Erasmus ECTS Information Package

Erasmus ECTS Information Package
Faculty of EEEA
0558 Communication and Geoinformation Technologies
ECTS credits: 3
Weekly classes: 3lec+0sem+0labs+3ps
Assessment: exam
Type of exam: written
Departments involved:
Department of Telecommunications
Faculty of Electrical Engineering, Electronics and Automation
Lecturer:
Assoc. Prof. Georgi Krastev, MEng, PhD, Dept. of Computing, tel.: 888 672,
E-mail:GKrastev@ecs.uni-ruse.bg
Abstract:
The course in Communication and Geoinformation Technologies focuses on the details of specialized hardware
and software designed for spatial data effective retrieval, storage, processing, analysis and various forms of
representations with regard to objects located on, over and under the ground.
Geoinformation is linked to graphics and, as such, it is subject of the modern tendencies for GIS application and
usage.
Course content:
Geoinformation basic terminology. Images and spatial data processing. Modelling, graphs, topology. Organization
of geoinformation systems creation. Mobile, stationary and redirect-centralized solutions based on GPS, GSM,
GPRS. Automated systems for mobile devices tracking. Application of geoinformation technologies.
Teaching and assessment:
The lectures comprise 3 hours a week and provide basic knowledge of GIS.
The 3-hour practice sessions are conducted in a specially equipped room. Students are assigned practice-oriented
tasks. Continuous assessment is based on the results from the allotted individual tasks. Final assessment is
based on a written exam conducted during the exam session. Besides their lecture notes, students are provided
with a list of specialized reference literature to help them to prepare for the exam.
0559 Artificial Intelligence
ECTS credits: 3
Weekly classes: 3lec+0sem+0labs+3ps
Assessment: exam
Type of exam: written
Departments involved:
Department of Automatics and Mechatronics
Faculty of Electrical Engineering, Electronics and Automation
Lecturers:
Prof. Miroluyb Ivanov Mladenov, MEng, PhD, Dept. of Automation, Information and Control Engineering,
tel.: 888 747, E-mail: mladenov@uni-ruse.bg
Assoc. Prof. Valentin Bogdanov Stoyanov, MEng, PhD, Dept. of Automation, Information and Control Engineering,
tel.: 888 372, E-mail: vstojanov@uni-ruse.bg
Abstract:
The course objective is to provide the students with working knowledge of the basic tasks, principles and methods
used in artificial intelligence systems, as well as their main areas of application. Topics, related to knowledge
presentation, expert systems, fuzzy systems, action planning, machine learning, pattern recognition, artificial
neural networks and genetic algorithms are considered in the subject.
Course content:
Knowledge representation and use. Expert systems. Fuzzy logic. Action planning. Pattern recognition. Neural
networks, genetic algorithms and their application in artificial intelligence systems.
Teaching and assessment:
The lectures include the basic theoretic tasks in this subject area, which are illustrated with appropriate examples.
During workshops the students have the opportunity to apply their theoretical knowledge and skills in practice.
They prepare a written report for the work done. The final mark is formed on the basis of the exam results and
work done at the workshops.
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