PROGRAME
ANALITICE
MASTER
COMPUTER ENGINEERING
UNIVERSITATEA "POLITEHNICA" DIN TIMIŞOARA
FACULTATEA DE AUTOMATICĂ ŞI CALCULATOARE
DOMENIUL CALCULATOARE ŞI TEHNOLOGIA INFORMAŢIEI
SPECIALIZAREA COMPUTER ENGINEERING (MASTER)
SEMESTRUL 1
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
for the discipline:
“TESTING OF COMPUTER SYSTEMS”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I or II (MASTER)
Semester: 1
Course instructor: professor Mircea Vlăduţiu, PhD
Applications instructor: assistant professor Lucian Prodan PhD, teaching assistant Versavia Ancuşa,
teaching assistant Alexandru Amaricăi, teaching assistant Oana Boncalo
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
2
Project
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
This course introduces fundamentals of theory and practice of detecting failures in complex digital systems, fault
analysis, test generation, and design for testability for digital ICs and systems. Covered topics include circuit and
system modeling; fault sources and types, fault simulation methods, automatic test pattern generation (ATPG)
algorithms for combinational and sequential circuits, testability measures, design-for-testability, VLSI testing issues and
processor and memory testing.
Fundamental techniques of detecting failures in complex digital systems will be introduces along with algorithms for
automatic test generation, schemes for designing systems to be easily testable and with self test capability; hands-on
experience with state-of-the-art computer-aided test tools in the laboratory.
B. COURSE SUBJECTS
Chapter 1. Introduction
1.1. Dependability attributes and scope. Reliability and Fault tolerance
1.2. Applications. Systems with high reliability, high availability, safety critical
1.3. Fault tolerance as a design target
1.4. Fault modeling. Fault causability chain
1.5. Physical and logical defects. Types of faults
1.6. Fault recovery techniques
1.7. Redundancy and reconfiguration
1.8. Defects specific to digital computing
Chapter 2. Automatic Test Pattern Generation
2.1. One path sensitization algorithm
2.2. D-algorithm
2.3. Poage-McClusky
Chapter 3. Error Checking and Correcting Codes
3.1. Fault detection and correction concepts
3.2. Detecting and correcting a single error
3.3. Hamming codes
3.4. Hamming modified codes
3.5. Correction of a single error with detection of all double errors
3.6. Correction of a double error
3.7. Error coding for memory chips
Chapter 4. Self-Testing Techniques
4.1. Introduction
4.2. Self-checking ALUs
4.3. Parity checked ALU
4.4. Checksum codes
4.5. Combination codes
4.6. Residue codes
4.7. Self checking PLAs
4.8. Berger codes
C. APPLICATIONS SUBJECTS
(laboratory, seminar, project)
The project can comprise of
1. a thorough survey of a topic, with original insight
2. a development of a new scheme, or a fresh implementation of an existing scheme
3. or modeling and analysis of an existing scheme.
A project proposal, a progress report and a final report will be due at the beginning, in the middle and at the end of the
semester. The proposal should include a title, name, one paragraph abstract, motivation, proposed approach and
applicable references The progress report should indicate that at least half of work has been finished, with a summary of
the findings, any refinements of the objectives as a result of the past study, what the final report will contain and the
applicable references. An oral presentation is required. The final report should follow the structure and formatting of a
research paper.
D. REFERENCES
1. Parag K. Lala. Digital Circuit Testing and Testability. Academic Press, 1997.
2. A.J. van de Goor. Testing Semiconductor Memories. Theory and Practice. John Wiley and Sons, 1991.
3. M. Abramovici, M.A. Breuer and A.D. Friedman. Digital Systems Testing and Testable Design. Computer Science
Press, New York, NY, 1990.
E. EVALUATION PROCEDURE
Course ends with a 2 hour written exam accounting for 50%. Candidates will have to cover several subjects (3-4) based
on course topics. Projects are based on a one page proposal that should include motivation, brief scope of study and
some specific references. The progress report and the final report will account for 20% and 30% of the final mark.
F. INTERNATIONAL COMPATIBILITY
1. Carnegie-Mellon University, 18765 – Digital Systems Testing and Testable Design
2. University of Illinois at Urbana-Champaign, ECE 543 – Digital System Testing & Design for Testability
3. Stanford University, EE488: Testing Aspects of Computer Systems
Date:
HEAD OF DEPARTMENT
Prof. Dr. Eng. Vladimir CREŢU
COURSE INSTRUCTOR,
Prof. Dr. Eng. Mircea VLADUTIU
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
For the discipline:
“IMAGE PROCESSING AND RECOGNITION”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I or II (MASTER)
Semester: 1
Course instructor: Associate professor Horaţiu Moldovan, PhD
Applications instructor: ing. Ronald Wagmann
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
2
Project
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
The course was originally designed to present processing and recognition techniques of digital images.
B. COURSE SUBJECTS
1. Introduction: generalities, numerical images representation, fundamental steps in image processing
2. Basic notions: elements of human visual perception, image model, pixels relations
3. Images transformation: Fourier transformation – introduction, description, properties
4. Image improvement: generalities, image improvement by points processing, spatial filters and image improvement
regarding frequency
5. Restoration of images
6. Compression of images
7. Segmentation of images
8. Representation and description: representation schemes, regional descriptors, morphology.
C. APPLICATIONS SUBJECTS
(laboratory, seminar, project)
1. Image representation
2. Fourier transformation
3. Properties of Fourier transformation
4. Uniform filter
5. Image improvement by point processing
6. Spatial filters
7. Increasing image quality. Filters for front detection
8. Frequency filters
9. Dilatation and erosion
10. Restoration of images with a band stop filter
D. REFERENCES
1. R.C. Gonzalez, P. Wintz - "Digital Image Processing. Addison Wesley, 1987
2. R.C. Gonzales, R.E. Woods - "Digital Image Processing", Addison Wesley, 1992.
3. F.C.A. Groen, R.J. Ekkers, R. de Vries - "Image processing with personal computers", Signal Processing 15,
1988
E. EVALUATION PROCEDURE
Examiner 2/3, applications 1/3
F. INTERNATIONAL COMPATIBILITY
1. Wien Institute of Technology, Austria
2. University of Karlsruhe, Germany
3. University of Dortmund, Germany
Date: 10.09.2007
HEAD OF DEPARTMENT
Prof. Dr. ing. Vladimir CREŢU
COURSE INSTRUCTOR,
Conf. Dr. Ing. Horaţiu MOLDOVAN
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
for the discipline:
“SMART SENSORS AND SENSOR NETWORKS”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I or II (MASTER)
Semester: 1
Course instructor: professor Mircea Popa, PhD
Applications instructor:
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
2
Project
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
- to understand the Smart sensor term; to know its characteristics, architecture, software level and applications;
- to understand the Sensor networks; to know the topics for the sensor networks: communication protocols, data
gathering and processing, energy management, security, reliability and foult tolerance;
- to know examples, standards, platforms and tools for sensor networks;
- to be able to choose among different smart sensors and to establish the topics for designing a sensor network.
