topics:

• Introduction to Computer Graphics • Process Database - Development and Management • Advanced Graphical Objects - Signal Generators • Picture System Management • Trending and Archiving of Data


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• Industrial Databases (Proficy Historian) • Implementing Shortcut Keys • Tag Group Technology • Scheduling Tasks • Multilevel Security System • Communication with PLC Controllers • Alarming – Defining, Acknowledgement, Viewing and Printing • Network Solutions – Controlling In Computer Networks • Visual Basic for Applications in Industry Environment • Configuring SCDA Systems

More advanced topics:

• Troubleshooting of SCADA Systems • Windows and SCADA Security • Recipes In Beer Production • VisiconX Objects • Alarm and Event Archiving In Relational Databases • Electronic Signatures • Using ActiveX • Understanding Database Dynamos • OPC Servers and Clients In SCADA systems • Introduction to ADO DB and ODBC • Using SQL Database Tags • Reporting • LAN and Auto-Failover Redundancy • Using Terminal Servers

Laboratory

1. Animation of graphical objects; Development and management of industrial databases. 2. Signal generators; Tools and methods of picture development. 3. Presenting archived data on charts. 4. Shortcut keys and Tag group techonology. 5. Multilevel security system. Alarams – defining, management, acknowledgement, viewing and

printing. 6. Communication with PLC Controllers, ADO DB and ODBC.

References:

1. Technical documentations for SCADA systems. 2. Ryszard Jakuszewski, “Basic Programming of SCADA Systems”, Wydawnictwo Komputerowe Jacka Skalmier-

skiego, Gliwice 2009

3. Ryszard Jakuszewski: „Advanced Programming Solutions of SCADA Systems”, Wydawnictwo Komputerowe Jacka Skalmierskiego, Gliwice 2009.


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Subject: Industrial measurements Code: CEIE_S1_81


Teacher: prof. Stanisław Waluś


Physics, Mathematics, Fundamentals Metrology, Measurement Systems

Course objectives:

To acquaint the students with industrial measurements on the base of chosen values (flowrate, level, pH, conductivity), expressing of metrological properties, uncertainty calculations and using buses (for example - Profibus) for communication and data processing.


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Lecture

1. Introduction to industrial measurements. Evaluation of measuring instruments for steel works pro-cess – as an example of typical difficulties in measuring and controlling industrial process.

2. Practical advices and recommendations for one who can control a process.

3. Calculation and treatment of measurement errors: classification of errors, uncertainty, statistics in measurement, calculation of measurement error for no correlated and correlated values. Accuracy rating. Linearity (independent, terminal-based, zero-based).

4. The mathematical modelling of flowmeter sensors (role of the sensor in flow measurement, classifi-cation of flowmeter sensors, full-bore and sampling flowmeters, mathematical models of flowmeter primary device for various sensors (point, surface, segment, whole flow area).

5. Measuring instruments selection and evaluation on the example of flowmeter selection procedure.

6. Level measurement: classification of level measurement techniques, mechanical based level meas-urement, ultrasonic level sensors, nucleonic in level measurement.

7. Ionselective (ISE) measurements, pH measurements and conductivity measurements (concentra-tion measures; dissociation; membrane potential; Nernst equation; potentiometric measuring cir-cuit; ISE electrode; reference electrode; troubleshooting checklist; limit of detection; interference ions; Nikolsky-Eisnemnan equation; Measurement methods: direct potentiometry, know addition methods, flow injection analysis, titration; industrial and medical applications).


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8. Profibus overview (the main advantages and disadvantages of fieldbus system, the Profibus family applicable at all levels of automation, Profibus protocol, operation including device addressing, sta-tion types and network configuration, Profibus - designed for the hazardous environments).

Laboratory

1. Level measurements: Students will familiarize with level measuring techniques. There are two level transducers on the stand: FMD78 (the differential pressure transducer which can be programmed to level measurement mode) and FMP40 (the guided level radar). During laboratory students learn how to configure industrial level transducers. Students perform also different calibration procedures, check advantages and disadvantages of both level measurements methods.

2. Open channel flow measurements: Exercise is made on the open channel flow measurement laboratory stand. On this stand ultrasonic level meter is investigated. Students will learn about flow measurement with help of weirs and methods of communication and programming smart sensor.

3. Conductometry: Students learn about conductivity measurements. The ABB 4620 Industrial Conductivity Transsmiter is used during laboratory. Students make some measurements for conductivity standards and samples and perform analysis of measurements and uncertainty of measurements.

4. Profibus: Students task is to build up the software in LabVIEW via PROFIBUS RS-485 for: enumerat-ing measured value, execute several measurements on line, estimating the response time of measur-ing device, warning banner after crossing alarm value of methane concentration in air, growth of concentration of carbon dioxide, fall of oxygen concentration, etc.

5. HART: During laboratory students get acquaint with fundamental features of HART technology. Students use example of industrial HART intelligent transmitter to learn how to configure transmitter with the assistance of HART protocol and dedicated configuration software. Students learn how to create commissioning documentation - configuration control – element of meeting ISO9000 requirements.

6. Ion-selective measurements: Students get acquaint with ionselective measurement techniques: direct potentiometry, know addition methods and automatic determination of ionselective electrode's parameters. Students using laboratory Orion 930 Ionanalizer learn how in industry automatic laboratory measurements can be performed.

References:

1. Instrument Engineers’ Handbook, Process Measurement and Analysis, Vol. I, Lipták B. G. Editor-in-chief, ISA-The Instrumentation, Systems, and Automation Society, CRC Press, Boca Raton London New York Washington, D.C. 2003.



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Subject: Robot vision Code: CEIE_S1_82


Teacher: prof. Henryk Palus


The subject complements a basic knowledge of image processing acquired by students in the subject of Computer Graphics and Vision, and directs it to problems of automation and robotics.

Course objectives:

The course aims to familiarize students with state of the art in the field of vision systems used in auto-mation and robotics. As a result of the subject, students should be able to both design the vision system for a particular application, as well as to construct a suitable algorithm for it, implement it and perform the necessary tests. The laboratory exercises realized as part of the subject will help achieve these goals.



Lecture

Basic concept of sensor. Idea of smart sensor. Sensory system in the structure of robot. Robot-human analogy. Comparison of human and robot vision. Lighting systems (traditional lighting and LEDs). Ring illuminators. Structured lighting. Grid projectors and line generators. Examples of advanced lighting systems. Camera obscura. Pin-hole camera. Optical systems (lenses for cameras, filters). Properties of lenses (aperture, magnification, vignetting, depth of field, distortions and aberrations). Choice of lens from nomogram. Spectral characteristics of colour filters. Image sensors (linear and matrix, CCD and CMOS). Layouts of the photosites. CCD architectures. Frome black and white to colour. Colour wheel. Mosaic colour filters (Bayer filter). Microlenses. Fill factor for CMOS sensors. Comparison: CCD vs. CMOS. Foveon three-layer CMOS technology. Monochrome and color cameras. Multicamera systems. High-speed cameras (fps). Smart camera and its software. Webcams. 3CCD cameras. Multispectral cam-eras. Spectral sensitivites of colour camera. Special cameras (pill camera, HDR camera). Elements of television technology. Framegrabbers. Image processors. Look-up tables (LUT) and their applications for image processing. Camera interfaces (IEEE 1394, USB, CameraLink, Ethernet etc.). Image acquisi-tion: noise and ISO. Dark current image. Interpolation artefacts (demosaicking). Human vision system: light receptors. Spectral characteristics of cones. Opponent colours. Defective colour vision: Ishihara tests. Colour matching system. Metameric pairs. Colour sensors. The colour and colour spaces. Discrete structure of RGB cube. Colorimetric and TV colour spaces. Munsell colour system. Simple colour image processing (swapping and negation). Colour image quantization (splitting and clustering methods). The problem of empty clusters. Calibration of colour vision systems. Segmentation of the image. Threshold-ing of the image. Region-based segmentation techniques. Features: moments of geometric shape factors, topological characteristics. Object recognition. Recognition of objects using models. Overview of senso-


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ry systems, vision applications in automation and robotics. Universal and specialized systems. Examples of real applications of robot vision systems.

