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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology

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metadata of articles for the last 2 years

Assessment of the reliability and effectiveness of artificial intelligence systems in radiation diagnostics at the operational stage

2025. T.13. № 2. id 1886

Zinchenko V.V. Vladzimirskyy A.V. Arzamasov K.M.

DOI: 10.26102/2310-6018/2025.49.2.016

In the context of the active implementation of artificial intelligence (AI) technologies in healthcare, ensuring stable, controlled and high-quality operation of such systems at the operational stage is of particular relevance. Monitoring of AI systems is enshrined in law: within three years after the implementation of medical devices, including AI systems, it is necessary to provide regular reports to regulatory authorities. The aim of the study is to develop methods for assessing the reliability and effectiveness of medical artificial intelligence for radiation diagnostics. The proposed methods were tested on the data of the Moscow Experiment on the use of innovative technologies in the field of computer vision in the direction of chest radiography, collected in 2023. The developed methods take into account a set of parameters: emerging technological defects, research processing time, the degree of agreement of doctors with the analysis results and other indicators. The proposed approach can be adapted for various types of medical research and become the basis for a comprehensive assessment of AI systems as part of the monitoring of medical devices with artificial intelligence. The implementation of these methods can increase the level of trust of the medical community not only in specific AI-based solutions, but also in intelligent technologies in healthcare in general.

Keywords: artificial intelligence, reliability, efficiency, artificial intelligence system, radiology, radiation diagnostics, monitoring

Optimization of the nomenclature-volume balance of suppliers and consumers in the management of the organizational system of drug supply

2025. T.13. № 2. id 1885

Shvedov N.N. Lvovich Y.E.

DOI: 10.26102/2310-6018/2025.49.1.018

The article discusses approaches and tools aimed at improving the intelligent management of the nomenclature component in the drug supply system using optimization problems. We are talking about the relationship between the list of drugs and their quantitative distribution in such a way that the degree of balance between supply and demand is taken into account. The problem lies in insufficient coordination of drug flows, imbalances in stocks and inefficient distribution of resources. All these factors lead to increased costs and reduced availability of vital drugs for end consumers. Effective management of the nomenclature-volume balance allows you to avoid shortages, excess stocks and increase the sustainability of the drug supply system, ensuring optimal stocks and availability of drugs. The main attention is paid to the use of optimization problems and expert assessments of their parameters in managing the digital interaction of suppliers and consumers, which allows for increased accuracy in controlling the range and demand. Control means minimizing shortages or excess stocks, guaranteeing the availability of the necessary drugs for the end consumer. The results of the study were used to develop an intelligent subsystem for supporting management decisions, promoting balanced resource management and increasing the availability of drugs.

Keywords: organizational system, drug provision, management, optimization, expert assessment

Application of the task of finding the minimum vertex coverage in a graph to improve the robustness of digital identity system

2025. T.13. № 2. id 1883

Akutin A.S. Pechenkin V.V.

DOI: 10.26102/2310-6018/2025.49.2.015

This paper examines the features of building digital identity systems for managing information technology processes in an enterprise, the architecture of which depends on decentralized data registers - blockchains. The paper considers blockchains as weighted graphs and formulates a number of theses that speak about the specifics of the functioning of such distributed networks in real information technology enterprises. The features of various network topologies and possible architectural vulnerabilities and flaws that can affect the operation of the entire network are considered – centralization of mining, centralization of staking, various attacks on a functioning network (topological and 51% percent attack). Blockchains using various consensus-building algorithms, taking into account their features, are considered. The paper considers the task of finding the minimum coverage in a graph and emphasizes the importance of applying this task to the described digital personality system in order to increase the reliability of the blockchain computer network by analyzing its topology. Various methods of finding the minimum coverage in a graph are considered – exact and heuristic algorithms. The paper analyzes an application that implements the ant colony algorithm to solve the problem, provides numerical characteristics of the algorithm and its formal description.

Keywords: digital identity system, blockchain, distributed systems, graphs, minimum coverage search

Mathematical model of competition for a limited resource in ecosystems: numerical and analytical study of sustainability

2025. T.13. № 2. id 1877

Gutnik D.I. Belykh T.I. Rodionov A.V. Bukin Y.S.

DOI: 10.26102/2310-6018/2025.49.2.017

This paper investigates the dynamics of interaction between two species competing for a limited resource using a mathematical model that is an autonomous system of ordinary differential equations in normal form. The model is based on Gause's principle, Volterra's hypotheses, Tilman's theory of resource competition, and the Michaelis-Menten equation to describe population growth. The system of nonlinear ordinary differential equations is analyzed for stability at stationary points using the first approximation analytical method proposed by A.A. Lyapunov, which is suitable for the study of systems consisting of two or more equations, and analytically and numerically solved for various values of model parameters. The results show that species survival and coexistence depend on the level of the limiting resource, the ratio of fertility and mortality rates and intraspecific competition, and substrate concentration. Numerical simulations correspond to scenarios of extinction of one species, dominance of one species, or their coexistence depending on environmental conditions. The results obtained in this work are consistent with natural ecological relationships and emphasize the importance of considering anthropogenic factors, such as eutrophication, when predicting changes in ecological systems.

