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

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issn 2310-6018

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metadata of articles for the last 2 years

Product specification transfer standard

2023. T.11. № 3. id 1388

Shishkin A.G.

DOI: 10.26102/2310-6018/2023.42.3.007

The economic indicators of any online store directly depend on the quality of product content. The acquisition of such content is often automated, but there is no single data exchange format on the market yet. As a result, companies spend a lot of resources integrating with various content suppliers and consumers. The author of the article proposes a format for process standardization taking into consideration the features of all types of e-commerce market participants. The format is based on the experience of developing a technological platform for a large online store and its integration with partners. The features of various market segments, types of goods, statistical data, existing exchange formats, international standards, market development trends are accounted for. The format is designed so that any market representative can start using it by means of the converter modules based on reading the required speed of commodity consumption detail without major modifications inside the access system. Such standardization will help to cut costs for market participants while integrating mutually, quickly distribute quality content, verify it, reduce the number of errors. This may lead to increased competition as small market participants will have equal access to data. Ultimately, all of this will enable venders offer their clients higher quality services and reduced prices.

Keywords: product content, database, content analytics, content error control, quality management, product card, electronic product passport, e-commerce, content transfer

Computational modeling of coolant flow in channels of complex shape at high medium parameters

2023. T.11. № 3. id 1387

Rosnovskii V.S. Yaurov S.V. Danilov A.D. Gusev K.Y.

DOI: 10.26102/2310-6018/2023.42.3.010

Nowadays, modeling the flow of a medium in channels of complex shape is impossible without the use of numerical methods. The complexity of the form should be understood as the impossibility of a formulaic assignment of a function that would describe the change in the shape and area of the flow living section. Nevertheless, channels of complex shape are of interest for practical use in various fields of industry. A special case of such a channel is a hydraulic diode. The main purpose of the paper is the computational modeling of the flow of the medium in a hydraulic diode at elevated parameters of the medium by means of finite element methods. The relevance of the research lies in the absence of experimental studies and examples of the operation of hydraulic diodes at elevated environmental parameters. In this paper, a hydraulic diode is modeled according to the schematics by physicist Nikola Tesla. The parameters of the medium were set as follows: pressure 16 MPa, temperature 298 °C. As evidenced by the results of calculations, the ratio of hydraulic resistances at different directions of the medium flow was 19–23. It was found that the hydraulic diode is not applicable as a check valve in technological systems since it is not able to completely block the return flow. It was also demonstrated that the hydraulic diode is physically more effective than classical leak limiters because it has a jet reaction force in the "small leak" mode of 24.5 kN versus 220 kN of the closest classical leak limiter in terms of parameters. The results of the research indicate the complex nature of the efficiency of hydraulic diodes. They also made it possible to estimate the parameters and nature of the flow of the medium in channels of complex shape with increased parameters of the medium. They can be used to optimize future calculations and modeling of hydraulic diodes for various technological systems.

Keywords: hydraulic diode, diodicity, tesla valve, jet reaction force, insert-leak limiter

Researching the refractive index of seawater for underwater radio communication

2023. T.11. № 3. id 1385

Preobrazhenskiy A.P. Preobrazhenskiy Y.P. Avetisyan T.V. Lvovich Y.E.

DOI: 10.26102/2310-6018/2023.42.3.025

Underwater radio communication is necessary for the exchange of information with various objects that are under water, especially at great depth. In addition, the development of radio oceanography has made it possible to carry out remote monitoring over large areas of the World Ocean. The effectiveness of radar measurements will be greatly influenced if various processes that affect the interaction of radio waves with the sea surface is accounted for. To achieve this, it is necessary to develop various models. This paper examines the problem of electromagnetic wave propagation through the interface of two media: air and sea water. Models of reflection and refraction of an electromagnetic wave are presented. Different cases of polarization are considered. Properties of water found in seas and oceans are analyzed. It is shown how the dielectric permittivity of water depends on such characteristics as salinity and temperature. The salinity values of the Atlantic, Pacific and Indian Oceans are given. The case of an ultra-long wave falling on the boundary between air and water was regarded. The refractive coefficients of the electromagnetic wave were calculated depending on the angle of its initial propagation at given values of salinity and temperature.

Keywords: radio wave propagation, communication, refractive index, electrodynamics

The algorithm to determine the highest priority of enrollees in the 2023 admissions campaign

2023. T.11. № 3. id 1384

Baryshnikova N.Y. Fedkin P.S. Knysh T.P.

DOI: 10.26102/2310-6018/2023.42.3.026

In 2023, changes to the admissions procedure came into force which affected enrollment in educational programs of higher education – bachelor's programs, specialty programs, master's programs for the academic year 2023/2024. The main innovation of the future admission campaign is the enrollment of applicants based on priorities. By prioritization, the applicant demonstrates his or her desire to be enrolled in specific fields of study in a particular order. The authors concluded that there is a problem associated with the lack of an algorithm that helps to automatically determine the highest priorities of the applicant at each stage of enrollment. Therefore, the purpose of the study is indicated – to develop an appropriate algorithm. The Gale-Shapley algorithm and its scope are considered – in particular, the possibility of using it to stable matching between applicants and competition groups. It was concluded that this algorithm cannot be employed by educational organizations of higher education in the 2023 admissions campaign due to the existing assumptions in its operation. We have proposed our own methods for solving the problem of determining the highest priorities according to the approved admission rules for the academic year 2023/2024. The article presents a mathematical model of the problem and the computational part of a computer program using Python programming language. The algorithm will be tested at Admiral Makarov State University Maritime and Inland Shipping during the admission campaign in 2023. The materials of the article are of practical value for the admission commissions of educational organizations.

