Bulletin of Lviv State University of Life Safety

Титульна сторінка

М. Сорочич — Wed, 18 Jun 2025 00:00:00 +0300

Wed, 18 Jun 2025 11:20:53 +0300

MORPHOLOGICAL COMPOSITION OF POLYMER COMPONENTS IN ELECTRONIC WASTE

E. V. Grechaniuk, V. A. Ishchenko — Thu, 19 Jun 2025 00:00:00 +0300

Nowadays, the recycling of polymers, including those contained in waste electrical and electronic equipment, is relevant. The possibility and method of polymer recycling depend on their composition and properties. The purpose of this study is to analyse the composition of the main polymeric components of e-waste, typical impurities, and their impact on the properties of materials based on literature data. The article discusses the chemical composition of polymers used in electrical and electronic equipment, in particular acrylonitrile-butadiene-styrene (ABS), polyvinyl chloride (PVC), polystyrene (PS), polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET), styrene-acrylonitrile resin (SAN), polycarbonate (PC), polyurethane (PU), polyamide (PA), polyoxymethylene (POM), polymethyl methacrylate (PMMA), polybutylene terephthalate (PBT). It is investigated that large appliances and devices, monitors, and TVs of the old model (with a cathode ray tube) contain the smallest number of different polymers - up to 10 different types, while in other devices the number of different polymers is much higher. Typical impurities included in the composition of each of these polymers are also analysed: antioxidants, stabilizers, plasticizers, fillers, dyes, modifiers, and residual monomers. In particular, the impurities include several potentially hazardous substances that can cause environmental risks in the further management of waste electrical and electronic equipment. We have identified shortcomings that can reduce the productivity of further recycling: the lack of polymer identification marks, the use of several different types of polymers in one type of equipment, and the combination of plastic and metal in the equipment, which creates problems for the recycling of both fractions. Further research should be aimed at developing safer polymer modifications and efficient methods of recycling.

THE IMPACT OF PHYSICAL PROCESSES ON WATER QUALITY INDICATORS FROM NATURAL SOURCES IN THE CITY OF VYNNYKY, LVIV REGION

U. V. Khromiak, M. A. Vorobets — Thu, 19 Jun 2025 00:00:00 +0300

Introduction. The quality of drinking water is a critical factor influencing both public health and environmental safety. Special attention should be given to natural water sources that are used by the local population without prior treatment.
Purpose. To study water from various natural sources in Vynnyky, a town in the Lviv Region, and to analyze the effects of boiling and freezing on its quality.
Methods. Water samples were collected from two natural springs in Vynnyky, a town in the Lviv Region, located on B. Khmelnytsky Street and M. Kypriyan Street. The study involved three types of samples: untreated (ordinary) water, water after freezing, and water after boiling. The following parameters were analyzed on-site: pH, nitrate, nitrite, sulfate, and chloride concentrations.
Results. The pH values of the water samples varied depending on the treatment method. An increase in pH was observed in the boiled water, which can be attributed to the evaporation of water and the resulting concentration of alkaline salts. In the samples from the spring on M. Kypriyan Street, a slight increase in pH was also recorded after freezing, indicating a high concentration of alkaline components.
The most significant changes were recorded in nitrate concentrations. In the samples from the spring on M. Kypriyan Street, the highest nitrate levels were detected — 393 mg/L in frozen water and 307 mg/L after boiling, which greatly exceeds the maximum allowable limit of 50 mg/L according to the drinking water standard DSanPiN 2.2.4-171-10. This may indicate contamination of groundwater in the area by agrochemicals or domestic sources. In the water from the spring on B. Khmelnytsky Street, nitrate levels were lower but also increased after thermal treatment. Nitrites, chlorides, and sulfates were not detected in any of the analyzed samples.
Conclusions. The condition of natural springs located on B. Khmelnytsky Street and M. Kypriyan Street in Vynnyky was analyzed. The conducted research determined that the water is unsuitable for drinking purposes. According to the results, all samples showed exceedances in various parameters.

PREDICTION OF RADIOACTIVE COMPOUND SEDIMENTATION FROM DEACTIVATION STATION WASTEWATER IN URBAN SEWERAGE SYSTEMS

Thu, 19 Jun 2025 00:00:00 +0300

Problem. Under current conditions of urban wastewater management, the issue of safe discharge of effluents containing radioactive substances is of particular relevance. The risk of forming insoluble radioactive sediments in sewer pipes remains unresolved, which could lead to accumulation, operational difficulties, and a significant increase in environmental hazards at such industrial facilities.
Objective. To assess the probability of sedimentation of radioactive compounds from the industrial wastewater of a deactivation station upon discharge into urban sewer systems. To assess the probability of insoluble compound formation and subsequent sedimentation in urban sewerage networks, arising from the interaction of radionuclides in deactivation station wastewater with components of urban wastewater.
Research Methods. Hydrochemical analysis, gamma spectrometry for measuring radionuclide activity, and specially developed software for converting radionuclide activity to mass concentration were used. Calculations were carried out based on sedimentation equilibrium considering the chemical properties of the substances.
Main Results. It was found that most radioactive substances (Ra-226, Th-232) present in the wastewater of the deactivation station precipitate at the stage of local treatment in a sump, especially when coagulants are applied. Iodine-131 and other water-soluble isotopes (K-40, Cs-137) do not precipitate under urban sewer conditions. Calculations confirmed that the residual radionuclide concentrations are significantly lower than the threshold levels required for sediment formation, including in reactions with hydrogen sulfide.
Conclusions and Author’s Proposals. It is proven that by adhering to established technological standards"and the use of coagulation, the risk of radioactive compound sedimentation in urban sewer systems is eliminated. It is recommended to implement similar monitoring and treatment systems at other radiation-hazardous industrial facilities.

SOFTWARE PRODUCTS' COMPREHENSIVE SUPPORT DECOMPOSITION MODEL BASED ON PERCEPTION DIMENSIONS

A. I. Pukach, V. M. Teslyuk — Thu, 19 Jun 2025 00:00:00 +0300

The main problem is the need to develop a comprehensive support model for software products, based on the dimensions of perception formed by the relevant impact factors influencing the subjectivisation of the researched support objects (i.e. the supported software complexes themselves and the processes of their comprehensive support) by the relevant interaction subjects. The purpose of the research is to develop an appropriate decomposition model for the comprehensive support of software products based on perception dimensions. Comprehensive support of software products is an extremely multifaceted and complex process that encompasses all activities aimed at ensuring the existence and operation of supported software products. That is why comprehensive support of software products requires effective and efficient decomposition mechanisms and tools, one of which is, in fact, the proposed decomposition model that is based on perception dimensions. Thus, the developed model enables the decomposition of the complex support of software products, providing the opportunity for more effective research into the comprehensive support processes at each component level. At the same time, basic classification and decomposition methods are used as the primary research tools. The main results of the research consists in obtaining a decomposition models (of comprehensive support of the investigated software products) based on perception dimensions. The practical applied task of identifying the dominant perception’s dimension (of the researched environment of investigated software product’s comprehensive support) has been solved in scope of current research. The main prospects for further application of the developed decomposition model (based on perception dimensions) in the context of scientific and applied problematics of automation and intellectualization of software products’ comprehensive support are declared.