Keywords: population dynamics, limiting resource, mathematical model, lyapunov method, simulation, eigenvalues, stability of equilibrium state

Enhancing the trustworthiness of explainable artificial intelligence through fuzzy logic and ontology

2025. T.13. № 2. id 1872

Kosov P.I. Gardashova L.A.

DOI: 10.26102/2310-6018/2025.49.2.014

The insufficient explainability of machine learning models has long constituted a significant challenge in the field. Specialists across various domains of artificial intelligence (AI) application have endeavored to develop explicable and reliable systems. To address this challenge, DARPA formulated a contemporary approach to explainable AI (XAI). Subsequently, Bellucci et al. expanded DARPA's XAI concept by proposing a novel methodology predicated on semantic web technologies. Specifically, they employed OWL2 ontologies for the representation of user-oriented expert knowledge. This system enhances confidence in AI decisions through the provision of more profound explanations. Nevertheless, XAI systems continue to encounter difficulties when confronted with incomplete and imprecise data. We propose a novel approach that utilizes fuzzy logic to address this limitation. Our methodology is founded on the integration of fuzzy logic and machine learning models to imitate human thinking. This new approach more effectively interfaces with expert knowledge to facilitate deeper explanations of AI decisions. The system leverages expert knowledge represented through ontologies, maintaining full compatibility with the architecture proposed by Bellucci et al. in their work. The objective of this research is not to enhance classification accuracy, but rather to improve the trustworthiness and depth of explanations generated by XAI through the application of "explanatory" properties and fuzzy logic.

Keywords: explainable artificial intelligence, explainability, ontology, fuzzy system, fuzzy clustering

Modeling of radiopaque angiographic images for determining vessel parameters using dual spectral scanning

2025. T.13. № 2. id 1871

Kuzmin A.A. Sukhomlinov A.Y. Zhilin I.A. Filist S.A. Korobkov S.V. Serebrovskiy V.V.

DOI: 10.26102/2310-6018/2025.49.2.011

The purpose of the study is to develop a methodology for cognitive determination of medical halftone images’ parameters based on dual spectral scanning methods. The mathematical model of radiopaque images of vessels is described in this work. Based on this model, the method for determining the vessel parameters using spectral scanning was developed. The model is based on the representation of oriented brightness differences using Walsh functions. This vessel model was convolved with wavelets based on the first Walsh functions. The result of the convolution will yield extremes at the points of brightness differences. We can use this result as an informative parameter for the presence of a vessel contour. Information from many such parameters in a local area is aggregated and gives an averaged characteristic of this area. This leads to a significant decrease in the influence of noise on the final result due to an acceptable decrease in the resolution of localization of significant arterial occlusions. The averaged results of the convolution of Walsh functions are recommended to be calculated using a two-dimensional spectral Walsh transform in a sliding window with subsequent frequency selection. The method is illustrated by the example of classifying the contour of the boundary of a vessel model and a real radiopaque image of an artery with a high noise level. A comparison of theoretical and practical approaches to solving the problem of detecting the contour of arteries is carried out. Experimental studies of the proposed method have shown the possibility of estimating informative parameters even under conditions of analyzing images with unsatisfactory contrast and with a low signal-to-noise ratio. The use of the dual spectral scanning method in systems for automatic analysis of radiopaque angiographic images allows obtaining informative parameters in conditions of high noise in the images.

Keywords: spectral analysis, informative parameters, image of a vessel, radiopaque angiography, walsh functions

A method for quantifying the danger of implementing threats to the information security of objects of critical information infrastructure by potential violators

2025. T.13. № 2. id 1870

Chernov D.V.

DOI: 10.26102/2310-6018/2025.49.2.013

In the context of increasing informatization of various production areas, when most technological processes and information flows are automated and controlled by computer technology, the choice of measures to ensure the security of information (SI) of critical information infrastructure objects (CIIO) becomes a pressing issue. The article discusses existing methods and approaches to assessing the risk of implementing SI threats to CIIO, which include automated process control systems, information systems, and information and telecommunication networks. These approaches help SI specialists assess the risks associated with possible cyberattacks and data leaks. A method is proposed for quantitatively assessing the degree of danger of implementing SI threats based on the intelligent analysis of data stored in the CIIO logging subsystem. The method allows for a quantitative assessment of the degree of danger of implementing SI threats by potential violators with respect to a specific CIIO. The developed method complements the available assessments of SI specialists by forming expert assessments from additionally involved specialists - professionals in the field of technological processes and information flows of CIIO. The results of the study are recommended for use in modeling SI threats and developing requirements for information security tools in the CIIO.

Keywords: information security, critical information infrastructure, automated control system, technological process, threat, violator, potential, danger of threat realization, risk, damage

Simulation of trajectory for additive printing of tree-like fractal structure with a six-axis robot

2025. T.13. № 2. id 1865

Bersenev K.A. Ogorodnikova O.M. Ogorodnikov A.I.

