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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

Methods of constructing a dialog mode for solving polyadic automated control tasks in a natural-like language in military sets of automation tools

2022. T.10. № 2. id 1149

Morozov P.A. Krutalevich Y.A. Anoshin R.I. Belikov N.N.

DOI: 10.26102/2310-6018/2022.37.2.005

The continuous improvement of a potential enemy’s means of attacking from air or space leads to a sharp reduction in the available time for their destruction and makes relevant the increase in the efficiency of troop automated control, which, in turn, imposes more requirements for the speed of control body combat crews. Known approaches to lessening the working time of control body combat crews are either ineffective or incur significant financial costs. The aim of the research is to diminish the working time of control body combat calculation by reducing the time for solving polyadic automated control tasks in military automation sets of tools. To achieve the purpose of the study, a modification of the method for generating operational information by the combat calculation of the control body is proposed by presenting the necessary data when solving automated control tasks as a production-frame model. We also employed a set of subject, language and graphic models as an information resource, which allows us to take into account the predicate structure of the control body combat calculation request and the conceptual as well as graphical representation of display objects when solving polyadic automated control tasks in a dialogue mode in a natural-like language. The experimental studies on the software and hardware complex, conducted before, showed that the average value of control body combat calculation working time fell by 19.3% for all categories of participants in the experiment. It is suggested to implement this solution in the form of a software module within the framework of a high-level programming language C/C++ using the Qt library, which will enable it to be integrated into special software for a set of automation tools.

Keywords: set of automation tools, automated control tasks, dialog mode, operational information, air situation, natural-like language

Synthesis of neural network architecture for ship pattern recognition based on pre-training technology

2022. T.10. № 2. id 1148

Gulamov A.A. Konarev D.I.

DOI: 10.26102/2310-6018/2022.37.2.011

The relevance of the article is due to the information and communication support of navigation by monitoring river vessels using video surveillance cameras. The main goal is to recognize ships in images, for which the application of neural networks has potential. The aim of the paper is to study the performance indicators of vessel recognition by means of available pre-trained networks after their additional training for the assigned tasks and to select the most efficient network. The research considers various pre-trained neural networks. The input data for the networks are ship images. The training sample was collected manually and includes two independent DataSets with images of river vessels and many other objects apart from ships. The networks were built and further trained with the aid of Keras and TensorFlow machine learning libraries. The employment of pre-trained convolutional artificial neural networks for pattern recognition problems and the advantages of utilizing such networks over synthesizing a neural network from scratch are presented. The architecture of efficient pre-trained VGG16 neural network is described in detail. An experiment was conducted in additional training of available pre-trained convolutional neural networks for the assigned task. The efficiency of various pre-trained neural networks was evaluated in terms of the percentage of correct pattern recognition cases on the test set. The most efficient neural network for ship pattern recognition tasks has been selected. NASNetMobile and NASNetLarge networks have shown the maximum accuracy. However, the minimum image size that these networks can work with is larger than for other available networks and the great number of parameters in the convolutional layers of these networks causes a significant increase in retraining and operation time than for other available networks. Concurrently, VGG16 neural network with a small number of parameters and a short time for additional training has proven to be highly efficient which is why it is recommended for the purposes of ship pattern recognition.

Keywords: artificial neural networks, pre-trained networks, convolutional neural networks, keras, tensorFlow, google Colaboratory, VGG16, NASNetMobile, NASNetLarge

Algorithmization of repeated query optimization in cloud databases with the aid of computer training

2022. T.10. № 1. id 1147

Almusawi O. Kravets O.J.

DOI: 10.26102/2310-6018/2022.36.1.020

In cloud environments, hardware configuration, data usage, and workload distribution are constantly changing. These changes make it difficult for the query optimizer of the cloud database management system to choose the optimal query execution plan (QEP). In scientific literature, it was proposed to re-optimize the query during its execution for the purpose of optimizing it with a more accurate cost estimate. However, some of these optimizations cannot provide performance gains in terms of query response time or monetary costs, which are the two optimization goals for cloud databases, and may have a negative impact on performance due to overhead. This raises the question of how to determine when the optimization is efficient. The aim of the study is to develop a method of repeated query optimization that uses computer training. The key idea of the algorithm is to employ past query executions to learn how to predict the effectiveness of query re-optimization, and this is done in order to help the query optimizer avoid unnecessary re-optimization of queries for future ones. The method runs the query step-by-step, utilizing a computer training model, to predict whether re-optimization of the query will be useful after the stage is completed, and calls the query optimizer to automatically perform re-optimization. An experimental evaluation of the effectiveness is to be carried out.

Keywords: repeated query optimization, cloud databases, computer training, multi-stage query, automation of execution

Network-centric motion control algorithm for a group of mobile robots

2022. T.10. № 1. id 1146

Diane S. Iskhakov A.Y. Iskhakova A.O.

DOI: 10.26102/2310-6018/2022.36.1.026

When solving reconnaissance and tactical tasks, methods of mobile robots group application show high efficiency. Robotic groups, based on the network-centric system of control, are characterized by the superiority of intelligence systems over enemy intelligence systems, including the reliability, timeliness and accuracy of the extracted information. At the same time, planning the group trajectory that facilitates communications maintenance with the aim of transmitting control signals becomes a priority in the implementation of such secure systems. The paper proposes a scientific approach to handling the task of mobile robots motion planning under the conditions of providing mechanisms for secure interaction between the agents of a robotic system, using steganographic methods to hide control signals. Previously, the authors developed and tested methods and algorithms as well as software solutions for concealing control signals and the facts of their transmission within the process of intellectual interaction of a robotic systems group when they address a common problem, as well as verification of agents by a dynamic tuple of identification attributes. In the ongoing study, we put forward the software for trajectory planning of a heterogeneous multi-agent robotic system on the condition of maintaining communications to perform the transfer of control signals.

