ISSN 0236-235X (P)
ISSN 2311-2735 (E)

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Higher Attestation Commission (VAK) - К1 quartile
Russian Science Citation Index (RSCI)

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2
Publication date:
16 June 2024

Articles of journal № 2 at 2022 year.

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Public date | Title | Authors

1. An optimized design of serial logic comparator [№2 за 2022 год]
Authors: Niyonsaba T., Akimana A., Kibeya H., Uwizeyimana P.
Visitors: 1770
Comparator is a combinational circuit which is used to compare the values by taking two numbers as input and determines whether one number is greater than, less than or equal to the other number. Com-parators have many applications in mainstream electronics and modern digital VLSI design, such as – Threshold Detector, Zero crossing Detector, Relaxation Oscillator, Schmitt Trigger and digital signal processors. This paper presents an efficient serial comparator design by block optimization techniques. The proposed 8-bit binary serial comparator is designed using a parallel to serial converter circuit as first stage that converts parallel data into serial rotated data. The second stage involves implement-ing a switching circuit in order to place data in two-comparison shift register. Only Most Significant Bit values of the two registers are compared through one-bit comparator cell as the third stage. The design and simulation of the proposed miniaturized global circuit of the serial comparator has been imple-mented by using DSCH 3.5 and Microwind 2.0 software showing a good quality performance. Moreo-ver, the paper describes the simulation of layout and parametric analysis for the proposed 8-bit com-parator design. It is noted that the area cost, the number of cycles and power consumption values are less in the proposed technique compared to the existing approaches.

2. Automating the assessment of the power grid state in remote areas of Russia using smart structures [№2 за 2022 год]
Author: Shevnina Yu.S.
Visitors: 2021
The paper discusses a method for automating the assessment of the power grid state in remote regions of Russia using smart structures. The proposed automation method is implemented as a mobile applica-tion. The smart structure underlying the described method of automating the assessment of the power grid state consists of modules for receiving and processing data from sensors, searching for patterns in the power grid characteristics and generating state classifiers, offering recommendations for repair and optimal operation of the power grid and substation. The scientific novelty of the proposed solution is in the method of analyzing and processing the power grid characteristics and their combinations. In addition, the external influence parameters in the form of natural and man-made factors are taken into account. The method of analyzing and processing information about the power grid and substation is based on the machine learning method – logical data analysis. Assessing the state of a power grid and a substation is important when studying and solving the problems of predicting changes in the power grid state, selecting recommendations and making de-cisions on repair and maintenance work. The method for assessing the power grid state is based on the search for patterns and the construc-tion of classifiers. It allows taking into account all the characteristics and parameters of a power grid, their totality and the relationship between them. In addition, the described method allows analyzing and obtaining patterns for incomplete and inaccurate data, which is a fairly common occurrence in real power networks. The method can be used in the design and maintenance of power grids and substations in hard-to-reach and remote regions of the Russian Federation. The proposed reduction of the characteristic regularities and their sets based on their recurrent con-junction makes it possible to obtain optimal classifiers of the states of a power grid and a substation with high interpretability and generalization. It increases the accuracy of assessing the power grid state, therefore, increases the accuracy of predicting behavior, recommendations and making decisions about repair work and the optimal mode operation.

3. Automated detection and classification of objects in the traffic flow on satellite images of the city [№2 за 2022 год]
Author: V.S. Tormozov
Visitors: 2377
The paper discusses the developed methods of detecting and classifying objects in a traffic flow on ul-tra-high spatial resolution space survey data. Due to appearing the large amounts of free access satellite data, the development of machine learn-ing methods based on geospatial data, in particular satellite data, is becoming increasingly urgent. The paper justifies the choice of a source of data on traffic flows – ultra-high resolution satellite images. It also describes the main problems and tasks associated with the recognition and classification of objects in traffic flows. The purpose of scientific work is to develop and study a chain of algorithms that allows detecting and classifying objects in traffic flows with high accuracy. The research is based on a numerical as-sessment of the quality of the algorithms. The work uses the methods of pattern recognition, machine learning and digital image processing. The scientific novelty of the completed work is based on: a unique algorithm for extracting images of local sections of the road network, an algorithm for determining the direction of object’s road movement, modernization of the selective search algorithm, which consists in filtering the extracted candidates. The work novelty is also confirmed by the fact that the used ultra-high resolution survey data have become accessible for private use relatively recently.