Keywords: education, admissions office, enrollee, highest priority, enrollment, algorithm, stable matchings

Metrics of semantic proximity of a user's request as a security criterion in a thematic hierarchical access control model

2024. T.12. № 1. id 1382

Khvostov V.A. Sych G.V. Choporov O.N. Gulov V.P.

DOI: 10.26102/2310-6018/2024.44.1.030

The increasing scope of application of mobile technologies and devices as elements of distributed systems to enhance the efficiency and convenience of access to various information systems and digital services has made it necessary to improve methods and mechanisms for information protection and information security. One of the main security mechanisms is access control. Features of traditional (discretionary and mandatory) access control model application in distributed information systems (IS) when using mobile systems (MS) as elements are analyzed. Thematically, hierarchical model is proposed as the most effective model that meets the required security policy. For this access control model, an ontological method for forming trust rights to access objects is proposed based on the use of semantic proximity metrics. When using traditional thematic hierarchical access control models, the logical information architecture of IS resources forms a thematic hierarchical classifier (categorizer). The Hasse diagram introduces order relations in the thematic classifier on the security grid to form trust-thematic powers of IS users. Constructing Hasse diagrams on a security grid that includes several security levels is a rather complex algorithmic task. When constructing trust-thematic powers of users in order to avoid uncertainty due to the incompleteness of the constructed Hasse diagram and overestimation of the granted powers when forming access rights, it is proposed to use the semantic proximity of the user access request and the thematic heading of the hierarchical classifier. An analysis of existing approaches to the formation of semantic proximity metrics has shown that proximity measures based on the hierarchy of concepts can be used as the best metric for setting the user’s trust authority.

Keywords: mobile station, access control, hierarchical thematic classification, semantic proximity, semantic distance

Formation of data in fixations of oil and gas well models using an intelligent method for missing value completion

2023. T.11. № 2. id 1381

Shariyanov N.V. Latypova V.A.

DOI: 10.26102/2310-6018/2023.41.2.022

In the oil and gas sector, a lot of attention is paid to the issue of improving the quality of data because poor quality can distort the presentation of the situation and eventually cause making the wrong decision. Oil production monitoring and preventive maintenance involve the collection of data from a variety of sensors that need to be correctly processed and “packaged”. Therefore, particular emphasis is given to improving the quality of the generated data in oil and gas well model fixations. Fixing oil and gas well models is the process of collecting, analyzing, and storing information about well operation parameters such as fluid, gas and oil flow rates, pressure, temperature, fluid composition, and other parameters used to optimize production processes and improve well performance. The presence of gaps in the formation of well models can significantly reduce the quality of these models, which can lead to an incomplete representation of the overall picture of well operation and decrease the accuracy of predicting its productivity. The article proposes an intelligent method of completing missing values for generating data in fixations of oil and gas well models to solve this problem. The method has been successfully tested at the oil and gas company Gazprom Neft PJSC using the data on the fluid flow rate of the wells in the Vyngapurovskoye field.

Keywords: intelligent method, completing missing values, nearest neighbor method, data quality, oil and gas well, well model fixation

A technique for selecting cutting conditions based on the control of average chip thickness

2023. T.11. № 3. id 1378

Khisamutdinov R.M. Urmanov M.D. Khusainov R.M.

DOI: 10.26102/2310-6018/2023.42.3.004

Managing the pace of production is a relevant issue for a modern enterprise. It is necessary to select cutting tools and cutting conditions according to a given schedule. Errors in the production process can lead to huge time and money costs. The main goal of this paper is to provide a flexible algorithm that will allow the user to select the optimal combination of cutting conditions in compliance to the production rate. The algorithm being developed also helps to quickly respond to errors that occur during the production process. The theoretical model shows the user the risks when using a particular pace of work. The technologist will be able to make a decision independently while taking as a basis data on the tool life and productivity. The presented algorithm is based on the control of the average chip thickness. This makes it possible to describe the theoretical “cutting pattern” for any pair of tool and workpiece material. The paper presents a comparative analysis of the algorithm and tabular values of cutting modes. Following on from this analysis, it is apparent that the representation obtained by the technique used in this paper helps to analyze in more detail the rationality of choosing certain cutting modes.

Keywords: optimal tool wear, chip thickness, feed per tooth, theoretical cutting force, specific cutting force, net cutting force

Construction and selection of signs for non-invasive endometriosis diagnostics using machine learning

2023. T.11. № 2. id 1375

Korotkikh I.N. Rusinova A.K. Usov Y.I.

DOI: 10.26102/2310-6018/2023.41.2.021

Endometriosis is a common but poorly understood disease. From the appearance of the first symptoms to the diagnosis, it sometimes takes more than ten years. There is still no treatment that can help to recover from it completely. Computational models can help in understanding the mechanisms by which immune, hormonal and vascular disorders manifest in endometriosis and complicate treatment. The study deals with the construction and selection of signs of endometriosis risk and the formation of a mathematical model using several machine learning algorithms. In this case, an analysis of the importance of the signs is carried out, in which a subset of the signs that do not degrade the performance characteristics of the model (accuracy, speed, stability of operation) is reduced. The method which enables the selection of signs for constructing a prognostic model based on a selector containing filtering methods of sign significance for a processed data set is proposed. Voting for the inclusion of the sign is carried out by means of the majority function. The quality of sign construction and selection in the subject area of non-invasive diagnosis of endometriosis was assessed by a mathematical risk prediction model for endometriosis based on logistic regression with 30 traits. Model performance was evaluated using common machine learning metrics: accuracy, sensitivity, specificity, F1-score, and area under the ROC curve. The best result was achieved with an AUC of 0.950. The material is valuable to medical professionals in cybernetics.

