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    <title>DSpace Collection:</title>
    <link>https://dspace.chmnu.edu.ua/jspui/handle/123456789/815</link>
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    <pubDate>Wed, 04 Mar 2026 17:45:02 GMT</pubDate>
    <dc:date>2026-03-04T17:45:02Z</dc:date>
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      <title>Logical Operations for DSS Components based on Optical Fuzzy Color Computing</title>
      <link>https://dspace.chmnu.edu.ua/jspui/handle/123456789/3083</link>
      <description>Title: Logical Operations for DSS Components based on Optical Fuzzy Color Computing
Authors: Timchenko, V.; Kreinovich, V.; Kondratenko, A.
Abstract: The article is devoted to developing intelligent computing systems for decision support in various fields of application with a large volume of fuzzy input information. The proposed approach is based on a combination of the advantages of optical color logic architecture, with high performance performing the main logical operations of disjunction, conjunction and negation, and fuzzy digital computing, significantly expanding the functionality of soft computing for the formation of various trajectories of decision output. Such hybrid computing systems use, among other things, algebraic summation and multiplication operations and form logical operations, for example, when it is necessary to consider the completeness of identical data and their mutual influence. The structure of the computing network and algorithmic procedures for modeling the basic component of the hybrid architecture for decision-making systems are formed. The proposed approach applies to the construction of hierarchically organized multi-level intelligent computing networks in various fields of application with large volumes of fuzzy data.
Description: Timchenko, V., Kreinovich, V., &amp; Kondratenko, A. (2025). Logical Operations for DSS Components based on Optical Fuzzy Color Computing. Journal of Multiple-Valued Logic &amp; Soft Computing, 46 (1), 311–333.</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://dspace.chmnu.edu.ua/jspui/handle/123456789/3083</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
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    <item>
      <title>Framework for enhancing digital competence among philology students.</title>
      <link>https://dspace.chmnu.edu.ua/jspui/handle/123456789/3082</link>
      <description>Title: Framework for enhancing digital competence among philology students.
Authors: Kazak, Y.; Bosa, V.; Moiseienko, N.; Ababilova, N.; Horbolis, L.
Abstract: The article reveals the content and structure of digital competence. The purpose of the study is to develop and test the developed pedagogical conditions and system for the formation of digital competence in students of philological specialties. The research methodology is based on: a combination of theoretical analysis and experimental verification; comprehensive measurement of digital competence; implementation of pedagogical conditions aimed at the practical application of digital technologies in philological training; statistical confirmation of the effectiveness of the developed model. As a result of the pedagogical experiment, the effectiveness of the developed pedagogical conditions and system for the formation of digital competence in students of philological specialties, which was implemented in higher educational institutions within the framework of professional training of students of philological specialties, was assessed and proven.
Description: Kazak, Y., Bosa, V., Moiseienko, N., Ababilova, N., &amp; Horbolis, L. (2025). Framework for enhancing digital competence among philology students. Revista Eduweb, 19 (4), 99–124. DOI: 10.46502/issn.1856-7576/2025.19.04.7</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://dspace.chmnu.edu.ua/jspui/handle/123456789/3082</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
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    <item>
      <title>Modern diagnostic methods using neuroimaging in neurology and neurosurgery</title>
      <link>https://dspace.chmnu.edu.ua/jspui/handle/123456789/3081</link>
      <description>Title: Modern diagnostic methods using neuroimaging in neurology and neurosurgery
Authors: Bidzilya, P. V.; Gudak, P. S.; Drosyk, M. M.; Chaika, O. M.; Dzhyvak, V. N.; Khramtsov, D. M.; Kuhel, Y. I.
Abstract: The purpose of the study was to provide a comprehensive overview of current neuroimaging technologies in neurology and neurosurgery, with a focus on their diagnostic and therapeutic applications. This review explores the neuroimaging technologies currently in clinical use that form the basis of modern diagnosis and treatment of neurological and neurosurgical diseases. A systematic analysis of studies from 2020 to 2025, drawn from medical databases Scopus, Web of Science, PubMed, and Google Scholar, highlights the advantages of neuroimaging technologies, which provide detailed, safe, and non-invasive information about the structure and function of the brain and central nervous system. The authors stress that computed tomography, magnetic resonance imaging, functional MRI, and positron emission tomography have become integral to clinical practice in neurology and neurosurgery. CT provides rapid and accessible diagnostics for patients with emergencies such as traumatic brain injury or stroke, thanks to its ability to quickly detect intracranial haemorrhages, fractures, and other damage. MRI is the gold standard for assessing neurodegenerative diseases, tumours, strokes, and brain injuries, as it offers high sensitivity to soft tissues, allowing for accurate localisation of pathological changes. Functional MRI, which measures brain activity by detecting changes in blood flow, is an important tool for neurosurgical planning, especially for localising functional areas of the brain prior to surgery. PET, in turn, allows the detection of molecular changes in brain tissue, which is important for the early diagnosis of diseases such as brain cancer, Alzheimer's, and Parkinson's. The basic conclusion is that further neuroimaging development promises significant improvements in the accuracy of diagnosis and personalisation of treatment for patients with neurological diseases.
Description: Bidzilya, P. V., Gudak, P. S., Drosyk, M. M., Chaika, O. V., Dzhyvak, V. H., Khramtsov, D. M., &amp; Kuhel, Y. I. (2025). Modern diagnostic methods using neuroimaging in neurology and neurosurgery. World of Medicine and Biology, 94 (4), 222–228. DOI: 10.26724/2079-8334-2025-4-94-222-228</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://dspace.chmnu.edu.ua/jspui/handle/123456789/3081</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
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    <item>
      <title>Dielectric properties and relaxation processes in nanocomposites based on polylactic acid and carbon nanotubes</title>
      <link>https://dspace.chmnu.edu.ua/jspui/handle/123456789/3080</link>
      <description>Title: Dielectric properties and relaxation processes in nanocomposites based on polylactic acid and carbon nanotubes
Authors: Lysenkov, E. A.; Bilyi, S. A.; Nesin, S. D.; Klepko, V. V.
Abstract: The dielectric properties of nanocomposites based on polylactic acid with the addition of carbon nanotubes, as well as relaxation processes in them, have been studied. The dependence of the dielectric permittivity on the frequency and the filler concentration is found, the percolation threshold is determined, and the relaxation behavior of the system is analyzed using the electric modulus. The results obtained testify to the influence of the structural and interfacial effects on the dielectric characteristics of the composite, which is important for the development of new functional materials.
Description: Lysenkov, E. A., Bilyi, S. A., Nesin, S. D., &amp; Klepko, V. V. (2025). Dielectric properties and relaxation processes in nanocomposites based on polylactic acid and carbon nanotubes. Ukrainian Journal of Physics , 70 (12), 860–860. DOI:&#xD;
10.15407/ujpe70.12.860</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://dspace.chmnu.edu.ua/jspui/handle/123456789/3080</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
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