Сучасні інформаційні системи

Постійне посилання на розділhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/62915

Офіційний сайт http://ais.khpi.edu.ua/

У журналі публікуються результати досліджень з експлуатації та розробки сучасних інформаційних систем у різних проблемних галузях.

Рік заснування: 2017. Періодичність: 4 рази на рік. ISSN 2522-9052 (Print)

Новини

Включений до "Переліку наукових фахових видань України, в яких можуть публікуватися результати дисертаційних робіт на здобуття наукових ступенів доктора і кандидата наук" (технічні науки) наказом Міністерства освіти і науки України від 04.04.2018 № 326 (додаток 9, п. 56).

Переглянути

Фільтри

2023 - 20242

Налаштування

Автор: search.filters.author.Chumachenko, Dmytro

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  • Ескіз
    Документ
    Performance evaluation of python libraries for multithreading data processing
    (Національний технічний університет "Харківський політехнічний інститут", 2024) Krivtsov, Serhii; Parfeniuk, Yurii; Bazilevych, Kseniia; Meniailov, Ievgen; Chumachenko, Dmytro
    Topicality. The rapid growth of data in various domains has necessitated the development of efficient tools and libraries for data processing and analysis. Python, a popular programming language for data analysis, offers several libraries, such as NumPy and Numba, for numerical computations. However, there is a lack of comprehensive studies comparing the performance of these libraries across different tasks and data sizes. The aim of the study. This study aims to fill this gap by comparing the performance of Python, NumPy, Numba, and Numba.Cuda across different tasks and data sizes. Additionally, it evaluates the impact of multithreading and GPU utilization on computation speed. Research results. The results indicate that Numba and Numba.Cuda significantly optimizes the performance of Python applications, especially for functions involving loops and array operations. Moreover, GPU and multithreading in Python further enhance computation speed, although with certain limitations and considerations. Conclusion. This study contributes to the field by providing valuable insights into the performance of different Python libraries and the effectiveness of GPU and multithreading in Python, thereby aiding researchers and practitioners in selecting the most suitable tools for their computational needs.
  • Ескіз
    Документ
    Methodological support for Agile resource reallocation in a multi-project healthcare environment
    (Національний технічний університет "Харківський політехнічний інститут", 2023) Dotsenko, Nataliia; Chumachenkо, Igor ; Bondarenko, Andriy; Chumachenko, Dmytro
    The organization of medical assistance in de-occupied territories and territories close to combat activities necessitates reorganizing the existing medical system, making the task of developing methodological support for Agile-redistribution of resources in a multi-project medical environment relevant. The article aims to develop a methodological framework for Agile redistribution of resources in the medical environment. Research results & conclusions. In the paper, the issue of resource reallocation in a multi-project healthcare environment is examined. A methodological framework for Agile redistribution of human resources in a healthcare setting has been developed, which is based on the use of donor-acceptor interaction. An Agile method of resource redistribution in a multi-project healthcare environment has been developed, enabling healthcare facilities to be provided with resources, taking into account the principles of resilience, adaptability, and functional reservation. A model of the Agile resource redistribution process (IDEF0) has been constructed. The use of a scenario approach to ensure Agile resource redistribution is considered. The main scenarios for redistribution have been identified. An IDEF3 model of the resource redistribution process (scenario approach) has been developed. An example of applying the developed methodological framework for conducting Agile redistribution of human resources in a healthcare environment is considered. The use of the developed support for the selected example allowed for the selection of a redistribution option that meets the defined reservation requirements, taking into account the chosen scenario.