Software & Systems

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1. Method of automatic configuration of routers [№1 за год]
Authors: Roza R. Fatkieva, Anton S. Sudakov
Visitors: 405
Modern network infrastructure includes various layers and types of devices, as well as a variety of protocols and services for interaction between devices. This complicates their management and first-time configuration. Mass configuration of the same type of devices enhances the likelihood of errors during their configuration. Automatic configuration of network devices facilitates the administration task, reduces the likelihood of errors and time for deploying a large number of network nodes. The paper considers existing approaches to configuring network devices. It presents a method of auto-mating the process of configuring routers using the theory of finite automata. It is shown that in terms of automatic configuration of routers, finite automata can be used to represent various states and actions that may occur during a configuration process. This allows developing an automated system responding to changes and events in the network, adapting to new conditions. The presented method is a base for algorithms of automatic detection of routers, their configuration and a method for collecting information messages that occur during device configuration. There is also a developed software package represented by a web application, which allows reducing the time of network infrastructure deployment. A practical example shows the ability to search for devices in the network, to analyze the equipment manufacturer by MAC address, remotely connect to it and automatically configure MikroTik routers. The developed software package can be used for quick and easy configuration of routers in medium and large organizations.

2. Analyzing the time of Bell inequality test for information retrieval [№1 за год]
Authors: Alaa Aldarf, Alaa Shaker, Bessmertny I.A.
Visitors: 431
The Bell inequality test enhances information retrieval and search engine efficiency. It orders retrieved results based on word relationships while prioritizing relevant outcomes. However, its time aspect remains unexplored since it is slower than the TF-IDF method. The research methodology of this work involves conducting experiments to analyze the time of the Bell test and exploring various aspects of the Bell test and its components. The experiments demonstrate that the HAL matrix computation constitutes a significant part of the total Bell test time exceeding 80%. The study also examines the use of the CuPy library on GPUs to accelerate HAL matrix calculations, which reveals that the benefits of GPU acceleration are limited due to data transfer overheads. Additionally, this work introduces the “save and restore” method, which involves precomputing and storing the HAL matrix in a database in order to reduce the time required for future queries. The effectiveness of this method is demonstrated for texts containing numerous repeated words that results in faster execution times compared to recalculating the HAL matrix for each query. The research holds practical significance for developing efficient and real-time IR systems. When identifying the major time-consuming components of the Bell test, particularly the the HAL matrix computation, the study points to potential areas for optimization and improvement in search speed and performance. Moreover, the introduced “save and restore” method provides a useful strategy for optimizing IR systems with texts containing repetitive content.

3. Intelligent system for analyzing traffic flows in automated traffic control systems [№1 за год]
Authors: Rumil M. Khusainov, Nafis G. Talipov, Aleksey S. Katasev, Darya V. Shalaeva
Visitors: 420
The paper presents the results of developing an intelligent system for analyzing traffic flows. The system development process involved mathematical calculations of a motion trajectory, speed, determining incidents and collecting statistics, and object-oriented programming. The source data are images taken from CCTV footage uploaded on the Internet. To match the YOLOv3 neural network, the video stream frames have a resolution of 1280720 and a scale of 16:9. The developed functional model reflects the intelligent system structure and functions, as well as the flows of information and material objects that link these functions. The paper considers examples of system operation and fulfillment of assigned tasks, as well as possibilities for further application of the developed traffic flow analysis system. Checking the intelligent system operation, as well as the results of its use for analyzing traffic flows, predicting and identifying incidents showed the effectiveness of the developed software and the practical suitability of the intelligent system for solving tasks. During operation, the system recognized the following objects: a car, a truck, a motorcycle, a bicycle, a pedestrian. It also recognized such incidents as traffic accidents, a stop, a congestion of cars, a traffic jam. According to the results of testing the implemented intelligent system using authors’ (prepared) video data and video data downloaded from the Internet, the reliability of the study results (correct recognition of traffic flow objects) in the intelligent traffic control system was 85–90 %. The results obtained were used to effectively manage traffic flows, increase the capacity of the road network, prevent traffic congestion, reduce delays in traffic, improve traffic safety, optimize the transportation process, inform road users about a traffic situation and options for an optimal route, ensuring the uninterrupted movement of ground urban passenger transport.