METHODS AND MEANS OF DATA PROCESSING IN MODERN AUTOMATED SYSTEMS

D. D. Smyk, N. E. Burak — Thu, 19 Jun 2025 00:00:00 +0300

Introduction. In modern automated systems, data processing is crucial for ensuring efficient and accurate processes. The use of various methods and tools, such as artificial intelligence algorithms, cloud technologies and big data, enables system performance to be optimised and decision-making to be accelerated. These approaches increase productivity, reduce costs, and improve adaptability to changes in the digital environment.
Goal. The aim is to analyse the methods and means of data processing in modern automated systems in order to determine their efficiency, application features and impact on process optimisation.
Research objectives: The aim is to investigate and evaluate the methods and means of data processing in modern automated systems, with a view to improving their effectiveness. This will involve developing a conceptual model for managing information flows in the context of digital transformation.
Research methods. The research employed literature analysis methods to study the theoretical foundations of data processing in modern automated systems. It also used comparison and generalisation methods to determine the efficiency and application features of different approaches. A systematic approach was also employed to evaluate the relationship between data processing methods and their effect on process optimisation.
The results. A lack of comprehensive studies covering the synergy of machine learning methods, big data processing, and quantum computing in the context of optimising analytical processes was revealed in the studied subject area, modern standards, and the current state of scientific research in the field of automated data processing systems.This requires the establishment of a conceptual framework and the development of an integrated data processing model that takes into account the volatility of the digital environment and the evolving nature of information technology. The formation of the data processing concept in automated systems is based on a multifactor approach that includes five vector directions of information flow management: analysis of the structure and sources of big data, application of machine learning methods for classification and forecasting, optimization of distributed processing processes, implementation of streaming analytics technologies, and the use of quantum algorithms to improve analytical computations. The developed concept involves creating an adaptive system that enables real-time decision-making based on large volumes of information, considering environmental variability factors and data security. The study of data processing revealed the benefits of an integrated approach combining traditional statistical methods, deep learning algorithms, quantum optimisation models and streaming analytics technologies. A conceptual data management model for automated systems has been developed. Consisting of five interconnected blocks, it provides comprehensive data analysis and processing at various levels of digital infrastructure. These include systemic big data analysis, the application of neural network technologies for classification and forecasting, the implementation of streaming data processing algorithms, the integration of distributed computing systems and the implementation of quantum algorithms for accelerating computation. The proposed model improves the accuracy of analytical forecasts, reduces data processing time and ensures continuous information updates.
Conclusions. This study examines modern data processing methods in automated systems, including statistical approaches, machine learning, distributed computing and quantum technologies. The advantages and limitations of each approach are identified, and the importance of integrating them to improve the efficiency and adaptability of such systems is emphasised. Particular attention is paid to the role of automated systems in different sectors, ranging from medicine to industry, and their effect on data-driven decision-making processes. The paper also emphasises the importance of the ethical and security aspects of data processing within the context of digital transformation. The development of a conceptual data management model is feasible and aims to support the evolution of a resilient and secure digital infrastructure.

APPLICATION OF HYBRID MODELS IN MONITORING ECOLOGICAL COMMUNITIES

Yu. M. Sorochych, S. P. Striamets, O. V. Khlevnoi, N. V. Zhezlo-Khlevna — Thu, 19 Jun 2025 00:00:00 +0300

Monitoring ecological communities in natural reserves is of critical importance for biodiversity conservation, especially in the context of climate change and human-induced pressures. Traditional methods, such as manually analysing camera trap data or using statistical modelling, have limitations. These include low image quality due to weather conditions or insufficient lighting, uncertainty when classifying similar species and a lack of adaptation to local ecosystems. Although modern approaches based on convolutional neural networks (CNNs) demonstrate high accuracy with global datasets, their effectiveness decreases in real-world conditions involving noise and limited training data, particularly with regard to regional peculiarities. The application of hybrid models combining CNNs with fuzzy logic offers a promising solution, enabling the handling of uncertainty and enhancing system robustness. However, these approaches remain underexplored, and their practical value for biodiversity monitoring requires detailed analysis.
The purpose of this article is to review the current state of applying hybrid models in the monitoring of ecological communities; to assess their respective advantages and disadvantages compared to traditional methods; and to outline prospects for their future development. The study employs comparative analysis methods to evaluate the accuracy, computational complexity, and adaptability of models, alongside data synthesis to identify trends and gaps. Special attention is given to examples of hybrid approaches (CNN + fuzzy logic) in species classification and ecosystem dynamics forecasting tasks.
The analysis conducted in the study indicates that hybrid models achieve an accuracy improvement in species classification of up to 85–90% under challenging conditions (low-quality images, species similarity), surpassing traditional CNNs (70–80%). Their ability to manage uncertainty through fuzzy logic makes them promising for local ecosystems, such as Ukrainian reserves. Nevertheless, gaps are identified: high computational complexity, limited training data, and insufficient integration with geographic information systems (GIS). Prospects include the development of optimized algorithms, adaptation to regional conditions, and the creation of cost-effective solutions for nature conservation. The findings of this article will contribute to further research and practical implementation of hybrid models in biodiversity monitoring.

ANALYSIS OF THE APPLICATION FEATURES OF PROBABILISTIC AND STATISTICAL METHODS OF DATA PROCESSING FOR FORECASTING AND MODELING CRISIS SITUATIONS

O. R. Staso, N. Ye. Burak — Thu, 19 Jun 2025 00:00:00 +0300

This article explores the role of probabilistic and statistical methods in crisis management. It provides an analysis of the most effective approaches, including machine learning, Monte Carlo simulations, time series analysis, probabilistic graphical models, and natural language processing. The study examines the advantages and limitations of each method, as well as their potential applications in modelling crisis situations, risk assessment, and decision-making. The article also outlines the prospects for integrating these approaches with modern technologies to enhance the effectiveness of managerial decisions under complex conditions.
Problem. In today’s world, traditional approaches to crisis management are often insufficient due to the complexity of analysing large volumes of data and the rapid pace of situational change. This necessitates the implementation of innovative tools that enable real-time analysis, scenario modelling, and risk assessment.
The purpose of this work the aim of this study is to analyze the effectiveness of probabilistic-statistical methods in crisis management, to investigate their advantages and disadvantages, and to identify the prospects for applying these approaches in various fields to improve the decision-making process in crisis situations.
Methods of Research. The study employed a comprehensive approach combining theoretical analysis, empirical observations, and comparative analysis. Current trends in the application of probabilistic-statistical methods were examined. The comparative analysis enabled the evaluation of the effectiveness of various approaches in crisis management. The empirical part included the analysis of time series and textual data to model risks under conditions of uncertainty. This comprehensive approach provided a thorough assessment of the role of probabilistic-statistical methods in crisis management.
Results. The results of the study demonstrated that probabilistic-statistical methods are effective tools for crisis management. In particular, these methods enable:

modeling scenarios of event development under crisis conditions;
assessing levels of risk and uncertainty;
optimizing managerial decisions under time constraints;
integrating modern technologies such as artificial intelligence and big data to enhance the accuracy of analysis.