DOI: 10.26102/2310-6018/2025.49.2.012

Currently, the widespread use of additive technologies fully raises the issues of creating and implementing optimal bio-inspired designs, because a number of technological restrictions on the geometry and shaping of surfaces are removed. This article presents the results of developing control system algorithms that take into account the operation of an articulated robot as part of technological equipment for multi-axis printing of parts by the fusion deposition method. For non-solid filling of the internal volume of parts, a bio-inspired tree-like structure was chosen, which was formally described using a fractal in the trajectory planning problem. The geometry of the printed object is presented in a cylindrical coordinate system, based on which it is possible to create a layer-by-layer trajectory with a set of concentric circles using a simplified procedure for recalculating coordinates. The results of the work performed are part of a hardware and software complex in a robotic cell for manufacturing parts from PLA and ABS thermoplastics. The trajectory planning is carried out in a simulator, the program code of which is written in the C language and refers to the functions of the Raylib library to perform mathematical operations with vectors, matrices and quaternions. The robot's movement along the planned trajectory is controlled by the STM32H743VIT6 microcontroller with the Free RTOS real-time operating system.

Keywords: additive manufacturing, bio-inspired structures, tree-like fractal, six-axis articulated robot, kinematics simulation, trajectory planning

Using ResNet and Transformer architectures in the problem of source code generation from an image

2025. T.13. № 2. id 1863

Nikitin I.V.

DOI: 10.26102/2310-6018/2025.49.2.002

This study examines different ways to optimize a system designed to generate source code from an image. The system itself consists of two parts: an autoencoder for processing images and extracting the necessary features from them, and text processing using LSTM blocks. Recently, many new approaches have been released to solve problems of both improving image processing performance and text processing and prediction. In this study, ResNet architectures were chosen to improve the image processing part and Transformer architecture to improve the text prediction part. As part of the experiments, a comparison was made of the performance of systems consisting of various combinations of architectural solutions of the original system, ResNet architecture and transformers, and a conclusion was made about the quality of prediction based on the performance of the BLEU, chrF++ metrics, as well as the execution of functional tests. The experiments showed that the combination of ResNet and Transformer architectures shows the best result in the task of generating source code from an image, but this combination also requires the longest time for its training.

Keywords: code generation, image, machine learning, resNet, transformers

Development of a software platform for implementing feedback in an urban self-organizing system

2025. T.13. № 2. id 1862

Denisov V.A. Shebarshov A.A. Karchagin E.V. Parygin D.S. Kizim A.V.

DOI: 10.26102/2310-6018/2025.49.2.007

The relevance of the study is determined by the need to increase the level of self-organization of urban systems through the involvement of the population in the processes of management and optimization of infrastructure, which corresponds to the concept of «The right to the city». In this regard, this article aims to identify effective methods of organizing feedback between residents and city authorities through multiplatform online surveys with geospatial reference. The leading approach to the study of this problem is the development of a client-server system that combines a web client, a Telegram bot and other platforms, which allows for a comprehensive review of the features of data collection, analysis and visualization in real time. The article presents the architecture and functionality of the system, reveals the principles of its operation, identifies the advantages of a multiplatform approach compared with traditional survey methods, and substantiates the importance of geospatial mapping for localization of problem areas. It has been experimentally confirmed that using multiple channels of interaction increases the activity of respondents and the representativeness of data: 6022 publications from 94 participants were collected in four months. The materials of the article are of practical value for city administrations, researchers in the field of urban studies and developers of civic engagement platforms focused on creating adaptive management systems for the urban environment.

Keywords: system management, feedback, multi-agent system, self-organization, urban studies

Network planning and resource optimization of a project in conditions of fuzzy group expert assessment of the duration of work

2025. T.13. № 1. id 1861

Azarnova T.V. Asnina N.G. Bondarenko Y.V. Sorokina I.O.

DOI: 10.26102/2310-6018/2025.48.1.041

This article presents an algorithm for calculating time parameters and resource optimization of a network graph, the lengths of which are estimated by an expert group in the form of fuzzy triangular numbers. To account for the variation in expert assessments, the examination results are first summarized as fuzzy interval-digit numbers and then converted into fuzzy triangular numbers based on the risk factor of the decision maker. The use of fuzzy interval-valued numbers allows not only to take into account the uncertainty of expert opinions regarding the duration of work, but also the differences in expert opinion when forming the membership function of fuzzy triangular numbers. The network planning algorithm is based on the classical algorithm for finding the critical path using special methods for calculating the early and late times of events when setting the duration of work in the form of fuzzy triangular numbers. Instead of taking the maximum and minimum operations when finding the early and late times of events, a probabilistic comparison of fuzzy numbers is used. Based on the calculated fuzzy triangular estimates of the early and late completion of events, fuzzy estimates of the early and late moments of the start and completion of each job and the probability of each job being completed at each time are calculated. The probabilities obtained allow us to estimate the resource availability of the project at any given time. The paper also proposes a mathematical model for optimizing the resource availability of a project due to shifts in the beginning of each work within the early and late start.

Keywords: network graph of the project, fuzzy triangular and interval-valued representation, duration of the project work, fuzzy time parameters of the project work, resource optimization of the project

Development of a code translator from C to Promela as a component of an intelligent tutoring system for programming learning

2025. T.13. № 2. id 1860

Kulyukin K.S. Yakimov G.A. Smutin D.A.