4. Information support for decision making when monitoring the condition of cryogenic equipment [№1 за год]
Author: Evgeny S. Soldatov
Visitors: 365
The article discusses the issues of information support for decision making when monitoring the condition of cryogenic equipment to increase safety and reduce cryogenic product losses during its operation. The main disadvantage of technical and organizational decision-making support systems, which are currently used in monitoring the condition of cryogenic capacitive equipment, is an inability to obtain real-time information about the predicted storage time of a cryogenic product taking into account the technical condition of the vessels, changing environmental conditions and operating modes. During this study, the author used methods of structural systems analysis, software engineering, computational fluid dynamics and reliability theory. The main result is the architecture of a decision support system for monitoring the condition of cryogenic equipment connected to a unified wireless data transmission network. The functionality of the system is to provide remote monitoring of the condition of cryogenic capacitive equipment, including the ability to predict the time of non-drainage storage of a cryogenic product based on the results of computer modeling and statistical data. The monitoring control center is organized according to the digital twin concept, which uses computer models of cryogenic equipment to organize two-way information interaction between a digital twin and a monitoring object. The developed decision support system ensures timely notification of responsible persons about potentially dangerous and emergency situations, as well as the accumulation of statistical information about the process of drainless storage of a cryogenic product. The paper presents a schematic diagram of an autonomous telemetry device for transport cryogenic equipment based on a long-range telemetry module and low-power autonomous telemetry modules for stationary and transport cryogenic equipment used in modern sensor networks. The practical significance of the results obtained is to ensure the possibility of timely adoption of preventive measures to prevent cryogenic product losses during storage and to prevent fire and explosion hazards.

5. Modeling biotechnological processes using a mathematical apparatus of artificial neural networks [№1 за год]
Authors: Sergey P. Dudarov, Ilya V. Maklyaev, Yury A. Lemetyuynen, Guseva E.V., Boris A. Karetkin, Svetlana A. Evdokimova
Visitors: 263
The paper focuses on studying and applying neural network technologies and tools for mathematical modeling and computer analysis in terms of biotechnological processes. The research considers modeling processes associated with gut microbiota functioning meaning microorganisms residing in the human intestine and performing several crucial functions for his health. To gather necessary data and construct models, the authors collected various indicators through experiments using a fermenter. These studies were conducted under various initial conditions: different concentrations of micro-organisms and nutrient substrate, with different environmental components. The acquired data became a base for two da-tasets: training and testing. The neural network modeling method was chosen as the research approach. Based on the training and testing datasets, neural network models were trained and subsequently tested for accuracy. A two-layer perceptron was employed as a neural network structure. The research resulted in special software to facilitate neural network modeling of biotechnological processes and to provide a mathematical description of the metabolic processes of bifidobacteria. This software was used to study relationship between the initial conditions, fermentation conditions, and bifidobacteria metabolism. The modeling results were analyzed and compared with alternative methods; they confirmed their high efficiency and the feasibility of using the neural network approach for modeling biotechnological processes. It was corroborated that using neural network models is a promising direction in the discussed domain. Due to their versatility and learning capability, neural networks can be effectively used for analyzing and describing complex processes, particularly the metabolism of gut microbiota. The developed software and algorithmic solutions offer models characterized by high accuracy and reliability. Consequently, they can be used for devising new methods for monitoring and optimizing biotech-nological processes, as well as for creating decision support systems in this field. Hence, the research presented in this paper holds substantial practical significance in advancing modeling and analysis methods for biotechnological processes. This, in turn, can play an essential role in the development of various biotechnology areas, including bifidobacteria production for the food industry and the creation of new pharmaceuticals.

6. Modeling information processes of big data management systems to solve cybersecurity problems [№1 за год]
Authors: Poltavtseva M.A., Dmitry P. Zegzhda
Visitors: 435
The imperfection of classical security models when applied to real systems has led to developing a reverse approach: modeling systems of different classes to subsequently supplement their models with security attributes. Nowadays solving distributed system security problems based on such models is a dynamically developing area of scientific knowledge. The paper considers modeling of heterogeneous big data management systems for solving modern cybersecurity problems. The authors identify and take into account such key features of the system class under consideration as using heterogeneous data structures and limitations of data manipulation tools, primarily with respect to the granularity of security functions during implementation. The paper proposes a graph model of a big data management system using generalized operations on data: merge, split and transform. Graph vertices represent structured data fragments, the arcs represent their processing operations regardless of a specific tool and a transformation type. Due to generalized operations, the model allows taking into account data transformations both within processing tools and when transferring information between them; it provides a comprehensive representation of information processing at the data engineering level. A special feature of the model is its construction automation based on a specific big data system, which helps maintaining adequacy during evolutionary changes in the modeled object. The presented model allows solving a wide range of problems in the field of security of large-scale heterogeneous systems, such as access control, auditing, security assessment. As an example, the paper shows how use the proposed model to automate the analysis of security policies in this class of systems.

7. Modifying the algorithm for frontal modeling of accidental release consequences based on the empirical and statistical approach [№1 за год]
Authors: L.O. Chernyshev , Matveev, Yu.N.
Visitors: 234
The paper examines an empirical-statistical approach to constructing a cellular model for visualizing the consequences of toxic substances being released into the atmosphere in case of a local accident. It is shown that under conditions of a priori uncertainty of input data, the computing core of the supervisory system, which reproduces accidental release consequences, should implement a two-loop information processing scheme. The effectiveness of parametric estimation of a model in the outer loop of such scheme largely depends on the speed and accuracy of model computations implemented by algorithms in the inner loop of modeling and visualizing release consequences. The paper analyzes features of parametric estimation procedures under conditions of information deficit for a continued release of toxic substances. It forms requirements for an alternative modification of the modeling algorithm taking into account the advantages of the empirical-statistical approach. There is a brief description of the developed algorithm: the choice of a sixteen-point modeling template is substantiated; the features of an empirical function modifying a field of distances depending on the angular direction of wind mass transfer are considered; a detailed algorithm block diagram and the main relations forming the distance map calculation basis with the subsequent assessment of the upper limits of pollutant concentration are disclosed. The paper identifies the advantages and disadvantages of the practical implementation of the algorithm. There are results of testing the algorithm while processing actual experimental data on a conditional model of a terrain map. The proposed approach will increase the performance of the frontal modeling algorithm and reduce the time spent on searching for a reference solution in a two-loop information processing scheme. The paper materials can be used to improve the functionality of supervisory decision support systems in eliminating the consequences of accidental releases.

