Models, systems, networks in economics, technology, nature and society

Background. The article substantiates the relevance of industry foresight strategizing for the oil and gas complex of Russia, as for one of the key sectors of the domestic economy. Problems in the implementation of predictive vision are indicated, such as a high degree of inertia and complexity of the object under consideration, and the insufficiency of theoretical and methodological tools for the formation of predictive parameters. The importance of using expert surveys when implementing strategic foresight sessions is discussed. The author saw the purpose of the research as searching for an evidentiary basis for choosing the vector of strategic development of the domestic oil and gas complex and confirming the presence of inertia in the thinking of experts. Materials and methods. The study was carried out using the Google Forms technology platform by posting on this platform the author’s survey “The Future of the Russian Oil and Gas Complex” and receiving responses from respondents, who were employees of industry companies, as well as representatives of scientific and educational organizations and institutions. Results. As a result of the study, structured answers were obtained to key questions about the prospects and opportunities for the development of the oil and gas complex, regarding the horizon of its existence, the reasons for the crisis and possible stagnation, and the role in the implementation of the sustainable development agenda. Conclusions. The results obtained can be used as reasoned constituent justifications in the development of industry strategic documents and serve as the basis for further development of the theoretical and methodological foundations of strategizing in the oil and gas complex.

Background. The relevance is determined by the need to develop new strategies aimed at improving the technological, resource and environmental efficiency of enterprises in the industrial sector of building materials. The aim of the study is to develop approaches to strategic scenario modelling to improve resource efficiency and potential of enterprises. Materials and methods. The methodological basis of the study is scenario modelling as a tool of strategic analysis and forecasting. The complex of deterministic and adaptive approaches allows strategic scenarios to develop in conditions of high uncertainty and variability of the external environment. Results. Scenario modelling of the enterprise resource potential development through the construction of a set of models (adaptive, ecological-social and "green" integration model) was implemented. The proposed approaches were tested on the example of JSC "Nefrit Ceramics", which allowed us to develop a scenario of resource-efficient development for the enterprise. Conclusions. The conducted research demonstrates the growing importance of the green agenda and harmonisation, which consists in the combination of environmental, technological and economic aspects of the process of production of building materials. The practical significance of the research conducted lies in the possibility of reducing losses and costs in an environmentally oriented development scenario.

Background. In today's healthcare environment, there is an increasing need for efficient methods to analyze biomedical images for disease diagnosis. The present study aims to develop a biomedical image texture analysis system that uses various approaches to detect structural differences between objects. Materials and methods. In this work, local pixel distributions, Fourier transform, and fractal analysis methods are applied. A random forest classifier and dimensionality reduction and clustering methods implemented in the Scikit-learn library are used to evaluate the informativeness of texture features. Experimental data include bone marrow cell images, CT scans, and skin neoplasms. Results. Experimental results show that features based on spatial adjacency matrix and Fourier transform are the most informative for classifying blood and bone marrow cell images. For CT images and skin neoplasms, effective texture features are also identified, achieving f1 metrics as high as 0.93. Conclusions. The developed system enables efficient texture analysis of biomedical images and provides tools for automated evaluation of tumor features, which can significantly improve diagnostic accuracy. Further research will focus on extending the functionality of the system and improving data visualization methods.

Background. In the context of digital transformation, a thorough assessment of the effectiveness of online courses is required to ensure a high-quality educational process, identify optimal teaching methods and timely correction of curricula. The relevance of the research is caused by the need to find new solutions for evaluating the effectiveness of online courses, since existing methods either focus solely on quantitative indicators, which does not allow an adequate assessment of the perception and assimilation of educational material, or are limited to qualitative indicators subject to subjectivity and possible distortions. Inaccuracies in the assessment lead to incorrect management decisions to improve educational materials, student dissatisfaction, and inappropriate use of financial and time resources, which negatively affects the overall level of the educational process. The purpose of the research is to develop and test an integrated approach that will allow for a comprehensive analysis of the educational process and identify problem areas that require correction. Materials and methods. The methodological basis of the research is the systematization of the results of the analysis of scientific literature, practical developments and personal experience of the author, which allowed to form a comprehensive methodology for evaluating the effectiveness of online courses. Results. A concept has been developed based on a balance of qualitative and quantitative indicators, the use of tools that guarantee the reliability and reliability of data, and the use of the Bayesian mathematical model to predict changes in the effectiveness of the exchange rate when indicators change. The practical implementation is demonstrated by the example of the online course "Web Design". Conclusions. Actions to optimize the course structure, recommended by the results of a comprehensive effectiveness assessment, led to an improvement in the quality of the educational process, an increase in the level of material assimilation and an increase in overall student satisfaction.

Background. The relevance of this research is determined by the need to improve the methods of managing complex projects in the military-industrial complex in the face of modern challenges, including geopolitical instability, sanctions pressure and stricter requirements for the implementation of the state defense order. Under the current conditions, traditional approaches to managerial decision-making demonstrate insufficient effectiveness, due to the high degree of uncertainty and the multi-criteria nature of the tasks facing defense industry enterprises. The aim of the research is to develop a scientifically based decision support methodology for optimizing management processes at all stages of the life cycle of creating weapons and military equipment. Matherials and methods. The proposed approach is based on the integration of multicriteria analysis and discrete optimization methods into the decision support system (DSS), which provides comprehensive consideration of technological, resource and time constraints typical of defense industry projects. The methodological basis of the research consists of modern achievements in decision theory, including methods of multi-criteria optimization. Special attention is paid to the development and application of a discrete mathematical apparatus, in particular, the full search method for problems with a limited set of alternatives. The work also uses modern design techniques such as FMEA risk analysis, critical path methods and visualization of project data using Gantt charts. Results. The application of this approach in DSS makes it possible to take into account a set of constraints (resource, time, risk, and production) and find optimal management solutions at various stages of the life cycle of creating IWT samples. The full search method implemented within the framework of the DSS ensures the selection of the best corrective actions even under harsh conditions, which is confirmed by the example of the OCD stage, where the use of weighted estimates and data visualization (Gantt charts) allowed minimizing deviations from the schedule. The proposed methodology increases the validity of decision-making by formalizing the selection process, provides adaptability to changing conditions, and can be integrated into existing project management systems in the defense industry, contributing to their effectiveness. Conclusions. The prospects for further research are related to the integration of artificial intelligence and machine learning methods for predictive analytics in project management. Of particular interest is the development of adaptive decision support systems capable of working in real time and taking into account dynamically changing conditions for the implementation of projects in the military-industrial complex.

Background. The relevance of the research is determined by the growing gap between the long-term nature of the development of complex radio engineering systems and traditional approaches to operational management. This problem is particularly acute in the military-industrial complex, where project life cycles reach 3–5 years, while management systems remain focused on short-term annual planning. This fundamental contradiction leads to systemic crises of manageability, reducing the effectiveness of the implementation of strategically important projects. The aim of the work was to create an adaptive management model capable of overcoming existing limitations through an organic combination of modern management techniques and digital technologies. Materials and methods. In the course of the research, a comprehensive methodological approach was applied, including a historical and evolutionary analysis of management paradigms, a systematic study of project management mechanisms, as well as methods of situational analysis and scenario modeling. Results. A conceptual management model based on a synthesis of situational analysis and a process approach based on modern information technologies is proposed. It is based on the dynamic interaction of three key components: constant monitoring of changing conditions, a flexible decision-making process and a technological management support platform. Conclusions. The findings of the study indicate that the transition to the concept of "management management" opens up new opportunities for defense industry enterprises, allowing not only to minimize existing risks, but also to create sustainable competitive advantages.