Systems and Technologies

NEURAL NETWORK MODEL FOR PREDICTING RISK LEVEL OF IMPLANTATION TREATMENT IN PATIENTS WITH GASTROESOPHAGEAL JUNCTION PATHOLOGY

O. I. Halushko — Tue, 30 Dec 2025 00:00:00 +0200

The article presents a mathematical model for predicting the risk level of potential therapeutic device implantation in patients with gastroesophageal junction pathology, based on a multilayer perceptron (MLP) artificial neural network. The model integrates 15 clinical, endoscopic, and morphometric indicators reflecting both the functional state of the esophagus and struc- tural changes in the mucosa. The model was developed using a dataset of 558 observations (401 for training, 157 for testing), ensuring a statistically reliable assessment of its predictive performance. The network architecture includes an input layer with 50 parameters (after variable encoding), a single hidden layer with 7 neurons, and an output layer with 5 nodes corresponding to risk levels (0–4). Training was performed using the backpropaga- tion algorithm with the Scaled Conjugate Gradient optimizer. The model demonstrated extremely high classification accuracy – 99.8 % for the training set and 99.4 % for the test set, with the area under the ROC curves (AUC) for each class equal to 1. Such stability indicates the absence of overfitting and high generalization ability of the model. The greatest contribution to the prediction comes from morphometric parameters characterizing the degree of gastric prolapse into the esophagus, diaphragmatic constriction indices, and the position of the Z-line, as well as endoscopic features of mucosal damage, including the presence of erosions and ulcers covered with hematin. The results demonstrate the potential of the neural network approach for automated patient stratification by risk level and informed selection of interventional strategies (including the implantation of Bravo, JSPH-1, BEST Capsule, EndoStim systems, etc.). The proposed model could serve as a foundation for the development of an intelligent clinical decision support system, improving diagnostic accuracy, enabling personalized treatment, and reducing the risks of unjustified invasive interventions in gastroenterological practice.

ANALYTICAL BOUNDS ON THE TOPOLOGICAL STABILITY OF DYNAMICAL SYSTEMS UNDER NOISE AND STRUCTURAL ANOMALIES

S. V. Yershov, Ye. D. Symonov — Tue, 30 Dec 2025 00:00:00 +0200

The paper develops a generalized analytical model for determining the bounds of topological stability of dynamical systems under noise and structural anomalies. Topological stability is interpreted as the invariance of the qualitative type of dynamics– preservation of the Conley index, Morse decomposition, and the homological class of the attractor–under stochastic and discrete structural perturbations that modify the geometry and connectivity of system components. Unlike classical approaches based on local metric stability, the proposed methodology integrates the operator formalism of evolutionary flows, the spectral analysis of the semigroup generator, and topological–statistical invariants. The core of the method is the representation of stochastic and structural effects as parametric perturbations of the system, which enables tracing the continuity of the generator spectrum and deriving the analytical conditions for the preservation of topological invariants. An integral functional of topological stiffness is introduced as a quantitative measure of the mean structural change of the attractor; its behavior determines the threshold condi- tions for the loss of stability and delineates the invariance domain of the system. Analytical relations are derived that define the region of analytical stability–the set of noise intensities, correlation times, and depths and ranks of structural defects–within which the probability of changing the topological invariant does not exceed a prescribed level. Numerical testing confirms the adequacy of the model: analytical bounds are consistent with empirical results obtained through topological data analysis using persistence diagrams. It is shown that in the low-perturbation regime the empirical boundary is nearly identical to the analytical one, while deviations in the transition zone remain within the expected stochastic uncertainty. The results demonstrate the effectiveness of the proposed approach for quantitative prediction of the onset of topological instability and for assessing the stability margin in reaction–diffusion, networked, neurodynamic, and controlled technical systems. The methodology is universal, reproducible, and can be integrated into adaptive control modules of complex systems operating under uncertainty and noisy environments.

MATHEMATICAL MODELING OF CARGO DELIVERY OVER LONG DISTANCES USING LIGHT SAILS

S. I. Zhyr, A. I. Kuzmenko, B. O. Gavrilov, V. O. Shapovalov — Tue, 30 Dec 2025 00:00:00 +0200

The article examines the prospects of using light sail technology for the delivery of cargo and satellites over long distances in outer space. The physical principles of the light and laser sail, based on the pressure of light created by the flow of photons, are considered. An analysis of the current state of development in this field, including real missions (NASA Cosmos-1, LightSail, JAXA IKAROS), was conducted, as well as the technical and economic challenges of implementing this technology in practical space missions were studied. The purpose of the research is mathematical modeling of the process of acceleration of the satellite with the help of pho- tons, determination of the main limitations and ways of increasing the efficiency of light sails. The article examines the features of sail design and materials for their manufacture (polyamide, graphene, and metallized coatings), as well as ways to reduce their weight without losing reflectivity. Mathematical dependences for determining the pressure of light, traction, acceleration of the device, time and energy consumption to achieve a speed of 0.1c are given. It is shown that with a total laser power of 100 MW, a 2 kg satellite can reach this speed in approximately 1045 days, and the required energy is ≈2.5 TWh. Special attention is paid to the economic aspects of the project: the cost of energy consumption, the construction of laser installations, the expediency of launching small satellites (nano-satellites) instead of large devices. Options for braking the interstellar vehicle and the possibility of creating mirror systems to reflect the laser beam from the opposite side of the trajectory are considered. The potential risks associated with dust and micrometeorites in space were analyzed and alternative solutions for the protection of the device were proposed, including the use of dispersive lenses instead of armor. Also presented is the concept of using heat from laser radiation to power ion engines that can perform trajectory correction. The study concluded that the technology of light sails can become the basis for the creation of interplanetary and interstellar transport systems. Under the condition of large-scale support, development of laser infrastructure and materials science, the formation of cosmic light highways for cargo transportation and scientific missions becomes possible. The technology combines environmental friendliness, low fuel consumption and high speed potential, which makes it one of the most promising areas of modern space logistics.

SYNERGETIC APPLICATION OF ANSYS AND MATLAB FOR MODELING THE CONTACT INTERACTION OF A COMPLEX-SHAPED STAMP WITH AN ELASTIC HALF-SPACE

T. A. Zaytseva, Ya. A. Honcharov — Tue, 30 Dec 2025 00:00:00 +0200

An integrated methodology for numerical modeling of the contact interaction between a perfectly rigid punch of complex geometry and an isotropic elastic half-space is presented, based on the synergistic use of ANSYS and MATLAB. The approach treats the contact region as a doubly connected ring (annular domain) whose inner and outer boundaries are described by concen- tric curves, thereby capturing geometric features that strongly influence local stress fields. A finite-element model was constructed in ANSYS with due account of the intricate geometry, boundary conditions, and loading schemes; this enabled the computation of a detailed distribution of contact stresses and displacements under prescribed indentation scenarios. A systematic sensitivity analysis with respect to mesh density, local refinement near anticipated singular zones, and interpolation settings was performed, leading to practical convergence criteria and stable error tolerances suitable for repeated studies. Special attention was paid to adaptive discretization of the contact zone so as to ensure numerical convergence, suppress spurious oscillations, and improve the accuracy of peak-stress estimation along the edges of the active contact. Upon completion of the simulation, the computed fields were exported to MATLAB, where a dedicated post-processing pipeline was implemented to provide consistent graphical interpre- tation and quantitative comparison. In particular, masking outside the physically realized contact patch was applied to eliminate non-physical interpolation artifacts and to isolate the effective load-transfer area for analysis. The toolkit supports the generation of contour maps of contact pressure, 3D visualizations of the stress–strain state, and targeted diagnostics of edge effects, including the localization and ranking of stress concentration zones. The use of MATLAB also facilitates the identification of local features in the pressure distribution and regions of reduced contact interaction, and it enables structured parametric comparisons across multiple geometric variants and loading levels using a uniform set of metrics. Overall, the proposed methodology spans the full computational cycle–from geometric modeling and robust finite-element solution to standardized interpretation and reporting of results–and is designed to be scalable and amenable to scripting and automation for batch studies. The resulting datasets and visual products can be directly used for verification and validation of models, optimization of design parameters, and the development of applied engineering practices for contact mechanics problems, particularly in settings with complex interaction geometries and pronounced stress gradients where reliable resolution of edge behavior is essential.

METHODS FOR ANALYZING INDIVIDUAL BLOOD PRESSURE MEASUREMENTS: TRENDS, SEASONALITY, AND FORECASTING

T. Zh. Nadryhailo, M. V. Peremitko — Tue, 30 Dec 2025 00:00:00 +0200

The article investigates an approach to analyzing individual daily blood pressure measurements with the aim of identifying long-term trends, periodic fluctuations, and forecasting possible future changes. The study explores the use of linear regression, STL decomposition, and the ARIMA, SARIMA, and Holt-Winters models for analyzing blood pressure as a time series. The application of these methods made it possible to assess changes in a patient’s physiological parameters and to determine regularities in the dynamics of blood pressure. The analysis was conducted on data obtained from long-term home monitoring of a 67-year-old patient diagnosed with atherosclerosis. Linear regression was found to be effective in identifying baseline long-term trends that reflect gradual changes in the average blood pressure level. The STL decomposition method allows for the visualization of the time series structure and the separation of trend, seasonal, and residual components, providing a clearer understanding of the underlying patterns. The results of the study showed that the Holt-Winters model provides the highest forecasting accuracy for both systolic and diastolic blood pressure in cases where seasonal fluctuations are absent or weakly expressed. Conversely, the SARIMA model demonstrated better performance when the data contained pronounced periodic patterns, while ARIMA was found to be most appropriate as a baseline approach for assessing general trends without emphasizing seasonal influences. To quantitatively evaluate the accuracy of the models, standard statistical metrics – Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) – were employed. The comparative analysis of these metrics confirmed the importance of accounting for seasonality when building predictive models of physiological processes. The study highlights the potential of time series analysis methods for use in personalized medical analytics. It demonstrates that these methods can effectively reveal the dynamics and variability of an individual’s cardiovascular parameters, enabling a more nuanced understanding of personal health trajectories. However, the research also indicates that the reliability and accuracy of such models significantly depend on the quantity and duration of collected data. For reliable short-term forecasting, a dataset containing at least one hundred observations is recommended, while more extensive time series are required for identifying stable long-term trends and seasonal cycles. Furthermore, integrating additional physiological and environmental parameters – such as heart rate variability, physical activity, stress levels, and ambient temperature – into forecasting models could significantly enhance their precision and adaptability. These factors may influence blood pressure fluctuations and thus should be incorporated into future predictive frameworks. The study concludes that comprehensive, long-term monitoring combined with advanced time series modeling can serve as a foundation for developing precise individualized risk profiles that reflect the true dynamics of a patient’s physiological condition and support data-driven medical decision-making.