DOI: 10.26102/2310-6018/2025.49.2.004

This work focuses on the development of a C to Promela translator for the automated verification of programs written by programming students. The goal is to create a tool that allows checking the correctness of intermediate program execution steps using Model Checking. The proposed translator is geared towards sequential programs with a single main function, operating on integers and arrays. It analyzes the student’s C code, input data range requirements, and a hierarchical LTL specification (goal tree) that describes the expected program behavior. The translation process utilizes clang to construct the syntax tree and creates additional variables to track array accesses. The generated Promela code contains variable declarations, a main process that includes non-deterministic variable input and the translated C code, and an LTL properties block. The resulting Promela model is verified using Spin against the LTL properties specified by the instructor. If a violation is detected, a counterexample is generated, demonstrating the program execution trace containing the error. The result of this work is a command-line utility written in Python that generates a .pml file with Promela code and LTL properties, as well as a .json file containing the annotated goal tree and the counterexample. Future plans include automating the generation of LTL properties from natural language requirement descriptions and generating hints for students based on the counterexamples.

Keywords: intelligent tutoring systems, programming learning, formal verification, model checking, code translation

Development of a method of applying neural and mivar networks for identification and selection of indoor and garden plants

2025. T.13. № 2. id 1859

Konygina D.A. Kotsenko A.A. Varlamov O.O. Sokolov B.O. Gracheva A.A.

DOI: 10.26102/2310-6018/2025.49.2.009

In recent years, there has been a surge of gardeners' interest in growing plants both on farms and at home. The aim of the study is to develop a method for the integrated application of neural networks for plant identification from photos and mivar technologies to provide personalized recommendations. A residual convolutional neural network ResNet20, pre-trained on a dataset of plants, is used for image classification. The mivar expert system provides a personalized recommendation based on the growing conditions and parameters of the plant defined by the neural network. A model for describing the provision of recommendations is created, which helps users to get the desired result in the form of the name of the plant. A method of applying neural and mivar networks is developed to generate logically sound plant recommendations depending on environmental conditions and user preferences. According to the results of experiments, we can conclude that in order to increase the accuracy of image classification, it is necessary to increase the number of layers of the neural network by about 1.5 times when increasing the recognized plants from 3 to 9. The complex application of convolutional neural networks and mivar technologies allows to achieve high accuracy of plant detection and provide high-quality recommendations for users.

Keywords: intelligent system, convolutional neural network, mivar, providing recommendations, mivar networks, mivar expert systems

Developing a computer vision model for region detection in visually rich documents

2025. T.13. № 2. id 1858

Nikitin P.V. Gorokhova R.I.

DOI: 10.26102/2310-6018/2025.49.2.010

The problem of efficient automation of visually rich document processing is an important part of computer vision research. This paper is devoted to the development of a computer vision model for region detection in visually rich documents, with an emphasis on receipt processing using reinforcement learning. In the context of the growing volume of paper documentation and the need to automate data processing, efficient identification of key elements of receipts (such as amounts, dates, and product names) is becoming especially relevant. The paper presents the architecture of the model based on convolutional neural networks (CNN), which is trained on a variety of datasets including receipt images of different formats and qualities. The methods of information extraction and the reinforcement learning algorithm are considered, which uses a trimmed loss function, a reinforcement learning loop presented in SpanIE-Recur. The stages of data preprocessing are described, including sample augmentation and image normalization, which contributes to increasing the detection accuracy. The experimental results show the high efficiency of the proposed model, achieving significant accuracy and recall in identifying regions of interest. Possible applications of this technology in the fields of accounting automation, financial analysis and electronic document management are also discussed. In conclusion, the importance of further research in the field of improving image processing algorithms and expanding the functionality of the model to work with other types of documents is emphasized.

Keywords: visually rich document, computer vision, reinforcement learning, object detection, receipt processing, automation, document areas, data preprocessing, electronic document management

Analysis of the influence of gas dynamic processes on temperature stratification in an energy separation device, taking into account Bernoulli's law and Joule-Thomson effect

2025. T.13. № 1. id 1855

Matveev A.F. Kovalnogov V.N.

DOI: 10.26102/2310-6018/2025.48.1.045

The article provides an analysis of a number of gas-dynamic processes affecting the efficiency of the gas-dynamic temperature stratification device. The relevance of the study is due to the need for a more accurate description of the processes of gas-dynamic temperature stratification in energy separation devices, which is important for improving the efficiency of heat exchange and aerodynamic systems. This article is aimed at identifying patterns of energy redistribution in the flow, taking into account the Bernoulli law and the Joule-Thomson effect, as well as analyzing their impact on temperature gradients inside the gas-dynamic temperature stratification device. The study employs mathematical modeling conducted within the STAR-CCM+ framework, enabling a thorough exploration of gas flow characteristics, as well as variations in velocity, pressure, and temperature throughout the system. The article presents the results of a numerical experiment, reveals the mechanisms of influence of the main gas-dynamic effects on temperature stratification, identifies key dependencies between the input parameters of the device and the flow characteristics, and substantiates the possibility of targeted optimization of energy separation. Mathematical models are derived, supplemented by equations that take into account the role of Bernoulli's law and the Joule-Thomson effect. The corresponding equations are considered. The materials of the article are of practical value for the development and improvement of energy separation devices, optimization of working processes in gas-dynamic systems and increasing the efficiency of temperature stratification in aerodynamic installations for use in the real sector of the economy.