Laboratory

1. Basics of mathematical morphology. 2. Size of objects. 3. Objects and holes in binary image. 4. Shape factors. 5. Introduction to colour image processing. 6. K-means for colour image segmentation. 7. Case studies.

References:

1. Corke P., Robotics, Vision and Control, Springer, Berlin 2011.

2. Szeliski R., Computer Vision: Algorithms and Applications, Springer, Berlin 2010.

3. Horn B.K.P., Robot Vision, The MIT Press, Cambridge 1986.

4. Niemann H., Pattern Analysis and Understanding, Springer, Berlin 1990.


Subject: Design & Configuration of LAN infrastructure Code: CEIE_S1_83


Teacher: dr. Mirosław Skrzewski


Knowledge and basic understanding of operation of the computer networks and operating systems.

Course objectives:

The course deals with basic solutions of wired and wireless local area network infrastructure. Princi-ples of structural cabling design, wireless LAN communication, protocol configuration and WAN inter-connection will be presented, along with the VLAN design and configuration.


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Lectures:

The concept of LAN infrastructure. Classical Ethernet (802.3, Ethernet v2.0) segment design, transceiv-er, terminators, repeaters, collision domain, broadcast domain. Versions of standard (10BaseT, 10BaseF, 10Base2). Modification of basic principles of network operation – introduction of store & for-ward technology (hub, switch, managed switch operation). Modification of topology, problems witch loops, spanning tree protocol.

Virtual networks (VLAN), VLAN connections, 802.1Q protocol, VLAN configuration. Standards Fast Ethernet (100BaseT), 1G Ethernet, 10G Ethernet, cabling standards. Cables UTP, STP, connectors, cables categories cat3, cat5, cat5e, cat6.

Wireless LAN connections, standards 802.11a/b/g/n, Bluetooth, 802.16, network organization, ad-hoc, infrastructure networks, radio network access control, connection security. Access point configuration, radio bandwidth and channel allocation.

LAN systems IP configuration, protocols rarp, arp, bootp, dhcp, apipa. LAN – WAN interconnections, access line protocols, serial protocols SLIP, PPP, PPPoE, protocol tunneling. Access router, network ad-dress translation, problems of LAN systems security and LAN access protection.

Laboratories

During lab exercises students has admin access to typical devices used in network infrastructures and familiarize with their configuration, testing tools and network protocol configuration. There are planned following lab exercises:

1. Wireless LAN channel configuration and testing 2. Testing of physical network cabling infrastructure 3. Managed switches infrastructure configuration 4. LAN IP protocol configuration and testing 5. Monitoring of LAN protocol operation 6. WAN access router configuration

References:

1. W. Stallings, Data and Computer Communications, Prentice-Hall Int. 2. Kurose J., Ross K., Computer Networking: A top-down approach.

3. D. Comer, Internetworking with TCP/IP, Vol. I: Principles, Protocols, and Architecture.



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Subject: Industrial Process Visualization Code: CEIE_S1_84


Teacher: dr. Rafał Cupek


Computer networks, Theory of computer science, Control fundamentals.

Course objectives:

The structure and methods used in industrial process visualization applied to heterogeneous industrial computer systems. Presentation of the embedded visualization tools, Supervisory Control and Data Ac-quisition (SCADA) Systems and Manufacturing Execution Systems (MES). Data gathering and processing in distributed visualization systems. Historian, an industrial database.


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Lectures

- Control panels and local visualization

- Vertical communication in distributed industrial computer systems on OPC example

- Supervisory Control and Data Acquisition (SCADA) Systems on Wonderware: ArchestraA example

- Distributed Control Systems (DCS) on ABB Frilance example

- Industrial Database – historical data visualization

- Visualisation in Manufacturing Execution Systems (MES)

Laboratories

1. Graphic Panels Programming

2. InTouch Wonderware - SCADA System

3. Industrial Application Server on ArchesrA Example

4. Vertical communication on OPC Standard Example

5. Historian an Industrial Database

References:

1. F.Iwanitz, J.Lange: OPC Fundamentals 2. Jurgen Keletti: Manufacturing Execution System



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Subject: Programming LEGO Mindstorms NTX robots Code: CEIE_S1_85


Teacher: dr. Piotr Czekalski


Computer programming, Physics

Course objectives:

The main goal is to present audience a modern robot building platform and wide range of construction and programming methods of LEGO Mindstorms NXT robots.


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Lectures:

The course contains a presentation on both constructing and programming universal robotics platform based on LEGO Mindtstorms NXT. Programming in NXT-G visual language on LabVIEW-based Mind-storms EDU NXT Software environment will be presented (autonomous systems), programming in VPL and C# with means of Microsoft Robotics Development Studio (remote systems) as well, as running programs on dedicated NXT Virtual Java Machine (NXJ) will be presented. Additionalny the course co-vers communication ideas on both inter-robotics and robots-to-PC models. As an extra part this course presents embedded system construction of NXT Intelligent Brick considerations on popular sensors, to let the students design and implement their own interfaces, robot constructions. Topics: 1. Why just NXT platform? From a game to the business and industry. Platform preceedors. 2. Overview of NXT Intelligent Brick construction and it's communication interfaces. Platform specifi-

cation and capabilities. 3. Overview of available platform sensors and servo motors. 4. Constructing NXT robots. Theory vs physics. 5. Open hardware platform Mindstorms NXT – Hardware Development Kit. 6. The most popular NXT models overview. 7. Mindstorms NXT application software models. Internal (autonomous) software and remote man-

aged software. Serial and parallel programing. Calibrating sensors and servo motors. Starting point and border conditions. Uploading autonomous programs and communicating over Bluetooth proto-col.

8. Programing in NXT-G Visual Language on LabVIEW environment. 9. Programming in Microsoft Visual Programming Language (VPL) and Clanguage on Microsoft Robot-

ics Studio. 10. Programming with means of Virtual Java Machine for NXT Intelligent Brick.


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Laboratories:

The main target is to let the audience practice construction and programming of NXT base robots. All exercised are performed by students during laboratories. The laboratory is equipped with 8 complete Mindstorms NXT platforms (edu edition) each equipped with NXT Intelligent Brick, a set of genuine LEGO sensors and servo motors and about 1200 pcs. of building bricks plus suitable software and mod-ern PC Workstations. The laboratory also contains a set of third party sensors, including object tracking cameras, tilt/accelerometer sensors, gyro sensors, compass sensors and colour recognition sensors.

