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Item type:Наукова стаття, Model of formalized information security audit of an organization with a critical infrastructure facility for compliance with international security standards(CEUR-WS, 2025) Lishchyna, Nataliia; Lishchyna, Valerii; Kozubtsov, Igor; Yashchuk, AndriiThe article emphasizes the importance of conducting information security audits for information systems of critical infrastructure organizations. Effective protection is ensured by aligning security systems with international standards. The audit monitors and assesses compliance but remains effective only when performed regularly by trained specialists. Due to the routine nature of audits and wartime constraints, such as power outages and loss of communication, AI-based methods are often impractical. Therefore, the authors propose a temporary solution using formalized security assessment criteria with clear indicators for objective verification. The study develops a methodology for conducting audits aligned with international standards, addressing the lack of practical guidance in existing ones. It also analyzes global regulatory documents to identify typical management approaches and proposes an adaptable checklist-based methodology covering 10 key information security areas, particularly useful for organizations operating under wartime conditions. © 2025 Copyright for this paper by its authors.Item type:Наукова стаття, A Web-Based Approach for Assessing CO2 Emissions during the Russo-Ukrainian War(Greece, 2024-10-11) Surynovych, Olena; Lishchyna, Nataliia; Yashchuk, Andrii; Povstiana, Yuliia; Lishchyna, ValeriiThe paper is devoted to the development of a web service for calculating and reducing CO2 emissions into the atmosphere during the Russo-Ukrainian War. An analysis and study of the environment of the regions of Ukraine in 2023 was carried out. Emissions from the hostilities in Ukraine are described in detail. An analysis of existing methods and technologies for calculating CO2 emissions was carried out. A prototype of the web service interface was developed to visualize the main elements and functionality of the system. The software was thoroughly tested with various fuel types to ensure compliance with standards and requirements. The architecture and functionality of the web service are partially described.Item type:Наукова стаття, Methods of Presenting the Structure of the Syllabus of a Training Discipline in a Game Form(Dnipro, 2025) Kozubtsov, Igor; Lishchyna, ValeriiOne of the modern requirements of higher education is to ensure that students have the right to freely choose educational components from the list of variable academic disciplines. This is in theory. In practice, it is difficult for students to find logical, not to mention interdisciplinary, connections with the needs of other educational components offered by the department as variable components of the educational component. This is one part of the overall problem. In the future, it is difficult for a teacher in the traditional form of a silobus of an academic discipline to explain to such students the rules of learning, to convey its logical content of structure. The author's research article is aimed at solving these interrelated partial tasks of the general problem. To achieve the purpose of the study, the following tasks were solved: the current state of research and publications in this area was analyzed; theoretical and practical basis for developing a game-based outline was developed. The main part of the study considers the purpose of the syllabus (silhouette) in the traditional form of presentation, and the peculiarities of its writing. An experimental express survey of students' opinions on the sufficient level of information to explain the need to choose this discipline and to evaluate the discipline was conducted. The result confirmed the hypothesis about the need to further improve the structure and content of the curriculum syllabus. At the same time, the students noted a significant improvement in the silhouette sample presented by the lecturer in a game form to improve mental perception. The assumption was experimentally confirmed and students demonstrated an increased interest in the discipline. Thus, the proposed approach to the formation of silhouettes can be announced as a teaching method. The article describes in detail the approach to solving the scientific and applied problem of increasing students’ interest in choosing an academic discipline through understanding the structure, logic and necessity of studying academic disciplines. This is achieved by presenting students with an algorithm for reporting stages in a non-standard game form. The scientific result expands the scientific boundaries of pedagogical sciences in the field of teaching methods for higher education students through the use of simulation as a game-based pedagogical technology. Game-based pedagogical technologies have significant potential in teaching modern students. The proposed solution is fully ready for use by the teacher in practice, but leaves it up to each teacher to adapt the algorithm to a specific discipline. The theoretical results obtained in the course of the research form the basis for its further study and improvement as a teaching methodology. It is expected that the study will have academic and practical value beyond the higher education institutions surveyed.Item type:Наукова стаття, Approach To Risk Management Based On The Assessment Of The Cost Of Quality Of Implementation Of Cybersecurity Measures Of The Organization(Helsinki, 2024-04-24) Kozubtsov, Igor; Lishchyna, Valerii; Yashchuk, AndriiBackground: Intelligent conference rooms are crucial to 21st-century enterprises for events. Safety, resource optimization, and event management depend on accurate counting in such contexts. Manual headcounts are effective yet inefficient and error-prone, particularly for big crowds, requiring automatic people counters. Objective: This article introduces and validates a data-driven algorithm to count and track people in an intelligent conference hall. The concept uses IoT infrastructure, low-resolution cameras, and powerful image-processing algorithms to improve security, resource usage, and real-time management choices. Methods: The message-oriented IoT algorithm incorporates motion detection, background subtraction, people counting, and tracking modules. Blob analysis, edge detection, and low-maintenance, low-resolution cameras are used to capture real-world data. Based on real-time data, a decision-making module controls the conference hall's atmosphere. Results: With a 96.5% accuracy rate and 95% confidence interval in real-time individual counts, the algorithm operates with exceptional dependability. Using real-world data and experimental findings, the algorithm has been extensively tested and shown to work in diverse head counting situations. Conclusion: Intelligent conference hall management using the suggested algorithm might revolutionize venue management. The algorithm's accurate, real-time headcounts improve security, resource utilization, and management decisions, making it a promising candidate for intelligent conference hall management and optimization for diverse events and gatherings.Item type:Наукова стаття, Classification of Landsat 8 Images Using Convolutional Neural Network Based on Minimum Noise Fraction Transform(Helsinki, 2024-04-24) Lishchyna, ValeriiThe use of remote sensing methods has transformed environmental management and regional planning by allowing the identification of items or phenomena on the Earth's surface. However, noise in picture data remains a chronic difficulty in this discipline, compromising spatial resolution and object detection accuracy. The purpose of this study is to improve the classification accuracy of Landsat 8 pictures by developing a Convolutional Neural Network (CNN) based on the Minimum Noise Fraction (MNF) transform. The goal is to evaluate MNF's efficacy in compressing and organizing multispectral images, hence reducing the influence of noise on picture categorization. The MNF transform is used to Landsat 8 image data to remove noisy bands before adopting CNN as a supervised classification approach. The current study takes use of CNN's inherent benefits in dealing with high-dimensional data, learning complicated representations, and automatically extracting key features from pictures, while simultaneously evaluating MNF's efficiency in increasing image quality. The findings show that using MNF as a preprocessing step produces images with improved quality and organization. Subsequent classification using CNN obtained an astounding accuracy of 97.41%, with a great representation of the study region and varied land use categories, highlighting the synergy between MNF and CNN in improving classification performance. The article suggests that combining MNF transform with CNN enhances classification accuracy of Landsat 8 pictures, with positive implications for developments in environmental monitoring, land use mapping, and remote sensing technologies.