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BEZBJEDNO

URBANO

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Vol. 2 No. 1 (2012): JITA - APEIRON

Dalibor Vučić, Saša Salapura

E-Commerce in DinaCard System

Original scientific paper

DOI: https://doi.org/10.7251/JIT1201044V

Abstract

This paper presents the status of e-commerce in Serbia with the focus on the domestic DinaCard system, its architecture and participants in the system. We reported results on Internet transaction in DinaCard system in 2009, 2010 and 2011. We found that the number of all participants, including banks with the license for acquiring, banks with the license for issuing and Internet merchants was extremely low (up to 5) and showed no significant positive trend. As a consequence, the number of transactions with the DinaCard cards was also unacceptably low. Based on these results, we concluded that the DinaCard system for Internet transactions have a great potential, but all the participants have to make an effort to significantly increase the use of the domestic card in e-commerce.

Keywords: e-commerce, DinaCard, Internet payments, e-business.

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.