Lab exercises:

1. Programming in NXT-G on LabVIEW environment – simple operations on Tribot, Spike, Roboarm popular models.

2. 2-3. Programming in VPL and C# on Microsoft Robotics Studio environment - simple operations on Tribot, Spike, Roboarm popular models.

3. Programming in Java on dedicated JVM.

4. Wireless inter-robot and robot-to-PC communication.

5. 6-8. Advanced programming – following the path seamlessly by Tribot. Running through unknown environment and avoiding obstacles.

References:

1. Creating Cool MINDSTORMS NXT Robots, Daniele Benedettelli, Apress, 2008. 2. LEGO Mindstorms NXT-G Programming Guide, Jim Kelly, Apress, 2007.

3. LEGO Mindstorms NXT: The Mayan Adventure, James Floyd Kelly, Apress, 2006. 4. Advanced NXT: The Da Vinci Inventions Book, Matthias Paul Scholz, Apress, 2007. 5. Extreme NXT: Extending the LEGO Mindstorms NXT to the Next Level, Michael Gasperi, Philippe E. Hurbain,

and Isabelle L. Hurbain, Apress, 2007. 6. The LEGO MINDSTORMS NXT Zoo! - A Kid-Friendly Guide to Building Animals with the NXT Robotics System,

Fay Rhodes, No Starch Press, 2008. 7. Building Robots with LEGO Mindstorms NXT, Mario Ferrari, Guilio Ferrari, and David Astolfo, Syngress, 2007.

8. The Unofficial LEGO MINDSTORMS NXT Inventor's Guide, David J. Perdue, No Starch Press, 2007. 9. Maximum LEGO NXT: Building Robots with Java Brains, Brian Bagnall, Variant Press, 2007.


Subject: Programming of mobile devices Code: CEIE_S1_86




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It is assumed, that the student has elementary skills in computer programming.

Course objectives:

The ain of the course is to provide techniques for developing applications for mobile devices with re-stricted computing power and memory. The main focus is on design and optimization of applications and user interfaces for devices like smartphones, tablet PCs, PDAs. Within the course, students will ac-quire the ability to create applications for Android, Windows Phone, Symbian, iOS.


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Lectures

1. Introduction 2. Architecture of mobile devices 3. Differences between applications for desktop computers and mobile devices 4. Mobile devices based on Linux 5. The Android operating system 6. Event handling 7. Localization of programs, applets 8. Multithreaded applications 9. The Windows Phone operating system 10. Other mobile operating systems 11. Application Security

Laboratories:

Will follow topics presented during the lectures.

References:

1. Andy Wigley, Daniel Moth, Peter Foot: Mobile Development Handbook

2. Andy Wigley, Stephen Wheelwright: .NET Compact Framework

3. Ivo Salmre: Writing Mobile Code

4. Paul Yao, David Durant: .NET Compact Framework Programming with C#



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Subject: XML technologies Code: CEIE_S1_87


Teacher: dr. Dariusz Mrozek


Databases, Database Applications. It is assumed that before start of this course, students have knowledge on the relational data model, architecture of database management system, skills in SQL language and designing relational database schemas.

Course objectives:

XML is recently widely used and widely accepted standard for data exchange, due to its self-descriptive character, the ability to define the hierarchy, the ability to check a validity of data and independence from hardware and software platforms. XML Technologies Course is designed for individuals who wish to deepen their knowledge of the rich world of XML technologies – especially, database developers, da-tabase administrators, data analysts, report designers and developers of web sites.


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Lectures

1. Introduction to the world of XML technologies – creation of well-formed XML documents, rules of XML documents creation, namespaces, XML documents validation

2. Document Type Definition – creating documents describing structures of XML documents, XML data validation based on DTD

3. XML Schemas – designing XML schemas, XML data validation based on XML schema, type deriva-tion, setting constraints, type unions, enumerations

4. DOM and SAX parsers – parsing XML documents, reading data with the use of SAX, creating docu-ment tree using DOM parser

5. XPath, XQuery query languages – formulating queries to XML documents using XPath and XQuery, defining filtering criteria, data aggregation, using functions and operators, constructors

6. Xlink – defining references to local and remote resources, type of links, arcs, link databases 7. XPointer languages – pointing to fragments of XML documents, creating sequences, relative point-

ing, points and ranges 8. Integration of data into an XML format – mapping and transforming XML documents to XML docu-

ments, transferring and integrating relational data to XML 9. XML Spy – presentation of the XML Spy tool, creating XML schema diagrams and XML documents

using XML Spy 10. Reporting from XML documents, XSL stylesheets and XSLT transformations – transforming data

using XSLT expressions, generating web pages and reports using XSL and XSLT


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11. XML in selected database systems – storing XML data in relational databases, generating XML data with the use of SQL language and user functions, XML validation in relational databases, invoking XPath/XQuery queries in SQL

12. Web services – creating and using web services, purpose of the WSDL, UDDI, SOAP documents 13. XML applications – XML in electronic data interchange, creating web portals based on XML, dedicat-

ed XML formats for data exchange

Laboratories

The aim of the laboratory is to acquaint students with XML technologies through practical exercises. The laboratory is carried out mainly using Altova's tools.

1. XML Schema 2. XSLT transformations 3. Querying data in XPath and XQuery 4. DOM and SAX parsers 5. Mapping data to XML 6. XML in selected database system

References:

1. Erik T. Ray: Learning XML, Second Edition, O'Reilly Media; Second Edition edition (September 29, 2003)

2. Bill Evjen, Kent Sharkey, Thiru Thangarathinam, Michael Kay, Alessandro Vernet, Sam Ferguson: Professional XML (Programmer to Programmer), Wrox; 1 edition (April 9, 2007)


Subject: Constraint Logic Programming Code: CEIE_S1_88


Teacher: dr. Szymon Ogonowski


Skills in object-oriented programming

Course objectives:

The aim of this lecture is to present Constraint Logic Programming techniques for solving Constraint Satisfaction Problems and Constraint Optimisation Problems. Applications of those techniques are demonstrated by many examples taken from real-world combinatorial problems, such as scheduling, planning or job-shop problems. The theory presented in the lecture is supported by problems solving using Java language (JaCoP library).


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Lectures

Constraint Logic Programming is a methodology having backgrounds in Operational Research and belongs to wide concept of Artificial Intelligence Methods. Its main concept is based on declarative programming – the programmer needs only to describe what computation should be performed and not how to compute it (this part is already implemented in solver). Lecture is based on a multimedia presentation (available for the course students), supported with example code testing.The course presents concepts of:

− constraint propagation, global constraints, arc-consistency,

− different domains of variables - boolean domains, finite domains, sets and real intervals,

− global constraints such as: alldifferent, count, element, cumulative, diff2, circuit, knapsack, among, regular,

− search distributions – first-fail, most-constrained, max-regret,

− tree-based search such as - branch-and-bound, depth first search, limited discrepancy search, spe-cial search techniques,

− methods of default search algorithms modification – creating own search techniques,

− modelling and solving constraint optimisation problems and soft constraints - Weighted CSP, Fuzzy/Possibilistic CSP, Probabilistic CSP, over-constrained problems,

− scheduling/planning problems,

− incorporating local search techniques into constraint programming methodology. Details of concepts mentioned above are presented while solving examples of simple academic and more complex, real-world combinatorial problems with usage of Java language and dedicated JaCoP (Java Constraint Programming) library. Advantages of using well known and well documented language allows the students to focus on getting to know the idea behind constraint programming. During laboratory exercises students constructs Java desktop applications and incorporates in it different modules, designed to solve different combinatorial problems. Laboratories

