JITA

JITA Journal of Information Technology and Applications

Vol. 1 No. 2 (2011): JITA - APEIRON

Velimir Štavljanin, Vinka Filipović, Milica Kostić-Stanković

Social Media in Marketing and PR

Original scientific paper

DOI: https://doi.org/10.7251/JIT1102113S

Abstract

Social media as a new communication channel has managed to radicalize the way companies communicate with consumers and other stakeholders. Companies that are not on time engaged in social media weaken its ability for competitive struggle. In this paper we present possibilities of different types of social media in relation to marketing and public relations. Also, the paper will give specific recommendations for the use of social media in mark eting and public relations.

Keywords: Marketing, Public Relations, Social Media.

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.