Work place: The National Defence University of Ukraine/ Scientific and methodological center for the organization of scientific and technical activities, Kyiv, 03049, Ukraine
E-mail: kibtor@gmail.com
Website:
Research Interests: Machine Learning, Computer Vision, Artificial Intelligence
Biography
Doctoral сandidate Serhii Tsybulia, Scientific and methodological center for the organization of scientific and technical activities, The National Defence University of Ukraine, Ukraine.
(ORCID ID https://orcid.org/0000-0003-0323-1771)
Major interests: artificial intelligence, machine learning, artificial neural networks, convolutional network, computer vision, camouflage of objects, camouflage synthesis, texture mapping.
By Artem Volokyta Heorhii Loutskii Oleksandr Honcharenko Oleksii Cherevatenko Volodymyr Rusinov Yurii Kulakov Serhii Tsybulia
DOI: https://doi.org/10.5815/ijcnis.2024.01.08, Pub. Date: 8 Feb. 2024
This article considers the method of analyze potentially vulnerable places during development of topology for fault-tolerant systems based on using betweenness coefficient. Parameters of different topological organizations using De Bruijn code transformation are observed. This method, assessing the risk for possible faults, is proposed for other topological organizations that are analyzed for their fault tolerance and to predict the consequences of simultaneous faults on more significant fragments of this topology.
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