Course descriptions for ERASMUS students
1st semester, academic year 2014/2015

Faculty of Science and Informatics

Faculty of Science and Informatics / /Institute of Informatics

Course Code 11.30
Module 0
Title: Algorithms and Data Structure 1
Teacher: Csanád Imreh
Contact:
Level
Termin 1st
Module Aims
The students have to learn the basic datastructures (linked lists, binary heap, stack, queue, trees) some advanced datastructures (binary search trees, priority queue) and some basic technologies to design algorithms (divide-and-conquer, programming greedy, dynamic programming). Moreover, they have to learn the most important sorting algorithms, and graph algorithms.

Module Subject

Overview of algorithmic design, Asymptotic notations and their properties Time complexity analysis of algorithms Elementary data structures (linked lists, binary heap, stack, queue, trees), advanced data structures: binary search trees, priority queue. Algorithm design techniques (divide-and-conquer, greedy, dynamics programming); Sorting and searching algorithms. Graph algorithms, Breadth-First-Search (BFS) and shortest paths, Depth-First-Search (DFS), Topological sorting, Strongly connected components, Minimum Spanning Trees (greedy algorithms: Kruskal, Prim), Single Source Shortest Paths (Dijkstra), All Pairs Shortest Paths (dynamic programming: Floyd-Warshall)
Number of Credits 4

Course Code 11.30
Module 0
Title: Algorithms and Data Structure 2
Teacher: Csanád Imreh
Contact:
Level BA
Termin 2nd
Module Aims
The students have to learn many advanced data sructures (Hash tables, AVL trees.Red-black trees, B-trees, Disjoint sets management, Fibonacci heap, binomial heap), and some advanced techniques of designing algorithm (backtrack, branch and bound). Moreover they have to learn some important subfield of the theory of algorithms.

Module Subject

Medians, sound samples, the k-th smallest element selection algorithms. Backtracking (n Queen, knapsack) Branch and bound (knapsack). Advanced data structures (Hash tables, AVL trees, Red-black trees, B-trees, Disjoint sets management, Fibonacci heap, binomial heap) Amortized analysis. Special areas of algorithmic design: geometric algorithms, pattern matching (the Knuth-Morris-Pratt algorithm), arithmetic algorithms (public key encryption), approximation algorithms (travelling salesman), online algorithms, randomized algorithms.
Number of Credits 4

Course Code 11.30
Module 0
Title: Databases
Teacher: Péter Balázs
Contact:
Level BA+MA
Termin Both
Module Aims
The course is to provide mathematical foundations and practical techniques for the design, implementation, and manipulation of databases; databse modelling, normalization, relalional algebra, SQL language, transaction management, privileges. Education Aims: To introduce the fundamentals of designing and implementing databases. To gain practical experience in desgning and writing programs for manipulating databses.

Module Subject

The Entity-Relationship model The relational data model From E-R diagrams to relational models Relational algebra The redundancy problem: functional dependencies, decomposition, normal forms SQL language: relational schema definitions, queries, subqueries, views Constraints and triggers in SQL Embedded SQL: shared variables, cursors Transaction management, privileges Application work: designing and implementing a database application
Number of Credits 5

Course Code 11.30
Module 0
Title: Digital image processing
Teacher: Kálmán Palágyi
Contact:
Level BA+MA
Termin Both
Module Aims
The course is to provide mathematical foundations and practical techniques for digital manipulation of images; image acquisition; preprocessing (smoothing, filtering, restoration); segmentation; feature extraction; shape representation; and compression. Education Aims: To introduce the fundamentals of digital image processing theory and practice. To gain practical experience in writing programs for manipulating digital images.

Module Subject

1. Image sampling and quantizing 2. Fourier transform 3. Convolution 4. Point operations and histogram transformations 5. Image enhancement in spatial domain 6. Image enhancement in frequency domain 7. Feature (line, edge, corner) detection 8. Image segmentation 9. Shape representation and description 10. Image coding and compression
Number of Credits 5

Course Code 11.30
Module 0
Title: Operations Research
Teacher: András Pluhár
Contact:
Level All
Termin Both
Module Aims
The course is to provide mathematical foundations and examples of Operations Research. It introduces the basic ideas of Linear Programming, how to build models, standard forms, the main issues of simplex algorithm and the two-phase simplex method. The LP duality and its use is also covered, such as the geometric ideas behind the algrebraic machinery.