All laboratory exercises are focusing on different CP problems, that are solved as a separate Java mod-ules. Designed modules are incorporated in main Java desktop application, creating compact and scala-ble project. 1. Design of CLP application base 2. Simple combinatorial problems modules 3. Soft constraint problem module - reified constraint 4. Scheduling/planning problem module – building bridge example 5. Search strategy module – queens problem 6. Optimisation problem module


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References:

1. Francesca Rossi, Peter Van Beek, Toby Walsh “Handbook of constraint programming”,

2. Peter van Hentenryck “Constraint-based Local Search”.


Subject: Electromechanical devices Code: CEIE_S1_89


Teacher: prof. Krzysztof Kluszczyński


Automatics and robotics – obligatory; Electronics and telecommunications, Informatics

Course objectives:

This curriculum develops basic skills in the field of design, measurement and application of electrical machines and modern drives. Up to date information concerning various types of machines and their control schemes is provided. Special attention is focused on applications in automatic control systems and robotics.


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Lectures

Basics of electromechanical energy conversion: force and torque development. General aspects of mo-tor selection for electrical drives. Alternating Current (AC) machines. Distributed windings and magnet-ic fields of AC machines. Converters for AC drive systems. Asynchronous machines: construction, theory and performance. Basic types of induction motors. Equivalent circuits of slip-ring and squirrel cage mo-tors. Steady-state and transient operation. Speed-torque characteristics. Starting methods. Performance of converter-fed induction motors. Speed control: U/f and vector control schemes. Synchronous ma-chines: construction, theory and performance. Basic types of synchronous machines. Generator and motor operation of salient-pole and cylindrical-rotor machines. Equivalent circuits. Steady-state and transient operation. Load angle-torque characteristics. Methods of starting and synchronisation. Stabil-ity margin. Performance of converter-fed synchronous machine. Control schemes for rotor positioning. Direct Current (DC) machines: windings and commutation. Basic types of DC machines: generator and motor operation. Equivalent circuits of series, shunt and separately excited machines. Steady-state and transient operation. Starting methods. Solid-state converters for DC drive systems and speed control. DC servomotors. Application and control schemes of small electric motors. Single-phase induction mo-


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tors. Stepping motors. Switched Reluctance Motors (SRM). Permanent Magnet motors. Hysteresis mo-tors.

Laboratories

Open-circuit and short-circuit tests of a transformer. No-load and locked-rotor tests of a slip-ring motor. Speed-torque characteristics of a squirrel-cage motor - scalar and vector control. Motor and generator operation of a Synchronous Permanent Magnet machine. DC separately excited machine - generator operation characteristics. Methods for measuring dynamic properties of controlled drives. Speed con-trol of induction machine - measurement and computer simulation (Matlab/Simulink). Stepping motor - speed and position control (FESTO). Synchronous Permanent Magnet servomotor - speed and position control (FESTO).

References:

1. Analysis of Electric Machinery, Paul C. Krause, McGrew-Hill Book Company, 1986; 2. Electric drives, Ion Boldea, S.A. Nasar, Taylor & Francis, 2005


Subject: Linux – advanced programming Code: CEIE_S1_91


Teacher: dr. Dariusz Bismor


Computer programming, Operating systems

Course objectives:

The course has two aims. The first is to present the basics as well as more advanced techniques used in Linux kernel programming. As there are (soft) real time versions of Linux kernel, this aim agrees with real time systems teaching requirement. The second aim is to demonstrate object oriented program-ming techniques with application to graphical user interface programming in KDE/Qt environment. This extends the information technology knowledge of course attendants.


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The lecture discuses the following areas of Linux kernel programming: differences between user and kernel mode code, Linux kernel modular structure and design, what all modules must have; how to compile a simple module; devices in Linux system: block devices, character devices and network inter-faces; character devices: numbering, file operations, talking to; memory issues: types of memory, cach-


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es, paging; ioctls, blocking, poll and select, asynchronous operations; race conditions, semaphores, mutexes and spin locks; scheduling tasks; interrupt handling basics; block devices: differences between character and block devices, buffer cache, virtual file system, structure inode, writing simple file system, second extended file system.

The lecture discuses the following areas of KDE programming: KDE 4.x architecture overview; 3-level structure of KDE/Qt programs; signals and slots; designing applications using XML GUI framework; design patterns in application config files and setting dialogs; layout management; composing GUI with KDE Designer and Qt Designer; graphical operations basics; writing new widgets.

The lecture is based on slides displayed with multimedia projector. Students are allowed to download outlines prior to lecture. All issues mentioned above are discussed by the lecturer, with emphasize on the issues selected by students. Many issues are illustrated by working program code.

Laboratories

1. Writing a simple Linux kernel module.

2. Writing a character device driver, part 1: reading and writing from device file.

3. Writing a character device driver, part 2: more advanced operations.

4. Writing a block device driver.

5. Writing a simple KDE application.

6. Using QT Designer to compose GUI.

References:

1. M. Mitchell, J. Oldham and A. Samuel: Advanced Linux Programming, New Riders Publishing,

2001.

2. P. J. Salzman, M. Burian and O. Pomerantz: The Linux Kernel Module Programming Guide,

Peter Jay Salzman, 2001

3. A. Rubini and J. Corbet: Linux Device Drivers, 2nd

Edition, O'Reilly, 2001.

4. E. Raymond: The Art of Unix Programming, Eric Steven Raymond, 2003.

5. J. Thelin: Foundations of Qt Development, Apress, 2007.


Subject: Industrial Control Systems Design Code: CEIE_S1_90


Teacher: dr. Zbigniew Ogonowski


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Control fundamentals, Introduction to system dynamics, Fundamentals of signal processing, Measure-ment systems, Numerical methods, Optimization and decision making

Course objectives:

The course provides an overview of advanced control design methods for industrial systems. It is aimed to extend control engineering knowledge of the students onto system scientist knowledge. It is then assumed that students understand control fundamentals, dynamic modeling, signals measurement and processing as well as numerical methods and optimization issues. The course gathers these aspects and assume to use them as a tool in the control system design for industrial processes. The main aim is to teach design principles according to hierarchical structure of the industrial processes. Students should acquire skills to create realistic and practical solutions of the industrial control problems.


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The course consists of three parts covering the most important aspects of Industrial Control System Design. Beginning with the general hierarchical structure of control system (part one) the course pro-ceeds with the direct control layer (part two). The most important in this part are the principles of structure choice of the control system. In part three, functionality of the upper control layer is present-ed including acquisition and data processing together with process optimization.

Part I

1. Basic notions: Analysis of the process, Functional structure, Equipment, Control System and its pur-pose, Process state, Process model, Horizon of control, Functional structure and equipment struc-ture of the control system.

2. Hierarchy of control algorithms: Properties of algorithms connected hierarchically, Necessity of using hierarchical structures, Hierarchy of the models.

3. Functional structure of control systems: General scheme of industrial process, Direct control layer, Upper control layer, Operating (optimization) control layer, managing layer.

Part II

1. Direct control layer: Tasks, Structure of direct control layer, Leading streams, Constructive postu-lates for direct control layer.