B. COURSE SUBJECTS
Smart sensors fundamentals: Basic sensor technolog Sensor systems; Smart sensors definitions; Smart sensors:
Characteristics; Smart sensors architectures; Smart sensors buses and interfaces; Smart sensors software; Data
acquisition methods for smart sensors; Virtual sensor systems; Smart sensors for electrical and non-electrical
variables; Sensor networks architectures: Single node architecture; Multi node architectures; Design principles;
Energy efficient topologies; Wired sensor networks and wireless sensor networks; Applications; Communication
protocols: Phisical layer; MAC protocols; Link layer protocols; Localization and positioning; Routing protocols;
Transport layer; Data gathering and processing: Protocols for gather information; Data processing techniques;
Energy management: Energy consumption of sensor nodes; Techniques for reducing consumption and communication
energy; Energy aware routing; Security, reliability and fault-tolerance: Security and privacy protection; Reliability
support; Fault-tolerance; Sensor networks standards; platforms and tools: IEEE 802.15.4 and IEEE 802.11; Berkeley
motes; Operating systems.
C. APPLICATIONS SUBJECTS
(laboratory; seminar; project)
Projects:
1. Smart sensors for electrical variables
2. Smart sensors for non-electrical variables
3. Study of Berkeley Motes
4. Study of Smart Dusts
5. Microsensors and MEMS
6. Operating systems for sensor networks;
7. Time synchronization and calibration in sensor networks;
8. Distributed sensor networks
9. Coverage in sensor networks
10. Localization in sensor networks
11. Data centric protocols in sensor networks
12. Routing and information aggregation in sensor networks
13. Dynamic sensor networks
14. Low power design in sensor networks
15. Minimization of consumption in sensor networks
D. REFERENCES
1. N. V. Kirianaki, S. Y. Yurish, N. O. Shpak V. P. Deynega: Data Acquisition and Signal Processing for Smart Sensors,
John Wiley, 2004
2. H. Karl, A. Willig: Protocols and Architectures for Wireless Sensor Networks, John Wiley, 2005
3. M. Ilyas, I. Mahgoub (ed.): Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems, CRC,
2004
E. EVALUATION PROCEDURE
Exam and project each of them with 50% of the final note.
F. INTERNATIONAL COMPATIBILITY
1. Stanford University: Sensor Networks
2. Lancaster Engineering University: Smart Sensors
3. Harvard University: Wireless Communications and Sensor Networks
Date: 26.03.2007
HEAD OF DEPARTMENT
Prof. dr. ing. Vladimir CREŢU
COURSE INSTRUCTOR;
Prof. dr. ing. Mircea POPA
"POLITEHNICA" UNIVERSITY OF TIMISOARA
SYLLABUS
for the discipline:
"DATA TRANSMISSION, CODING AND COMPRESSION"
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of Studies: I or II (MASTER)
Semester: 1
Course instructor: associate professor Mihai V. Micea, PhD
Applications instructor: teaching assistant Bogdan Ciubotaru
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
Project
2
0
2
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
The course provides a detailed view of underlying support techniques employed in data communication networks. The
students attending this course will gain detailed knowledge about data transmission techniques, data processing for
enhancing communication efficiency and security. The students will also gain specific skills and abilities in analyzing,
designing and implementing communication solutions for various types of networks and distributed applications.
B. COURSE SUBJECTS
Introduction: General description of the field; Data communication principles, issues and solutions; Fundamental
aspects of data transmission: Signal transmission; Signal representation; Modulation techniques; Data transmission
protocols: OSI Layer 1 and 2 implementations for different network architectures; Coding: Notion of channel coding;
Block coding; Convolution coding; Mobile networking: Mobile networks characteristics; Mobile networks specific
design issues; Mobile network specific protocols; Mobile network location and mobility management; Ad-hoc mobile
networks: Characteristics of ad-hoc mobile networks; Specific issues; Ad-hoc mobile communication protocols;
Wireless sensor networks; Data compression techniques: Huffman coding, MNP5, V.42; Security in data
communication: General issues; Security in traditional networks and Internet; Security in wireless networks;
Encryption and Authentication Techniques: Symmetric key encryption, RSA, Diffie-Hellman, Digital signature,
SSL/TSL, PGP.
C. APPLICATIONS SUBJECTS (laboratory, seminar, project)
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Evaluation and testing of network protocols using NS-2 (Network Simulator).
Evaluation and testing of wireless network protocols using NS-2 (Network Simulator).
Implementation of a simple protocol stack for data transmission in wireless sensor networks.
Protocol evaluation metrics.
Wireless sensor networks SPIN protocol implementation in NS-2.
Wireless sensor networks Directed Diffusion protocol implementation in NS-2.
Wireless sensor networks SPIN protocol implementation on a 5-node network platform.
Wireless sensor networks Directed Diffusion protocol implementation on a 5-node network platform.
Data encryption library implementation.
Data compression library implementation.
D. BIBLIOGRAPHY
1.
2.
3.
J.G. Proakis, "Digital Communications", 4-th Edition, Prentice-Hall, 2001.
J. Schiller, "Mobile Communications", Addison Wesley, 2000.
Pahlavan, Krishnamurthy, "Principles of Wireless Networks", Prentice Hall, 2002.
E. EVALUATION PROCEDURE
The final grade is composed of the evaluation during the semester at the project workshops and at the course classes
(50%), and of the final written exam evaluation (3 hours, 50%).
F. INTERNATIONAL COMPATIBILITY
1.
2.
3.
Carnegie Mellon University, SUA, Computer Scinece Department, Undergraduate Program: “Computer
Networks” (15-441) , Masters Program: “Networking” (15-744)
Johns Hopkins University, SUA, Whiting School of Engineering, Undergraduate Program: “Introduction to
Information Theory and Coding” (520.447), “Basic Communications” (520.401), “Digital Communications I ”
(520.465), “Digital Communication II ” (520.466)
Stony Brooks State University of New York, SUA, Computer Science Department, Undergraduate Program:
“Data Communications and Networks” (CSE/ISE 310), “Wireless and Mobile Networking“ (CSE370)
26.03.2007
HEAD OF DEPARTMENT
Prof. Dr. Eng. Vladimir CRETU
COURSE INSTRUCTOR,
Assoc.Prof. Dr. Eng. Mihai V. MICEA
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
for the discipline:
“EMERGING SYSTEMS”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I or II (MASTER)
Semester: 1
Course instructor: lecturer Mihai Udrescu, PhD
Applications instructor: teaching assistant Oana Boncalo
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
2
Project
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
This course approaches an essential aspect regarding the engineering training process of the master program:
understanding and employing the emerging computing technologies and techniques. The need for these new
technologies and the benefits that come along are thoroughly explained, as well as the difficulties in implementing
them. The advent of the first commercial quantum computer (built by the D-Wave Systems Company) and its
presentation at Stanford University has transformed quantum computation into a high priority trend within the
emerging computing technology field. This course is presenting the fundamental features that make quantum
computation able to solve in polynomial time (efficiently) some problems that have exponential (inefficient) solutions on
a classical computer.
B. COURSE SUBJECTS
Introduction: ITRS (International Technology Roadmap for Semiconductors) guidelines; The ERD – Emerging
Research Devices Document; Emerging technologies comparison; Introduction to quantum mechanics; Computer
science basics; Quantum Circuits: Quantum algorithms; One-qubit operations; Controlled operations; Measurement;
Universal gate sets; The circuit model of the quantum computer; Quantum systems simulation; Quantum Fourier
transform and its applications: Quantum Fourier transform; Phase estimation; Factoring problem – Shor’s algorithm;
General applications; Quantum search algorithms: Grover’s algorithm; Quantum simulation; Quantum counting; NPcomplete problems solution speedup; Search algorithms performance; Black-box algorithms limitations; Quantum
computer physical implementation: Basic principles; Conditions for quantum computation; Harmonic oscillator
quantum computer; Optical photon quantum computer; Nuclear Magnetic Resonance; Ion Trap technology, Optical
cavity quantum electrodynamics; Quantum computer reliability: Classical noise and Markov models; Quantum noise;
Quantum information measures; Quantum error correction; Quantum error detection and correction codes; Entropy
and information: Entanglement; Quantum cryptography.