MATHEMATICAL MODEL AND OPTIMIZATION OF PARAMETERS OF AND PNEUMATIC ROTARY PISTON ENGINE

A. M. Pasichnyk, T. Zh. Nadryhailo — Tue, 30 Dec 2025 00:00:00 +0200

A special role in the organization of modern production is played by the use of small-scale mechanization, in particular manual mechanized tools that allow to significantly increase productivity, reduce the need for labor and improve working con- ditions. Pneumatic engines have become the most widely used drive in such tools, which is explained by the high level of their operational safety and reliability. At the same time, the most common rotary vane engines have certain disadvantages: low effi- ciency, rapid wear of working blades, which leads to an increase in inefficient consumption of compressed air and a reduction in service life. There are also problems with increased noise levels, high air consumption and excessive vibration exceeding sanitary standards. To solve these problems, a fundamentally new pneumatic rotary-piston engine has been proposed, the design of which does not have blades separating the working chambers, which ensures an increase in the efficiency of its technical and economic characteristics and a reduction in noise and vibrations. Accordingly, the development of methods for calculating and optimizing the parameters of such an engine is of great importance. This paper presents a mathematical model of the functioning of a pneumatic rotary-piston engine and the results of opti- mizing its technical characteristics based on gas-dynamic calculations. According to the results of the optimization of the engine torque, it was established that to ensure smooth rotation of its shaft, it is necessary to use designs with three working chambers offset along the circumference by 2/3π. Calculations of the main parameters and their optimization are carried out for the given dimensions, power and speed of the pneumatic engine. The relevance of the topic of the presented research is due to the growing need for cost-effective and environmentally friendly technical solutions in mechanical engineering and other areas of industry, since reducing energy consumption and increasing the efficiency of production processes are priority tasks of modern technology.

ADAPTIVE STRATEGIES OF TEACHING AND ASSESSMENT IN WARTIME CONDITIONS

I. A. Safronova, S. I. Zhyr, O. V. Verba, G. A. Shyshkanova — Tue, 30 Dec 2025 00:00:00 +0200

The modern system of higher education in Ukraine has faced unprecedented challenges due to the war. Traditional pedagogical approaches to teaching and assessment have proven ineffective amid constant psychological stress, technical disruptions, and large student cohorts. This creates an excessive workload for lecturers, making an individual approach nearly impossible. The widespread failure to meet deadlines leads to a chaotic verification process and devalues traditional control mechanisms. The purpose of this work is to analyze these problems and develop adaptive approaches to organizing the educational process that will help maintain the quality of education while minimizing the workload on lecturers. The paper proposes a rethinking of task design. Instead of a large number of lengthy assignments, it suggests focusing on 2-3 key, process-oriented tasks per semester that require knowledge integration. The importance of using group projects is also emphasized. Special attention is paid to adapting the feedback and assessment system. Instead of individual comments, minimalist and scalable feedback (e.g., a "traffic light" system, templates, general seminars) is proposed. It also considers combined verification methods that integrate automated tests with elements to prevent academic dishonesty and the misuse of AI, as well as selective oral interviews. The work also highlights the importance of fostering students' intrinsic motivation through projects with real-world application. It emphasizes the need for systematic psychological and methodological support for lecturers from the university administration, including adapting assessment requirements and providing access to modern digital tools. The conclusions underscore that the proposed solutions are effective, compromise-based strategies that help maintain the quality of education and academic integrity while minimizing the risk of professional burnout in unpredictable conditions. The results can serve as a basis for developing practical recommendations for higher education institutions operating in a crisis.

MULTILAYER MICROSERVICE-AGENT ARCHITECTURE OF A PERSONALIZED LEARNING SYSTEM

N. G. Axak, A. О. Tatarnykov — Tue, 30 Dec 2025 00:00:00 +0200

The goal of this work is to develop a multi-layered microservice-agent architecture for implementing personalized learning based on the use of behavioral data with an integrated computer vision module (SBMS–LMS), which ensures the adaptability of the learning process and the ability to automatically track various student activities. The methodological basis is a combination of the principles of multi-agent systems, microservice architecture, sensory behavioral analytics, and formal security verification in temporal logic. The architecture implements a seven-level model that includes a sensor layer (SBMS), analytical services (Learning Analytics, Adaptive Learning), agent orchestration (MAS), and integration with the widely used LMS Moodle via REST API technology. The system allows for the collection of behavioral signals (student attendance, attention in lectures, disciplinary violations, and use of control system bypasses), students activity and full performance analytics, the formation of recommendations for students, and real-time feedback, which allows students to influence the learning process and improve its quality. The security module guarantees authentication, encryption, and fully anonymization of users data in accordance with GDPR/FERPA standartisation policies. The scientific novelty lies in the creation of a unified, standardized cognitive-analytical circuit that combines agent-based decision-making logic, stream analytics of behavioral data, and the microservice capability to break down educational service functions into independent modules, which in turn increases fault tolerance and protection against full access to the system by a potential attacker. The work results obtained in the course of the research confirm in real practice the effectiveness of SBMS integration with LMS Moodle and the ability of the created system to dynamically adapt current learning trajectories, improving the quality of learning and improve personalization level of education.

METHOD FOR CLASSIFYING DOCUMENTS ACCORDING TO THE COMPLEXITY OF DATA EXTRACTION BY LARGE LANGUAGE MODELS

O. Yu Bozhko — Tue, 30 Dec 2025 00:00:00 +0200

The article addresses the urgent problem of optimizing automated data extraction from business documents using large language models (LLM). The quality of processing documents varies significantly depending on their structural and semantic characteristics. The absence of methods for predicting extraction quality leads to inefficient resource utilization. Existing document classification research focuses on thematic categorization rather than assessing the technical complexity of data extraction. To address this problem, a method for classifying documents based on the complexity of their processing by language models is proposed. The method is based on document markup using binary features of structural-semantic complexity. For each document, automatic data extraction is performed by three language models in zero-shot mode, with calculation of an integral quality metric through the harmonic mean of precision and recall. Based on these metrics, complexity classes are formed, followed by construction of classifiers using multiclass logistic regression. Validation is performed through stratified cross-validation. The key feature of the method is the ability to automatically determine the expected quality of document processing based on its formalized characteristics. The method was tested on a corpus of synthetic documents with varied complexity characteristics. For three LLMs, three-level complexity classifiers were built. Analysis of weight coefficients revealed critical complexity factors that demonstrate the greatest negative impact on extraction quality. The proposed solution has both theoretical and practical significance. The scientific novelty lies in creating the first empirically validated method for classifying documents where the target variable is the expected quality of data extraction by language models. The practical value is the possibility of automated decision-making regarding processing strategy in production systems. The results create a methodological foundation for developing intelligent document processing systems and optimizing computational resource utilization.

AUTOMATION OF SERVERLESS APPLICATION DEPLOYMENT USING IAC: CASE OF 'AGRO MONITOR'

O. F. Bulhakova, V. V. Kostenko, D. S. Bulhakov — Tue, 30 Dec 2025 00:00:00 +0200

The article presents the results of research and practical implementation of serverless application deployment automation based on the Infrastructure as Code (IaC) concept. The primary focus is placed on analyzing modern tools and technologies that enable automated infrastructure management in cloud environments, as well as the deployment of serverless applications using IaC in a real-world project. The first part of the article examines the theoretical foundations of serverless architecture, which allows companies to reduce infrastructure maintenance costs, ensure automatic scaling, and pay only for the actual use of computing resources. The advantages and challenges of adopting the serverless approach are analyzed, including component interaction issues, version control, integration complexity, and security concerns. Particular attention is given to Function-as-a-Service (FaaS) platforms such as AWS Lambda, Azure Functions, Google Cloud Functions, and OpenFaaS. The article thoroughly investigates the role of Infrastructure as Code in the context of automating the deployment of serverless solutions. Two primary approaches to infrastructure description are considered-declarative declarative (Terraform, AWS CloudFormation) and imperative (Pulumi), and configuration-management tools (Ansible) – with an overview of their characteristics, benefits, and limitations. The key advantages of IaC for ensuring standardization, infrastructure reproducibility, CI/CD process integration, version control, and enhanced system security are highlighted. The practical section of the article focuses on the deployment automation of the «Agro Monitor» system, which is built on serverless architecture in the Microsoft Azure cloud environment. The Pulumi tool, which enables infrastructure definition using programming languages and provides flexibility in creating complex infrastructure scenarios, is applied. The system architecture, key components, API-based interaction mechanisms, as well as processes for automatic scaling, data processing, and report generation are described in detail. It is demonstrated that the proposed approach enables rapid deployment of new environments, reduces maintenance costs, enhances system stability, and improves scalability. The results confirm the effectiveness of combining serverless architecture and Infrastructure as Code for developing modern information systems characterized by high flexibility, stability, and economic feasibility. The developed solution can be beneficial for enterprises in various industries seeking to optimize infrastructure and accelerate the deployment of innovative IT products.

REVIEW AND SYNTHESIS OF VIRTUALIZATION IMPLEMENTATION PRACTICES IN IT PROFESSIONAL TRAINING

O. F. Bulhakova — Tue, 30 Dec 2025 00:00:00 +0200

The digital transformation of contemporary society has fundamentally reshaped the requirements and approaches to education in the field of information technology. This article demonstrates how virtualization technologies transform professional preparation by aligning technical solutions with pedagogically grounded approaches. It examines the capabilities of virtual machines, containerization, software-defined networking (SDN), storage virtualization, and cloud-based remote laboratories for safe and reproducible modeling of instructional environments. The aim is to show how these technologies strengthen hands-on training, optimize costs, expand access, and align learning outcomes with employer expectations. The study presents a review of recent publications and an analysis of typical deployment architectures. It shows that isolation, compatibility, and repeatability enable students to practice complex scenarios safely and accelerate the acquisition of practical skills. At the same time, the study identifies constraints: requirements for network and compute resources, performance overhead in resource-intensive tasks, the need for targeted faculty development, and risks of reduced motivation and interaction in fully online settings. Practical guidelines are proposed, including phased implementation with standardized virtual machine images, development of learner support services, integration of assessment tools, and partnerships with companies for project-based learning. The paper outlines prospects for using artificial intelligence for personalized tutoring, edge computing to reduce latency, extended reality (XR) for intuitive three-dimensional interfaces, and cloud-native and serverless approaches that accelerate scaling and simplify the operation of educational infrastructure. The proposed solutions help reconcile instructional quality, scalability, and cost-effectiveness and increase graduates’ readiness for contemporary professional challenges.

