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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

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

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.