ROAD TRAFFIC ACCIDENTS ANALYSIS USING DATA MINING TECHNIQUES
Vol. 7 No. 2 (2018): JITA – APEIRON G. Janani, N. Ramya Devi ROAD TRAFFIC ACCIDENTS ANALYSIS USING DATA MINING TECHNIQUES Original scientific paper DOI: https://doi.org/10.7251/JIT1702084J Download Article PDF Abstract Road Traffic Accidents (RTAs) are a major public concern, resulting in an estimated 1.2 million deaths and 50 million injuries worldwide each year. In the developing world, RTAs are among the leading cause of death and injury. Most of the analysis of road accident uses data mining techniques which provide productive results. The analysis of the accident locations can help in identifying certain road accident features that make a road accident to occur frequently in the locations. Association rule mining is one of the popular data mining techniques that identify the correlation in various attributes of road accident. Data analysis has the capability to identify different reasons behind road accidents. In the existing system, k-means algorithm is applied to group the accident locations into three clusters. Then the association rule mining is used to characterize the locations. Most state of the art traffic management and information systems focus on data analysis and very few have been done in the sense of classification. So, the proposed system uses classification technique to predict the severity of the accident which will bring out the factors behind road accidents that occurred and a predictive model is constructed using fuzzy logic to predict the location wise accident frequency. Keywords: : Road Traffic Accident (RTA), Data Mining, k-means, Association Rule Mining (ASM), Classification, Prediction. 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.
THE USE OF ENERGY STORAGE DEVICES OF UNCONTROLLED TYPE ON THE MOSCOW METRO (THEORY AND PRACTICE)
Vol. 7 No. 2 (2018): JITA – APEIRON Shevlyugin Maxim Valerievich, Alexandr Nikolaevich Stadnikov, Anastasiya Evgenievna Golitsyna THE USE OF ENERGY STORAGE DEVICES OF UNCONTROLLED TYPE ON THE MOSCOW METRO (THEORY AND PRACTICE) Original scientific paper DOI: https://doi.org/10.7251/JIT1702078V Download Article PDF Abstract The problem of increasing energy saving and energy efficiency in the system of traction power supply of the Moscow Metro is considered due to the use of energy storage devices of uncontrolled type. The results of simulation modeling of the operation of an energy storage device of uncontrolled type in the system of traction power supply of the subway are presented. A particular line of the Moscow Metro, Filevskaya, was studied, on which experiments on the introduction of energy storage devices based on electrochemical super capacitors were conducted. With the help of experimental measurements, the electric power indicators of the operation of a stationary energy storage device had been obtained at regular service on the traction substation of the Filevskaya line of the Moscow Metro for several months. The maximum levels of the converted energies, the cyclicity, the efficiency of the plant operation, and the amount of the energy economy are determined. By statistical processing of the instantaneous values of the performance of the traction substation with the accumulator and the analysis of the data of the energy monitoring of the Moscow metro, an important parameter of reducing the installed capacity was investigated. The similarity of the data of theoretical calculations and experimental measurements is shown. Keywords: : modeling of the operation, energy storage devices, capacitive energy storage, regeneration of braking energy, traction power supply, underground. 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.
ENCRYPTION BASED ON BALLOT, STACK PERMUTATIONS AND BALANCED PARENTHESES USING CATALAN-KEYS
Vol. 7 No. 2 (2018): JITA – APEIRON Muzafer Saračević, Edin Korićanin, Enver Biševac ENCRYPTION BASED ON BALLOT, STACK PERMUTATIONS AND BALANCED PARENTHESES USING CATALAN-KEYS Original scientific paper DOI: https://doi.org/10.7251/JIT1702069S Download Article PDF Abstract This paper examines the possibilities of applying Catalan numbers in cryptography. It also offers the application of appropriate combinatorial problems (Ballot Problem, Stack permutations and Balanced Parentheses) in encryption and decryption of files and plaintext. The paper analyzes the properties of Catalan numbers and their relation to these combined problems. Applied copyright method is related to the decomposition of Catalan numbers in the process of efficient keys generating. Java software solution which enables key generating with the properties of the Catalan numbers is presented at the end of the paper. Java application allows encryption and decryption of plaintext based on the generated key and combinatorial problems. Keywords: Cryptography, Catalan numbers, Ballot notation, Stack permutations, Balanced Parentheses. 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.