NEURAL-DRIVEN HYBRID METHOD FOR OPTIMAL AREA COVERAGE WITH PLACEMENT CONSTRAINTS

Ye. А. Havryliuk — Tue, 30 Dec 2025 00:00:00 +0200

The article proposes a novel methodology for addressing the Maximum Coverage Location Problem (MCLP) in continuous spaces, incorporating arbitrarily shaped objects, their rotation, and restricted zones for object centers. The problem is formulated as a nonlinear optimization task, where constraints are enforced through a dynamically tuned penalty function driven by a neural network. To enhance computational efficiency, a surrogate neural network approximates the computationally intensive objective function, significantly reducing processing time. The proposed hybrid evaluation strategy integrates precise geometric computations using the Shapely library with Monte Carlo approximations, achieving an optimal balance between accuracy and computational speed. Swarm intelligence algorithms, such as Particle Swarm Optimization (PSO), and memetic algorithms, which combine global exploration with local refinement, are employed to navigate the high-dimensional, multi-extremal solution space effectively. The adaptive penalty mechanism, powered by a neural network, enables automatic adjustment of constraint parameters, eliminating the need for manual tuning and enhancing the robustness of the method across varying problem conditions. This approach proves highly effective for complex geometric configurations, where traditional optimization techniques struggle due to the multi-extremal nature of the objective function and placement constraints. The method is scalable and adaptable to diverse object shapes and restricted zone configurations, making it suitable for practical applications in multiple domains, including telecommunications (e.g., optimal placement of base stations), healthcare (e.g., deployment of mobile medical units in crisis scenarios), ecology (e.g., sensor placement for environmental monitoring), and urban planning (e.g., infrastructure design with restricted access zones). The integration of neural network-based adaptive penalties with geometric optimization provides a robust and efficient framework for solving real-world coverage problems. Future prospects include real-time optimization integration with geographic information systems, further refinement through deep neural networks with active learning, and expansion to dynamic environments with time-varying constraints. This approach advances the state-of-the-art in AI-driven optimization, offering a versatile and reliable solution for complex spatial planning challenges.

ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN RECRUITING AND STAFF MANAGEMENT SYSTEMS

О. М. Haitan, V. E. Bublii — Tue, 30 Dec 2025 00:00:00 +0200

The article examines modern approaches to the use of artificial intelligence (AI) in recruitment and staff development processes under the conditions of business digital transformation. Theoretical foundations and practical tools for the automation of HR processes are analyzed, focusing on the integration of intelligent technologies into recruitment, evaluation, and employee retention systems. Special attention is paid to augmented writing technologies for generating job descriptions that enhance linguistic relevance and gender neutrality, as well as to automated candidate profiling in social networks, intelligent resume scanners, chatbots, and AI-based preliminary testing systems. The study provides a detailed analysis of machine learn- ing and natural language processing algorithms, including BERT, GPT, and T5 models, which enable semantic analysis and classification of candidate profiles, as well as predictive models for assessing employee success. The typical stages of data processing are examined, including the creation of embeddings (vector representations) of candidate profiles and the use of vector databases for semantic matching, particularly Milvus, Pinecone, and Weaviate, which ensure context-aware candidate search and ranking. Mechanisms for integrating such models into automated recruitment systems, performance evaluation tools, and employee success prediction frameworks are discussed. The paper analyzes performance metrics such as accuracy, precision, recall, and F1-score, used for quantitative measurement of HR analytics effectiveness. It is demonstrated that the integration of intelligent technologies can reduce recruitment time by 40–60%, increase selection accuracy by 25–30%, and lower bias in decision-making processes. Ethical challenges associated with AI use are also outlined, including algorithmic discrimination, model opacity, data privacy risks, and data access limitations. The study proposes approaches to ensuring transparency and fairness of AI-driven systems through Explainable AI methods and compliance with GDPR principles. The findings have practical significance for HR technology developers, analysts, and resource managers implementing intelligent automation systems in recruitment and staff management processes.

FORMULATION OF THE INTENTIONALLY GAPPED PROBLEMS FOR AI-LITERATE LEARNING IN HIGHER EDUCATION

H. А. Dobrovolskyi, S. A. Sgadov — Tue, 30 Dec 2025 00:00:00 +0200

This case study proposes and evaluates a pedagogy for integrating generative AI into software engineering students' work by turning known model limitations–hallucination, confident completion, and gap-repair–into structured learning opportunities. Building on evidence that large language models tend to produce fluent but unverifiable answers, the method reframes assessment as a sequence of activities that require higher-order thinking, process transparency, and oral defense. An instructor begins with a «seed» programming task and either diagnoses its ambiguities or deliberately introduces controlled gaps to create a hands-on problem that is underspecified by design. Students then pursue one of two routes: consult an LLM to obtain an initial solution or independently analyze the prompt to surface missing constraints. In both cases, they must request clarifications, revise the specification, and substantiate design choices through tests and justifications. Assessment weights the quality of clarification requests, identification and explanation of ambiguities, correctness and coherence of the final solution, and conceptual mastery demonstrated in a brief viva that probes reasoning rather than code mechanics. An example–the classic factorial table in C#–illustrates how underspecification (range, data type limits, error policy, output format, and purity) predictably elicits plausible yet defective LLM outputs (e.g., sentinel values that conflate error modes, mixed I/O and computation, unreliable overflow checks). Contrasting this seed with a fully specified “corrected” version shows that explicit constraints improve uniform grading but reduce opportunities to critique AI assumptions. By contrast, an intentionally gapped version most effectively compels students to interrogate model completions, formulate testable requirements, and defend choices orally. The approach thereby promotes responsible AI use (verification over deference), strengthens academic integrity (process artifacts and viva-based authorship evidence), and targets upper levels of Bloom’s taxonomy (analysis, evalu- ation, and creation). The paper concludes that gapped, critique-centered tasks, coupled with process-oriented submissions and oral assessment, offer a scalable, human-centered pathway for AI-literate computing education, and motivates empirical studies comparing learning and integrity outcomes against conventional, fully specified assignments.

DISTRIBUTED ARTIFICIAL INTELLIGENCE SYSTEM WITH AGENT- ORCHESTRATED ARCHITECTURE

М. М. Korablyov, I. V. Novoseltsev, I. V. Kobzev, O. K. Tkachuk — Tue, 30 Dec 2025 00:00:00 +0200

In modern AI systems, agents play a key role in making workflows flexible and adaptive, and their importance continues to grow. Agents are small components that perform focused tasks and exchange results through clear rules, which makes them useful for building reliable adaptive systems. This paper introduces an Agent-Orchestrated Architecture for adaptive AI systems. It consists of an Orchestrator and Domain Agents working together. The Orchestrator maintains a small plan with guarded steps, applies clear rules when inputs are missing or confidence is low, and records a per-case thread for audit. Domain Agents (models, tools, services) plug in behind stable contracts and handle specialized tasks. As a practical implementation, the architecture is demonstrated through a Melanoma Diagnostic Workflow: one agent gathers structured answers through focused questions and another provides a risk score from images. The Orchestrator combines both signals and applies two thresholds on the score to determine the next action – reassure with a reminder, request one or two follow-ups or a clearer photo, or recommend an in person exam – while logging every decision. The workflow is practical, auditable, and adjustable to local practice without adding complexity. The proposed architecture is applicable to domains where uncertainty and partial information are common, providing a structured way to keep systems safe, explainable, and adaptable. Beyond the medical domain, the approach generalizes to incident response, financial monitoring, and customer support, where adaptability is critical. The contribution lies in combining orchestration, reasoning, and observability as first – class design elements, offering a reproducible framework for building safer and regulation-ready AI systems.

PROCEDURAL GENERATION IN FOUR-DIMENSIONAL SPACE: FROM 4D GRADIENT NOISE TO VISUALIZATION OF QUATERNION FRACTALS

I. O. Novokhatko, N. A. Fedotova — Tue, 30 Dec 2025 00:00:00 +0200

The article offers a comprehensive review of procedural content generation (PCG) methods in four-dimensional (4D) space, which is a relevant direction in modern computer graphics. The theoretical and practical aspects of using the fourth dimension as a tool for creating complex animations and seamless textures are considered. The Euclidean 4D space and its mathematical foundations are formally defined. Unlike 3D, where rotation occurs around an axis, in 4D space it occurs around a plane, which allows for the unique phenomenon of double rotations4. The geometry of 4-polytopes, such as the tesseract, whose boundaries consist of 3D polyhedra, is also studied. Gradient noise algorithms are analyzed in detail, in particular, a comparison of classical Perlin noise with more productive and high-quality simplex noise is carried out. It is shown that the hypercubic Perlin noise mesh leads to undesirable visual artifacts and has a high computational complexity of O(n4), while the simplex noise (O(n2)) uses a more isotropic simplicial mesh. Methods for generating 4D fractal structures, such as the Mandelbrot and Julia sets, using quaternion algebra are investigated. A key property of quaternion algebra is the noncommutativity of multiplication, which allows the generation of complex and asymmetric 4D structures that are not possible in lower dimensions. The generation algorithm is based on an iteration formula, where the Mandelbrot quaternion set is defined as the set of constants C for which the iteration Z Z C n� n 1 � � � � 2 � remains bounded. Since direct perception of 4D objects is impossible, the paper systematizes key visualization techniques: 3D slicing (slices), orthographic and perspective projections, and volumetric rendering using ray marching. Perspective projection creates the well-known "cube-in-cube" effect for the tesseract, giving a sense of depth along the fourth axis. Volumetric rendering using ray marching has been shown to be particularly effective for implicitly specified surfaces, as it uses sign distance functions (SDFs) for photorealistic visualization. The conclusions summarize the current state of the art and outline promising research directions related to hardware acceleration on GPUs and the use of generative models based on AI.

