Journal archive

The article presents an economic and mathematical model that may predict financial effects and maximize the enterprise profit by optimal distributing costs among various types of advertising. The underlying algorithm, tools and application example are discussed and economic efficiency of the proposed approach is estimated.

The problem of the structural and functional description of the business environment which provides the requirements for information systems implementation is considered. Basic terms definitions are proposed followed by comparative analysis of concepts and tools of the two most elaborated modeling methodologies.

The paper deals with economic issues of internet projects developing for travel companies. The various criteria of economic efficiency based on the total cost of ownership methodology featuring Web-based projects costing are discussed. Alternatively, reduced costs, cash flow, business activity, competitiveness, profitability of capital investment indices and functional complex are considered.

The paper deals with optimization models of service support choosing for business processes complex. Approaches to services performance crucial indicators measurement in information system based on serviceoriented architecture are suggested.

On the 80th anniversary Article is devoted to the anniversary of outstanding scientist in the field of computerization of education, doctor of technical sciences, Prof. J. Saveliev, who stood at the origins of computer technology in education. Under his leadership a number of government projects on the automation of higher education in the Russian Federation have implemented. Being the Director of the Institute of Higher Education and the International Academy of Higher Education AY Saveliev is active involved in public education and training of the teaching staff activities.

On the 75th anniversary of V. Volkova This article is devoted to 75th anniversary of a member of the Editorial Board of «Applied Informatics» Violetta Nikolaevna Volkova. V. Volkova — candidate of techical sciences, doctor of economic sciences, professor, honored worker of higher school of the Russian Federation. The author of several monographs, textbooks and teaching aids in systems theory, a permanent author and editor of the first reference book «Applied Informatics». Made a significant contribution to the development of information theory, developed and teaches a number of original training courses. Actively involved in the development of federal education standards in informatics.

Methods for knowledge testing are discussed and a new method for testing results refinement is suggested. The method is based on a combination of traditional testing methods and models of neural networks model. The methods proposed were the basis of the developed application software.

A training model for students of various specialties in the People’s Friendship University of Russia is suggested. Information technology based approach improving educational process parameters and the application of system approach principles to development of intelligent tutoring systems are considered.

Comparative analysis of popular image compression methods based on discrete cosine transform and fractal coding is presented. Image compression principles incorporating these approaches are discussed. The obtained results make it clear the promise of fractal coding technique implementation for image compressing tasks.

Computer system mathematical model is suggested. Program execution process is represented as a process of OS resources consumption which are distributed among consumers. The task of estimating backup progress and execution time using the approach is described. The experimental data show good affinity to the theoretical ones.

The paper presents high-precision software techniques for random distributions number generating. Generally the generators are embedded in simulation systems used to analyze the processes occurring in risk environment. Some of the tools are introduced for the first time.

The method for reconfiguration and training of RBF network parameters adjusting is presented. An approach suggested is based on determining the quality for current BF functions covering of training set and their dynamical recalculation. The neural model features high performance and enables automated radial functions parameters evaluation. Both RBF network development and the network optimization applications are allowed.

A method of polymorphic execution of the algorithms on multiple data context is suggested. The method allows us to construct efficient algorithms without duplicating code and can work seamlessly with relational data structures.