Кафедра "Електронні обчислювальнi машини"

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http://crust.ust.edu.ua/handle/123456789/695

ENG: Department "Electronic Computers"

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Advanced Study on Resource-Saving Methods of Forming Information Infrastructure of Sorting Stations
(BP International, West Bengal, India, 2021) Kosolapov, Anatolii A.
EN: This chapter discusses a resource-saving method for choosing a rational structure of an automated control system when technical structure migration from a centralized system based on a powerful processor to a functionally distributed system based on microcontrollers. The method allows you to determine a rational number of subsystems that effectively use the computing and financial resources of the project. The approach is illustrated by a real example of designing an automated control system for a marshalling yard.
An Approach to Assessing the Operational Reliability of Real-Time Systems at the Stage of Conceptual Design
(ScientificWorld-NetAkhatAV, Karlsruhe, 2023) Belyaev, Nikolai; Kosolapov, Anatoliy; Egorov, Oleh Yo.; Sokur, Maria; Parpolita, Oleksandr M.
ENG: Сurrently, many facilities operate in real-time mode in an environment with a high level of radio-magneto-electronic interference. The software of such systems, debugged in stationary conditions, during the period of pilot operation gives a large number o.
Basis for Innovation in the Computerization of Society
(ScientificWorld-NetAkhatAV, Karlsruhe, Germany, 2022) Kosolapov, Anatolii A.; Egorov, Oleh Yo.; Dziuba, Volodymyr V.; Parpolita, Oleksandr M.
ENG: In this chapter, the authors have tried, in the context of the high rate of innovation in the computerization of society, to highlight the immutable in their view basic concepts and their definitions, which make it possible to understand the essence of the ongoing transformations. The paper considers the main stages and levels of the implementation of enterprise automation systems and components of their structures. A formula for describing the concept of "CS architecture" is proposed, a generalized structure of a WEB-system and its safe implementation is given.
Choice of the Optimal Parameters of Measuring the Shaft Rotation Frequency of the Hydraulic Transmission of the Locomotive Using Microcontroller
(Дніпропетровський національний університет залізничного транспорту імені академіка В. Лазаряна, Дніпро, 2017) Zhukovytskyy, Igor V.; Kliushnyk, Ihor A.
ENG: Purpose. The article provides for finding solution to the problem of developing and improving the means for measuring tachometric data of the previously created information and measuring system for testing hydraulic locomotive transmission by substantiating the optimal sensor design and signal processing algorithms. At the same time first of all it is necessary to start from the possibility of modifying the already existing test bench for hydraulic locomotive transmissions at the Dnipropetrovsk diesel locomotive repair plant «Promteplovoz». Methodology. In the work, the researchers proposed a methodology for modifying the sensor design and the algorithm for processing its signals. It is grounded on previous developments of tachometric sensor of the optical type on the basis of D-2MMU-2 sensor of the microprocessor automated test bench system of hydraulic locomotive transmission in the locomotive repair plant conditions. Selection of the necessary measurement algorithm and the number of sensor teeth is substantiated by calculating instrumental and methodological errors. Also, the studies aimed at identifying the source of interference in the measurement of rotational speed are described and solution for its elimination has been found. Findings. For the designed rotation speed sensor of the optical type based on the existing D-2MMU-2 sensor, the authors analyzed the dependence of the methodological and instrumental errors. Based on the obtained data more rational variant of the rotation speed calculation algorithm is proposed, and the number of teeth of the sensor disk is justified. Further, the main source of measurement interference was established and a method for improving the hardware of the hydraulic locomotive test bench was proposed. Originality. There were conducted the studies according to the methodological and instrumental errors of the designed rotation speed of sensor. The mechanisms of interference filtering arising from the sensor rotation speed fixing were proposed. Additional studies have shown the need for a hardware revision of signal conditioner scheme. Practical value. Conducted studies make it possible to establish a rational number of sensor disk teeth, which allows improving the measurement algorithm. It was also performed a hardware improvement of signal conditioner scheme from the sensor, helping to get rid of interferences. The results of measurements in studies are the initial data to perform further studies in order to determine the technical condition of hydraulic transmission UGP 750-1200 during factory testing after repair.
Computer architecture
(Ukrainian State University of Science and Technologies, Dnipro, 2023) Yehorov, Oleh I.; Dziuba, Volodymyr V.; Ivin, Pavlo
ENG: Methodical recommendations are intended for students of the 3rd year of the specialty 123 "Computer engineering" to prepare for practical work in the discipline "Computer architecture".
Computer Architecture
(Ukrainian State University of Science and Technologies, 2024) Kosolapov, Anatolyi; Yehorov, Oleh I. ; Tymoshenko, Liudmyla
ENG: Educational and methodical recommendations are intended for students of the 3rd year of the specialty 123 "Computer Engineering" to prepare for the coursework in the discipline "Computer Architecture". Educational and methodological recommendations contain the main theoretical provisions for mastering the material, instructions for performing coursework, requirements for analysis of results and design of works.
