Systems and Technologies

MOISTURE ESTIMATION IN SUGAR DRYING BASED ON A HYBRID MATHEMATICAL MODEL

G. V. Grygorchuk — 2026-05-30

The paper addresses the problem of moisture estimation in the sugar drying process, which is a critical stage of sugar production affecting product quality, storage stability, and energy efficiency. Direct continuous measurement of moisture in industrial conditions is difficult due to technological limitations and time delays associated with laboratory analysis. Therefore, the development of reliable indirect estimation methods is an important task for improving process control. A hybrid mathematical model for real-time moisture estimation is proposed. The model combines a physical description of heat and mass transfer dynamics with a neural network-based soft sensor used as a nonlinear correction element. The linear discrete model describes the main inertial behavior of the drying process, while the nonlinear component compensates for model uncertainties, parameter variations, and external disturbances. The structure of the model and the data processing algorithm are presented. Simulation studies were performed taking into account measurement delays typical for industrial conditions. The influence of the discretization step on estimation accuracy and control performance was also analyzed. The results demonstrate that the hybrid model reduces the moisture estimation error by approximately 25–30 % compared to the linear model and provides stable performance under varying operating conditions. The proposed approach enables reliable estimation of an unmeasured state variable and can be integrated into industrial control systems. The developed model is suitable for real-time applications and can be used for monitoring, stabilization, and optimization of the sugar drying process.

BILATERAL ESTIMATES OF THE MAXIMUM LYAPUNOV INDICATOR

S. Yu. Poslavskyi — 2026-05-30

Many systems encountered in problems of mechanics, control theory, and other fields of science and engineering are described by nonlinear differential equations with time delay. Most studies consider systems with constant delay; however, information about the delay function is often unavailable, with only its upper bound known; furthermore, the system may contain distributed delay. Known methods, in most cases, allow one to obtain only sufficient conditions for stability or upper bounds on the maximum Lyapunov exponent. A drawback of such results is that the degree of their conservativeness remains unknown. In this regard, the task of localizing the maximum Lyapunov exponent is relevant; that is, in addition to an upper bound, it is necessary to find its lower bound. The proximity of these bounds guarantees the accuracy of the obtained upper bound and, consequently, of the sufficient stability conditions. The article provides a detailed examination of a class of systems of nonlinear differential equations with a given linear part and a norm-bounded nonlinear term containing a variable delay. Particular attention is paid to the effect of the delay on the system’s dynamics and the estimation of its stability characteristics. Was obtained two-sided estimates of the maximum Lyapunov exponent, expressed in terms of the norm of the nonlinear term as well as in terms of the maximum values of the delay functions. This allows us to establish quantitative bounds on the behavior of the solutions and to estimate the rate of their convergence or divergence. For certain classes of systems, it was possible to determine exact values of the maximum Lyapunov exponent, which is an important result for stability theory. Based on the obtained estimates, sufficient, and in certain cases necessary, conditions for the exponential stability of the studied systems have been formulated. A characteristic feature of these conditions is their invariance with respect to delay, which significantly expands their scope of application. A simple and effective method for verifying exponential stability is also proposed, which does not require complex calculations and has a computational complexity that is practically independent of the system’s dimension (order). This makes the approach convenient for practical use, particularly for high-dimensional systems. Finally, a series of examples is provided that illustrate the application of the developed method, demonstrate its effectiveness, and confirm the theoretical results.

AUTOMATED WORK WITH FINITE AUTOMATA: A TOOL FOR TEACHING IN THE ERA OF ARTIFICIAL INTELLIGENCE

T. M. Sopronyuk — 2026-05-30

The article addresses the problem of maintaining objectivity in student assessment in the context of widespread access to artificial intelligence tools, particularly large language models such as ChatGPT. The study focuses on the discipline of formal languages and automata theory, where traditional task formats (transition tables) are easily solved by modern AI models. The purpose of the work is to develop software for automated generation, determinization, and visualization of finite automata, enabling rapid creation of individual assignment variants in visual format (transition diagrams). The system includes a random NFA generator with guaranteed state reachability and controlled transition density, a visualization module with customizable parameters, a pairwise automaton display function for concatenation and union operations, an assignment variant generator (20 variants with concatenation, union, and iteration tasks), and an NFA determinization algorithm that reads automata from text files and visualizes the resulting DFA. Experimental results show that visual format tasks significantly reduce AI solution success, while student testing confirms reduced AI usage. The developed software can be used in teaching courses on automata theory and language processors.

ON THE METHODOLOGY FOR CALCULATING THE AERODYNAMIC CHARACTERISTICS OF AN UNMANNED AERIAL VEHICLE IN THE EARLY STAGES OF DESIGN

A. V. Sokhatskyi — 2026-05-30

Determining the aerodynamic characteristics of unmanned aerial vehicles is an extremely complex problem. It is believed that the most accurate way to determine the aerodynamic characteristics of any vehicle is through computational modeling. This procedure is performed on high-performance computers using Reynolds-averaged Navier–Stokes equations. However, this process is complex and costly. It requires significant time for developing methodologies, constructing algorithms, writing software packages, and the actual operation of the computers. In the numerical solution of aerodynamic problems using the Reynolds-averaged Navier–Stokes equations, it is not the differential equations themselves that are solved, but their finite-difference analogs. It is necessary to correctly enforce the physical conservation laws of mass, momentum, and energy. In addition, a specific turbulence model must be applied. This is a challenging task for mesh-based methods for solving problems in mathematical physics. Designing the aerodynamic configuration of an unmanned aerial vehicle requires solving an inverse problem. Currently, no such methods exist. Problems involving the search for the optimal aerodynamic configuration of a transport vehicle for any purpose are solved iteratively through a process of gradual approximation. This requires significant time and financial resources. To calculate the aerodynamic characteristics of unmanned aerial vehicles in the early stages of design, it is proposed to use empirical approaches. This paper presents a methodology for calculating the aerodynamic characteristics of an unmanned aerial vehicle. To develop this methodology, algebraic relationships obtained from experimental studies of aircraft aerodynamics by domestic and foreign researchers were utilized. To perform the necessary calculations, algorithms were developed and a software package was written in the Fortran-95 programming language. Calculations of the aerodynamic characteristics of the fuselage for an unmanned aerial vehicle were performed and compared with experimental data.

NONLINEAR ALGORITHMS FOR LOAD DISTRIBUTION TO WIND TURBINE STABILIZATION CHANNELS

S. V. Tarasov — 2026-05-30

Today, wind power plants are increasingly taking up a place among operating renewable energy systems. To achieve their most successful operation, it is extremely important to use the maximum available wind power to achieve wind turbine (WT) operation at maximum power. Algorithms for tracking the maximum power point and algorithms for stabilizing the operation of the WT in a small vicinity of this point are extremely important in this context. To ensure small deviations in the rotation speed around the maximum power point for the current wind flow speed, the traditional means is to use a generator to control the rotation of the WT rotor. The use of changes in the turbine rotor configuration for this purpose is a fairly new direction in the design of control systems. Researchers note a number of useful properties of WTs with a variable rotor configuration, which make them quite promising for further use. The difficulties of designing such VTs are associated with the increased methodological complexity of the analysis and synthesis of rotor rotation control systems – general mathematical models of the rotor are nonlinear, which is associated with the dependence of the rotor inertia tensor on changes in generalized coordinates, and their linearization leads to non-stationary models. Unfortunately, there is no comprehensive description of such systems. A possible way to reduce the complexity of the description is to reduce the maximum changes in the length of the traverses while ensuring the loading of both stabilization channels – the channels for changing the length of the blades and the traverses during their joint operation. The purpose of the article is to analyze the stability of dynamic algorithms and quality indicators of the regulation system for stabilizing the rotation of the Darie VT rotor of variable configuration, as well as the conditions for the absence of a static regulation error. The methods for solving the problem are methods of the classical theory of automatic control and mathematical modeling. The novelty of the obtained results lies in the constructed dynamic stabilization algorithms, the conditions of their stability and the absence of a static regulation error, as well as in the dissemination of the method of load distribution on stabilization channels with algorithms that dynamically The conducted mathematical modeling proved a significant improvement in the dynamic properties of the variable configuration Darier rotor rotation stabilization system using dynamically changing algorithms.

COMPUTER MODELING OF EPIDEMIC SPREAD BASED ON CELLULAR AUTOMATA

Y. V. Ulianovska — 2026-05-30

The paper provides a comprehensive analysis of modern methodological approaches to the computer modeling of infectious disease spread processes, with the mathematical apparatus of cellular automata serving as the pivotal tool. The author substantiates the scientific expediency of transitioning from classical analytical models of the SIR type, characterized by a certain level of abstraction and simplification, to more flexible discrete-spatial models. Such models allow for a significantly more adequate reproduction of the complex and non-linear spatio-temporal dynamics of epidemic processes, taking into account the structural heterogeneity of the environment and the stochastic nature of interpersonal contacts within a population. Within the framework of the conducted research, a comparative review of existing scientific paradigms was carried out, specifically multi-agent modeling concepts, which enabled a clear definition of the advantages of the cellular automata approach in tasks involving the mapping of local interactions, diffusion processes, and the direct impact of physical spatial constraints on pathogen transmission. The primary scientific result of the work is the development and full-featured software implementation of an interactive model of infection spread, which provides high-quality visualization of the epidemic process dynamics in real-time, supporting the functionality for operational changes in simulation parameters. The model architecture is based on a two-dimensional state matrix structure, where each individual cell is identified as an autonomous agent and can reside in one of the predefined epidemic states: susceptible, infected, immune (recovered/removed), deceased, or a stationary barrier. Transition rules between states are formalized based on developed probabilistic mechanisms of infection transmission and temporal characteristics of the disease course, ensuring high flexibility in adapting the model to various scenarios for both viral and bacterial outbreaks. The software implementation of the model was performed using the Python programming language, employing specialized NumPy libraries for optimizing matrix calculations and Pygame for implementing the graphical user interface and interactive visualization. During the study, a series of complex computational experiments were conducted, including varying the initial vaccination levels, changing the intensity of social contacts, and modeling the implementation of quarantine restrictions of various degrees of severity. The obtained empirical results confirm the adequacy of the developed model, particularly its ability to accurately reproduce characteristic wave-like epidemic dynamics, outbreak localization effects, and the formation of herd immunity. It has been established that the synergetic combination of high preventive immunization levels and timely restrictive measures is the most effective factor in containing an epidemic threat. The practical significance of the developed software complex lies in the possibility of its wide application as a tool for fundamental scientific research, short-term forecasting, and for educational purposes for specialists in relevant profiles. Prospects for further investigation in this direction are associated with the deep integration of the cellular automata model with modern machine learning methods and Big Data analysis to increase predictive accuracy based on real statistical indicators of urban mobility.

MODELING THE TRANSFORMATION OF PROGRAM PERSONNEL MANAGEMENT PROCESSES IN A MULTIPROJECT ENVIRONMENT

N. V. Dotsenko — 2026-05-30

The article is devoted to the study of the transformation of HR management processes of programs in a multi-project environment. The purpose of the study is to develop a model of the transformation of HR management processes of programs in a multi- project environment. The study is based on the use of the project and program approaches to managing program projects, the methodological support for business process reengineering, the combinatorial analysis and optimization methods. The scientific novelty is the development of a set of models of transformations of management processes: a contextual model and a decomposition model of the transformation of HR management processes of programs in a multi-project environment. The study yielded results that contribute to improving the effectiveness of transformation. An analysis of approaches to studying transformation processes identified aspects that should be considered when developing an adaptive digital HR ecosystem. The structure and functions of an adaptive digital HR architecture are defined. Typical characteristics of an adaptive digital HR architecture for a multi-project environment are identified, and their classification is proposed. To formalize transformations, the contextual model for transforming HR management processes for programs in a multi-project environment was developed. A decomposition of the transformation processes was performed, and a model for transforming HR management processes for programs in a multi-project environment was constructed. Elements of a multi-agent transformation system were identified, and information support for transformation was considered. The application of reengineering to manage transformation processes is considered. The main stages of transformation are identified. Using the proposed models will formalize transformation processes and identify the starting point for transformations. The created TO BE process models, a register of transformation changes, and transformation recommendations will provide information and methodological support for management decision-making.

