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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Publication date:
16 June 2024

Articles of journal № 4 at 2020 year.

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Public date | Title | Authors |

1. Optimizing speed for VPN providing the possibility of telework using routers powered by ARM CPU [№4 за 2020 год]
Authors: S.V. Andreev , A.A. Khlupina
Visitors: 3851
This paper devotes to the problems of optimizing VPN speed connections when using routers with ARM processors. In the current context, many enterprises and institutions around the world raise the urgent issue of ensuring access for employees, as well as a remote branch or unit, to the resources of the head office local area network. The paper discusses the possibility of connecting employees through an encrypted VPN channel using modern home routers using ARM processors. With this ap-proach, all remote user devices are automatically connected to the local network resources of the head office, enterprise, and there are no needs for enterprise IT specialists to configure each of the user’s device individually. The paper considers a solution to a key problem of this approach, namely, ensuring the maximum speed of an encrypted VPN connection, and, therefore, accelerating the software components of routers included in its internal software (firmware) to provide a high-speed encrypted VPN connection. We consider the optimization of the speed of encryption and decryption algorithms using the features of the target processor of the device, such as parallelizing the execution of processor instructions using SIMD (Single Instruction, Multiple Data), general improvement of router performance when using op-timal compiler options, non-traditional use of PCI hardware encryption devices, use of alternative op-tions for modern private virtual networks (VPNs) for routers with a relatively low clock cycle frequen-cy of the ARM central processor (CPU), but containing more than two cores, while providing VPN channel multithreading.

2. Simulation of the heat conduction process using cellular automata systems [№4 за 2020 год]
Authors: S.P. Bobkov , E.G. Galiaskarov
Visitors: 3340
The paper concentrates on the use of discrete dynamic models as an alternative to the classical meth-ods of studying thermal processes in chemical technology. An adequate description of heat transfer phenomena is a hugely important problem, both in theoret-ical terms and from the standpoint of the practical use of thermal processes. In addition, modern teach-ing methods require the introduction of electronic textbooks, virtual laboratory workshops, simulation programs, which also need a correct description of the phenomena under study. The classical approach to modeling heat transfer in a continuous medium involves the use of heat conduction equations, in which the thermophysical characteristics of materials are usually constants. Taking into account the effect of temperature on the characteristics of materials leads to the need to study nonlinear equations, which causes significant computational difficulties. In this regard, it be-comes expedient to use fundamentally different approaches to modeling thermal conductivity, one of which is models based on systems of cellular automata. Discrete dynamic models in the form of deterministic cellular automata systems are used. In this case, a continuous medium is considered as a set of interacting elements whose behavior is completely described by local functions. The paper describes the main approaches and general methodology for the development of discrete models. The examples of cellular automata systems use for simulation of nonlinear heat transfer processes are considered, taking into account the heterogeneity of the material and the presence in the material of volumetric sources of variable power in it. The obtained data of discrete simulation are in good agreement with the results of using the classi-cal approach and do not contradict the generally accepted views adopted in the theory of thermal phe-nomena. The paper shows the features of the discrete approach in comparison with the use of partial differential equations with nonlinear coefficients, shows the advantages and disadvantages.

3. Method of functioning of the onboard radar system while ensuring their stealth operation on radiation [№4 за 2020 год]
Authors: A.V. Bogdanov , D.V. Zakomoldin , S.I. Akimov
Visitors: 3296
The survivability of a military aircraft depends to a significant extent on the survivability of its on-Board radar station, the main areas of improvement of which are, first, the application of the multi-position principle of building on-Board radars, and secondly, increasing the stealth of its work on radi-ation. This paper sets and solves the problem of developing a method that combines these areas of in-creasing survivability. The application of the multi-position principle is implemented by combining all on-Board radars into a single system controlled by the on-Board radar of the leader aircraft, which is determined in advance and serves as a point for processing radar information received from the on-Board radars of all the group's aircraft and issuing information to all the group's aircraft about the re-quired parameters of their on-Board radars. Secrecy operation of the system of airborne radar at the ra-diation detection group of enemy aircraft, equipped with electronic intelligence stations, implemented by means of reception on each side of the radar system information from the aircraft-leader about the required parameters, their on-Board radars, namely the values of the average radiation power of the transmitter, the time of coherent accumulation in the receiver and the time of irradiation of air targets and the formation of current data values of managed parameters of the onboard radar so that the differ-ence between the required and current values of the onboard radar parameters is zero. Held on Board the aircraft-leader calculations given in this paper, the results of these calculations for each on-Board radar systems as well as manage settings of each onboard radar systems allow you to control the signal-noise generated at the input of the receivers of all stations of electronic intelligence of the enemy, and thereby to ensure the secrecy of the operation of the onboard radar system for radia-tion with a given probability upon detection of a group of enemy aircraft equipped with radio engineer-ing reconnaissance.