Conceptual Resource-Saving Design of Real-Time Socio-Technical Systems
(IOP Publishing Ltd, England, 2021) Kosolapov, Anatolii A.; Ivin, Pavlo
EN: The article discusses the methodological resource-saving approach to the System design of socio-technical systems for real-time managing (STS RTM). The definition of STS RTM from the point of view of computer systems architecture is introduced. This approach made it possible to classify the main paradigms of using computer systems, including the modern stage, corresponding to STS RTM. For such complex systems, it is important to ensure their energy efficiency, which is ensured by the use of resource-saving models and methods for optimizing structural solutions. This is ensured by minimizing the total length of communications at the enterprise, saving computing and financial resources during system migration from a centralized structure to a functionally distributed hierarchical multi-microcontroller system. STS is a human a real-time machine system, therefore, the system's response time to the processing of requests related to the issuance of messages to the system's operating personnel is determined. The complex of formulated tasks and their solution on a common information and analytical base is extremely difficult without a unified system design methodology and automation tools for solving problems. Such a Framework is described in this article.
Cемиотико-агентно-онтологическая модель интеллектуальных систем
(ООО "Научный мир", Иваново, 2017) Косолапов, Анатолий Аркадьевич
RU: В работе рассматривается предложенная автором гибридная интегрированная семиотико-агентная-онтологическая модель интеллектуальных систем. САО-модель является развитием семиотической модели Д.А. Поспелова на основе новых парных агентных моделей и онтологических баз знаний для хранения агентов и описания системной семантики и прагматики. Дополненная средствами имитационного моделирования, организации диалога и процедурами принятия решений в условиях неполноты и неопределённости, а также большого количества данных САО-модель будет интеллектуальным инструментарием для создания, познания и развития интеллектуальных систем.
Cемиотико-агентно-онтологическая модель интеллектуальных систем (препринт)
(ООО "Научный мир", Иваново, 2017) Косолапов, Анатолий Аркадьевич
RU: В работе рассматривается предложенная автором гибридная интегрированная семиотико-агентная-онтологическая модель интеллектуальных систем. САО-модель является развитием семиотической модели Д.А. Поспелова на основе новых парных агентных моделей и онтологических баз знаний для хранения агентов и описания системной семантики и прагматики. Дополненная средствами имитационного моделирования, организации диалога и процедурами принятия решений в условиях неполноты и неопределённости, а также большого количества данных САО-модель будет интеллектуальным инструментарием для создания, познания и развития интеллектуальных систем.
Databases : methodical recommendations for individual task
(Ukrainian State University of Science and Technologies, Dnipro, 2022) Pakhomova, Victoria M.
ENG: Methodological recommendations are aimed at preparing and doing individual tasks in the discipline «Databases» for foreign applicants of Bachelor’s Degree of specialties 123 «Computer Engineering» and 125 «Cybersecurity».
Design of Databases by Bachelor’s Degree Applicants when Writing a Qualification Paper
(Kupriyenko SV in conjunction with KindleDP, USA, Seattle, 2023) Pakhomova, Victoria M.
ENG: For use by applicants for a bachelor's degree when writing qualification papers, the «BachelorDesignDB» methodology is proposed, which consists of the following stages: review of sources on existing databases; study of the subject area in order to form an initial attitude; database design using well-known methods («Normal Forms» and «Essence-Relation») and analysis of the design results obtained; creation of a designed database with the help of the selected software application and its protection; optimization and performance improvement of the created database; formulating conclusions and providing recommendations for the practical use of the created database.
Detection of Attacks of the U2R Category by Means of the SOM on Database NSL-KDD
(Український державний університет науки і технологій, ННІ «Інститут промислових та бізнес технологій», ІВК «Системні технології», Дніпро, 2022) Pakhomova, Victoria M.; Mehelbei, Yehor O.
ENG: Creating an effective system for detecting network attacks requires the use of qualitatively new approaches to information processing, which should be based on adaptive algorithms capable of self-learning. The mathematical apparatus of the Kohonen self-organizing map (SOM) was used as a research method. Python language with a wide range of modern standard tools was used as a software implementation of the Kohonen SOM addition, this section compiles the Python software model «SOM_U2R» using a Kohonen SOM. Created «SOM_U2R» software model on database NSL-KDD an error research was performed for different number of epochs with different map sizes. On the «SOM_U2R» model the research of parameters of quality of detection of attacks is carried out. It is determined that on the «SOM_U2R» created software model the error of the second kind of detection of network classes of attacks Buffer_overflow and Rootkit is 6 %, and for the class Loadmodule reached 16 %. In addition, a survey of the Fmeasure was conducted for a different number of epochs of learning the Kohonen SOM. It is determined that for all network attack classes (except Buffer_overflow) the F-measure increases, reaching its maximum value at 50 epochs.
