Software Platforms Based on the Principles of GraphicDesign, Automatic Command Generation and VisualProgramming
Vol. 11 No. 2 (2021): JITA – APEIRON Dražen Marinković, Zoran Ž. Avramović Software Platforms Based on the Principles of Graphic Design, Automatic Command Generation and Visual Programming Original scientific paper DOI:https://doi.org/10.7251/JIT2102110M Download Article PDF Abstract This paper presents a new approach to software application development using a graphical interface. The approach is based on a combination of drag and drop elements and logic based on the model’s own concept. Low code platforms and principles have been developed and are still being developed precisely to enable the rapid creation and use of applications that meet all the special needs and requirements of various organizations. No code platforms allow professionals and laymen to create applications via graphical user interfaces without any prior knowledge or qualifications in programming. However, code platforms are closely related to low code platforms because they are both created with a similar goal, based on a very similar way of working and almost the same principles of operation. Many vendors point out that the future of software development is based on configuration, not program. We believe that eliminating code is one way to bring development to higher standards in application development. One of the biggest advantages of the LC/NC platform is that they allow us to take advantage of innate problem solving and human skills by removing at least a significant number, if not all barriers to implementing software solutions in today’s software world. Keywords: low code, no code, visually integrated development environment, low-skilled people, professional developers. 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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.
E-Learning Platform Directions and Future ExpansionWith Case Study
Vol. 11 No. 2 (2021): JITA – APEIRON Nedeljko Šikanjić, Zoran Ž. Avramović E-Learning Platform Directions and Future Expansion With Case Study Original scientific paper DOI:https://doi.org/10.7251/JIT2102104S Download Article PDF Abstract When we look at the current situation in the world we can see that world shifts into digital era. This means, it will also influence the learning and educational section. In this science paper we will analyze e-learning platform architecture, propose architecture based on the teaching process and perform comparative analysis of leading e-learning provides. Keywords: E-learning, Education, Databases. 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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.
On the Possibility of Embedding the Mechanism ofLinguistic Anticipation into Speech RecognitionSystems
Vol. 11 No. 2 (2021): JITA – APEIRON Daniel Kurushin, Natalia Nesterova, Olga Soboleva On the Possibility of Embedding the Mechanism of Linguistic Anticipation into Speech Recognition Systems Original scientific paper DOI:https://doi.org/10.7251/JIT2102099K Download Article PDF Abstract The paper deals with the problems of modeling speech recognition systems. The authors proposed to use the mechanism of linguistic anticipation in the speech recognition systems. It is known that anticipation is a kind of phenomenon of anticipatory reflection, which can provide an opportunity for the subject to “look into the future.” Anticipation is believed to be an effective method of improving reading technique in children as it enables to increase the speed of reading [1]. The similarity of the learning processes of the human brain and artificial neural-like algorithms allows to suggest that the inclusion of anticipation mechanisms into the operation of the speech recognition algorithm can improve the quality of the system. The paper presents the experiment carried out with the purpose to study the probability of increasing the quality of modern speech recognition systems provided that linguistic anticipation is embedded into such a system. The obtained results are discussed and possible directions for further work on this topic are considered. Keywords: natural language processing, speech recognition systems, language models, anticipation. 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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.
: A Serious Game for Social SkillsTraining
Vol. 11 No. 2 (2021): JITA – APEIRON Filimonas Papadiou, Fotis Lazarinis, Dimitris Kanellopoulos <A day at School>: A Serious Game for Social Skills Training Original scientific paper DOI:https://doi.org/10.7251/JIT2102087P Download Article PDF Abstract Soft skills are the personal characteristics of an individual that enhance his/her interactions, career prospects, and job performance. Soft skills include social skills which incorporate characteristics like empathy, self-control, socialization, and friendliness. The development of soft skills at an early age is vital. Currently, there are few serious games for social skills training aimed at primary school pupils. A serious game does not only provide fun but a player can discover knowledge about himself. This paper presents a serious game named “A Day at School” that helps primary school pupils to develop social skills through an educational scenario. In this scenario, the hero of the game faces various situations during a usual day at school. The scenario deals with the situations of bullying, racism, and social awareness of children. By using the educational application, pupils discover appropriate behavior and get the first stimulus for acquiring their social skills. The serious game helps them to socialize and gain the basis to cultivate empathy, friendliness, and self-control. Primary school pupils and teachers evaluated the serious game. The results showed that teachers found that the game is suitable for teaching purposes and its graphical user interface (GUI) is appealing. Keywords: Serious games; Soft skills; Social skills; Educational games. 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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.
Demystification of RNAseq Quality Control
Vol. 11 No. 2 (2021): JITA – APEIRON Dragana Dudić, Bojana Banović Đeri, Vesna Pajić and Gordana Pavlović-Lažetić Demystification of RNAseq Quality Control Original scientific paper DOI:https://doi.org/10.7251/JIT2102073D Download Article PDF Abstract Next Generation Sequencing (NGS) analysis has become a widely used method for studying the structure of DNAand RNA, but complexity of the procedure leads to obtaining error-prone datasets which need to be cleansed in order to avoid misinterpretation of data. We address the usage and proper interpretations of characteristic metrics for RNA sequencing (RNAseq) quality control, implemented in and reported by FastQC, and provide a comprehensive guidance for their assessment in the context of total RNAseq quality control of Illumina raw reads. Additionally, we give recommendations how to adequately perform the quality control preprocessing step of raw total RNAseq Illumina reads according to the obtained results of the quality control evaluation step; the aim is to provide the best dataset to downstream analysis, rather than to get better FastQC results. We also tested effects of different preprocessing approaches to the downstream analysis and recommended the most suitable approach. Keywords: data preprocessing, Illumina sequencing, NGS analysis, quality control, sequence analysis, total RNAseq. 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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.
