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Vol. 11 No. 2 (2021): JITA - APEIRON

Slavojka Lazić, Tijana Talić

Application of Information Technologies in New Forms of Teaching Processes

Original scientific paper

DOI:https://doi.org/10.7251/JIT2102131L

Abstract

Educating young people is one of the most beautiful and humane vocations. The transfer of knowledge to young people and their introduction into the world of science requires a well-prepared and organized educator. The application of information technologies in education has become an everyday tool, so that its role in the educational process has come to the fore during the last two years. The Covid 19 pandemic brought new challenges to the education system in Republika Srpska. The best solutions for the teaching process were sought. At the beginning, the classes were conducted at a distance, last year in classrooms with classes shortened to 20 minutes, and this year the classes again last 45 minutes, with respect to protection measures. The paper will show how the students coped with all these changes and how much their knowledge of information technology helped them in all this. The research includes an analysis of data collected by a survey of high school students and refers to their attitudes towards the performance of the teaching process in the past few years.

Keywords: education, teaching process, IT.

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.