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Computation
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Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III
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Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III

A special issue of Computation (ISSN 2079-3197). This special issue belongs to the section "Computational Engineering".

Deadline for manuscript submissions: 20 September 2024 | Viewed by 2108

Special Issue Editors

Prof. Dr. Mykola Nechyporuk

E-Mail Website
Guest Editor
National Aerospace University “Kharkiv Aviation Institute”, Chkalova Str., 61070 Kharkiv, Ukraine
Interests: aerospace engineering; math modeling
Special Issues, Collections and Topics in MDPI journals
Dr. Volodymyr Pavlikov

E-Mail Website
Guest Editor
National Aerospace University “Kharkiv Aviation Institute”, Chkalova Str., 61070 Kharkiv, Ukraine
Interests: radar; positioning; navigation; engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Dmytro Krytskyi

E-Mail Website
Guest Editor
National Aerospace University “Kharkiv Aviation Institute”, Chkalova Str., 61070 Kharkiv, Ukraine
Interests: artificial Intelligence; computer vision; UaV
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will publish a set of selected papers from the International Conference “Integrated Computer Technologies in Mechanical Engineering” (ICTM 2023: ictm.khai.edu), which was held 27-29 December 2023 in Kharkiv, Ukraine. You are invited to submit contributions for consideration in this Special Issue.

Topics of the Special Issue include but are not limited to the following:

  • Information technology in the design and manufacture of engines
  • Information technology in the creation of rocket space systems
  • Aerospace engineering
  • Control systems and engineering
  • Transport systems and logistics
  • Big data and data science
  • Nano-modeling
  • Artificial intelligence and smart systems
  • Networks and communication
  • Cyber-physical system and ioe
  • Software engineering and it-infrastructure
  • Information modeling
  • Project management and business informatics
  • Hyper reality
  • Robotics and uav
  • Smart energy and grids
  • Cyber security and safety
  • Signal and image processing
  • Remote sensing radars

Prof. Dr. Mykola Nechyporuk
Dr. Volodymyr Pavlikov
Dr. Dmytro Krytskyi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computation is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence and smart systems
  • robotics and UAV
  • mechanical engineering
  • creation of rocket space systems