AUTOMATED PERSONALITY TESTING BASED ON JUNG’S AND REININ’S PSYCHOLOGICAL MODELS

I. H. Tsmots, I. V. Gado, N. O. Borysyak, S. V. Tesliuk, O. O. Morushko — Thu, 19 Jun 2025 00:00:00 +0300

Introduction. Modern psychological assessment methods are essential tools in a wide range of fields, including education, recruitment, healthcare, military applications, and crisis management. One of the most prominent frameworks for personality typology is the model proposed by Carl Jung and later expanded by Aleksandr Reinin. These typologies offer a structured approach to understanding individual differences in cognition, behavior, and interpersonal interaction. However, the practical use of such methods often relies on manual processing and expert interpretation, which can be time-consuming and prone to subjectivity. As demand increases for rapid and accurate personality assessments in both individual and organizational contexts, automation presents a valuable solution for enhancing consistency, objectivity, and scalability.
Objective. The primary objective of this study is to develop a comprehensive software system that automates the process of determining an individual’s psychological type based on the typologies of Jung and Reinin. The aim is to eliminate reliance on subjective evaluation by using deterministic algorithms and formalized mathematical models that interpret test responses with precision and repeatability.
Methods. The methodology involves encoding psychological typologies into a set of quantifiable parameters. Each test question is mapped to specific personality traits and assigned numerical values representing the strength of the expressed feature. These values are then processed using weighted summation and normalized to ensure comparability across different traits and users. Reinin traits are derived through the application of logical functions that analyze complex patterns in user responses. The final personality profile is constructed as a multidimensional vector, which is then compared against a database of standardized type templates using Euclidean distance metrics to identify the closest match. The implementation was carried out in Python, employing the Tkinter library for the graphical user interface, SQLite for data management, and Openpyxl for exporting results in Excel format.
Results. The developed system provides users with an intuitive interface for completing tests and receiving results. Automated analysis eliminates the need for manual intervention, ensuring reliability and consistency of outcomes. Throughout the development and testing phases, the system demonstrated high operational stability, classification accuracy and was positively received by users. The formalization of typological models ensures transparency in how results are generated and interpreted, which enhances the objectivity of the diagnostic process.
Conclusion. The developed software system contributes to the modernization of psychological testing by introducing a deterministic and mathematically grounded approach to personality type assessment. It addresses key limitations of traditional manual testing and provides a robust platform for practical application in educational settings, professional counseling, personnel development, and beyond. By leveraging algorithmic processing and structured data analysis, the system delivers fast, reproducible, and interpretable results. Furthermore, future developments include the integration of Big Five-type models and the use of machine learning to enhance adaptability and personalization.
Overall, the solution offers a reliable and efficient method for psychological diagnostics that aligns with contemporary demands for digital tools in human assessment.

THE METHOD OF FORECASTING THE NUMBER OF RESIDENTIAL SECTOR FIRES BASED ON MACHINE LEARNING ALGORITHMS

O. M. Shopskyi, О. V. Khlevnoi — Thu, 19 Jun 2025 00:00:00 +0300

Пожежі в житловому секторі є серйозною загрозою для безпеки населення. Вони спричиняють значні збитки та потребують ефективних методів прогнозування для їх профілактики. У цій статті представлено метод прогнозування кількості пожеж у житловому секторі на основі алгоритмів машинного навчання, який базується на аналізі даних про виїзди рятувальних підрозділів Львівського району. Дані включають інформацію про час, місце й характер подій, агреговану за шестикутниками площею 3 км². Як предиктори використано густоту населення (осіб/км²) і місяць року, закодований як набір із 11 dummy-змінних для врахування сезонності. Для тренування моделей обрано дані за 5 років (2016-2020), для тестування використовувалися дані за 2021 рік. Загальний обсяг даних перевищив 3 тисячі записів, що забезпечує надійну основу для аналізу.
У дослідженні використано чотири моделі: лінійну регресію, поліноміальну регресію (другого степеня), випадковий ліс і нейронну мережу (багатошаровий перцептрон). Лінійна регресія дала змогу оцінити базовий лінійний зв’язок між предикторами та кількістю пожеж, тоді як поліноміальна регресія дозволила врахувати нелінійні ефекти, такі як квадратичний вплив густоти. Випадковий ліс створив передумови для моделювання складних взаємодій між змінними, а нейронна мережа дала можливість виявити приховані закономірності. Точність оцінено за метриками MAE, RMSE і R² на тренувальній вибірці. Найкращі результати показав випадковий ліс із найнижчими похибками, що свідчить про його перевагу в задачах із вираженою сезонністю й середнім обсягом даних. Нейронна мережа виявилася чутливою до обсягу вибірки, а недоліками лінійної та поліноміальної регресій стала обмежена гнучкість. Модель випадкового лісу також було застосовано для прогнозування кількості пожеж на тестових даних. Порівняння прогнозів із реальними значеннями показало задовільну точність, хоча відхилення в зимові місяці вказують на потребу врахування додаткових факторів (наприклад, погодних умов). Метод дозволяє ідентифікувати зони підвищеного ризику, що може бути використано для перерозподілу ресурсів підрозділів цивільного захисту і планування профілактичних заходів. Перспективи включають додавання температури, опадів і просторових моделей, таких як GWR, для підвищення точності.

IMPROVING ENVIRONMENTAL PROTECTION USING FUZZY LOGIC ALGORITHMS FOR ANALYSIS OF WATER RESOURCE CHANGES

A. E. Lahun, N. P. Kukharska, L. I. Chyshynska-Hlybovych — Thu, 19 Jun 2025 00:00:00 +0300

Problem. As humanity develops and the planet’s population increases every day, the problem of environmental threats is becoming increasingly serious. In order to reduce damage to the environment, some people monitor conditions and take action to ensure a better future. This includes cleaning up rivers, lakes and oceans, planting new trees in place of felled ones, and introducing carbon-free technologies. The development of information systems that use artificial intelligence, quadcopters and remote sensing methods to analyse changes in water resources and identify environmental risks allows for a quick and accurate assessment of water resource dynamics. These systems can collect large amounts of data for further analysis and are an important tool for maintaining ecological balance.
The article presents the results of a study on an information system that automates the assessment of water resource conditions by using neural networks, geographic information systems and remotely sensed data acquired by quadcopters.
This system will help users optimize their working environment by providing tools for automating analysis and monitoring tasks. All calculations involving mathematical models and fuzzy logic are performed on the server part, which is responsible for storing data and calculation results in the database. Due to its flexible API architecture, the server component can be integrated into any application. The study also presents mathematical models based on fuzzy logic for analysing water resource indicators and the final state of a body of water.
Purpose. The research objective is to develop an artificial intelligence-based system for monitoring and analysing changes in water resources, using quadcopters and remote sensing methods. The system should provide accurate and timely assessments of the condition of water bodies to inform decisions regarding their preservation and restoration. Fuzzy logic algorithms were employed to achieve the required forecasting outcomes.
Research results. An information monitoring system was designed to assess the pollution of water resources. The main advantages of this system are its ability to predict the general state of water bodies based on photo and video information, and its graphical interface, which displays biological, hydromorphological, chemical, physicochemical and specific polluting indicators of water bodies on a map.
The study of water body pollution indicators was carried out in two stages, using the fuzzy logic apparatus of the MATLAB environment. At the first stage, the poor, average or good condition of the reservoir concerning the above indicators was detected. These indicators included numerous biological indicators related to phytoplankton, hydromorphological indicators in the form of water level and interaction with the environment, chemical indicators in the form of the number of chemical pollutants, and physicochemical indicators determined by temperature, oxygen availability and the physical condition of the water body. At the second stage, a forecast of the reservoir's pollution level was made based on the analysed indicators, and a conclusion was reached by experts about the condition being very poor, poor, moderate, good or excellent.
Conclusions. The information system developed for monitoring water resources uses fuzzy logic algorithms and biological, hydromorphological, chemical and physicochemical indicators.An important stage is ensuring the functionality and speed with which the predicted result is obtained through the use of information technologies associated with the improved, high-precision processing of photos and videos, as well as the fast processing of large volumes of information, due to the features of relational and non-relational databases. The system works correctly by following the developed base of fuzzy rules to produce a forecast, enabling the necessary actions to be taken to improve the environmental safety of water bodies.