Module Subject

1. The basic model of Linear Programming 2. Standardization, Diet problem 3. Simplex algorithm, iteration, termination 4. Cyclization, Bland's theorem 5. Two-phase Simplex method, initialization 6. The speed of different methods 7. Fundamental theorem of LP, all optimal solutions 8. Duality and complementarity theorems, and their use 9. The economic significance of Strong duality 10. Geometry of LP, matrix games, Minimax theorem
Number of Credits 5

Faculty of Science / Physical Geography and Geoinformatics

Course Code XSE041:ERASTEF04G
Title: GIS and Applications (only in 1st semester)
Teacher: Tobak Z., Van Leeuwen B., Bódis K., Faculty of Science / Physical Geography and Geoinformatics
Contact:
Module Aims
(minimum 210 characters)
 

Module Subject

(minimum 350 characters)

 

Number of Credits 5

Course Code XSE041:ERASTEF08G
Title: Geoinformatics project (only in 1st semester)
Teacher: Van Leeuwen B., Tobak Z., Faculty of Science / Physical Geography and Geoinformatics
Contact:
Module Aims
(minimum 210 characters)
 

Module Subject

(minimum 350 characters)

 

Number of Credits 5

Course Code XSE031:ERASTEF13E
Title: Environmental Geography (only in 1st semester)
Teacher: György SIPOS, Faculty of Science / Physical Geography and Geoinformatics
Contact:
Module Aims
(minimum 210 characters)
The aim of the course to introduce the students to urban ecology, landscape planning and applied geomorphology, using Hungarian case studies. A special attention will be paid on relations between the system-elements of the different landscapes. Furthermore, the aim is to teach the students how to evaluate and present field measurements

Module Subject

(minimum 350 characters)

Urban ecology:

  1. Effects of urban land-use on physical geographical parameters (soil, climate, ground water)
  2. Urban land use and urban ecological mapping
  3. Application of databases and digital images in urban ecological investigations

Landscape planning:

  1. Urban planning
  2. Green surface management
  3. Protection against soil erosion caused by wind and running water
  4. Geomorphology of agriculture
  5. Environmental impact assessment of investments (motorways, land-use changes, irrigation etc.)

Applied geomorphology:

  1. Monitoring geomorphological change, geomorphological mapping
  2. Floodplains and flooding
  3. River regulations
  4. Geomorphological assessments of slope failure
Number of Credits 3

Course Code XSE041:ERASTEF09G
Title: Geospatial data collection and processing (Geoinformatics fieldwork) (only in 1st semester)
Teacher: Szatmári J., Tobak Z., Van Leeuwen B., Faculty of Science / Physical Geography and Geoinformatics
Contact:
Module Aims
(minimum 210 characters)
 

Module Subject

(minimum 350 characters)

 

Number of Credits 5

Course Code XSE031: ERASTEF11E
Title: Environmental capabilities, hazards and conflicts (only in 1st semester)
Teacher: Gábor MEZŐSI, Faculty of Science / Physical Geography and Geoinformatics
Contact:
Module Aims
(minimum 210 characters)
 

Module Subject

(minimum 350 characters)

 

Number of Credits 3

Course Code XSE031: ERASTEF12E
Title: Applied Hydrography (only in 1st semester)
Teacher: Tímea KISS, Faculty of Science / Physical Geography and Geoinformatics
Contact:
Module Aims
(minimum 210 characters)

1. To point on the facts, that

  • the river regulations altered the river regime differently on different rivers
  • the rivers reached different equilibrium stages and they responded in different ways

2. To teach the students how to evaluate and present hydrological data

Module Subject

(minimum 350 characters)
  1. Development of the drainage network of the Great Plain since the Pleistocene, with special respect to Holocene changes
  2. Review of regulation works (main ideas, facts, consequences)
  3. Evaluation of hydrological parameters (stage, discharge, bed geometry, slope etc.)
  4. Evaluation of morphological changes on the floodplain (horizontal and vertical river bed changes, island and bar formation, land slides on the banks, point bar formation)
  5. Flood hazard estimation in a certain area
Number of Credits 3