MODELING AND OPTIMIZATION OF DYNAMIC CONTROL IN STOCHASTIC SYSTEMS BASED ON MACHINE LEARNING

S. I. Zhyr — 2026-05-30

The problem of optimizing the functioning of the entry group of a container terminal operating under conditions of stochastic uncertainty of transport flows caused by global logistics trends and random external factors is considered. The relevance of the chosen direction is due to the need to reduce truck waiting time, minimize operating costs and level the negative environmental impact from excess emissions during transport downtime in queues. Obviously, a simple expansion of the physical infrastructure is often economically impractical. A transition to an intelligent hybrid dynamic control model based on the reinforcement learning (RL) paradigm is proposed, which allows the system to adaptively regulate the number of active service channels. The developed model is based on a Markov decision-making process. To adequately reproduce the real dynamics of truck arrivals, a Poisson distribution is used. The entry group is represented through a discrete approximation of the classical mass service model. The use of Q-learning ensures finding the optimal control policy even in the absence of exhaustive a priori information, allowing the agent to «learn» directly during interaction with the environment. The study illustrates the evolution of agent learning and confirms its convergence to a theoretically justified optimal strategy. The modeling results show that the implementation of RL methods contributes to effective smoothing of peak loads, a significant reduction in queue length and an overall increase in terminal throughput. The possibilities of scaling the model through the integration of deep neural networks are considered, which allows operating with large data sets and complex state spaces. The Hamilton–Jacobi–Bellman equation, which determines the optimality limits in continuous control problems, is a theoretical verification of the obtained strategies. The proposed approach has practical significance for the development of logistics systems, as it allows integrating hybrid intelligent algorithms into infrastructure management and ensures optimization of economic indicators.

PROCEDURAL AND GENERATIVE METHODS FOR GAME CONTENT CREATION

H. A. Zavhorodnia — 2026-05-30

This paper investigates contemporary methods of procedural and generative game content creation, with a focus on rulebased approaches and stochastic models, as well as the challenges of integrating these methods to improve generation efficiency. Special attention is given to the problems of scalable content generation under limited computational resources and high requirements for variability, structural consistency, and realism of game environments. The study analyzes current trends in automatic content generation, including algorithmic rules, probabilistic models, Markov processes, stochastic grammars, and hybrid approaches that combine the advantages of deterministic and random mechanisms. The work proposes a formalization of the content generation process as a composition of deterministic and stochastic operators, allowing for simultaneous improvement of controllability and diversity of results. A mathematical model of the generative process is introduced, based on a state distribution function and a constraint function, ensuring the validity of generated game configurations. The study demonstrates how combining rule-based systems with stochastic generators enables a balance between predictability and variability of results, providing flexible adaptation to user requirements and dynamic game processes. Particular attention is paid to analyzing the efficiency of different approaches in terms of computational complexity, scalability, and quality of generated content. A series of experimental studies were conducted comparing the proposed hybrid model with baseline generation algorithms, including pure rule-based systems and random stochastic generators. The results show that hybrid methods can significantly increase content diversity (by 35–50 %) while maintaining structural integrity, and also reduce generation time compared to classical approaches. The study confirms that integrating deterministic and stochastic mechanisms is an effective approach to improving the quality of procedural content in modern game systems. The obtained results can be applied in the development of procedural worlds, adaptive generative environments, and modern computer games, ensuring a balance between predictability, variability, and computational efficiency.

STOCHASTIC OPERATORS OF ACTION IMPACT: FORMALISATION AND MULTI-STEP REGULARISED LEARNING

B. Yu. Zaika — 2026-05-30

This paper proposes a formalisation of action impact in stochastic dynamical systems as a dedicated stochastic operator acting on system states. Accurate modelling of action impact is an important problem in sequential decision-making under uncertainty, since in many real-world systems actions are applied repeatedly and their consequences propagate through system dynamics over time. While modern machine learning approaches, including reinforcement learning and conditional density estimation, can approximate short-term transitions, the behaviour of learned models under recursive multi-step application remains insufficiently studied. In most existing frameworks, transition dynamics are embedded within policy optimisation or trajectory prediction objectives and are rarely treated as independent modelling entities. In the proposed approach, the action impact operator maps the current system state and applied action to a conditional distribution of future states and is defined with explicit compositional structure. This enables the analysis of recursive operator application across multiple time steps. A learning objective is introduced that combines one-step negative log-likelihood with a multi-step consistency term derived from operator composition. The central hypothesis of the study is that one-step maximum likelihood training does not guarantee stable long-horizon behaviour when the learned operator is recursively applied. To investigate this hypothesis, empirical evaluation is conducted in a fully observable stochastic dynamical system using a minimal realisable linear Gaussian model. The empirical results show that purely one-step training leads to long-horizon degradation, including accumulation of trajectory error and systematic underestimation of predictive uncertainty. Introducing explicit multi-step regularisation significantly improves long-horizon stability and uncertainty calibration, and the improvement persists beyond the training horizon. The proposed formulation establishes a basis for modelling action impact in stochastic dynamical systems and provides a machine-learning framework for robust modelling of recursively applied transitions. This provides a foundation for further research in partially observable environments, nonlinear architectures, and decision-support systems.

A SET-THEORETIC APPROACH TO MODELING CASCADING DERIVATIVE RISKS IN SOCIO-TECHNICAL SYSTEMS

V. I. Ziuziun — 2026-05-30

The article addresses a pressing scientific and applied problem: modeling complex hierarchical relationships among risk factors arising in the operation of high-tech, socially oriented systems. The object of the study is a network of sorting stations, considered as a complex dynamic system with distributed business processes. The relevance of the research is driven by the high level of turbulence in the external environment and the need to move from qualitative descriptions of risks to their digital formalization and quantitative measurement. The proposed approach is grounded in systems analysis, which enabled a multi-level decomposition of the organizational structure into subsystems of financial planning, logistics, sales, and marketing. Set theory was employed as the mathematical framework to describe the interactions among these subsystems. This made it possible to represent the cascading development of risks as a sequence of system states in which the emergence of a primary threat (funding shortfall) initiates a set of derivative risks, ranging from technological degradation of sorting lines to the loss of intellectual capital. The scientific novelty of the work lies in the further development of set-theoretic membership models that establish logical relationships between the causes and consequences of critical situations in a format suitable for automated processing. For the first time, an algorithm for the quantitative assessment of cascading impacts has been proposed through an integral indicator of Expected Risk Value (ERV), based on a combination of probabilistic characteristics and degrees of influence on the system’s target performance indicators. The practical significance of the research is realized in the form of a strategic management map-scheme representing a set of algorithmized response strategies (avoidance, mitigation, acceptance). The proposed measures integrate both managerial decisions and technical-technological innovations, including the use of robotic systems to automate sorting processes. This reduces critical dependence on the human factor and minimizes operational risks. The application of the developed models creates a mathematical foundation for the design of intelligent Decision Support Systems (DSS) capable of predictive monitoring of complex systems and the automatic generation of cascading threat neutralization scenarios. The use of such digital tools ensures not only the short-term stabilization of business entities but also creates conditions for their sustainable development and enhanced competitiveness in the context of the economy’s digital transformation.

ALGORITHMS AND METHODS OF ADAPTIVE BEHAVIOR OF NON-PLAYER CHARACTERS IN COMPUTER GAMES

Y. Y. Iliash — 2026-05-30

The article is devoted to a comprehensive study of the Behavior Tree model as a tool for implementing artificial intelligence of Non-Player Characters (NPCs; Agents) in modern computer games. The relevance of applying hierarchical decision-making architectures is substantiated in the context of increasing demands for interactivity, adaptability, and realism in NPC behavior. It is demonstrated that the structured behavior tree model ensures logical organization of an agent’s actions, a transparent prioritization mechanism, and the possibility of system scalability without loss of manageability. The paper proposes a formalized architecture of a behavior tree, distinguishing composite nodes such as Selector and Sequence, as well as leaf nodes that implement specific actions (pursuit, attack, patrol, idle/wait). The tri-state execution model (Success, Failure, Running) and the tick-based evaluation principle are analyzed in detail, ensuring real-time system reactivity. Particular attention is given to constructing a priority hierarchy of behaviors, in which combat scenarios have higher significance, while alternative states serve as background or fallback actions. The practical implementation of the model was carried out in the Unity environment using the C# programming language. The uniqueness of the proposed algorithm implementations lies in the adaptability of the code for other engines based on C++. Examples of programmatic implementation of the base node class, composite structures, and tree initialization are presented, demonstrating the correspondence between theoretical principles and real software implementation. It is shown that the proposed architecture is modular, extensible, and suitable for integration into game projects of varying complexity. The obtained results confirm that behavior trees allow combining algorithmic rigor with game design flexibility, ensuring predictable yet dynamic agent behavior. The proposed approach can be used in educational prototypes, indie projects, and commercial developments, and can also serve as a foundation for further research related to Behavior Trees.

SOFTWARE IMPLEMENTATION OF A DESKTOP INFORMATION SYSTEM FOR LIBRARY AUTOMATION

V. S. Morokhovych — 2026-05-30

This article describes the development of a desktop solution for the automation of library operations, which optimises the management of the collection, users, book circulation and staff work. The system provides for the authentication of users with the roles of librarian and administrator, with data verification via a secure connection to the database. The application implements functionality for viewing, adding, editing and searching for information about readers, books and loan transactions, with access to certain actions restricted depending on the user’s role. The “Loans” tab supports automatic calculation of service charges based on the duration of book use, determination of book return or loss status, and the imposition of fines for late returns. The administrative section of the system allows you to manage library staff, change passwords, dismiss employees, and update reference information on genres and publishers. The database structure is also described, error handling is implemented, and a reliable connection to the database is ensured. Thanks to its intuitive interface, clear separation of roles, and extensive functionality, the information system significantly improves the efficiency of library operations, ensuring transparency and convenience in day-to-day tasks. The technical methods described can be adapted for use in related fields, such as archival record-keeping, the development of local CRM systems or electronic card catalogues, where the key requirements are autonomy, performance and data security. The primary focus of the application’s development is to expand its functionality whilst maintaining full autonomy and stable operation within a local network. This is particularly important for libraries that do not have constant access to the internet or operate in environments with stringent requirements for data storage on internal media.

VISUALIZATION OF THE ALGORITHM FOR MUNICIPAL GREEN BOND ISSUANCE IN UKRAINE: A GRAPH-AS-A-CODE APPROACH

T. V. Ratushnyak — 2026-05-30

In Ukraine, despite the legislative implementation of green bonds since 2020, the market remains in its infancy, represented only by isolated corporate cases. There is a critical gap between international trends in scaling sustainable investment and the domestic financial environment, which is constrained by systemic barriers. Ukrainian territorial communities, as potential public issuers, lack effective algorithms for issuing municipal green bonds. In the context of post-war reconstruction based on environmental modernization, this financial instrument acquires strategic importance for attracting capital into renewable energy, energy efficiency, and waste management. However, the high complexity of the emission procedure creates significant risks of management errors, highlighting an urgent need for the visualization of financial and legal processes. The purpose of the study is the scientific substantiation and development of a methodology for the dynamic visualization of the municipal green bond emission algorithm in Ukraine based on the «Graph-as-a-Code» concept. This involves using generative artificial intelligence to transform semantic legal descriptions into declarative Mermaid code to minimize management risks and overcome institutional barriers. The study employs a multidisciplinary approach based on systemic analysis and logical generalization to identify barriers in the sustainable finance market. Structural-functional modeling was used to decompose the emission algorithm into six stages in accordance with budget and financial legislation. The practical implementation of the model is based on semantic analysis combined with prompt engineering, ensuring the transformation of legal descriptors into valid Mermaid code. The final stage involves graphical visualization and rendering in digital environments to convert large arrays of text into interactive diagrams. The integration of the Gemini multimodal AI model allowed for the intellectual convergence of multi-source data, eliminating information gaps. The study proposes a technology for visualizing the emission algorithm through the «Graph-as-a-Code» method, implemented via five operations: from forming the semantic description to automatic rendering on GitHub. The research resulted in a dynamic visualization of the algorithm, which allows municipalities to perceive the emission process as a clear path rather than a wall of restrictions. The scientific substantiation and practical testing of the dynamic visualization methodology prove that traditional modeling methods (UML, BPMN) require adaptation to modern digital environments through declarative markup languages. The use of AI for code generation ensures high accuracy in reflecting complex financial and legal processes. The proposed approach minimizes management risks for local self-government bodies and ensures transparency in emissions.