C. APPLICATIONS SUBJECTS (laboratory, seminar, project)
Representing quantum states and transformations with procedural programming languages;
Quantum program algorithmic emulation. QPL (Quantum Programming Language) scripts;
Describing quantum circuits with hardware description languages: QHDL and VHDL;
Automated synthesis of quantum circuits with genetic algorithms;
Template-based automated synthesis of quantum circuits;
Quantum circuit reliability assessment: partitioning and reliability graphs;
Simulation-based quantum fault injection in order to evaluate the accuracy threshold as main reliability measure;
Gate-level quantum algorithm simulation by FPGA board configuration;
D. REFERENCES
1. Michael A. Nielsen, Isaac L. Chuang. Quantum Computation and Quantum Information. Cambridge University
Press, 2000.
2. Sandeer K. Shukla, R.. Iris Bahar (Eds.) Nano, Quantum and Molecular Computing: Implications to High Level
Design and Validation. Springer Verlag, 2005.
3. Dan C. Marinescu, Gabriela M. Marinescu. Approaching Quantum Computing. Prentice Hall, 2006.
E. EVALUATION PROCEDURE
The evaluation process output consists of two grades: one for the laboratory activity, which is yielded by evaluating the
implementation of the lab projects, and one for the final exam grade. The relative weight of these grades in the final
grade outcome is 66% for the exam and 33% for the lab projects assessment. The final exam lasts for 120 minutes,
and consists of a written response to 10 short theoretical questions, plus 2 problems (quantum circuit synthesis and
quantum algorithm assessment).
F. INTERNATIONAL COMPATIBILITY
1. Massachusetts Institute of Technology (MIT)
2. University of California Berkeley
3. California Institute of Technology (CALTECH)
Date: 27 March 2007
HEAD OF DEPARTMENT
Prof. Dr. ing. Vladimir CREŢU
COURSE INSTRUCTOR,
Lecturer dr. Mihai UDRESCU-MILOSAV
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
For the discipline:
“HIGH-END INTERFACES AND EQUIPMENTS”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I or II (MASTER)
Semester: 1
Course instructor: professor Mircea Stratulat, PhD
Applications instructor:
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
2
Project
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
The course was originally designed to introduce optical recording systems to undergraduates and postgraduates in
science and engineering
B. COURSE SUBJECTS
1. Introduction to optical recording, Basic optics, Lasers, photoreceptors, media substrates
2. Optical recording drive systems
3. Magneto–optic recording
4. Magneto–optic recording, drive systems
5. DVD recording, HDVD, Ray-blue DVD. Holographic memories, other memories
C. APPLICATIONS SUBJECTS (laboratory, seminar, project)
Optical recording, Basic optics, Lasers, photodectectors, media substrates, Optical recording drive systems, Magneto–
optic recording, Magneto–optic recording, drive systems, DVD recording, HDVD, Ray-blue DVD. Holographic
memories, other memories
D. REFERENCES
1. E.W.Williams – The CD-ROM and Optical Disc Recording Systems. Oxford, 1995
2. S.O.Kasap – Optoelectronics and photonics. -”, Prentice Hall, New Jersey, 2001
3. Linda G. Shapiro, George C: Stockman – Computer Vision - Prentice Hall, New Jersey, 2001
E. EVALUATION PROCEDURE
Examiner 2/3, applications 1/3
F. INTERNATIONAL COMPATIBILITY
1. 1. 1. University of. California. Berkeley,
2. Linkoping Institute of Technology,
3. Massachusetts Institute of Technology
Date: 20.03.2007
HEAD OF DEPARTMENT
COURSE INSTRUCTOR,
Prof. Dr. ing. Vladimir CREŢU
prof.dr.ing.Mircea Stratulat
„POLITEHNICA” UNIVERSITY OF TIMIŞOARA
SYLLABUS
for the discipline:
“RESEARCH TOPICS IN COMPUTER SYSTEMS”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I (MASTER)
Semester: 1
Course instructor: associate professor Marius Minea, PhD, lecturer Radu Marinescu, PhD
Applications instructor:
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
0
Project
0
Evaluation
Distributed
Credits
3
A. COURSE OBJECTIVES
To present research papers that have been influential in shaping the field of software systems. Students will learn to
appreciate past and future developments in the field, contents and structure of a good research paper, make a critical
analysis, a clear and consistent presentation, and participate actively in discussions. The papers will address topics that
are essential both for researchers and practitioners. Thus, students will gain insight into the essence of the most widely
used software techniques, practices and paradigms. By understanding the foundations of current approaches, they will
form solid reference points for taking future competent decisions on adopting novel techniques, practices or paradigms.
B. COURSE SUBJECTS
Programming language paradigms; software system architecture and design; program semantics, specification,
modeling; program analysis techniques; managing software development
C. APPLICATION SUBJECTS (laboratory, seminar, project)
D. REFERENCES
Donald D. Chamberlin, Raymond F. Boyce - SEQUEL: A Structured English Query Language, 1974
Frederick P. Brooks, Jr: The Mythical Man-Month, 1975
Walter Tichy: Software development control based on module interconnection, ICSE-4, 1979
Mark Weiser: Program Slicing, ICSE-5, 1981.
D. L. Parnas, P. C. Clements, D. M. Weiss: The Modular Structure of Complex Systems, ICSE-7, 1984
Frederick Brooks, Jr.: No Silver Bullet: Essence and Accidents of Software Engineering. Computer, 1987
Lee Osterweil: Software processes are software too, ICSE-9, 1987.
David Ungar, Randall B. Smith - Self: The Power of Simplicity. OOPSLA, 1987
David Harel, H. Lachover, A. Naamad, Amir Pnueli, Michal Politi, Rivi Sherman, Aharon Shtul-Trauring: Statemate: A
Working Environment for the Development of Complex Reactive Systems, ICSE-10, 1988
David S. Rosenblum: Towards a Method of Programming with Assertions, ICSE-14, 1992
W. Harrison and H. Ossher - Subject-Oriented Programming (A Critique of Pure Objects) OOPSLA, 1993
Michael Jackson, Pamela Zave: Deriving Specifications from Requirements: An Example, ICSE-17, 1995
J. Dean, C. Chambers, and D. Grove: Selective Specialization for Object-Oriented Languages, PLDI, 1995
Bjarne Steensgaard, Points-to Analysis in Almost Linear Time, POPL, 1996
George Necula: Proof-Carrying Code, POPL, 1997
E. EVALUATION PROCEDURE
Students will each present one paper and participate in the discussion of other papers, both activities contributing to the
final grade.