DESIGN AND IMPLEMENTATION OF A CHATBOT FOR PROSPECTIVE STUDENTS

Yu. F. Oleksiichuk — Tue, 30 Dec 2025 00:00:00 +0200

This paper addresses the pressing issue of digitalizing communication processes in higher education, focusing on the development and implementation of an intelligent chat-bot designed to facilitate interaction with prospective students of the Computer Science educational program. In the context of increasing competition among higher education institutions and the growing need to provide year-round informational support for applicants, the study substantiates the feasibility of employing the Telegram messenger as a platform for automated consultation. The paper analyzes the key shortcomings of traditional communication channels with potential applicants, including their temporal and geographical constraints, fragmentation of information across different web resources, and the excessive workload imposed on admission office staff and academic personnel. The software solution was developed using the Java programming language and the Spring Boot framework. The system is designed according to a multilayered architecture that follows the Controller–Service–Repository design pattern, ensuring modularity, scalability, and ease of maintenance. Integration with the Telegram API is achieved through the Telegram Bots library, while data persistence is managed via the Oracle Database management system. The chat-bot's functional capabilities include providing information about the advantages of the educational program and the university, specific admission requirements for school and college graduates, features of studying at different academic levels, current tuition fees, scholarship and grant opportunities, and the option to subscribe to important updates. The request-handling mechanism, based on user session management and dedicated message handlers, enables a multi-stage interaction flow with logical transitions between dialogue states. For administrative management, the system incorporates an interface built with the Swagger library, which provides automatically generated interactive API documentation and supports the execution of test requests directly through a web interface. The results of the research confirm the effectiveness of the proposed approach in addressing current challenges related to the digitalization of higher education. The developed system significantly reduces the workload of administrative personnel, ensures applicants' round-the-clock access to essential information, and improves the overall quality of communication between the university and prospective students.

CONTRACTS AS AN ELEMENT OF QUALITY ASSURANCE OF IT PRODUCTS

I. D. Pogorielovska, A. Yu. Horbovyy, O. V. Hladchenko, T. V. Ratushnyak — Tue, 30 Dec 2025 00:00:00 +0200

The importance of high-quality IT products in the modern digital world is considered; the SQuaRE series of interna- tional standards is analyzed, which defines requirements for the quality of systems and software, for quality measurement and recommendations for evaluating a software product; it is emphasized that ensuring the quality of IT products is not only about quality models, guidelines for evaluating functionality, checking code or testing a product, but also about ensuring high quality of execution of all stages of the product life cycle, starting from the formation of customer requirements and until obtaining the final result; an analysis of studies devoted to the application of contract models in software engineering is performed; the fea- tures of contracts in the IT sector, which are custom or highly specialized, due to the specifics of the subject of the contract, are indicated; the content of the contract, which provides it with the role of a quality control mechanism for IT products, is defined, namely: requirements, quality standards, scope of work and the procedure for calculating its cost, deadlines, criteria for accept- ing results, key performance indicators, formal verification procedures that provide the opportunity to control quality at each stage, change management rules and the responsibility of the parties for breach of obligations, as well as the speed of product development, roles in the team, defect accounting system, backlog clarification sessions, methods for assessing the complexity of task performance; the content characteristics and differences between the Fixed Price, Time&Materials, Dedicated Team contract models and their impact on ensuring the quality of IT project implementation are investigated; conclusions are drawn that when choosing the type of contract model, it is necessary to take into account the specifics of the IT project and the available budget, the number of uncertainties in the project and the willingness to take risk; prospects for further research are outlined – the potential of Smart contracts, which are currently being integrated into various areas of the IT industry.

APPLICATION OF PSEUDO-RANDOM SEQUENCE GENERATORS FOR ENERGY-EFFICIENT CONTROL OF IOT NETWORKS

S. V. Popereshnyak — Tue, 30 Dec 2025 00:00:00 +0200

The paper proposes a novel method for energy-efficient management of wireless IoT networks based on the use of short pseudo-random sequences to coordinate node activity in time. Unlike traditional centralized control schemes, the proposed approach enables decentralized self-organization of the network, where each node independently determines its operation schedule using a local pseudo-random number generator. Such an organization ensures a statistically uniform distribution of active intervals, reduces the number of collisions in the radio channel, optimizes energy consumption, and increases the overall stability of communication within the network. An information model of the pseudo-random sequence generator adapted for low-power microcontrollers has been developed, as well as a local coordination mechanism that allows synchronization of node activity without a central coordinator or global time reference. The proposed state-update algorithm provides flexible adaptation to changes in network topology and traffic conditions. The paper discusses the advantages of stochastic synchronization compared to classical medium access control schemes and outlines the possibilities for integrating the method into existing IoT communication protocols. The practical value of the research lies in the ability to apply the proposed method in a wide range of sensor and monitoring systems without hardware modification. The approach can be effectively implemented in environmental and industrial monitoring networks, agricultural IoT platforms, smart city systems, and autonomous wireless infrastructures. Its application contributes to reducing energy consumption, maintaining reliable data exchange, and extending the lifetime of distributed IoT devices operating under energy constraints.

FORMALIZATION OF AUTOMATED TESTING PROCESSES OF COMPLEX SOFTWARE SYSTEMS BASED ON MULTIAGENT MODELING

D. I. Symonov, I. O. Demenko — Tue, 30 Dec 2025 00:00:00 +0200

The study is devoted to the formalization of automated testing processes for complex software systems operating in dynamic and stochastic environments. It is shown that traditional testing methods based on fixed test scenarios do not ensure sufficient adaptability and scalability as the complexity of modern software increases. The research substantiates the feasibility of applying a multi-agent approach as an effective tool for building intelligent testing systems capable of self-organization, learning, and optimization of defect detection processes. The study performs a system-theoretic analysis of the testing process as a dynamic system composed of multiple autonomous agents interacting with each other and with the testing environment. A generalized formal model of the multi-agent testing process is proposed, which defines the main structural elements: a set of agents, the environment of their interaction, the test scenario space, behavioral policies, and the evaluation function of the obtained results. This approach allows considering testing as an evolutionary process in which agents adapt their strategies based on accumulated experience and feedback, gradually improving the efficiency and completeness of software verification. A graph-based and stochastic model of the test scenario space is developed, taking into account the probability of defect detection, testing cost and duration, coverage degree, and other efficiency attributes. A system of metrics is defined, encompassing both classical measures of testing performance and multi-agent specific parameters such as cooperativity, conflict rate, and convergence speed of agent policies. Algorithms for model correctness verification are described, providing consistency, reach- ability, stability, and adequacy assessment under stochastic disturbances. The obtained results form a theoretical foundation for developing intelligent multi-agent systems of automated testing capable of adaptation and self-organization. The proposed approach enhances the efficiency of the testing process, reduces time and resource costs, and increases software reliability. Future research will focus on developing agent learning mechanisms and integrating the proposed model into CI/CD processes and continuous quality control systems.

VISUALIZATION OF 3D METADOXES USING THREE.JS

O. D. Firsov — Tue, 30 Dec 2025 00:00:00 +0200

The work developed an algorithm and a corresponding application for visualization of a specialized 3D object using the capabilities of the specialized cross-browser library Three.js. The object of the study is the process of creating realistic models of metadocs using theoretical data, which are based on the model of three-vertex metadocs. In the course of the work, options for visualization of 3D modkley metadocs were analyzed with the idea of accessibility for a non-professional user who is a spe- cialist in his subject area, but does not have a sufficient level of programming technologies or does not have the skills to operate specialized software for visualization. The results of the study show that JavaScript with an extension in the form of the Three.js library is a powerful tool for 3D visualization, which, due to its flexibility and browser support capabilities, allows you to create effective and dynamic models of metadocs, which allows you to better understand the dependencies between linguistic objects and transfer the developed constructs to interested parties. The proposed solution can be used to develop educational interactive applications and models that require the integration of real data of arbitrary origin. The identified approaches to organizing the processes of processing and visualization of data for metadocs can be used in the development of virtual metadocs and fractal objects generated by them, taking into account the productivity and realism of the representation. The results obtained can serve as the basis for building more complex models and expanding the functionality of the corresponding applications. Here the question arises of the balance between the complexity of the solution and its accessibility for analysts working in a specific subject area. A separate part of the research was the use of Grok for testing and debugging the application. In this work, artificial intelligence demonstrated the ability to analyze errors detected by the developer in manual mode, and most interestingly, the reworking of the architecture in the case when the detected errors are caused by external factors.

THE ROLE OF GENERATIVE AI IN THE AUTOMATION OF LEGAL DOCUMENT PREPARATION: AN ANALYSIS OF ACCURACY, EFFICIENCY, AND ETHICAL ASPECTS

O. A. Shamov — Tue, 30 Dec 2025 00:00:00 +0200

This article explores the transformative impact of generative artificial intelligence (AI) on legal practice, with a particular focus on the preparation and analysis of legal documents. It examines modern generative AI models, their capabilities, limitations, and the risks associated with their implementation in the legal domain. The aim of the article is to analyze the current state of generative AI applications for automating legal tasks, identify key issues related to the accuracy and reliability of generated content, and propose a hypothetical model to enhance the trustworthiness of AI-generated outcomes. To achieve this, the article sets out the following objectives: to review recent academic research and publications evaluating the effectiveness and precision of large language models (LLMs) in legal tasks; to identify the unresolved issue of factual verification of generated content; and to formulate and justify a hypothesis for improving baseline research results through the implementation of a hybrid architecture. The study employs methods of systems analysis, comparative analysis of empirical studies, synthesis, and modeling. It analyzes foundational research on structured approaches to AI-assisted legal document analysis and the outcomes of comparative tests between LLMs and human legal professionals, highlighting the persistent challenge of factual accuracy in AI-generated content The article proposes a hypothesis that integrating structured prompting techniques with a Retrieval-Augmented Generation (RAG) architecture-leveraging a curated and dynamically updated legal knowledge basecan significantly improve the factual precision and reliability of AI-generated legal documents. This hypothesis is substantiated with a formalized expression and a potential mechanism for implementation and verification. The proposed approach is shown to not only minimize the risk of AI "hallucinations" but also to lay the groundwork for the development of more responsible and ethical tools that augment, rather than replace, the professional competencies of legal practitioners.