RELIABILITY-DRIVEN STREAMING MODELLING OF MULTIMODAL TIME SERIES FOR ROBUST DECISION SUPPORT UNDER DRIFT AND MODALITY DEGRADATION

I. S. Uzun — 2026-05-30

Streaming decision support systems that process multimodal time series must remain robust under simultaneous concept drift and temporary modality degradation. Existing approaches usually treat multimodal fusion, drift adaptation, anomaly detection, and probability calibration as separate problems, which makes it difficult to distinguish whether a loss of predictive quality is caused by a real change in the process or by a temporary failure of one modality. This paper presents a unified online pipeline in which online reliability estimation is used as a single control interface for reliability-adaptive dynamic fusion, driftinitiated budgeted micro-adaptation, and reliability-constrained anomaly detection under a false alarm rate budget. Reliability is modeled as a causal probability of the current non-degraded modality state, post-hoc calibrated, and reused in all downstream control rules. Evaluation follows the prequential protocol on controlled streams with deterministic injections of modality degradation, concept drift, and anomalies, and on real data from UCI Appliances Energy Prediction and UCI Air Quality. The calibrated reliability model retains high degradation-separation ability (ROC - AUC = 0.8624) and improves calibration to ECE = 0.0845 versus 0.1840 without calibration. RADF preserves clean-regime quality (MAE = 0.5557; RMSE = 0.6952) and improves degraded segments, for example MAE = 0.6402 versus 0.6820 for early fusion under alternating missingness. Budgeted micro-adaptation improves post-drift forecasting relative to no adaptation (MAE = 0.6613 versus 0.7046; average recovery 157 versus 800 steps) while updating only a three-parameter head within fixed budgets. RC-AD increases Recall@FAR at all tested budgets, including 0.335 versus 0.103 at a false alarm rate budget of 0.05 on controlled streams. In the integrated stress scenario, the system achieves ROC - AUC = 0.983, ECE = 0.029, Recall@FAR=0.311, and PR - AUC = 0.287; in robust application protocols with severe segment missingness, it reduces MAE by about 35 % in the energy domain and about 93 % in the BTC/USD domain relative to naive fusion. These results present one coherent streaming decision support result rather than isolated local methods.

THE APPLICATION OF INSTANCEDMESH FOR VISUALIZING THE DYNAMICS OF PROCESSES IN THREE-DIMENSIONAL CELLULAR STRUCTURES

O. D. Firsov — 2026-05-30

In the present study, an algorithm along with its software implementation has been developed for the visualization of specialized three-dimensional cellular structures. The solution utilizes the capabilities of the INSTANCEDMESH class provided by the Three.js library in the JavaScript programming language. The object of research is the process of constructing models of cellular structures that evolve in accordance with theoretical algorithms, resulting in corresponding changes to their visual representation. Within the framework of this work, an algorithm for visualizing a three-dimensional array has been proposed, implemented, and tested. In this array, cell values are updated according to specific time steps (tacts) of the modeled system’s operation. The research findings demonstrate that array processing technology extended by the INSTANCEDMESH class serves as an effective tool for the three-dimensional visualization of cellular structures of limited size. It enables the creation of dynamic visualizations that reflect changes occurring during the modeling process. The issue of visualized structure size has been analyzed in detail. In the three-dimensional case, the volume of data required to identify significant structures grows according to a third-degree polynomial, in contrast to standard one-dimensional cellular automata. While this growth facilitates the organization of the modeling process, it simultaneously introduces challenges in visualizing the dynamics of changes, particularly regarding the ability of a human analyst to interpret the resulting three-dimensional image effectively. The initial number of cells that permits meaningful analysis of the generated constructions ranges from 10⁴ to 10⁶. The visualization of cellular structures is constrained not only by computational performance but also by the necessity to render each individual element with sufficient clarity, ensuring a distinct perception of both separate elements and the overall construction. The proposed solution can be applied to the modeling of dynamic processes that are amenable to formalization and representation as voxel-based structures. Approaches to the organization of data processing and visualization for three-dimensional cellular structures – taking into account both performance requirements and the accessibility of each representational element for analysis – have been successfully implemented and tested. The obtained results will support further computational experiments aimed at analyzing the development of three-dimensional cellular automata and analogous structures.

AN INTERACTIVE SYSTEM FOR SEMANTIC EDITING OF RASTER GRAPHICS BASED ON THE INTEGRATION OF MULTIMODAL GENERATIVE APIS

D. V. Chornobryvets — 2026-05-30

This paper investigates the process of automated semantic editing of raster images using artificial intelligence methods. The relevance of the study is обусловлена high computational demands of modern generative models, which require powerful graphics processing units (GPUs) to perform inpainting operations, as well as the limited flexibility of cloud-based services in terms of precise spatial control over editing. This creates a significant barrier to the accessibility of intelligent image editing tools for users with limited computational resources. The aim of the work is to improve the accessibility and efficiency of semantic image editing processes by distributing the computational workload between the client-side and server-side components of the system. The proposed approach combines local tools for spatial mask generation with the use of a cloud-based multimodal API (Gemini 3 Flash Image) to perform generative transformations. As a result, a lightweight desktop application with a modular client-server architecture has been designed and implemented. The key features of the system include asynchronous multithreaded processing of network requests, which ensures a responsive graphical user interface, as well as the use of reverse compositing algorithms for seamless integration of generated fragments into the original image. A real-time binary mask generation mechanism based on cursor coordinates has been implemented, enabling high-precision selection of regions of interest. The obtained results are explained by the effective offloading of tensor computations to cloud infrastructure while maintaining local control over the editing process. Experimental evaluation confirmed the feasibility of performing complex image transformations on low-performance devices without loss of output quality. The practical significance of the work lies in the possibility of using the developed system by digital artists, designers, and researchers for rapid prototyping and image editing without the need for specialized hardware.

ARCHITECTURE AND METHOD FOR ADAPTIVE PERSONALIZATION IN A DISTRIBUTED E-LEARNING SYSTEM BASED ON AGENT TECHNOLOGIES

N. H. Axak — 2026-05-30

The paper develops an architecture of a distributed personalized e-learning system based on agent technologies and proposes a method for adaptive personalization of the learning process that supports dynamic formation of individual learning trajectories with regard to the current state of the student. The relevance of the study is determined by the need to improve the effectiveness of e-learning in the context of distance and blended learning, the growth of digital educational content, and the demand for intelligent learner support in real time. Unlike conventional LMS platforms that mainly rely on test results, activity logs, and statistics of content access, the proposed approach takes into account the student’s behavioral and psychophysiological parameters as indicators of cognitive state, concentration level, fatigue, and emotional engagement. The system architecture includes a student state monitoring module, an agent-based decision-making environment, data synchronization tools, a unified database, and mechanisms for integration with learning management systems. Within the proposed method, the tutor agent applies the Q-learning algorithm to select adaptive pedagogical actions, while the student’s state parameters are integrated into the reward function to adjust learning content, presentation pace, and task complexity. Particular attention is paid to the coordination of interactions between system components, synchronization of data between the monitoring module and the agent’s cognitive model through a unified database, and privacy protection based on the Local Inference architecture. To validate the feasibility and effectiveness of the proposed solutions, simulation modeling was carried out in the NetLogo environment. The experimental results confirmed the effectiveness of the proposed architecture and method: the speed of personalization of learning trajectories increased by 38 %, academic performance improved by 28 %, and students’ cognitive discomfort decreased. The obtained results demonstrate the feasibility of using distributed agent-based systems for the development of intelligent e-learning platforms.

METHOD FOR IDENTIFYING PROMISING RESEARCH TOPICS BASED ON HYBRID TRANSFORMER ARCHITECTURES USING SCIENTOMETRIC DATABASES

O. V. Moiseienko — 2026-05-30

The article addresses the critical challenge of automating the identification of promising research topics within largescale scientometric databases. The exponential growth of scientific publications creates significant information overload, complicating the discovery of latent trends. To solve this, the study proposes a universal method based on a hybrid deep learning architecture that integrates the strengths of Convolutional Neural Networks (CNN) and Transformer architectures. The core of the proposed architecture utilizes a CNN layer as a local feature extractor to identify stable terminological patterns (n-grams) within article abstracts. This is followed by a cascade of three Transformer layers with a MultiHeadAttention mechanism, which models global semantic dependencies, ensuring high relevance in specialized domains. To handle the significant class imbalance typical of scientometric data (where «High Impact» topics account for approximately 28 %), the Focal Loss function was implemented. This allows the model to concentrate on «hard» examples, significantly improving the detection of emerging breakthrough directions. The method was validated using a Scopus metadata dataset from the IoT Security domain, comprising 4833 publications from 2020–2025. Experimental results show that the model achieves a Recall of 0.80 and an F1-score of 0.61, outperforming previous LSTM-based approaches. Such a balance of metrics is methodologically justified for research discovery tasks, where minimizing the risk of missing a «breakthrough» topic (Type II error) is the primary priority. Furthermore, the approach includes a trend forecasting module based on linear regression of citation time series, enabling the prediction of a topic’s future popularity. The developed solution is universal and can be adapted to any scientific or applied field to accelerate research discovery and support decision-making in grant allocation.

MODELS AND METHODS OF OPERATIONAL MANAGEMENT OF MOBILE PLATFORMS IN CONDITIONS OF DYNAMIC INSTABILITY AND INFORMATION UNCERTAINTY

Yu. M. Molodozhon — 2026-05-30

The paper is devoted to the problem of ensuring dynamic stability of operational control systems for mobile platforms under conditions of high informational uncertainty inherent to modern Smart City logistics environments. The study is concerned with the degradation of traditional telemetry sources caused by the absence of full IoT sensor coverage and the suppression of GNSS/GPS signals, which leads to the transformation of the system into a nonlinear dynamic regime with features of deterministic chaos. The main objective of the research is to develop a method for real-time operational control of mobile platforms based on the integration of chaos theory tools for assessing and predicting the stability of logistical plans. The paper considers the application of nonlinear dynamics, time-series analysis, phase space reconstruction using Takens’ theorem, and information theory approaches to evaluate system uncertainty. It is proposed to use the largest Lyapunov exponent as a quantitative indicator of system sensitivity to small perturbations. As it is shown in the paper, when λ > 0, the system enters a chaotic regime characterized by exponential divergence of trajecto- ries and loss of planning reliability. This allows early identification of bifurcation points, where minor deviations lead to critical instability of the entire service schedule. The paper describes a method for reconstructing the phase space of the system based on indirect telemetry obtained via RFID verification. This approach makes it possible to estimate hidden dynamics of waste accumulation processes even in the absence of direct sensor measurements. Special attention is paid to the improvement of a three-level control architecture by integrating Edge Computing and swarm intelligence principles. It is shown that such an approach enables decentralized self-organization of mobile platforms and realtime task redistribution under communication loss conditions. The results of simulation experiments demonstrate that the proposed method improves the robustness of routing plans, reduces system entropy, and enables proactive adaptation to dynamic disturbances. The practical significance of the work lies in the development of resilient Smart City systems capable of maintaining operational efficiency under conditions of incomplete data and external disruptions

МОДЕЛІ ТА МЕТОДИ ІНТЕЛЕКТУАЛЬНОГО КЕРУВАННЯ АВТОНОМНИМ РУХОМ МЕРЕЖІ МОБІЛЬНИХ СИСТЕМ У ДИНАМІЧНОМУ АНТРОПОГЕННОМУ СЕРЕДОВИЩІ

D. V. Patlai — 2026-05-30

The article develops theoretical and methodological foundations and proposes architectural solutions for intelligent control of autonomous movement in heterogeneous networks of mobile robotic systems. The study addresses the problem of robotic platform operation in dynamic anthropogenic environments characterized by uncertainty, variable infrastructure constraints, and complex social interactions between technical agents and human participants. Such conditions require adaptive coordination mechanisms capable of ensuring safe and efficient collective behavior of heterogeneous autonomous systems. The aim of the research is to develop a unified multi-agent platform that enables synergistic interaction between ground unmanned vehicles (UGV) and unmanned aerial vehicles (UAV) for real-time optimization of logistics and monitoring processes in dynamically changing environments. Particular attention is given to ensuring coordination stability under partial observability and communication limitations. The methodological framework combines graph-theoretic representations of network topology, intelligent trajectory planning methods based on social penalty functions, and multi-criteria optimization techniques. A coordination model is proposed that incorporates dynamic estimation of human flow density and predictive motion vectors of environmental agents. The control architecture integrates hierarchical decision-making mechanisms allowing adaptive redistribution of tasks between heterogeneous agents depending on environmental conditions and operational constraints. The scientific novelty of the research lies in the development of an adaptive agent-selection algorithm based on cascade analysis of physical, meteorological, and social constraints. Unlike existing approaches, the proposed solution integrates principles of social navigation directly into a multi-level network control architecture, enabling reduction of interaction conflicts and improving coordination stability in dense human environments. Simulation-based validation demonstrated the feasibility of the proposed architecture under dynamically changing environmental conditions. The obtained results confirmed stable coordination of heterogeneous agents and adaptability of the control strategy to variations in social density, mission complexity, and communication limitations The practical significance of the study lies in the possibility of applying the developed architectural solutions and mathematical models to scalable autonomous urban logistics systems, last-mile delivery platforms, service robotics, and monitoring of complex infrastructure facilities. Future research directions include software implementation of the proposed methods in robotic simulation environments and quantitative evaluation of energy efficiency, scalability, and network resilience.

