JITA

JITA Journal of Information Technology and Applications

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

Mihajlo Travar, Igor Dugonjić, Saša Ristić

ANALYSIS OF USING CLOUD BUSINESS IN BOSNIA AND HERZEGOVINA AND THE REGION

Original scientific paper

DOI:https://doi.org/ 10.7251/JIT1902118T

Abstract

Cloud business is the basic support to operations of modern companies. It enables companies to be more agile and innovative. Such form of digital transformation improves business and company productivity and solves business problems in innovative ways. On one hand, Cloud business makes possible for users to get the best expertise possible which they cannot develop independently. On the other hand, it offers possibilities to reduce the costs related to hardware and software to a reasonable level. The time value of money present in Cloud business is also significant. Namely, companies no longer need to invest large sums of money in equipment or software solutions; it is sufficient to rent those and use revenues for future business investments. Cloud solutions mean that users, using modern technology, access their business software solution through a web browser (web application) thus completing their business processes and accessing the database. Expansion of business leads to a new phenomenon – users are no longer tied to a physical location. In this way, users more frequently work from home or on the move by using different mobile devices. We all use a number of applications (Gmail, outlook.com, Facebook, LinkedIn, Twitter etc.) and take advantage of the Cloud business without being aware of it. We do not install any of the mentioned applications on our devices but access those using an internet browser. Given the lack of IT experts due to economic migrations, as is the situation here, insufficient supply and enormous demand for IT professionals, the traditional model of using business information systems will become practically unsustainable. In this paper, following introductory and general remarks on Cloud business, an analysis was made of using Cloud business IT systems in RS/BH, Serbia and the EU.

Keywords: Cloud business, Business IT systems ICT, Cloud, Digitalization of 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.