JITA

JITA Journal of Information Technology and Applications

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

Jefto Džino, Stefan Džino, Danijela Injac

Analysis of public administration, effects and impact of digitalization and interoperability in public administration

Original scientific paper

Abstract

For the purpose of digitization and interoperability of public administration, we researched the organization and challenges in public administration in Bosnia and Herzegovina as well as in general in public administration. We presented parts of public administration as well as the influences of public administration. The effects and influence of digitalization and interoperability in institutions in B&H, strategic approach to the development of public administration, the relationship between Vision and Technology as an indicator of business success in public administration are given. We also presented a view on the provision of digitalized and interoperable public administration services.

Keywords: digitalization, interoperability, public administration, Big Data.

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.