Keywords: gas dynamic temperature stratification, energy separation device, mathematical modeling, STAR-CCM+, bernoulli's law, joule-Thomson effect

Methods for comparative analysis of evolutionary design methods in software for solving multicriteria optimization problems

2025. T.13. № 2. id 1854

Baranov D.A.

DOI: 10.26102/2310-6018/2025.49.2.008

The relevance of the study is due to the need to improve methods for solving multi-criteria transportation problems, which represent an important class of optimization problems with a wide range of practical applications. Traditional approaches often fail to handle the computational complexity of such problems, while existing heuristic methods require additional adaptation and parameter tuning.In this regard, this paper aims to identify the most effective configurations of evolutionary algorithms for solving multi-criteria transportation problems in terms of both solution quality and speed. The leading approach to studying this problem is the comparative analysis of various configurations of evolutionary algorithms on a large set of test tasks (about 85 thousand unique tasks with 4 criteria), allowing for a comprehensive examination of the features of each algorithm under different parameters. The paper presents the results of analyzing the effectiveness of about 50 configurations of evolutionary algorithms, reveals patterns of how various parameters influence solution quality and speed, identifies optimal configurations for each type of algorithm, and justifies the advantage of a combined approach to problem-solving. The materials of the paper are of practical value for software developers in the field of logistics and transportation systems, as well as for researchers working on optimization and evolutionary design issues, as they enable the creation of more efficient automated systems for solving multi-criteria transportation problems.

Keywords: optimization, evolutional algorithms, travelling salesman problem, transportation problem, multicriterial problems

Segmentation of liver volumetric lesions in multiphase CT images using the nnU-Net framework

2025. T.13. № 1. id 1853

Kulikov A. Kashirina I.L. Savkinа E.

DOI: 10.26102/2310-6018/2025.48.1.040

The article presents a study on the application of the nnU-Net (v2) framework for automatic segmentation and classification of liver space-occupying lesions on abdominal computed tomography. The main attention is paid to the effect of the batch size and the use of data from different contrast phases on the classification accuracy of such lesions as cysts, hemangiomas, carcinomas, and focal nodular hyperplasia (FNH). During the experiments, batch sizes of 2, 3, and 4 were used, as well as data from two contrast phases ‒ arterial and venous. The results showed that the optimal batch size is 3 or 4, depending on the pathology, and the use of data from two contrast phases significantly improves the accuracy and sensitivity of space-occupying lesions classification, especially for carcinomas and cysts. The achieved best sensitivity rates were 100% for carcinomas, 94% for cysts, 81% for hemangiomas, and 84% for FNH. The paper confirms the effectiveness of nnU-Net v2 for solving medical image segmentation and classification problems and highlights the importance of choosing the right training parameters and data to achieve the best results in medical diagnostics.

Keywords: nnU-Net v2, CT images, liver pathologies, batch size, segmentation, classification, medical images, contrast phases, carcinoma

Indoor wireless local area network design using digital twin and algorithm for automated placement of wireless LAN access points

2025. T.13. № 2. id 1852

Shorokhov M.E. Pechenkin V.V.

DOI: 10.26102/2310-6018/2025.49.2.005

The article discusses a method for designing a wireless local area network using a digital twin of a room. It considers the capabilities of a digital twin to simplify the storage and synchronization of data on the structure of the room and the location of devices. It describes the developed structure of the building, which includes floors storing information on the coordinates and models of access points, user devices and obstacles. The information on the floors is divided into corresponding layers, which allows for quick access to any data by coordinates. The article also discusses the implementation of an algorithm for the automated placement of access points in the room. The algorithm includes a system of "agents", where each access point acts as a separate entity trying to fulfill the set conditions in its area. Depending on the number of iterations set by the designer, the initial number of access points, accuracy and limitations, different results can be obtained. Thus, the result of the algorithm allows you to evaluate various situations and choose the most suitable option for arranging access points in the room, taking into account all the set conditions. Using the developed tools, the designer can clearly see how the access points were located using the algorithm, how the signal from each point spreads throughout the room, and whether all the conditions for the devices located in the room are met.

Keywords: wireless local area network, wireless local area network design, BIM-technologies, digital twin, automation algorithm, placement of access points

Modeling of newborn breathing patterns using electrical impedance tomography

2025. T.13. № 2. id 1849

Konko M.A. Aleksanyan G.K. Pyatnitsyn S.I. Gorbatenko N.I.