INFORMATION SECURITY AND CYBER SECURITY MANAGEMENT IN HIGHER EDUCATION INSTITUTIONS

A. I. Ivanusa, R. L. Tkachuk, N. O. Maslova, V. I. Yashchuk, A. M. Tkachenko — Thu, 19 Jun 2025 00:00:00 +0300

Research problem. In the current conditions of rapid digitalization of education, the issues of information security and cybersecurity in higher education institutions are becoming extremely relevant. Educational institutions store a significant amount of confidential data, including personal information of students, employees, research results or intellectual property. Unauthorized access to such data can cause significant reputational and financial damage. In this context, the implementation of an effective information security policy is a key element of the risk management strategy. It allows you to regulate the procedure for processing, storing, and transmitting information, preventing leaks and misuse. Constantly evolving cyber threats demand a systematic approach to the formation of protective mechanisms. A cybersecurity policy promotes the implementation of procedures for detecting, responding to, and eliminating security incidents. It also ensures compliance with legal and regulatory requirements, particularly with regard to personal data
protection. Implementation of this policy raises awareness of information security among participants in the educational process. Thus, the development and implementation of information security and cybersecurity policies in higher education institutions is a prerequisite for the stable and secure functioning of the educational environment.
Aim. The aim of the work is to improve the working tools for managing information security and cybersecurity in higher education institutions by identifying threats, analyzing network infrastructure vulnerabilities, and developing information security policies based on risk assessment, according to modern international and national standards in the field of information security.
Research methods. The study uses system analysis, observation, modeling, comparison, expert evaluation, ranking, normalization, probability theory, decision-making theory, and information security theory.
Results. The study examines the process of information security management and its relationship with the continuity of operational processes. It has been found that the lack of effective information security measures and policies can jeopardize the continuity of the daily activities of the higher education institution. Particular attention is paid to discretion in managing information security processes, which is a key aspect of protecting information assets. Using the example of Lviv State University of Life Safety, the author analyzes the means of information protection and network infrastructure, identifies shortcomings, and proposes organizational, software, and technical measures to improve the level of information security. The proposed adaptive methodology for analyzing technical software is suitable for use by business entities regardless of their financial capabilities.

MODELING THE PROTECTION OF OPERATING SYSTEMS FROM CYBERATTACKS USING THE PEARSON CRITERION

R. L. Tkachuk, O. I. Polotai, V. S. Balatska, T. B. Brych, N. P. Kukharska — Thu, 19 Jun 2025 00:00:00 +0300

Introduction. In today's conditions of rapid development of digital technologies and the increase in the number of cyberattacks, the issue of effective protection of operating systems is becoming particularly relevant. Traditional information security tools are often unable to respond in a timely manner to the latest types of threats that are constantly evolving and becoming more complex. One of the key problems remains the insufficient effectiveness of methods for predicting cyberattacks, which does not allow for timely detection of potential vectors of interference in systems. At the same time, modern statistical analytics opens up new opportunities for developing models that can determine the probability of an attack even before it is actually carried out. One of such methods is the use of the Pearson correlation coefficient to identify patterns between system activity and the probability of cyber incidents. However, in practice, research in this area remains fragmented, and a systematic approach to modeling protection - taking into account statistical
dependencies between security parameters - is still developed. Thus, the arises a need to develop a comprehensive model for protecting operating systems from cyberattacks. This model should be based on the analysis of correlations between the system’s behavioral characteristics and indicators of a potential threat, using the Pearson criterion as a tool for identifying significant dependencies.
Purpose. The purpose of this article is to develop and substantiate a model of an action plan for protecting operating systems from cyberattacks. The proposed model identifies correlations between system performance parameters and threat indicators using the Pearson criterion, and applies the results to predict the probability of attacks and enhance anomaly detection systems in cyberspace.
Results. The article presents the results of a study that modelled the protection of operating systems against cyberattacks. The study used the Pearson criterion to identify statistically significant relationships between quantitative cyberthreat cases against different types of operating system.
A cybersecurity action plan for Windows and Linux operating systems was modelled based on the results obtained, taking into account their specifics and equivalent vulnerability to cyberattacks.
The key areas of protection are outlined, including system updates, access control, monitoring, network security, redundancy and staff training.
Conclusion. The proposed modelling, based on the Pearson criterion, enables the effective detection of statistical patterns preceding the implementation of cyberattacks on operating systems.
The use of such an approach increases the level of preventive protection and contributes to the timely detection of
potential threats.

CONCEPTUALIZATION OF INTEGRATIVE USE OF VULNERABILITY DATABASES IN THE CONTEXT OF SYSTEM MANAGEMENT OF INFORMATION SECURITY