METHOD FOR ENSURING FAILURE-RESISTANT REMOTE CONTROL OF INTELLIGENT SYSTEMS IN THE LIVING ENVIRONMENT BASED ON MOBILE PLATFORMS

V. A. Permiakov — 2026-05-30

The main objective of the research is to justify and develop a method that ensures the complete functional autonomy of local home automation systems. The work is aimed at creating an architecture that retains the ability to control lighting, heating and security even in the absence of external communication channels and in the event of a centralised power supply failure, which is a critical shortcoming of modern cloud-based IoT solutions. The methodological basis of the research is the conceptual transition from the traditional cloud model to the fog computing paradigm. For practical implementation, a local server based on a Raspberry Pi 3B+ microcomputer was selected, which functions as a message broker using the MQTT protocol. The technical solution includes the use of a split-power supply circuit from an uninterruptible power supply (UPS) to eliminate energy losses due to double conversion. The software component is implemented in C++ to ensure low-level interaction with the GPIO interface, whilst the client mobile application is built on the Flutter platform using the ‘Local-First’ principle and the SQLite database for reliable local caching of information. The scientific novelty of the results lies in the development of a hybrid method for organising information exchange and power supply in intelligent systems. The proposed approach combines decentralised data processing on a local Edge gateway with direct DC power supply to actuators. This eliminates critical dependence on external cloud providers, removing the ‘single point of failure’ inherent in most existing commercial automation systems. The results of practical testing of the developed system demonstrated its high operational reliability and stability. It has been established that the system retains full controllability in critical scenarios involving simultaneous power failure at the facility and loss of internet connection. Localisation of the communication core has reduced the system’s response time to commands to a range of 5–10 ms, whilst also ensuring a high level of confidentiality, as the user’s personal data remains physically within the local network of the residential premises

TRAINING METHOD ON IMBALANCED DATA WITH ADAPTIVE WEIGHTING FOR SOFTWARE CODE VULNERABILITY DETECTION

O. V. Tazetdinov — 2026-05-30

The article is devoted to the development of a neural network training method on imbalanced data for the task of automatic software code vulnerability detection. In real-world software projects, the proportion of vulnerable code typically does not exceed 5–10 % of the total codebase, resulting in a significant class imbalance with ratios ranging from 10 to 100. Such imbalance leads to gradient dominance of the majority class and substantially reduces the ability of models to detect vulnerabilities, which constitutes their primary objective. An analysis of existing approaches to handling imbalanced data has been conducted, including resampling methods (Random Oversampling, SMOTE, Random Undersampling), static class weighting, and Focal Loss. A comparative evaluation of these approaches is presented with respect to their applicability to source code analysis tasks. It has been demonstrated that resampling methods do not work correctly with the discrete structures of program code, static weights fail to adapt to changes in sample difficulty during the training process, and Focal Loss exhibits sensitivity to hyperparameters under conditions of extreme class imbalance. An adaptive weighting method is proposed that combines three components: class weighting with parametric control of correction strength based on the inverse class frequency raised to a tunable power, dynamic assessment of sample difficulty based on prediction uncertainty measured through classification entropy, and a curriculum learning component that ensures gradual introduction of complex samples through an exponential pacing function. Additionally, an adaptive minibatch sampling strategy has been developed that dynamically adjusts class ratios depending on training progress and guarantees the representation of the minority class in each mini-batch, addressing the problem where standard random sampling results in most batches containing no minority class examples. A mathematical formalization of all method components is provided, including weight normalization mechanisms ensuring unit mean weight and partial compensation of sampling bias through a tunable balance parameter. The research results can be applied to improve the effectiveness of automated software security analysis systems

COMPARATIVE ANALYSIS OF DETERMINISTIC FINITE AUTOMATA MINIMIZATION ALGORITHMS WITH RESPECT TO IMPLEMENTATION EFFICIENCY

Ie. V. Tysh — 2026-05-30

The problem of minimizing deterministic finite automata, which belongs to the fundamental problems of automata theory and formal languages, is investigated. The practical importance of the minimization problem is associated with syntactic analysis, digital circuit optimization, compiler design, and the construction of search and lexical analyzers. Particular attention is paid to the comparison of the efficiency of implementations of the most common automata minimization algorithms, namely the table-filling method, Hopcroft’s algorithm, and Brzozowski’s algorithm. An experimental study is carried out on several types of deterministic automata, including random automata, lexical automata, automata with high transition density, and automata with a large number of redundant states. For each algorithm, execution time and memory consumption are determined depending on the number of states, the alphabet size, and the nature of transitions between states. Based on the experimental results, it is demonstrated that Hopcroft’s algorithm exhibits the best or near-best performance in most of the considered cases and is characterized by high stability and good scalability as the size of automata increases. The analysis of Brzozowski’s algorithm reveals significant variability in its efficiency, as well as its advantages for automata with a large number of states, alongside a substantial degradation in performance for automata with dense transitions. It is experimentally established that the table-filling method demonstrates the worst scalability and is therefore mainly suitable for automata of small size. The obtained results are consistent with theoretical complexity estimates of the considered algorithms and can be used to justify the selection of a minimization method for deterministic finite automata in practical applications

RANSOMWARE: MECHANISM OF ACTION AND METHODS OF PROTECTION

S. D. Luchyk — 2026-05-30

Among the many contemporary digital threats, malicious software in the ransomware category occupies a dominant and distinctive position, posing an unprecedented danger not only to data confidentiality but also to human safety and the resilience of entire sectors of the economy, including critical infrastructure and the public sector. Global digitalization, the transition to cloud technologies, and the expansion of corporate network boundaries have significantly increased the attack surface. The impact of ransomware on organizations, as it continues to evolve and become more sophisticated, results in enormous financial losses, paralysis of business processes, and reputational damage. This necessitates a fundamental reassessment of approaches to information security and gives this topic considerable social and scientific significance. The aim of this article is to provide a comprehensive examination of the ransomware phenomenon – from typological classification and historical development to a detailed study of the technical mechanisms of attack execution and the development of comprehensive practical recommendations for protection. The article identifies and outlines the historical stages in the emergence and spread of ransomware: from basic encryptors to modern “Ransomware-as-a-Service” (RaaS) business models, which have substantially lowered the barrier to entry for cybercriminals. The study examines the algorithm of a modern ransomware attack, with a detailed description of its key phases: initial compromise (through phishing, exploitation of RDP vulnerabilities, or zero-day vulnerabilities), lateral movement, exfiltration, and encryption. Based on the analysis conducted, an effective ransomware protection system is proposed, grounded in the Zero Trust concept and combining technological, organizational, and procedural components. Organizations need to implement rigorous patch management to ensure the immediate updating of vulnerable services, mandatorily use multi-factor authentication (MFA) for all entry points, and regularly conduct practical phishing simulations for personnel. Technical protection should include strict network segmentation and be based on the mandatory deployment of EDR/XDR-class solutions capable of automatically blocking anomalous activities before irreversible consequences occur. It is critically important to implement end-to-end cryptographic encryption of confidential data at rest, which will render such data useless to hackers in the event of a leak, as well as to strictly adhere to the “3-2-1” backup rule with isolated copies. Every institution should develop, formally approve, and regularly test an Incident Response Plan, while establishing in advance a communication channel with governmental protection agencies such as CERT-UA.

POST-QUANTUM CRYPTOGRAPHY IN THE JAVA ECOSYSTEM

Yu. F. Oleksiichuk — 2026-05-30

The completion of NIST standardization in 2024, with the publication of ML-KEM (FIPS 203), ML-DSA (FIPS 204), and SLH-DSA (FIPS 205), has confronted Java developers with a concrete practical question: how to integrate these algorithms into real-world applications using the available platform tools. The Java ecosystem offers several fundamentally different integration paths depending on the JDK version; however, a systematic description of these approaches from a practitioner’s perspective remains insufficiently represented in the scientific literature. This paper analyzes the evolution of post-quantum cryptography support in the Java platform from JDK 17 through JDK 25, with an outlook toward JDK 27. The Java Cryptography Architecture and the role of the provider model as a foundation for implementing the crypto agility concept are examined. Two API levels of the BouncyCastle 1.83 library – the JCA provider and the low-level lightweight API – are compared, and the appropriate use cases for each are identified. It is established that native support in JDK 25 covers only ML-KEM and ML-DSA, while SLH-DSA remains available exclusively through BouncyCastle across all JDK versions, demonstrating the asynchronous nature of NIST standardization and JDK platform integration. Practical code examples are developed and analyzed for two typical scenarios. The first involves hybrid JWT token signing using both classical ECDSA and post-quantum ML-DSA simultaneously in a Spring Boot application, ensuring backward compatibility with existing infrastructure. The second addresses secure inter-service communication via ML-KEM with public key authentication using ML-DSA to protect against man-in-the-middle attacks. It is shown that direct use of ML-DSA in JWT is incompatible with existing libraries due to the absence of corresponding algorithms in RFC 7515 and RFC 7518, and practical mitigation approaches for the transition period are proposed, including reference tokens and token introspection. A four-phase migration strategy for enterprise Java systems is proposed: inventory of cryptographic dependencies, introduction of crypto agility through centralized algorithm configuration in Spring Boot, a hybrid mode of parallel classical and post-quantum algorithm usage, and full migration following PQC TLS standardization in JDK 27. The results of this work can be directly applied by Java developers when planning and implementing the migration of enterprise applications to postquantum cryptographic standards

ABOUT THE SECURITY MODEL OF DUAL-CHANNEL DEVICES WITHOUT CHANNEL RESTARTС

S. А. Razghonov — 2026-05-30

The majority of technical devices in transport have their own heating control. The article examines the power supply for the functional safety of dual-channel transport devices of robotic on-board systems. Current research into the safety and reliability of dual-channel monitoring devices has not been given sufficient respect. Thus, in other regulatory documents, for reliability, a comprehensive indicator of reliability (readiness coefficient of the device) is indicated by the appearance of average focus on vidmova to the sum of average focus on At the end of the day, at the middle hour of renewal. The values of the availability coefficient are determined for the purposes of operation of dual-channel devices if the average parameter for the flow of outputs and the average cost of renewal are deprived of steel. Such an interpretation conveys that any kind of device is revealed and then immediately updated, so that the control methods are ideal. It is difficult for real minds to create control mechanisms to provide a further guarantee of the identification of your identity. This article examines an approach that formalizes applied problems of functional security and allows one to find optimal solutions to applied problems. The safety and reliability of dual-channel control devices have been studied for many years now. The formulaic expressions of stationary and international networks have been removed for updating dual-channel devices with the required hardware control. These formulas allow us to establish real characteristics of the effectiveness and reliability of control methods, which promotes the reliability of the results of system analysis. It is clear that the reliability of the transport device lies in the power to preserve efficiency at a given time by preserving the performance characteristics of the relevant technical minds of the operation. This power is closely related to economical operating parameters. In the end pouch, economical parameters, in current minds, play a vital role in both the manufacturing system and business processes of operation. Take a brief look at the hourly demonstrations of the safety and reliability of the dual-channel controlled transport device of robotic on-board systems. What is important is the display of triviality between the vids and around the visiting vids, as well as the time of renewal and the time of the simple structure

КОМПЛЕКСНА СИСТЕМА ЗАХИСТУ ІНФОРМАЦІЇ З ПОЗИЦІЙ СИТУАЦІЙНОГО МЕНЕДЖМЕНТУ В ІНФОРМАЦІЙНО-ТЕЛЕКОМУНІКАЦІЙНИХ СИСТЕМАХ

Iu. V. Savchenko — 2026-05-30

The article proposes research into new and improved classical methods and means of information systems and message transmission technologies, which additionally increase the requirements for implementing a high level of potential security of their standard tactical and technical characteristics. Comprehensive information protection systems are studied from the standpoint of situational security management in information and telecommunication systems. The set of components of an informatization object is generally formed as a set of three interdependent subgroups (systems). They include the human factor, which forms a biosocial system, technical means, their systems and premises for placement, as well as computer software, which acts as an intellectual mediator between man and technology. Ensuring information security is a continuous and multi-stage process. It includes monitoring the level of information security, analyzing and eliminating vulnerabilities in the protection system, as well as developing and implementing the most effective methods of modernization and progressive technological solutions. In modern conditions, the comprehensive use of available protection tools, in particular highly professional training of users and their strict adherence to information protection rules, are becoming key factors in ensuring the proper level of security. However, it is important to remember that no protection system can be absolutely flawless. It is worth noting that all principles of information security have the same weight: it is hardly advisable to single out more or less important ones among them. Therefore, in the design of a comprehensive information protection system, it is necessary to consider all principles as components of a single holistic mechanism that provides a synergistic effect. To support decision-making processes, a structural- linguistic functional scheme for the use of information and telecommunication systems has been developed. Information protection systems are an organized set of objects and subjects that implement methods and means of protection using a whole range of measures necessary to perform security tasks of modern information technologies. The effectiveness and reliability of such systems directly depends on their balance and comprehensive approach, because the asynchrony between individual components significantly increases the risks of «failures» in operation. The quality and reliability of protection are determined not only by the variety of constituent elements, but also by their completeness, which can be achieved by taking into account all relevant factors and circumstances. Shielding of electronic and digital devices is a necessary component of information security, and the use of anechoic chamber technologies significantly improves its quality. Awareness of the importance of a comprehensive approach to information protection consists of the following aspects: integration of local protection systems; ensuring the integrity of the entire system; guaranteeing comprehensive information protection