F. INTERNATIONAL COMPATIBILITY
1. What Makes Good Research in Software Engineering, course 17-939A, Carnegie Mellon University
http://spoke.compose.cs.cmu.edu/ser04/course-info.htm
2. Research Topics in Software Engineering, course P02102, University of Edinburgh
http://www.drps.ed.ac.uk/06-07/course.php?code=P02012
3. Research inSoftware Engineering, course CMSC 838p, University of Maryland
http://www.cs.umd.edu/~vibha/838p/
Date: 28.03.2007
HEAD OF DEPARTMENT
Prof. Dr. ing. Vladimir CREŢU
COURSE INSTRUCTOR,
SEMESTRUL 2
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
for the discipline:
“EMBEDDED SYSTEMS”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I (MASTER)
Semester: 2
Course instructor: professor Mircea Popa, PhD
Applications instructor:
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
2
Project
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
- to understand the design goals and methodologies for high performance embedded computing;
- to learn the main and specific topics for high performance embedded systems;
- to understand the modeling process for embedded systems;
- to obtain a consistent overview of the specific problems of the embedded systems;
- to be able to outline the adequate embedded system architecture for a type of applications.
B. COURSE SUBJECTS
High-Performance embedded computing: Design goals; Design methodologies; Models of computation; Typical
architectures; CPUs: Microprocessors vs. Microcontrollers vs. DSPs; Parallel execution mechanisms; Processor
memory hierarchy; CPU simulation; Automated CPU design; Programs: Code generation; Program performance
analysis; Models of Computation and Programming; Processes and operating systems: Real-time process scheduling;
Operating system design; Verification; Modeling embedded systems: System level modeling; Models of computation;
Represntations of different models; Specific software: The GNU toolchain; The GNU assembler; The GNU linker;
Converting files; The GNU debugger; Specific topics: Design and validation of embedded systems; Design and
verification languages; Operating systems; Timing and performance analysis; Memory organization techniques for low
power computing; Power aware computing; Security; Applications
C. APPLICATIONS SUBJECTS
(laboratory; seminar; project)
Projects:
1. Modeling embedded systems
2. The GNU operating systems
3. Operating systems for embedded systems
4. Programming languages for embedded systems
5. System-on-chip’s (SoC’s)
6. Network-on-chip’s (NoC’s)
7. Debugging embedded systems
8. Solutions for minimizing the consumption in embedded systems
D. REFERENCES
1. W. Wolf: High-Performance Embedded Computing, Elsevier, 2006
2. A. Jantsch: Modeling Embedded Systems and SoC’s: Concurrency and Time in Models of Computation, Morgan
Kaufmann, 2004
3. R. Zurawski: Embedded Systems Handbook (Industrial Technology), CRC, 2005
E. EVALUATION PROCEDURE
Exam and project each of them with 50% of the final note.
F. INTERNATIONAL COMPATIBILITY
1. University of Essex: Advanced Embedded System Design
2. University of Utah School of Computing: Advanced Embedded Systems
3. University of Leicester: Embedded Systems for condition monitoring and control.
Date: 26.03.2007
HEAD OF DEPARTMENT
Prof. dr. ing. Vladimir CREŢU
COURSE INSTRUCTOR;
Prof. dr. ing. Mircea POPA
"POLITEHNICA" UNIVERSITY OF TIMISOARA
SYLLABUS
for the discipline:
"ROBOTIC SYSTEMS"
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of Studies: I (MASTER)
Semester: 2
Course instructor: associate professor Mihai V. Micea, PhD
Applications instructor: teaching assistant Dan Chiciudean
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
Project
2
0
2
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
The course objective is to learn the theory and practice of mobile robotic systems and applications. The students will
gain advanced knowledge on designing and implementing relative complex applications which involve real world
problems like robot movement control, navigation and interaction, obstacle avoidance using robotic modular perception
equipment and techniques. The students will apply the learned knowledge using real-life systems during course
projects.
B. COURSE SUBJECTS
Introduction: General description of the field; Overview and preliminaries; Application of robotic systems. General
architecture: Description of the main blocks and subsystems. Power supply block: Battery types, Charging modules,
Power control and management. Locomotion subsystem: Locomotion types (Tricycle method, Differential system,
Ackerman principle, Syncronous locomotion systems); Electric motors (DC, steppers, brushless); Electric motor driving
techniques (H-bridge, PWM). Perception block: Transducers and sensors (proximity and collision, ultrasonic sensors,
optic and video sensors); Data acquisition and processing. Control subsystem: Central processing unit (embedded
systems, microcontrollers); Data communication block (wireless communication: 802.11 standard, 802.15.4 standard,
bluetooth, GSM and GPRS modules). Robot operating modes: Remote control (tele-operation); Autonomous
operation techniques. Navigation and localisation techniques: Obstacle avoidance algorithms, GPS and ultrasonic
localisation, 3D perception. Collaborative robotic systems: Robot swarms; Distributed sensing and control;
Cooperative behavior.
C. APPLICATION SUBJECTS (projects)
1.
2.
3.
4.
5.
Maze solving project: the mobile robot must find autonomously its way out from a predetermined starting position
next to the central area of the maze.
Line following robot: the robot must follow a light-reflective stripe.
Autonomous mini-vehicle using ultrasonic Sonar. Desing and implementation.
Autonomous orientation and obstacle avoidance techniques implemented on the Sonar-based robot.
Soccer player robotic team: development of a robotic team to play a simplified soccer game.
D. BIBLIOGRAPHY
4.
5.
U. Nehmzow, "Mobile Robotics: A practical introduction", 2nd Edition, Springer-Verlag London, 2003.
G. Dudek, M. Jenkin, "Computational Principles of Mobile Robotics", Cambridge University Press, 2000.
6.
G. Branwyan, "Absolute Beginner’s Guide to Building Robots", Que, 2003.
E. EVALUATION PROCEDURE
The final grade is composed of the evaluation during the semester, at the project workshops and at the course classes
(50%), and of the final written exam evaluation (3 hours, 50%).
F. INTERNATIONAL COMPATIBILITY
4.
5.
6.
University of Ottawa, Canada, Computer Engineering, Undergraduate Program: “Computer Control in Robotics”,
“Robotics: Intelligent Connection of the Perception to Action”
Carnegie Mellon University, SUA, The Robotics Institute, Undergraduate Minor in Robotics: "Introduction to
Robotics " (16-311), "Introduction to Mobile Robot Programming" (16-362 / 16-862)
University of Cambridge, UK, Department of Engineering, Undergraduate Program: "Computer Vision and
Robotics " (4F12)
26.03.2007
HEAD OF DEPARTMENT
Prof. Dr. Eng. Vladimir CRETU
COURSE INSTRUCTOR,
Assoc.Prof. Dr. Eng. Mihai V. MICEA
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
for the discipline:
“OPTIC FIBER TRANSMISSIONS”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I (MASTER)
Semester: 2
Course instructor: professor Mircea Stratulat, PhD
Applications instructor:
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
2
Project
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
If you hope to become a professional in components field and concentrate in the area of optical fiber, transmitters,
receivers, amplifiers, and active and passive components, you will need understanding of the technology.