V. I. Yashchuk, A. I. Ivanusa, N. O. Maslova, R. L. Tkachuk, T. B. Brych — Thu, 19 Jun 2025 00:00:00 +0300

The article discusses the conceptual principles of the integrative use of vulnerability databases within the framework of information security system management. In the context of the rapid growth of the number of cyber threats and the expansion of digital attack surfaces for state and corporate structures, the need for systematic, automated and context-oriented use in information security processes is becoming particularly relevant.
The research addresses the problem of the lack of coordination between different sources of vulnerabilities, the diversity of data submission formats (for example, CVE, CWE, CVSS), the lack of real-time prioritization mechanisms, as well as the limited integration of vulnerability databases into existing information security management systems in accordance with the requirements of ISO/IEC 27001, NIST CSF and other regulatory documents.
The central issue addressed by this research is the lack of coordination between different vulnerability sources, the diversity of data submission formats (e.g., CVE, CWE, CVSS), the absence of real-time prioritization mechanisms, and the limited integration of vulnerability databases into existing information security management systems, despite the requirements of ISO/IEC 27001, NIST CSF, and other regulatory documents.
The methodological basis of the study is the logical-structural modeling of the processes of collecting, normalizing, processing, contextualizing and prioritizing vulnerability data in order to integrate them into information security systems.
A conceptual model is proposed that includes sources of external vulnerability databases (NVD, CVE, CISA KEV, Microsoft SUG, etc.), aggregation and normalization modules, a contextual analysis block taking into account threats (Threat Intelligence), as well as prioritization mechanisms using CVSS, EPSS metrics, exploit availability, and connection to critical assets. Particular attention is paid to integrating the obtained results into the existing information security infrastructure, including SIEM, SOAR, CMDB, ITSM, and other components.
The research results enable effective support of decision-making processes in the field of information security, reduce response time to critical vulnerabilities, and increase the overall level of cyber resilience of organizations. The research results enable effective support of decision-making processes in the field of information security, reduce response time to critical vulnerabilities, and increase the overall level of cyber resilience of organizations. A comparative analysis of current vulnerability databases was carried out according to a number of criteria (availability of CVE identifiers, CVSS support, availability of risk calculators, integration capabilities, etc.), which allows justifying the choice of sources for
automated monitoring and risk assessment.
The scientific novelty lies in the formalization of an integrative approach to the use of vulnerability databases in information security system management, the identification of critical requirements for such databases in terms of automation of information security processes, as well as in the proposed logical-structural model that covers the full vulnerability management life cycle - from detection to response. The presented results can be used as a basis for the
development of information and analytical platforms for monitoring cyber risks, building risk calculators and security audit tools.

TECHNOLOGY FOR THE PREPARATION OF COPPER(II)-AMINE COMPLEXES FOR THEIR APPLICATION AS ANTI-FIRE CURRENT IN EPOXY COMPOSITIONS

O. I. Lavreniuk, B. M. Mykhalichko — Thu, 19 Jun 2025 00:00:00 +0300

Introduction. In recent years, there has been a growing interest in metal-containing flame retardants, which are suggested to be used in reducing the fire hazard of polymers, particularly composite materials based on epoxy resins. Complex metal compounds are highly promising for creating epoxy compositions with reduced fire hazard and regulating their characteristics.
Such flame retardants can form stable metal oxides that become part of the carbonized residue during combustion, as well as catalyze polymer decomposition in the direction of increasing the yield of carbonized residue, which prevents further contact between the polymer material and the flame. Moreover, toxic intermediate aromatic compounds and benzene derivatives, which are the main components of smoke, can be converted into more stable hydrocarbon or polyaromatic compounds in the presence of metal-containing flame retardants, which leads to a decrease in smoke emission. A noticeable effect from the use of reactive metal-containing flame retardants is manifested even with a small content of them in the polymer.
Aim. To develop an effective technology for the preparation of chelated copper (II)-amine complexes, to establish
their structure, which will make it possible to predict the feasibility of their use as flame retardants for epoxy compositions.
Methods. The development of an effective technology for the synthesis of chelated copper (II)-amine complexes
included empirical selection of the ratio of the starting components, the method of their pretreatment, and the
determination of the optimal temperature and duration of the reaction. To establish the relationship between the spatial
structure of the synthesized copper (II)-amine complexes and their physicochemical properties, the crystal structure of
the chelated complexes was studied by X-ray crystallography.
Results. The copper (II)-amine complexes were synthesized by direct interaction of the corresponding Cu (II) salt with PEPA, a hardener of epoxy resins. The formation of high-quality crystals suitable for X-ray crystallographic analysis occurred after the mixture of salt and amine was kept at room temperature for several days. The chemical composition, structure, and crystallographic parameters of the synthesized chelated copper (II)-amine complexes were studied.
Conclusions. A series of chelated copper (II)-amine complexes have been synthesized using an efficient technology. It was found that in the molecules of the complexes, the Cu (II) atom forms strong coordination σ-bonds with the atoms of the N amine ligands. It has been found that copper (II)-amine complexes can simultaneously act as both epoxy resin hardeners and flame retardants. The strength of the amine retention in the complex is a crucial factor in the resistance to ignition and combustion of polymeric materials based on the epoxy amine compositions modified with copper (II)-amine complexes.

STUDY OF THE COMPOSITION OF SUBSTANCES FOR FIRE PROTECTION OF WOODEN BUILDING STRUCTURES IN THE CONTEXT OF REPLACING FIRE-RETARDANT AGENTS

A. F. Havryliuk, М. О. Haiduk — Thu, 19 Jun 2025 21:36:36 +0300

Introduction. Thousands of fires occur every year at facilities of various forms of ownership, where state supervision (control) measures are carried out in the field of technogenic and fire safety. In a significant number of cases, fires occur in buildings in which, according to the Fire Safety Rules in Ukraine, wooden building structures are subject to fire protection. Fire protection ensures a reduction in fire hazard indicators, in particular combustibility, flammability, flame spread, etc.
According to the Fire Protection Rules for Wood, it is determined that the main criterion is the fire protection efficiency group, which is characterized by determining the percentage of mass loss of wood subjected to fire protection after testing. Fire protection methods such as fire protection impregnation and treatment are characteristic of wooden building structures.
Fire protection impregnation itself has become widely used in Ukraine. When analyzing the quality of fire protection by impregnation, it was found that when performing repeated fire protection work using a product different from that used during the previous impregnation, there is a loss of fire protection efficiency. The experiments conducted confirmed this hypothesis and prompted the isolation of this direction for further research.
The purpose of the work is to reveal the patterns of the influence of the ratio of the composition of the fire retardant on ensuring fire protection of wooden building structures when replacing fire retardants.
Methods. As part of the scientific work, analytical studies of the components of impregnating fire and bioprotective substances were conducted. Individual substances were studied using chemical and X-ray fluorescence analysis methods. Based on the identified components, as well as taking into account the results of previous studies, a full-factorial experiment was planned and implemented.
Results. A full-factorial experiment was conducted, within the framework of which key factors and their levels of variation were determined, which ensured the construction of a mathematical model. Based on this model, an experimental matrix was constructed. Eight experimental studies were carried out according to the specified methods, numerical values of mass loss and ignition temperature were obtained, which made it possible to calculate regression coefficients.
Using X-ray fluorescence analysis and chemical analysis methods, it was established that the most common components of fire-retardant substances are diammonium phosphate, orthophosphoric acid and urea. Based on the specified components, the optimal ratio of the composition of the fire-retardant substance was developed using the full-factorial experiment method, which ensures fire protection of wooden building structures when replacing fire-retardant agents. The pattern of the influence of the percentage mass value of phosphoric acid, urea and diammonium phosphate on the fire protection of wooden building structures - in particular, on the ignition temperature and mass loss - was established.
Conclusion. Based on the analysis of experimental research data, regression equations and graphical dependencies, the ratio of the mass composition of the fire retardant substance that is capable of providing fire protection of wooden building structures when replacing fire retardants was determined, namely: diammonium phosphate – 4%, urea – 6%, phosphoric acid – 12%, water – 78%.