4. Experimental analysis of the accuracy and performance of varieties of YOLO architectures for computer vision problems [№4 за 2020 год]
Authors: P.A. Bokov , P.D. Kravchenya
Visitors: 3583
Unmanned vehicles are increasingly being introduced into everyday life. To achieve full autonomy when traveling, unmanned vehicles use computer vision systems, which are responsible for analyzing the status of traffic lights, signs, and other objects that can appear on the road. Today, the standard in this area is YOLOv1 architecture, however, it is already obsolete. In this regard, a computer vision sys-tem for an unmanned vehicle based on modern technologies is being developed. There is the problem of choosing a computer vision architecture that will be responsible for analyz-ing traffic. First of all, it must be fast and accurate, because road traffic changes very quickly, and the accuracy of determination directly affects the degree of involvement of passenger-drivers in the pro-cess in order to avoid emergency situations. In addition, the architecture should occupy as little compu-ting power as possible, and not waste a large number of energy resources. To investigate these issues, it was decided to carry out an experiment that would reveal the advantages and disadvantages of various YOLO architectures. Also, the data provided by different researchers is very different due to using dif-ferent equipment while training and testing of networks. This makes it impossible for data to be com-pared objectively. The paper analyzes various types of YOLOv3 architecture and its versions for low-power compu-ting systems YOLOv3-tiny, describes their advantages and disadvantages for computer vision systems. The experiments are carried out on single hardware for all analyzed architectures. Experimental re-search on the accuracy and performance of various YOLO architectures is being done. The VOC2012 dataset is used for training and testing. As a result of the research, the strengths and weaknesses of the architectures under consideration are determined and options for the further development of the tech-nology are analyzed, taking into account the growth in the power of computing systems and the emer-gence of new technological solutions.

5. Method of synthesis of adaptive radio technical monitoring system [№4 за 2020 год]
Author: S.V. Butsev
Visitors: 2297
Radio technical monitoring systems for various mission objectives operate in the presence of both un-certainties in the parameters of the monitored process and the uncertainty of a generalized disturbance. The author of the paper has developed a method for synthesizing algorithms for the functioning of an adaptive radio technical monitoring system, consisting of an adaptive filter and an adaptive control system. The synthesis of an adaptive filter for a monitoring input signal includes the development of a slid-ing adaptation algorithm based on a direct estimate of the filter parameters, in particular, the gain weights generated by the adaptation unit and used in the main filter of the monitoring system. The paper proposes to use a two-level structure, which includes two stages of synthesis: the main control loop (optimal controller) and the adaptation loop (adaptive controller). The optimal controller is synthesized on the basis of the principles of the theory of optimal control of stochastic processes, provided that the parameters of the control object of the radio engineering tracking system are constant and known, and external disturbances do not change (or are absent). The synthesis of the adaptive con-troller is carried out for the case of the simultaneous presence of the uncertainty of the parameters of the control object of the radio technical monitoring system and external disturbances acting on it (model of disturbances of the control object of the radio technical monitoring system), based on the re-current modification of the least-squares identification method. The proposed approach makes it possible to formalize the problem of the functioning of an adaptive radio technical monitoring system under conditions of uncertainty of generalized disturbance parame-ters. New relationships are obtained for the evaluation of gains of an adaptive filter and an adaptive regulator transmission matrix. The adaptive radio technical monitoring system developed on the basis of the proposed method en-sures efficient functioning within the formalized quality description on the basis of the indicator de-termined by the quadratic function which characterizes the accuracy of the system operation and its control costs. The paper provides some efficiency evaluation results of the synthesized adaptive radio tracking system functioning.