Keywords: machine learning, non-invasive diagnosis, logistic regression, prediction, endometriosis

Optimizing interaction of the components in a human-machine system of digitalization

2023. T.11. № 2. id 1374

Yermolova V.V. Lvovich Y.E. Preobrazhenskiy Y.P.

DOI: 10.26102/2310-6018/2023.41.2.031

The article considers the application of the optimization approach to ensuring efficient interaction of the components in a human-machine system of digitalization. The structure of such system is seen as a junction of ergatic elements with reference to nonergatic elements when performing a set of tasks of digital transformation. The formalized description of the two primary objectives is given, they include optimizing the number of ergatic elements involved in the support of the performance of digitalization system nonergatic elements and distributing the tasks among ergatic elements. The optimization models on a set of Boolean variables have been developed and the modifications to the algorithms of guided random search have been proposed. As the optimization criterion, a number of indicators are considered – performance, reliability and cost. The optimization model of the first objective is bicriterial. To define it, the integer values of the ergatic components that interact with the nonergatic elements in binary notation are recorded on a set of Boolean variables. The optimization problem is solved by means of guided random search managed for each iteration by changing the value of additive convolution of standard criteria values based on expert assessment of their priority ranking. Probabilistic characteristics of engagement in the search for Boolean variables are adjusted in concurrence with the development of convolution. The final solution is selected by group expert assessment. The optimization model of the second objective is created on a set of Boolean variables characterizing the engagement of the ergatic component in solving the specific problem of digitalization. At the same time, average operation time for the set of tasks in its entirety is regarded as an extreme requirement while boundary requirements are determined by the completion of each task within a single time frame using one ergatic element. Implementation of the guided random search algorithm is characterized by the awareness for multi-index representation of Boolean value variables and the means for excluding the solutions that do not comply with boundary constraints.

Keywords: digitalization, human-machine system, boolean optimization, random search, expert assessment

Mathematical modeling of the coolant flow in a Venturi nozzle at high medium parameters by means of the finite element method

2023. T.11. № 3. id 1372

Yaurov S.V. Danilov A.D. Gusev K.Y. Skorodumov D.G.

DOI: 10.26102/2310-6018/2023.42.3.019

Venturi nozzles have found quite wide application in various industries. The paper considers the design and operating modes of the basic leak limiter made in the form of an asymmetric Venturi nozzle which is one of the technological systems of the first circuit of the Novovoronezh NPP-2 power unit No. 1 (NPP-2006 project). Methods for modeling in the ANSYS CFX software and hardware complex using the finite element method and operating modes of the device to assess its effectiveness in emergency mode and normal operation mode are presented. The results of thermohydraulic calculations of the stationary operation mode of the leak limiter insert are given, comparison with the results according to basic calculation methods is performed. The complexity of the task being performed lies in the fact that the leak limiter is installed on the pipeline where the coolant has a temperature significantly higher than the saturation temperature consistent with the pressure of the medium into which the leakage occurs when the pipeline breaks. The section of the cylindrical neck of the minimum cross-section provides boiling of the liquid within its length, which leads to partial self-locking of the leaking coolant flow because of enabling a critical flow mode; in essence, this refers to the solution to the problem of a two-phase medium flow.

Keywords: leak limiter insert, venturi nozzle, modernization, purge, pipeline rupture, coolant leak, finite element method

Mathematical modeling of composite technological systems by the finite element method

2023. T.11. № 3. id 1371

Yaurov S.V. Danilov A.D. Gusev K.Y. Gusev I.N.

DOI: 10.26102/2310-6018/2023.42.3.024

The finite element method has been known for a long time, but its active application for modeling physical processes began shortly after the development of modern computer machines. One of the advantages of such modeling is the reduction of time and financial costs compared to conventional experiments. The paper presents the results of hydraulic calculation of the design mode of a complex technological system operation by the finite element method. The calculation was performed using the thermal hydraulic CFX module of Ansys software package. At the same time, as part of the computational domain, a porous body model was employed as an alternative to direct modeling of system devices with a complex design. The object of the simulation was the cooling tower recharge system of power unit No. 1, 2 of Novovoronezh NPP-2. The test (verification) calculation showed an acceptable discrepancy with the real parameters of the system (within 15 %). According to the results of the computational analysis, the optimal number and combination of constantly operating pumps in the system were identified which achieved an increase in the consumption of the main cooling water by 30-40 % which, in turn, will reduce the accumulation of calcium carbonate on the main structural elements of cooling towers. The porous body model can be used both to predict the operating modes of equipment with complex design individually and as part of technological systems.

Keywords: complex technological systems, purging, operation, main cooling water, cooling tower, water chemistry specifications, porous body model, finite volume method

Algorithmizing the management of project launch risks

2023. T.11. № 3. id 1368

Rossikhina L.V. Kalach A.V. Nefediev S.A.