8. Neural network diagnosis of the cardiovascular diseases based on data-driven method [№1 за год]
Author: Mosin S.G.
Visitors: 232
The paper considers methods for diagnosing cardiovascular diseases by electrocardiogram (ECG) tracing using artificial intelligence methods. It also determines the problems of diagnosing cardiovascular diseases by model-driven methods. The author proposes an approach to diagnosing cardiovascular diseases by a data-driven machine learning method without extracting the characteristic parameters of ECG signals. There is a presented architecture of a neuromorphic ECG signal analyzer based on a one-dimensional convolutional neural network, as well as its design route. Experimental studies were carried out on a set of ECG signals PTB-XL; they confirmed the operability and efficiency of the proposed approach. Both structural and parametric synthesis of a neuromorphic analyzer was performed for a different number of internal layers and initial training parameters. A comparative analysis of the obtained results found that a neural network with two convolutional layers has low training accuracy and high diagnosis errors; a three-layer neural network contributes to the growth of type I error; a four-layer neural network contributes to the growth of type II error. The use of a three-layer convolutional neural network with a smaller pooling window provided the diagnosis of up to 85.66 % of myocardial infarction cases. In conclusion, the author gives the directions for further research to improve the diagnosis accuracy by reducing an input ECG signal dimension, as well as introducing a probabilistic assessment of whether the considered signal belongs to one of the possible states of an ambiguity group.

9. Software implementation of algorithms for electrical equipment diagnostics (by the example of harmonic oscillation analysis) [№1 за год]
Authors: A.E. Kolodenkova , S.S. Vereshchagina
Visitors: 338
The paper proposes an algorithm for selecting electrical equipment parameters, an algorithm for searching deviations of harmonic oscillation values, as well as measures for preventing equipment malfunctions in complex diagnostics under conditions of multiple heterogeneous information. The algorithm for selecting electrical equipment parameters is based on classifying parameters by a character and degree of their impact on the equipment using a knowledge base containing product rules about the types and impact of a parameter on the equipment (basic, additional, auxiliary), as well as a database (equipment failure data, data from devices and sensors). The proposed algorithm allows classifying and selecting the most important diagnostic parameters affecting the state of electrical equipment; thus, it rejects insignificant parameters without information loss. The algorithm for searching deviations of harmonic oscillation values allows not only determining the time of a parameter deviation occurrence, but also the total deviation time in order to identify the causes of harmonic oscillations. The authors consider the structure of the program system of electrical equipment diagnostics with the description of interconnected modules, which have a database, a knowledge base and system interface screen forms as connecting links. The developed software system allows selecting methods of electrical equipment diagnostics, measures to prevent equipment malfunctions according to the selected type of its parameter; detecting malfunction, instability of equipment operation that results in an increase in voltage harmonics, for example, as well as poor power quality. Implementing the proposed approach to diagnostics of electrical equipment in production will allow making a scientifically sound decision regarding the choice of parameters for further diagnostics taking into account a variety of different information types. It will allow conducting deeper diagnostics and thereby identifying equipment failure.

10. Software emulator of quantum algorithms for sophisticated simulation on a conventional computer [№1 за год]
Authors: Ulyanov, S.V., Ulyanov, V.S.
Visitors: 572
A quantum software engineering platform includes quantum computing methods, a quantum algorithm theory and quantum programming. These areas develop according to a technological structure of nanotechnology development for hardware design of various configurations. In about 10 to 30 years we expect the appearing of an industrial quantum computer for real software engineering; this fact is due to overcoming a number of technological difficulties in implementing hardware, as well as the fundamental difficulty of eliminating decoherence physical phenomenon and correcting errors in quantum computers in near future. A key question in quantum computing is searching for quantum algorithms that potentially have a significant advantage and supremacy over classical algorithms for problems of practical interest. Therefore, currently, an approach is being developed to create quantum algorithm structures for quantum simulators with the possibility of effective implementation on classical architecture computers. This paper proposes an effective modelling method with information analysis of quantum search and decision-making algorithm structures in order to eliminate redun-dancy in practical implementation of a simulator on a classical structure computer. As an example, we demonstrate the method of modeling Grover's quantum search algorithm with stopping the search for a good solution based on the Shannon information entropy minimum principle. There are modeling examples to demonstrate the effectiveness of the developed approach in quantum software engineering and intelligent control robotics.

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