MODELLING THE PROCESS OF IS AUDITING IN THE PUBLIC ADMINISTRATION USING UML DIAGRAMS
Vol. 7 No. 1 (2018): JITA – APEIRON Dalibor Drljača, Branko Latinović, Dušan Starčević MODELLING THE PROCESS OF IS AUDITING IN THE PUBLIC ADMINISTRATION USING UML DIAGRAMS Original scientific paper DOI: https://doi.org/10.7251/JIT1701032D Download Article PDF Abstract Although information system audit is a very important business process, at present this is not obligatory in the public administration institutions in Bosnia and Herzegovina and Republic of Srpska. Due to the importance of this process, this paper proposes a model for auditing of information systems in the public administration institutions. The model intends to explain the audit process using a visual representation of the process with UML diagrams. UML is an internationally recognised language for business process modelling and has a number of advantages over other similar languages and standards. Therefore, UML is selected in modelling for modelling of information system auditing process in the public administration institutions. Keywords: UML, auditing, information systems, public administration, business process modelling 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.
Expert Systems In A Cloud Computing Environment Model For Fast-Paced Decision Making
Vol. 7 No. 1 (2018): JITA – APEIRON Mihalj Bakator, Dragica Radosav EXPERT SYSTEMS IN A CLOUD COMPUTING ENVIRONMENT MODEL FOR FAST-PACED DECISION MAKING Original scientific paper DOI: https://doi.org/10.7251/JIT1701024B Download Article PDF Abstract In this paper the use of cloud computing technologies and expert systems will be analyzed. Furthermore, the use of expert systems in a cloud computing environment will be addressed. Specifically a Cloud-Based Expert System (CBES) model for decision making will be presented. The mentioned model will include the model’s infrastructure and its application. In addition, a theoretical approach will be used as a basis for the research and analysis. The CBES model offers effective, fast and reliable support for individuals or organizations when it comes to fast-paced decision making. Keywords: cloud computing, environment, CBES model, decision, expert system. 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 DIGITAL SIGNATURE IN ELECTRONICCOMMUNICATION IN BIH – RESEARCH
Vol. 7 No. 1 (2018): JITA – APEIRON Tijana Talić THE USE OF DIGITAL SIGNATURE IN ELECTRONIC COMMUNICATION IN BIH – RESEARCH Original scientific paper DOI: https://doi.org/10.7251/JIT1701020T Download Article PDF Abstract The increasing use of electronic mail for identity theft and unsolicited marketing and frequent presence of viruses as well, reduced the credibility of email as a communication tool. Authentication of the sender is well known defense against such attacks. One of the methods to ensure that authentication, secure communication via e-mail, is the use of digital signature. Keywords: a digital signature, authentication, the education sector, business users. 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.
Space Complexity Analysis of the Binary Tree Roll Algorithm
Vol. 7 No. 1 (2018): JITA – APEIRON Adrijan Božinovski, George Tanev, Biljana Stojčevska, Veno Pačovski, Nevena Ackovska Space Complexity Analysis of the Binary Tree Roll Algorithm Original scientific paper DOI: https://doi.org/10.7251/JIT1701009B Download Article PDF Abstract This paper presents the space complexity analysis of the Binary Tree Roll algorithm. The space complexity is analyzed theoretically and the results are then confirmed empirically. The theoretical analysis consists of determining the amount of memory occupied during the execution of the algorithm and deriving functions of it, in terms of the number of nodes of the tree n, for the worst – and best-case scenarios. The empirical analysis of the space complexity consists of measuring the maximum and minimum amounts of memory occupied during the execution of the algorithm, for all binary tree topologies with the given number of nodes. The space complexity is shown, both theoretically and empirically, to be logarithmic in the best case and linear in the worst case, whereas its average case is shown to be dominantly logarithmic. Keywords: Binary Tree Roll Algorithm, space complexity, theoretical analysis, empirical analysis. 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 Computer Search Algorithms in the Research of Statistical, Semantic and Contextual Rules of Language in Digital Information Space
Vol. 7 No. 1 (2018): JITA – APEIRON Zoran Ž. Avramović, Dražen Marinković, Igor Lastrić Use of Computer Search Algorithms in the Research of Statistical, Semantic and Contextual Rules of Language in Digital Information Space Original scientific paper DOI: https://doi.org/10.7251/JIT1701005A Download Article PDF Abstract This paper will discuss and practically explore the interdependence between information technology and linguistics in the modern information society. The relationship between information technology and linguistics, which has opened new opportunities in linguistic research, will be practically seen in the application of linguistic engineering in researching rules of language. The aim of this paper is to extend knowledge about the possibilities of application of information technologies in researching rules of language, as well as emphasizing the importance that language technologies have in the field of linguistic research, preservation of language and culture and national identity. Keywords: :information technology, search algorithm, rules of language, linguistic engineering, digital information space. 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.
