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Vol. 13 No. 1 (2023): JITA - APEIRON

Mirjana Landika, Željko Račić, Bogdana Kondić

Panel Analysis in Function of Measuring the Impact of Higher Education on International Competitiveness of the Western Balkan Countries

Original scientific paper

Abstract

An important aspect of the development and perspectives of the development of the socio-economic community refers to the level of coverage of the labor market with adequate staff in terms of expertise and competencies, which largely derive from the results of the educational process. Expressing and measuring the results of the educational process is a continuous and complex process, and requires the application of adequate methodology, such as a panel analysis model. The aim of the researchers is to examine the impact of higher education on appropriate macroeconomic indicators countries of the Western Balkans, which are not yet members of the European Union. The practice of such research has been formalized in Western European countries, where researchers have adequate access to the empirical material on which research is based, but also a standardized procedure for presenting appropriate indicators, which is not the case in the selected geographical area. The context of the educational process since the period of introduction and adoption of the determinants defined by the Bologna Declaration, is going through a turbulent process of transformation. The next turning point in the education system is justified by the pandemic caused by the COVID – 19 virus.

Keywords: econometric model, economic growth, international competitiveness, panel analysis, crisis management.

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.