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

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Publication date:
16 March 2021
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Journal articles №4 2021

1. On the implementation of a multifunctional web-based system for recording and accounting the scientists’ intellectual activity [№4 за 2021 год]
Authors: S.A. Vlasova (svlasova@jscc.ru) - Joint Supercomputer Center of the Russian Academy of Sciences – JSCC (Leader Researcher), Ph.D; N.E. Kalenov (nkalenov@jscc.ru) - Joint Supercomputer Center of the Russian Academy of Sciences – JSCC (Professor, Chief Researcher), Ph.D;
Abstract: The paper describes a WEB-system that implements services related to the formation and provision of multi-sided information about the results of scientific activities (publications and reports at sci-entific events) achieved by the employees of one organization or a group of organizations. The sys-tem focuses both on the end user seeking to obtain specific data, and on the administrative staff who forms reporting materials for the superior organization. The information base of the system contains related data on the following object classes: per-sons (authors of publications and reports), organizations and their divisions; publications at the an-alytical, monographic and summary levels; author's certificates; scientific events (conferences, symposiums, seminars); reports. The system consists of two modules: administrative (for data input and editing) and user, which is a special search engine that searches for information and visualizes it, provides the ability to navigate through related resources and to export data. A distinctive feature of the system is the introduced concept of equivalent objects. The objects represented in the system by different metadata, but related to the same physical entity, are consid-ered equivalent. Such objects are “persons” corresponding to the same author with different spell-ings of their surname in the bibliographic entries of publications; organizations with different vari-ants of their names; papers published unchanged in different languages. In accordance with modern requirements for reporting on publications, the system shows the funding sources for scientific re-search, as well as the affiliations of each author indicated in the papers. The system has a user-friendly interface, which does not require special computer skills. This al-lows recommending it as a tool for solving a set of tasks related to evaluating the results of intellec-tual activity of employees of scientific institutions.
Keywords: software product, network technologies, database, an automated system issue, scientific activity results
Visitors: 800

2. A software platform demonstrator for joint use of evidence theory algorithms and neural networks in fuzzy systems [№4 за 2021 год]
Authors: Ivanov V.K. (mtivk@mail.ru) - Tver State Technical University, Ph.D; Palyukh B.V. (pboris@tstu.tver.ru) - Tver State Technical University, Ph.D;
Abstract: The diagnostics of a complex multi-stage technical process involves the joint primary data pro-cessing to obtain probabilistic characteristics of abnormal critical events or incidents under uncer-tainty. The paper presents the research demonstrator Status-4 that is a software platform prototype for joint using the evidence theory and neural network methods in fuzzy diagnostic systems. The purpose of the demonstrator development is to create a scientific and technical reserve for ready-to-implement solutions transfer to the next project stages. The demonstrator makes it possible to show the main platform functional components, assess their system readiness level, conduct the platform research tests, perform software implementations testing of the selected and theoretically confirmed methods in various modes, check the functioning operability and efficiency at various parameter values and their combinations quickly. The demonstrator shows the options for the joint application of neural network and evidence theory methods in a hybrid expert system for diagnos-tics process. In addition, these methods joint application effectiveness is experimentally confirmed in terms of reducing the uncertainty level and increasing the confidence in data level when making decisions. The demonstrator enables minimizing the key risks of creating a full-featured software platform for diagnosing and evaluating the complex multi-stage technologies state. The paper provides brief information about the demonstrator functionality, including the tech-nology description and the suppositions description about diagnostic variables influence on pro-cessing performance, loading incident descriptions into the technological database, forming hy-potheses about the incidents causes, generating production rules, adapting the parameters of the technology state assessing algorithms using neural network and fuzzy inference. The paper consid-ers the main data warehouse and object model parameters, provides the software implementation and user interface information and illustrates it by examples. It also highlights the used methods features, which allow us to hope for the effectiveness of their joint use in diagnostic systems.
Keywords: technological process, technological chain, evidence theory, fuzzy system, neural network, malfunction, incident, diagnostics, demonstrator
Visitors: 706