Keywords: information security, control systems in robotic devices, communications security, multi-agent robotic system, network-centric control

Modeling of information systems: review of textbooks

2022. T.10. № 3. id 1143

Erzhenin R.V.

DOI: 10.26102/2310-6018/2022.38.3.026

The article is devoted to the problem of training modern IT specialists. The study examines the content of educational publications related to information system modeling which are registered in the Unified Electronic Catalog of the Russian State Library (RSL) from 2000 to 2020. The analysis of educational publications sorted by theme was carried out according to the main bibliographic indicators including, among other things, the LBC code and the specification of the academic major. The results of the analysis were summary tabular data as well as graphical and schematic representations of the relationship of information system modeling subject to the scientific fields in which educational publications were prepared. Following on from the findings, conclusions were made regarding the quantitative, thematic and content aspect of educational publications, which made it possible to form a knowledge base of educational literature, determine the boundary and relationships of scientific areas with the subject of information system modeling. To assess the final result of the activity on the creation of service publications, it is recommended to use the principle of targeted causality. In order to improve the effectiveness of this activity, it is proposed to devise a special methodology for evaluating training models that can ultimately affect the quality of modeling educational activities and reduce the risks of developing semantic degradation. The knowledge obtained after reviewing educational publications can be used in science studies, development of new modern textbooks as well as for the purposes of improving curricula and discussing the approaches to developing IT education from the standpoint of interdisciplinarity and polydisciplinarity.

Keywords: IT education, IT specialist, IT personnel, scientific and educational environment, science studies, modeling methodology, training model

Locally one-dimensional method for the transfer equation of a continuous medium with distributed parameters on a network-like domain

2022. T.10. № 2. id 1141

Tran D.

DOI: 10.26102/2310-6018/2022.37.2.008

The paper considers a wide range of issues related to the solution of an initial-boundary value problem for a parabolic partial differential equation with a multidimensional space variable belonging to the Euclidean space and changing on a network-like domain. The mathematical model describing the process of transferring a continuous medium over a network carrier is determined by the formalism of the initial-boundary value problem. An idea that has become classical is further developed for the case when a network-like region is a directed bounded graph, i.e., a collection of a finite number of segments connected to each other by means of end points. The study employs classical approximations of evolutionary differential equations of the 2-nd order as well as non-classical approximations of differential relations illustrated by generalized Kirchhoff conditions at the branching points of a network-like region (nodal points of the region). When using difference approximations of the initial-boundary value problem operator, the approximation error and stability conditions for the difference scheme are established. The characteristic properties of the locally one-dimensional method and the sweep method utilized to solve the stated problem are studied. An algorithm for the numerical solution of the stated problem is proposed, a computer program is designed, and a computational experiment is carried out on a series of applied problems. The findings are of interest in the analysis of applied problems of multiphase continuum media transfer along network-like 3D carriers.

Keywords: initial-boundary value transfer problem, network (directed graph), continuous medium transfer, difference scheme, locally one-dimensional method

Component optimization of an evolving digital management environment in organizational systems

2022. T.10. № 2. id 1140

Ryndin N.A.

DOI: 10.26102/2310-6018/2022.37.2.013

The article deals with the formation of optimization models for component optimization of a digital management environment in organizational systems based on probabilistic assessments of component functional requirements fulfilment and estimation of the components implementation influence parameters on the achievement of established requirements. Methods and algorithms for calculating the parameters of digital environment components implementation influence on the achievement of established requirements are considered. As a principal method, it is proposed to use multi-alternative optimization and choosing the option of component integration into a single digital environment that provides the specified requirements for the functioning of a digitalized organizational system. Special attention is given to evaluating the functionality of digital environment components to determine the suitability of a component or a need to replace it in case of non-compliance with the specified requirements at the stage of its development. Boundary conditions for the transition from the stage of functioning to the stage of digital environment development are regarded in terms of fulfilling the established requirements for organizational system parameters and developing control actions: further operation of the component or its replacement; introduction of a new component to meet new system requirements; adjustment of component functionality under the conditions of the system unchanged structure.

Keywords: digital environment, probabilistic estimates, life cycle, resource allocation, component optimization

Safe distance determining algorithm in terms of the thrust force dependence on the aircraft speed during takeoff-run

2022. T.10. № 2. id 1139

Nguyen V. Uvaysov S.U. Florova I.A. Rychkova O.V.

DOI: 10.26102/2310-6018/2022.37.2.001

The importance of air communication between various points of the globe in the modern world is difficult to overestimate. Yet the employment of this means of transport is associated with high risks for passengers, crew, cargo and the aircraft itself due to the possibility of serious accidents at all phases of the flight, but especially during takeoff and landing. This article presents a physical and mathematical model of an aircraft takeoff-run. Its analysis helps to avoid accidents in the event of emergency situations. This model enables the creation of an electronic device for monitoring takeoff dynamic characteristics and warning the aircraft crew about arising inconsistencies. The article presents differential equations describing the dynamic characteristics of the aircraft during takeoff-run. Additionally, solutions of these equations are obtained, which explicitly determine the functional dependencies of the distance necessary for a safe takeoff on the time elapsed since the start of the takeoff-run. The influence of external factors, such as ambient air temperature, wind speed during takeoff and runway slope on the calculated characteristics is considered. As an example, the article also offers the results of an emergency takeoff modeling with the aid of modern software (flight simulator flightgear 2020.3, GeoGebra mathematical program). From the authors’ point of view, the materials of the article may be of practical value for developers of non-embedded on-board control devices, as well as for users of these devices.