6. Implementation of data classification software based on convolutional neural networks and case-based reasoning approach [№4 за 2020 год]
Authors: Varshavskiy P.R., A.V. Kozhevnikov
Visitors: 5375
This paper devotes to the implementation of software for data classification using case-based reasoning (CBR) and convolutional neural network technology (CNN). CBR-methods are widely used to find so-lutions to various problems based on accumulated experience, and CNN are successfully used in solv-ing classification problems by isolating individual elements and forming high-level features using con-volution kernels. One of the necessary conditions for the success of solving the data classification problem is the presence of a correct training dataset. Unfortunately, this condition cannot always be fulfilled (for ex-ample, due to the complexity of the objects under consideration and lack of base information). Due to the ability to accumulate, use, and adapt existing experience, CBR-methods can be used to form a train-ing dataset that can be further used by other methods to solve the data classification problem. Thus, the integration of CNN and CBR improves the efficiency of solving the data classification problem. In addition, CBR-methods can be applied in areas with unpredictable behavior and can be trained in the process of functioning, for example, in the process of training neural networks. This paper proposes the CBR-method for CNN training, managing the process of training, and presentation of iterations of CNN training as a case. The selection of a training step based on precedents improves the performance of the neural network training algorithm. Based on the proposed methods a neural network block using CNN for extending the capability of the CBR-system for data classification is implemented in MS Visual Studio in C# language. To evaluate the effectiveness of the solutions proposed in the work, computational experiments were performed on real data sets.

7. Development of a computational environment for the simulation of gas transmission systems regimes based on telemetry data [№4 за 2020 год]
Author: Е.А. Golubyatnikov
Visitors: 3277
The paper discusses the problems of software systems for modeling the regimes of pipeline systems based on telemetry data for dispatch control. The author analyzes the subject area, as well as the fea-tures of the modeling software implementation. As a result, the requirements for such systems are for-mulated. The main requirements are modularity; extensibility and flexibility of integration mechanisms with enterprise information systems and calculation modules; organization of complex and autono-mous computing process; support for distributed component interactions. It is noted that the regime-modeling software operated in the gas oil and gas transportation industry today do not fully meet the stated requirements. Therefore, the paper proposes to develop a specialized distributed computing sim-ulation environment based on telemetry. The paper presents architectural solutions for the computing environment. A microservice approach was chosen as the basis for creating the architecture. According to the ap-proach, the designed system is divided into small, context-sensitive functional blocks. The author pro-poses the way to decompose the developing system into services, describes the roles and functions of each service and methods for service integration. The developed architectural solutions were tested during dispatch control of a real gas transporta-tion system. The paper presents the implementation of the developed architecture. It is integrated with the SCADA-systems of the enterprise for the exchange of telemetry data and simulation results, as well as the Vesta software for solving hydraulic modeling problems. The created software product is used by dispatching personnel on a daily basis and allows solving urgent problems of operational manage-ment: real-time modeling, forecasting the process, calculation of analytical indicators of the system’s functioning.

