Application of Methods of Multi-criteria Evaluation in Choosing a Method of Compression as a Means of Heightening the Information Security of System and Applied Objects

In this paper is proposed a model for researching the capability to influence, by selected methods’ groups of compression, to the co-efficient of information security of selected objects’ groups, exposed to selected attacks’ groups. With the help of methods for multi-criteria evaluation are chosen the methods’ groups with the lowest risk with respect to the information security. Recommendations for future investigations are proposed.

The Methods of Conducting Studies with the Application of Combined Didactic Interactive Programme Systems

The methods of the application of the Combined didactic interactive programme system on electrical engineering disciplines has been worked out and the possibility of its application for providing a complex of different kinds of studies: lectures, tutorials, laboratory studies and also for organizing students’ independent work has been verified. The given methods provide the organization of the reproductive (recognition and reproduction) and productive heuristic educational-cognitive students’ activity in conditions of gradualness and completeness of education with the closed directed automatic control.

Application of Classification Methods to a Problem Related to Specific Groups of E-Government Users

This paper was partly supported by ELOST – a SSA EU project – No 27287.

Application of Artificial Intelligence Methods to Computer Design of Inorganic Compounds

In this paper the main problems for computer design of materials, which would have predefined properties, with the use of artificial intelligence methods are presented. The DB on inorganic compound properties and the system of DBs on materials for electronics with completely assessed information: phase diagram DB of material systems with semiconducting phases and DB on acousto-optical, electro-optical, and nonlinear optical properties are considered. These DBs are a source of information for data analysis. Using the DBs and artificial intelligence methods we have predicted thousands of new compounds in ternary, quaternary and more complicated chemical systems and estimated some of their properties (crystal structure type, melting point, homogeneity region etc.). The comparison of our predictions with experimental data, obtained later, showed that the average reliability of predicted inorganic compounds exceeds 80%. The perspectives of computational material design with the use of artificial intelligence methods are considered.