B. COURSE SUBJECTS
1. Introduction to Telecommunications and Fiber Optics
2. Optical Fibers – Basics2.1 Attenuation, 2.2 Intermodal and Chromatic Dispersion, 2.3 Bit Rate and Bandwidth
3. Multimode Fibers
4. Singlemode Fibers
5 Fabrication, Cabling, and Installation
6. Receivers, Light sources and Transmitters
7. Components of Fiber – Optic Networks 7.1. Passive Components, Switches, and Functional Modules of Fiber Optic
Network
8. An Introduction to Fiber Optic Networks
C. APPLICATIONS SUBJECTS
(laboratory, seminar, project)
Optical Fibers Basics, Attenuation, Intermodal and Chromatic Dispersion, Bit Rate and Bandwidth, .Multimode
Fibers, Single mode Fibers, Fabrication, Cabling, and Installation, Receivers, Light sources and Transmitters,
Components of Fiber – Optic Networks, Passive Components, Switches, and Functional Modules of Fiber Optic
Network, An Introduction to Fiber Optic Networks
D. REFERENCES
1. Jeff Hecht – Understanding Fiber optics – Howard w. Sams&Company. Prentice Hall, New Jersey, 2001
2. D.Mynbaev, L.L. Scheiner – Fiber Optic Communication Technology - . Prentice Hall, New Jersey, 2001
3. Leon W. Couch – Digital and analog Communication Systems, sixth edition, Prentice Hall, New Jersey, 2000
E. EVALUATION PROCEDURE
Examiner 2/3, applications 1/3
F. INTERNATIONAL COMPATIBILITY
1. 1.University of. California. Berkeley,
2. Linkoping Institute of Technology,
3. Massachusetts Institute of Technology
Date:
HEAD OF DEPARTMENT
Prof. Dr. ing. Vladimir CREŢU
COURSE INSTRUCTOR,
prof.dr.ing.Mircea Stratulat
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
for the discipline:
“CELLULAR DATA NETWORKS”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I (MASTER)
Semester: 2
Course instructor: lecturer Doru Todincă, PhD
Applications instructor: lecturer Doru Todincă, PhD
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
Project
2
0
2
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
The goals of the course are to give first an overview of mobile communication systems, then to give more detail about
cellular data network, with an emphasis on mobile data networks.
B. COURSE SUBJECTS
1. Introduction: applications, history, market vision
2. Wireless Transmission: frequencies & regulations, signals, antennas, signal propagation, multiplexing, modulation,
spread spectrum, cellular system
3. Medium Access Control: motivation, SDMA, FDMA, TDMA (fixed, Aloha, CSMA, DAMA, PRMA, MACA, collision
avoidance, polling), CDMA
4. Telecommunication Systems: GSM, UMTS/IMT-2000
5. GPRS/EGPRS: main concepts, system architecture, protocol architecture, Quality of Service (QoS)
6. Wireless LAN: IR vs. radio, infrastructure/ad-hoc, IEEE 802.11 (a, b, g, h), HiperLAN2, mobile QoS, Bluetooth,
IEEE 802.15
7. Mobile Network Layer: Mobile IP, DHCP, ad-hoc networks, routing optimization
8. Research issues concerning cellular data networks: QoS and QoS differentiation; applications of artificial
intelligence techniques in cellular data networks
C. APPLICATIONS SUBJECTS
(laboratory, seminar, project)
Students can choose one of two types of projects:
- Select a particular topic of component mobile communication and analyse it in detail, writing a
technical report
- Design a simulation model of a mobile data network
D. REFERENCES Se pastreaza indicatiile din modelul in lb. romana
1. Jochen H. Schiller, Mobile Communications, second edition, Addison-Wesley, 2003, ISBN 0 32112381 6
2. William Stallings, Wireless Communications and Networking, Prentice Hall, 2005
3. T. Halonen, J. Romero, J. Molero (editors), GSM, GPRS and EDGE Performance, John Wiley & Sons LTD, 2002
E. EVALUATION PROCEDURE
50% written examination and 50% evaluation of assignments
F. INTERNATIONAL COMPATIBILITY Se pastreaza indicatiile din modelul in lb. romana
1. University of California, Irvine, U.S.
2. Dublin City University, Ireland
3. Freie Universität Berlin, Germany
Date:
HEAD OF DEPARTMENT
Prof. Dr. ing. Vladimir CREŢU
COURSE INSTRUCTOR,
Conf. Dr. Ing. Doru TODINCA
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
for the discipline:
“AUTOMATIC DESIGN AND OPTIMIZATION OF VLSI CIRCUITS”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I (MASTER)
Semester: 2
Course instructor: professor Marius Crişan, PhD
Applications instructor:
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
2
Project
0
Evaluation
E
Credits
9
A. COURSE OBJECTIVES
Upon completion of the course, students will have an understanding of the characteristics of CMOS circuit construction
and emerging nanometer-scale electronic circuit technologies and processes. Stuents will be able to use mathematical
methods and circuit analysis models in analysis of VLSI circuits, including logic components and their interconnect.
Students will be able to complete a significant VLSI design project having a set of objective criteria and design
constraints.
B. COURSE SUBJECTS
Introduction, Objectives: VLSI concept. VLSI design methodology. Transistors and layout.
CMOS Process and Layout: Basic CMOS device topology and fabrication. Construction of digital logic gates in
CMOS.
Advanced interconnect models: Delay bottlenecks. Reducing crosstalk. Modeling copper interconnect.
Power Estimation and Optimization: Advanced low-power design techniques. Minimizing power utilization.
CAD Systems and Algorithms: Overview of HDLs. Practical IP-based design solutions
C. APPLICATIONS SUBJECTS
(laboratory, seminar, project)
1. Designing and simulating CMOS gates
2. Designing a simple sequential circuit (e.g. one-bit accumulator)
3. Designing a comparator of two n-bit numbers.
4. Designing a 4-bit Parallel Full Adder with carry-look-ahead.
5. Designing “latch” and memory circuits.
6. Designing a A/D and D/A converter.
D. REFERENCES Se pastreaza indicatiile din modelul in lb. romana
1. Neil Weste, David Harris, CMOS VLSI Design: A Circuits and Systems Perspective, 3rd Edition, , Addison Wesley,
2003
2. Wayne Wolf, Modern VLSI Design, 3rd edition, Prentice Hall, 2002.
3. Rabaey, J., et al., Digital Integrated Circuits: A Design Perspective, 2nd. ed., Prentice Hall Publishers, Inc., 2003.
E. EVALUATION PROCEDURE
There will be a final examination from lecture notes and project paper. The paper will be graded on technical content,
format, and writing skill. 40% lab assignments and 60% final exam and project paper.
F. INTERNATIONAL COMPATIBILITY Se pastreaza indicatiile din modelul in lb. romana
1. University of Massachusetts: VLSI Design Principles
2. University of South Carolina: Design of VLSI Circuits
3. Princeton University: Design of VLSI Sytems
Date: 20.03.2007
HEAD OF DEPARTMENT
COURSE INSTRUCTOR,
Prof. Dr. ing. Vladimir CREŢU
Prof.dr.ing. Marius Crisan
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
for the discipline:
“VIRTUAL MEASUREMENT SYSTEMS”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I (MASTER)
Semester: 2
Course instructor: professor Mircea Popa, PhD
Applications instructor:
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
2
Project
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
- to understand the Virtual Instrumentation (VI) concept, its features, advantages and implementation;
- to learn about a classical VI software, the National Instruments’ LabVIEW, the programming techniques and concepts
from labVIEW;
- to learn about the hardware needed for instrumentation;
- to be able to design a LabVIEW based virtual instrument.