4. Process control algorithms in responsive sensory networks in object protection problems [№2 за 2022 год]
Author: Vinogradov G.P.
Visitors: 2610
Localization, classification and tracking of objects intruding into the protected zone of especially im-portant objects form the basis of their protection system. The purpose of the article is to study ways to improve the efficiency of the system by using distributed sensor networks as a part of cyber-physical systems. It is shown that achieving this goal involves organizing the interaction of tracking algorithms with traditional initialization/routing algorithms in sensor networks. The paper considers the problem of joint data processing by nodes in distributed sensor networks. The subject of consideration is actual and complex methods for tracking a multitude of moving objects in a protected area, their implementation by means of sensor networks involves solving a number of problems including the two main ones that should be singled out. The first problem is the development of effective methods of information exchange between local nodes in the invasion zone. The second problem is the organization of joint processing of signals by a group of nodes based on the collected in-formation about the environmental state in their area of responsibility as a result of the occurrence of events. It is shown that the main tracking procedure stages consist of target detection, their classification, location estimates and target movement trajectory prediction. A model example of the procedure im-plementation is the task of detecting, localizing and tracking the penetration of one object into the pro-tected area. The paper considers the approaches underlying these algorithms, as well as the main as-pects of their implementation. The proposed solutions take into account the limitations associated with the capabilities of local nodes, the network as a whole and routing. The source of data for the proposed algorithms are signals from sound, seismic, thermal, etc. sensors, in which the signal power has a pronounced maximum de-pending on the distance from the target to the network node. The obtained results are applied to the problem of tracking a plurality of objects, which involves as-sessing the applicability of identification and classification methods under conditions where there is an overlap of perceived signals by sensors by different objects. There is also a discussion of the algo-rithms for solving such problems.

5. Diagnosing the functional suitability of developing multifunctional automated systems based on a reconfigurable model [№2 за 2022 год]
Author: Loginov I.V.
Visitors: 2769
The paper considers the problem of low relevance of the diagnostic functional suitability model for multifunctional automation systems in the case of high intensity flow of requests for new automation services. The solution of the problem is changing the contour of diagnosing the functional suitability of mul-tifunctional automated systems based on clarifying the boundaries of the control object. At the same time, the functions of identifying changes in requirements are transferred from external system design (the stage of adjusting management goals) to the stage of structural synthesis of the system model. There is a developed approach for diagnosing the functional suitability of multifunctional automat-ed systems based on the inclusion of additional diagnostic parameters of the requirements changes to the diagnostic model; the use of an adaptive diagnostic model that changes its structure depending on the identified requirements; adding additional mechanisms for collecting data on new needs in the au-tomation. The paper presents a description of the software tool for information and analytical support of the activities of the automated system administration unit developed according to the GOST 59194-2020. The software basis is a database that supports an automation system adaptive model and a set of interfaces for connecting monitoring software (functional status and destination requirements). The mechanisms of collecting requirements data and their application in solving the problem of diagnosing functional suitability are considered. The paper describes the considered approach to the automation control system for communication services operating based on the eTOM model. The using of a monitoring data post-processing module based on process-mining technology made it possible to reduce the time required to rebuild the diag-nostic model. Increasing the relevance of diagnostic information provides an increase in the coefficient of functional suitability of the automation system by 1–6 % with limited modernization resources. The proposed approach to diagnosing the functional suitability of evolving multifunctional automa-tion systems can be used in substantiating the system, operating and technical requirements for promis-ing systems, as well as in the implementation of system-technical solutions within the framework of their design processes to ensure higher awareness of engineering personnel.

6. An addition to the clustering algorithm of a wireless sensor network [№2 за 2022 год]
Authors: Tatarnikova, T.M., Bimbetov F., Gorina E.V.
Visitors: 2875
The choice of a method for organizing information interaction is one of the urgent scientific tasks when deploying the Internet of things. In turn, the wireless sensor network, which is the physical basis of the Internet of things, has a serious limitation that is the requirement of low power consumption. The life of the network depends on energy consumption - the time during which the network performs its func-tions. The energy of sensory devices is spent on receiving and transmitting data, processing them, and calculating the route. New algorithms are required to reduce the number of data processing operations, route length, and more without losing network functionality. One mechanism that has proven to reduce power consumption is the clustering of a wireless sensor network due to the transfer of part of the functions to the head nodes of the clusters. The bee swarm al-gorithm proposed in the paper develops the idea of searching for the head nodes of wireless sensor network clusters. According to the proposed algorithm, at the beginning of the cycle, the head of the cluster of the current round and potential heads of clusters for the remaining rounds of the cycle are immediately determined. Thus, the phase of choosing the cluster head node, starting from the second round of the cycle, becomes redundant, and the sensor nodes get rid of some of the calculations associ-ated with choosing the head of the cluster. The simulation results show the superiority of the bee swarm algorithm in comparison with the well-known LEACH low power adaptive clustering algorithm in terms of the duration of the wireless sensor network.

7. A group multicriteria decision analysis module based on fuzzy extension of TOPSIS method [№2 за 2022 год]
Authors: Shershnev R.V., A.V. Radaev, Korobov A.V., Yatsalo B.I.
Visitors: 2838
The theory of group decision making is widely studied and applied in various fields of human activity. The theory of group decision making proposes various voting methods, assessing the consensus among the participants in the group analysis of decisions and recommendations for choosing/ranking alterna-tives. Different computer systems are developed to implement the process of group analysis and deci-sion support for practical applications. The paper presents the DecernsFMCDA-G-FT framework for group multicriteria decision analysis based on the fuzzy TOPSIS model. The framework is a component of the group decision support system DecernsFMCDA-G under development. The system provides the necessary functionality to define a problem, collect expert information, visualize individual and group preferences, rank alternatives, ana-lyze the results. Visualization of individual preferences, group assessments and the possibility of choosing different approaches for ranking the alternatives give a visual representation of the process of group multicriteria analysis. When solving applied problems, input fuzzy quantities of various shapes, several methods for cal-culating functions of fuzzy numbers as well as various methods for ranking fuzzy quantities can be used. The problem of multicriteria sorting candidates for employment is solved by using the Decerns-FMCDA-G-FT framework. The developed module is intended for study of decision theory within universities’ courses, risk analysis and management and for multicriteria analysis of a wide range of scientific and applied problems.

