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Vol. 4 No. 1 (2014): JITA - APEIRON

Velibor Srdić, Milan Nešićć

The Application of Information and Communication Technologies in Dance Sport in Bosnia and Herzegovina

Original scientific paper

DOI: https://doi.org/10.7251/JIT1401023S

Abstract

The research was performed with the aim of determining the frequency and ways of application of information and communication technologies (ICT) in dance sport in Bosnia and Herzegovina. The research was conducted on the sample of 33 dance clubs, that is, their representatives, with the condition for the clubs to belong to one of the two national dance associations of Bosnia and Herzegovina. The data were collected via interviews, associations’ web pages and their archives. The research utilized analysis and induction method. The results showed weak application of ITC in everyday work of dance clubs, but they also indicated the appropriate usage of ICT by dance associations (as the “umbrella” organizations of dance sport) at dance competitions. In this sense, it is advisable to steer finances towards improvement of dance clubs’ equipment and IT training of employees.

Keywords: information and communication technologies, dance sport, application.

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.