DOI: 10.26102/2310-6018/2023.42.3.005

Nowadays, increasing attention is paid to the issues of risk assessment and management, which are strongly associated with the globalization process of modern civilization. Based on the analysis and generalization of available statistical data on project risk management, it was found that less than half of the existing organizations carry out activities aimed at risk management (identification, monitoring, development and implementation of risk mitigation measures). The article considers a special case of solving the problem of risk management which consists in achieving the goal of the program at minimal cost taking into account restrictions on financing high-risk projects or on their number. It should be noted that in the existing documents on the regulation of project management processes, there is no methodological support for identifying, assessing and minimizing risks at all. In addition, there are currently no effective methods of comparative identification, analysis of interrelations and mutual influence of risk values and mechanisms for their minimization in the implementation of projects and project management. To account for the degree of project implementation risk, two objectives of forming the programs being implemented are proposed. The first objective implies identifying single-purpose projects for inclusion in the program that ensures the achievement of its goal at minimal cost with due regard for restrictions on high-risk project funding or their number. An original algorithm for solving the problem based on the branch-and-bound method with the proposed method for estimating a subset of solutions from below and an approximate heuristic algorithm using the “expense-effect” method are presented. The second objective was to reduce the cost of implementing the program by converting a number of low-risk projects to medium- and high-risk options. To solve this problem, the branch-and-bound method to obtain estimates of solutions by the network programming method was employed.

Keywords: project, program, risk, branch-and-bound method, heuristic algorithm, generalized dual problem

Approaches to the development of mutual information coordination algorithm for intelligent agents in a distributed multi-agent monitoring system

2023. T.11. № 3. id 1367

Rykshin M.S.

DOI: 10.26102/2310-6018/2023.42.3.003

The article discusses the rationale for the choice of methods and algorithms for mutual information coordination (consensus achievement) in a distributed multi-agent system used to solve the problem of information monitoring in complex technological objects. The architecture of this multi-agent system is decentralized and based on the set of intelligent monitoring agents that receive and process data from the object under control which is a part of the system within which information monitoring is performed. The purpose of the monitoring is to predict the instances of non-stationary load occurrence at the objects being monitored. A feature of the system is the presence of non-stationary load propagation time lag over the subsets of monitoring objects. The problem of predicting the instances of non-stationary load occurrence and propagation as part of an intelligent monitoring agent is solved by means of a neural network model trained using the precedents occurring at the object. To account for the propagation of non-stationary load time lag, it is proposed to perform additional training of the neural network model not only on its own data set, but also on the data sets of the nearest neighbors connected by the propagation of non-stationary load time lag which requires solving the problem of their mutual information coordination. The article discusses approaches to the selection and modification of the algorithms for the multi-agent system architecture – multicast messaging concerning the instances of non-stationary load occurrence and routing of these messages in a decentralized structure of an information monitoring system. The data structures necessary for these algorithms and protocols for the interaction of intelligent monitoring agents, which provide an increase in the speed of message delivery, are considered.

Keywords: monitoring systems, multi-agent systems, intelligent agent, consensus achievement, decentralized systems, message routing, message delivery time

Configuration and development of artificial neural network model for spacecraft power supply system control system under the conditions of uncertain factors

2023. T.11. № 2. id 1366

Loginov I.V. Burkovsky V.L. Netesov G.A.

DOI: 10.26102/2310-6018/2023.41.2.016

The paper considers uncertain factors that can lead to abnormal situations in the control system of the power supply system of a spacecraft. Certain factors that can be predicted as well as factors whose influence can be accounted for when designing the control system and building control algorithms are highlighted. Uncertain factors that can be predicted using the intellectualization of electric power distribution control system have been identified. Elements of the system the reliability of which can be improved by applying intelligent control system and the prediction of abnormal situations on the basis of artificial neural networks have been identified. The analysis of existing control algorithm for power supply system has been carried out. By means of the telemetry parameters used in this algorithm, selected telemetry parameters for use in the intelligent control system of the power supply system have been identified. The criterion for an emergency situation the occurrence of which must predict the artificial neural network is defined. The configurations of artificial neural networks which can be used as a foundation for intelligent control system of power supply system of a spacecraft are considered. The problem of available training data sample optimization for training the artificial neural network is regarded. Suitable methods for the optimization of neural network training in the context of the specifics of the problem are considered. A specific configuration of artificial neural network, mindful of the specifics of application and the heterogeneous nature of the training data sample, is proposed.

Keywords: spacecraft power supply systems, regulation and control equipment, neural networks, intellectualization, forecasting systems

Information structure of power supply system and spacecraft regulation and control equipment

2023. T.11. № 2. id 1365

Loginov I.V. Burkovsky V.L. Netesov G.A.

DOI: 10.26102/2310-6018/2023.41.2.019

Improving the quality of automatic control systems is an important problem in many areas. This issue is particularly relevant in systems requiring an increased level of reliability, such as control systems for space equipment including power supply systems. Power supply systems must fully meet the need of a spacecraft in electric power required for regular flight program performance, which implies the increased requirements for its reliability and quality of its operation. The article considers functional and informational structure of spacecraft power supply systems. The principles of data exchange between the elements of regulation and control equipment with the power supply system are described and the hierarchical structure of the power supply control system elements is built. The current approaches to the automatic systems of control and management of spacecraft power supply systems are regarded. Based on these data, the algorithms of power supply system control are analyzed using the example of battery charging and discharging algorithms. The phenomena which are not accounted for when building the algorithms are considered. The means to improve the algorithms for controlling battery charging and discharging by introducing new parameters to track the degree of battery degradation are proposed, and the means of intellectualizing the algorithm are considered. A proposal is made to intellectualize the control system using a neural network trained on the spacecraft onboard telemetry.