INCREASED CONTACT RESISTANCE IN ELECTRICAL NETWORKS AS A CAUSE OF FIRES

A. V. Bespalova, O. P. Dashkovska, O. I. Knysh, O. L. Mirus, O. B. Нornostaі — Thu, 19 Jun 2025 00:00:00 +0300

Problem statement. The article focuses on the actual problem of increased fire hazard of power grids of old buildings in Odesa and Lviv, which is associated with an increase in electrical load and the presence of areas with high transient resistance (TR). Based on the analysis of electrophysical parameters, a method for assessing the state of power grids is proposed, which allows timely detection of emergency areas with HTR.
Research methods. To detect areas with increased transient resistance (TR) in hidden low-voltage power grids (up to 1000 V inclusive), we propose to use a diagnostic approach based on the analysis of the ratio between the input electrical power supplied to the consumer load and the power directly consumed by this load. The methodology involves comparing the input and output voltages with the calculation of the fire hazard factor, which determines the input power to output power ratio, i.e. the proportion of energy that does not reach the load and is lost to heating.
Results. An increase in the fire hazard factor indicates an increase in losses in the network, which, in turn, may indicate a decrease in the cross-section of conductors, oxidation of contacts, or areas with critical transient resistance. Experimental studies of the power distribution network with areas of high transient resistance confirm the effectiveness of this approach for diagnosing hidden networks with voltages up to 1000 V. A photo of the experimental setup for determining the emergency state of a hidden electrical network is shown.
Scientific significance. The proposed approach makes it possible to prevent the emergence of fires in intra-building electrical networks and reduce the risk of fires caused by the thermal effect of electrical energy, that is, to minimize the possibility of fires in buildings, in particular in historical heritage sites.

PROBLEMATIC ISSUES OF INTEGRATING UNMANNED AERIAL VEHICLE TECHNOLOGIES INTO CIVIL DEFENSE SECTOR

Thu, 19 Jun 2025 00:00:00 +0300

Currently, the issue of territorial security and protection against large-scale emergencies is becoming increasingly important. To ensure high-quality monitoring and surveillance, civil defense workers have begun using unmanned aerial vehicles, which are on duty at the units of the State Emergency Service of Ukraine.
The aim of the article is to investigate the problematic aspects and develop recommendations for the effective and efficient integration of unmanned aerial vehicle technologies into the practical activities of civil defense units.
Research Methods. To study the problematic aspects and develop recommendations for the effective and high-quality integration of unmanned aerial vehicle technologies into the practical activities of civil defense units. The article analyzes the functions of the structural units of the State Emergency Service of Ukraine regarding the use of unmanned aerial vehicles to predict the likelihood of emergencies and monitor high-risk facilities. The article analyzes the statistical data on the distribution of unmanned aerial vehicles across the country in the units of the State Emergency Service of Ukraine and also develops a flowchart of the types of unmanned aerial vehicles used by the operational and rescue units of the State Emergency Service of Ukraine.
Research Results. The article analyzes the functions of the structural subdivisions of the State Emergency Service of Ukraine regarding the use of unmanned aerial vehicles to predict the probability of emergencies and monitor hazardous situations, which in turn will have a positive impact on the emergency response time and will also make it possible to monitor an emergency (hazardous) situation in real-time mode.
The result of the study is a set of recommended measures that will enhance the integration of the unmanned aerial vehicle system into the practical activities of the units of the State Emergency Service of Ukraine.

TERMINOLOGICAL ASPECTS IN TRANSPORT SYSTEM MODELING

L. P. Hashchuk, P. М. Hashchuk — Thu, 19 Jun 2025 00:00:00 +0300

In the theory of transport processes and transport systems, we often have to use terms whose meaning is not fully understood. For example, are transportation and a transportation system two completely different concepts? If transportation is a system, what is the system's backbone or substrate? When we manipulate transport, do we carry out transport production (materially enrich the world), or do we provide a useful service? What are the actual products of transport? How can we treat logistics objectively: is transport a tool in the hands of logistics, or is it the other way around? The purpose of the study is to clarify or organize the content of the listed concepts and terms widely used in the theory of transport processes and transport systems with the help of more reliable arguments.
It appears that the terms “transport” and “transport system” are synonyms of the same thing. It can be said that the term “transport” is an object designation of the same thing that, in cognition, is a transport system. A completely extraneous spatio-temporal factor, which can be called transport potential or transport pressure, generates a transport system as such. Potentials arise due to the uneven dispersion of civilization products and civilization demand.
Transport is a full-fledged participant in production, and the transportation process is rather a material production. It makes no sense to consider the transportation process itself as a product. Rather, products are goods or an interested party at the destination, which were forced to be in the status of cargo or passenger during the transportation process. In particular, transport picks up a finished product of “someone else's” production, but brings goods to the final destination, while goods are a product of “its” production. However, it is not necessary to categorically deny the service aspect of transport use. The sphere of services and the sphere of goods seem to be closely intertwined.
If logic is the science of thinking, then logistics is a hybrid ideology (or perhaps philosophy) of doing and managing. Transportation should be driven by logistics, not the other way around. This statement should become a postulate of the theory of transport systems, and postulates are known to be the framework of science.

INFORMATION TECHNOLOGIES IN THE MANAGEMENT OF EDUCATIONAL INSTITUTIONS OF THE STATE EMERGENCY SERVICE OF UKRAINE

D. I. Andrukhiv, O. V. Prydatko — Thu, 19 Jun 2025 00:00:00 +0300

Problem: The modern educational system, especially in the institutions of the SES of Ukraine, faces the need to adapt to rapid technological and social changes. The conservative approaches to managing educational processes, insufficient digitalization and lack of automated systems for organizing educational activities complicate the effective functioning of the education system.
The study aims to analyze the integration of information technologies into the management of educational institutions of the SES of Ukraine, determine their impact on the quality of the educational process and suggest ways to optimize through the introduction of modern digital solutions.
Research methods: The analysis of scientific sources, regulations, international experience, as well as examples of platforms implementation (e.g., Indico, Open Conference System, LMS MOODLE) in educational institutions was used. The methods of comparative analysis, systematic approach and evaluation of the effectiveness of technological solutions were applied.
The main results of the study: The study proves that digital technologies are a powerful tool for transforming educational management. They provide comprehensive automation of administrative processes, create new opportunities for communication between participants in the educational process, and open access to new generation interactive learning resources. Of particular scientific value is the justification of the need to develop digital competence as a key competence of modern teaching staff and students, which is a decisive factor in the successful adaptation of the educational system to the challenges of the digital age.
Conclusion: The integration of information technologies into the management of SESU educational institutions is a necessary way to improve the quality of education, optimize processes and ensure the competitiveness of graduates. To achieve this, it is necessary to develop infrastructure, improve the digital skills of teaching staff and actively implement modern platforms.

