National Aviation University

This paper reports the design of a methodological toolkit for financial provision of enterprise sustainability, taking into account the target needs of the enterprise's capital management, available opportunities, and digital changes in the business environment. This study considers the processes and mechanisms of financial provision sustainability of enterprises in the context of digital transformations of the economy. The task addressed relates to the lack of effective methodological tools for flexible adaptation to changes under financial conditions and strategic needs for ensuring financial sustainability of enterprises, taking into account the requirements of balanced economic development. Such tools are based on the mechanism of capital structure optimization and make it possible to build the financial architecture of the enterprise and effectively respond to digital challenges. Using the linear programming method, an economic and mathematical model for optimizing the capital structure of the enterprise has been constructed. It includes an objective function that is focused on maximizing profit and minimizing the weighted average cost of capital and makes it possible to determine the rational ratio of the enterprise's equity and debt capital. The system of constraints of the objective function takes into account the policy of financing the assets of the enterprise under the conditions of digital transformations, and covers the criteria of financial stability, solvency, and efficiency of capital use of the enterprise. This makes it possible to ensure the consistency of financial decisions with the strategic goals of the enterprise's development, to increase its resistance to the latest challenges of the digital economy. The practical significance of the designed methodological toolkit is in the possibility of its application for substantiating management decisions, developing financial and economic policy.

Type of the article: Research ArticleAbstract Military and economic turbulence transform the relationships between factors shaping national cyber resilience. This study aims to analyze the impact of technological, institutional, and financial determinants on cyber resilience under armed conflict and post-conflict recovery. The empirical analysis covers neighboring European non-EU countries within the European security space that are exposed to armed conflict or post-conflict instability (Ukraine, Moldova, Georgia, Armenia, Azerbaijan, and Serbia) from 2010 to 2024, using panel data from the World Bank, IMF, and ENISA. Cyber resilience is measured by the Global Cybersecurity Index. Institutional, technological, and financial factors are proxied by standard governance, digitalization, and the financial sector and estimated using a fixed-effects model with Driscoll-Kraay robust standard errors. The results reveal pronounced regime-dependent effects. Institutional capacity plays a decisive role during armed conflict: government effectiveness shows a strong positive association with cyber resilience (β ≈ 1.04) but becomes statistically insignificant in post-conflict and stable environments. Technological factors exhibit context-sensitive effects: digital government development is positively associated with cyber resilience during armed conflict (β ≈ 0.95) and relative stability (β ≈ 1.78), while its impact weakens in post-conflict recovery. Macroeconomic conditions exert systematic influences across regimes: higher unemployment reduces cyber resilience (β ≈ −0.027), whereas inflation shows a positive association (β ≈ 0.008). Financial indicators display mixed and predominantly negative effects under relative stability. Accordingly, cybersecurity policy should be explicitly regime-sensitive: institutional and digital interventions should dominate during armed conflict, while governance and risk-management mechanisms should prevail in post-conflict and stable environments.AcknowledgmentThe authors acknowledge with gratitude the financial support provided by the Ministry of Education and Science of Ukraine for the research project “Modeling mechanisms for countering organized and transnational cybercrime in wartime and post-war times” (state registration number 0124U000550).

The network traffic analysis problem in large companies utilizing Big Data is considered. An ensemble of clustering algorithms based on Bayesian probability updating employing various distance metrics and adaptive weighting is proposed. An exponential dependence was applied in the weight calculation to enhance differentiation between algorithms. This enhanced the method's sensitivity to the quality of individual models. The developed approach was tested on open datasets CIC-IDS2017, UNSW-NB15, and CTU-13. The results demonstrated a consistent improvement in clustering quality, with ARI and NMI values reaching 0.78 and 0.75, respectively. The result surpasses the performance of baseline methods (K-means, DBSCAN, classical ensembles). The proposed method demonstrated linear scalability and is applicable for analyzing high-volume corporate network traffic. The results obtained confirmed the practical value of integration into monitoring and anomaly detection systems.