Keywords: control algorithms, spacecraft power supply systems, regulation and control equipment, onboard computer network, control system intellectualization

Finite-dimensional analogues of transfer differential operators with carriers on spatial networks

2023. T.11. № 2. id 1363

Hoang V. Makhinova O.A. Timoshenko V.V.

DOI: 10.26102/2310-6018/2023.41.2.030

The presented results provide justification for the applicability of numerical methods for analyzing initial-boundary value problems for evolutionary differential equations with a spatial variable changing on a network (graph), i.e., on a manifold of one-dimensional continua with a scalar variable. Similar results for -dimensional spatial variables ( ) changing on a network-like -dimensional domain are still in the stage of formation due to the incomparably high level of technical complexity that naturally arises when increasing the dimensionality of the spatial variable. Confirmation of the possibility of justifying numerical methods for analyzing initial-boundary value problems for cases is provided using the results of applying computational methods to solving a test problem with a spatial variable changing on a two-dimensional network-like carrier – a two-dimensional complex-structured domain. The presented example of numerical analysis opens prospects for extending the obtained results to differential operators defined on functions with an m-dimensional carrier. To simplify the representations of difference schemes, a method of semi-discretization with respect to the time variable is used (in a sense, numerous routine costs that arise as a direct consequence of the multidimensionality of the spatial variable are leveled). The obtained results are applied in constructing and numerically analyzing mathematical models of laminar and turbulent network-like processes in applied hydrodynamics.

Keywords: differential operators on network-like domains, finite-dimensional analogues, properties of finite-dimensional analogues, difference schemes, numerical analysis

On the issue of cost minimization in GERT-network models of UAV transport and technological cycles

2023. T.11. № 2. id 1362

Kovalev I.V. Kovalev D.I. Komil D.A. Podoplelova V.A. Ikonnikova M.F.

DOI: 10.26102/2310-6018/2023.41.2.014

The article discusses the use of a graphic-analytical method for evaluating and revising plans for GERT-network modeling of transport and technological cycles of unmanned aerial vehicles utilized in the precision farming system. A formal description of the model and an algorithm for searching for the optimal implementation of the UAV transport and technological cycle are proposed, which allows minimizing the costs of its implementation taking into account the characteristics of production situations that arise in the precision farming system when using the UAV. The formalization method is based on the notion of the UAV transport and technological cycle as an acyclic GERT network with a source and sinks. Since the stochastic dynamic structure of the transport-technological cycle is considered, the possibility of introducing random events during its implementation and the execution of several successive cycles is provided. At the same time, the minimum possible costs when performing these transport and technological cycles must satisfy the optimality criterion. It is suggested to switch to cost reduction by means of an iterative procedure at the optimization stage taking into account the finite number of UAV transport and technological cycle implementation stages. As a result, the decision maker, employing the decision GERT network, will be able to choose the implementation of the transport and technological cycle that minimizes costs for its implementation. The paper proposes an algorithmic procedure that ensures the choice of the best possible solution, which helps to increase the efficiency of formation, analysis and management of UAV transport and technological cycles, as it enables full consideration of the characteristics of production situations in precision farming systems using unmanned aerial vehicles.

Keywords: GERT-network, modeling, cost minimization, unmanned aerial vehicle, transport and technological cycle

Optimizing a human-machine environment for enterprise management using a cyber-physical system

2023. T.11. № 3. id 1360

Yermolova V.V. Lvovich Y.E. Preobrazhenskiy Y.P.

DOI: 10.26102/2310-6018/2023.42.3.001

The article considers the application of the optimization approach to enterprise management using a cyber-physical system. A human-machine environment is the object of optimization. Features of interaction of nonergatic elements with the elements of physical and computational levels of cyber-physical architecture are observed. It is shown that ergatic element function allocation by the indexes of reliability and efficiency of a human-machine environment is the optimization task at the lower level. In the formalized form, the optimality requirements determine the multi-objective model by a set of alternative variables. The decision-making algorithm based on random search combined with expert assessment is offered. The capabilities of establishing the division of the total amount of ergatic OS elements between three functions at the initial stage of the search by expert way followed by the assignment of each ergatic element in the iteration mode have been considered. The optimization of a human-machine environment at the upper levels of a cyber-physical system is aimed at assigning each ergatic element to perform a specific action. The structure of the optimization model differs from the first task. The developed decision-making algorithm based on the integration of random search iteration procedure and expert assessment procedure is used for both optimization tasks. Multicriteriality is accounted for along with the iterations of probabilistic characteristic adjustment by changing the probability of engaging the criteria in the search. The models and algorithms listed above help to optimize the structure of ergatic element operation in a human-machine environment for enterprise management using a cyber-physical system.

Keywords: organizational system, management, human-machine environment, cyber-physical system, optimization

Development of StegoStream decorator for associative protection of byte stream

2023. T.11. № 2. id 1359

Vershinin I.S. Gibadullin R.F. Gashigullin D.A.

DOI: 10.26102/2310-6018/2023.41.2.023

The .NET streaming architecture is based on three concepts: reference repositories, decorators, and adapters. A reference repository represents an endpoint, such as a file on a storage device, an array in RAM, or a network connection. It cannot be used unless the programmer has access to it. The standard .NET class designed for this purpose is Stream; it provides a standard set of methods that allow byte-by-byte reading, writing, and positioning. Streams fall into two categories: streams with reference repository and streams with decorators. Streams with reference repositories and streams with decorators deal exclusively with bytes. While flexible and efficient, applications often operate at higher levels, such as text or XML. Adapters bridge this gap by putting a stream into a class shell with specialized methods that are typified for a specific format. The paper presents the StegoStream decorator developed by the authors, which is based on associative data protection mechanism. This decorator has the following advantages: it provides interaction with the adapter; it releases streams with reference repositories from the necessity of independent implementation of such features as hiding and unhiding; streams decorated with StegoStream do not suffer from interface changes; StegoStream may be used when chaining with other decorators (for example, the compression decorator may be combined with the hiding decorator). Practical use of StegoStream decorator is presented drawing on the example of the developed multi-client secure chat with a centralized server.