Keywords: takeoff, takeoff-run, runway, gravity, friction force, lifting force, normal reaction force of the support, thrust force, drag force, satellite receiver

Analysis of the COVID-19 pandemic impact on the development of human capital in the region using machine learning algorithms

2022. T.10. № 1. id 1137

Kashirina I.L. Azarnova T.V. Bondarenko Y.V.

DOI: 10.26102/2310-6018/2022.36.1.004

The COVID-19 pandemic has had a major impact on the formation and development of human capital through its negative effect on education and public health. This disease has already claimed hundreds of thousands of lives, caused long-term health problems and deprived many of them of access to quality education. In this regard, during the COVID-19 pandemic, it is of great importance to design modern and accurate methods for analyzing, modeling and predicting the dynamics of the spread of this disease, which enable to identify factors that significantly affect the spread of the infection. The article discusses the stages of constructing machine learning models for conducting a predicative analysis of the COVID-19 incidence, which makes it possible to study the dynamics of the spread of this virus at the regional level, identify the influence of various factors on the severity, the duration of the disease, and subsequently create timely scenarios for managing the human capital of the region in order to reduce the negative impact of the pandemic. To devise the methods, a large array of depersonalized data on the spread of COVID-19 in the Voronezh region, provided by the Voronezh Regional Clinical Consultative and Diagnostic Center, was used. The article presents the results of an exploratory analysis of the available data, highlights additional features that can be employed to build machine learning models and develops methods for interactive visualization and forecasting of COVID-19 dynamics.

Keywords: human capital, COVID-19, machine learning, trend forecasting, exploratory data analysis

Means of optical and radio frequency identification in the technological process of automated control of mobile on-board equipment circulation

2022. T.10. № 1. id 1136

Styskin M.M. Stepanov P.V. Zheltov S.Y. Sokolov B.V. Ronzhin A.L.

DOI: 10.26102/2310-6018/2022.36.1.003

The relevance of developing multicomponent means of identifying mobile on-board equipment is due to the increasing requirements for the quality and routine maintenance speed of aircraft. This article analyzes the problems of existing methods for controlling mobile on-board equipment circulation of civil aviation aircraft. The tasks, solved by the equipment circulation control system in the course of loading and unloading mobile on-board kitchen equipment, its transportation, downtime in remote warehouses at destination airports, are formulated. The main problem, solved by the mobile on-board kitchen equipment circulation control system, is the identification of each equipment unit in a reliable manner. To address this issue, various options for automatic contactless identification of mobile equipment, based on RFID, QR-coding, Bluetooth technologies, are proposed. As a result, each unit of equipment receives its own unique digital identifier, which is stored and tracked throughout the entire life cycle in the enterprise information system. The architecture of the mobile equipment circulation control system is presented, including subsystems for generating visual tags, programming identification tags (RFID, BLE), registration, disposal, control of loading, unloading, stocktaking, search, and etc. The application of the mobile equipment circulation control system, which is a part of the technological process of aircraft service maintenance at an airport, is outlined. The advantages of the devised system for controlling the loading/unloading of on-board equipment are demonstrated.

Keywords: circulation control system, mobile equipment, identification tags, visual tags, QR code, RFID, bluetooth, BLE

The algorithm for pulse measurement using a human’s and fetus’s phonocardiogram without classifying heart sounds

2022. T.10. № 1. id 1135

Kosteley Y.V. Zhdanov D.S. Borovskoy I.G.

DOI: 10.26102/2310-6018/2022.36.1.018

The relevance of the research is due to the prospects of phonocardiogram employment for daily monitoring of a fetus’s and mother’s state by designing inexpensive portable devices. Currently, there are no software and hardware systems that completely solve this problem. In this regard, the article presents the algorithm for pulse measurement by means of a phonocardiogram for signal processing in the streaming mode. The algorithm feature is a human’s and fetus’s pulse measurement based on the heart sound segmentation without classifying them into the first and second heart sounds, as well as detecting them under the conditions of other physiological and mechanical sounds, absence of one of the heart sounds in the signal, and deviations in the segmented sound boundaries from the actual localization of the cardiovascular system. For assessing the credibility of the results, the pulse values, obtained by the developed algorithm and reference methods, were compared. The pulse values, calculated by two experts with the aid of a phonocardiogram, were used as a standard for comparison. The average relative deviation between the findings and the reference method results does not exceed 3 %. The article materials are of practical value for the design of a fetus and human state daily monitoring systems.

Keywords: phonocardiogram, cardiointervalogram, heart sound segmentation, heart rate, signal processing

Adaptive control of magnetotherapy by means of biotechnical feedback on the impedance of biologically active points in physiotherapy of ischemic patients

2022. T.10. № 1. id 1134

Miroshnikov A.V. Petrunina E.V. Pavlenko A.V. Protasova Z.O. Shekhine M.T. Shulga L.V.