The paper is devoted to the study of the impact of innovations on increasing the competitiveness of food industry enterprises in the context of increasing market turbulence, increasing resource costs and rapid changes in consumer priorities. The relevance of the topic is due to the need to ensure stable development of the industry and increase the efficiency of the functioning of enterprises, in particular in the confectionery segment, which demonstrates a high dependence on technological changes. The purpose of the paper is to identify areas of innovative renewal and assess their potential for strengthening the market positions of enterprises. The methodology is based on the application of structural and functional analysis, modeling of innovation processes, comparative assessment of technological solutions and logical and analytical interpretation of their impact on production efficiency. The paper established the systemic nature of the relationship between the introduction of innovations and the increase in the efficiency of enterprises; the impact of product renewal, automation, digitalized quality control procedures, resource-efficient technologies and innovative marketing solutions is characterized. A structural model of innovation and resource support is proposed, which describes the mechanisms for increasing the competitiveness of enterprises through the intensity of technological changes, flexibility of production and the ability to quickly adapt. The paper summarizes the factors of formation of innovative activity of enterprises, reveals the features of the impact of innovations on the cost structure, product quality and speed of response to market needs. Prospects for further research relate to deepening the empirical verification of the model and increasing the accuracy of indicators for assessing innovation performance.

The article is dedicated to a new field for Ukraine – the acoustic study of the architectural environment, the semantics of sound, and the impact of sound signals on human behavior in urban spaces. The concept of the soundscape, introduced into scientific discourse in the 1970s by R. Murray Schafer and his followers, is explored. They laid the foundation for and initiated acoustic studies of cities in the context of their auditory pollution. The methodology for studying the urban soundscape developed by them became the basis for contemporary practical work and was tested by students of the National Academy of Fine Arts and Architecture (Kyiv, Ukraine). Their task involved recording changes in the soundscape according to different types of urban spaces and observing human behavior under the influence of sound signals. All research results were visualized on graphic sound maps. The role of sound in perceiving the architectural space of a city is defined in comparison to the significance of sound in cinema. It is noted that, as in cinema, sound in the urban architectural environment has its own functions: illustration; contrast or counterpoint to the visual sequence; communication; synchronization; structuralization. As in films, sounds can emphasize events (e.g., the sound of a theatrical celebration in a city square), maintain tension in transitional spaces (e.g., the sound of a traffic light), warn of danger, obstacles, or threats (e.g., the sound of a siren), act as a dominant element indicating direction (e.g., a clock on a town hall), convey the novelty of a space or its mystery (e.g., unclear, atypical sounds for a given soundscape), and so on. Based on this, it is hypothesized that the architectural environment can be modeled by programming impressions of its perception and influencing people’s behavior within it. Sound is one of the most powerful tools for shaping the perception of architectural space, and sound compositions become an essential component of the sound environment of a modern city, requiring further research and the development of principles for urban sound design. The authors note that the study of the semantics of sound in general and sound signals in particular, as well as their influence on human behavior, is not yet complete but holds great promise for further development of such research on the architectural environment of cities, particularly in Ukraine.

The article presents a method for detecting low-intensity DDoS attacks, focused on identifying difficult-to-detect “low-and-slow” scenarios that remain undetectable by traditional defence systems. The key feature of the developed method is the statistical criteria’s (χ2 and T statistics, energy ratio, reconstruction errors) integration with a combined neural network architecture, including convolutional and transformer blocks coupled with an autoencoder and a calibrated regressor. The developed neural network architecture combines mathematical validity and high sensitivity to weak anomalies with the ability to generate interpretable artefacts that are suitable for subsequent forensic analysis. The developed method implements a multi-layered process, according to which the first level statistically evaluates the flow intensity and interpacket intervals, and the second level processes features using a neural network module, generating an integral blend-score S metric. ROC-AUC and PR-AUC metrics, learning curve analysis, and the estimate of the calibration error (ECE) were used for validation. Experimental results demonstrated the superiority of the proposed method over existing approaches, as the achieved values of ROC-AUC and PR-AUC were 0.80 and 0.866, respectively, with an ECE level of 0.04, indicating a high accuracy of attack detection. The study’s contribution lies in a method combining statistical and neural network analysis development, as well as in ensuring the evidentiary value of the results through the generation of structured incident reports (PCAP slices, time windows, cryptographic hashes). The obtained results expand the toolkit for cyber-attack analysis and open up prospects for the methods’ practical application in monitoring systems and law enforcement agencies.

