The paper is devoted to the actual problem of ensuring the information security of web-sites. It discusses a method for detecting intentional threats to the confidentiality of information as a result of unauthorized access and is manifested in the form of atypical requests to resources by users. The paper proposes a method based on data mining. Its essence lies in the classification of users' behavior on the basis of information about their actions using an artificial neural network. As a basis for the implementation of the proposed tools, site security audit tools are used as a source of information. The structure of neural network, training methods and practical application are described, and the effectiveness of the proposed methods is evaluated.

Keywords: Data mining, artificial neural network, web-design, machine learning, classification

The article is devoted to the problem of using artificial neural networks as one of the methods of data mining (intellectual data analysis) for classifying the competencies of university students when determining the educational specialization. It describes the complexity of the process of selecting specialization and the associated negative consequences, as well as an approach to solving the given problem using software classification tools. As a basis for the implementation of the proposed tools, the student's information system is used on the website of the University of Tartus, Syria. The article presents data selection criteria to form the training sample, which includes the academic performance in some courses as input vectors. The values of the output vector depend on completed specialization and it get into the training set only if it is properly selected. On the basis of these data, the structure of a multilayer artificial neural network is formed and the learning algorithm is selected, the results of which are reflected on the university's website in the form of advice on the choice of future specialization, which has allowed increase the effectiveness of the educational process.

Keywords: Data mining, artificial neural network, web-design, machine learning, classification

Nonstoichiometric tungsten oxides WO3–x and oxide alkaline tungsten bronzes have been studied because of their potential applications in electrochromic devices such as solar panel arrays and “smart windows”. Different phases of 
WO3–x have been considered. In this part we present results of our research which clearly show that all Magneli phases of tungsten oxides  WOx (namely W40O118, W20O58, W5O14, W18O49, W8O23, W3O8) and oxide tungsten bronzes MxMyWO3 at M-Li, Na, K, Rb, Cs. They are characterized by metal – like properties. Their band structures display an energy gap in the valence band just below the Fermi level.
We present results of our electrochemical synthesis of tungsten oxide bronzes in ionic melts of the polytungsten salts. Among the new state – of – the art methods for their manufacture, electrochemical synthesis in ionic melts, which  makes considerably better use of existing technologies, is highly productive, based on the discharge of oxyanions of the polytungstates.  

Keywords: oxide alkali bronzes, alkaline tungsten bronzes, tungsten, molybdenum, nonstoichiometry, tungsten oxides, electroconductivity, electrochromism

This paper presents the results obtained at simulation of various algorithms dynamic route guidance. A simulation experiments has been executed for the CBD network of Rostov-on-Don with using AIMSUN package. The main objectives of research are estimate routing strategy and relation between shape of the macroscopic fundamental diagram and traffic assignment on the network.

Keywords: re-routing, rate, dynamic traffic assignment, traffic conditions