DOI: 10.26102/2310-6018/2022.36.1.023

The article examines a biotechnical system of rehabilitation and treatment of ischemic patients. A generalized structural diagram of rehabilitation of patients with high ischemic risk by exposing them to magnetic fields with controlled biotropic parameters is presented. The scheme allows building a model of the living system functional state and implementing adaptive control of magnetotherapy through biotechnical feedback on surrogate markers. A biotechnical system of magnetotherapy for patients with coronary heart disease has been developed. Biotechnical feedback was introduced into the system, which enabled it to adapt the magnetotherapy program to the functional state of the patient and correct it during the therapeutic session. Adjusting the therapeutic magnetic field parameters made it possible to increase the therapeutic effect of the physiotherapeutic procedure, reduce the adaptation and negative reactions of the body to magnetotherapy, and plan magnetotherapy programs. To implement the feedback, which ensures the adaptation of the magnetic field biotropic parameters to the functional state of the patient, we used information about the impedance of biologically active points and ischemic risk classifiers, the descriptors of which were determined on the basis of this information. An algorithm for controlling the biotropic parameters of the magnetic field by means of the functional state multimodal classifiers of the patient and a fuzzy inference module, designed to correct the biotropic parameters of the magnetic field in the course of a magnetic therapy session, is given. In a clinical setting, it was shown that the application of adaptive magnetic therapy is an effective method of treating patients with angina pectoris II and III of functional classes (85% and 77%, respectively), which is 14% and 15% higher than the corresponding results in the control group.

Keywords: ischemic risk, adaptive magnetotherapy, biotechnical system, biologically active point, neural network, fuzzy control module, base of fuzzy decision rules, algorithm

Optimization of a supply chain digital thread in the practice of managing organizational systems

2022. T.10. № 1. id 1132

Mukha V.V.

DOI: 10.26102/2310-6018/2022.36.1.027

The article discusses an approach based on the use of methods for modeling, optimization and expert assessment in the development of a supply chain digital thread in the practice of managing organizational systems. It is shown that a digital thread needs to ensure, on the one hand, the movement of material flows within the supply chain and, on the other hand, the exchange of information flows during the interaction of the control center digital platforms and objects of the organizational system. The task is to make a managerial decision regarding the necessity to modernize the operating system of the logistics process digital control in comparison with the results of multivariate modeling and optimization of the digital thread structure. First of all, a model assessment of information exchange efficiency indicators is carried out in the case of basic structures of interaction between digital platforms of the control center and objects that form the supply chain: centralized and decentralized. In order to expand the expert evaluation possibilities of the new version of the logistics process digital management, simulation of the material flows movement processes and data exchange is undertaken to optimize the three-level cluster structure of the digital thread. All these stages of making a managerial decision are combined into a structural scheme for choosing an effective option for implementing a digital thread of supply chains.

Keywords: organizational system, management, logistics process, digital thread, optimization, simulation, expert assessment

Study of current chronograms, structure of dissociation, recombination and equilibrium regions in problems of non-stationary 1:1 electrolyte transfer in membrane systems using a mathematical model

2022. T.10. № 1. id 1131

Kovalenko A.V. Gudza V.A. Chubyr N.O. Khromykh A.A. Urtenov M.K.

DOI: 10.26102/2310-6018/2022.36.1.028

The joint research of the dissociation-recombination reaction and space charge along with their effect on the transfer of 1:1 electrolyte ions appears to be a relevant issue. The article is a theoretical study of the dissociation, recombination and equilibrium areas and the features of salt ion transfer in each of these areas using the method of mathematical modeling. In the article, for the first time, on the basis of a mathematical model of non-stationary transfer of 1:1 electrolyte, the main regularities of the influence of the dissociation and recombination non-catalytic reaction on the transfer of 1:1 salt ions and electroconvection are theoretically established. In particular, the chronograms of the current density with and without taking into account the dissociation/recombination reaction of water, the structure of the dissociation regions, recombination and equilibrium were examined, the dependences on the input parameters were determined: the initial concentration, the potential sweep rate. It has been shown that in the boundary layers of ion-exchange membranes, the dissociation reaction prevails over the recombination reaction due to the fact that in these regions the electric field strength takes such high values that the electric field breaks the water molecules and separates the Н+ and ОН- ions, preventing them from recombining. It has been demonstrated for the first time that in the middle part of the desalination channel, a region is formed where the recombination of H+ and OH- ions predominates. This reaction is local in nature, so all H+ and OH- ions cannot recombine at the same time. As a result, in the region of recombination, an excess of H+ ions emerges on the one side and OH- on the other side, in other words, an electric double layer is developed in the middle part of the desalination channel, and the recombination region is rather narrow. The obtained theoretical results and conclusions can be applied to analyze the operation of electrodialysis machine desalination channels.

Keywords: electrolyte, membrane, dissociation, recombination, electroconvection, desalination channel

Implementation of numerical methods for assessing the probabilistic-temporal characteristics of a set of operations in the form of a problem-oriented software package

2022. T.10. № 2. id 1130

Oleinikova S.A. Selishchev I.A. Nedikova T.N.

DOI: 10.26102/2310-6018/2022.37.2.012

The object of research in the article is a project represented by a set of sequential-parallel operations with a random duration. A feature of the project class under study is the dependence of the execution time of any operation on the executive assigned to it. The goal is to assess the probabilistic and temporal characteristics of the project, which include, first of all, the duration of service. Due to the stochastic nature of operation duration, this characteristic will be random. Based on this, it is required to estimate the mathematical expectation of the investigated random variable in the first instance. In addition, the variance of the random variable, its distribution law, and the ability to estimate the probability of project completion in a given timeframe (i.e., the probability of the investigated random variable falling within a given timeframe) pose an interest. To achieve this goal, the article presents a software package consisting of an application for assessing the parameters of individual operations, a simulation system for assessing the duration of the entire project and a database that stores information about the required entities. All components of the software package are implemented using the Java language; MySql was chosen as the DBMS. As a result, it became possible to evaluate the parameters of individual operations, transfer them to the simulation environment for conducting an experiment to assess the necessary characteristics of the duration of the entire project and save the obtained values in the database for their possible further use.