INTELLIGENT LOAD BALANCING IN MICROSERVICE ARCHITECTURE

N. G. Axak, Yu. O. Shelikhov — Tue, 30 Dec 2025 00:00:00 +0200

This paper presents an intelligent method for load balancing in microservice architectures that combines parallel (hedged) request routing with the Thompson Sampling Multi-Armed Bandit (MAB) algorithm. The goal is to address tail-latency spikes and performance variability that traditional policies (Round Robin, Least Connections) cannot handle under heterogeneous, bursty workloads. The proposed architecture comprises a YARP-based API Gateway that executes weighted hedging, an AI load balancer (FastAPI) that learns routing probabilities from live telemetry, and a Prometheus–Grafana stack providing continuous feedback for adaptation. The balancer transforms observed metrics (latency percentiles, error rate) into rewards and updates per-replica posteriors via Thompson Sampling, thereby balancing exploration and exploitation while preventing persistent bias toward temporarily fast but unstable instances. We evaluate four strategies–static round-robin (k=1), static hedging (k=2), adaptive MAB hedging (k=2), and adaptive MAB hedging (k=3). Experiments with up to 1,000 concurrent clients show that adaptive hedging with Thompson Sampling reduces P99 latency by ≈65% and the error rate by ≈45% versus baseline, with negligible throughput loss and moderate CPU overhead. Increasing parallelism beyond two replicas yields diminishing returns, confirming that small k is sufficient when combined with probabilistic weighting and strict idempotency. The findings demonstrate that integrating speculative duplication with Bayesian decision-making provides a lightweight, cloud-native path to tail-tolerant performance. The solution is modular and reproducible, and it generalizes to Kubernetes-based deployments and IoT/cyber-physical scenarios where real-time, context-aware coordination and reliability are essential.

AUTOMATED ASSIGNMENT GRADING SYSTEM FOR PROGRAMMING COURSES

T. S. Diachuk, S. Yu. Skrupsky, T. V. Holub — Tue, 30 Dec 2025 00:00:00 +0200

The purpose of the article is to present the results of the development and implementation of an automated assignment grading system designed to help instructors organize a high-quality, objective, and effective educational process in an asynchronous distance learning environment. The relevance of the work is driven by the challenges of distance education in Ukraine, caused first by the COVID-19 pandemic and later by the full-scale war, which demands the implementation of effective, flexible, and secure educational tools capable of functioning in a predominantly asynchronous learning environment. Manual grading of numerous programming assignments creates a significant burden on instructors, leads to delays in providing feedback, and introduces elements of subjectivity into the assessment. An analysis of recent research confirms a global trend toward assessment automation in IT education as a means of increasing efficiency and objectivity. The developed system is a component of a broader educational platform in which assignments for students are already generated individually. The proposed grading architecture is based on the integration of version control and continuous integration tools. The workflow is organized as follows: a student completes an assignment in their repository and creates a Pull Request to merge the changes. This action automatically triggers the verification process (a GitHub Action), which compiles the code and passes it to a validator. The validator generates a large set of test data, executes both the student's code and a reference implementation (described by formalized formulas) on this data, and then compares the results. In case of discrepancies, the system instantly provides the student with an error report, including the specific data set that caused the failure. This allows the instructor to focus not on routine correctness checks, but on analyzing code quality, architecture, and providing meaningful comments. The system is implemented in Kotlin, uses the Gradle build system, and is distributed as a library (a Maven artifact) that students connect to their projects. Approbation was conducted within the «Basics of Programming in Kotlin» course with the participation of 23 students. The implementation of the system proved its effectiveness in saving instructor time, ensuring objective assessment, and increasing student motivation to experiment and independently correct errors, thanks to the instant feedback. Future development of the system includes the integration of modules for assessing code quality.

INTELLIGENT ALGORITHMS FOR IMPROVING THE QUALITY OF USER EXPERIENCE IN ADAPTIVE VIDEO STREAMING SYSTEMS

K. V. Karmazin, J. V. Pisarenko — Tue, 30 Dec 2025 00:00:00 +0200

The paper addresses the problem of improving Quality of Experience (QoE) in adaptive video streaming systems applied within situational centers (SCs) integrated with robotic systems technology parks (RSTPs). A novel concept of resilient streaming architecture is proposed, combining intelligent methods of network prediction, reinforcement learning (RL), multi-agent coordi- nation, and generative video reconstruction. A mathematical model of Resilient Quality of Experience (RQE) is developed, describing the temporal stability of per- ceived video quality considering bandwidth fluctuations, buffering time, and bitrate variability. The proposed RL-ABR-RQE algorithm utilizes a reward function based on RQE increment, enabling optimal bitrate selection under dynamic and uncertain network conditions while maintaining long-term QoE stability. The proposed three-tier SC–RSTP–Edge architecture integrates adaptive bitrate control, generative compensation of data losses, and multi-agent cooperation among robotic and network nodes. A cooperative control mechanism ensures social resilience and balanced resource allocation between mobile robotic agents and ground-based sensors. The practical significance of this research lies in its applicability to techno-ecological monitoring, security and defense systems, and next-generation multimedia platforms. Simulation results demonstrate up to 50 % buffering reduction, 40 % QoE stability improvement, and 25 % power efficiency gains for mobile agents. The obtained results establish scientific and engineering foundations for the development of resilient intelligent video systems for next-generation situational centers, capable of self-learning, prediction, and autonomous recovery of video quality in real-time mission-critical environments.

CLOUD SERVICES IN DISTRIBUTED NETWORK INFRASTRUCTURE

H. H. Kyrychek, R. O. Tseluiko, M. Yu. Tiahunova, V. A. Zhyvohliad — Tue, 30 Dec 2025 00:00:00 +0200

The article considers approaches to implementing cloud services into distributed network infrastructure. An overview of modern platforms (AWS, Microsoft Azure, Google Cloud Platform) and monitoring systems (Prometheus, Grafana) is provided, automation methods and resource scaling algorithms based on events and metrics are described. The main focus is on the implementation and verification of models that ensure dynamic scaling, fault tolerance, and cost optimization. The purpose of the work is to analyze leading cloud platforms, implement and verify a model for managing distributed network infrastructure using cloud services, which provides: centralized monitoring using Prometheus and Grafana; adaptive scaling of resources based on metrics and security of data transmission between local nodes and cloud services. The object of research is the process of integrating cloud technologies into the infrastructure of distributed networks. The subject is software, tools, methods, models for monitoring and managing distributed networks. The authors developed an infrastructure management model using integration with a public cloud. Several load scenarios were simulated and private, public, and hybrid integration models were compared in terms of performance, fault tolerance, and costs. Algorithms for automatic scaling based on Prometheus Alertmanager and AWS Auto Scaling are presented, and a set of practical recommendations for the secure integration of cloud services into distributed networks is proposed. The management system was modeled with the integration of Prometheus and Grafana tools. The results confirm that the integration of cloud solutions and Software-Defined Networking (SDN) methods allows for a significant increase in the performance and resilience of the network infrastructure, which is critical for modern scalable solutions. The results obtained can be used when modernizing corporate network infrastructure to increase its reliability and efficiency. The results showed that as the number of users increases, latency increases, but the system maintains functionality even under peak conditions.

FOUNDATIONS OF INTELLIGENT AGENT DESIGN: FROM ARCHITECTURE TO MATHEMATICAL MODELING

M. V. Кrykhiskyi, Т. O. Vavryk, L. M. Hobyr — Tue, 30 Dec 2025 00:00:00 +0200

Intelligent agents (IA) have become a central topic of modern research in the field of artificial intelligence. They are an important component of modern information technologies used to automate complex tasks such as data processing, decision-making, and adaptive learning. The development of intelligent agents is a complex, multifaceted process that includes the choice of architecture, the development of decision-making algorithms, and integration with the environment. Over the past decades, many new technologies and approaches have emerged that can significantly improve the effectiveness of agents in real-world applications. The article explores the conceptual foundations of intelligent agents, various approaches to their design, and key technologies that allow for the creation of autonomous and adaptive systems. The authors consider the general algorithm of the functioning of an intelligent agent, its main stages and architecture. An overview of the concept of intelligent agents is presented, including their basic properties, models of interaction with the environment and adaptive mechanisms. The main attention is paid to a universal algorithm that can be adapted to various applications in the field of artificial intelligence (AI). The article presents a mathematical basis for describing intelligent agents, which allows modeling their behavior, decision-making and interaction with the environment. The article presents a mathematical basis for describing intelligent agents, which allows modeling their behavior, decision-making and interaction with the environment. The main components of agents, their formalization through theoretical models and corresponding algorithms are considered. The mathematical description of agents is also considered, taking into account their properties, such as adaptability, autonomy and interaction with the environment. Mathematical analysis of intelligent agents is an important and rapidly developing area, covering a wide range of methods and techniques for modeling, analyzing and optimizing the behavior of intelligent agents.

METHOD FOR IMPLEMENTING THE SQUARING OPERATION IN THE RABIN CRYPTOSYSTEM BASED ON THE USE OF THE RESIDUE NUMBER SYSTEM

D. M. Kovalchuk — Tue, 30 Dec 2025 00:00:00 +0200

The article proposes a method for implementing the operation of squaring a number in the Rabin cryptosystem, which increases the speed of arithmetic operations by using the Residue Number System (RNS). The proposed approach is based on the transition from the positional numeral system to RNS, which allows computations to be performed independently for each modulus and enables parallel data processing. Unlike traditional methods that rely on sequential execution of arithmetic operations with large numbers, the use of RNS avoids carry propagation, thereby reducing time complexity. A mathematical model of the process of multiplying two numbers represented in RNS has been developed based on the use of table multiplication coding. This approach takes into account the symmetry properties of table multiplication, allowing the volume of required computations to be reduced to 25% of the full table. Based on this mathematical model, a method for squaring numbers in RNS has been proposed. A comparative analysis showed that the use of the proposed approach provides a significant performance gain: for 32-bit operands, the speedup is 2048 times, and for 64-bit operands, up to 8192 times compared to the positional numeral system. The research results confirm the feasibility of applying the Residue Number System in the Rabin cryptosystem for implementing the squaring operation. The proposed method can be effectively used in high-performance cryptographic systems designed for processing large numerical fields. Further research should focus on developing a universal structure for modular computations in RNS for other asymmetric cryptosystems, as well as creating a hardware implementation of the method to practically evaluate its performance.

ANALYSIS OF SIMULATION RESULTS OF CET- OPERATIONS BASED ON ELEMENTARY FUNCTIONS OF INFORMATION-DRIVEN OPERATIONS

V. M. Rudnytskyi, Ya. V. Tarasenko, N. V. Lada, V. H. Babenko, D. A. Pidlasyi — Tue, 30 Dec 2025 00:00:00 +0200

The article considers the currently relevant task of synthesizing CET operations based on elementary functions of infor- mation-driven operations. The work is devoted to reducing the complexity of generating the maximum number of CET operations based on elementary functions of information-driven operations for low-resource stream ciphers. The work involved modelling CET-operations and obtaining four subgroups of 10 symmetric operations. Any of the subgroups can be used to construct 48 CET-operations that include all 10 operations of that subgroup. An analysis of a computational experiment on modelling CET-operations based on elementary information-driven operations was conducted. The absence of intersection among the synthesized sets of CET-operations was established, based on modifications of CET-operations from different subgroups. Based on the selection of four CET-operations (one from each group), it is possible to synthesize a complete group of CET-operations based on elementary information-driven functions. Such a group includes 192 operations. The paper presents a group of ele- mentary functions of information-driven operations and a subset of symmetric CET-operations based on elementary functions of information-driven operations. The requirements for selecting a base group for constructing a method for synthesizing CET- operations based on elementary functions of information-driven operations are described. The conditions for considering the requirements for CET-operations of the base group are presented. Based on the results of a computational experiment, a method for selecting basic groups of symmetric CET-operations has been developed, which makes it possible to reduce the complexity of generating the maximum number of CET-operations based on elementary information-driven operations for low-resource stream ciphers. The developed method can be applied in low-resource telecommunication systems of both mobile and stationary types. The prospect of further research in this area is the construction of low-resource systems for cryptographic information transformation using CET-operations based on elementary functions of information-driven operations.

