Odessa National Polytechnic University

The rapid proliferation of human-computer interaction (HCI) systems, virtual reality (VR), augmented reality (AR), and contactless interfaces has intensified the demand for reliable automated recognition and interpretation of human gestures.A fundamental prerequisite for constructing accurate spatio-temporal gesture recognition models lies in the choice of input data format, as each representation captures different aspects of spatial structure, temporal dynamics, and motion semantics.In this context, the present paper focuses on four principal formats of human motion data used in gesture recognition-RGB video, optical flow, skeleton (pose) models, and keypoint representations-and analyzes how their properties influence downstream deep learning pipelines.Specifically, the study investigates how these formats interact with state-of-the-art spatio-temporal architectures and how they affect performance on a standard benchmark.To this end, we evaluate the suitability of each data format for spatio-temporal analysis within deep learning architectures by comparing their behavior when coupled with representative models on the Jester dataset.Modern deep learning approaches, including 3D Convolutional Neural Networks (3D CNN [1]), hybrid CNN+LSTM architectures, and Transformer-based models [2][3][4], each impose distinct requirements on the input data representation, which in turn affects classification performance and inference speed.Therefore, this work systematically relates specific motion data formats to concrete model families, examining how choices such as RGB versus optical flow or skeleton versus keypoints shape achievable accuracy, latency, and robustness on Jester.A structured comparison of data formats, grounded in empirical results on a common benchmark, is thus essential for selecting an optimal configuration of input representation and model architecture for real-world deployment scenarios.RGB video is the most accessible and widely used data format for gesture recognition.It captures full colour information of each frame in a video sequence and preserves the complete visual context of the scene.RGB video serves as the primary input for architectures such as 3D CNN, which process the data as a spatio-temporal tensor of dimensions (height width time), simultaneously extracting spatial features and temporal patterns through three-dimensional convolutional kernels.When applied

The article is devoted to the analysis of the basic scientific literature of contemporary Ukrainian historians on the struggle of the intelligentsia of the Ukrainian SSR for Ukrainian identity, state independence, and democratic transformations under the pressure of imperial power, in particular, the activities of the generation of the 1960s, i.e. the dissident movement, and national-democratic forces that advocated for the sovereignty and independence of Ukraine at the turn of the 1980s and 1990s. The process of reviewing the factual and scientific base on the topic created by foreign researchers by a professional group of Ukrainian historians is traced, and the ideas and conclusions of foreign scholars that were developed in the works of domestic historians are studied. It is concluded that there are still many aspects of the topic that require in-depth study and generalization for a systematic study of the dynamics of the protest movement of the Ukrainian intelligentsia – from educational activities in the field of national cultural work to the creation of a national-democratic opposition and, ultimately, to clarify how the process of building national protest potential took place. Key aspects include: clarification and analysis of the factors that led to the transformation of the intelligentsia into an influential factor in socio-political life and a subject of political relations; systematization and generalization of information and factual data on the development of the resistance movement of the national-patriotic intelligentsia; determination of the range of cultural and educational work; analysis of various forms of political struggle for human and national rights; analysis and generalization of the socio-political role of the national-patriotic intelligentsia in the decisive period of Ukrainian history that preceded the restoration of state independence, in particular in the processes of national revival, the development of civil society structures, and democratic transformations.

Psychology, Physical Culture, Sports, and Comprehensive Rehabilitation: A Multidisciplinary Approach in the Context of Social Transformations : Scientific monograph. Riga, Latvia : «Baltija Publishing», 2026. 332 p.

A study was conducted to generalize the analysis of the results of previous studies by the authors devoted to assessing the mutual transboundary impact of nuclear power plants of Ukraine and neighboring countries. The main attention was paid to radiation impact in cases of normal operation and possible beyond-design-basis accidents. The distribution of radionuclide concentrations, annual radiation doses and risks to the population for a period of 50 years was performed using the PC COSYMA and HotSpot software packages, taking into account the most adverse meteorological conditions that determine the scale of potential radiation contamination of territories in a transboundary context. The maximum radiation doses for adults on the border of Ukraine do not exceed the permissible dose limits under the conditions of normal operation of NPPs of Ukraine and Europe and in the event of a beyond-design-basis accident.