Keywords: probabilistic-temporal characteristics, sequential-parallel operations, numerical method, software package, simulation modeling

Information support in scientific paper preparation management on the basis of intelligent review analysis

2022. T.10. № 1. id 1128

Latypova V.A.

DOI: 10.26102/2310-6018/2022.36.1.005

Intelligent technologies are actively entering different fields of activity. These technologies are also beginning to be utilized at certain stages of scientific paper preparation management process to organize information support for peer reviewers and editors of the academic journals for the purpose of reducing their labour costs and accelerating the procedure of paper publication. However, tools, implementing intelligent technologies, are mostly used in major publishing houses due to the fact that their application requires strong computing resource consumption in their work. This entails the need for appropriate hardware and large financial expenditure. For that reason, the employment of intelligent technologies is nowadays limited for most of other academic journals. To deal with this problem, an approach to decision-making information support in scientific paper preparation management on the basis of intelligent review analysis is suggested in this article. The testing of the proposed measure to information support at the Aeterna Research and Publication Centre has proven its effectiveness by the example of paper preparation management in Academicheskaya publitsistika (Academic Publicism) and Innovatsionnaya nauka (Innovative Science) Journals.

Keywords: information support, scientific paper, paper preparation management, peer review, intelligent review analysis

Simulation modeling features of capacitive sensor measurement circuits

2022. T.10. № 1. id 1127

Mishukov S.V.

DOI: 10.26102/2310-6018/2022.36.1.017

The main universal and effective method of researching numerous technical systems and objects is the implementation of simulation modeling in special software, for example, SimInTech (Simulation In Technic), which is a unique software package that makes it possible to combine calculation projects and schemes with various mathematical, physical, electrical, hydraulic and other processes in real time. This feature of the SimInTech environment enables to simulate measuring circuits based on the original method of determining the capacitive sensor parameters, which consists in a two-stage measurement algorithm in steady-state and transient modes of the circuit under study. Using the example of the specified measuring circuit, the features of constructing its model by means of a built-in programming language, the development of custom blocks of a capacitive sensor, an operational amplifier, a sampling and storage device are shown. In addition, a study of the random component of the sensor parameter measure error, when the accuracy of voltage sampling changes, was carried out and the possibility of performing measurements with an error not exceeding 0.5% was confirmed. The materials of the article are of practical value for specialists in the field of control and measuring technology since the application of the SimInTech dynamic modeling environment for building models of measuring circuits will facilitate theoretical research relating to multi-element circuits and objects represented by them.

Keywords: capacitive sensor, measuring circuit, simulation modeling, multi-element circuit, submodel

A training device for the analysis of anomaly detection methods based on machine learning theory

2022. T.10. № 1. id 1122

Grekov M.M.

DOI: 10.26102/2310-6018/2022.36.1.019

Nowadays, the timely detection of new malicious attacks on computer networks appears to be a relevant issue. In this regard, it is necessary to develop anomaly detection methods that enable the identification of unknown attacks. The paper presents a model of a training device for analyzing anomaly detection methods in reliance on machine learning theory. A model has been developed for generating datasets with characteristics of real network traffic by means of a generative adversarial neural network. The generated dataset can be employed to train and test detection models while the sample emulates the features of a real network, which increases the efficiency of anomaly detection. The training device can also use publicly available datasets: NSL-KDD, CICIDS2017. Support vector machine, k-nearest neighbors, naive Bayes, logistic regression, decision trees, random forest, k-means are utilized as training methods, and a multilayer neural network, based on the PyTorch library, is implemented. The training device simplifies the process of analyzing machine learning methods, applied to obtain anomaly detection models. The developed software product facilitates not only training and testing with the aid of publicly available datasets, but also provides the ability to collect network traffic and supplements it with generated data with the characteristics of real traffic.

Keywords: anomaly detection systems, datasets, generative adversarial neural networks, machine learning, computer network security

Stochastic filtering in the space of expert opinions

2022. T.10. № 1. id 1121

Grechanyi S.A. Krivobokova S.E.

DOI: 10.26102/2310-6018/2022.36.1.022

Currently, there are many difficulties associated with the financial aspect that affects the security of the facility when assembling a set of technical security equipment. To solve the problems of the facility safety, and therefore the reliability of individual security devices, it is recommended to involve experts. At the same time, experts’ opinions may not always be infallible. In this study, it is proposed to carry out a stochastic analysis and filtering of the expert opinion space in order to identify a conditional trend (established opinion) of each expert. The main method of researching this issue is the analysis of conditional time series (testing the hypothesis of the trend absence by means of the median method in the sequence of expert assessments), which makes it possible to determine the validity of the method, as well as to ensure experts’ objectivity of assessments. The article presents a step-by-step operation algorithm for empirical data, calculates the average deviations from the trend line, considers two methods for testing the null hypothesis – the median method and Foster–Stewart method. The materials of the article can be applied in various areas of setting the average score since the algorithm for testing the null hypothesis is universal in nature.