MATHEMATICAL MODEL AND SOFTWARE CALCULATOR FOR EVALUATING MEDIA CONTENT ENCRYPTION PARAMETERS

M. S. Svynarenko — 2026-05-30

In the context of the rapid development of digital technologies and the growing volume of multimedia content transmitted over open telecommunication channels, fundamental issues of information security are of critical importance. Multimedia data regularly become targets of cyberattacks and unauthorized access. The practical application of encryption requires consideration of numerous technical factors, as media content fundamentally differs from transactional data due to its specific entropy characteristics and varying compression potential. Despite the existence of theoretical research, there is currently a shortage of comprehensive mathematical models capable of organically combining performance evaluation, data size variation, and security levels into a single predictive system adaptable to the content type. The article presents a mathematical model and a software calculator for a comprehensive evaluation of multimedia data encryption parameters. The developed predictive model covers four types of media data (video, audio, images, documents) and five popular symmetric encryption algorithms (AES-128, AES-256, ChaCha20, Blowfish, Twofish). Symmetric encryption is considered an indispensable choice for the mass processing of large multimedia files due to its high performance speed. The proposed mathematical apparatus allows for accurate forecasting of the encrypted file size, encryption time, security level, and computational resource requirements with an average error of less than 5 %. To account for the stochastic nature of the processing, a corresponding component was introduced into the model, which allowed the formation of realistic confidence intervals. In addition, the study formulates and solves the problem of multi-criteria optimization for algorithm selection. By applying the Pareto optimality method and normalized weighted sums, the ability to flexibly balance cryptographic security and hardware performance is provided. The forecasting models were successfully verified through full-scale experiments. The validation results proved the high accuracy of the developed apparatus: the root mean square error (RMSE) was 0.21 s, and the maximum relative error did not exceed 3.2 %. It was established that the file size and hardware performance have a decisive influence on the encryption time, while the impact of the media content type is secondary. The practical significance of the work is confirmed by the development of software – an interactive web calculator that encapsulates the mathematical apparatus under an intuitive interface. This software tool is implemented as a single-page application (SPA) capable of generating dynamic recommendations, such as the feasibility of switching to the ChaCha20 algorithm on low-power devices. The created tool is intended for practical use by information security specialists and can be effectively integrated into DevSecOps processes, as well as applied by architects when designing video surveillance systems, streaming platforms, and PACS medical databases.

POSSIBILITIES OF USING TECHNOLOGIES BASED ON ARTIFICIAL INTELLIGENCE TO BUILD MATHEMATICAL MODELS FOR ASSESSING THE EFFICIENCY OF USING OWN RESOURCES IN SMALL BUSINESS

O. M. Vytvyts’ka — 2026-05-30

The purpose of the study is to develop theoretical and methodological principles and mathematical approaches to building models for assessing the efficiency of using own resources in small business using technologies based on artificial intelligence. The object of the study is the process of using own resources in small business and its quantitative reflection in the system of mathematical assessment of efficiency. The paper reveals the theoretical and applied principles of using technologies based on artificial intelligence to build mathematical models for assessing the efficiency of using own resources in small business. It is ubstantiated that in conditions of limited financial, labor, material, time and information resources, mathematical modeling is the key basis for forming an objective analytical vision of the effectiveness of economic activity. The approaches to interpreting the own resources of small businesses as a multi-component system are generalized, the effectiveness of which should be assessed through quantitative dependencies, objective functions, a system of constraints and integral indicators. It is determined that technologies based on artificial intelligence provide the opportunity to identify hidden patterns, take into account nonlinear relationships between parameters, specify the weights of factors, increase the accuracy of forecasting and adapt mathematical models to changes in the internal and external environment. Special emphasis is placed on the mathematical component of the study, in particular on the importance of formalizing variables, building functional dependencies, assessing the impact of factors and optimizing the use of resources. It has been proven that the use of artificial intelligence technologies in combination with economic and mathematical tools contributes to increasing the validity of management decisions, reducing the level of subjectivity in assessment and forming the basis for ensuring the sustainability and development of small businesses

INNOVATIVE STRATEGY FOR THE DEVELOPMENT OF LOGISTICS SERVICE PROVIDERS AMIDST DIGITALIZATION AND EVOLVING SECURITY CHALLENGES

T. M. Denysenko — 2026-05-30

The article explores the theoretical and methodological foundations and develops practical recommendations for forming an innovative development strategy for logistics service providers amid the active digitalization of the economy and persistent security challenges. The relevance of the topic is driven by the need to adapt Ukraine’s logistics sector to martial law conditions, infrastructure destruction, and the global transformation of business processes under the influence of Industry 4.0 technologies. The authors define the essence of a logistics enterprise’s innovation strategy as a comprehensive adaptation program based on the implementation of advanced technological, managerial, and process solutions. Particular attention is paid to the technological component, specifically the integration of Internet of Things (IoT) systems, which enables end-to-end cargo monitoring (Track & Trace) and the creation of «smart warehouses». The role of Big Data and advanced analytics as the intellectual core of logistics is justified, ensuring route optimization (resource savings of up to 15–20 %) and predictive fleet maintenance. The paper provides a detailed analysis of the Industry 4.0 concept, which transforms logistics into a «smart» ecosystem through the use of automated guided vehicles (AGVs), “dark warehouses” and digital twins. The advantages of blockchain technologies and smart contracts in ensuring supply chain transparency and automating financial settlements are highlighted. A significant portion of the study is devoted to logistics management in conditions of instability. The transition from the “Just-in-Time” model to a “Just-in-Case” strategy is substantiated, involving the formation of buffer stocks and the decentralization of warehouse networks. A SWOT analysis of a logistics enterprise was conducted, serving as the basis for a strategic decision matrix that combines route flexibility with enhanced cybersecurity and physical asset protection. The result of the study is a conceptual framework for a digital transformation model of logistics services, integrating technological, operational, and strategic management levels. The proposed model aims to increase enterprise resilience and create unique value propositions for customers in critical conditions

APPLIED HR ENGINEERING TOOLS IN THE AUTOMATED SYSTEM FOR STRATEGIC MANAGEMENT OF ENTERPRISE HUMAN RESOURCES POTENTIAL

N. I. Novalska — 2026-05-30

The article is devoted to the study of the practical application of HR engineering tools for systemic and strategic management of the enterprise’s human resources. An analysis of HR engineering as a holistic tool for strategic design of the architecture of personnel processes in an organization, which integrates business strategy directly into the structure of HR processes, is carried out. The theoretical basis of HR engineering is considered, in particular the role of HR engineering in the digital architecture of the enterprise and the principles of its implementation. An analysis of key segments and tools of the digital HR ecosystem is carried out. The importance of taking into account differences in the legislation of Ukraine and other countries when making a decision on the use of foreign tools of the digital HR ecosystem in the practical activities of domestic enterprises is substantiated. An example of the interdependence of the functioning of digital tools of the socio-technical system based on an automated employee development cycle using the “Performance Management” module is shown. A comparative characteristic of HRM systems that are actively used on the Ukrainian market as platforms for engineering management processes is provided. An algorithm for the practical implementation of HR engineering has been developed, in particular the stages of HR process redesign from the “as is” audit to the “to be” design. The qualitative transformation of HR processes before and after the redesign has been visualized. A comparative characteristic of HR processes in the “as is” and “to be” models has been presented. The issue of the economic efficiency of implementing automated HR processes based on HR engineering has been considered, in particular, the performance indicators of using modern digital technologies in the process of personnel management. Examples of the use of HRM systems in the practice of foreign and domestic enterprises in various fields of business activity have been studied

COMMUNICATION STRATEGY IN THE FIELD OF DEVELOPING THE INNOVATIVE POTENTIAL OF FIFTH-GENERATION TRANSPORT

V. V. Ohlikh — 2026-05-30

In this article, the authors substantiate the theoretical and methodological foundations for the role of scientific institutions in shaping Ukraine’s innovative post-war recovery model, with an emphasis on the development of intermodal transport, highspeed, and maglev transport. The study is based on the thesis of the need to move from the paradigm of rebuilding destroyed infrastructure to a model of endogenous innovative growth, within which the state and scientific institutions view transport infrastructure as a strategic investment in long-term development. The theoretical basis of the study is formed by the concepts of endogenous technological progress, national innovation systems, and the ‘entrepreneurial state.’ The authors argue that the development of high-speed rail systems and magnetic levitation technologies provides a multiplier economic effect, strengthens agglomeration processes, integrates Ukraine into trans-European transport networks, and increases the competitiveness of the national economy in line with the strategic guidelines of the European Commission. The authors focus on the communication policy of scientific institutions, the National Academy of Sciences of Ukraine, and higher education institutions, viewing it as a tool for shaping public demand for innovation. The study demonstrates that scientific institutions, through effective science communication, ensure public support for long-term infrastructure projects in the post-war period. Particular attention is paid to the communication policy of scientific institutions, the National Academy of Sciences of Ukraine, and higher education institutions as a tool for shaping public demand for innovation. It has been proven that effective science communication is a necessary condition for supporting long-term infrastructure projects in the post-war period. A multidimensional model for assessing the effectiveness of communication policy in the field of maglev and high-speed transport is proposed, which includes allocation effect, adaptive effect, X-efficiency and socio-emotional effects. The model combines quantitative and qualitative indicators and accounts for both direct economic results and long-term institutional transformations. It is concluded that the integration of an innovative transport strategy, institutional modernisation of scientific institutions and systematic communication activities creates the basis for the formation of a new model of economic development in Ukraine, based on intellectual capital, high-tech infrastructure and public trust in science

ECOLOGICAL STANDARDIZATION AND CIVIL PROTECTION MANAGEMENT UNDER MARTIAL LAW AT CRITICAL INFRASTRUCTURE FACILITIES

I. V. Perkun — 2026-05-30

Relevance. Under the conditions of full-scale armed aggression against Ukraine, the anthropogenic load on the natural environment has undergone fundamental and catastrophic changes. The traditional planned technogenic impact has transformed into chaotic, massive, and highly toxic pollution of a multimedia nature. In such conditions, the existing static system of ecological standardization, based on sanitary and hygienic maximum permissible concentrations (MPC) and maximum permissible emissions (MPE), has proven methodologically incapable of effectively responding to unpredictable challenges. This creates a critical gap in the national life safety system and limits the ability of civil protection (CP) units to implement scientifically sound operational management of ecological and technogenic risks during the mitigation of attacks on critical infrastructure facilities. Goal. To develop and scientifically substantiate innovative methodological approaches for adapting the anthropogenic load standardization system, as well as to create a conceptual model for its integration with civil protection management mechanisms under martial law and post-conflict recovery (using the example of the oil and gas industry). Methodology. The study utilizes a comprehensive approach combining systemic and risk analysis methods, the theory of territorial ecological capacity, the concept of socio-ecosystem resilience, and principles of mathematical modeling of pollutant dispersion in the atmosphere. Results. The fundamental necessity of implementing flexible, multi-level standardization tools has been proven. The implementation of a mechanism for temporary emergency standards (MPC-EMERGENCY), adapted similarly to international AEGL and ERPG standards, is proposed for use directly in active combat zones and areas of critical infrastructure damage. A concept of a unified digital management contour has been developed, in which real-time local environmental monitoring data, processed using geographic information systems (GIS) and artificial intelligence (AI) algorithms, serve as automatic triggers for activating specific CP protocols (evacuation, sheltering, zone isolation). Additionally, the concept of transitional standardization (MPC-TRANSITION) for the safe management of destruction waste and land reclamation is substantiated. Conclusions. It is proven that adaptive ecological standardization must evolve from a passive tool for recording environmental damage into a proactive, preventative management mechanism within the civil protection system. Integrating ecological criteria into safety protocols will minimize sanitary and hygienic losses among the population and rescuers, and ensure the sustainable post-conflict recovery of territories in accordance with European “Build Back Better” principles

