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Vol. 7 No. 1 (2018): JITA - APEIRON

Zoran Ž. Avramović, Dražen Marinković, Igor Lastrić

Use of Computer Search Algorithms in the Research of Statistical, Semantic and Contextual Rules of Language in Digital Information Space

Original scientific paper

DOI: https://doi.org/10.7251/JIT1701005A

Abstract

This paper will discuss and practically explore the interdependence between information technology and linguistics in the modern information society.

The relationship between information technology and linguistics, which has opened new opportunities in linguistic research, will be practically seen in the application of linguistic engineering in researching rules of language.

The aim of this paper is to extend knowledge about the possibilities of application of information technologies in researching rules of language, as well as emphasizing the importance that language technologies have in the field of linguistic research, preservation of language and culture and national identity.

Keywords: :information technology, search algorithm, rules of language, linguistic engineering, digital information space.

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.