Keywords: conditional short time series, stochastic filtering, least square method, regression equation, median method, foster–Stewart method, standard deviation

Model with latent parameters for step-by-step procedure for evaluating learning outcomes

2022. T.10. № 1. id 1118

Bratischenko V.V.

DOI: 10.26102/2310-6018/2022.36.1.015

The relevance of the research is due to the importance of studying learning outcomes to improve the quality of educational process. For this, a knowledge assessment model is proposed in the form of a task sequence. The probability of successful completion of the task depends on the latent parameters: the ability of the student and the difficulty of the task. The model is similar to the Partial Credit Model used in Item Response Theory to analyze test results. In reliance on the maximum likelihood method, a procedure has been developed for estimating parameters by numerical methods according to students' grades. The convergence of the estimation procedure has been substantiated. Adequacy verification of the model by the means of variance analysis, correlation analysis, Infit and Outfit criteria, based on the chi-square distribution, is put forward. To evaluate the usefulness of the model, it is suggested to utilize the coefficient of determination. Information on the application of the model for the analysis of students’ grade array in the academic group is given. Following on from the results of the analysis, the model passed the adequacy tests and made it possible to significantly clarify the characteristics of the learning outcomes and knowledge assessment procedures. To enhance the accuracy of modeling, it is recommended to employ grades of current academic performance. The practical value of the model lies in the identification of assessment procedures with characteristics that differ notably from the average for further meaningful analysis and upgrade.

Keywords: knowledge assessment model, latent parameters, maximum likelihood method, variance analysis, correlation analysis, infit statistics, outfit statistics, coefficient of determination

Modeling of large data array processing in distributed information and telecommunication systems

2022. T.10. № 1. id 1117

Melnikova T.V. Pitolin M.V. Preobrazhenskiy Y.P.

DOI: 10.26102/2310-6018/2022.36.1.025

The article considers the problem of modeling large data array processing in distributed information and telecommunication systems. The analysis of the problem, associated with the incorrect operation of the information system, is conducted. It is shown that distributed systems allow distribution of logic and data across multiple physical servers, which, with the correct allocation of resources and logic, makes it possible to reduce the risks of failures. It is demonstrated how the calculation of productivity loss percentage from a failure in one of the distributed information system components is carried out. A fragment of the diagram, outlining the options for the store information system application, is examined. If it is necessary to purchase physical servers when building an information system, then it is possible to calculate the coefficient of decrease in the performance of the information system in the event of a failure on one of the servers while ensuring the conditions for simultaneous operation of servers. The graph, illustrating the dependence of the performance change on the number of nodes that comprise the distributed network, is given. The analysis indicates that the cases when there are not too many servers have the greatest effect on reducing the risks from adding nodes to a distributed system. If a distributed system already consists of many different servers and any logic is duplicated on many of them, the risk reduction from adding an additional server will be negligible.

Keywords: distributed data processing, information system, modeling, information transfer, algorithm

The application of the relative acoustic nonlinear parameter for the development of biological tissue imaging systems

2022. T.10. № 1. id 1111

Chernov N. Varenikova A. Laguta M.

DOI: 10.26102/2310-6018/2022.36.1.021

The paper discusses the issues of developing a method for visualizing the internal structures of the body, based on the restoration of the acoustic nonlinear parameter distribution. The process of occurrence and propagation of the second harmonic wave in tissues with high nonlinearity and attenuation is considered. The use of the relative acoustic nonlinear parameter in relation to the absolute nonlinear parameter of the medium is proposed. To solve the problem of restoring the distribution of the relative acoustic nonlinear parameter in biological media, an equation is obtained that eliminates the necessity to measure changes in absolute pressure values for both the fundamental frequency wave and its second harmonic. Mathematical expressions are derived that enable accounting for the attenuation processes for the fundamental frequency and for its second harmonic, taking into consideration the influence of the medium in which the object under study is placed. Expressions for determining the relative acoustic nonlinear parameter are acquired. Drawing on these expressions, the construction of a visualization system, utilizing algorithms for restoring the distribution of the acoustic nonlinear parameter in the cross section of a biological object, is presented. The main advantage of these equations is that there is no need to identify changes in the absolute amplitudes of the fundamental frequency and second harmonic waves. The outlined methods for calculating the nonlinear characteristics of biological tissues make it possible to simplify the technical implementation of ultrasound imaging systems.

Keywords: ultrasound imaging, nonlinear parameter, second harmonic, nonlinear acoustics, structure of biological objects

Chatbot based on neural networks and word embedding to increase customer loyalty

2022. T.10. № 2. id 1110

Kovalenko A.V. Syusyura D.A. Sharpan M.V.

DOI: 10.26102/2310-6018/2022.37.2.014

In the digital era mobile devices are becoming the main instrument of human social interaction. With the growing popularity of instant messengers, the role of chatbots in the mobile environment appears to be more and more significant. Intelligent interactive chatbots are often used in mobile applications and help improve the interaction between companies and their customers, which ultimately increases customer loyalty to that organization. Chatbots allow companies to communicate with customers on an individual basis, without involving employees and thereby saving time, money, and human resources. The majority of chatbots works with scripted algorithms and they are not universal. This is due to the simplicity and speed of development. However, in this case, there is a risk of missing many choices in the decision tree. Chatbots based on neural networks can solve this problem, but it should be taken into consideration that both of them have a drawback – long processing of messages and feedback. In the context of the scenario approach, this is caused by long branch transitions. For neural networks, complexity arises because of the feedback processing algorithm. In that instance, the application of the service will not be justified, customer loyalty to the organization will deteriorate. In this connection, the article discusses an alternative approach to creating chatbots with the aid of neural network technologies and text representation methods, which avoids the problems described above. As a means of chatbot design, the following technologies were utilized: Python 3.6, genism libraries, sklearn, scipy, pandas, word2vec and doc2vec technology. The article also describes a way to accelerate chatbot feedback and training using KD-Trees.