Computer Control Systems With Critical Safety Applications: Problems And Some Solutions
lems And Some SolutionsSimulation of Electric Drive With Direct Torque Control of Induction Motor – [Cloned #1848] Vol. 7 No. 2 (2018): JITA – APEIRON Hristo Hristov, Mariya Hristova Computer Control Systems With Critical Safety Applications: Problems And Some Solutions Original scientific paper DOI: https://doi.org/10.7251/JIT1702061H Download Article PDF Abstract Safety Critical Systems (SCS) are defined as systems controlling critical technological processes, on the proper functioning of which depends human safety. The taxonomy of concepts related to SCS is presented as a dendritic classification scheme. The emphasis is on hierarchical relationships between concepts. After studying global scientific literature, international standards and corporate materials, a classification of the scientific issues accompanying the creation of new SCSs was made. Regarding a part of the broached issues, technical solutions are suggested based on the structural system of the system. In particular, methods and means have been developed to detect and tolerate failures and errors in building the structure and to reduce their adverse impact on the functionality and safety of the systems. Formal models have been developed, concerning which calculations and studies have been performed. Quantitative dependencies are established between the technical and probability parameters of diversity structure on the one hand and the reliability and safety of the system on the other. Conclusions are drawn as regards the practical application of the methods and models. Keywords: Safety Critical Systems, risk, security, safety, reliability. 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.
EU Service Directive, Digital Identity and ID Documents in Bosnia and Herzegovina
Vol. 8 No. 1 (2018): JITA – APEIRON Siniša Macan EU Service Directive, Digital Identity and ID Documents in Bosnia and Herzegovina Original scientific paper DOI:https://doi.org/ 10.7251/JIT1801032M Download Article PDF Abstract In 2006, the European Union adopted the Services Directive, which establishes the obligation to establish unique points of contact through which citizens and businesses receive certain services from government bodies. The Services Directive unifies the services market throughout the European Union and creates an obligation for each Member State to improve its way of providing services to citizens. Citizens are accessing services through digital identities. Having in mind that Bosnia and Herzegovina have for more than 65% turnover with EU countries, there is a need and legal obligation for the introduction of the same standards in the field of digital services and digital identities in BiH as in the EU. Citizens and businesses in Bosnia and Herzegovina need to have same position with competitive and compatible markets in EU countries. To validate digital identities, it is possible to use ID documents in BiH. This paper described the way of validating the digital identity in BiH using ID card or passport. ID documents issued according to ICAO 9303 standards and EU regulations must have embedded chips. These documents can be used to access electronic services as well as for digital identity verification. Keywords: Digital identity, ID documents, BAC, EAC, SAC, interoperability, PSCs, Service Directive. 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.
Use of Multiparameter Adaptation in Communication Systems
Vol. 8 No. 1 (2018): JITA – APEIRON Klyachko Lev Mikhailovich Use of Multiparameter Adaptation in Communication Systems Original scientific paper DOI:https://doi.org/ 10.7251/JIT1801027M Download Article PDF Abstract The article discusses the use of multiparameter adaptation in communication VHF waves communication, provides specific schema that implements the proposed algorithm. Keywords: adaptation, multiparameter system VHF waves communications, the transmission of information. 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.
