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Vol. 4 No. 2 (2014): JITA - APEIRON

Željko Stanković, Ljiljana Tešmanović

E-textbook Development Capacities Within the Current Context in the Republic of Serbia

Original scientific paper

DOI: https://doi.org/10.7251/JIT1402062S

Abstract

The study is a short sublimation of the e-book and e-textbook development. In digital age and with the adoption of new technologies, new educational digital platform has become an integral part of our everyday life and education which requires adjustments and changes in the educational system structure. In order to make the students be equal and functional members of the society and to prepare them for contemporary digital era, it is the entire society’s most important responsibility to enable educational system to provide, in most optimal and proficient way, equal opportunities for each and every student to gain knowledge. Expensive process of a book digitalization will, in time, become economically acceptable for all in the broader community.

Keywords: traditional book / textbook,e-book, digital textbook.

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.