3. Thermodynamic constraints and information conditions of intelligent cognitive control stability, controllability, and robustness [№4 за 2021 год]
Authors: Ulyanov S.V. (ulyanovsv46_46@mail.ru) - Dubna State University – Institute of System Analysis and Control, Dubna, Joint Institute for Nuclear Research – Laboratory of Information Technology, Ph.D; Shevchenko A.A. (allabard@yandex.ru) - Dubna State University – Institute of System Analysis and Control (Postgraduate Student); Shevchenko A.V. (sh3vchenkoav@yandex.ru) - Dubna State University – Institute of System Analysis and Control (Postgraduate Student); Tyatyushkina O.Yu. (tyatyushkina@mail.ru) - Dubna State University – Institute of System Analysis and Control (Associate Professor), Ph.D;
Abstract: The paper considers information and physical (entropy and energy) patterns, as well as the features of the model of a quantum strong artificial computational intelligence as a self-organizing intelli-gent control system. The model is based on the principles of minimal information entropy (in the “intelligent” space state of control signals) and the minimal generalized thermodynamic measure of the entropy production in the unified system “control object + intelligent cognitive controller”. The main result of applying the self-organization process is the guaranteed possibility of achieving the necessary reliability and flexibility level of the reproducible structure of the cognitive intelligent control system. The paper briefly describes the main physical principles of management processes allowing es-tablishing the relationship between the qualitative characteristics of the dynamic behavior of the control object and the executive device of the automatic control system: control stability, controlla-bility, and robustness. To achieve this purpose, it uses the information and thermodynamic ap-proaches that combine dynamic stability (Lyapunov function), controllability and robustness crite-ria by a homogeneous condition. The authors give the relations between the amount of pure work, information and the extracted free energy, which confirm the possibility of increasing the intellectual control system robustness due to the production of entropy of a cognitive controller that reduces the loss of the useful re-source of the control object. In turn, the negative entropy of cognitive control reduces the require-ments for the minimum initial information to achieve robustness. Based on the retrieved infor-mation from the cognitive controller knowledge base, it is possible to obtain an additional resource for useful work, which is equivalent to a targeted action on the management object, ensuring the management goal achievement.
Keywords: quantum self-organization algorithm, imperfect knowledge base, information process thermodynamics, , cognitive control system
Visitors: 603

4. Semiotic control system for a mobile robotic platform [№4 за 2021 год]
Author: M.A. Rovbo (rovboma@gmail.com) - National Research Centre “Kurchatov Insitute” (Research Engineer); Sorokoumov P.S. (petr.sorokoumov@gmail.com) - National Research Centre “Kurchatov Institute” (Research Engineer);
Abstract: The paper considers the problem of combining a control system based on a semiotic model of a ro-bot’s world and human-machine interfaces, in particular, a voice interface, into a single system that processes both user commands and the robot’s autonomous behavior. The developed system allows controlling a robot using a voice interface, executing extended be-haviors, eliminating command ambiguities by resolving spatial relationships and taking into account the operator's gaze direction. This is achieved by integrating all the information necessary for mak-ing a decision and choosing the robot's action into the world model, applying logical inference to supplement it, and using heuristics to eliminate ambiguities in the speech command when there are not enough known facts for this. The decision-making system based on this world model also pro-vides the robot’s autonomous response to special situations. The paper describes the developed system architecture and demonstrates the applicability of this approach using a simulated model of a mobile robot in Gazebo. The simulation showed the possibil-ity of controlling a mobile platform using the developed system and the indirect control proved to be more ergonomic. Although, it should be noted that the computational load increases substantially when it is necessary to process a large number of objects in the world and it is impossible to process conflicting information in the current implementation. The computational load is partially compen-sated by algorithms that make it possible to infer only the information necessary to process the current command.
Keywords: voice control, human-machine interface, robotics, a control system, semiotic models
Visitors: 658

