JITA

JITA Journal of Information Technology and Applications

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

Saša Paunović, Lazar Nešić, Jovan Kovačević

Application of Voice Biometrics in Protection Systems and Crime Fighting

Original scientific paper

DOI: https://doi.org/10.7251/JIT1202059P

Abstract

Modern communication relies increasingly more on the verbal communication between a machine and a human, aiming to govern certain resources and robots, increase the security of certain means, initiate certain processing protocols, faster financial transactions… This paper illustrates the possibility of using the voice biometrics in modern living, from simple examples, such as starting the motor of a vehicle, through opening security gates, to proving fraud and embezzlement. Special emphasis has been put on the systems of automatic speaker identification and forensic speaker recognition.

Keywords: Biometry, Biometry systems, Speech, Speaker, Voice recognition, Identification, Security.

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.