Keywords: associative steganography, cryptography, streaming architecture, decorator, information security

Object detection and tracking when constructing mobile robot motion trajectory using image processing

2023. T.11. № 2. id 1356

Han M.H. Aleksey N.Y.

DOI: 10.26102/2310-6018/2023.41.2.027

Currently, mobile robot (MR) technologies are rapidly developing with a view to performing reconnaissance tasks on land, underground, on water, under water and in space. To provide MR motion control, various methods such as building trajectories using sensors and cameras are employed as part of these developments. The main objective of this article is to study the process of detecting and tracking objects when constructing MR motion trajectories. As a result of operating in real time using video processing from a video surveillance camera, the motion parameters of objects were successfully detected and identified. The obtained data were utilized to calculate the coordinates of the position of objects in pixels, which in turn helps to determine the distance and angular velocity of the MR. To determine the MR motion trajectory, the resulting image was processed by means of the full-featured MATLAB/Simulink programming language. This makes it possible to ensure the accuracy of calculations and obtain more detailed information about the trajectory of the MR. In general, the use of mobile robot technologies in various fields is a relevant and promising direction for scientific and engineering research.

Keywords: detection, tracking, mobile robot (MR), video surveillance, distance, angular velocity

Methodology for developing and selecting the project of a fire protection system

2023. T.11. № 3. id 1355

Nikulina Y.V. Shulga T.E. Sytnik A.A.

DOI: 10.26102/2310-6018/2023.42.3.009

The article is devoted to the issues of analyzing a large number of regulatory documents in the design of fire protection systems. The main characteristics of the object are defined, which determine the design decisions when creating such a system. A technique for choosing the most significant factors and criteria for making fundamental design decisions is described; they make it possible to establish if it is necessary to equip the facility with a particular type of fire automatics systems. The implementation of existing foreign applications in Russian design companies causes difficulties associated both with the lack of a regulatory document base and with the peculiarities of introducing foreign products, including the reorganization of business processes and the requirement to retrain personnel. Specialists can spend hours adding to these systems the information that complies with the Russian legislation as well as reference information, for example, from a guide to combustibility of materials. The article describes the structure and composition of the decision support system that helps to create an accompanying fire protection system for the project as well as to choose a configuration according to the specified criteria. The ontological model developed by the authors is the knowledge base of such a system. The generated RDF file and the ontology of the subject area "Fire protection systems" are available in the public domain. Although they were developed for a specific application, they can be used by developers to solve other problems in the design, installation and maintenance of fire protection systems.

Keywords: fire safety, fire protection system, project development methodology, decision support system, criteria for making fundamental design decisions

Analysis of the possibilities of passive radar when operating in the ultrashort wave range

2023. T.11. № 2. id 1354

Unger A.Y.

DOI: 10.26102/2310-6018/2023.41.2.025

The article proposes an analysis of radio transmitters operating in the ultrashort wave range as a convenient signal source for determining the detection range in a passive bistatic radar. A theoretical analysis of the main specific features of a bistatic passive radar is presented; its energy characteristics are considered along with the impact of various types of noise during instantaneous reception of a direct illumination signal and weak reflections from an object. The bistatic characteristics of the passive technology were evaluated when designing such radar for long-range object detection. Additionally, the dynamic range of the passive radar receiver when exposed to noise and the power of the reflected signal based on the effective scattering area, which makes it possible to create a more effective bistatic passive detection technology, was investigated. Experimental evidence is presented in the form of the mathematical modeling, which includes scanning the spectrum of the ultrashort wave range under various conditions for long-range detection of objects. Several options for influencing the range of different terrain and landscape conditions are considered. The results of the mathematical modeling are compared with the theoretical analysis of the specific features of a passive bistatic radar.

Keywords: detection range, band, radar, bistatic technology, interference

Mathematical models for calculation and analysis of resources efficiency use indicators of automated control systems

2023. T.11. № 2. id 1346

Bochkarev A.M.

DOI: 10.26102/2310-6018/2023.41.2.018

The modern automated control system (ACS) of production processes is characterized by a fast pace of updating, an increase in the volume of incoming information, and the development of integrated management processes. This is achieved through the introduction of corporate information systems, information and telecommunication technologies, and professional training of specialists. At the same time, experience shows that all the capabilities of the currently functioning automated control systems are not fully utilized, and the available information technologies and resources are not used effectively enough. There are also problems with the coordination of information resources and the availability of specialists who are able and ready to use them. In the process of evaluating the subsystems of an industrial enterprise (organization) automated control system, the principle of uniformity is highlighted which determines the continuity of the managerial business processes of industrial enterprise management when improving the technical, system-logical, applied and organizational-methodological subsystems of an automated control system ensuring the integration and coordination of linear and functional link interaction in the rational allocation of resources for the production of marketable products. The paper considers business procedures for analysis, evaluation, and design of an automated control system according to various criteria. The following criteria are proposed: availability, accessibility, demand. The current performance indicators of the enterprise (organization) operation are evaluated and compared with the specified ones. The method of automated control system improvement has been developed, which made it possible to identify "bottlenecks" using forecasting tools, make the necessary management decisions and evaluate the results of their impact. Based on the conducted research, the model for evaluating the improvement of the automated management system of an industrial enterprise has been developed using an approach that evaluates the current performance indicators of the enterprise (organization) operation. The materials of the article are of practical value for improving the economic activities of enterprises and organizations of various kinds using the proposed mathematical, software and methodological tools.