5. Analysis of hybrid controllers in control models of technical objects operating in changing conditions [№4 за 2021 год]
Authors: V.V. Ignatyev (vova3286@mail.ru) - Southern Federal University (Associate Professor), Ph.D; V.V. Solovev (soloviev-tti@mail.ru) - Southern Federal University (Senior Lecturer); Beloglazov D.A. (vvignatev@sfedu.ru) - Southern Federal University (Associate Professor), Ph.D;
Abstract: The paper analyzes hybrid controllers for control models of technical objects operating in changing conditions. It also considers the models which involve control based on hybrid controllers imple-mented on the basis of sequential interaction between PI- and IPI-FUZZY-controllers and PID- and IPD-FUZZY-controllers with the generated structure of the Sugeno-type fuzzy inference system and the developed ANFIS model. In hybrid controllers, the fuzzy controller rule base is formed automatically using a specially developed algorithm based on data obtained from a classical controller with subsequent training us-ing a neural network. The ANFIS design principle in the form of a hybrid network for PI and IPI-FUZZY controllers is the use of the output signal error indicators, its integral (differential for PID and IPD-FUZZY controllers) and control action. The following aspects have become the develop-ment features. In order to test the hybrid network efficiency to identify the fact of its retraining, the authors used the data obtained as a result of the classical regulator operation; to form a training sample for building a hybrid network they used the data obtained as a result of the fuzzy regulator operation. This makes it possible to exclude expert’s participation in the synthesis of the fuzzy con-troller rule base and to ensure efficient and robust control of an object functioning in unforeseen external situations. The IPI-FUZZY-controller and the IPD-FUZZY-controller have shown better quality indicators comparing to the corresponding classical ones, which makes it possible to recommend using in real control systems. The presented models were developed in the Simulink environment and the ANFIS editor of the Fuzzy Logic Toolbox extension package.
Keywords: control management, hybrid model, intelligent controller, rule base, the training, uncertainty
Visitors: 610

6. A simulation model for estimating the service life of the Internet of Things under the conditions of attacking effects emitting the node energy [№4 за 2021 год]
Authors: T.M. Tatarnikova (tm-tatarn@yandex.ru) - St. Petersburg State University of Aerospace Instrumentation (Associate Professor, Professor), Ph.D; P.Yu. Bogdanov (45bogdanov@gmail.ru) - Russian State Hydrometeorological University (Senior Lecturer);
Abstract: The low power of the sensor nodes of the Internet of Things determines the search for solving sev-eral urgent problems: increasing the service life of sensor nodes and the security of the Internet of Things. Sensor nodes use batteries with limited resources as a power source, therefore if a sensor network is installed and deployed in a remote geographic space to observe physical phenomena, then recharging or replacing sensor nodes may become impossible or expensive due to the long dis-tance. Power consumption is one of the important quality indicators of the Internet of Things defined as the amount of energy used and spent by sensor nodes. Energy consumption determines the network lifespan – the time when the sensor network is fully functional. On the other hand, the implementa-tion of IoT security mechanisms requires additional energy costs associated with their implementa-tion. However, the lack of security mechanisms causes the proliferation of attacks that emit the node energy, as well as reduced service life of the Internet of Things. The paper presents the results of a simulation experiment proving that timely detection of at-tacks contributes to an increase in the service life of the network compared to a network with no se-curity mechanisms. To understand the operation principles of the simulation model, there is a a de-scription of its main modules, which simulate real objects of the Internet of Things network: sensor nodes, routers, protocols, communication channels, attacks, data packets. The estimates of energy consumption and service life are given in the form of graphs of dependences on various parameters of the Internet of Things network.
Keywords: model experiment, simulation model, energy costs, lifespan of internet of things, internet of things network
Visitors: 720