OPTIMIZATION OF INTERNATIONAL LOGISTICS FLOWS BASED ON METHODS OF THE THEORY OF DECISION-MAKING IN CONDITIONS OF UNCERTAINTY

A. I. Kuzmenko, A. A. Cherchata, N. V. Khalipova, I. Yu. Lesnikova — Tue, 30 Dec 2025 00:00:00 +0200

The article examines the theoretical and practical aspects of optimizing international logistics flows in conditions of uncertainty in the external environment. The main factors affecting the efficiency of logistics systems on an international scale are identified, including geopolitical instability, exchange rate fluctuations, changes in customs legislation, lack of transport resources and information opacity. Special attention is paid to the application of decision-making theory methods that allow you to reasonably choose the optimal options for actions under conditions of limited or incomplete information. The paper analyzes the possibilities of using the Laplace, Wald, Savage, and Hurwitz criteria to assess the risks and effectiveness of logistics solutions. It is demonstrated how each of these criteria reflects a different level of risk attitude (from pessimistic to optimistic) and can be applied to select a delivery route, supplier, carrier or transportation scheme. The practical task of optimizing international logistics flows in the Dresden-Uzhgorod direction by road, as one of the relevant logistics corridors between the European Union and Ukraine, has been solved. For this purpose, a network graph was developed, corresponding calculations were performed and comparative diagrams were constructed.A generalized risk matrix has been developed, which allows to assess the impact of external factors on the stability of international supplies and to determine the priority directions of management actions. The results of the study confirm that the integration of decision-making methods into the international logistics management process increases its adaptability, helps reduce risks and ensures a balance between costs, time and reliability of supplies. The proposed approach can be used by exporting enterprises, transport and forwarding companies and logistics operators for strategic planning and increasing competitiveness in the world market.

LOGISTICS METHODS FOR MANAGING THE TRANSPORTATION OF HUMANITARIAN CARGO NEAR THE WAR ZONE

M. I. Muzykin, H. I. Nesterenko, S. I. Bibik, О. І. Чубенко — Tue, 30 Dec 2025 00:00:00 +0200

This article analyzes existing logistics systems, identifies problematic aspects of their functioning, and develops practical recommendations for optimizing the transportation of humanitarian cargo. The logistical delivery of humanitarian cargo faces many challenges near the war zone. The authors research the impact of various factors, including security risks for carriers, limited access to transport and infrastructure, adverse weather conditions, and insufficient coordination between different humanitarian organizations and local authorities. The characteristics of cargoes provided to citizens as humanitarian aid are considered, and a means of transport for transporting goods from large warehouses to intermediate storage facilities is selected, and transport routes are developed, taking into account the uncertainty of route selection due to shelling. Simulating the routes for delivering humanitarian aid to frontline settlements has been carried out. The research emphasizes that efficient transportation of humanitarian cargo from central warehouses to frontline areas is a complex but solvable challenge. Transporting cargoes from central warehouses to intermediate ones, developing routes for further transportation to humanitarian aid distribution points, and optimising the transport fleet are the main stages in developing an effective transport and logistics system. Specialised algorithms of linear programming tasks were used to allocate vehicles and minimise costs. In the event of a danger associated with hostilities, the availability of developed alternative routes ensures continuity of supply. Risk probability analysis makes it possible to choose the safest routes.

FROM OCCUPATIONAL SAFETY TO COMPREHENSIVE SECURITY: STRATEGIES FOR INTEGRATING CIVIL DEFENSE INTO CORPORATE MANAGEMENT SYSTEMS

V. G. Pogrebnyak, I. V. Perkun, O. V. Vyshnikina, A. V. Pogrebnyak — Tue, 30 Dec 2025 00:00:00 +0200

The article substantiates an urgent scientific and practical problem that has arisen due to the full-scale war in Ukraine – the fundamental inadequacy of traditional corporate safety management systems in the face of new hybrid threats. It is proven that the classic model, where occupational safety (OS) and civil defense (CD) function as two parallel, weakly integrated sys- tems, is outdated and incapable of providing an adequate level of protection for personnel and assets of enterprises, which have become potential targets for military attacks. Existing occupational safety management systems, built on peacetime standards (e.g., ISO 45001), are focused on preventing unintentional incidents and lack the tools to counter deliberate external impacts. The purpose of the article is to develop scientifically-backed strategies for integrating civil defense functions into corporate occupational safety management systems to create a unified, comprehensive enterprise security model adapted to the conditions of hybrid threats. Based on an analysis of classical concepts (Safety-I, Safety-II, Resilience Engineering) and the legal frame- work of Ukraine, a key gap has been identified – the absence of a holistic model for managing all types of security risks at the corporate level. The scientific novelty of the work lies in the proposal of a conceptual model for an integrated comprehensive security management system (CSMS) for the first time. Unlike existing approaches, this model synthesizes OS and CD into a single management cycle ("analysis – prevention – response – recovery"), based on five key principles: unity of command, pro- activity, total risk orientation (including military risks), human-centricity, and continuity. This approach allows for a transition from the outdated dichotomy of "internal/external threats" to a single management loop for all identified risks, regardless of their origin. The practical significance lies in the development of four groups of specific integration strategies: legal-regulatory (creating a unified Comprehensive Security Regulation), organizational-managerial (forming a single security center), technical-technological (integrating alert and monitoring systems), and socio-psychological (conducting comprehensive training and providing psychological support). The proposed strategies can serve as a roadmap for managers of Ukrainian enterprises to reform existing systems, enhance personnel protection, ensure the resilience of business processes, and save human lives under martial law.

EFFECT OF FRICTION STIR PROCESSING (FSP) ON THE MICROSTRUCTURE AND MECHANICAL PROPERTIES OF ADDITIVELY MANUFACTURED TI-6AL-4V

S. V. Kyrylakha — Tue, 30 Dec 2025 00:00:00 +0200

This study investigates the influence of Friction Stir Processing (FSP) on the microstructure and mechanical properties of additively manufactured Ti-6Al-4V alloy. A hybrid technological route, “additive manufacturing + friction stir welding (AM + FSW),” was employed, involving electron beam melting (EBM) for the fabrication of initial samples, followed by FSP to enhance structural integrity. The research focuses on the detailed characterization of weld zones, including the stir zone (SZ), thermo- mechanically affected zone (TMAZ), and heat-affected zone (HAZ). Microstructural analysis was conducted to evaluate grain orientation, β-phase recrystallization, and deformation gradients, while mechanical testing assessed ultimate tensile strength and plasticity. Comparative analysis with conventional FSW of pure titanium highlighted specific features of additively manufactured Ti-6Al-4V, such as the influence of the initial columnar grain structure and intrinsic melting-induced defects on the formation of a fine-grained SZ and the overall mechanical performance of the joints. Results indicate that optimization of FSP parameters, particularly tool rotational speed and traverse rate, critically affects microstructural homogeneity, defect elimination, and enhancement of mechanical properties. The findings demonstrate that the hybrid AM + FSW route can effectively compensate for typical additive manufacturing defects, improving isotropy, tensile strength, and ductility of structural components. This research provides a scientific basis for the further development and optimization of hybrid manufacturing routes, allowing for the prediction and control of mechanical behavior in high-performance Ti-6Al-4V components intended for aerospace and transport applications. The integration of additive manufacturing with friction stir processing represents a promising strategy to produce reliable, high-quality titanium alloy components with enhanced durability and mechanical resilience.

MATHEMATICAL MODELING OF ENGINEERING PRODUCTION VOLUME DEPENDENCE ON IRON ORE EXTRACTION

N. V. Maiborodina, V. P. Gerasymenko — Tue, 30 Dec 2025 00:00:00 +0200

Engineering is a key and strategically important sector of the Ukrainian economy, despite significant challenges, especially those associated with the full-scale war. This sector possesses considerable production and scientific-technical potential. This article examines the development a mathematical model for forecasting and analyzing the volume realized output of the engineering complex enterprises, based on the volume of iron ore mining in Ukraine. When creating an economic model or forecast, it is not necessary to consider the entire multitude of factors influencing the studied indicator. The key task is the filtering and selection a limited number of factors that exert the highest degree of influence. These dominant factors form the basis for reliable analysis, while the impact of secondary factors can be legitimately omitted. In this work, the volume of iron ore mining was chosen as the dominant factor affecting the volume the realized engineering output. For modeling the dependence realized engineering output volume in Ukraine, statistical data from the State Statistics Service of Ukraine and regression analysis methods were utilized. The model was developed using the Excel spreadsheet processor to automate the construction, analysis, and forecasting process based on the chosen model. The study includes the calculation of confidence intervals for the forecasted values the realized output volume of the Ukrainian engineering complex for the year 2026. To ensure the reliability the obtained forecasted values, the regression line with the highest approximation coefficient was selected. The research fully complies with the requirements of mathematical modeling: from setting the problem and selecting the key indicator to constructing, analyzing the model, and applying the results for forecasting the realized output volume of the Ukrainian engineering complex for 2026.