Keywords: automated control system (ACS), efficiency management of the organizational and economic system, expert assessment, availability, affordability, demand, controlling influence

Means for monitoring, modeling and predicting the concentration of urban air pollution by microparticles

2023. T.11. № 2. id 1345

Vyalova E.P. Kvashnina G.A. Fedyanin V.I.

DOI: 10.26102/2310-6018/2023.41.2.008

Air pollution is one of the biggest threats to the environment and humans. Due to meteorological and transport factors, industrial activity and emissions of power plants are the main agents of air pollution. Therefore, environmental authorities are focused on the effects of air pollution and the development of guidelines to minimize it. The main objective of this study is to design a system that uses a machine learning approach for predicting urban air pollution by analyzing a set of data on air pollutants, PM2.5 particulate matter in particular. A linear controlled machine learning algorithm, which has a RMSE error value of 31.29 and a Decision Forest Regression algorithm with an RMSE value of 29.26, is used for predictions. The system is developed on a web-based platform and is accessible for mobile phones; it is user-friendly and represents the values of air pollutant concentration with PM2.5 particles and the values of the air quality index. Values of PM2.5 particle concentration are dependent on other sources and background levels, which indicates the importance of localized factors for understanding spatio-temporal model of air pollution at intersections and supporting individuals making decisions in the field of regulating and controlling pollution in cities.

Keywords: air quality, PM2.5 microparticles, machine learning, regression models, SDS011 sensor, forecasting

Application of the individual-based model for the epidemic process modeling

2023. T.11. № 2. id 1344

Borisenko A.A. Borisenko A.B.

DOI: 10.26102/2310-6018/2023.41.2.024

Forecasting of epidemic processes makes it possible to develop and substantiate measures to prevent the spread of infectious diseases among the population as well as eliminate the negative consequences caused by epidemics. The paper deals with modeling the development of the epidemic process by means of an individual-based model. In these models, modeling is carried out using not an average group, but an individual level with consideration to the heterogeneity of the population by characteristics. Each individual can have three states: Susceptible (S), Infected (I), or Recovered (R). Transmission in a population occurs from individuals in state I to individuals in state S. After recovering, individuals I change state to R and become immune. Immunity wanes over time and individuals R revert to a susceptible state S. This paper is devoted to the development and software implementation of an algorithm for solving an individually oriented model, which helps to study the population dynamics of those groups. The results obtained for various model parameter values are presented. The results obtained using the individual-based simulation are compared with the results obtained by solving numerically the well-known SIRS model, which is a system of ordinary differential equations. As a further work, it is planned to modify the model by introducing additional groups of individuals while taking into account additional individual parameters (age, spatial coordinates, social contacts, etc.). To reduce the computation time in the study of the epidemic spread in large populations, algorithm parallelizing appears to be a prospective option.

Keywords: modeling of the epidemic process, epidemic models, individual-based model, computer modeling

Patch-based training of a convolutional neural network in the problem of cerebral aneurysms recognition

2023. T.11. № 2. id 1341

Kruzhalov A.S.

DOI: 10.26102/2310-6018/2023.41.2.017

Nowadays, intelligent systems are widely used in the field of medicine. Especially relevant is the problem of developing intelligent computer-aided diagnostics (CAD) systems which can be used as an auxiliary tool to improve specialist’s efficiency in the context of the growing volume of medical data requiring analysis and processing. One of the important components of modern CAD systems is the module for recognizing pathological changes in medical images. The paper considers the problem of training a convolutional neural network to recognize cerebral vascular aneurysms. The architecture of a fully convolutional neural network based on the UNet architecture, a data preprocessing technique, a technique for constructing a seamless prediction based on the separation of the original image into a set of intersecting fragments are proposed. The influence of the size of image fragments used for training on the effectiveness of neural network training was investigated. Drawing on the statistical analysis of the results of the conducted computational experiments, it was concluded that the size of the fragment is not a determining parameter since no increase in recognition accuracy is observed with its increase. At the same time, experiments have shown that increasing the batch size while fixing the remaining parameters at the same level can significantly improve the recognition accuracy.

Keywords: convolutional neural network, pattern recognition, medical images, cerebral aneurysm, computer-aided diagnostics system

The use of an artificial neural network in the problem of ultrasonic diagnostics of defects in printed circuit boards of electronic devices

2023. T.11. № 2. id 1338

Uvaysov S.U. Chernoverskaya V.V. Nguyen H.D. Lu N.T.