2. Structure choice – general aspects: Control tractability, Multivariable processes and input/output assignment problem, Analysis of degree of freedom, relative gain array method, Special structures (recycling process with losses complement).

3. Structure choice – certain problems: Flow, pressure and level control, Quality control of material streams, Thermal processes control, Mass diffusion control.


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Part III

1. Data acquisition and processing: Periodical data acquisition, Acquisition methods, AD/DA conver-sion, Acquisition file, Basic data processing, Special processing of process variables.

2. Signaling, supervision and documenting the process: Purpose, Signaling, Supervision, Document-ing, Alarm system, Supervision.

3. Optimization of the process: Elements of the process optimization, Principles of quality index crea-tion, Principles of mathematical models creation, Standard optimization problem, Basic optimiza-tion method, Decomposition of optimization problems.

4. Standardization of project description: ISO norm, Topology of the project, Graphical signs, Abbrevi-ation system

Laboratory

1. Simple industrial process analysis and control design. 2. Continuous stirred tank reactor - Three-level hierarchical control system. 3. Sodium bicarbonate technology - Leading steam choice. 4. Evaporation process – DoF analysis and input-output assignment. 5. Drying spray-both system – recycling process with losses complement. 6. Oil refiner – optimizing control layer.

References:

1. C.A. Smith, A.B. Corripio: „Principles and practice of automatic control” Wiley, 1997.


Subject: Object oriented programming Code: CEIE_S1_92


Teacher: dr. Dariusz Bismor


Computer programming

Course objectives:

The aim of the course is to introduce the modern, object-oriented program design and programming techniques. Students should learn the difference between procedural and object-oriented techniques as well as analysis and design techniques for object-oriented style and those programming languages that give support for object-oriented programming. Knowledge attained during the course should allow for


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easy and fast completion of even large programming projects. The examples illustrating the lecture are based on control theory and practice.


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The lecture emphasizes, but is not limited to the following topics: introduction to object-oriented analy-sis, object statics, object dynamics, object relationships and interactions, class as object part, class rela-tionships, constructing a model of a system, Unified Modeling Language (UML), design patterns, crea-tional patterns, structural patterns, behavioral patterns.

The lecture is based on slides displayed with multimedia projector. Students are allowed to download outlines prior to each lecture. All issues mentioned above and below are discussed by the lecturer, with emphasize on the issues selected by students. Many issues are illustrated by working program code.

The detailed lecture content is given below.

1. Introduction: the course aim, the tools and references. Unified Modeling Language (UML): basic constructs, rules and diagrams. Use case diagrams, class diagrams, object diagrams, sequence dia-grams, collaboration diagrams, state-chart diagrams, activity diagrams, component and deployment diagrams.

2. Object-oriented analysis: the purpose, the importance, the input and the output. Understanding the needs of clients, describing what the system will do and how the system should behave, identification of objects. Four-component model, other models. Object statics: instances, classes, attribute features, constrains. Object relationships: collections, property inheritance, subclasses. Object dynamics: describing behavior, transition networks, actions, exceptions. Object interaction: transitions, sending and receiving events. Constructing a system model: the use of the above notions to describe a system.

3. Design patterns: the use of design patterns in object-oriented analysis and design. Design pattern classification. Creational patterns: builder, abstract factory, factory method, prototype.

4. Creational patterns: singleton. Structural patterns: adapter, decorator, facade, composite, bridge.

5. Structural patterns: proxy, flyweight. Behavioral patterns: interpreter, iterator, chain of responsibility.

6. Behavioral patterns: mediator, template method, observer, visitor, memento, command.

7. Behavioral patterns:, state, strategy. Other patterns and concepts: lazy and eager computation, advanced reference counting, copying on write, pimpl idiom.

Laboratory exercises aim at writing a single, complete piece of code, solving the problem selected by a tutor.

1. Introduction to the project: analysis and design. 2. Finding the design patterns in the project. 3. Creational, structural and behavioral patterns in practice, part 1.


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4. Creational, structural and behavioral patterns in practice, part 2. 5. Creational, structural and behavioral patterns in practice, part 3. 6. Other patterns and programming idioms.

References:

1. E. Gamma, R. Helm, R. Johnson, J. Vlissides: Design Patterns, Addison Wesley, 1995.

2. I. Graham: Metody obiektowe w teorii i praktyce,WNT, Warszawa, 2004 (eng. version: Object-Oriented Methods:

Principles and Practice (3rd Edition), Addison-Wesley Professional, 2000.

3. A. Koenig, B. Moo: Accelerated C++. Practical Programming by Example, Addison Wesley Professional, 2000.

4. B. Eckel: Thinking in C++, Second Edition, vol. 1 & 2, Upper Saddle River, NJ, 2000 & 2004.


Subject: Reliability and Intrinsic Safety Code: CEIE_S1_93


Teacher: dr. Andrzej Kozyra


Understanding of most important terms like: reliability, fault, MTBF, MTTF, failure rate, types of explo-sion-proof protections, national and international standards, explosion-proof apparatus marking. Abil-ity to estimate reliability parameters of elements and systems by using modular decomposition, fault tree, Markov processes.

Course objectives:

Goal of the course is to acquaint students with reliability assessment of technical objects and systems, reliability analysis methods, constructions of explosion-proof apparatus and designing an intrinsically safe systems.


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Lectures

1. Introduction, Statistical Approach to Reliability – reliability, maintainability, failure, fail function, hazard rate, MTBF, MTTF, Wiener's equation.

2. Reliability Assessment of System Elements - statistical methods, estimation of reliability of electron-ic components and circuits. Mil Hndbk 217.


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3. Reliability Structures, Modular Decomposition – properties of basic reliability structures, modular decomposition method of reliability analysis, fault tree analysis.

4. Markov Processes in Reliability Analysis – repairable systems, state-transition diagrams, influence of human error, influence of inspection on reliability.

5. Hazardous zones- Basic properties of flammable and combustible materials, area classification, types of explosion-proof protections. National and international standards, marking.

6. Intrinsically Safe Systems 'i'- An intrinsically safe protection as the most safe protection, require-ments for intrinsically safe apparatus, certification procedures, basic installation requirements.

Laboratories

1. λ-models, Analysis of reliability of electronics circuits based on Mil Hndbk 217. Students estimate reliability of electronic devices and reliability of whole electronic circuits.

2. Basic reliability structures. Students learn how to create a graph of system states and estimate reli-ability of basic systems. Analysis bases on Markov models.

3. Reliability assessment of complex system. Boolean reliability theory. Estimation of reliability of complex system by using modular decomposition, fault tree analysis.

4. Safety factor in a reliability context. Safety factor concept for explosive area with intrinsically safe devices. Determination how parameters of intrinsic safe devices influence safety of systems.

5. Reliability of complex system with influence of a human error. Analysis of influence of critical hu-man errors on reliability of systems. Estimation of reliability of ventilation system in coal mines. Analysis of influence of inspection of system state on reliability of systems.

6. Fuzzy reliability. Application of fuzzy logic for estimation of reliability of systems. Students use Mathlab application to estimate reliability of systems. Demonstration of system with intrinsically safe modules. Students learn how to make system more reliable and how intrinsically safe system can be built.

References:

1. Schooman M.L.: Probabilistic Reliability: An Engineering Approach. 2nd ed., R.E.Krieger Publishing Company, Malabar, Florida 1990.

