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Vol. 1 No. 1 (2011): JITA - APEIRON

Gordana Radić

The Usage of Information Technology in the Implementation of the Bologna Principle of the Student Mobility

Original scientific paper

DOI: https://doi.org/10.7251/JIT1101024R

Abstract

In this paper, student mobility is observed as one of the steps in realization of the Digital Agenda of the European Union. Student mobility, as one of the main principles of the Bologna process, is the means of effectiveness increase and quality of the educational system in European Higher Education Area, EHEA, because it enables better exchange and flow of knowledge and ideas, as well as the adoption of good practices. Management Identity (IdM) system of the Higher Educational institution is a system which supports student mobility by using personal information when accessing data. The basic identity document in this system is a student smart card with the owner’s fingerprint. This biometrical data insures high level of data and identity protection. This paper proposes informational system which, in itself, contains standards for student mobility support as one of the modules of the IdM system of the Higher Educational institution.

Keywords: Identity management, student mobility, smart card, biometrics.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.