B. COURSE SUBJECTS
Overview of virtual instrumentation: Evolution of virtual instrumentation (VI); Architecture of a virtual instrument;
Software level; Advantages of VI; LabVIEW; VI in engineering; Programming techniques: LabVIEW environment;
Dataflow programming; G programming; Programming concepts: Control structures; Selection structures; Arrays;
Clusters; Strings; Waveform charts and graphs; Tables; File input/ output; Inputs and outputs: Transducers; Sensors;
Signal operations; A/D and D/A control; Interfaces for instrumentation: Current loops; RS232; RS422; RS485; GBIP;
VISA; Input/ output buses: USB; PCI; PCI Express; PXI; PCMCIA; VXI; LXI; Data acquisition: Data acquisition in
LabVIEW; Hardware installation and configuration; Data acquisition hardware; Data acquisition software; Data
transmission: Pulse codes; A/D modulation techniques; Wireless communications; Distributed automation and control
systems; SCADA; Applications
C. APPLICATIONS SUBJECTS
(laboratory, seminar, project)
Projects:
1. Remote data acquisition using the ADVANTECH PCI 1710 board and LabVIEW
2. Remote data analysis and control using the ADVANTECH PCI 1712 board and LabVIEW
3. Remote data acquisition using the ADVANTECH PCL 816 board and
4. Study of the IEEE 1488 GPIB interface
5. Client – Server applications in LabVIEW
6. Distributed virtual instrumentation with LabVIEW
7. LabVIEW based robot control system
8. LabVIEW tools
D. REFERENCES
1. J. Travis: LabVIEW for Everyone (2nd Edition), CRC, 2002
2. S. Sumathi, P. Surehka: LabVIEW based Advanced Instrumentation Systems, Springer-Verlag, 2007
3. R. Bitter, T. Mohiuddin, M. Nawrocki: LabVIEW Advanced Programming Techniques, 2006
E. EVALUATION PROCEDURE
Exam and project each of them with 50% of the final note.
F. INTERNATIONAL COMPATIBILITY
1. University of Glasgow: MSc Virtual Instrumentation
2. Cornell University: Computer Instrumentation Design
3. New Jersey’s Science & Technology University: Virtual Instrumentation
Date: 26.03.2007
HEAD OF DEPARTMENT
Prof. dr. ing. Vladimir CREŢU
COURSE INSTRUCTOR,
Prof. dr. ing. Mircea POPA
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
for the discipline:
“INTRODUCTION TO RESEARCH”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I (MASTER)
Semester: 2
Course instructor: each dissertation thesis coordinator for his master students group
Applications instructor:
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
0
Project
0
Evaluation
Distributed
Credits
3
A. COURSE OBJECTIVES
The main objective of the discipline “Introduction to research activity” is the creation of support for the
student-centered research activities. The coordinators introduce, based on their experience, the main specific
aspects of the research activity.
B. COURSE SUBJECTS
Research methodology, bibliographical synthesis elaboration, practical aspects of research activity.
Establishing the dissertation thesis domain.
C. APPLICATIONS SUBJECTS
Each master student will elaborate a state-of the-art report concerning his dissertation thesis domain as
starting point for the dissertation thesis elaboration.
D. REFERENCES
Specific domain bibliography and references
E. EVALUATION PROCEDURE
The state-of-the-art report will be presented and defended by each master student in a special presentation
session, and will be evaluated by a commission
F. INTERNATIONAL COMPATIBILITY
Date: 27-th of March 2007
HEAD OF DEPARTMENT
Prof. Dr. ing. Vladimir CREŢU
COURSE INSTRUCTOR,
SEMESTRUL 3
"POLITEHNICA" UNIVERSITY OF TIMISOARA
SYLLABUS
for the discipline:
"ADVANCED DIGITAL SIGNAL PROCESSING"
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of Studies: I or II (MASTER)
Semester: 1
Course instructor: associate professor Mihai V. Micea, PhD
Applications instructor: teaching assistant Dan Chiciudean
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
Project
2
0
2
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
The course focuses on the advanced techniques and algorithms used in digital signal processing. Students will learn the
main design and analysis techniques of advanced types of digital filters such as: efficient FIR and IIR filters, adaptive
filters, linear prediction and optimum filters. Students will also gain abilities of designing and implementing advanced
digital signal processing algorithms and systems using generic and specialized digital devices (Digital Signal Processors
– DSPs).
B. COURSE SUBJECTS
Implementation of discrete-time systems: Structures for FIR and IIR systems; State-space system analysis and
structures; Quantization of filter coefficients; Round-off effects in digital filters. Design of digital filters: Generic
model for digital filter design; Design of FIR and IIR filters; Frequency transformations; Design of digital filters based
on Least-Squares Method. Multirate digital signal processing: Decimation and interpolation; Sampling rate
conversion; Filter design and implementation for sampling-rate conversion; Multistage implementation of sampling-rate
conversion; Applications of multirate signal processing. Design of adaptive digital filters: Goal of adaptive digital
filtering; General concepts; Theory of Wiener-type digital filters; Adaptive LMS algorithm; Least-Squares recursive
algorithm; Applications of adaptive digital filtering. Elements of spectral analysis and estimation: Principle and
traditional methods of spectral estimation; Modern methods of parametric estimation; Applications of spectral analysis.
Linear prediction and optimum linear filters: Forward and backward linear prediction; Properties of the linear
prediction – error filters; Applications of linear prediction.
C. APPLICATIONS SUBJECTS (laboratory, seminar, project)
11.
12.
13.
14.
15.
16.
17.
18.
19.
Architecture and programming of the Freescale StarCore DSP system.
FFT implementation and evaluation on a PC and on the StarCore DSP.
Implementation and evaluation of FIR digital filters on a PC and on the StarCore DSP.
Implementation and evaluation of IIR digital filters on a PC and on the StarCore DSP.
Design and implementation of a digital audio effects processor.
Design and implementation of a digital audio equalizer on specialized devices (DSP).
Design, implementation and analysis of multirate systems.
Adaptive digital filters: design, implementation and evaluation.
Linear prediction filters: design, implementation and evaluation.
D. BIBLIOGRAPHY
7.
G. Proakis, D. G. Manolakis, "Digital Signal Processing. Principles, Algorithms and Applications", 3rd Edition,
Prentice-Hall, 1996.
8.
9.
A. V. Oppenheim, R. W. Schafer, "Digital Signal Processing", Prentice-Hall, 1996.
S. Stergiopoulos (editor), "Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar,
and Medical Imaging Real-Time Systems", CRC Press LLC, 2001.
E. EVALUATION PROCEDURE
The final grade is composed of the evaluation during the semester at the project workshops and at the course classes
(50%), and of the final written exam evaluation (3 hours, 50%).
F. INTERNATIONAL COMPATIBILITY
7.
8.
9.
Massachusetts Institute of Technology, SUA, Department of Electrical Engineering and Computer Science,
Basic Undergraduate Program: "Discrete-Time Signal Processing" (6.341, A. V. Oppenheim, V. K. Goyal), "Digital
Speech Processing" (6.343, T. F. Quatieri), "Introduction to Communication, Control, and Signal Processing"
(6.011, A. V. Oppenheim, G. C. Verghese)
Carnegie Mellon University, SUA, Department of Electrical and Computer Engineering, Undergraduate
Program: "Advanced Digital Signal Processing" (18-792), "Digital Signal Processing" (18-491), "Digital
Communication and Signal Processing Systems Design" (18-551)
University of Cambridge, UK, Department of Engineering, Undergraduate Program: "Digital Filters and
Spectrum Estimation" (4F7, S. J. Godsill, S. Singh), "Signals and Systems" (3F1, J.M. Goncalves, N.G.