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

10 pages, 2344 KiB  
Article
An Analysis of the Stress–Strain State of a Layer on Two Cylindrical Bearings
by Vitaly Miroshnikov, Oleksandr Denshchykov, Iaroslav Grebeniuk and Oleksandr Savin
Computation 2024, 12(9), 182; https://doi.org/10.3390/computation12090182 - 6 Sep 2024
Viewed by 319
Abstract
A spatial problem of elasticity theory is solved for a layer located on two bearings embedded in it. The bearings are represented as thick-walled pipes embedded in the layer parallel to its boundaries. The pipes are rigidly connected to the layer, and contact-type [...] Read more.
A spatial problem of elasticity theory is solved for a layer located on two bearings embedded in it. The bearings are represented as thick-walled pipes embedded in the layer parallel to its boundaries. The pipes are rigidly connected to the layer, and contact-type conditions (normal displacements and tangential stresses) are specified on the insides of the pipes. Stresses are set on the flat surfaces of the layer. The objective of this study is to obtain the stress–strain state of the body of the layer under different geometric characteristics of the model. The solution to the problem is presented in the form of the Lamé equation, whose terms are written in different coordinate systems. The generalized Fourier method is used to transfer the basic solutions between coordinate systems. By satisfying the boundary and conjugation conditions, the problem is reduced to a system of infinite linear algebraic equations of the second kind, to which the reduction method is applied. After finding the unknowns, using the generalized Fourier method, it is possible to find the stress–strain state at any point of the body. The numerical study of the stress state showed high convergence of the approximate solutions to the exact one. The stress–strain state of the composite body was analyzed for different geometric parameters and different pipe materials. The results obtained can be used for the preliminary determination of the geometric parameters of the model and the materials of the joints. The proposed solution method can be used not only to calculate the stress state of bearing joints, but also of bushings (under specified conditions of rigid contact without friction on the internal surfaces). Full article
(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III)
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17 pages, 4355 KiB  
Article
On the Impact of Discrete Atomic Compression on Image Classification by Convolutional Neural Networks
by Viktor Makarichev, Vladimir Lukin and Iryna Brysina
Computation 2024, 12(9), 176; https://doi.org/10.3390/computation12090176 - 1 Sep 2024
Viewed by 338
Abstract
Digital images play a particular role in a wide range of systems. Image processing, storing and transferring via networks require a lot of memory, time and traffic. Also, appropriate protection is required in the case of confidential data. Discrete atomic compression (DAC) is [...] Read more.
Digital images play a particular role in a wide range of systems. Image processing, storing and transferring via networks require a lot of memory, time and traffic. Also, appropriate protection is required in the case of confidential data. Discrete atomic compression (DAC) is an approach providing image compression and encryption simultaneously. It has two processing modes: lossless and lossy. The latter one ensures a higher compression ratio in combination with inevitable quality loss that may affect decompressed image analysis, in particular, classification. In this paper, we explore the impact of distortions produced by DAC on performance of several state-of-the-art classifiers based on convolutional neural networks (CNNs). The classic, block-splitting and chroma subsampling modes of DAC are considered. It is shown that each of them produces a quite small effect on MobileNetV2, VGG16, VGG19, ResNet50, NASNetMobile and NASNetLarge models. This research shows that, using the DAC approach, memory expenses can be reduced without significant degradation of performance of the aforementioned CNN-based classifiers. Full article
(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III)
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21 pages, 6177 KiB  
Article
Statistical Synthesis and Analysis of Functionally Deterministic Signal Processing Techniques for Multi-Antenna Direction Finder Operation
by Semen Zhyla, Eduard Tserne, Yevhenii Volkov, Sergey Shevchuk, Oleg Gribsky, Dmytro Vlasenko, Volodymyr Kosharskyi and Danyil Kovalchuk
Computation 2024, 12(9), 170; https://doi.org/10.3390/computation12090170 - 23 Aug 2024
Viewed by 378
Abstract
This manuscript focuses on the process of measuring the angular positions of radio sources using radio engineering systems. This study aims to improve the accuracy of measuring the angular positions of sources that radiate functionally determined signals and to expand the range of [...] Read more.
This manuscript focuses on the process of measuring the angular positions of radio sources using radio engineering systems. This study aims to improve the accuracy of measuring the angular positions of sources that radiate functionally determined signals and to expand the range of the unambiguous operation angles for multi-antenna radio direction finders. To achieve this goal, the following tasks were addressed: (1) defining the models of signals, noise, and their statistical characteristics, (2) developing the theoretical foundations of statistical optimization methods for measuring the angular positions of radio sources in multi-antenna radio direction finders, (3) optimizing the structures of radio direction finders with different configurations, (4) analyzing the accuracy and range of the unambiguous measurement angles in the developed methods, and (5) conducting experimental measurements to confirm the main results. The methods used are based on the statistical theory of optimization for remote sensing and radar systems. For the specified type of signals, given by functionally deterministic models, a likelihood function was constructed, and its maxima were determined for different multi-antenna direction finder configurations. The results of statistical synthesis were verified through simulation modeling and experiments. The primary approach to improving measurement accuracy and expanding the range of unambiguous angles involves combining antennas with different spatial characteristics and optimally integrating classical radio direction-finding methods. The following results were obtained: (1) theoretical studies and simulation modeling confirmed the existence of a contradiction between high resolution and the width of the range of the unambiguous measurements in two-antenna radio direction finders, (2) an improved signal processing method was developed for a four-antenna radio direction finder with a pair of high-gain and a pair of low-gain antennas, and (3) to achieve maximum direction-finding accuracy within the unambiguous measurement range, a new signal processing method was synthesized for a six-element radio receiver, combining processing in two amplitude direction finders and one phase direction finder. This work provides a foundation for further theoretical studies, highlights the specifics of combining engineering measurements in direction-finding systems, and offers examples of rapid verification of new methods through computer modeling and experimental measurements. Full article
(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III)
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36 pages, 12528 KiB  
Article
Relation Models of Surface Parameters and Backscattering (or Radiation) Fields as a Tool for Solving Remote Sensing Problems
by Kseniia Nezhalska, Valerii Volosyuk, Kostiantyn Bilousov, Denys Kolesnikov and Glib Cherepnin
Computation 2024, 12(5), 104; https://doi.org/10.3390/computation12050104 - 16 May 2024
Viewed by 652
Abstract
In this paper, an analysis of existing models for describing surfaces of various types is performed, and the possibilities of their application at the level of mathematical modeling are analyzed. Moreover, due to the large number of models and the complexity of selecting [...] Read more.
In this paper, an analysis of existing models for describing surfaces of various types is performed, and the possibilities of their application at the level of mathematical modeling are analyzed. Moreover, due to the large number of models and the complexity of selecting the appropriate model, e.g., when conducting a practical experiment, an algorithm for choosing a specific model depending on the initial data is proposed. According to the algorithm, a software prototype that implements this algorithm (written in Python) is proposed. Full article
(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III)
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