WEB BASED DECISION SUPPORT SYSTEM YO DETERMINE YHE APPROPRIATE PACKAGING OF ETHNIC AND TRADITIONAL INDONESIAN FOODS
Vol. 7 No. 2 (2018): JITA – APEIRON Latifah Nurbaiti, Kudang Boro Seminar, Nugraha Edhi Suyatma ć WEB BASED DECISION SUPPORT SYSTEM YO DETERMINE YHE APPROPRIATE PACKAGING OF ETHNIC AND TRADITIONAL INDONESIAN FOODS Original scientific paper DOI: https://doi.org/10.7251/JIT1702115N Download Article PDF Abstract Culinary efforts, especially ethnic and traditional snacks attract many people to Indonesia. Maintaining the quality of snacks for consumers requires a good packaging technique. Food packaging consists of a wide variety of packaging options that match the characteristics of each snack; this is no easy task. Decision support systems can help to facilitate decisions made regarding selection of the right packaging. This paper focuses on identifying snacks, types of packaging and active packaging parameters to build a decision support system in order to determine appropriate packaging. Types of packaging are determined using fuzzy Sugeno 4 parameters: fat, water activity, shelf-life and price. Active packaging of the snacks is done using the if-else rule with parameterised types of packaging, preservatives, oxygen barriers and water vapour barriers. The end result of this research is a web-based decision support system, which recommends types of packaging and active packaging for snacks. Keywords: :active packaging; snacks; fuzzy logic. 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.
INFLUENCE OF INFORMATION TECHNOLOGIES ON THE COMPANY’S COMPETITIVE ADVANTAGE ON THE MARKET IN CONDITIONS OF THE GLOBAL CRISIS
Vol. 7 No. 2 (2018): JITA – APEIRON Nataša Đalić, Mina Paunović INFLUENCE OF INFORMATION TECHNOLOGIES ON THE COMPANY’S COMPETITIVE ADVANTAGE ON THE MARKET IN CONDITIONS OF THE GLOBAL CRISIS Original scientific paper DOI: https://doi.org/10.7251/JIT1702108DJ Download Article PDF Abstract In the recent decades, there has been recorded a great expansion in the computing and communication field and all the predictions are pointing to the further technological progress when using information technologies (IT) in the companies’ business. The appearance of IT in business offers certain advantages, has an influence on the business quality, cost control and also on achieving and maintaining competitive advantage of companies in conditions of the global crisis. The research was carried out on the teritory of Republika Srpska, on the sample of 136 small and medium enterprises. The key goal of this research work was to analyze the existing effects of IT at the level of competitive advantage of companies on the market in the global crisis conditions. The research results confirmed a big importance of IT in the company business for the purpose of achieving and maintaining competitive advantage on the market in conditions of the global crisis. Keywords: : information technologies, competitive advantage, market, global crisis. 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.
IMPLEMENTATION OF FOG COMPUTING IN IOT-BASED HEALTHCARE SYSTEM
Vol. 7 No. 2 (2018): JITA – APEIRON Mirjana Maksimović IMPLEMENTATION OF FOG COMPUTING IN IOT-BASED HEALTHCARE SYSTEM Original scientific paper DOI: https://doi.org/10.7251/JIT1702100M Download Article PDF Abstract INowhere do the technology advancements bring improvements than in the healthcare sector, constantly creating new healthcare applications and systems which completely revolutionize the healthcare domain. The appearance of Internet of Things (IoT) based healthcare systems has immensely improved quality and delivery of care, and significantly reduced the costs. At the same time, these systems generate the enormous amount of health-associated data which has to be properly gathered, analyzed and shared. The smart devices, as the components of IoT-driven healthcare systems, are not able to deal with IoT-produced data, neither data posting to the Cloud is the appropriate solution. To overcome smart devices’ and Cloud’s limitations the new paradigm, known as Fog computing, has appeared, where an additional layer processes the data and sends the results to the Cloud. Despite numerous benefits Fog computing brings into IoT-based environments, the privacy and security issues remain the main challenge for its implementation. The reasons for integrating the IoT-based healthcare system and Fog computing, benefits and challenges, as well as the proposition of simple low-cost system are presented in this paper. Keywords: : Fog computing, Cloud computing, healthcare, Raspberry Pi. 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 APPLICATION OF ONLINE PLATFORMS IN OPEN INNOVATION
Vol. 7 No. 2 (2018): JITA – APEIRON Radul Milutinović, Biljana Stošić, Velimir Štavljanin THE APPLICATION OF ONLINE PLATFORMS IN OPEN INNOVATION Original scientific paper DOI: https://doi.org/10.7251/JIT1702092M Download Article PDF Abstract It is well known that innovation has been recognized as a crucial success factor for companies. The development of information technologies enabled integration of innovators (suppliers, customers, institutes) into innovation process by the use of IT-based tools. This facilitated the access to a large pool of ideas that can grow into innovation as new product/service, process. The connection of open innovation concept and information systems resulted in platforms for open innovation that enabled easier access, not only to customers, but also to other potential participants, who are willing to independently contribute in solving the specific problems of the company. Having in mind the importance of this contemporary approach, the main goal of the paper is the systematization of platforms for open innovation. Moreover, we presented platform classification, key elements of existed platforms design, as well as various examples of best practice of platforms for open innovation with recognized design elements. Keywords: : Open innovation, Innovation platforms, Customer involvement. 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.