JITA

JITA Journal of Information Technology and Applications

Vol. 9 No. 2 (2019): JITA - APEIRON

Boris Kovačić, Nedim Smailović

DESIGN, DEVELOPMENT AND IMPLEMENTATION OF DATABASES IN PHARMACEUTICAL AND MEDICINE

Original scientific paper

DOI:https://doi.org/ 10.7251/JIT1902106K

Abstract

This paper presents the design and implementation of databases in pharmacy, points out the most common problems that may be encountered, and describes practical solutions. The paper also describes the structure in terms of linking multiple applications to one single database in terms of achieving business automation.

Keywords: Pharmacy and medicine database design, business automation, multiple applications to one database, SQL.

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.