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Vol. 6 No. 1 (2018): JITA - APEIRON

Paula Maria de Sá

VirtualSign Translator as a Base for a Serious Game

Original scientific paper

DOI: https://doi.org/10.7251/JIT16012S

Abstract

The goal of this paper is to present the development of a game aimed at making the process of learning sign language enjoyable and interactive, using the VirtualSign Translator. This game aims to make the process of learning sign language easier and enjoyable. In the game the player can control an avatar and interact with several objects and Non-player characters in order to obtain signs. Through the connection with VirtualSign Translator the data gloves and Kinect support, this interaction and the gestures can then be represented by the character. This allows for the user to visualize and learn or train the various existing configurations of gestures. To improve the interactivity and to make the game more interesting and motivating, several checkpoints were placed along game levels. The game has as an inventory system where the signs are kept and can be checked allowing for the user to visualize and learn or train the various existing configurations of gestures. A High Scores system was also created, as well as a History option, to ensure that the game is a continuous and motivating learning process.

Keywords: VirtualSign, Serious Games, Portuguese Sign Language, Kinect.

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.