Modern socio-economic transformations in Ukraine have led to radical changes in higher education, serving as a basis for generating new knowledge and training highly qualified personnel. At the same time, market economic conditions significantly affect the processes of formation and use of financial resources of higher education institutions. The purpose of this study is to deepen the theoretical foundations and develop practical recommendations regarding the adaptive-selective type of financing of higher education institutions in overcoming sustainable development disparities. It is argued that financing is the process of providing the subjects of all institutional sectors of the economy, including types of economic activity (in particular education) and their institutions, with the necessary monetary resources. The work systematizes the sources of formation of financial resources of higher education institutions in overcoming sustainable development disparities, and also defines external (economic and political state of the country; scientific, technical and informational environment; external economic environment; natural and ecological environment) and internal influencing factors (material and the technical base of institutions of higher education; the volume of state orders for the training of specialists; fees for educational and other services) for the formation of financial resources in institutions of higher education. Conceptual approaches to improving the financing mechanism of higher education in Ukraine to overcome sustainable development disparities are justified, which will take into account the need to rethink the theoretical and methodological foundations of the influence of higher education on the development of the national economy. The implementation of the proposed recommendations will contribute to strengthening the influence of the adaptive-selective type of financing of higher education institutions in overcoming disparities in development on the activation of educational activities in Ukraine.

The paper provides a comprehensive analysis of financial restructuring, focusing on its core principles, primary strategies, and the key challenges faced during wartime conditions. Particular emphasis is placed on issues such as reduced economic activity, heightened financial pressures, and the growing risk of corporate bankruptcy – all of which become critically significant in the context of armed conflict. Additionally, unresolved issues such as socioeconomic inequality and instability within the banking system are discussed in detail. The authors highlight the importance of financial restructuring as an effective tool for addressing economic challenges and ensuring stability during times of crisis. The study offers an in-depth exploration of strategy development for financial restructuring, prioritizing pressing issues and presenting practical approaches to enhance reforms in the financial sector. Overall, the research aims to bolster economic resilience and ensure the stable operation of Ukraine’s financial system amid geopolitical tensions. The topic of financial restructuring is particularly relevant for Ukraine due to the urgent need to adapt to new realities and establish pathways for strengthening the financial system. The paper identifies opportunities to improve this process by integrating modern technologies and optimizing regulatory mechanisms. Special attention is drawn to the need for further research into how wartime conditions impact financial markets, as such studies could foster innovative strategies to maintain economic resilience in times of uncertainty. The effective efforts of the National Bank of Ukraine have helped maintain stability and ensure the functionality of the banking sector under demanding circumstances. The study emphasizes that increased lending activity by banks is a decisive factor in achieving economic stability during a crisis. In this context, particular importance is placed on examining issues related to bank lending as a foundational element for shaping strategies aimed at fostering economic growth.

This scientific work is dedicated to the development of an intelligent system for diagnosing vestibular schwannoma. A new approach to texture analysis of magnetic resonance imaging images of schwanomas has been proposed as a method for assessing the growth of swelling. The use of this approach will help to avoid the risks of the progression of the neoplasm and immediately eliminate the need for surgical intervention. At the boundaries of the research, a number of classes of texture descriptors were put together, including: first-order statistics (intensity histograms), grey-color consistency matrix, dovzhin sequence matrix Gray Rivne, zone size matrix, Gray Rivn deposit matrix, as well as hvillet-transformed signs. The comprehensive analysis of these descriptors made it possible to formalize the internal microstructure of the fluff and implement an effective model for predicting its growth.