CREATION OF A MATHEMATICAL MODEL OF A FIVE-INDICATION STATION EXIT SIGNAL IN THE FORM OF A FINITE-STATE AUTOMATON

N. V. Malovichko — 2026-05-30

The work is aimed at improving the operational functional reliability of microprocessor-based station interlocking systems by verifying the correctness of system operation during commissioning using simulation models of trackside equipment. Methodology. Various types of mathematical models were analyzed. It was determined that, for the given task, the most effective approach is the use of models based on finite discrete automata, since such a model allows the interaction between the controlled object and the microprocessor-based part of the system to be easily implemented through the selection of input and output parameters. It is proposed to use a Moore finite-state automaton with two output states (signal cleared and signal at stop) and five internal states (signal indication of the railway signal). A finite-state automaton was developed, and its input, output, and internal states were defined. State transition and output tables were constructed, sequential equations describing the automaton operation were derived, and their minimization was performed using an analytical method. The states of memory elements based on three RS flip-flops were determined, and the minimization of their encoding was carried out using Karnaugh maps. A structural diagram of the developed automaton was created, and the model operation was verified using computer simulation. For the first time, a mathematical model of a five-indication station signal with double-yellow aspects and a shunting indication has been developed in the form of a finite-state discrete automaton, which enables its use for simulating the operation of this object under various operating modes. The use of the proposed model makes it possible for the manufacturer to verify the correctness of system operation at the design stage, where the model can be implemented as software emulation without physical realization. It also enables verification of compliance with regulatory documentation during the system commissioning stage at a railway station, where a physical circuit simulating the operation of the signal using logic elements and flip-flops is employed

IMPROVING EQUIPMENT FOR DRYING FRUIT AND VEGETABLE RAW MATERIALS USING RENEWABLE ENERGY SOURCES

O. V. Omelchenko — 2026-05-30

The article states that the food industry plays a key role in the global demand for food products, while significantly affecting energy consumption and the state of the environment. Therefore, the primary task of the food industry should be to transition to a green course, namely, the reduction or recycling of waste heat in order to reduce energy consumption and control green house gas emissions. Analysis of scientific sources showed that recently energy-efficient technologies based on renewable energy sources have been used, namely heat pumps in the drying process of plant raw materials. An effective drying system is substantiated to reduce energy consumption, as well as minimize deterioration in the quality of dried products based on active heat recovery methods. A structural diagram of the drying process with a heat pump using forced convection, operating in a closed environment with full recirculation of dried air, is proposed. It is considered appropriate to consider a drying system with a heat pump as an interaction of three subsystems, the first of which is responsible for the drying chamber – a set of elements involved in the movement of air, where heated air circulates, passes through the raw material, picks up moisture and transfers it to the evaporator of the heat pump. This subsystem is considered as an open subsystem due to the exchange of energy with the heat pump. The second subsystem is a closed subsystem operating in a closed air circuit, where only energy exchange in the form of heat occurs through its boundaries, while moist air is not lost, but recirculated. The second subsystem includes a heat pump, the main elements of which are a compressor, condenser, evaporator and expansion valve. The third subsystem provides control of the drying process, which requires the installation of humidity and temperature sensors inside the drying chamber at the inlet to the evaporator and at the outlet from the condenser. The ability to transfer heat from one subsystem to another is a key factor in achieving optimization of energy consumption in the drying process. This allows for high drying efficiency using a heat pump and high quality of the resulting dried raw materials.

FORMATION OF AN ADAPTIVE MODEL OF THE CONTAINER TERMINAL FUNCTIONING TECHNOLOGY

S. M. Prodashchuk — 2026-05-30

Container terminals play a crucial role in organizing rail container transportation, as they contribute to the rapid and safe handling of cargo, while also optimizing logistics processes. However, in today’s environment, the existing technology for handling containers at terminals does not ensure uninterrupted operation, which worsens the quality of transportation services and does not meet all the needs of transportation stakeholders. Due to the downtime of containers and loading and unloading equipment, railways and other participants in the transportation process suffer losses. Therefore, instead of stationary cranes, the use of reach stackers is proposed in the work, and the relevance of their application is justified. The article formalizes the technology of container terminal operation in the form of a stochastic adaptive model. The criterion for the optimality of the objective function is the minimum operating costs when processing containers. The model takes into account the risk of possible financial losses associated with the failure of loading and unloading machines during container processing. Risk events are considered, which are proposed to include organizational and technical delays and force majeure circumstances in the operation of reach stackers. The risk of financial losses is represented by a polynomial distribution law and a second-order Erlang distribution density function. The proposed model of the container terminal operation technology adapts the existing technology to the unstable conditions of its operation, which allows to ensure safe working conditions and reduce the risks of railway transport workers. The study takes into account the risks of potential losses associated with the failure of loading and unloading machines during container handling. The proposed adaptive model can be used in the future when designing new container terminals, as well as for modernizing and restoring existing ones

UPDATED REFRIGERATION AGENTS AND THEIR APPLYING ON THE MARITIME TRANSPORT

А. І. Yesyev — 2026-05-30

The article examines the main groups of refrigerants and their impact on the environment. Ensuring the correct and safe technical use of refrigerants and preventing their negative impact on the environment is a very important task for preserving the Earth’s atmosphere at a natural level. The main types and properties of refrigerants used in ship refrigeration systems from the moment of their introduction to the present day are considered. Particular attention is paid to the requirements for refrigerants of the freons group and their impact on the environment. The main requirements of the International Convention in Vienna in 1985 and subsequent protocols, amendments and agreements enshrined in international legislation are given. As a result of many scientific developments and experiments by world scientists and scholars, it was determined that the most negative impact on the ozone layer that protects the Earth’s atmosphere is exerted by chlorine-containing refrigerants of the freons group. Information is provided on the developed and successfully implemented for application modern refrigerants that are safe for the environment. The analysis of the latest research and publications of domestic and foreign leading specialists and scientists in the field of refrigeration technology is taken into account. Refrigeration units used in maritime and river transport operate in difficult conditions and therefore special requirements are also imposed on them by the International Maritime Classification Societies (Register of Shipping). The necessity and possibility of retrofit ship refrigeration units designed, manufactured and installed in previous years to approved “ozone-safe” refrigerants is determined. The process of ensuring and implementing such a retrofit using the necessary equipment and modern technical means and devices is considered in detail. The necessity is proven and a method for conducting a leak test of the refrigerant system in ship conditions is proposed. Today, the production of artificial refrigeration is constantly being improved. Researchers and engineers are working to improve the efficiency of refrigeration machines, installations and cooling systems. Particular attention is paid to environmentally safe working fluids, which are refrigerants. In addition, active developments are underway regarding the most effective and safe refrigerants with a view to their use in the near future. The article identifies practical recommendations for retrofit of ship refrigeration systems to modern approved refrigerants, taking into account scientific research in this area, as well as many years of practical experience in practical operation

MECHANISM OF DYNAMIC ADAPTATION OF SIMULATOR PARAMETERS FOR IMPLEMENTING INDIVIDUAL-AND-TEAM STRATEGIES IN AIR TRAFFIC CONTROLLER TRAINING

A. S. Palonyi — 2026-05-30

The paper presents mechanism for dynamic adaptation of simulator content aimed at implementing individual-and-team strategies in air traffic controller (ATCO) training within a competency-based learning paradigm. The relevance of the study is determined by the transition of ATCO training to ICAO- and EASA-based competency models, as well as by the need to improve simulator efficiency under increasing traffic complexity, staffing constraints, and stringent flight safety requirements. The purpose of the paper is to design mechanisms for dynamic control of simulator parameters that adapt the scenario to the individual-and-team state of trainees. The research combines systems analysis, competency-based training and assessment principles, Bayesian Knowledge Tracing for estimating the probability of mastering specific skills, and interpretable machinelearning models for explaining the team result. A cyclic six-module architecture of an adaptive simulator is proposed. It includes behaviour monitoring, diagnostics of risk and good-practice indicators, prediction of skill acquisition, dynamic scenario adaptation, explainable assessment, and post-session reporting. The study formalizes the session state vector, workload index, skill-deficit index, and the rule of wave-like complexity variation based on the logic “increase – peak – recovery”. It is shown that adaptation should be not only quantitative but also targeted: depending on the dominant deficit, the system selects a focused event from a library of scenario interventions without driving the team beyond the productive training zone. Gradient boosting models combined with SHAP analysis are proposed to explain team assessment and to identify individual, negative, positive, and compensatory contributions of team members. The practical value of the results lies in creating a foundation for a new generation of simulator systems capable of maintaining trainees in a productive workload zone in real time, generating a posttraining report for instructor, and increasing the precision of corrective pedagogical influence

RESEARCH ON THE EFFECTS OF DELAYS IN THE FORMATION OF FREIGHT TRAINS ON THE RAILWAY NETWORK OF UKRAINE

A. M. Kyman — 2026-05-30

The article presents the results of a study of time-lag relationships between the volumes of wagons accepted for transportation and train-hours of delays of freight trains on the railway network of Ukraine. The aim of the study is to identify and quantitatively assess the temporal inertia of delay formation in the railway transportation process in order to substantiate the possibility of forecasting the development of network congestion and timely identification of bottlenecks in the railway network. The research is based on operational data of JSC Ukrzaliznytsia on wagon loading volumes and the duration of idle time of abandoned trains on the network. To analyse temporal relationships, cross-correlation analysis was applied using the Pearson linear correlation coefficient and the Spearman rank correlation coefficient. This made it possible to evaluate both linear and monotonic relationships between the studied indicators. Calculations were performed for lags in the range of up to 34 days, which allowed the identification of both short-term and medium-term inertial effects in the functioning of the railway system. The results of the analysis revealed a statistically significant time-delayed relationship between changes in the volumes of wagons accepted for transportation and train-hours of delays. It was shown that the strength of the correlation gradually increases with the growth of the lag and reaches its maximum values in the medium-term interval of 15-23 days, where the Pearson correlation coefficient reaches up to 0.66. The obtained results indicate the presence of pronounced temporal inertia in the functioning of the railway transportation process, when the consequences of increased traffic volumes manifest themselves with a significant time delay. In addition, spatial heterogeneity of lag effects was identified at the level of individual railway stations, where peak lags vary from 1 to 29 days depending on the role of a station in the network and its technological capacity. The obtained results demonstrate the potential of lag analysis for identifying critical periods of network congestion formation and for substantiating decisions on the introduction of temporary restrictions (conventions) on freight dispatching. A rule is proposed for determining the optimal time interval for introducing such conventional restrictions on the acceptance of freight for transportation. The practical significance of the study lies in forming an analytical basis for the development of decision-support systems aimed at enabling proactive management decisions for the early identification of critical bottlenecks within the railway network

INFLUENCE OF THE EU-UKRAINE SOLIDARITY LANES INITIATIVE ON THE TRANSFORMATION OF RAILWAY GRAIN EXPORT LOGISTICS IN UKRAINE IN 2022-2025

O. H. Strelko — 2026-05-30

The article examines the influence of the EU-Ukraine Solidarity Lanes initiative on the transformation of railway logistics for grain exports from Ukraine during the period 2022-2025. The relevance of the study is determined by the profound disruption of traditional export logistics caused by the full-scale war, which resulted in the blockade and severe restriction of operations at the Black Sea ports. Prior to 2022, the overwhelming majority of Ukrainian grain exports were transported through the ports of the Black Sea basin, forming a stable port-oriented export model. The loss of this infrastructure created a significant logistical crisis and required the rapid development of alternative transport routes to ensure the continuity of agricultural exports and maintain Ukraine’s role in global food supply chains. In response to these challenges, the European Union launched the EU-Ukraine Solidarity Lanes initiative, aimed at establishing alternative land transport corridors for the export of Ukrainian agricultural products through the territory of EU member states. The purpose of this study is to analyze how the functioning of the Solidarity Lanes affected the structure of transport flows and the organization of railway grain transportation in Ukraine. The research examines the prerequisites for the creation of these corridors and analyzes their transport structure, which combines railway routes to European Union countries, the use of Danube ports, and transshipment operations at border logistics hubs. Particular attention is paid to the role of major border railway nodes such as Chop, Mostyska, Izov and Yahodyn, which became critical elements in maintaining cross-border freight flows during the initial phase of the war. The study demonstrates that in 2022 the launch of the Solidarity Lanes led to a rapid increase in pressure on border crossings, expansion of grain transshipment operations, longer turnaround times for grain wagons, and a decentralized structure of shipment organization. In 2023 the railway transport system gradually adapted to the new logistics environment through the formation of route trains, the concentration of cargo flows at key hubs, and the growing importance of the Danube export direction. The partial restoration of maritime shipping in 2024-2025 resulted in a gradual decline in the relative importance of land corridors and the re-emergence of a port-oriented export model. The findings indicate that the Solidarity Lanes played a significant role in shaping a multimodal grain export logistics system, where railway transport acts as a key feeder mode delivering cargo to seaports, river terminals and border logistics hubs. The results of the study may contribute to improving the organization of international grain transportation and to the further development of Ukraine’s transport infrastructure within the framework of its integration with the European transport network