Detection of Attacks on a Computer Network Based on the Use of Neural Networks Complex
(Дніпровський національний університет залізничного транспорту імені академіка В. Лазаряна, Дніпро, 2020) Zhukovyts’kyy, Igor V.; Pakhomova, Victoria M.; Ostapets, Denis O.; Tsyhanok, O. I.
ENG: Purpose. The article is aimed at the development of a methodology for detecting attacks on a computer network. To achieve this goal the following tasks were solved: to develop a methodology for detecting attacks on a computer network based on an ensemble of neural networks using normalized data from the open KDD Cup 99 database; when performing machine training to identify the optimal parameters of the neural network which will provide a sufficiently high level of reliability of detection of intrusions into the computer network. Methodology. As an architectural solution of the attack detection module, a two-level network system is proposed, based on an ensemble of five neural networks of the multilayer perceptron type. The first neural network to determine the category of attack class (DoS, R2L, U2R, Probe) or the fact that there was no attack; other neural networks – to detect the type of attack, if any (each of these four neural networks corresponds to one class of attack and is able to identify types that belong only to this class). Findings. The created software model was used to study the parameters of the neural network configuration 41–1–132–5, which determines the category of the attack class on the computer network. It is determined that the optimal training speed is 0.001. The ADAM algorithm proved to be the best for optimization. The ReLU function is the most suitable activation function for the hidden layer, and the hyperbolic tangent function – for the output layer activation function. Accuracy in test and validation samples was 92.86 % and 91.03 %, respectively. Originality. The developed software model, which uses the Python 3.5 programming lan-guage, the integrated development environment PyCharm 2016.3 and the Tensorflow 1.2 framework, makes it pos-sible to detect all types of attacks of DoS, U2R, R2L, Probe classes. Practical value. Graphical dependencies of accuracy of neural networks at various parameters are received: speed of training; activation function; optimization algorithm. The optimal parameters of neural networks have been determined, which will ensure a sufficiently high level of reliability of intrusion detection into a computer network.
Detection of U2R Attacks by Means of a Multilayer Neural Network
(Sworld & D. A. Tsenov Academy of Economics, Svishtov, Bulgaria, 2024) Pakhomova, Victoria M.; Mostynets, Vladyslav L.
ENG: As a research method, multi layer neural network (MLNN) configurations 41-1-Х-4 were used, where 41 is the number of input neurons; 1 – the number of hidden layers; X – the number of hidden neurons; 4 – the number of resultant neurons created using the Neural Network Toolbox of the MatLAB system, to detect U2R network attacks: y1 – Rootkit attack, y2 –Buffer_overflow attack, y3 – Loadmodule attack, y4 – No attack. Using the open database of NSL-KDD network traffic parameters on the created MLNN, a study of its error and number of epochs at different number of hidden neurons (25, 35 and 45 was carried out using different training algorithms: Levenberg-Marquardt; Bayesian Regularization; Scaled Conjugate Gradient. It is determined that the smallest value of the MLNN error was based on the use of the hyperbolic tangent as a function of activating a hidden layer according by the Levenberg-Marquardt training algorithm, and it is enough to have 25 hidden neurons. An assessment of the quality of detection of U2R attacks on MLNN configuration 41-1-25-4 at its optimal parameters was carried out. It is determined that errors of the first and second kind are 9 % and 10 %, respectively.
Determination of Network Attacks Using Neural Network Technologies
(ScientificWorld-NetAkhatAV, Karlsruhe, Germany, 2021) Pakhomova, Victoria N.
ENG: Formulation of the problem. Intrusion-Detection Systems (IDS) are used to detect network attacks in real time. In the information and telecommunication system (ITS) of railway transport, the problem of a large volume of network traffic arises, since standard approaches to data processing cease to be effective. One of the most effective approaches to classifying a large amount of data is the use of neural network technology. This approach allows detecting not only already known network attacks, but also detecting new ones.
Determination of the Optimal Parameters of Wireless Local Network on the Created Program Using the Ant Algorithm
(ProConference in conjunction with KindleDP Seattle, Washington, USA, 2022) Pakhomova, Victoria M.; Salohub, Maksym V.
ENG: The «WLAN_EliteAS» program, created in the JavaScript language of the ant algorithm, determines the optimal number of base stations of wireless local networks and their location on the territory of USUST. Initial data of the «WLAN_EliteAS» program: parameters of the territory of USUST (coordinates of vacant places; number of clients that need to be connected to base stations); wireless local network parameters (base station coverage radius, maximum number of clients to one base station); parameters of the ant algorithm (number of ordinary and elite ants, irrigation and evaporation, greed and laziness). The quality of the obtained solutions depends significantly on the choice of parameters of the ant algorithm.