HYDRO-PULSE PERFORATION OF OIL AND GAS WELLS WITH A POLYMER SOLUTION JET

I. V. Perkun — Tue, 30 Dec 2025 00:00:00 +0200

This paper analyzes the existing intensification method: hydro-abrasive jetting (or hydro-sandblasting perforation). Despite its effectiveness in establishing a reliable hydrodynamic connection between the formation and the wellbore, this method has significant drawbacks. Chief among these are the intense hydro-abrasive wear of pumping equipment and fittings, leading to a decline in the quality of perforation channels due to nozzle erosion, as well as the high resource and energy intensity of the process. As a promising and more advanced alternative, the authors propose the use of a high-velocity polymer solution jet (polyethylene oxide). The key innovative idea of the work is the application of a pulsed, rather than a steady (continuous), mode for delivering the water-polymer jet. The main hypothesis of the research posits that this approach, owing to the unique rheophysical properties of polymers, can significantly enhance the destructive capability of the jet. Theoretical justification and a series of experiments have fully confirmed this hypothesis. Studies of the behavior of polymer solutions under oscillatory flow conditions, which simulate the perforator's operation, revealed the existence of a critical pulsation frequency. It was established that maximum destructive efficiency is achieved when the pulse frequency corresponds to the maximum of the dissipative function. In this mode, the largest portion of the flow's energy is irreversibly dissipated and converted into destructive work. Experiments involving the perforation of a target model (steel, concrete, and rock formation) clearly demonstrated that the pulsed jet creates significantly deeper channels than a steady jet at identical initial pressures. Based on the results obtained, a conceptual solution and design for a new device–the hydro-pulse perforator–were developed. Its novelty lies in the use of a rotating rotor with V-shaped grooves, driven by an integrated hydraulic turbine. As it rotates, the rotor mechanically interrupts the flow of the working fluid to the nozzles, thereby generating powerful hydrodynamic pulses. An important design feature is the capability for axial displacement of the rotor, which allows for the precise adjustment of the pulse shape, duration, and frequency to achieve maximum destructive effect depending on the properties of the rock formation. Thus, the work demonstrates that the transition to a pulsed mode for water-polymer perforation is scientifically justified and highly effective. The proposed hydro-pulse perforator represents an innovative technical solution that meets the 'inventive step' criterion and paves the way for creating an energy-efficient and more productive technology for developing oil and gas formations.

DEVELOPMENT OF A MAGLEV TRAIN’S CARRIAGE’S DYNAMIC’S MODEL CONSTRUCTING ALGORITHM

V. О. Polyakov, S. Yu. Poslavsky — Tue, 30 Dec 2025 00:00:00 +0200

The main requirements for a system dynamics model are: relevance, effectiveness, reliability, cost-effectiveness, systematicity, accessibility for review, and informativeness. To the greatest extent, models obtained using tensor methods meet these requirements. The nature of the problems, in the solution of which it is planned to use the developed methodology, as well as the structure of their object of study, indicate that an aggregate of mechanical and electromagnetic inertial elements that interact through flexible ones can be adopted as its calculation scheme. The aim of the research was to further develop the method of maglev train's motion's tensor modeling using the example of its carriage, taking into account the presence of mechanical and electromagnetic elements which determine its movement. Before being combined into an aggregate, which is accepted as the design scheme of the object under consideration, the supporting elements of this scheme are not connected in any way, their movements are not restricted in any way. After coupling, constraints are imposed on the movements of the elements, which are reflected by the bond equations. The structure of an aggregate is described by its structural matrix. The design scheme of the carriage is an aggregate of ideal inertial elements connected according to a structural matrix. The motions of both a separate support body and their non-conjugated conglomerate are described by tensor equations. To take into account the structure of a wagon's calculation scheme, the equations describing the movements of an unconnected set of support bodies are convoluted with the structural matrix of the unit. The resulting carriage's dynamics model is also tensor and can be easily converted to another coupling structure by convolution with the transition matrix from the previous support body coupling structure to the next. The basis for building a carriage's motion model is the equations describing the dynamics of the supporting bodies, as well as the structural matrix of the unit, which reflects its structure. Such a model meets the requirements of holistic consideration of both the parametric and structural organization of the object under consideration. The developed methodology for its construction can be successfully used when researching such trains dynamics.

PROSPECTS FOR THE DEVELOPMENT OF PASSENGER TRANSPORTATION LOGISTICS INFRASTRUCTURE: ORGANIZATIONAL, TECHNOLOGICAL AND ECONOMIC ASPECTS

N. I. Novalska, V. V. Klymenko, O. R. Yeroshenko, D. O. Sytnyk — Tue, 30 Dec 2025 00:00:00 +0200

The article is devoted to the study of the issue of further development of the logistics infrastructure of passenger transportation in Ukraine. It is determined that the development of passenger transportation infrastructure should be carried out taking into account the needs of the population in high-quality, safe and comfortable services. The need for the formation of a single passenger space by integrating different types of transport and taking into account the requests of the population is substantiated. Further improvement of the passenger transportation system should occur through the use of innovative and technological solutions that will ensure increased economic and social efficiency of the transport services market. Examples of implemented projects of interaction between modes of transport in the organization of passenger transportation, which ensured an increase in the economic and social efficiency of the transport services market in Ukraine, are considered. Taking into account domestic and foreign experience in organizing passenger transportation in the «airport-railway station» connection, the technical and technological characteristics of the Odessa International Airport as a strategic transport hub of the southern region of Ukraine were considered. The dynamics of passenger traffic at the Odessa International Airport in the pre-war period were analyzed. The state of the connection system between the Odesa International Airport and the Odessa railway station was studied. The results of the analysis of the advantages and disadvantages of existing passenger transportation options in the analyzed connection system were represented. In order to improve passenger transport services and ensure convenient transfers from one mode of transport to another, a project to ensure uninterrupted and convenient movement of passengers between the railway station and the airport was considered. The implementation of the proposed organizational, technological and infrastructure solutions for the passenger transportation system is economically justified and strategically important for the development of the Odessa International Airport, increasing its competitiveness and ensuring the overall efficiency of transport logistics in the region. A comparison of the level of comfort for passengers using existing and proposed transportation options was carried out.

IMPACT ASSESSMENT OF LINER SCHEDULE DISRUPTION ON FLEET EFFICIENCY BASED ON TIME CHARTER EQUIVALENT

O. L. Drozhzhyn, S. P. Onyschenko — Tue, 30 Dec 2025 00:00:00 +0200

The article discusses the problem of liner schedule disruption (LSD) and its impact on the economic efficiency of shipping companies. It has been determined that failure to comply with container ship schedules leads to direct economic losses, which are reflected in a decrease in the time charter equivalent (TCE) indicator, which is a universal indicator of the profitability of ship operation regardless of the form of chartering. It is shown that schedule disruptions have a double negative effect: on the one hand, a decrease in efficiency due to an increase in voyage time, and on the other hand, a deterioration in the carrier's image, which in the long term reduces demand and market share. The paper proposes a mathematical model for quantitative assessment of losses from delays in port and during the voyage. Analytical dependencies allow determining the decrease in TCE due to an increase in downtime in ports and the time a vessel spends in sea transit. The calculations showed that delays during ship movement are 2–3 times more costly than delays of equivalent duration in port, due to high bunker fuel costs and the need to recover the schedule by increasing speed. The assessment methodology developed by the author allows analyzing the economic consequences of schedule non- compliance for both individual voyages and the entire line or fleet of the company as a whole. It takes into account the difference in the size of vessels and their contribution to the total volume of transportation, which ensures the adequacy of the assessment in strategic planning. The results obtained are of practical importance for optimizing management decisions in the field of liner shipping, in particular for improving the reliability of schedules, minimizing operational risks, and reducing financial losses. Thus, the proposed approach transforms the abstract problem of schedule disruption into a specific financial indicator that can be used as a tool for monitoring performance and making decisions in real time, as well as for long-term strategic planning of container transport development.

DETERMINING THE TIME OF A VESSEL´S SINGLE VOYAGE UNDER THE TERMS OF A VOYAGE CHARTER-PARTY

Yu. O. Koskina — Tue, 30 Dec 2025 00:00:00 +0200

The paper is devoted to the procedure for determining the elements and total voyage time in accordance with the terms of a voyage charter-party. The basis for the performance of a voyage for the carriage of goods by a tramp vessel is a voyage charter party concluded between the shipowner-carrier and the charterer, which is in essence a contract for the carriage of goods. The terms of such a contract largely determine the duration of the voyage, which for the shipowner-carrier is a certain benchmark for the employment of the vessel under the contract concludede and for the charterer allows to estimate the time of cargo trans- portation on the sea leg of its delivery. The paper considers a single voyage of a vessel, which is carried out on the terms “1 port of loading – 1 port of discharg- ing”. The voyage of a vessel is considered in the paper as consisted of separate components – a ballast passage (if necessary), the vessel is at the port of loading, passage with cargo and staying at the port of discharging. The procedure for their calculation is presented with reference to the terms of the voyage charter party, which are used in the relevant calculations as initial data. Among these terms, the ports of loading and unloading are of fundamental importance for determining the duration of the ves- sel's passages, as far as they determine the distance of the vessel's passages with cargo and also the route of the voyage. It is emphasized the importance of considering the terms of the voyage charter party regarding the timing of the vessel's arrival at the port of loading, as specified in the voyage charter party by the laydays and cancelling dates. When calculating the time a vessel is at berth in ports for the relevant cargo operations, the cargo operations rates agreed in the voyage charter party, the procedure for counting days off and holidays, and the terms for begining the laytime running are of great importance. The varied wording of these terms of the voyage charter party may require certain adjustments, but the basic procedure for calculating the duration of the elements and the total voyage time remains unchanged.

PROCESSING OF SATELLITE IMAGES USING THE APPARATUS OF FUZZY SET THEORY

S. I. Alpert — Tue, 30 Dec 2025 00:00:00 +0200

Fuzzy set theory is a branch of applied mathematics devoted to methods of analysis and processing of vague and inac- curate data. Main concept of this theory is membership function. Membership function defines the degree to which a certain element or object belongs to a fuzzy set. Fuzzy set theory accurately describes mathematical models of complex natural objects and processes, it is widely applied in various fields, such as: computer science, artificial intelligence, pattern recognition, and others. This theory is used to model, analyze and study various complex systems with uncertain data. Fuzzy Set Theory is a considerable mathematical tool in remote sensing. The concept of «fuzzy set» is used in classification tasks when common clas- sification methods give inaccurate results. This theory describes the classes of land cover with the degrees of belonging of object to each of these classes. This mathematical approach is useful when dealing with imprecise and ambiguous boundaries between classes. The use of fuzzy sets makes it possible to build more realistic models for solving remote sensing problems. It was noted that the proposed theory plays a serious role in the processing of satellite images for solution of remote sensing tasks, because this technique allows to accurately describe the structure of the satellite image. Some logical operations with fuzzy numbers applying the alpha-cut method were described. These logical operations with fuzzy numbers were considered using numerical examples. Fuzzy clustering using the C-means method was analyzed in detail. It was noted that this approach is widely applied for unsupervised classification of satellite images. It allows, that pixels belong to multiple classes with different degrees of mem- bership, unlike other known clustering methods. Fuzzy C-Means clustering is useful for processing, analyzing and classification mixed pixels. Apparatus of Fuzzy Set Theory can be applied for solution of such actual and important remote sensing tasks, such as: agricultural tasks, water resources monitoring, vegetation classification, various ecological and geological problems.

