Software & Systems

Latest issue articles

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1. Analyzing the time of Bell inequality test for information retrieval [№1 за год]
Authors: Alaa Aldarf, Alaa Shaker, Bessmertny I.A.
Visitors: 433
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.

2. The structure of a network multilevel computer model in terms of the component circuit method for implementing network virtual laboratories [№1 за год]
Authors: Alexey S. Boldenkov, Gandzha T.V., Dmitriev V.M.
Visitors: 473
The paper presents the architecture design and operation principle of a distributed computer laboratory for remote modeling of physical processes, as well as the application of a tool for distance learning using web technologies. The computer model is formed in terms of the component circuit method and provides flexibility in the modeling process. Its structure is based on the multilevel computer simulation method. It includes a visual level with visualization tools and interactive communication, a logical level that has the experiment algorithm itself, and an object level containing a model of the object under study as a component circuit with connected models of actuators and measuring devices. The architecture assumes a client-server connection for data exchange over the Internet. The paper proposes to develop a cross-platform application that is a web configurator including a library of visual components (digital indicator, pointer, slider, etc.). Special network components Receiver and Transmitter enable network interaction between a server and client applications. Client and server parts of the network computer model are connected via components developed within the development of the Russian MARS modeling environment. The practical significance of the proposed solution is in organizing multi-user network virtual laboratories and a unique combination of distance learning and computer modeling, which in turn simplifies the learning process and increases its efficiency. The presented structure is suitable both for implementing network multi-user simulators to train different technical specialists and for conducting remote experiments using one physical test bench.

3. 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: 266
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.

4. 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: 342
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.

5. Risk-oriented approach to designing an anti-terrorist protection system of educational institutions [№1 за год]
Authors: Vladimir M. Kolodkin, Dina M. Varlamova, Artem D. Shakirov
Visitors: 246
The paper presents a problem-oriented software package for computer forecasting of the consequences of terrorist attacks on educational institutions. One of the main forecasting tools is mathematical modeling. The complex simulates the development dynamics of an antagonistic conflict between a violator (terrorist) and risk recipients in a educational institution. When building a software package, the authors used a new concept of countering a terrorist attack. The concept feature is countering a terrorist attack by risk recipients expressed in moving human flows into security zones along safe trajectories in a building. The software package supports data integration of the spatial information model of a building, the intruder model characteristics, the characteristics of the controlled movement of human flows in emergency situations. The spatial information model of a building is created in a domestic BIM system Renga. The topological graph corresponding to the building topological model is constructed by a specialized plugin created by Renga. The advantage of the author's software package is the automatic mode of designing the reaction of risk recipients to violator’s actions. The mode provides damage minimization. Designing takes into account the characteristics of an institution engineering and technical protection system. The software package originality is to ensure the process of designing safe ways for moving human masses in a real-time emergency situation development. Real-time mode support provides a fundamental opportunity to build a decision support system based on a problem-oriented software package. The practical significance of the complex is also due to the possibility of using it as a simulator for training persons responsible for the integrated safety of educational institutions in emergency situations. The paper shows the application of the software package for ranking educational institutions by the anti-terrorist security level.

6. Neural network diagnosis of the cardiovascular diseases based on data-driven method [№1 за год]
Author: Mosin S.G.
Visitors: 236
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.

7. A system for recognizing, tracking and describing ant behavior on video footage taken in the field [№1 за год]
Authors: Elizaveta D. Moskovskaya, Evgeny V. Burgov, Anton D. Moscowsky, Natalia A. Grevtsova
Visitors: 409
The work is dedicated to developing a system for recognizing, tracking, and assessing quantitative behavioral characteristics of ants in video sequences. Such software is essential for biological research, specifically for studying ants (myrmecology). The current version of the system focuses on calculating the dynamic density of specimens in a given area, specifically the number of worker ants in a designated region per minute. Determining the dynamic density of ants in an area involves considering videos recorded on artificially marked surfaces in field conditions. Individual ants are recognized using a neural network-based detector that determines their position and key points corresponding to their head and abdomen. The object orientation in space is calculated based on these key points. The accuracy of determining ant boundary images was 92% with an orientation detection error of 0.4 radians. Due to determining object's orientation, we use an extended Kalman filter for tracking; the filter considers the tracking problem in motion prediction. The data correlation problem is solved by a criterion of minimum ant travel time. The ant movement trajectories obtained during the system operation are used to calculate dynamic density in arbitrary regions. The tracking system uses several developed heuristic techniques to reduce false-positive detections. Due to the employed algorithms, automatic calculation of dynamic density has become as accurate as manual video processing by humans. The obtained results will significantly facilitate myrmecologists’ work with video recordings, replacing manhours with more cost-effective machine hours. In the future, the system can be expanded with modules for determining other quantitative characteristics of animal movement.

8. Synchronous distributed computing at continuous execution of blocks of a limited number of program resource copiess [№1 за год]
Authors: Pavel А. Pavlov, Nikolay S. Kovalenko
Visitors: 370
When creating multiprocessor distributed computing systems, the problems of constructing and investigating mathematical models for organizing the interaction of processes competing for a software resource are of particular relevance. In this connection, distributed computing tasks related to obtaining mathematical relations, which can have both direct and inverse character, are of interest. When setting direct problems, the conditions are the values of multiprocessor system parameters, the solution is the minimum total time for making given volumes of calculations. The formulation of inverse problems is reduced to calculating multiprocessor system characteristics, searching for criteria of efficiency and optimality of organizing the execution of a set of distributed competing interacting processes. The apparatus of graph theory, linear Gantt diagrams, schedule theory, combinatorial optimization, matrix algebra, etc. is widely used when constructing and studying mathematical models and problems of optimal organization of distributed processes. This paper shows a constructed mathematical model of distributed computations, solves the problems of finding the minimum execution time of heterogeneous processes competing for using a limited number of program resource copies in a synchronous mode in cases of unlimited and limited parallelism in the number of processors of a multiprocessor system. It also uses the ideas of structuring a program resource into linearly ordered blocks with their further conveying by processes and processors of a multiprocessor system.

9. Modeling information processes of big data management systems to solve cybersecurity problems [№1 за год]
Authors: Poltavtseva M.A., Dmitry P. Zegzhda
Visitors: 442
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.

10. Information support for decision making when monitoring the condition of cryogenic equipment [№1 за год]
Author: Evgeny S. Soldatov
Visitors: 367
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.

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