THE PROBLEM OF DISTRIBUTION OF SHUNTING LOCOMOTIVES BETWEEN RAILWAY NETWORK TERMINAL STATIONS

S. V. Sushko — 2026-05-30

This article outlines the tasks related to ensuring the implementation of the shunting plan at stations, which will have to be addressed in connection with the allocation of a separate structural unit, the “Locomotive Company,” within the management structure of Ukrainian Railways. The article highlights the problems associated with developing a methodology for distributing shunting locomotives between stations in connection with the creation of a locomotive company within the management structure of Ukrainian railways and identifies possible ways to improve the method of determining the number of shunting locomotives at a station. The current methodology for determining the number of shunting locomotives at a railway station is analyzed in detail and found to be imperfect. Based on the results of the study, the dependence of the change in the required number of shunting locomotives on fluctuations in the volume of local car traffic arriving at each station of the railway network was determined, and organizational measures were proposed to help determine the required number of shunting locomotives depending on fluctuations in the volume of local car traffic. The work takes into account the unevenness of transport volumes, which leads to unevenness in the volume of shunting work when determining the required number of shunting locomotives at the station, and also develops algorithms for determining the required number of shunting locomotives during peak transport volumes. The results of the study can be used to make decisions on the rational distribution of shunting locomotives between stations in the railway network, as well as to organize interaction between the newly formed locomotive company and the structural divisions of the railway network station service

INTEGRATION OF TECHNICAL AND ECONOMIC TRAINING IN THE FORMATION OF PROFESSIONAL COMPETENCIES OF FUTURE ROAD TRANSPORT SPECIALISTS

S. М. Prystinskyi — 2026-05-30

The article addresses the problem of integrating technical and economic training in the formation of professional competencies of future automotive transport specialists under conditions of digitalization, development of transport logistics, and increasing requirements for economically justified decision-making. Based on the analysis of recent scientific studies, it has been established that existing educational approaches mostly implement technical and economic components separately, which reduces the effectiveness of forming integrated competencies required for professional activity in the transport sector. An integrated competency-based training model is proposed, grounded in the concept of a multidimensional educational space and taking into account the synergistic interaction of academic disciplines. The model provides a formalized representation of compe- tency formation through a system of weighting coefficients and interdisciplinary interaction parameters, enabling the assessment of the level of integration within an educational program. Transport logistics is identified as a key integrative component that ensures the connection between technical knowledge and economic reasoning in the process of professional decision-making. A quantitative approach to evaluating training effectiveness is introduced based on an integral indicator reflecting the levels of technical, economic, and integrated competencies. The practical significance of the proposed model lies in its applicability for optimizing curricula, improving training quality, and aligning educational outcomes with the needs of the modern transport services market. The results obtained can be applied in the design and modernization of educational programs for automotive transport specialists.

NEW STATISTICAL METHODS FOR SATELLITE IMAGE CLASSIFICATION

S. I. Alpert — 2026-05-30

Nowadays remote sensing of the Earth is one of the most efficient methods for acquiring information about the state, properties and spectral characteristics of the Earth’s surface objects. Classification of satellite images is a main task in remote sensing, that contains the assignment of each image pixel to a specific thematic class based on its spectral characteristics. The result of classification procedure is a thematic map, that shows the distribution of various surface types. Statistical classification methods are based on analysis of spectral characteristics of image pixels and their assignment to land cover classes. The maximum likelihood method is one of the most dependable and precise supervised classification methods. The main assumption of this method is that spectral characteristics of pixels within each class follow a normal (Gaussian) distribution. But it was noted, that this assumption is correct only for homogeneous natural surfaces such as water bodies or agricultural fields. This assumption is not valid for mixed cover types and heterogeneous urban territories. It was conducted a comparative analysis of maximum likelihood method applying three statistical distributions for representing spectral characteristics of land cover classes: normal distribution, exponential distribution, and Weibull distribution. The maximum likelihood criterion was applied for classification procedure and formulas of the log-likelihood functions were considered for these three distribution types. It was noted, that normal distribution is effective for classes with homogeneous structure such as, water surfaces, dense vegetation and paved roads. The exponential distribution is optimal for radar imagery classification. It describes intensities of radar signals from rough surfaces. The Weibull distribution is effective for heterogeneous classes with variable texture such as urban territories. This distribution is commonly used to model the amplitude characteristics of radar signals. The choice of statistical distribution should be justified for each specific land cover class. It was shown that exponential distribution is a special case of Weibull distribution. Future research directions include applying ensemble approaches combining various distribution types for different classes and integration with machine learning methods

METHODS FOR OPTIMIZING THE USE OF FREQUENCY AGGREGATION IN WI-FI 7 TO MINIMIZE LATENCY AND PACKET LOSS IN IOT SYSTEMS WITH LIDAR AND VIDEO CAMERAS

D. M. Karnaukh — 2026-05-30

The article investigates the influence of frequency aggregation mechanisms and Multi-Link Operation in wireless networks of the IEEE 802.11be standard (Wi-Fi 7) on the delay and packet loss indicators in heterogeneous IoT systems that integrate video cameras and LiDAR sensors. The relevance of the study is due to the rapid growth of sensor data volumes in smart city systems, autonomous transport, industrial automation and intelligent video surveillance, for which the stability of information delivery, minimization of marginal delays and preservation of time consistency of multi-channel streams are critical. The aim of the work is to provide theoretical justification and applied analysis of the effectiveness of Wi-Fi 7 multi-link mechanisms in reducing latency and packet loss in scenarios with a combination of video and LiDAR traffic, as well as to develop an adaptive model for distributing flows between frequency links taking into account the requirements of different data classes. The object of the study is the processes of transmitting heterogeneous sensor traffic in multi-frequency wireless networks, and the subject is the regularities of the influence of frequency aggregation and Multi-Link Operation on the quality of service indicators of real-time IoT systems. The methodological basis of the study is the methods of queuing theory, multi-criteria optimization, stochastic analysis of wireless networks and system modeling. A model for adaptive link selection, which is based on the assessment of the predicted delay, probability of loss and the level of channel congestion and is implemented in the form of a weighted decision-making criterion, is proposed. The model weights are adjusted according to the priorities of video and LiDAR traffic, achieving a balance between time stability, reliability and efficient use of the radio resource. The analysis shows that the use of Multi-Link Operation allows to significantly reduce the average and marginal data transmission delay by distributing the load between several partially independent access environments, reducing the frequency of retransmissions and the time of air occupation. It is shown that the greatest gain is achieved in high-load scenarios with a large number of clients, where single-frequency networks are characterized by QoS fluctuations. The proposed packet routing model provides a reduction in tail-latency and loss coefficient, which is critically important for maintaining sensor data synchronization and video stream stability. The scientific novelty of the work lies in the formalization of an adaptive model of traffic distribution between multi-frequency Wi-Fi 7 links, taking into account the specifics of heterogeneous sensor load and in establishing quantitative dependencies between multi-link architecture parameters and quality of service indicators. The practical significance of the results obtained lies in the possibility of their use in the design and optimization of wireless infrastructures for video surveillance systems, autonomous navigation, industrial Internet of Things, and sensor data fusion complexes operating in real time. Prospects for further research are related to the development of intelligent Multi-Link Operation control algorithms based on machine learning methods, the integration of multi-link mechanisms with edge computing technologies and next-generation mobile networks, as well as experimental verification of the proposed approaches in large-scale multi-cell environments with real sensor load

MODELING THE DEPENDENCE OF ENERGY CONSUMPTION ON PRODUCTION VOLUMES

N. V. Maiborodina — 2026-05-30

The article examines the dependence between production output (performance of works) and electricity consumption by enterprises of the Chernihiv region. The relevance of the study is determined by the necessity of increasing the efficiency of energy consumption under conditions of economic instability in the region. The analysis of descriptive characteristics showed the proximity of the mean value and the median for production volumes and electricity consumption by enterprises, which indicates the relative symmetry of the distributions and the absence of outliers in the samples. Negative skewness values indicated left-sided asymmetry, while negative kurtosis values characterized the distributions as flatter compared to the normal distribution. The standard deviation and the range of variation are significantly higher for the indicator of electricity consumption, which indicates greater variability of energy consumption compared to production volumes and confirms the higher sensitivity of energy consumption to external economic conditions. The obtained statistical characteristics confirmed the expediency of applying correlation and regression analysis to investigate the dependence between the specified indicators. For the quantitative assessment of the interrelationship between the indicators, a linear regression model was constructed. The correlation and determination coefficients, the standard error of regression, and the mean approximation error were calculated. The results of the analysis showed the presence of a close direct statistically significant relationship between production volumes and electricity consumption. The value of the coefficient of determination confirmed a high level of explanatory power of the model and the dominant influence of production volume on the formation of electricity demand. Verification according to Student’s and Fisher’s criteria confirmed the statistical significance of the model parameters and the model as a whole. The obtained model is characterized by high approximation accuracy and may be used to forecast electricity consumption volumes depending on the dynamics of production output

SELECTING THE OPTIMAL OPTION FOR A GROUND-BASED AUTOMATED CONTROL SYSTEM FOR AIRBORNE ELECTRONIC EQUIPMENT

S. V. Rahulin — 2026-05-30

The current state of civil aviation operations is characterized by a rapid increase in the complexity of on-board avionics and flight navigation systems (FNS). The high level of system integration means that operational monitoring on the apron is limited by the capabilities of the built-in monitoring systems (BMS). However, the limited reliability of the ISC results in a significant number of erroneous removals of serviceable easily removable units (ERUs), creating a stream of ‘unconfirmed defects’. This requires airlines to implement effective ground-based automated inspection systems (GAIS) capable of performing in-depth diagnostics on removed equipment. The problem lies in the absence of a unified methodological approach to selecting the AGS architecture (centralized or distributed) depending on the size of the aircraft fleet and economic risks. The object of the study is the processes of maintenance and restoration of the operational capability of An-148 aircraft using automated ground control systems. The subject of the study is the methods and indicators for assessing the effectiveness of the structural design of the AGCS based on the criterion of total operating costs. The study employs a comprehensive approach based on methods of systems analysis, queuing theory and industrial engineering. To assess efficiency, a mathematical model has been developed that integrates indicators of power plant reliability, VSK reliability and NASK throughput capacity. Particular attention is paid to accounting for the time value of capital investments (discounting) and the cost of the LZB replacement fund during the post-warranty period of operation. Scientific novelty and results obtained. 1. For the first time, a comprehensive methodology has been developed for selecting the optimal NASC structure which, unlike existing approaches, accounts for the probabilistic losses from aircraft downtime due to queues at security checkpoints. 2. A comparative analysis of centralized (single-site) and distributed (multi-site) NASC architectures has been carried out. It has been demonstrated that universal single-site systems, despite their lower initial cost, have limited resilience: any system failure or overload leads to a complete halt in the fleet diagnostic process. 3. Based on calculations for the An-148 aircraft, a pattern has been established: the economic efficiency of the transition from a centralized to a distributed NASC structure directly depends on the size of the registered fleet. A critical value of 12 aircraft has been determined; once this is exceeded, a distributed structure becomes the priority due to the minimization of costs associated with forming a surplus exchange fund and the prevention of operational downtime. The results obtained enable airlines and maintenance, repair and overhaul (MRO) centers to plan the development of their ground-based diagnostic facilities in an informed manner, optimize the costs of after-sales maintenance for An-148 aircraft, and improve the fleet’s technical utilization rate

ORGANIZATION OF BUSINESS EVENTS IN THE TOURISM AND HOSPITALITY INDUSTRY

K. M. Horb — 2026-05-30

The article is devoted to the systematization of service technological operations of various enterprises in the organization of business events in the field of tourism and hospitality, provided that they perform various functions. Business events, which are widely spread and gaining popularity in the world, diversify organizational forms of preparation and conduct and expand the thematic spectrum, are distinguished by a rather complex implementation technology and require the involvement of various business entities working mainly in the field of tourism and hospitality. The main subjects of their development and implementation are customers, organizers, performers and participants. Different enterprises in the organization of various business events can act as each of the above-mentioned subjects. The sequential chain system of «order – execution» for business events of various scales and profiles can demonstrate, respectively, a different level of complexity and branching of mutual orders, obligations and guarantees of the mentioned subjects. The customer can fully rely on one organizer, which provides the preparation and holding of the event on a turnkey basis, can partially order only individual services from different entities for organizing a business event, and provide part of the work independently. There are mainly three types of entities that can act as organizers of a business event: firstly, tour operators and travel agencies, secondly, business hotels (conference hotels, congress hotels), thirdly, event agencies, provided that the companies of each of these types declare MICE-tourism as their main or at least additional profile and accumulate experience and build a reputation in this segment. Each of them has its own specifics regarding the implementation of the functions of a business event organizer and can in various cases also act as a performer of individual service operations as a contractor of another similar enterprise. Among the performers of individual operations for the implementation of a business event may be transport companies, accommodation and catering establishments, leisure and recreation, excursion activities, individual industrial, construction, trade and agricultural enterprises, exhibition centers, etc. The proposed approach to systematizing subjects and organizers of business events, taking into account their interchangeability and the possibility of «role exchange», will allow improving organizational and service support in business tourism and hospitality.