2. Kai- Yuan Cai: Introduction to fuzzy reliability. Kluwer Academic Publishers, Boston, 1996. 3. Smith D.:''Reliability, Maintainability and Risk -- Practical methods for engineers'' Butterworth--Heinemann

Oxford 2000



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Subject: Face recognition and biometric systems Code: CEIE_S1_94


Teacher: dr. Michał Kawulok


Programming in C++.

Course objectives:

The course aims to familiarize students with the basic technologies used in biometrics and prepare them for designing and developing advanced biometric systems. Students will be given the experience gained in the course of operating a system of automatic face recognition. The lecture will discuss the fundamental problems associated with biometric systems with particular emphasis on face detection and recognition. The laboratories involve practical implementation of the various stages of face recogni-tion by applying the methods known in the field. Students will create or modify parts of the existing system, which simplifies the testing and evaluation of the solutions.


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Lectures

1. Introduction to biometrics and identification systems. 2. Face detection. 3. Normalization of facial images. 4. Feature extraction using the Eigenfaces method. 5. Linear discriminant analysis (LDA) and Fisherface feature extraction method. 6. Possibilities of improving the Eigenfaces method. 7. Methods based on local features analysis (Gabor Wavelets). 8. The use of classifiers for face recognition, support vectors machines (SVM). 9. Face tracking.

Laboratories

1. Presentation of the environment, basic image processing tasks. 2. Normalization of frontal facial images. 3. PCA training and generation of the eigenfaces. 4. Extraction of features using the Eigenfaces method. 5. Application of SVM to face verification.


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References:

1. W. Zhao, R. Chellappa, P.J. Phillips, and A. Rosenfeld. Face recognition: A literature survey. Technical Report

CARTR-948, Center for Automation Research, University of Maryland, College Park (2000)

2. S. Gong, S.J. McKenna, and A. Psarrou. Dynamic Vision From Images to Face Recognition. Imperial College Press (1999)


Subject: 802.11 WIRELESS LOCAL AREA NETWORKS Code: CEIE_S1_95


Teacher: dr. Dariusz Wójcik


principles of electric circuits, computer and digital systems fundamentals, fundamentals of information systems security, fundamentals of access control systems; fundamentals of antenna theory.

Course objectives:

The aim of this course is to familiarize students with all aspects of 802.11 wireless local area networks: overview of the technology and architecture of WLANs, explanation of services and advanced features. The course gives knowledge needed to design, deploy, manage, and troubleshoot wireless local area networks (WLANs).


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Lecture:

1. Fundamentals of wireless local area networks, usage of non-licensed ISM bands, the legal regu-lations

2. The role of IEEE standards 802.11 family of wireless networks against the reference model OSI / ISO and other standards IEEE 802

3. Medium access control, resource reservation methods, topology, ad-hoc and infrastructure net-works, c

4. The physical layer, link layer protocols, the management layer protocols, upper layer protocols. 5. The organization of the network, the structure of frames. 6. Ad-hoc (IBSS) networks 7. Infrastructure networks 8. Energy management in 802.11 9. Quality of service in 802.11.


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10. Roaming. 11. Security in 802.11 networks. 12. Network configuration. 13. Design of 802.11 networks

Laboratory:

1. Configuration of 802.11 networks 2. Ad-hoc networks 3. Wireless gateway configuration 4. Access-point management 5. Network management - network scanning, access control and data encryption

802.11 network design

References:

1. M. Gast, 802.11 Wireless Network s: The Definitive Guide, O’Reilly, 2002.

2. P. Roshan, J. Leary, 802.11 Wireless LAN Fundamentals, Cisco Press, 2003.


Subject: Computer Networks II Code: CEIE_S1_96


Teacher: dr. Mirosław Skrzewski


introduction to computer science, basics of digital data transmission systems

Course objectives:

The aim of the course is to familiarize students with the basic principles of the communication proto-cols design and the construction and operation of computer networks. The solutions of the data link layer, network and transport layer protocols will be discussed in details, as well as the basic functions of higher layer protocols of the ISO model. Finally, the basic rules for the implementation of core ser-vices of Internet network, like dns., email, web will be presented.


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Lecture:


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Problems of information exchange between computers, the concept of the transmission channel, the communication protocol, algorithms of reliable transmission, the form of information processing, networks services. The logical architecture of computer networks, the ISO OSI reference model, the division of tasks into layers, layer functions, communication (interface) between layers, layer data units, layer services, service delivery models, addressing.

Physical layer functions, tasks of link layer, characters oriented protocols, bit oriented protocols, the methods of obtaining reliable transmission in the presence of interference, modem protocols. Local area network channels, the problem of media access, classification of media access algorithms, CSMA protocols, token based protocols, media allocation protocols. LAN infrastructure, network management, VLAN networks.

Network of transmission channels, modes of operation, the network topology, the tasks of the network layer, network addressing, route selection algorithms, mechanisms of adaptation to changes in topology and load on the network. Protocols Distance Vector, Link State, hierarchical routing, examples of protocols (RIP, OSPF, BGP), cooperation of networks of different organization of transmission .

Transport of information, organization of transmission, addressing, synchronization of network endpoints. Connection oriented, connectionless communication, quality of service (QoS). The problem of interruptions in transmission, the tasks of the session layer, session state registration , recovery algorythms. Processing the form and structure of the information, the notation ASN-1, the problem of information security.

Examples of the wide area network architectures - XNS, Internet (TCP / IP). Structure and function of protocols, network addressing, auxiliary protocols (DNS, ARP, ICMP), transport layer algorithms. LAN architecture - the NetBIOS protocol, the principles of addressing, the SMB protocol.

Network operating systems, client-server systems, peer-to-peer networks, addressing access to services, safety. Unix communication services, rpc, ftp, telnet, smtp, http. Windows, NetBEUI, network environment, mapping drives, shared network resources (folders, printers), the system of access rights.

Laboratory:

Laboratory exercises presents the basic issues related to communication in computer networks, the rules of their configuration and network performance monitoring tools available at network operating systems. In various exercises, students will configure and test the operation of the different network protocols and services using them:

- Principles of communication in IP networks

- Application Programming Interface of TCP/IP stack

- Translation services of system names

- WAN routing protocols

- Local network infrastructure

- Windows Network Environment


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References:

1. Tanenbaum, Computer Networks, 2. W. Stallings, Data and Computer Communications, Prentice-Hall Int. 3. Kurose J., Ross K., Computer Networking: A top-down approach.

4. D. Comer, Internetworking with TCP/IP, Vol. I: Principles, Protocols, and Architecture.


Subject: Fiber Optics Code: CEIE_S1_97


Teacher: dr. Grzegorz Wieczorek


Course attendants are supposed to have general knowledge concerning basic electronic components and analog circuits. It is assumed that students passed the following courses: Physics, Introduction to Electronics.

Course objectives:

The course aims objectives include having the students got acquainted structure, properties and pa-rameters of fiber optics and basic optoelectronic components applied in fiber optic transmission sys-tems. Discussed in the lecture are fiber optic applications in telecommunication, configurations and types of connections, transmission and multiplexing techniques.


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Lecture:

1. Types of fiber optics. Structure of single-and multimode fiber. Internal reflections. Nonlinear Phenomena. Properties.