DOI: 10.26102/2310-6018/2025.49.2.001

The article presents the results of experimental studies aimed at modeling five basic breathing patterns of newborns using an electrical impedance tomograph and a simplified physical model of the neonatal mediastinum. The study covers such patterns as normal breathing (eupnea), periodic breathing, tachypnea, breathing with retractions and central apnea. The previously developed simplified physical model of the neonatal mediastinum is equipped with a controlled air filling system, which allows reproducing various volumes and modes of ventilation. Experimental studies confirmed the possibility of modeling and recording each of the five breathing patterns using an electrical impedance tomography. The developed technique allows research and testing of new data processing algorithms in the field of electrical impedance tomography of the lungs of newborns. The results confirm that electrical impedance tomography is a promising tool for diagnosing and monitoring respiratory disorders in newborns. The proposed solutions can be used to develop new approaches to the diagnosis and treatment of respiratory diseases in neonatology.

Keywords: electrical impedance tomography, newborns, patterns, diagnostics, monitoring, lungs

Optimization of consumer order fulfillment management in a digitalized organizational system of interaction with producers

2025. T.13. № 1. id 1845

Lvovich Y.E. Preobrazhensky Y.P. Pupykin A.N.

DOI: 10.26102/2310-6018/2025.48.1.043

The article explores the application of an optimization approach in managerial decision-making within a digitalized organizational system for consumer order fulfillment. It is demonstrated that when constructing a model of interaction between consumers and producers, the characteristics of human-machine environment elements must be taken into account. Such consideration enables the optimization of management in the interaction between ergatic and non-ergatic elements based on performance, reliability, and cost indicators. The formation of the optimization model is based on the introduction of alternative variables characterizing the choice of the number of ergatic elements interacting with a specific non-ergatic element. The extremal requirement considered is the maximization of the performance of the consumer order fulfillment process in the digitalized organizational system, while the boundary requirements are the specified levels of reliability and costs. A transition to an equivalent unconstrained optimization function is implemented. The algorithmic procedure for managerial decision-making is oriented towards the structure of the equivalent optimization function and includes several stages: automatic generation of feasible solutions in a randomized environment, iterative settings of variables, verification of the stopping condition for the iterative process, and expert selection of the final solution.

Keywords: organizational system, digitalization, management, human-machine environment, optimization, expert evaluation

Structure of software for managing the activities of an IT company

2025. T.13. № 1. id 1843

Oleinikova S.A. Dyatchina A.V. Politov V.A.

DOI: 10.26102/2310-6018/2025.48.1.044

This article is devoted to the development of software designed to manage the activities of a large IT company by assessing the start time of individual project tasks and assigning specialists to them. Optimizing the process of solving these two interrelated tasks is one of the key factors in the effective functioning of an IT company. In addition to the specific features of this industry, which include different qualifications of specialists, the need to finalize tasks after their completion, and others, a key factor in planning is the periodic occurrence of unplanned events that increase the duration of the project (for example, adjusting certain tasks after agreement with the customer, the emergence of new tasks during discussion, etc.). All this requires the use of new algorithms that take into account the above nuances. This necessitates the development of software that implements the main management mechanisms for IT companies and allows for a prompt response to random factors that lead to a change in the previously found characteristics of the IT project. This software will combine a management system, client applications that allow recording all the nuances related to individual tasks (their implementation, changes in customer requirements, correction, etc.) and a database containing all the data on the project tasks, their interdependence, specialists, etc. As a result, a software structure has been obtained that manages the activities of an IT company by planning the start time of individual tasks, assigning specialists to them, and monitoring execution by introducing subsystems for planning, correction and evaluation of stochastic parameters.

Keywords: project management, IT company management, software, planning, schedule adjustment

Mivar expert system for supporting personnel decision-making in the production of planetary gearboxes

2025. T.13. № 1. id 1842

Antonova A.A. Varlamov O.O.

DOI: 10.26102/2310-6018/2025.48.1.042

The article analyzes the field of production of planetary gearboxes and identifies problems that arise at enterprises during production. As a solution to the problems, the development of a mivar expert system is proposed, the task of which is to monitor the progress of gearbox production, support decision-making and timely notification of enterprise employees about errors and deviations. The relevance of the work is due to the need to increase automation in gearbox production. The decision-making basis will be the mivar knowledge base, for the compilation of which the stages and parameters of the technological process of gearbox production are formalized. The result of the work is a mivar expert system to support decision-making of personnel at an enterprise producing planetary gearboxes. The materials of the article are of practical value for specialists in the field of automation of production processes, as well as for managers and engineers seeking to improve management efficiency and optimize production processes. The scientific novelty of the work is to substantiate the feasibility of using mivar expert systems to automate production processes related to the assembly of gearboxes, their testing and storage in a warehouse. This system can serve as a basis for further developments and research in the field of integrating intelligent technologies into production processes.

Keywords: mivar, gearboxes, production of gearboxes, mivar expert system, knowledge base, wi!Mi, MESD, razumator, big knowledge

Traffic modeling at a regulated intersection using Petri nets with constraints on the crossing time period

2025. T.13. № 2. id 1841

Pechenkin V.V. Kovatsenko I.N.