OPTIMIZATION OF SECURITY INFRASTRUCTURE IN POST-WAR RECONSTRUCTION PROGRAMS USING MODERN GEOGRAPHIC INFORMATION SYSTEMS (GIS)

А. M. Tryhuba, R. T. Ratushnyi, А. R. Ratushnyi, L. S. Koval, A. I. Ivanusa — Wed, 18 Jun 2025 12:27:26 +0300

Introduction. The article substantiates the peculiarities of managing the configuration of fire and rescue units and highlights the relevance of optimizing their deployment in the post-war period to restore the functionality of security infrastructure. Based on an analysis of the current state of theory and practice, it has been established that the effective deployment of fire and rescue units requires the use of geographic information systems (GIS) for spatial analysis of territories, risk assessment, resource constraints, and infrastructure accessibility. In the context of limited funding, demographic shifts, and damage to the transport network, the project-based management of fire and rescue units necessitates a systematic approach, the application of modern management tools, and the integration of spatial data into the decision-making process for developing security infrastructure at the level of administrative districts and communities.
Purpose. To substantiate an approach and develop a method for optimizing the location of fire and rescue units in the post-war period using modern geographic information systems. The proposed method aims to enhance the efficiency of management decision-making, ensure rational resource planning, minimize emergency response time, and improve the safety of critical infrastructure facilities under conditions of limited resources and a dynamic planning environment.
Methods. To examine the post-war conditions of the territories within selected administrative districts, a statistical evaluation method was applied to assess socio-demographic and infrastructure characteristics. This approach made it possible to identify key factors influencing the project environment. A systematic approach, geographic information analysis, territorial coverage modeling, and optimization techniques for the placement of fire and rescue units were employed. Additionally, methods of analysis and synthesis were used to determine the main variables shaping the system structure for deploying fire and rescue units in specific areas. The proposed tools are based on modern information technologies. In particular, geographic information systems (GIS), spatial modeling, and optimization algorithms were applied to support informed management decisions regarding the location of fire and rescue units during the post-war recovery period.
Results. A method for optimizing the location of fire and rescue units within a given administrative territory has been developed. It consists of a systematic implementation of ten stages and utilizes geographic information systems (GIS) based on the OpenStreetMap (OSM) framework. The approach accounts for the topography of the area and existing damage to infrastructure facilities (such as roads, bridges, and buildings), which affects travel time to emergency scenes and the effectiveness of territorial deployment.
Fire and emergency risk forecasting serves as the basis for modeling possible location scenarios. The optimization process involves clustering risk zones, analyzing the transport network to assess accessibility, and applying algorithms to minimize the response time of fire and rescue units to emergencies.
Conclusions and specific proposals of the author. The study confirms the relevance and necessity of implementing projects aimed at establishing fire and rescue units, as well as the urgency of optimizing their deployment in the post-war period to restore the functionality of security infrastructure.
Based on the research, a method was developed that utilizes modern geographic information systems (GIS) to provide accurate, up-to-date spatial data. This enables comprehensive analysis of a given administrative territory and supports informed decision-making regarding the optimal placement of fire and rescue units. The method considers available resources, demographic trends, the condition of transport infrastructure, and risks associated with a dynamic project environment.
The use of analytical tools based on the OpenStreetMap (OSM) framework allows the territorial deployment of fire and rescue units to be coordinated with ongoing changes in the project environment.
Further research is recommended to apply the proposed method in various administrative areas affected by military operations. This will help to substantiate practical recommendations for project managers regarding the configuration and planning of fire and rescue services.
The author also proposes integrating computational intelligence tools into the planning and implementation processes to enhance adaptability in dynamic and resource-constrained conditions.

INTELLIGENT MODELS FOR MANAGING COMMUNITY INFRASTRUCTURE DEVELOPMENT PROJECTS UNDER MULTILEVEL RISKS

Thu, 19 Jun 2025 00:00:00 +0300

Introduction. The article substantiates the relevance of managing community infrastructure development projects in the context of multilevel risks. Three types of infrastructure projects (security, medical, and energy) are considered. Based on the analysis of modern approaches in science and practice, it is established that existing management models are mostly narrowly focused, do not take into account the dynamic project environment, which causes multi-level risks, and do not provide adaptability to the project environment, the need for rapid changes in projects. Given the important role of timely response and efficient use of limited resources, the management of community development infrastructure projects requires a multisectoral approach. It integrates intelligent methods, risk forecasting, and prioritization of project implementation scenarios. In a dynamic project environment, it is especially important to develop value-based solutions based on the use of computational intelligence and multi-criteria optimization to ensure sustainable community development.
Purpose. To substantiate the approach and develop an intelligent multisectoral model of project management for the development of security, medical and energy infrastructures of communities, taking into account multilevel risks, which allows to increase the efficiency of management decisions, ensure adaptive resource planning, integrate modern artificial intelligence technologies into the process of strategic development of territories, minimize the consequences of undesirable events and improve the sustainability of infrastructure systems in a dynamic project environment with limited.
Methods. To achieve the stated research objective, a comprehensive approach was applied, combining modern methods of analysis, modeling, and optimization, along with the use of artificial intelligence tools and geoinformation technologies. This approach enables the consideration of the multicomponent structure of community infrastructure and ensures cross-sectoral integration within a single project management model focused on security, healthcare, and energy development in local communities. One of the key methodological foundations is the use of systems analysis, which allows for identifying interconnections among various components of infrastructure development projects, assessing their sensitivity to external and internal risks, and determining the priority of management interventions. This approach provides a holistic view of governance processes within a community and enables the identification of critical influences by focusing attention on the most significant elements. To construct models of interaction between infrastructure sectors, cognitive modeling was applied. This method makes it possible to visualize cause-and-effect relationships, evaluate system dynamics, and forecast potential development scenarios. The research also proposes the use of computational intelligence methods, including neural network modeling, fuzzy logic, and situational decision-making algorithms. These tools are employed to develop models that adapt projects to changes in the project environment, detect anomalous infrastructure development scenarios, and generate recommendations for future management actions under conditions of uncertainty.
Results. A conceptual model of intelligent multisectoral management of infrastructure projects (focused on security, healthcare, and energy) at the community level has been developed. The proposed model consists of five interrelated levels: 1) the information environment; 2) the project management office (PMO); 3) the portfolio of infrastructure projects (security, medical, and energy) at the community level; 4) the performance/output layer (infrastructure project deliverables); 5) value creation. The model is multisectoral, as it integrates the security, healthcare, and energy components of community infrastructure within a unified strategic space. It incorporates a multisectoral risk management subsystem, which is based on constructing risk matrices that take into account both the likelihood of threats and the severity of their consequences. Additionally, it includes a decision-making subsystem, which applies a function for determining the integral project value.
The value of infrastructure projects is calculated based on five key parameters: risk level, implementation duration, resource availability, accessibility of medical services, and energy autonomy. The model also considers the specific priorities of five stakeholder groups - community residents, the state, local administrations, specialists, and project managers - ensuring a well-grounded prioritization of projects.
Conclusions and specific proposals of the author. Based on the proposed conceptual model, a computer-based implementation was developed, enabling scenario modeling using Python tools. The model was tested on a hypothetical community, which allowed for the evaluation of the integral value of each type of project under three implementation scenarios. In the baseline scenario, the integral value of the healthcare development project was 0.585, the energy project — 0.570, and the security project — 0.609. Under the optimistic scenario, the highest value was observed for the security project (0.828), followed by the healthcare (0.798) and energy projects (0.778). The pessimistic scenario showed a decrease in project value indicators to 0.419 for security, 0.409 for healthcare, and 0.393 for energy. These results confirm the relevance of implementing dynamic models for managing community infrastructure development projects that are sensitive to changes in the project environment. The proposed model enables the consideration of dynamic shifts, supports the justification of priority project selection, and facilitates the adaptation of the infrastructure development portfolio in accordance with resource and risk constraints.
Further application of the model is advisable for evaluating infrastructure projects in real communities, taking into account the spatial, demographic, and security characteristics of the project environment.