2. Dispersion. Modal dispersion, material dispersion, waveguide dispersion and chromatic disper-sion. Optical fibers with shifted and flat dispersion characteristics. Dispersion compensation. The product of bandwidth and distance BDP. The concept of mods, graphic interpretation. Pow-er distribution in the fiber cross-section. Dispersion in multimode step-index and graded refrac-tive index optical fibers.

3. Attenuation in optical fibers. Attenuation characteristics and factors affecting the absorption. Transmission windows. Loss when connecting fiber. Connecting multimode optical fibers. Nu-merical aperture, numeric aperture mismatch. Axial displacement, angular displacement. Modes


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mixers, modes separators. Removable and permanent types of connections. Optical fiber cables - production, types and parameters.

4. Optical transmitters and modulators. Basic LED and LD driver circuits and their properties. La-ser transmitters – direct and external modulation.

5. Optical receivers. Configurations, Noise sources, sensitivity. 6. Optical amplifiers and passive optical components. Semiconductor optical amplifiers, doped

fiber amplifiers. Directional couplers, selective couplers, lenses, filters, attenuators, circulators, isolators, polarizers, polarization compensators.

7. Fiber optic networks. Multiplexing methods in fiber optic networks: WDM, FDM, SCM, TDM, OTDM, CDM. Multiple access methods WDMA , FDMA, TDMA, CDMA. Fiber network topologies.

8. Methods of measurement of optical fiber links. Optical power sources, optical power meters. Reflectometer - construction, principle of operation, discussion of measured quantities, properties, measurement methods.

Laboratory:

1. Determination of numerical aperture and acceptance angle of the optical fibers. 2. Coupling characteristics of the optical fibers. 3. Modems and fiber optic links. Measurement of the fiber optic modem. Optical link power

budget, and the extent of transmission. 4. Optical Time Domain Reflectometer OTDR. 5. Optical fiber arc fusion splicing. Preparation and cutting of fiber.

References:

1. K. Booth, S. Hill, ”The Essence of Optoelectronics”, Prentice Hall, 1998

2. J.D. Gibson, „The Communications Handbook – Second Edition”, CRC Press, Boca Raton 2002


Subject: Automotive Electronics Code: CEIE_S1_98


Teacher: prof. Zdzisław Filus


It is assumed that the course attendants know physical principles of operation of the internal combus-tion engine and have basic knowledge of circuit theory, electronic circuits, measurements and funda-mentals of control and regulation.


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Course objectives:

The objective of the lecture is to introduce the most important applications of electronic circuits to passenger vehicles. Particular attention is given to measurement of various physical quantities, connected with the movement of the car or with the operation of its individual blocks and to multiplexed wiring systems (automotive buses). Principles of control over various functions of the car are also discussed. The lecture should enable the students to understand peculiar features of the operation of electronic circuits in measurement systems, especially those designed for mechanical quantities, and in systems for control of mechanic and electric actuators.


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Introduction. First applications of electronic circuits to passenger vehicles. Current trends in automo-tive electronics: environmental protection, safety, ergonomics, social infrastructure.

Measurement transducers in cars. Pressure, linear and angular position, flow rate, temperature, line-ar and angular velocity, acceleration, engine torque sensors. Exhaust gas sensors (λ sensors). Engine knock sensors.

Vehicle electrical systems. Introduction. Electrical connections. Multiplexed wiring systems. CAN (Controller Area Network). Conventional electrical supply systems.

Microprocessor control systems in cars. Description of main electronically controlled vehicle sys-tems. Basic features of microcontrollers for automotive applications.

Engine control systems. Combustion process in SI (spark ignition) engines. Strategies for reduction of harmful emissions. Ignition systems. Fuel delivery systems.

Anti-lock braking systems (ABS) and Traction control systems (TCS). Principle of operation of ABS systems. Typical configuration of ABS systems. Principle of operation of TCS systems.

Electronically controlled transmission. Semi-automatic and automatic transmissions - principle of operation. Electronically controlled continuously variable transmissions (CVS).

Suspension and steering control. Electronically controlled suspension. Steering-wheel assist. Four-wheel steering systems.

Electronic switches for automotive applications. Configurations of power MOSFET switches for re-sistive and inductive loads. Protection circuits.

Body electronic systems. Instrument panel. Vehicle condition monitoring. Airbags. Air conditioning.

References:

1. Jurgen J.: Automotive Electronics Handbook. McGraw-Hill, Inc., 1999 2. Chowanietz E.: Automobile Electronics. Newnes (Butterworth-Heinemann Ltd), Oxford, 1995


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Subject: STM32 family ARM microcontrollers programming Code: CEIE_S1_99


Teacher: dr. Damian Grzechca, dr. Tomasz Golonek


A student has a basic knowledge in C/C++ programming and fundamental concepts of microprocessor systems.

Course objectives:

The aim of the course is to introduce students to STM32 family ARM microcontrollers programming with the use of JTAG interface and utilization of the standard library functions which support the micro-controller peripherals.


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Laboratory:

1. Description of the STM32 system specification: Software Development Environment and Standard Peripheral Library. 2. Configuration of clock signals for the microcontroller. GPIO port communication. 3. Control of alphanumeric LCD display. 4. UART interface communication, interrupts handling. 5. Configuration and use of counters (“Timer”). 6. Use of A/D converter. 7. Use of D/A converter. 8. DMA data transfer. 9. SPI interface communication. 10. I2C interface communication. 11. 1-wire network communication standard. 12. SD memory card operations.

References:

1. Reference manual RM0008:

2. http://www.st.com/internet/com/TECHNICAL_RESOURCES/TECHNICAL_LITERATURE/REFERENCE_MANUAL/CD00171190.pdf


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3. Jonathan W. Valvano, Embedded Systems: Real-Time Interfacing to Arm® Cortex(TM)-M Microcontrollers, CreateSpace Independent Publishing Platform


Subject: Radio frequency identification systems Code: CEIE_S1_100


Teacher: dr. Tomasz Topa


principles of electric circuits, computer and digital systems fundamentals, fundamentals of information systems security, fundamentals of access control systems; an understanding of antenna theory and de-sign would be useful but is not necessary, as the basics will be covered on the course.

Course objectives:

The aim of this course is to familiarize students with all aspects of technology used in modern RFID systems, including the near and far field electromagnetic coupling concept for detecting objects. The physics, design, data structures and control mechanisms for RFID systems are covered. Students will also be familiarized with associated standards, emerging business process models, applications, and social issues arising from the use of the RFID.


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Lecture:

1. RFID background: history, architecture, applications, shareholders, social implications and privacy 2. Barcode and barcode systems: EAN-8 and EAN -13 barcode, UPC-7 and UPC-12 barcode, 2D and 3D

barcodes, the pros and cons of barcode systems 3. Tag layer: tag classification, architecture, tag placement - shadowing risk and mitigation, antenna

configurations 4. Reader layer: reader classification, architecture, deployment requirements, interrogation zones,

antenna configurations, sessions, middleware, SmartLabel printers 5. Media interface layer: frequency bands, read range, modulation, encoding, communication proto-

cols, data rates, reader and tag collisions, anti-collision protocols, tag-to-tag and reader-to-reader interference, tag travel speed

6. RFID security and privacy: interactions with wireless LANs, chip clones, cryptography, symmetric ciphers, asymmetric ciphers, elliptic curve ciphers, authentication protocols, weaknesses in the en-cryption algorithm, weaknesses in key management, EPC trust services


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7. RFID standards: regulations, policies and guidelines: EPCglobal, ISO/IEC item management, contact-less Smart Cards, animal identification, FCC rules for ISM band, identity standards and guidelines for securing RFID systems

8. Case studies: patient tracking, blood services banks, boost asset awareness, asset-tracking platform, RFID pharmaceuticals seek system, library management system, public transport, ticketing, access control systems, animal identifications, electronic immobilization, container identification, industri-al automation, sport events

References:

1. K. Finkenzeller, RFID Handbook. Fundamentals and Applications in Contactless Smart Cards and Identification, John Wiley & Sons, 2003.