This article provides a comprehensive analysis of the transformation of regional public administration systems in Ukraine under martial law, focusing on the role of digital technologies and artificial intelligence (AI) as factors in enhancing the adaptability, efficiency, and sustainability of management decisions. It is shown that martial law accelerates destructive processes in infrastructure and destabilizes the socioeconomic environment, leading traditional linear administrative models to lose their managerial capacity and require innovative restructuring. It proposes considering amalgamated territorial communities as self-regulating systems whose development is possible through a combination of strategic planning, regular monitoring, and increased digital capacity. This article analyzes methodological approaches to the interpretation of “sustainable development” and “development,” highlighting their complementary nature and emphasizing the need for reflexive strategizing as a guide for the transition from inertia to qualitative transformation. AI is considered as a technological infrastructure that facilitates the algorithmization of management processes, increased transparency, forecasting of development dynamics, and policy inclusiveness. Key risks are also identified: privacy threats, algorithmic manipulation, unequal access to services, and the dangers of social injustice. Based on empirical data from the Digital Transformation Index (Q1 2025), the strengths and weaknesses of regional and community digitalization are identified: high indicators in public services and digital skills, and gaps in digital infrastructure and the digital economy. Examples of community leaders are highlighted. Practically oriented areas of AI application are presented (analytics, forecasting, GIS, crisis management, healthcare, education, logistics, monitoring and oversight). It is proven that the successful integration of AI into regional governance requires comprehensive coordination between the state, local government, business, and the scientific community, a clear moral and legal framework, investment in digital infrastructure, and improved digital literacy. Strategic approaches to overcoming barriers are proposed: medium-term planning, development of local digital infrastructure, inclusive educational programs, and mechanisms for democratic control over algorithmic decisions.

This paper presents a study of the quality metrics influence on a high-dynamic-range image reconstruction from a single low-dynamic-range image. The paper proposes an integrated quality index formed from weighted objective metrics, namely, the peak signal-to-noise ratio, the structural similarity index, and the correlation coefficient. These metrics are calculated for luminance and color-difference signals. Tables of metric values are provided for six intermediate images corresponding to six different exposures, from underexposed to overexposed. The quality index is calculated for each intermediate image involved in the reconstruction of the high-dynamic-range image. Using the set of quality indices, a probability density function is constructed, and statistical metrics are determined. The proposed method allows to predict the quality of the reconstructed high-dynamic-range image, taking into account the contribution of each intermediate image with different exposure times. Based on the analysis of statistical moments, a conclusion is drawn regarding the possibility of optimizing the number of intermediate images.

Introduction. In the modern business environment, characterized by rapid technological progress and intense competition, the success of enterprises largely depends on the effectiveness of their strategic management systems. Strategic management plays a crucial role in ensuring the long-term sustainability and competitiveness of an organization by aligning its objectives, resources, and market opportunities. The purpose of the paper is to substantiate theoretical and practical approaches to the formation of strategic management mechanisms that enhance enterprise competitiveness. Results. The research presents a comprehensive methodological framework based on analysis, comparison, and generalization. It systematizes the stages of enterprise competitiveness management, including planning, development of management methods, their formalization, and implementation through communication channels. The paper outlines how competitiveness can be improved through innovation, technology adoption, cost optimization, quality enhancement, and the development of unique products and services.The results indicate that strategic management should not only focus on internal organizational processes but also actively respond to external challenges through adaptive strategic planning and forecasting. The proposed adaptation model of strategic management includes four key components: analysis and forecasting, strategic planning, organizational changes, and other supporting methods. The study also identifies practical tools such as strategic partnerships, international expansion, digital transformation, and participation in government programs as effective instruments for increasing competitiveness. Conclusion. Strategic management serves as the foundation for sustainable enterprise development and competitiveness. To remain successful in a rapidly changing market, enterprises must implement adaptive management systems capable of responding to global challenges, technological shifts, and customer expectations.

A translator, or compiler, is a complex software system that converts a program written in a high-level programming language into a sequence of executable instructions. Alongside this core task, it performs error diagnostics, code optimization, and symbol table management, ensuring the correctness and efficiency of translation. The concept of translation, however, extends beyond programming, encompassing transformations between both formal and natural languages.