7. Diagnosing the condition of a technical object using machine learning classification [№4 за 2021 год]
Authors: Lomovtseva N.A. (natalya.lomovtseva@gmail.com) - Ulyanovsk State Technical University (Graduate Student); Yu.E. Kuvayskova (v_kl@mail.ru ) - Ulyanovsk State Technical University (Associate Professor), Ph.D; Klyachkin V.N. (v_kl@mail.ru) - Ulyanovsk State Technical University (Professor), Ph.D;
Abstract: Diagnosing the functioning of complex technical systems is necessary to ensure their safety and reliability. Sometimes the diagnosis is reduced to the division of objects into healthy and faulty: there is a binary classification of machine learning methods according to precedents (with the teacher). However, when there is a need to describe an object’s state with several possible options (not just two: a healthy object or a faulty object), a more detailed study is often needed. In this case, a multi-class classification of the object's states is carried out. Machine learning techniques can be used effectively as for binary classification. The sample obtained from the preliminary tests is divided into two parts: training and test. The training part is for building models that help to divided objects into a given number of classes. It is assumed that there is some connection between the object’s performance indicators and states. Based on the training sample, it is necessary to build an algorithm that provides a sufficiently accurate object’s state assessment for a given set of performance indicators. The paper presents a developed multi-class classification program allowing building an algorithm model for reliable diagnosis of the object’s condition. At the same time, cross-validation is used to eliminate retraining. The three quality measures of the built models are used to take into account the specifics of the training sample applying different types of classifiers. As a numerical example, the authors consider the robot's navigation: according to the results of 24 distance sensors, one of the four directions of its movement is determined.
Keywords: robot navigation, aggregated approach, cross-validation, multi-class classification, technical diagnostics
Visitors: 618

8. Using discrete optimization tools to classify cognitive deficits: special aspects of using the minimax and additive criterion [№4 за 2021 год]
Authors: Razumnikova O.M. (razoum@mail.ru) - Novosibirsk State Technical University (Professor), Ph.D; Mezentsev Yu.A. (mesyan@yandex.ru) - Novosibirsk State Technical University (Professor), Ph.D; Pavlov P.S. (fuzzokolobok@gmail.com) - Novosibirsk State Technical University (Senior Lecturer); Tarasova I.V. (iriz78@mail.ru) - State Research Institute for Complex Issues of Cardiovascular Diseases (Leading Researcher), Ph.D; Trubnikova O.A. (olgalet17@mail.ru) - State Research Institute for Complex Issues of Cardiovascular Diseases (Head of Laboratory), Ph.D;
Abstract: The paper devoted to the development of discrete optimization methods for solving the applied problem of clustering the cognitive resources of patients with coronary artery disease (CAD). The methods reflect the prospects of their surgical treatment. Many indicators of different cognitive functions and brain activity are used to determine the cognitive deficits associated with aging and concomitant cerebrovascular atherosclerosis. Coronary artery bypass grafting, which is widely used to treat CAD patients, increases the risk of postoperative cognitive deficits. In this regard, it is im-portant to identify the most informative markers of the cognitive status in patients in the preopera-tive state. To classify this state, the authors use the hemispheric activity characteristics, i.e. lateral-ized power of the theta, alpha, and beta rhythms together with the indicator of minimal cerebral dys-function (MMSE) and the integral cognitive indicator based on a set of parameters obtained during a recording sensory-motor responses and testing attention and memory in 114 male patients admitted to the clinic for coronary artery bypass grafting. The average patient’s age is 55.9 ± 5.3 years; 90 of them had secondary education and 32 had higher education. The results of computational experiments with clustering indicators of psychometric and neuro-physiological testing of CAD patients have shown the effectiveness of the developed toolkit for clustering by the discrete optimization means and the best discriminatory capabilities due to the ad-ditive criterion.
Keywords: clusterization, minimax quality criterion, additive function, linear relaxation, binary cuts and branches algorithm, cognitive deficit detection
Visitors: 560