KAIZEN IMPLEMENTATION METHOD OF “GREEN” PROJECT MANAGEMENT IN THE ORGANIZATION BASED ON LEARNING MODELS AND ARTIFICIAL INTELLIGENCE

O. V. Verenych, S. A. Dvorskyi — Thu, 19 Jun 2025 00:00:00 +0300

The problem. The current stage of development of the project and program management industry requires the development of new approaches to respond to the serious challenges facing the industry. One of these challenges is the destruction of the ecosystem due to human activity and resource depletion. In such circumstances, the scientific direction of ensuring the environmental compatibility, inexhaustibility, and sustainability of project-oriented enterprises is of particular relevance. The mechanism for such provision can be “green” project management, which is proposed by the authors as a concept and individual artifacts.
The aim of developing the concept of “green” project management is to develop appropriate principles, models, and methods that would ensure the possibility of implementing green transformation projects for project-oriented enterprises in their transition to green entrepreneurship. The purpose of this study is to develop principles and models of green project management, as well as to develop a kaizen method for implementing green project management in an organization based on learning models and artificial intelligence.
Methods. This study used general scientific methods of analysis and synthesis, systems theory and a systems approach for the decomposition of the overall task into subtasks, classification theory to supplement the project classification model, life cycle theory, process management and project management to develop a life cycle model of the proposed method, and the SWOT analysis method for the general characterization of the research conducted.
Results. An analysis of scientific research in the field of “green” entrepreneurship and lean project management, in particular Lean production and Lean project management, is carried out. The principles of kaizen-oriented “green” project management are proposed. In the further development of models for classifying project management methods, taking into account the proposed field of research, additional features of the classification of such methods and varieties of methods within them are proposed. In the further development of the project management thesaurus, definitions of the terms “green” project management”, “kaizen-oriented models and methods of “green” project management”, “green transformation projects” are proposed. For the first time, a kaizen method for implementing “green” project management in an organization based on learning models and artificial intelligence is proposed, and a SWOT analysis of the proposed approach is conducted.
Conclusions. The task of survival of both project-oriented organizations and the ecosystem as a whole must be ensured by a conscious movement in this direction. The way to fulfill such a task is the transition of organizations to “green” entrepreneurship and the management of projects of such a transition using the principles, models and methods of “green” project management. This study proposes such an approach and conducts its SWOT analysis, based on the results of which it is possible to conclude about the prospects of further developments in the direction of “green” project management and the feasibility of their practical implementation. Vectors of further research in the chosen direction have been formulated: further development of models and methods of “green” project management, development of models for implementing and adapting (tailoring) models and methods of “green” project management into the activities of project-oriented and project-managed organizations, development of models for training personnel in models and methods of “green” project management, development of neural network models to ensure increased efficiency of involving artificial intelligence in solving the problems of projects and programs of “green” transformation.

ВІДОМОСТІ ПРО АВТОРІВ

М. Сорочич — Thu, 19 Jun 2025 00:00:00 +0300

Bulletin of Lviv State University of Life Safety

Титульна сторінка

CONTENTS

MORPHOLOGICAL COMPOSITION OF POLYMER COMPONENTS IN ELECTRONIC WASTE

THE IMPACT OF PHYSICAL PROCESSES ON WATER QUALITY INDICATORS FROM NATURAL SOURCES IN THE CITY OF VYNNYKY, LVIV REGION

PREDICTION OF RADIOACTIVE COMPOUND SEDIMENTATION FROM DEACTIVATION STATION WASTEWATER IN URBAN SEWERAGE SYSTEMS

SOFTWARE PRODUCTS' COMPREHENSIVE SUPPORT DECOMPOSITION MODEL BASED ON PERCEPTION DIMENSIONS

METHODS AND MEANS OF DATA PROCESSING IN MODERN AUTOMATED SYSTEMS

APPLICATION OF HYBRID MODELS IN MONITORING ECOLOGICAL COMMUNITIES

ANALYSIS OF THE APPLICATION FEATURES OF PROBABILISTIC AND STATISTICAL METHODS OF DATA PROCESSING FOR FORECASTING AND MODELING CRISIS SITUATIONS

AUTOMATED PERSONALITY TESTING BASED ON JUNG’S AND REININ’S PSYCHOLOGICAL MODELS

THE METHOD OF FORECASTING THE NUMBER OF RESIDENTIAL SECTOR FIRES BASED ON MACHINE LEARNING ALGORITHMS

IMPROVING ENVIRONMENTAL PROTECTION USING FUZZY LOGIC ALGORITHMS FOR ANALYSIS OF WATER RESOURCE CHANGES

INFORMATION SECURITY AND CYBER SECURITY MANAGEMENT IN HIGHER EDUCATION INSTITUTIONS

MODELING THE PROTECTION OF OPERATING SYSTEMS FROM CYBERATTACKS USING THE PEARSON CRITERION

CONCEPTUALIZATION OF INTEGRATIVE USE OF VULNERABILITY DATABASES IN THE CONTEXT OF SYSTEM MANAGEMENT OF INFORMATION SECURITY

TECHNOLOGY FOR THE PREPARATION OF COPPER(II)-AMINE COMPLEXES FOR THEIR APPLICATION AS ANTI-FIRE CURRENT IN EPOXY COMPOSITIONS

STUDY OF THE COMPOSITION OF SUBSTANCES FOR FIRE PROTECTION OF WOODEN BUILDING STRUCTURES IN THE CONTEXT OF REPLACING FIRE-RETARDANT AGENTS

INCREASED CONTACT RESISTANCE IN ELECTRICAL NETWORKS AS A CAUSE OF FIRES

PROBLEMATIC ISSUES OF INTEGRATING UNMANNED AERIAL VEHICLE TECHNOLOGIES INTO CIVIL DEFENSE SECTOR

TERMINOLOGICAL ASPECTS IN TRANSPORT SYSTEM MODELING

INFORMATION TECHNOLOGIES IN THE MANAGEMENT OF EDUCATIONAL INSTITUTIONS OF THE STATE EMERGENCY SERVICE OF UKRAINE

OPTIMIZATION OF SECURITY INFRASTRUCTURE IN POST-WAR RECONSTRUCTION PROGRAMS USING MODERN GEOGRAPHIC INFORMATION SYSTEMS (GIS)

INTELLIGENT MODELS FOR MANAGING COMMUNITY INFRASTRUCTURE DEVELOPMENT PROJECTS UNDER MULTILEVEL RISKS

KAIZEN IMPLEMENTATION METHOD OF “GREEN” PROJECT MANAGEMENT IN THE ORGANIZATION BASED ON LEARNING MODELS AND ARTIFICIAL INTELLIGENCE

ВІДОМОСТІ ПРО АВТОРІВ