Keywords: neural networks, chatbot, word2vec technology, messengers, word embedding

Mathematical modeling of the collective solution accuracy

2022. T.10. № 1. id 1109

Ganicheva A.V. Ganichev A.V.

DOI: 10.26102/2310-6018/2022.36.1.001

Currently, the problem of collective decision-making is one of the most relevant in the organization of effective management in social and economic systems. One of the main issues in the theory of expert assessments is the assessment of the group solution quality. The article discusses the matters of assessing the socio-economic indicator by independent experts. The centered random variables sums value of individual estimates is accepted as the error of group estimation. The situation is examined when the values of the indicator have an arbitrary distribution with known and unknown parameters. Two algorithms have been developed to determine the required amount of experts depending on the accuracy and reliability of the assessment. The first algorithm is used to find the confidence interval of mathematical expectation when the variance of the indicator is not specified. In this event, an iterative process is undertaken to ascertain the volume of representativeness for the confidence interval of variance with a given accuracy and reliability. The second algorithm is employed to construct a confidence interval for variance when the number of experts is more than three. The important task of quantifying the proportion (percentage) of possible errors within a predefined interval in measuring the indicator has been solved. An econometric model is designed for the Laplace function. The case of determining the number of experts to evaluate an indicator having a uniform and exponential distribution over a given interval is considered. An example of the practical implementation of the devised method is shown.

Keywords: approximation, significance level, estimation accuracy, laplace function, econometric model, expert, estimation, probability distribution

Implementation of the method for dynamic content matching of learning and game scenarios in an adaptive learning game

2022. T.10. № 1. id 1107

Khairov A.V. Shabalina O.A. Kataev A.V.

DOI: 10.26102/2310-6018/2022.36.1.002

The paper describes a method for adapting the educational process in adaptive role-playing learning games using dynamic content matching of nonlinear learning and game scenarios. The training scenario and the game scenario, associated with it, are represented by structurally ordered spaces. The mechanism of dynamic content matching of nonlinear training and game scenarios implemented in the game is based on the activation of predefined game events in relation to the plot path chosen by the player. Triggers are assigned to each visible and invisible object of the game world in conformity with the constructed knowledge space. When a character enters a game situation tied to the trigger's scope, a system of dialog boxes is enabled to complete the objective, set by this game situation. The player dynamically builds their game scenario depending on the choice of a strategy for mastering the knowledge space and performing the corresponding game tasks while the method of dynamic content matching, executed in the game, ensures the development of the entire space in terms of any strategy formed by the player. The means of the method employment in the Cammi learning role-playing game for studying object-oriented programming and the C++ language is defined.

Keywords: learning game, adaptive learning game, training course, adaptation model, adaptation method, nonlinear scenario, knowledge space

Mathematical modeling of hydrogen extraction process from the natural gas steam reforming products

2022. T.10. № 1. id 1103

Alruyshid M.H. Skvortsov S.A. Ishin A.A. Dmitrievsky B.S. Terekhova A.A.

DOI: 10.26102/2310-6018/2022.36.1.024

Nowadays, the problems of the economy decarbonization and the transition to renewable energy sources are becoming more relevant. Hydrogen, above all, is among the decarbonated gases, the use of which is considered the most promising. It is regarded not only as an energy carrier but also as a means of storing excess energy, produced by renewable sources. The steam methane reforming, at the outlet of which a hydrogen-enriched gas stream is obtained, is deemed to be the most well-developed scheme. Adsorptive gas separation systems are widely used to extract hydrogen from the steam reforming gas. Mathematical modeling plays an important role in the design of adsorption gas separation plants. Optimization and control systems synthesis can be carried out with the help of a mathematical model for the process under review. The article proposes a mathematical model for the hydrogen extraction technological process by the pressure swing adsorption method employing a 6-beds gas separation unit. For the numerical solution of the mathematical model equations, the method of lines was applied, which converts partial differential equations to a system of ordinary differential equations. The integration of resulting equations system was undertaken with the aid of the Runge-Kutta method with automatic step selection. The results of numerical simulation calculations of the system dynamic operating modes are given. It is concluded that the proposed mathematical model for the adsorption process of gas separation is allowed for solving the problems of numerical simulation studies, optimization and control systems synthesis

Keywords: adsorbent, adsorber, adsorption, activated carbon, regeneration, zeolite

Evaluation of the Spatial Interpolation Efficiency in the Processing of Combined Different-Range Images

2022. T.10. № 1. id 1094

Vetrov A.N. Potlov A.Y.

DOI: 10.26102/2310-6018/2022.36.1.014

The article shows the methodology and results of laboratory tests to determine the performance indicators of operators with combined multi-band images, namely, video and thermal images acquired from the same object at the same scale and with the same sweep parameters. The images were presented in two versions. In the first one, tests were carried out to detect specified objects in a combined image from video and thermal imaging cameras. In the second one, the same detection procedure was undertaken on interpolated images, when each pixel of the resulting image contained information from both sensors. The relevance of the work done lies in obtaining the probabilistic characteristics of a given object detection from simply superimposed images and images subjected to spatial interpolation, which confirms the increase in the information content of the interpolated images, but in practical terms. The tests were run with the involvement of a large number of operators, each of which worked with images only once. As a result of the tests, data were collected on the time of object detection by each operator and the probabilistic characteristics of detection were calculated. A comparative analysis of the findings was carried out in order to ascertain the efficiency of operations with interpolated and non-interpolated images. The sufficiency of the conducted experiments is proved.