8. Using statistical indexes to distinguish between scientific and popular science texts on the example of the works of A. E. Fersman [№4 за 2020 год]
Authors: Gorbich, L.G. , А.А. Zhivoderov
Visitors: 2279
With the development of information technology and information systems, the problem of developing methods for machine attribution of texts has become more relevant. These techniques can be used to automatically search for texts of the required genre and style, and establish authorship using computer technology. The development of our methodology was based on the hypothesis that there are structural features of the text that allow it to be attributed to a certain genre or author without taking into account the semantic content, based on the calculation of purely quantitative values of certain parameters and indices. The authors of this paper, along with other researchers, have been developing such indices and forming an optimal set of them for a number of years, and have achieved some success in this. In particular, a set of indexes was formed that allows one to cor-rectly classify texts of different authors by genre with a probability of up to 86 %. To solve the problem of automatic classification of scientific and popular science texts, the authors applied and improved a set of statistical indexes that they had previously developed for attributing other styles. The re-search material was based on the works of academician A.E. Fersman. One of the features of this author is the style duality – the presence of a large number of scientific and popular scientific texts belonging to him, which created a unique opportunity to try to solve the problem of automatic classification of text styles belonging to one author. In the course of the work, it was shown that the sample averages of statistical indices for texts of the two styles differ significantly. Using the methods of discriminant analysis, logistic regression, and ROC-curves, the authors demonstrated the possibility of automatic classification of texts of two styles and, by optimizing the set of indexes used, achieved a significant improvement in the quality of classification. A new statistical index is also proposed that allows minimizing computational costs and successfully (up to 100 % accuracy) solving the problem of classification of scientific and popular science texts, even when using it as the only factor. The results of the study were checked for texts by other authors.

9. The software for the subsystem of quality control of manufactured products using intelligent algorithms [№4 за 2020 год]
Author: Grishin E.S.
Visitors: 3360
This paper solves the problem of reducing the production of welded pipes from stainless steel grades of products of inadequate quality by creating software that functions as part of the plant's process control system and provides quality control of products using intelligent algorithms. The author describes an algorithm for continuous control of product quality, the result of which is a conclusion about the quality of products. On its basis, a subsystem of continuous quality control was developed, which controls the quality of finished products, based on a database of materials and tech-nological maps of manufactured products. This subsystem was developed as part of the creation and implementation of an integrated automat-ed process control system (APCS) and a subsystem for continuous diagnostics and equipment condi-tion monitoring using intelligent algorithms based on machine learning. To implement intelligent ma-chine learning algorithms, the open-source ML.NET cross-platform modeling framework was used, which allows you to get a model based on input data and simplifies the integration of the model into a finished .NET application. If necessary, the framework allows you to train additionally or retrain the model. The subsystem of continuous diagnostics and monitoring of the state of equipment is based on the production model of knowledge representation, which in turn is based on the processing of diag-nostic rules. Diagnostic rules are developed for specific production and unit of equipment by a special-ist in this subject area. The result of the work of the subsystem for quality control of manufactured products is the control of the characteristics of technological equipment that affect the quality of products, control of the characteristics of products based on the data of production flow charts, the issuance of warnings about the tendency for the observed characteristics to leave the range of permissible values and information about incipient defects in products, associated with these characteristics. As a result of the develop-ment of software for the subsystem of quality control of manufactured products using intelligent algo-rithms, the number of products of inadequate quality has been reduced due to the early detection of de-fects (wear) of equipment.

10. Optimization of lighting calculation for interior scenes for stochastic ray tracing [№4 за 2020 год]
Authors: S.V. Ershov , I.V. Valiev , A.G. Voloboy
Visitors: 2787
Lighting simulation and the creation of realistic images increases the efficiency of building design. The most common method used for this simulation is bidirectional Monte Carlo ray tracing. The paper discusses the improvement of the Monte Carlo ray tracing which optimizes the emitting of rays from a natural light source for interior scenes. The proposed algorithms can accelerate the con-vergence of the method, i.e. reduce the noise remaining after a certain simulation time, and thus im-prove the final image of the virtual scene. These algorithms are effective for indoor scenes illuminated externally through windows or other openings. Rays from light sources are generated so that they are directed into these windows, deliberately cutting off the rays that do not illuminate the interior. In other words, the number of rays increases for directions that contribute to the image formed by the camera. The first of the proposed algorithms require supplementary user specifications for marking win-dows, transparent doors, or other openings through which light can enter into interior rooms. The sec-ond algorithm is fully automatic. It belongs to a wide class of algorithms for finding and using the opti-mal PDF (Probability density function) in stochastic ray tracing. The second algorithm provides less acceleration for simulation but does not require action from the user, in particular, eliminating the po-tential error that can lead to underestimation of the room illumination. The paper provides the mathematical justification of the correctness of the proposed algorithms. The examples show that the proposed approach allows calculating the image with the desired quality several times faster.

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