2. J. Banks, D. Hanny, M. A. Pachano, L. G. Thompson, RFID Applied, John Wiley & Sons, 2007.

3. H. Bhatt, B. Glover, RFID Essentials, O’Reilly, 2006. 4. B. Manish, M. Shahram, RFID Field Guide: Deploying Radio Frequency Identification Systems, Prentice Hall,

2005.

5. V D. Hunt, A. Puglia, M. Puglia, RFID: A Guide to Radio Frequency Identification, John Wiley & Sons, 2007. 6. S. Lahiri, RFID Sourcebook, Prentice Hall, 2005.


Subject: Digital System Design in Verilog HDL Code: CEIE_S1_101


Teacher: dr. Robert Czerwiński


It is assumed that the student is trained in the basics of digital technology, basics of digital circuit design and the computer programming.

Course objectives:

The aim of the course is to familiarize students with the digital systems designing using Verilog hard-ware description language.


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The purpose of the laboratory classes is to familiarize students with the Verilog hardware description language and the designing process using complex programmable logic devices. The first part of the


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laboratory exercises will be based on writing simple models, synthesizing, implementing and testing. In the second part students are going to implement the project of complex digital circuit. 1. Getting to know the tools for simulation, synthesis and implementation. Writing synthesizable mod-

els of combinatorial: translators, multiplexers, decoders, demultiplexers, arithmetic units. 2. Simulation and testing of combinational circuits. 3. Writing synthesizable models of simple sequential circuits: asynchronous flip-flops, synchroniza-

tion systems with a latch mechanism, edge-triggered systems. 4. Simulation and testing of sequential systems. 5. Writing synthesizable models of complex sequential devices: counters, registers, finite state ma-

chines. 6. Modelling complex hierarchical models. 7. Implementation of complex project.

References:

1. Palnitkar S., Verilog HDL. A Guide to Digital Design and Synthesis, Prentice Hall, 2003 2. Lee W.F., Verilog Coding for Logic Synthesis, John Wiley & Sons Inc., 2003 3. Lee J.M., Verilog Quickstart: A Practical Guide to Simulation and Synthesis in Verilog, Kluwer Academic Pub-

lishers, 2002 4. Bhasker J., Verilog HDL Synthesis. A practical Primer, Star Galaxy Publishing, 1998 5. Doulos, The Verilog Golden Reference Guide, Doulos, 1996


Subject: Program-based digital control systems Code: CEIE_S1_102


Teacher: dr. Robert Czerwiński, dr. Mirosław Chmiel


It is assumed that the student has a basic knowledge of microprocessors (including programmable logic controllers), and has the ability to program in C/C++.

Course objectives:

The aim of the course is to acquaint students with the methods of implementation of digital control sys-tems. The course focuses on the subject of software solutions, with particular emphasis on systems built using microcontrollers and programmable logic controllers.


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1. Microprocessors: microprocessor functional blocks, work cycles, pipelining, addressing modes, the system interrupts, etc.

2. Microcontrollers: characteristics, peripheral blocks. 3. Programmable controllers S7-200 (S7-300/400): characteristics, specifications, programming lan-

guages. 4. Designing algorithms, decomposition of complex problems into smaller, programming techniques. 5. Blocks of data, local and global variables, declarations. 6. Functions, passing parameters to / from functions. 7. Cyclic operation, interrupts. 8. I/O support, peripheral block support. 9. Programs executions: monitoring of the program, the location of faults, monitoring variables.

References:

1. Yiu J.: The Definitive Guide to the ARM Cortex-M3, Newnes, 20095.


Subject: GPU programming and architecture Code: CEIE_S1_


Teacher: dr. Tomasz Topa


C/C++ programming basics, familiarity with CPU architecture and multi-threaded programming; an understanding of computer graphics algorithms would be useful but is not necessary, as the basics will be covered on the course.

Course objectives:

The aim of this course is to introduce the programming techniques required to develop general purpose software applications for graphics processor units (GPUs). The ATI/AMD and/or NVIDIA GPU hardware allows achieving computing power unavailable for traditional central processing units (CPUs). Using CUDA and OpenCL framework, the course will focus on the solution to common problems encountered while developing software applications on the GPU. This will include an introduction to the program-ming techniques required to take advantage of the architecture, as well as more advanced optimization methodologies needed to get maximum performance out of the computing platform.


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Lecture:

1. Overview of computer animation and graphics systems: video display devices, output primitives, three-dimensional geometric modeling and transformations, illumination and surface-rendering methods, the viewing pipeline

2. Introduction to GPU programming: GPU architecture, overview of parallelism model, arithmetic accuracy and rounding

3. GPU hardware: CUDA Core, Radeon Core, special function unit, load/store unit, texture unit, dispatch unit, streaming multiprocessor, raster operations processor, thread sequencer, thread/graphics procesing cluster, streaming processor array

4. GPU progrmming model: threads and thread hierarchy, thread assignemnt and scheduling, synchronisation and transparent scalability, stream computing, host and device interactions

5. Execution model: warps, scheduling and divergence 6. Device memory: global and shared memory, local memory, constant and texture memory, registers,

memory hierarchy, memory latency 7. Performance optimizations: instruction performance, memory access patterns, global memory coa-

lescence, local memory bank conflicts, optimization strategies, data prefetching, thread granularity 8. CUDA: tools and libraries: detailed description of CUDA API, compilation using nvcc, debugging,

profiling, basic libraries, project assignment 9. OpenCL: introduction to OpenCL, differences comparing to CUDA, exploiting OpenCL for hardware

not accessible from CUDA 10. Case studies: acceleration of image and video compression, MRI reconstruction, molecular visualiza-

tion and analysis, computational electrodynamics, quantum chemistry, bioinformatics, signal pro-cessing, financial modeling, neural networks

Laboratory exercises:

1. GPU programming environment – installation, configuration, running and deploying applications 2. Data transfer and data caching 3. Memory access pattern 4. Launching kernels – thread cooperation, thread and device synchronization 5. Optimizing kernel code 6. Atomics 7. Concurrent transfer and execution 8. Mixing CUDA/OpenCL and rendering 9. Debugging and profiling kernel code

References:

1. Sanders, E. Kandrot, CUDA by example. An introduction to General-Purpose GPU Programming, Addison-Wesley

Press, New York, 2010


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2. D. Kirk, W. Hwu, Programming Massively Parallel Processors: A Hands-on Approach, Morgan Kaufmann Press, 2010

3. B. Chapman, F. Desprez, G.R. Joubert, A. Lichnewsky, F. Peters, T. Priol, Parallel Computing: From Multicores

and GPU's to Petascale, IOS Press, 2010


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