HOTEL SERVICE TECHNOLOGIES OF TOURIST GROUPS

K. M. Horb, M. V. Korneyev, V.V. Pavlov — Tue, 30 Dec 2025 00:00:00 +0200

The article is devoted to the analysis of approaches, generalization of experience and systematization of technologies of hotel service of tourist groups at different stages of the guest cycle, in different formats of tourist trips in different means of accommodation of tourists, including mobile ones (tourist trains, cruise ships, buses and airplanes with sleeping places, etc.), with the aim of further standardization and improvement of the group service process in tourism and hospitality. Technological processes of service of tourist groups in hotels have a number of significant differences from the provision of hotel services to individual guests. At the stage of booking hotel services for a group of tourists, it is important for the customer to provide the hotel with a list of tourists with their passport data, to agree on the distribution of tourists by rooms of different categories, with the priority of compact mutual arrangement of rooms where the tourists of the group will live, as well as the issue of group transfer to the hotel upon arrival and return transfer upon departure, to take care of parking at the hotel of the group vehicle. At the accommodation stage, it is important to promptly settle the group members in the hotel rooms through the coordinated actions of the hotel administrator on duty and the tour group guide. During the group’s stay at the hotel, it is important to ensure the compatibility of the purpose of the group’s stay with the purpose of the rest of the guests. At the last stage of final settlements, eviction and departure of the group from the hotel, it is important to ensure the efficiency of mutually agreed actions regarding checking rooms, handing over keys, packing personal belongings and loading them into a vehicle, etc. When providing group hotel services to tourists at each stage of the guest cycle, the key task is to avoid queues and minimize the time for any waiting by the majority of the group of the rest of the tourists. All of the above provisions for hotel services for tourist groups are valid for both stationary facilities and accommodation establishments and for mobile ones, namely for those tourist vehicles where it is intended to provide tourists with sleeping places for overnight stays. In the future, it is appropriate to pay attention to a more detailed justification of the concept of a group guest cycle of an accommodation facility, the essence of which will be the consist- ency and continuity of providing group hotel service.

OPTIMISATION OF THE STAFF MOTIVATION SYSTEM IN THE HOTEL BUSINESS

N. A. Horozhankina, Ye. L. Saihak, A. V. Grytsenko, D. S. Topol — Tue, 30 Dec 2025 00:00:00 +0200

The personnel motivation system is considered on the example of LLC "Hotel World (the hotel "Dnipropetrovsk")". Based on the questionnaire method, a check was made of the compliance of the existing personnel motivation system with the requirements of the company's employees. The compliance of the existing personnel motivation system with the requirements of the company's employees was checked by means of a questionnaire using a specially developed questionnaire. All hotel employees (100%) participated in the questionnaire. Factors of employee dissatisfaction with their work were identified, and the need to improve the personnel policy for employees was assessed. 38% of respondents are completely satisfied with their work in the institution, 43% are more satisfied than dissatisfied, 14% are more dissatisfied and 5% are completely dissatisfied. It was found that 60% of employees are satisfied with the organisation of their workplace, 40% are completely or partially dissatisfied. An assessment of the motivation system was conducted to assess the motivation system of the staff of the hotel "Dnipropetrovsk". It was found that many motivational elements of the hotel "Dnipropetrovsk" require improvement. The main problems associated with the motivation system are: lack of assessment of well-organised professional development and training activities for staff; lack of an adaptation process for employees; lack of career planning for employees; lack of awareness of employees; low level of financial incentives for employees. As a result of the audit of the personnel management system of the hotel "Dnipropetrovsk", it was found that the staff motivation system at the hotel needs improvement, which affects labour productivity. The following measures are recommended to improve the staff motivation system at the hotel "Dnipropetrovsk": 1. Implement an effective staff motivation system that increases labour productivity. When using schemes and bonuses in the salary structure, there should be a clear connection between the contribution of a particular employee and the amount of compensation. 2. Improve the system of material and non-material incentives for employees, including the introduction of additional salary payments at the end of the year, the issuance of certificates of the best employees, etc. A SWOT analysis of the staff motivation system of the hotel "Dnipropetrovsk" was conducted, based on which the shortcomings of the staff motivation system were identified: the staff motivation system is represented only by wages in the form of direct compensation and is practically limited; failure to use the entire motivational potential of employees to improve existing processes and results of the enterprise. The main opportunity of the hotel "Dnipropetrovsk" is to gain time during the recovery period after the economic crisis, reconstruction after Ukraine's victory in the war with russia and use it to develop a motivation system that meets modern market conditions.

CURRENT ASPECTS OF PERSONNEL MOTIVATION IN THE HOTEL AND RESTAURANT SECTOR OF UKRAINE

M. M. Kucher, M. V. Korneyev, H. V. Shcholokova, O. O. Zakharenko — Tue, 30 Dec 2025 00:00:00 +0200

The article explores the current aspects of employee motivation in Ukraine’s hotel and restaurant sector under conditions of social, economic, and technological uncertainty caused by martial law, large-scale population migration, a shortage of qualified personnel, and rapid digitalisation. Employee motivation in the hospitality industry serves as a key factor in ensuring productivity, service quality, workforce stability, and the competitiveness of enterprises. The features of modern approaches to staff motivation in the hotel and restaurant sector of Ukraine were studied, effective methods of stimulation were identified, and innovative solutions adapted to today's challenges were substantiated. Within the framework of the research, motivational methods have been classified into five categories: financial incentives, non-financial incentives, indirect methods, elimination of demotivating factors, and disciplinary measures. Their effectiveness has been analysed taking into account corporate culture, the age structure of personnel, and the specific features of labour processes. The study applies classical motivational theories (A. Maslow, V. Vroom, F. Herzberg, J. Adams, M. Seligman) as well as generational theory (X, Y, Z), which makes it possible to consider the social and value-based differences among employees. Particular attention is paid to innovative approaches to motivation, including flexible work models, digital gamification, personalised development programs, mental health support, transparent bonus systems, and employee participation in decision-making. The SWOT assessment of motivation strategies within hospitality enterprises highlighted key tendencies, including the enhanced significance of non-financial motivators, the prioritisation of emotional stability, intensified attention to professional development and career progression, the institutionalisation of KPI-linked compensation mechanisms, the integration of new social groups, and the increasing utilisation of digital human resource tools. The study substantiates that wages remain a fundamental motivator, especially under inflationary conditions; however, an effective motivational system should combine both financial and non-financial stimuli, be flexible, transparent, and socially sensitive. Effective management of employee motivation in the hotel and restaurant business represents a strategic resource that ensures resilience, operational efficiency, and sustainable development of hospitality enterprises.

IMPLEMENTING CUSTOMER-CENTRIC APPROACHES IN THE RESTAURANT INDUSTRY: ANALYTICS, MOTIVATION, EFFICIENCY

N. F. Stebliuk, N. O. Nebaba, М. Yu. Razinkova, S. V. Hryshchenko — Tue, 30 Dec 2025 00:00:00 +0200

The article explores current trends in the development of the restaurant business, which are associated with the need to respond promptly to changes in market conditions and increase the level of consumer expectations, and actualize the implementation of customer-oriented approaches in the service system of business models of establishments. The impact of a customer-oriented approach, staff motivation and key performance indicators (KPI) on the quality of service and the effectiveness of the activities of restaurant business establishments is determined. Key performance indicators are determined, which allow not only to determine the level of customer satisfaction, but also to identify weaknesses in the service process, and therefore, to improve business processes based on the obtained analytics. Specialized training programs are proposed, which are aimed at increasing the efficiency of personnel management in the restaurant business and improving the quality of customer service. It has been established that the focus on service quality, personalized interaction with consumers and the creation of a comfortable communication environment contributes to an increase in customer satisfaction, reducing their churn and stimulating repeated consumption. It has been determined that systematic monitoring of key performance indicators allows for timely identification of problem areas, optimization of business processes and effective use of marketing resources. The feasibility of implementing specialized motivational programs that positively affect staff productivity, reduce staff turnover and create a favorable internal climate has been substantiated. The practical significance of the results obtained lies in the possibility of their direct application in the activities of restaurant business establishments to improve the customer service system based on a customer-oriented approach. The results obtained can also be used to increase the economic efficiency and sustainability of restaurant business establishments in conditions of high competition. Prospects for further research are the development of digital KPI monitoring tools, the study of the impact of staff emotional intelligence on customer experience, as well as a comparative analysis of the effectiveness of customer-oriented strategies in different formats of restaurant business establishments.

CURRENT TRENDS AND CREATIVE APPROACHES TO INNOVATIVE DEVELOPMENT OF HOSPITALITY INDUSTRY ENTERPRISES IN WORLDWIDE

O. I. Yudina, M. M. Kucher, O. V. Sabirov, A. V. Boholiubova — Tue, 30 Dec 2025 00:00:00 +0200

The article considers current trends in innovative development of hospitality industry enterprises in Europe and worldwide, emphasising creative approaches that shape modern operational strategies within hotel and restaurant sectors. The features of innovative development of hospitality industry enterprises were investigated. Trends and creative approaches to the implementation of innovations in the "La Générale" restaurant were identified. The conducted analysis highlights several major trends defining contemporary transformation in the restaurant industry: the growing role of delivery and takeaway services, the promotion of healthy and balanced menus, the proliferation of casual dining concepts combining refined cuisine with quick service, and the accelerated digitalisation and automation of business processes through intelligent technologies. Additionally, the research identifies crucial directions in hotel innovations, such as the use of smart technologies, mobile client interaction, AI-based recognition systems, and environmental certification as markers of sustainable development. There has been a positive trend in investment activity of hotel companies in the global market and a downward trend in investment in new technologies in European restaurant establishments. The example of “La Générale” demonstrates how the integration of digital, environmental, managerial, and cultural innovations fosters operational efficiency, brand differentiation, and competitiveness. Overall, the hospitality sector today evolves under the influence of digitalisation, automation, ecological responsibility, and creativity in service design. Within the restaurant domain, innovations concentrate on health-oriented nutrition and digital service channels, whereas the hotel industry introduces smart and contactless solutions that enhance sustainability and comfort. The outcomes of the study confirm that modern approaches to innovation at “La Générale” ensure the enterprise’s resilience, economic adaptability, and distinct market position.