Development of a Framework for Conceptual Design of RTS (FCD_RTS)
(Український державний університет науки і технологій, ІВК «Системні технології», Дніпро, 2024) Kosolapov, Anatolii A.; Egorov, Oleh Yo.; Parpolita, Oleksandr M.; Zhuk, Stepan
ENG: The paper proposes new results in improving the CoDeCS framework for the conceptual design of complex systems. A new architecture consisting of a subsystem for generating variants of enterprise information architectures (GEntA) and a subsystem for conceptual analytics (ConAn) for characterisation of real-time computer systems (RTSCS) is considered. Both subsystems rely on a common intellectual knowledge bank consisting of a base of facts, a base of production rules and a base of goals formed on the basis of the known experience of conceptual design of complex information-management computer systems. The paper describes the information-technological structures of formalised production lines and presents the first results of subsystems development.
Development of a Self-Diagnostics Subsystem of the Information-Measuring System Using Anfis Controllers
(НВП ПП «Технологічний центр», 2018) Zhukovyts’kyy, Igor V.; Kliushnyk, Ihor A.
EN: A hybrid self-diagnostic system was designed to evaluate correctness of functioning of sensors of the information-measuring system of testing hydraulic transmissions of diesel locomotives of UHP 750 type. The system features the possibility of checking certain four parameters in steady-state operation conditions using known mathematical dependencies. For the other 14 parameters (for which mathematical dependencies were not studied and which have a high complexity of calculations), 14 neural-fuzzy ANFIS networks were developed. Self-diagnostic algorithms using ANFIS controllers were elaborated. The algorithms provide prediction of individual system parameters with the help of ANFIS controllers and a further comparison of the predicted parameters with the measured parameters. The ANFIS controller structure with the proposed Sugeno rule set was constructed and its efficiency was shown. Network training and test of the diagnostic subsystem were performed using the data sets obtained in a series of tests of hydraulic transmissions conducted at Promteplovoz diesel locomotive repair plant. The test results have shown that application of the proposed procedure ensures obtaining of correct result of the self-diagnostic subsystem operation.
Distribution of Information Flows in the Advanced Network of MPLS of Railway Transport by Means of a Neural Model
(Dnipro National University of Railway Transport named after Academician V. Lazaryan, 2019) Zhukovyts’kyy, Ihor; Pakhomova, Victoria N.; Domanskay, Halyna; Nechaiev, Andrew
ENG: Abstract. Ensuring interoperability of railway transport is possible only due to the developed information structure. Today, Ukraine uses the information-telecommunication system (ITS) of railway transport, which is based on a data communication network. The effectiveness of its work is largely determined by the routing system. The current algorithm for choosing the shortest route, which is used in the existing routing protocol (OSPF), does not always lead to an effective result. However, there is MPLS technology, which could improve the quality of the ITS network by creating virtual channels between its nodes. The authors proposed a scheme for selecting tunnels for the flows in the MPLS network, which is based on the neural model of a multilayer perceptron of configuration 18–3–3–10 with the activation function Softmax in hidden layers and a linear activation function in the input layer. To simulate the network operation, flow data is needed: class of service (CoS), sender and recipient identifiers, average flow rate vector and tunnel data (their initial load). The final load of the tunnels is taken as the resulting output of the neural network, on the basis of which the tunnel is selected for the flow of the k-th class of service.
Forecasting Network Traffic in the Information and Telecommunication System of Railway Transport by Means of a Neural Network
(MATEC Web of Conferences, 2023) Zhukovytskyy, Igor V.; Pakhomova, Victoria M.
ENG: Network traffic is one of the most important actual indicators of the information and telecommunication system (ITS) of railway transport. Recent studies show that network traffic in the ITS of railway transport is self-similar (fractal), for the study of which the Hirst indicator can be used. One of the possible solutions is a method of network traffic forecasting using neural network technology, which will allow you to manage traffic in real time, avoid server overload and improve the quality of services, which confirms the relevance of this topic. The method of forecasting the parameters of network traffic in the ITS of railway transport using neural network technology is proposed: for long-term forecasting (day-ahead) of network traffic volume based on network traffic volumes for the previous three days using the created multilayer neuro-fuzzy network; for short-term prediction (one step forward, which takes five minutes) of network traffic intensity based on network traffic intensities for the previous fifteen minutes using the created multilayer neural network. The corresponding samples are formed on the basis of real values of network traffic parameters in the ITS of railway transport. Studies of optimal parameters of the created multilayer neural network, which can be integrated into specialized analytical servers of the ITS of railway transport, are carried out, which will provide a sufficiently high level of short-term forecasting of network traffic parameters (in particular intensity) in the ITS of railway transport at the stage of deepening the integration of the national transport network into the Trans-European Transport Network.

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