Packet Loss Differentiation Over Manet Based on a BP Neural Network
Vol. 8 No. 1 (2018): JITA – APEIRON Dimitris Kanellopoulos, Pratik Gite Packet Loss Differentiation Over Manet Based on a BP Neural Network Original scientific paper DOI:https://doi.org/ 10.7251/JIT1801018K Download Article PDF Abstract An adaptive distributed routing algorithm is essential in MANETs, since there is no central routing system. Actually, there is no central point of coordination; each node is responsible for forwarding data packets to other nodes, thereby acting as router and host. A packet might travel through multiple intermediary ad hoc nodes in order to arrive to its destination, while the nature of wireless multi-hop channel is bringing in various types of packet losses. This paper focuses on three main reasons of online packet losses in MANETs: (1) losses due to wireless link errors; (2) losses due to congestion; and (3) losses due to route alteration. It proposes a deep learning-based algorithm for packet loss discrimination. The algorithm uses the backpropagation neural network (BPNN) concept. We performed simulation experiments for evaluating the performance of the proposed loss discrimination algorithm under different network configurations. Through simulation results, we confirmed that the proposed algorithm improves packet loss discrimination and route alteration in the network. It also reduces congestion and increases network throughput. Keywords: MANET, packet loss discrimination, multicast congestion detection, backpropagation neural network, deep learning. 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.
Evaluation of the Period of Sensors Motion Parameters of the Train
Vol. 8 No. 1 (2018): JITA – APEIRON Petr Filimonovich Filimonovich Evaluation of the Period of Sensors Motion Parameters of the Train Original scientific paper DOI:https://doi.org/ 10.7251/JIT1801014B Download Article PDF Abstract The choice of polling period sensors for measuring the speed and acceleration of the train can be produced using the spectral representation of functions of velocity and acceleration from time to time. Using the spectral method of determining the period of the survey, you can choose different value depending on the category of the train and its dynamic characteristics. For high-speed trains, the period of sensors is less than for trucks, since the latter are tightened by the transients during acceleration and deceleration. Keywords: Hartley transform, parameters of the train, period of sensors, spectral method. 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.
Simulation of Electric Drive With Direct Torque Control of Induction Motor
Vol. 8 No. 1 (2018): JITA – APEIRON Yuri M. Inkov, Andrey S. Kosmodaminskiy, Alexander A. Pugachev, Elena V. Sachkova Simulation of Electric Drive With Direct Torque Control of Induction Motor Original scientific paper DOI:https://doi.org/ 10.7251/JIT1801005I Download Article PDF Abstract The main requirements for traction electric drives are listed and discussed. The direct torque control of an induction motor electric drive is established by a survey of operation modes of traction electric drives to thoroughly satisfy the requirements for traction electric drive. The topologies and operation principles of two-and three-level voltage source inverters are presented. The advantages and shortcomings of three-level voltage source inverters to be applied on locomotive traction drives are highlighted in relation to the two-level ones. The recommendations of choice between different voltage source inverter topologies are given. The topology and principles of operation of direct torque control of induction motors with two- and three-level voltage source inverters are described. The simulation peculiarities of electric drives with direct torque control and two- and three-level inverters in Matlab are considered. The simulation results are presented. The techniques to reduce the torque oscillations are shown and implemented in Matlab Simulink. Keywords: induction motor, direct torque control, voltage source inverter, equivalent circuit, control system, Matlab. 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.
Safety Aspects in Shared Medical it Environment
Vol. 8 No. 2 (2018): JITA – APEIRON Igor Dugonjić, Mihajlo Travar, Gordan Bajić Safety Aspects in Shared Medical it Environment Original scientific paper DOI:https://doi.org/ 10.7251/JIT1802086D Download Article PDF Abstract Regional PACS and other shared medical systems are primary intended for sharing medical images. In these systems, the number of users is significantly increased in relation to local systems, and the fact is that the public network is very frequently used for data transfer. As medical data are very sensitive, such situation creates considerable risk regarding privacy, integrity and right to access to these data. This paper includes the most frequent risks and methods to solve these issues as well as recommendations for safe use of cloud computing systems in order to implement these systems. Keywords: PACS, DICOM, IHE. 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.