INTRA-ECONOMIC CALCULATION IN THE HOTEL AND RESTAURANT BUSINESS: STRATEGIC ORGANIZATIONAL MODEL

M. М. Kucher — 2026-05-30

Тhe article examines the problem of organizing internal cost accounting in hotel and restaurant enterprises in Ukraine. It is noted that traditional methods of financial management do not provide sufficient flexibility and transparency, which are essential for the survival of enterprises in crisis situations. The relevance of internal cost accounting is substantiated as a strategic tool that enables the redistribution of resources among departments, cost control, the formation of a system of material responsibility, and employee motivation. A model of internal cost accounting organization is proposed, based on the use of financial responsibility centers, budgeting, and transfer pricing. This model takes into account the specifics of hotel and restaurant enterprises and modern challenges, including service diversification. An implementation algorithm for internal cost accounting in hospitality enterprises is presented, which includes stages of business process diagnostics, model selection, and the organization of a budgeting system. The role of financial responsibility centers (FRCs) is emphasized as fundamental elements of the internal mechanism, allowing for the evaluation of the performance of individual departments. A model of economic management with transfer pricing has been developed, which considers the specifics of intermediate product and service production in hospitality enterprises. Recommendations for material incentives for personnel are formulated, directly linking departmental performance with the financial indicators of the enterprise. The proposed model of internal cost accounting combines theoretical foundations with practical tools for adapting international experience. The conclusions confirm that internal cost accounting in modern conditions performs not only the function of financial control but also becomes the basis for service diversification, employee motivation, and the long-term development of the industry

INNOVATIVE DIGITAL TECHNOLOGIES FOR ORGANIZING AND PROMOTING EVENTS AS PART OF EFFORTS TO IMPROVE THE OPERATIONAL EFFICIENCY OF HOTEL BUSINESSES

O. M. Radionova — 2026-05-30

This article examines the role of innovative digital technologies in organizing and promoting events as part of efforts to improve the operational efficiency of hotel businesses. It demonstrates the relevance of implementing digital solutions in the context of growing competition in the hotel services market and the need to optimize business processes. It is determined that the digitalization of event activities serves as a key factor in transforming approaches to event management, customer interaction, and the creation of added value in hotel services. Within the scope of the study, innovative digital technologies were categorized according to the stages of event organization, and their essential characteristics and functional capabilities were summarized. It has been established that the use of event management systems, CRM solutions, mobile applications, analytical platforms, artificial intelligence tools, and automated services ensures increased efficiency in managing event processes, optimization of resource costs, and improved quality of customer service. It is proved that the systemic integration of CRM and PMS ensures significant automation of routine operations, which directly affects the reduction of operating costs and the growth of ADR and RevPAR indicators. Innovative digital technologies for promoting events were examined, including tools for targeted advertising, social media, email marketing, SEO optimization, and marketing analytics. Their role in shaping demand, expanding the customer base, and increasing the visibility of hotel enterprises has been substantiated. It has been determined that the integration of digital tools into the processes of organizing and promoting events has a comprehensive impact on the operational, marketing, and communication effectiveness of hotel operations. The impact of events on key performance indicators of hotel enterprises has been established, specifically room occupancy rates, ADR and RevPAR metrics, revenue from ancillary services, and customer loyalty levels. The use of cloud solutions (SaaS) as a tool to minimize risks associated with the shortage of digital competencies among staff is justified. A model of the impact of innovative digital technologies for organizing and promoting events on the performance of hotel enterprises is proposed, reflecting the interrelationship between resources, digital tools, processes, and results. The results obtained contribute to deepening theoretical approaches to the study of the digitalization of event activities in the hotel industry and expand understanding of the role of innovative digital technologies in improving the operational efficiency of hotel enterprises in the context of the modern market environment.

SUSTAINABLE DEVELOPMENT MARKETING AS A TOOL FOR STRATEGIC TRANSFORMATION OF HOSPITALITY INDUSTRY ENTERPRISES

N. F. Stebliuk — 2026-05-30

The article is devoted to the justification of the transformation of marketing activities of hospitality industry enterprises in the context of implementing a sustainable development model. In the face of modern global challenges, traditional marketing tools require systematic adaptation to the principles of ethical consumption and environmental responsibility. The concept of sustainable marketing is based on a combination of three interrelated components: economic efficiency of business, social responsibility to the community, and environmental safety. The role of these components as key strategic guidelines that allow hospitality businesses to strengthen customer trust and form sustainable competitive advantages through the transmission of shared values with the guest is revealed. The structure of the main stages of a sustainable development marketing strategy adapted to the conditions of the hospitality industry is presented, which allows transforming the business processes of the enterprise into longterm competitive advantages and increasing its investment attractiveness. The main challenges that hinder the effective operation of hospitality establishments are identified: financial, marketing, legal and environmental. A combination of ABC analysis and Pareto charts was used to rank marketing strategies, which allowed for a clear distinction between management measures according to their level of impact on the adaptability of the enterprise. It was found that focusing on group A (digitalization of booking, personalization of service and implementation of energy-efficient solutions) provides the maximum cumulative effect and covers 76 % of the total significance of all identified strategies. Based on the results of the study, practical recommendations were formed to improve the marketing strategy for the sustainable development of the enterprise, structured according to three ESG vectors: environmental, social, and economic

ASSESSING THE LEVEL OF SUSTAINABLE DEVELOPMENT OF RESTAURANT ESTABLISHMENTS WITH REGARD TO HACCP IMPLEMENTATION

S. O. Khrychov — 2026-05-30

The article substantiates an applied approach to assessing the level of sustainable development of restaurant establishments with regard to the maturity of HACCP-based procedures as a mandatory component of contemporary food safety management. The relevance of the research stems from the fact that, during wartime and economic turbulence, Ukrainian restaurant businesses are expected to ensure food safety, optimize resource use, reduce food waste, and maintain social resilience of personnel simultaneously. Based on the analysis of relevant scientific publications from 2021 to 2025, the paper demonstrates that prevailing sustainability assessment models in hospitality tend to prioritize environmental and economic indicators while insufficiently integrating food safety performance, food safety culture, and the quality of HACCP implementation. The methodology combines a systems approach, content analysis of recent scholarly sources, comparative analysis of regulatory requirements, integral assessment, and model-based testing on three typical restaurant profiles: a full-service urban restaurant, a quick-service deliveryoriented outlet, and a catering operator. An integral sustainable development index is proposed. It includes four indicator blocks: HACCP performance, environmental and resource efficiency, social responsibility, and economic-managerial resilience. The findings show that the strongest contributors to the overall sustainability score are systematic staff training, documented critical control points, food waste monitoring, energy and water control, and ingredient traceability. The model-based testing produced the following results: the catering operator achieved the highest integral index (0.81), followed by the full-service restaurant (0.76), while the quick-service delivery outlet showed a moderate score (0.69). The practical value of the study lies in the possibility of using the proposed instrument for internal audit, self-assessment, preparation for official inspections, and the design of resource-efficiency and circularity programs. The paper argues that the sustainable development of restaurant establishments should be interpreted not only through the triple bottom line logic but also through the operational reliability of food safety management systems, especially HACCP. Therefore, HACCP should be treated not as a narrow regulatory burden but as an enabling managerial platform that links consumer protection, process discipline, waste prevention, and long-term competitiveness in the restaurant sector.

CONSUMER LOYALTY AS A BRANDING TOOL IN THE DEVELOPMENT STRATEGY OF RESTAURANT BUSINESS ENTERPRISES

S. O. Gaponenko — 2026-05-30

The article examines the nature of the NPS index, its calculation methods, and its significance for the catering industry, and also analyzes the results of the practical application of the given methodology when implementing it during the improvement of the development strategy at restaurant business enterprises. The current realities of economic activity in Ukraine are extremely difficult for many types of enterprises. In addition to external general unfavorable conditions, catering establishments are faced with increasing competition, which poses an important task for them not only to attract new customers, but also to retain existing ones. The success of a restaurant, cafe or coffee shop increasingly depends on customer loyalty - a factor that includes both their desire to return and their willingness to recommend the establishment to others. To measure this important indicator, the Net Promoter Score (NPS) index is often used – a tool that reflects the likelihood that customers will recommend the establishment to their friends and acquaintances. In the restaurant industry, where customer satisfaction is a key factor in success, the NPS is a valuable indicator as it helps to understand how satisfied customers are with their experience and whether they are willing to tell others about it. Through NPS analysis, restaurants can identify key points that affect loyalty and take measures to improve service, which will contribute not only to increasing customer satisfaction, but also to the successful development of the business. Considering that, according to a report by Nielsen, one of the leading international companies, recommendations from friends and family are the most reliable form of advertising, restaurants with a high NPS can count on a positive reputation and an increase in new customers due to word-of-mouth marketing or “word of mouth”. It is also worth noting that more than twothirds of Fortune 1000 companies use this indicator to monitor customer loyalty, which emphasizes its importance for business. The willingness of customers to return to a restaurant is a powerful tool for assessing the level of customer retention and loyalty. However, in order for a restaurant to thrive and remain successful in the market, it needs not only to ensure the loy-alty of regular customers, but also to attract new visitors, maintain their interest and ensure a high rotation of guests. It is important to understand that the success of a business depends not only on the level of customer satisfaction and their willingness to return, but also on how actively they recommend the establishment to their friends and family. Thus, recommendations are a powerful tool in the restaurant business, they can be one of the main components for the long-term development and prosperity of a restaurant

MATHEMATICAL MODEL FOR CALCULATION AND OPTIMIZATION OF FUNCTIONAL PARAMETERS OF A PNEUMATIC MICROTURBINES

T. Zh. Nadryhailo — 2026-05-30

В даній статті представлена методика удосконалення техніко-експлуатаційних характеристик пневматичної мікротурбіни для застосування в якості приводу ручних шліфувальних машин. Шліфувальні машини мають широке застосування для підвищення рівня автоматизації та механізації виробничих процесів. Для отримання достатньо високої чистоти обробки поверхонь деталей технічні характеристики таких машин мають забезпечувати достатньо велике число обертів та відповідну потужність. Таким вимогам відповідають пневматичні мікротурбіни завдяки їх компактності, ефективності та здатності перетворювати енергію стисненого повітря у корисну роботу. Тому удосконалення методів розрахунку технічних параметрів пневматичних мікротурбін має достатньо актуальне як наукове так і прикладне значення обумовлене потребою в енергоефективних і екологічно чистих енергетичних установках. Запропонована методика розрахунку функціональних характеристик мікротурбіни враховує зміну енергетичних параметрів газодинамічного потоку на вході і виході з робочого колеса та з урахуванням непродуктивних втрат повітря в зазорах і на тертя. Для забезпечення необхідних техніко-експлуатаційних характеристик проведено оптимізацію конструктивних параметрів лопаток мікротурбіни, соплового апарата та відповідних технологічних зазорів. Аналіз оптимальних енергетичних параметрів мікротурбіни підтверджує достатньо високу ефективність одноступеневої осьової турбіни з бандажем і циліндричними свердленими соплами. Розраховані у відповідності із запропонованою методикою техніко-конструктивні параметри забезпечують ефективну витрату повітря та достатньо високі значення енергетичних параметрів роботи пневматичної шліфувальної машини із приводом на базі мікротурбіни