Erasmus ECTS Information Package

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Erasmus ECTS Information Package Faculty of EEEA 3065 Economics ECTS credits: 3 Weekly classes: 2lec+1sem+0labs+0ps Assessment: continuous assessment Type of exam: written Departments involved: Department of Economics, Faculty of Business and Management Lecturers: Assoc.Prof. Djanko Hristov Minchev, MEcon, PhD, Dept. of Economics, tel.: 888 557 E-mail: Dminchev@uni-ruse.bg Assoc.Prof. Emil Georgiev Trifonov, MEcon, PhD, Dept. of Economics, tel.: 888 557 Abstract: The subject is concerned with the general problems, laps and categories of the contemporary market economy. Thus it creates a certain basis for the remaining economic objects. It also gives general knowledge, which is expressed in alternative ways of economic viewing and which forms and creates abilities for independent and expert choice in economic surroundings. Course prerequisite is knowledge of mathematics and it is related to concrete branch and functional economic subjects. Course content: Introduction – the economic system and the fundamentals of economic theory. Market mechanism. Public sector. Consumer demand and behavior. Manufacture, company assets and expenses. Imperfect competition and supplying. Price formation and incomes depending on production factors: Gross domestic product and economic growth. Economic cycles, unemployment and inflation. Taxation, budget and monetary policy. Teaching and assessment: Course material is taught in two ways – lectures and practical classes, which elucidate and develop further some of the issues discussed at lectures. Continuous assessment is carried out. It includes two test assignments and student performance during the semester. Final assessment is the average of the above-mentioned components of evaluation. 3066 English, part III for Computing and Communicating Technology ЕCTS credits: 4 Weekly classes: 0l+0s+0lab+4p Assessment: continuous assessment Type of exam: written Department involved: Department of Foreign Languages, Faculty of Law Lecturers: Senior Lecturer Mariela Georgieva Risova, MA, Department of Foreign Languages, tel:++359 82 888 816, E-mail: mrisova@ecs.uni-ruse.bg Senior Lecturer Pencho Konstantinov Kamburov, MA, Department of Foreign Languages, tel:++359 82 888 816, E-mail: pkamburov@ecs.uni-ruse.bg Senior Lecturer Diana Ilieva Stefanova, MA, Department of Foreign Languages, tel:++359 82 888 230, E-mail: dstefanova@ecs.uni-ruse.bg Lecturer Elitsa Dimitrova Georgieva, MA, Department of Foreign Languages, tel:++359 82 888 816, E-mail: edgeorgieva@ecs.uni-ruse.bg Abstract: The foreign language module 3 is also aimed at achieving communicative competence in the area of the subject specialism and the future job. The teaching objectives comprise the development of reading comprehension skills to handle specialist texts and the acquisition of communication skills to interact successfully in professional settings and everyday situations. At the end of the module it is expected from the students to be able to give and find out information from different information sources: texts, tables, instructions, etc., as well as to use it for particular purposes; to express agreement or disagreement, to request or give permission for doing certain activities, to persuade, give advice, instruction, to express opinions, to build a range of vocabulary of the main terms from their speciality in the foreign language; to understand the gist of the text and to make a summary. Course content: Higher education. Types of computers and structure of the computer. Peripheral devices. Graphic user interface. Nets. Internet. Preparation of a presentation – instructions for material gathering; structure; developing presentation skills. Communications. Text processing. Data base and electronic tables. Data protection and antivirus software. Development of the information technologies. Professional development in the sphere of computing and telecommunications. Teaching and assessment: To acquire the necessary language knowledge and to develop skills in using the language as a means of communication a wide range of authentic and specially constructed texts ( i. e. articles, diagrams and tables, brochures, catalogues, manuals etc.) as well as audio , video, and multimedia materials are used. Students are offered lessons in computer laboratories, in which multimedia learning packages and on-line materials in Internet are used according to the modern trends in foreign language teaching. In class students participate in role-plays, pair and group activities and they are encouraged to work on their own on their translation assignment. Continuous assessment involves at least two written tests and oral testing as well. 155
Erasmus ECTS Information Package Faculty of EEEA 3067 Discrete Structures and Modelling ECTS credits: 6 Weekly classes: 2lec+0sem+0labs+2ps+2cw Assessment: exam Type of exam: test Departments involved: Department of Computing Faculty of Electrical Engineering, Electronics and Automation Lecturer: Assoc. Prof. Irina Ilieva Zheliazkova, MEng, PhD, Dept. of Computing, tel.: 888 744, E-mail: Irina@ecs.uni-ruse.bg Abstract: The course gives theoretical knowledge and practical skills for modelling with systems of equations, graphs, sets, graphs, Petri nets, Markov chains, image recognition for analysis, synthesis, and optimization of complex systems. Course prerequisites include Advanced mathematics 3, Programming and Computer Applications, Synthesis and analysis of algorithms and is linked to Software engineering, Programming languages, and the work projects. Course content: Physical modelling with systems of equations. Data modelling with sets. Structural modelling with graphs. Behaviour modelling with Petri nets. Probability modelling with Markov chains. Modelling image recognition. Teaching and assessment: The lecture material for the separated mathematical apparatus includes: definitions, types, properties, setting, algorithms and methodology for modelling. Practical exercises are reduced to the acquisition of algorithms for solving different types of problems with different tools. The results from each exercise for each student are assessed by the assistant. Course work includes implementation of a program for modelling using one of the types of sets, or one of the image recognition methods. The final assessment of the course is formed as an average of the practical exercises, course work, and a test on the lecture material marks. 3068 Object-oriented programming ECTS credits: 5 Weekly classes: 2lec+0sem+0labs+2ps+1ca Assessment: exam Type of exam: written and oral Department involved: Department of Computing Faculty of Electrical Engineering, Electronics and Automation Lecturers: Assoc. Prof. Milko Todorov Marinov, MEng, PhD, Dept. of Computing, tel.: 888 356, E-mail: mmarinov@ecs.uni-ruse.bg Assoc. Prof. Svetlana Petrova Stefanova, MEng, PhD, Dept. of Computing, tel.: 888 356, E-mail: sstefanova@ecs.uni-ruse.bg Principal Assistant Julia Stoyanova Zlateva, MEng, Dept. of Computing, tel.: 888 681, E-mail: JZlateva@ecs.uni-ruse.bg Abstract: The course objective is for the students to familiarise themselves and to practically assimilate the methodology of object-oriented programming (OOP) as a basis of many modern languages and systems for developing computer applications. The course focuses on the practical application of the approach by using universal library functions as well as developing own functions. Course content: Introduction to OOP. Classes and objects – definitions. Constructors and destructors. Data members. Member functions. Overloaded functions. Inheritance. Multiple inheritance. Virtual classes. Virtual functions. Polymorphism. Template class library. Working with streams. Teaching and assessment: The lecture topics give the main theoretic aspects of the problems. The practice sessions and course work classes are conducted in a computer lab. The students have to independently solve, encode and test with the aid of a specific programming environment elements of given problems. Each student is assigned an individual task, which they have to complete by the end of the semester. The final mark is a weighted average of four marks: activity during practice sessions, implementation of the individual task, written report and final exam. 156
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