DOI: 10.26102/2310-6018/2023.41.2.020

Modern electronic devices are complex technical systems, the functioning of which is accompanied by various physical processes occurring in their nodes and blocks. The combination of circuitry, structural and technological complexity of radio-electronic devices is the cause of various defects in them including hidden ones with a long latency period. This, in turn, imposes higher requirements for the diagnosis and control of the technical condition of electronic devices. The relevance of the research presented in this article is due to the need to increase the reliability and accuracy of defect identification in nodes and blocks of electronic devices, the development of new methods and means of technical diagnostics combining traditional approaches with actively developing technologies of artificial neural networks, big data processing, computational experiment. The article presents a study on ultrasound diagnostics of internal defects in the delamination of printed circuit boards. The method of modeling various defects using specialized software ABAQUS is described. The features of the subsequent processing of experimental data – amplitude-time, amplitude-frequency characteristics, the formation of numerical arrays of the parameters under study – are defined. The structure of an artificial neural network for diagnosing and identifying defects of printed circuit boards is given and the technology of its training and testing is defined. The materials of the article are of practical value for design engineers, circuit and system engineers of electronic systems as well as developers of complex technical complexes.

Keywords: printed circuit board, non-destructive testing, ultrasound diagnostics, delamination, hidden defects, ultrasonic wave, piezoelectric transducer, artificial neural network, training, identification

Clustering of patients based on their functional, clinical and anthropometric indicators for the construction of models for assessing bio-age

2023. T.11. № 2. id 1335

Limanovskaya O.V. Meshchaninov V.N. Gavrilov I.V.

DOI: 10.26102/2310-6018/2023.41.2.011

Cluster analysis has become a widely used tool for analyzing medical data to identify groups of patients. But despite the widespread use of cluster analysis, it is rare to find publications where the identification of groups of patients and the attributes by which the division into groups occurred are mathematically justified. To solve this problem, a method called clustering with a teacher can be applied, the essence of which is to apply multiclass classification methods using cluster labels as a target variable. In this paper, this method is employed to identify indicators by which groups of patients will be divided in the databases of the autonomous public health care institutions SOCP Hospital for War Veterans and Institute of Medical Cell Technologies for years 1995-2022 in volume 6440. The HDBscan method was used for clustering method, and the CatBoost method in the multiclass classification mode was used as a verification method for the obtained clusters of patients. As a result, 4 clusters were obtained divided by gender and the patient's condition. In order to identify statistical differences between the obtained clusters, an AB analysis of these clusters was carried out by means of the Kruskal-Walis criterion. The results of the AB analysis showed that the clusters have statistically significant differences in all functional parameters included in the analysis. Further, an AB analysis of the differences in the functional indicators of patients in outpatient and inpatient status for the female and male cluster was carried out. For the AB analysis, a permutation criterion and a bootstrap were used with the construction of confidence intervals of averages from samples generated in the bootstrap.

Keywords: supervision clustering, AB analysis, geroprophylactic treatment, prediction of treatment effectiveness, bio-growth

3D reconstruction of objects by video stream in a dynamic scene

2023. T.11. № 2. id 1334

Logachev E.M.

DOI: 10.26102/2310-6018/2023.41.2.009

The article is devoted to the problem of 3D reconstruction of objects in dynamic scenes by stereo images. When performing any complex tasks by autonomous robots (repair work, inspection of the seabed), there is a need to simultaneously restore the trajectory of the autonomous robot and build a 3D model of the environment using video information. Data on the trajectories of robots and information about the environment are necessary for specialists to further correct drone operation and track the progress of work performed. Сurrently existing object identification solutions help to restore the geometry of dynamic objects with imposed restrictions that prevent from reconstructing the entire scene with the necessary accuracy. Also, the existing methods do not involve detailed visualization of the entire 3D scene using previously unknown point data and do not include the restoration of invisible parts of object surfaces. An approach to solving the problem of identification and 3D reconstruction of objects based on video information in relation to dynamic scenes is proposed. The basis of the software system implementing the proposed algorithmic and architectural solutions is described. Data on model scenes and features of scene objects are given. The results of computational experiments with virtual scenes are discussed. The regularities discovered as a result of tests affecting the accuracy of model reconstruction are considered.

Keywords: dynamic scene, object identification, openGL, 3D reconstruction, visualization, epipolar constraints, delaunay method

Method and algorithms for localizing clusters of adaptive potential in biotechnical systems of rehabilitation type for people with disabilities

2023. T.11. № 2. id 1333

Butusov A.V. Kiselev A.V. Hyder Alavsi H.A. Petrunina E.V. Safronov R.I. Shulga L.V.

DOI: 10.26102/2310-6018/2023.41.2.012

To improve the rehabilitation effectiveness for people with disabilities, an individual approach is required while taking into account the constitutional peculiarities of each patient with a view to optimizing the choice of means for rehabilitation measures or treatment. For the rehabilitation of people with disabilities, a method for classifying the adaptive potential is proposed to control and manage their functional state during therapy or a session of a rehabilitation procedure. A method for localizing clusters in the space of surrogate markers has been developed, which includes four stages differing in that the first stage reveals relevant markers that characterize the change in the adaptive potential of a living system under the influence of an exogenous factor; at the second stage, the proof of the reliability of adaptive potential level clustering is carried out; at the third stage, the classification results are analyzed on dynamic training samples, and at the fourth stage, the statistical heterogeneity and / or heterogeneity of the identified clusters is analyzed. A hybrid adaptive potential classifier has been developed, which includes five "weak" classifiers built on the basis of fuzzy decision-making logic, and a fully connected neural network of direct signal propagation as an aggregator. Testing of the hybrid classifier was carried out on the experimental group of postinfarction patients. Efficiency was evaluated using ROC analysis. The quality indicators of the synthesized hybrid classifier classification make it possible to recommend it for biotechnical systems of a rehabilitation type which carry out medical and restorative procedures for post-infarction patients.

Keywords: adaptive potential, hybrid classifier, virtual model, algorithm, recurrent myocardial infarction, cumulative survival