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:
13 September 2024

Journal articles №2 2024

11. Ensuring spatial information completeness, relevance and security in distributed computing systems of large organizations [№2 за 2024 год]
Authors: Trubin, V.D. ( - Ufa University of Science and Technology (Teaching Assistant), ; S.V. Pavlov ( - Ufa State Aviation Technical University (Professor), Ph.D; O.I. Khristodulo ( ) - Ufa State Aviation Technical University (Professor), Ph.D;
Abstract: Nowadays, it is a matter of course to use information technologies for collecting, managing and processing large volumes of heterogeneous information about organizations to manage them. The search for effective methods of storing and processing information on an organization computing infrastructure in order to manage that infrastructure more effectively remain an urgent task, as system administrators take an individual approach to each system. This paper investigates the use of GIS technologies to process spatial and attributive information about organization computing infrastructure objects on the example of a university as a complex distributed structure. One of the most important tasks is centralized storage of full and actual spatial data with access rights differentiation for users from different departments to different parts of a database to ensure data security. The result is a mechanism for forming a distributed spatial data structure designed to store geodata, taking into account the spatial distribution of organization individual subdivisions. The paper presents a diagram of interaction between different divisions of an organization with a geodatabase. The resulted research can be used for developing a storage structure of geodata about computer infrastructure objects, and any other area of organization activity. The subsystem of automated ensuring spatial data reliability and relevance that was developed for university GIS allows accelerating the processing of spatial information in a database eliminating outdated data duplication and current data replication, while leaving different forms of presenting this information for each GIS subsystem.
Keywords: data storage and processing methods, computing infrastructure, complex distributed system, attributive database, distributed database, geoinformation system
Visitors: 372

12. Secure file sharing based on trust networks and public key certificates using a developed application [№2 за 2024 год]
Authors: Khorev P.B. ( - National Research University “MPEI”, Ph.D; Losev, D.A. ( - National Research University (Graduate Student);
Abstract: The paper analyzes the shortcomings of existing software tools for file sharing (including cloud storage, messenger programs, e-mail). To eliminate the shortcomings, the authors of the paper have developed a project of a client-server application based on building a trust network using public key certificates of its participants. The project uses symmetric and asymmetric cryptography algorithms, methods for building trust networks and using public key certificates to ensure the authenticity, confidentiality and integrity of data. The implemented server part and the client mobile application allow users to exchange files with each other within one specific file storage. Uploaded files have electronic signatures of their creators and are stored on the server in encrypted form. When developing the application, the authors used the technology that facilitates its portability to other operating platforms. The client application is built and tested on devices running the Android operating system. The developed application has the functionality necessary for file hosting and ensures the authenticity, integrity and confidentiality of transferred files. This allows it to be used both by groups of private users and in corporate information systems.
Keywords: secure files sharing, trust network, public key certificates, client-server application
Visitors: 216

13. Study of the effectiveness of the search algorithm in image segmentation problems [№2 за 2024 год]
Authors: Zaporozhets, D.Yu. ( - Southern Federal University (Associate Professor), Ph.D; Kravchenko, Yu.A. ( - Southern Federal University (Professor), Ph.D; Kulieva, N.V. ( - Southern Federal University (Assistant); Semenova, M.M. ( - Southern Federal University (Postgraduate Student), ; Kuliev, E.V. ( - Southern Federal University (Associate Professor), Ph.D;
Abstract: Modern image processing techniques play a key role in a variety of applications, including medical diagnostics, robotics and computer vision. Image segmentation (selecting objects and areas in images) is an important task. The paper analyzes the application of three bioinspired algorithms: the bee colony algorithm, the firefly algorithm and the locust algorithm for the image segmentation problem. It presents a review of existing image segmentation methods, describes their limitations in terms of modern requirements for high accuracy and efficiency. Particular attention is paid to describing the mechanisms and operating principles of the bee colony and firefly colony algorithms, including their characteristics, advantages and disadvantages when solving segmentation problems. The authors of the paper have carried out an analysis of the locust algorithm regarding the image segmentation problem, including algorithm adaptation and experimental study using a variety of images. Algorithm adaptation involves introducing application-specific mechanisms to improve the accuracy and efficiency of finding an optimal solution that overcomes the limitations of existing methods. The paper presents experimental studies that confirm the locust algorithm superiority over other bioinspired approaches and demonstrates its effectiveness on a wide range of images. The advantages of the proposed locust algorithm are in image segmentation; it also opens new prospects when applied in various data processing fields. The paper focuses on such aspects of the locust algorithm as its flexibility, scalability, and the ability to adapt to complex segmentation problems. It makes the algorithm particularly valuable for applying in various fields requiring high accuracy and efficiency of image processing.
Keywords: locust behavior modeling, bee algorithm, bee colony optimization, locust algorithm, bioinspired algorithm, image segmentation
Visitors: 348