8. The DecernsFMCDA fuzzy multi-criteria decision support system [№2 за 2022 год]
Authors: Gritsyuk S.V., A.V. Korobov, A.V. Radaev, Yatsalo B.I.
Visitors: 3655
Risk management in the field of environmental protection, remediation of contaminated sites and land use planning requires using modern decision support systems. This paper presents a DecernsFMCDA fuzzy decision support system, which includes both well-known ordinary multicriteria decision analysis methods and original methods for dealing with uncer-tainties based on fuzzy sets and probabilistic approaches. There is an overview of the available com-puter systems for multi-criteria decision analysis, as well as a detailed description of the structure of DecernsFMCDA, its main components and differences from other multi-criteria analysis systems. The paper includes the list of classical, probabilistic and original fuzzy models of multicriteria decision analysis implemented as part of the system, as well as diagrams and descriptions of the general modular architecture of DecernsFMCDA and the original libraries of multicriteria decision analysis (mcda-lib4) and a library for working with fuzzy numbers (fuzzylib). A practical application of the DecernsFMCDA system is shown on the case of the multicriteria problem of finding the optimal method for producing single-wall carbon nanotubes. The problem anal-ysis involves the original fuzzy models FTOPSIS and FMAVT implemented within the framework of the system. The DecernsFMCDA fuzzy decision support system is currently the only system that actu-ally implements all the main methods for solving discrete MADM problems, including dealing with un-certainties. The system allows forming and exploring scenarios using various models of multicriteria decision analysis, including those with different sets of parameters of specified models, for subsequent comparison and analysis of the output results as a part of the decision support process.

9. On the clarification of the principle of organizing software products quality control [№2 за 2022 год]
Author: Tikhanychev, O.V.
Visitors: 3626
The subject of the research is the process of developing software for automated control systems. The object of research is the quality control system of this process. Currently, regulatory documents and models for assessing the quality of software are built on the basis of a paradigm that determines that the quality of programs is checked for compliance with the terms of reference for development. But, as practice has shown, such a paradigm does not fully correspond to modern development conditions, providing not quality control, but verification of the compliance of programs with the customer's ex-pectations formulated at the initial stage of development. Taking into account the fact that the custom-er's requirements may not be fully formulated, and may also be refined in the course of work, the list of indicators and criteria that determine the quality assessment model formed at the beginning of the work may not ensure the quality of control. This thesis is relevant both when using "agile" and "waterfall" development methods. To solve the problem, the article uses general scientific methods of analysis and synthesis. Based on the analysis of existing approaches to assessing the quality of software development, proposals have been synthesized to refine the paradigm of its assessment. The article formulates the formulation of a scientific and practical problem and proposes one of the approaches to its solution, based on the re-finement of the currently used quality assessment paradigm, the transition from a "rigid", predeter-mined model, to a refined one in the course of work. The solution of the formulated problem will pro-vide a general increase in the efficiency of automated control by clarifying the paradigm for quality assessment, transition to the use of a dynamic model for assessing the software being developed.

10. Optimization of multivariate statistical control of scattering technological process indicators [№2 за 2022 год]
Authors: Klyachkin, V.N., Alekseeva A.V.
Visitors: 2265
The paper investigates the stability control of a multiparameter technological process when many indi-cators of this process are monitored at certain intervals. A generalized variance algorithm is used when monitoring the scattering of correlated indicators. The paper proposes an approach related to the search for optimal parameters of this algorithm according to the criterion of the minimum cost associated with control. In order to monitor the stability of process indicators and identify violations to adjust the process timely, we use statistical control – a widespread method of diagnosing and controlling technological processes. When controlling a multiparameter process, some of its indicators are correlated. In this case, Hotelling charts are used to control the average level, and the generalized dispersion algorithm is used to control multivariate scattering. To minimize the parameters of the generalized variance algo-rithm, three numerical optimization methods are used. The program is written in Python. The paper proposes a methodology and develops an appropriate program for optimizing the pa-rameters of multivariate statistical control of process scattering according to the criterion of minimiz-ing the costs associated with control: the frequency of sampling (the interval between samples), the sample size and the position of the control boundaries. This technique is illustrated by the example of data from a specific technological process: numerical values of control parameters and expected costs are obtained. Multivariate statistical control is used both to monitor the stability of technological processes (for example, machining processes, drug production processes, quality control of drinking water purifica-tion), and to diagnose the functioning of systems for various purposes (for example, vibrations of a hy-draulic unit). This explains the relevance and practical significance of the research related to its opti-mization.

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