Kingsbury), "Signal and Pattern Processing" (3F3, S. J. Godsill)
G. OBSERVATIONS
1.
2.
3.
The course is presented using PowerPoint slides with a video projector. Students can receive the course support
(course slides) in electronic or printed format.
The project and application workshops will be hosted by the Digital Signal Processing Laboratories – DSPLabs,
which provides latest generation equipments and specialized modules through various partnerships with topranking companies in the domain, such as: Motorola/Freescale, Alcatel-Lucent, etc.
Interested students have the opportunity to collaborate at various projects and research contracts, developed within
the DSPLabs. Such participation replaces the applicative activities required by the syllabus.
26.03.2007
HEAD OF DEPARTMENT
Prof. Dr. Eng. Vladimir CRETU
COURSE INSTRUCTOR,
Assoc.Prof. Dr. Eng. Mihai V. MICEA
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
For the discipline:
“INTEGRATED INFORMATION SYSTEMS”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I or II (MASTER)
Semester: 1
Course instructor: Associate professor Horaţiu Moldovan, PhD
Applications instructor: ing. Ronald Wagmann
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
2
Project
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
The course was originally designed to understand what is the role of an ERP (Enterprise Resource Planning) system for
an enterprise, to be able to define and modify database structure, to show all the functions and modules of an ERP
system and to present implementation methodologies for an ERP system.
B. COURSE SUBJECTS
1. Introduction to information systems, defining and classifying integrated information systems
2. Enterprise organization
3. Life cycle of an ERP system
4. Enterprise business analysis
5. Technologies. Architectures. Design of ERP systems
6. Business processes
7. ERP implementation
8. Developing an ERP system
C. APPLICATIONS SUBJECTS
(laboratory, seminar, project)
We will demonstrate all the functionality of an ERP system. This includes an overview of the basis modules of an ERP
such as Accounting, Controlling, Material Management, Sales and Distribution and Production Planning. We will
create scenarios to simulate the main activities that take place in an enterprise.
D. REFERENCES
1. Travis Anderegg – ERP: A-Z Implementer’s Guide for Success. Resource Pub, SUA, 2000
2. Doina Fotache, Luminiţa Hurbean – Integrated information systems for managing businesses –
ERP, Ed.Economică, Bucureşti, 1999
3. ***, SAP Documentation; SAP Germany 2006 online
E. EVALUATION PROCEDURE
Examiner 2/3, applications 1/3
F. INTERNATIONAL COMPATIBILITY
1. University of Southern California, USA
2. Wien Institute of Technology, Austria
3. University of Missouri, USA
Date: 10.09.2007
HEAD OF DEPARTMENT
Prof. Dr. ing. Vladimir CREŢU
COURSE INSTRUCTOR,
Conf. Dr. Ing. Horaţiu MOLDOVAN
"POLITEHNICA" UNIVERSITY OF TIMISOARA
SYLLABUS
for the discipline:
"EMERGENT AND COLLECTIVE INTELLIGENCE SYSTEMS"
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of Studies: I or II (MASTER)
Semester: 1
Course instructor: associate professor Mihai V. Micea, PhD
Applications instructor: teaching assistant Răzvan-Dorel Cioargă
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
Project
2
0
2
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
The primary objective is to learn some of the main advanced techniques and architectures underlying distributed
systems and collaborative environments. The course is targeted at understanding and obtaining hands-on experience
with distributed, collaborative environments such as wireless sensor networks or robotic collectives, which are often
composed using relatively inexpensive nodes requiring low power consumption, processing power and bandwidth. The
students will apply the learned knowledge in working with real systems in course projects.
B. COURSE SUBJECTS
Introduction: Introduction to Distributed Systems; Examples and Applications of Distributed Systems; Introduction to
Emergent Behavior; Examples and Applications of Emergent Behavior. Distributed Embedded and Robotic Systems:
Real-time Operation; Fault Tolerance; Distributed Communications; Programming Paradigms. Emergent Behavior:
Principles of Emergent Behavior; Formalization of Emergent Behavior Patterns; Programming Paradigms;
Collaborative Environments: Scalable Networks; Discovery; Auto-configuration; Collaboration.
C. APPLICATIONS SUBJECTS (laboratory, seminar, project)
20.
21.
22.
23.
24.
25.
26.
27.
28.
Introduction to the architecture of a collaborative system node.
Basic programming of the collaborative system node.
Introduction to the eBML (Emergent Behavioral Modeling Language). Applications.
Solving a specific task for a collaborative system using distributed systems paradigms. Formal modeling using
eBML.
Solving a specific task for a collaborative system using emergent behavior patterns systems paradigms. Formal
modeling using eBML.
Implementing the “distributed” solution.
Implementing the “emergent” solution.
Comparison between solutions.
Presentation of final report
D. BIBLIOGRAPHY
10. S. Russell, P. Norvig, "Artificial Intelligence: A Modern Approach", 2nd Ed., Prentice Hall, 2002.
11. M. Wooldridge, "An Introduction to MultiAgent Systems", Wiley & Sons, 2002.
12. R.C. Arkin, "Behavior-Based Robotics (Intelligent Robotics and Autonomous Agents)", MIT Press, 1998.
E. EVALUATION PROCEDURE
The final grade is composed of the evaluation during the semester at the project workshops and at the course classes
(33%), and of the final exam evaluation. The final exam is composed of a theory module (1.5 hours, 33%) and a
problem solving module (1.5 hours, 34%). Each of the final exam modules can be attended independently.
F. INTERNATIONAL COMPATIBILITY
10. Carnegie Mellon University, USA, Department of Electrical Engineering and Computer Science, Undergraduate
Program, “Wireless Sensor Networks” (18748), “Distributed Systems” (18842), “Special Topics in Systems and
Control: Multi-Agent Systems” (18879N)
11. California Institute of Technology, USA, Computer Science, Undergraduate and Graduate Programs, “CS 141
abc. Distributed Computation Laboratory”
12. Université de Lausanne, Switzerland, HEC (Ecole des Hautes Etudes Commerciales), “Intelligent Agents for
Collaborative Information System” (“Agents Intelligents pour Système d'information Collaboratif”), Min-Jung
YOO.
26.03.2007
HEAD OF DEPARTMENT
Prof. Dr. Eng. Vladimir CRETU
COURSE INSTRUCTOR,
Assoc.Prof. Dr. Eng. Mihai V. MICEA
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
for the discipline:
“EVOLVABLE HARDWARE”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I or II (MASTER)
Semester: 1
Course instructor: assistant professor Lucian Prodan, PhD
Applications instructor: teaching assistant Versavia Ancuşa, teaching assistant Alexandru Amaricăi,
teaching assistant Oana Boncalo
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
2
Project
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
This course is a graduate level complement to Reconfigurable Computing (8L1.1.1) and Fault Tolerant Computing
(8L2.5). It introduces a range of computational models that appeared at the crosspoints between reconfigurable
hardware and evolutionary algorithms in the recent years as an attempt to solve traditionally hard computational
problems. The course surveys relevant aspects of means to evolve reconfigurable architectures by using evolutionary
techniques inspired from biological processes pertaining to phylogeny, ontogeny and epigenesis. In particular, the
following topics will be discussed: evolvability characteristics, evolutionary computation and design, traditional and
novel reconfigurable architectures, evolvable hardware. Typical applications will illustrate the mentioned approaches.
