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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, DmytroTopicality. 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.Документ Selection of the optimum route in an extended transportation network under uncertainty(Національний технічний університет "Харківський політехнічний інститут", 2021) Raskin, Lev; Sira, Oksana; Parfeniuk, YuriiRelevance. For a given values set of extensive transport network sections lengths an exact method has been developed for finding optimal routes. The method provides an approximate solution when the initial data - are random variables with known distribution laws, as well as if these data are not clearly specified. Fora special case with a normal distribution of the numerical characteristics of the network, solution is brought to the final results. Method. An exact method of deterministic routing is proposed, which gives an approximate solution in case of random initial data. The method is extended to the case when the initial data are described in theory of fuzzy sets terms. The problem of stability assessing of solutions to problems of control the theory under conditions of uncertainty of initial data is considered. Results. A method of optimal routes finding is proposed when the initial data are deterministic or random variables with known distribution densities. A particular case of a probabilistic -theoretical description of the initial data is considered when can be obtained a simple solution of problem. Proposed method for obtaining an approximate solution in the general case for arbitrary distribution densities of random initial data. The situation is common when the initial data are not clearly defined. A simple computational procedure proposed for obtaining a solution. A method for stability assessing of solutions to control problems adopted under conditions of uncertainty in the initial data, is considered.Документ Structural optimization in a multi-channel distributed mass service system(Національний технічний університет "Харківський політехнічний інститут", 2021) Raskin, Lev; Sira, Oksana; Parfeniuk, Yurii; Sukhomlyn, LarysaProblem of structural optimization in a distributed service system is solved by the example of system "Production - delivery - consumption" for mass market product. In this regard, the purpose of work is to develop a method for structural optimization of "Production - delivery - mass consumption" system, by introducing and rational placement of intermediate production points based on solving clustering problems with taking into account the peculiarities of calculating distances between city objects. To achieve the goal of the work, it is necessary to solve the following tasks: clustering of city objects, using the metric of city blocks, for a given number of groups for selected location of production and grouping centers; finding the best location for a given number of clustering centers; determination of a rational number of clustering centers. Task was solved in three stages. First stage - clustering a set of consumption objects for given intermediate delivery centers locations. The second stage - finding the best locations for a given number of intermediate delivery centers. The third stage - determination of the rational number of intermediate centers. Formulated problem is solved according to two criteria: combined length of delivery routes product consumers and the probability that a random delivery time exceeds the critical value. The numerical value of the second criterion is calculated on the assumption that for each path may be estimated value of the mean and variance delivery time. The appropriate number of production centers is determined by a simple comparison of system efficiency for several realistically possible options. An example of clustering problem solving in the metric of "city blocks" on a directed graph by both criteria is given.