DOI: 10.26102/2310-6018/2025.49.2.006

The study of optimization of urban traffic flows becomes especially relevant in the current conditions of rapid urbanization and growth in the number of vehicles. Effective traffic flow management allows not only to reduce the level of traffic jams and congestion, but also to improve the environmental situation in cities, reduce travel time for drivers and passengers, and improve road safety. This paper focuses on the methods of traffic flow modeling on the example of a regulated intersection. The authors propose a method for modeling traffic flow based on the use of Petri nets with time constraints. The presented analysis of the computational experiment using the proposed model demonstrates its effectiveness in predicting traffic flows and identifying bottlenecks. The authors propose the structure and rules of functioning of Petri net elements, which allows to adapt the model to the specific conditions of a given intersection. The materials of the paper are of considerable practical value for solving problems of traffic flow optimization at regulated intersections. The proposed methods and models can be used by urban planners and engineers to develop more effective traffic management strategies, which ultimately contributes to improving the quality of life in cities and reducing traffic congestion. Thus, this study makes an important contribution to the development of the theory and practice of traffic flow management, offering new tools and approaches for solving current urban mobility problems.

Keywords: road traffic, controlled intersection, petri net, time restrictions, mesoscopic model

Optimization modeling of personnel management process with automated devices in the information system of customer order fulfillment

2025. T.13. № 2. id 1840

Bakulin A.Y. Lvovich Y.E. Preobrazhensky Y.P. Bukreev A.D.

DOI: 10.26102/2310-6018/2025.49.2.003

The paper proposes an optimization approach to managing the interaction of personnel with automated devices in the information environment of a digitalized organizational system of customer order fulfillment using the results of simulation modeling. To build a simulation model of mass service system, the interaction of personnel with automated devices is considered as the interaction of non-ergatic and ergatic elements in the human-machine environment. The logical scheme of transforming the flow of consumer requests through local aggregators and service channels, including non-ergatic and ergatic elements, when transferring digital data on the order to manufacturers for their material realization is substantiated. It is proposed to vary the intensity of service not by choosing the parallel channels involved, but directly by the value of the total intensity, depending on the number of non-ergotic and ergatic elements. Formation of the optimization model is carried out, the optimizable variables of which are the values of intensities. The requirement of maximizing the system performance is considered as an extreme requirement, and the requirements of providing an acceptable level of costs and probability of erroneous actions act as boundary requirements. Transitions from the optimization problem with constraints to the equivalent optimization problem without constraints are carried out. Algorithmization of managerial decision making on choosing the number of interacting non-ergotic and ergatic elements by building an iterative search process using an optimization model in the process of simulation modeling of a digitalized organizational system of customer order fulfillment is proposed.

Keywords: digitalized organizational system, management, human-machine environment, simulation modeling, optimization

An importance of the portability factor for configuring the cycle of real-time actuator control system

2025. T.13. № 1. id 1839

Zekenskii A.A. Gribkov A.A.

DOI: 10.26102/2310-6018/2025.48.1.037

The paper studies the problem of optimization of real-time control systems described within the actor model. The optimization problem is formulated as a problem of optimal configuration of the control cycle, i.e., distribution of functional elements-actors by groups, flows and execution sequence. We propose a configuration algorithm, which, although it does not reduce the number of analyzed configuration variants, reduces the amount of calculations for each of the variants. In addition to the optimization variants with a limit on the total cycle time and with a limit on the control system resources considered in the authors' previous works, the paper considers the problem of reducing the number of input and output ports through which the element-actors exchange data. The research shows that the number of ports can be reduced without compromising the functionality of the control system. This is due to the sequential nature of element-actors execution within one group of one flow. As a result, the same input or output ports can be used to communicate an actor element with several others. In addition to matching different control loop configurations, the problem of reducing the number of ports can also be solved by using shared memory for element-actor communication. When the control system is built according to memory-oriented architecture, small amounts of data are transferred through high-speed shared memory, which reduces the acuteness of the problem of queue formation.

Keywords: control system, actor model, loop, optimization, configuration, portability, memory-oriented architecture

An intelligent system for evaluating the performance of researchers in research organizations

2025. T.13. № 1. id 1837

Sakharov Y.S. Kovaleva A.V.

DOI: 10.26102/2310-6018/2025.48.1.039

The relevance of the study is due to the fact that in the conditions of high competition for qualified personnel, research organizations seek to attract and retain talented employees. Effective motivation systems based on objective performance assessment are becoming an important tool for achieving this goal. Intelligent systems can provide management with analytical reports and recommendations based on data, which contributes to more informed decision-making in the field of motivation and management of employees. In this regard, this article is aimed at developing an intelligent system for assessing the performance of employees in research organizations, which is a powerful tool for analyzing and managing human capital in organizations. The expert method is based on the involvement of qualified specialists with deep knowledge and experience in the relevant field, which allows to increase the objectivity and reliability of the assessment results. The article describes the advantages and disadvantages of this approach. The work also proposes the use of a machine learning method to assess the performance of researchers based on key performance indicators. The main performance indicators selected for the assessment of labor activity are: scientific and educational activity, scientific work, presentation of results, scientific and educational activity. The materials presented in the article will be relevant and useful for the heads of scientific and research organizations.