Keywords: laboratory tests, combined images, interpolated images, detection time, probabilistic characteristics of detection, practical increase in information content

Neural network denoising in polygon meshes

2022. T.10. № 1. id 1093

Rotova O.M. Pivovarova N.V.

DOI: 10.26102/2310-6018/2022.36.1.013

One of the most important problems of creating 3D models with the aid of three-dimensional scanning systems is automatic processing to eliminate noise obtained due to the application of scanning devices with insufficient accuracy. The aim of the study is to develop a fully automatic approach for solving the problem of denoising in polygon meshes acquired after three-dimensional scanning. The principal method to overcome this is the application of neural networks that allow processing of polygon meshes to be performed automatically. The article presents an overview and comparative analysis of existing methods of denoising in polygon meshes. The mathematical formulation of noise elimination problem is provided. The description of the algorithms used to prepare data for neural network training is given. The method of polygon meshes filtering by the means of a bilateral filter, the method of principal components for reducing the dimension of data, the k-means clustering algorithm, the algorithm for updating vertex positions by updated face normals are employed. Details of a fully connected feedforward neural network implementation are described. The results of the study are outlined. The analysis of the findings is carried out utilizing the quality metrics of the Hausdorff distance and the average value of the angle between the normals of polygon meshes with and without noise.

Keywords: neural networks, data science, polygon meshes, mesh denoising, three-dimensional scanning, bilateral filter

Mathematical and statistical fire incidence forecasting model for use in the EMERCOM system of Russia

2022. T.10. № 2. id 1091

Kistanova L.A. Repin S.V. Boldyrevsky P.B. Lakhvitsky G.N.

DOI: 10.26102/2310-6018/2022.37.2.002

Making and analysing fire incidence forecasts is the issue which is in the focus of the attention of the supervisory activity directorate of the Ministry of the Russian Federation for Civil Defence, Emergencies and Elimination of Consequences of Natural Disasters because it concerns safety of human life and, thus, the tasks of solving this problem, and therefore planning and optimization of unit personnel. At the same time, about 30% of the control measures total number, carried out by fire supervision authorities, pertained to scheduled inspections. This article demonstrates the correlation between fire dynamics forecasting and scheduled inspections and determines the magnitude of the lag or delay in conducting scheduled inspections in relation to the number of fires. The mathematical and statistical model is based on the example of statistical data on the fire incidence in the Nizhny Novgorod region and the Russian Federation from 2010 to 2020. To define and address this problem, the mathematical apparatus of time series theory was used, in particular, the method with distributed lags - the Almon technique. The findings allow us to conclude that mathematical models with distributed lags, performed by means of the Almon technique, can be employed to predict fire incidence in the EMERCOM of Russia system, as well as to schedule inspections of the state fire services of the EMERCOM of Russia and formulate proposals for optimizing the personnel of the EMERCOM units.

Keywords: EMERCOM of Russia, fire incidence, scheduled inspections, mathematical and statistical forecasting model, time series, model with distributed lags, the Almon technique

Information system for students’ remote study of ecological and biological features of woody plants and mechanical stability of the main tree species used in landscaping of Donetsk

2022. T.10. № 1. id 1077

Kornienko V.O. Kalaev V.N. Preobrazhenskiy A.P. L'vovich I.Y. Firsov A.V.

DOI: 10.26102/2310-6018/2022.36.1.012

The developed information training system contains visual, generalized, structured material on mechanical stability, accident rate as well as ecological and biological features of the main woody plant species used in the landscaping of Donetsk: systematics, biology and ecology, biogeography, representation in the environment of Donetsk, mechanical stability and accident rate, crown shape, crown structure, wind resistance, resistance to anthropogenic factors, critical age in the environment of Donetsk, the presence of a cross-section/core sample in the xylotheque, recommendations for gardeners, landscaping concepts, illustrations. The information system is educational in nature and allows the researcher to quickly and visually familiarize themselves with the ecological and biological features of the growth and development of woody plants in the steppe zone, drawing on the example of the industrial city of Donetsk, as well as with the methodology of monitoring studies to assess the mechanical stability of woody plants, to learn to analyze the dependences of mechanical stability parameters for 18 species of woody plants growing in the Donetsk environment and to find and accurately identify the positive and negative aspects of employing various woody plant species for the purpose of landscaping in an industrial city. At the end of the training, there is an opportunity to evaluate the acquired knowledge and skills through interactive testing for each section. The described information system summarizes the results of Russian and foreign studies on the ecological and biological characteristics of the species presented and supplements them with information about the features of growth, physical and mechanical properties of wood, mechanical resistance to dynamic (wind) and static loads (glaciation, snow sticking, etc.) in a large industrial city. The information system is aimed at high-quality training of future specialists in the field of biology and ecology, contributes to the implementation of the results obtained in the educational process (as a study guide for students and postgraduates of biological universities). It can also be utilized in environment state monitoring and in assessing the accident rate of woody plants.

Keywords: information system, algorithm, distance learning, mechanical stability, ecology of woody plants, tree stability, landscaping concept, selection of species