Encapsulation and Functionality of Sensor Systems in theWelding Process
Vol. 12 No. 1 (2022): JITA – APEIRON Barbara Bagarić Encapsulation and Functionality of Sensor Systems in the Welding Process Original scientific paper DOI:https://doi.org/10.7251/JIT2201055B Download Article PDF Abstract This paper shows some aspects of interaction between human and robots and role of the sensors in welding process. Today, use of the robots is very important in modern industry. Sensors are very important in welding process and they increase the productivity and precision of the robot. It is very important to optimize use of the sensor, from choosing the right programming metod, creating good environment such as acceptable amounts of humidity in the air, temperature to educating the operators to be able to work with robot machine and understand and run pre-programmed codes. When all the mentioned steps are correctly defined, sensor will work perfectly and production can be as good as possible. Keywords: robots, online programming, offline programming, welding process. 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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.
IoT – Company Approach to IoT Modeling and Applications
Vol. 12 No. 1 (2022): JITA – APEIRON Dražen Marinković, Zoran Ž. Avramović IoT – Company Approach to IoT Modeling and Applications Original scientific paper DOI:https://doi.org/10.7251/JIT2201048M Download Article PDF Abstract Using the available literature, this paper attempts to present the company ‘s approach to IoT modeling and the incorporation of IoT technologies into business processes. Furthermore, a comprehensive overview of IoT technologies and systems of large corporations (Yokogawa, Intel) and commercial access to IoT technologies is provided. In conclusion, based on previous knowledge and scientifically based arguments, the advantages and disadvantages of IoT technologies are presented. Keywords: IoT, IioT, Digital Intelligence, Total Cost of Ownership, Operations Excellence, Cloud, CloudIoT. 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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.
Improving the Process of Online Education byIntroducing Innovation
Vol. 12 No. 1 (2022): JITA – APEIRON Boris Kovačić, Branko Latinović Improving the Process of Online Education by Introducing Innovation Original scientific paper DOI:https://doi.org/10.7251/JIT2201040K Download Article PDF Abstract The aim of this paper is to point out the information chain of supply to graduate pharmacists and masters of pharmacy, members of the Pharmaceutical Chamber of the Republic of Srpska. In addition, point to CRM in order to achieve greater satisfaction of members. Point out solutions and innovations that improve data exchange of associations that provide continuous education of graduate pharmacists and masters of pharmacy, members of the Pharmaceutical Chamber of Republika Srpska, as well as online platforms for online education of the Pharmaceutical Chamber of Republika Srpska and local databases. Keywords: Information supply chain, CRM, Online education, Moodle, data exchange, data exchange difficulties. 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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.
Evaulation of Homomorphic Encryption Implementationon Iot Device
Vol. 12 No. 1 (2022): JITA – APEIRON Goran Đorđević, Milan Marković, Pavle Vuletić Evaulation of Homomorphic Encryption Implementation on Iot Device Original scientific paper DOI:https://doi.org/10.7251/JIT2201032DJ Download Article PDF Abstract An encryption scheme is homomorphic if it supports operations on encrypted data. Homomorphic encryption allows a device to perform arbitrary computations on encrypted data without user secret key. Recently it is introduced new homomorphic encryption schemes with improved performance that can be implemented in IoT device in production environments. The IoT concept encompasses devices, sensors, and services existing within an interconnected infrastructure with an efficient access to sample computational facilities. In this paper we evaluated features of exact arithmetic homomorphic encryption mechanisms: BFV and BGV and approximate homomorphic encryption scheme: CKKS. In the paper we measured performances of operations of homomorphic encryption schemes: BGV, BFV and CKKS that are implemented in Raspberry Pi 4 IoT device. Keywords: Homomorphic encryption, Raspberry Pi IoT device, HE schemes performance. 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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.
prepRNA: an integrative tool for Illumina RNAseq datafiltering
Vol. 12 No. 1 (2022): JITA – APEIRON Dragana Dudić, Bojana Banović Đeri, Željko Stanković, Zoran Ž. Avramović prepRNA: an integrative tool for Illumina RNAseq data filtering Original scientific paper DOI:https://doi.org/10.7251/JIT2201026D Download Article PDF Abstract The vast amount of currently available transcriptome sequences is comprised of Illumina RNAseq data. Usually, publicly available datasets are provided as raw data and preparing them for the downstream NGS analysis is the first step required. Such preprocessing step, besides the evaluation of the quality of the raw data, includes data filtering, in order to provide high quality results of the downstream analysis. Existing tools for NGS data filtering are either too general or incomplete for the Illumina RNAseq filtering task, which is why a new tool for this endeavor was needed. We present prepRNA, a novel tool intended for Illumina RNAseq data filtering, which was designed as a comprehensive and user-friendly wrapper tool with possibility of further upgrading with a quality control option. Keywords: RNAseq, data filtering, data preprocessing, NGS data, Illumina. 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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 DOI: https://doi.org/10.7251/JIT2302061S Download Article PDF 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.