B. COURSE SUBJECTS
Chapter 1. Introduction
1.1. Characteristics of Evolvable Circuits and Systems
1.2. The Good and The Bad of Evolvable Hardware
1.3. Technology and Applications
1.4. Evolvable VS Evolved Hardware
1.5. Intrinsic VS Extrinsic Evolution. Online VS Offline Evolution
Chapter 2. Fundamentals of Evolutionary Computation
2.1. Definition of Evolutionary Algorithms
2.2. Components of an EA: Representation, Variation, Evaluation, Selection, Population and Termination Criteria
2.3. Peramenter Tuning and Selection of Best EA
Chapter 3. Reconfigurable Digital Devices
3.1. Basic Architectures: PLDs and FPGAs
3.2. Using Reconfigurable Hardware. Design Phase. Execution Phase
3.3. Experimental Results
3.4. The POEtic Architecture. Organic Subsystem. Molecules. Routing Layer
Chapter 4. Using Evolvable Hardware (EHW)
4.1. Synthesis VS Adaptation
4.2. Design of Self-Adaptive Systems. Fault Tolerant and Real Time Systems
4.3. Online Reconfigurable Systems
4.4. Examples of EHW-based Fault Recovery
C. APPLICATIONS SUBJECTS
(laboratory, seminar, project)
The project can comprise of
4. a thorough survey of a topic, with original insight
5. a development of a new scheme, or a fresh implementation of an existing scheme
6. or modeling and analysis of an existing scheme.
A project proposal, a progress report and a final report will be due at the beginning, in the middle and at the end of the
semester. The proposal should include a title, name, one paragraph abstract, motivation, proposed approach and
applicable references The progress report should indicate that at least half of work has been finished, with a summary of
the findings, any refinements of the objectives as a result of the past study, what the final report will contain and the
applicable references. An oral presentation is required. The final report should follow the structure and formatting of a
research paper.
D. REFERENCES
1. D. Mange, M. Tomassini (eds.). Bio-Inspired Computing Machines. Towards Novel Computational Architectures.
Presse Polytechniques et Universitaires Romandes, 1998.
2. G.W. Greenwood, A.M.Tyrrell. Introduction to Evolvable Hardware. A Practical Guide for Designing Self-Adaptive
Systems. IEEE Press Series on Computational Intelligence, 2007.
3. R.S. Zebulum et al. (eds.). Proceedings of the NASA/DoD Conference on Evolvable Hardware (EH’05). IEEE
Computer Society, Los Alamitos CA, 2003-2005.
E. EVALUATION PROCEDURE
Course ends with a 2 hour written exam accounting for 50%. Candidates will have to cover several subjects (3-4) based
on course topics. Projects are based on a one page proposal that should include motivation, brief scope of study and
some specific references. The progress report and the final report will account for 20% and 30% of the final mark.
F. INTERNATIONAL COMPATIBILITY
1. University of Missouri-Rolla, CpE/EE/SysEng 301 – Evolvable Hardware (Adaptive Devices, Circuits and Systems)
2. Brno University of Technology, EUD – Evolutionary and Unconventional Hardware
3. University of Oslo, INF-EHW – Evolutionary Computation and Evolvable Hardware
Date:
HEAD OF DEPARTMENT
Prof. Dr. eng. Vladimir CREŢU
COURSE INSTRUCTOR,
Assist. Prof. Dr. Lucian PRODAN
„POLITEHNICA” UNIVERSITY OF TIMIŞOARA
SYLLABUS
for the discipline:
“ADVANCED ARTIFICIAL INTELLIGENCE”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: I or II (MASTER)
Semester: 1
Course instructor: professor Marius Crişan, PhD
Applications instructor:
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
2
0
2
Project
0
Evaluation
Exam
Credits
9
A. COURSE OBJECTIVES
The course starts with a review of the theory and practice of the most advanced strategies in AI and how to utilize the
various techniques in knowledge-based systems. Then, the cognitive processes (perception, memory, language and
thought) are investigated. Finally, the main research approaches are presented that may lead to valid intelligent
techniques suitable for various applications. Upon completion of this course students will be able to provide solutions
for solving real human-like problems and develop their own research approaches.
B. COURSE SUBJECTS
1. Computational approaches in mental function modeling.
2. Models of vision and aural perception.
4
3. Memory systems.
4
4. Natural language processing
4
5. Reasoning and thinking models. 4
6. Learning and development.
4
7. Quantum model of brain.
4
Total 28
C. APPLICATIONS SUBJECTS
4
(laboratory, seminar, project)
1. Sensory system modeling based on self-organizing neural networks. 4
2. Models of perception and memory.
4
3. Complexity and information content analysis of cognitive systems. 4
4. Models of natural language understanding.
4
5. Approaches in Q & A systems. 4
6. Learning by simulating evolution.
4
7. Development of a mind/brain model based on quantum computing. 4
Total 28
D. REFERENCES Se pastreaza indicatiile din modelul in lb. romana
1.
2.
3.
S. Russell and P. Norvig. “Artificial Intelligence- A Modern Approach.” Prentice Hall, 2003.
T. Malim: “Cognitive Processes”, Macmillan Press Ltd, 1994 (translated Ro. Ed. Tehnica 1999)
Speech and Language Processing: An Introduction to Natural Language Processing, Computational
Linguistics, and Speech Recognition. By Daniel Jurafsky and James H. Martin. Prentice-Hall, 2000.
E. EVALUATION PROCEDURE
There will be a final examination from lecture notes weighting 60% of the final grade. The lab assignments weight
40% of the final grade.
F. INTERNATIONAL COMPATIBILITY Se pastreaza indicatiile din modelul in lb. romana
1. University of Houston: Advanced Artificial Intelligence
2. New York University: Advanced Artificial Intelligence
3. University of Adelaide: Advanced Artificial Intelligence
Date: 20.03.2008
HEAD OF DEPARTMENT
COURSE INSTRUCTOR,
Prof. Dr. ing. Vladimir CREŢU
Prof.dr.ing. Marius Crisan
„POLITEHNICA” UNIVERSITY FROM TIMIŞOARA
SYLLABUS
for the discipline:
“DIRECTED THESIS RESEARCH”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER SYSTEMS ENGINEERING
Year of studies: II (MASTER)
Semester: 1
Course instructor: each dissertation thesis coordinator for his master students
Applications instructor:
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
0
2
0
Project
0
Evaluation
Distributed
Credits
3
A. COURSE OBJECTIVES
Directed thesis research activity has as main objective to create the support for the student-coordinator
collaboration.
The main objective of directed thesis research activity is the elaboration of the dissertation thesis proposal by
the master student.
B. COURSE SUBJECTS
Starting from the state-of–the-art report and focusing on thesis topic, the master student will elaborate the
dissertation thesis proposal, under surveillance of the coordinator
C. APPLICATIONS SUBJECTS
Elaboration of the dissertation thesis proposal document
D. REFERENCES
E. EVALUATION PROCEDURE
The dissertation thesis proposal will be presented and defended by each master student in a special
presentation session, and will be evaluated by a commission.
F. INTERNATIONAL COMPATIBILITY
Date: 27-th of March 2007
HEAD OF DEPARTMENT
Prof. Dr. ing. Vladimir CREŢU
COURSE INSTRUCTOR,