14. Software for the technological process of electron beam welding of thin-walled products [№2 за 2024 год]
Authors: S.O. Kurashkin ( - Academician M.F. Reshetnev Siberian State Aerospace University, Information-Control Systems Chair (Postgraduate Student); Bukhtoyarov V.V. ( - Academician M.F. Reshetnev Siberian State Aerospace University, Ph.D; Tynchenko V.S. ( - Academician M.F. Reshetnev Siberian State Aerospace University (Associate Professor), Ph.D; Shutkina E.V. ( - Reshetnev Siberian State University of Science and Technology, Information-Control Systems Chair (Student);
Abstract: The purpose of the study is to increase the efficiency of electron-beam welding (EBW) of thin-walled structures. To this end, the authors of the paper propose developing and implementing software methods for EBW process automated planning and control, including statistical and data processing and a mathematical model for calculating temperature distribution. At the moment, there are several solutions for modeling and management of the EBW process, but they have drawbacks, such as the modeling time in MATLAB in parameter optimization and commercial software focused on specific customer hardware. The authors propose to develop an automated control system for EBW thin-walled parts (ACS EBW) based on a mathematical model for calculating the temperature distribution on the surface of welded parts. This system will allow to simulate the EBW process for different alloys taking into account their geometry and thermophysical parameters, as well as to control, plan and predict the EBW process. These functions are presented in the form of modules that provide the setting of managed and recorded parameters, target values and acceptable ranges, which allows you to monitor and control the process and its deviations. The system can also be integrated with various electron beam equipment. The application of the EBW developed by the ACS makes it possible to optimize parameters, minimize defects in welded joints and obtain joints of the required dimensions. The subject of the study is data of measurements of parameters of the EBW process, which are used for monitoring, evaluation of stability and forecasting. ACS EBW can be used at enterprises engaged in electron-beam welding.
Keywords: aerospace structures, technological process, electron beam welding, modeling, automated management
Visitors: 372

15. Developing predictive analytics models for industrial equipment failures [№2 за 2024 год]
Authors: Chernukhin, A.V. ( - Mendeleev University of Chemical Technology of Russian (Postgraduate Student), ; Bogdanova, E.A. ( - Lomonosov Moscow State University (Postgraduate Student), ; Savitskaya T.V. ( - D. Mendeleev University of Chemical Technology of Russian Federation (Professor), Ph.D;
Abstract: The paper describes new approaches to building a model for predictive analytics of industrial equipment failures. The relevance of the study is due to the need to identify failures that lead to a decrease in operating efficiency or downtime of large production lines at an industrial enterprise in advance. The study examines modern approaches, which use machine learning to solve similar problems, and describes their advantages and disadvantages in detail. Data for training models was obtained from PJSC Severstal and include information on sensor readings measuring currents, temperatures, pressure and vibrations for six exhausters over three years. Training and testing involved only technical locations with faults during the analyzed period. Due to the complex relationship between sensor readings and exhauster condition, it was decided to create a predictive model based on “soft voting” between three algorithms with different classification approaches: a convolutional neural network, logistic regression and a support vector machine. The proposed approach is based on the high-level Python programming language using the Anaconda distribution. The paper describes the procedure for performing the research, presents block diagrams of the developed algorithms and their detailed description. The authors carried out comprehensive testing of the developed software that implements the fault prediction model. The study results confirm the performance of the proposed model for predicting failures of equipment technical components, which can be adapted for predictive analytics of failures of a large number of types of industrial equipment at large enterprises in metallurgical, chemical and other industries.
Keywords: fault prediction, industrial equipment, neural network, machine learning, predictive analytics, data intelligent analysis, mathematical and computer modeling
Visitors: 437

16. Recognizing jet trajectories of fire monitor extinguishing agent based on digital images [№2 за 2024 год]
Authors: Pozharkova, I.N. ( - Siberian Fire and Rescue Academy of SFS EMERCOM of Russia, Siberian Federal University (Professor, Associate Professor), Ph.D;
Abstract: The paper focuses on developing a technology for high-precision recognition of fire monitor jet trajectories based on their digital images obtained from a full-scale experiment. The purpose of the study is to increase the efficiency of collecting empirical data describing jet trajectories of a fire extinguishing agent from fire monitors based on the recognizing digital images. The proposed method is based on identification of boundaries of a fire-extinguishing agent jet with geometrical reference of corresponding points. The work presents main operations of the developed procedure: correction of geometric distortions including promising ones, preliminary image processing with detecting a fire extinguishing agent jet, recognition of jet boundaries taking into account geometric binding, post-processing of recognition results. In addition, the paper describes a method for selecting a primary trajectory contour based on sections in a polar coordinate system. In order to demonstrate the effectiveness of the proposed technology, the paper presents the results of using its software implementation based on the developed modules. The upper and lower boundaries of the fire monitor water jets were recognized in the image obtained in difficult conditions in terms of identifying a trajectory. The practical significance of the presented technique consists in collecting empirical data in the amount necessary for solving various problems related, in particular, to constructing and debugging software control algorithms for fire robots. At the same time, the developed technology allows using digital images obtained as a result of observation or experiment, which can have geometric distortion and noise due to external objects characteristic of large-scale jets in open and closed spaces. The scientific novelty of the research is in developing a primary jet boundary allocation method based on sections in polar coordinates, which increases the spatial resolution of recognition, and a technology of forming significant brightness jump on jet boundaries based on adaptation for solving the corresponding task and for consecutive application of the existing common techniques for digital images processing.
Keywords: fire monitor, jet trajectory, machine learning, section in polar coordinates, digital image, pattern recognition
Visitors: 356