9. A comparative analysis of the parallel cluster multiple labeling technique on various sections of the MVS-10P OP supercomputer [№4 за 2021 год]
Author: S.Yu. Lapshina (lapshina@jscc.ru) - Joint Supercomputer Center of RAS (Head of the Scientific-organizational Department);
Abstract: The paper provides a comparative analysis of the Parallel Cluster Multiple Labeling Technique on five different sections of the MVS-10P OP supercomputer (taking into account the addition of a new section in 2021 and modernization of existing ones) installed at the JSCC RAS. At the JSCC RAS, the Parallel Cluster Multiple Labeling Technique is used to study the process-es of epidemic spread. At the same time, it is a versatile tool that can be used in any field as a tool for differentiating large lattice clusters receiving data as input in an application-independent format. There are known developments using this algorithm to study the processes of water flow through porous materials, the behavior of oil reservoirs, and the spread of forest fires. The supercomputer simulation experiment involved the improved version of the technique for multiple labeling of Hoshen-Kopelman percolation clusters associated with the labels linking mech-anism improved for using on a multiprocessor system. The paper provides a comparative analysis of the execution time of the algorithm for multiple marking of Hoshen-Kopelman percolation clusters at full load of computing nodes and different values of input parameters on five partitions (Broadwell, Cascadelake, Skylake, Optan, KNL) of the MVS-10P OP supercomputer installed at the Interdepartmental Supercomputer Center of the Rus-sian Academy of Sciences.
Keywords: processor cores, computing node, high-performance computing systems, parallel cluster multiple labeling technique, percolation’s cluster, multi-agent simulation
Visitors: 631

10. A synthesis method for fuzzy controllers based on clustering [№4 за 2021 год]
Authors: V.V. Ignatyev (vova3286@mail.ru) - Southern Federal University (Associate Professor), Ph.D; V.V. Solovev (soloviev-tti@mail.ru) - Southern Federal University (Senior Lecturer);
Abstract: The goal of this work is to develop a method for synthesizing fuzzy controllers from experimental data based on clustering, since this is the simplest way to determine the number of membership functions and create a rule base. To achieve this goal, it is proposed to use experimental data on the input and output signals of the control system for a technical object with a classical controller. The developed method for data clustering is based on the experimental data and makes it possible to de-termine the term-sets of input and output linguistic variables of a fuzzy controller that implements the Mamdani fuzzy inference algorithm and to compose a rule base. Clustering is performed by evaluating the boundaries of the experimental data variation inter-vals, uniform division into clusters depending on the required power of term-sets of linguistic vari-ables and determining if the data belongs to certain clusters. Since the experimental data are con-nected, that is, for each moment of time, data on both the input and output signals of the classical controller are stored and their belonging to clusters is determined, the development of the fuzzy controller rule base does not cause difficulties. To simplify the research, the authors have developed software in the MatLab environment. It makes it possible both to obtain experimental data, to synthesize a fuzzy controller and check its performance. The control system model is developed in the Simulink environment, the method of clustering and determining the parameters of linguistic variables is implemented as a program in an m-file; the fuzzy controller is implemented in the Fuzzy Logic Toolbox extension package. The high degree of integration of MatLab expansion packages made it possible to simplify the procedure of synthesizing fuzzy controllers as much as possible and to reduce it to determining the number of input and output variables and analyzing the simulation results. The paper presents the process of filling connected containers as an example, its mathematical model is a second-order transfer function with delay. To select an optimal structure of a fuzzy controller, the authors have carried out a study based on experimental data. The results obtained in this work were compared with the classical PD-controller, the model of which was implemented in the Simulink environment. The research results will be useful for developers of fuzzy control models.
Keywords: fuzzy controller, pid-controller, clustering, rule weight, reduction of the rule base, automatic synthesis rule base
Visitors: 619

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