Keywords: productivity of work activities, expert assessment method, machine learning, innovation, artificial intelligence, data modeling, researchers

Structural modeling in resource allocation management in a regional organizational system using decision-making intellectualization tools

2025. T.13. № 1. id 1835

Lomakov A.V.

DOI: 10.26102/2310-6018/2025.48.1.035

The paper presents the structuring of the regional organizational system and its management at the model level using the results of long-term statistical information for intelligent decision support. The first structural model allows us to assess the nature of the interaction between the control center and the components of the organizational system based on the used arrays of statistical accounting information. Population groups and territorial entities of the region carry out data transfer in the form of time series. The structural model of intelligent decision support by the control center is a component of the structure of the resource distribution management system. For its effective use as a basis for integrating the results of predictive analysis in the process of making management decisions based on optimization modeling, it is proposed to implement two-level intellectualization subsystems. An algorithmic scheme has been developed that provides two-level intellectualization in making management decisions, combining visual and predictive analysis modules for the subsequent use of the results of machine learning of predictive models in expert assessment and optimization modeling.

Keywords: regional organizational system, management, statistical accounting, predictive analysis, forecasting, optimization

Implementation of a set-theoretic approach to obtain a numerical estimate of data privacy when using modules for blocking access to mobile applications

2025. T.13. № 1. id 1831

Shulzhenko A.D. Kurpachenko D.M. Saveliev M.F.

DOI: 10.26102/2310-6018/2025.48.1.031

This paper considers the problem of assessing the confidentiality of data when using modules for blocking access to mobile applications. Messengers on the iOS17 platform were selected as an example. The relevance of the study is due to the need to increase the level of protection of user data in the face of growing threats to information security. The main goal is to obtain a numerical estimate, and the achievement of the goal is shown using the example of a comparative analysis of the confidentiality of data provided by the means of blocking applications VK, Telegram and WhatsApp. To achieve the goal, the methods of set-theoretical analysis and expert assessments were used. Key parameters for ensuring confidentiality (type and length of the lock code, use of biometrics, auto-lock time, etc.) were identified, normalized in the range [0,10]. The final score was calculated as the sum of the values of particle values for each application. The results showed that Telegram provides the highest level of confidentiality due to the ability to use more complex lock codes and strict security settings. VK is inferior to Telegram in a number of parameters, but demonstrates better results compared to WhatsApp, unless all parameters are forcibly disabled. The findings of the study can be used to improve data protection mechanisms in mobile applications, and the proposed methodology can be used for further research in the field of information security.

Keywords: data privacy, access blocking, PIN lock, privacy assessment, messenger security, personal data, set-theoretic analysis, application auto-locking, notification content hiding, user data protection

Assessing the quality of the result in the problem of source code generation from an image

2025. T.13. № 1. id 1830

Nikitin I.V.

DOI: 10.26102/2310-6018/2025.48.1.030

This study is an assessment of the feasibility of building a system for executing functional tests for the task of generating source code from an image. There are many different metrics for assessing the quality of text predicted by a neural network: from mathematical ones, such as BLEU, Rogue, and those that use another model for evaluation, such as BERTScore, BLEURT. However, the problem with generating source code for a program is that the code is a set of instructions to perform a specific task. The relevance is that in publications related to the pix2code system, there was no mention of an automated test environment that can check whether the resulting code meets the specified conditions. In the course of the work done, a subsystem was implemented that can automatically obtain information about the differences between an image based on a predicted code and an image based on a reference code. Also, the results of this system are compared with the BLEU metric. As a result of the experiment, we can conclude that the BLEU value and the execution of tests do not have an obvious relationship between them, which means that tests are necessary for additional checks of the efficiency of the model.

Keywords: code generation, image, machine learning, BLEU, functional tests

Using graph neural networks for solving the Steiner tree problem

2025. T.13. № 1. id 1828

Piminov D.A. Pechenkin V.V. Korolev M.S.

DOI: 10.26102/2310-6018/2025.48.1.038

The theory of discrete optimization plays a crucial role in solving graph theory problems, such as the Steiner tree problem. It is widely applied in transportation infrastructure, logistics, and communication network design. Since the problem is NP-hard, heuristic methods such as genetic algorithms and artificial neural networks are often required. To solve the Steiner tree problem, a graph neural network (GNN) was selected. The GNN architecture involves iterative feature updates using information from neighboring nodes, allowing it to model complex dependencies in graphs. A message-passing neural network (MPNN) mechanism is employed for information aggregation, updating node states based on data from adjacent nodes and edges. The model is trained on graphs generated using the Melhorn heuristic algorithm. Experiments show that GNN performs well on graphs similar to the training data but experiences a significant drop in precision and recall metrics as the input graph size increases. This decline is likely due to the limitations of the MPNN mechanism, which aggregates information only from neighboring nodes within a limited range. Graph neural networks demonstrate strong potential for small- and medium-scale graph problems, particularly in analyzing complex systems such as wireless networks, where node interconnections are critical. However, as graph size increases, performance deteriorates, highlighting the need for improvements in aggregation and optimization algorithms.

Keywords: steiner tree problem, graph neural networks, graph theory, artificial neural networks, mehlhorn algorithm