17. Computer modeling of steel chemical composition to optimize steel production by combining heats [№2 за 2024 год]
Authors: Karachunov, A.G. ( - Cherepovets State University (Postgraduate Student), ; E.V. Ershov ( - Cherepovets State University (Professor), Ph.D;
Abstract: The purpose of the work is software implementation of the algorithm for searching an optimal steel chemical composition based on combining several melts within the framework of an operational production plan. Nowadays, ferrous metallurgy enterprises use a number of software tools for drawing up a production schedule, including those for calculating the volume of ferroalloys required to implement a given steel chemical composition, as well as selective testing of chemical compositions for compatibility with each other. The disadvantage of these solutions is the lack of a possibility of selecting a chemical composition for solving a specific production problem in terms of operational planning that satisfies the criteria of ferroalloy minimum consumption and ensures a minimum volume of semi-product overproduction at a fixed volume of melting. The paper describes a software model for increasing the combinability of steel chemical compositions when adjusting the content of chemical elements “Calculator of combinability of steel chemical compositions” and the underlying algorithms. The development is based on the property of unifying (combining) several chemical compositions of steel for various orders in such a way that the chemical composition formed on their basis meets the requirements of standards for the production of steel grades corresponding to orders and can be implemented in production. The implementation of the described solution into production will allow optimizing a production plan in terms of surplus, ensuring a reduction in the number of rejected orders, single melts, unsold product volumes, and also increasing the serial production of cast steel due to introducing new chemical compositions.
Keywords: steel chemical composition, the software, algorithms, mathematical model, optimisation, combination
Visitors: 337

18. Increasing the level of automation and objectivity of decision-making when transporting liquid cast iron in production [№2 за 2024 год]
Authors: Yemelyanov, V.A. ( - Financial University under the Government of the Russian Federation (Professor), Ph.D; Chernyi, S.G. ( - Kerch State Marine Technological University (Associate Professor, Chief of Department, Research Associate), Ph.D; Yemelyanova, N. Yu. ( - Financial University under the Government of the Russian Federation (Associate Professor), Ph.D;
Abstract: The study solves the current applied problem of developing a decision support system for a liquid cast iron transporting process. The relevance of the work is due to the need to increase the level of automation and objectivity of decision-making when transporting liquid cast iron in production. The study uses the ArchiMate architecture modeling language to design the functional architecture of a decision support system for the process of transporting liquid cast iron. The authors used an object-oriented approach (including object-oriented analysis, object-oriented design and programming) and a unified modeling language UML to model use cases of a decision support system in the liquid iron transporting process. The study involves designing a model of the functional architecture of a decision support system for the process of transporting liquid cast iron. It also involves a functional analysis and an object-oriented design of the static structure of the decision support system. A decision support system software has been developed for transporting liquid cast iron; it allows calculating the weight of cast iron based on primary data from sensors and supporting decision-making regarding ladle repair and operation. The proposed functional model of the decision support system architecture made it possible to develop specialized software to automate the decision-making process regarding ladles repair and operation. The developed decision support system software was tested on ladle operation data at an iron and steel works.
Keywords: ladle, cast iron transportation, architecture, the software, decision support system
Visitors: 382

19. Neural network method and a software tool for estimating power losses [№2 за 2024 год]
Authors: V.N. Pichugin ( ) - I.N. Ulyanov Chuvash State University (Associate Professor), Ph.D; Soldatov, A.A. ( - I.N. Ulyanov Chuvash State University (Associate Professor), Ph.D; Tyuryushova, E.R. ( - I.N. Ulyanov Chuvash State University (Student);
Abstract: Electric power companies face the problems of large economic losses due to unreliable electricity metering. The paper considers the process of collecting remote electricity metering data, for example, digital substations of enterprises and network companies engaged in electricity transmission. For this purpose, a digital module is placed at a remote substation that allows scanning electricity meter readings. The purpose of the study is to implement a software tool for processing and predicting data obtained using a digital radio receiver module for detection, identification and remote data transmission based on fractal antennas. The software tool was developed in the Visual Studio 2019 integrated environment using original libraries on the Windows platform. All object properties are available for modification, the interface form and visual components are created both during the design process and during compilation. A statistical method and the method of an artificial neural network of a multilayer perceptron were used to programmatically assess misreporting of electrical energy according to indications. Such methods of big data research based on analyzing electric energy meter readings, which are formed due to monthly collection, allow assuming their inconsistencies with standards, characteristics and a non-accounting type, the amount of losses, etc. The main result of the study is a new neural network method for detecting power loss data, which allows identifying incorrect commercial data of electric meter readings. The main practical result is developing a software tool for a digital module for transmitting readings of energy consumption devices. The module uses smart algorithms of the method to account inconsistencies in data on transmitted electricity at digital substations of PJSC ROSSETI.
Keywords: unreliable electricity metering, incorrect commercial data of electricity meter readings, , digital substations of a network company, neural network method
Visitors: 226

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