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Process of 3D printing in online education
(Національний технічний університет "Харківський політехнічний інститут", 2022) Haidar, Nataliia; Zavolodko, Ganna; Pustovoitov, Pavlo
The subject of the review is methodology of the subsystem verification and printing 3D-model online learning system mixed type. To do this, a review of analogues, technologies, stages of printing were identified. Due to the development of technology, the educational process is being transformed. Education uses blended learning, part of which is distance learning. The object of research is use of additive technologies, which can make the learning process more motivating. Thus, if in distance education there is an opportunity to develop a 3D-model online, check it for fidelity, send the model to print, it optimizes the learning process. The aim is to design with IP topics that uses the additive technologies in the educational process. Methods used: IDEF-diagram describing the function of the system; authentication rules, verification of 3D-models, sending the model to print, selecting a device online, and basic screen forms. Conclusions. The development of innovative thinking in higher education students should become a priority of modern higher education, and the introduction of new elements in modern education is inevitable. And given the development of 3D-printing technologies, additive technologies are the most promising for the use of visualization in online and mixed teaching.
The Speed Calculating Increasing Method of the Markov Model Network Node
(Національний технічний університет "Харківський політехнічний інститут", 2021) Pustovoitov, Pavlo; Okhrimenko, Maxim; Voronets, Vitalii; Udalov, Dmitry
The subject of this research is the image classification methods based on a set of key points descriptors. The goal is to increase the performance of classification methods, in particular, to improve the time characteristics of classification by introducing hashing tools for reference data representation. Methods used: ORB detector and descriptors, data hashing tools, search methods in data arrays, metrics-based apparatus for determining the relevance of vectors, software modeling. The obtained results: developed an effective method of image classification based on the introduction of high-speed search using hash structures, which speeds up the calculation dozens of times; the classification time for the considered experimental descriptions increases linearly with decreasing number of hashes; the minimum metric value limit choice on setting the class for object descriptors significantly affects the accuracy of classification; the choice of such limit can be optimized for fixed samples databases; the experimentally achieved accuracy of classification indicates the efficiency of the proposed method based on data hashing. The practical significance of the work is - the classification model’s synthesis in the hash data representations space, efficiency proof of the proposed classifiers modifications on image examples, development of applied software models implementing the proposed classification methods in computer vision systems.
Mathematical model of server requests intensity description
(Національний технічний університет "Харківський політехнічний інститут", 2020) Pustovoitov, Pavlo; Kostyk, Kateryna; Kompaniiets, Volodimir; Voronets, Vitalii; Haidar, Hasan
The paper is devoted to the mathematical model development of non-stationary flow of requests from clients to the database in order to modulate the quality of service. The mathematical model of the queries number fluctuations to the database has the form of a regression equation and allows more accurate modeling of the connections pool size in the servlet. Connection pool is a pattern that helps to reduce responding time for queries to databases. To another hand the extra used memory wasting server resources. The task of calculating the optimal connection pool size could be solved by verity of mathematical apparatuses that demand information about intensity of stationary incoming queries flow. It is known, that real incoming queries flow is non-stationary. In the paper was suggested mathematical model of flow intensity fluctuations with daily and hourly harmonic vibrations. Statistics analyses of model adequacy was made, homogeneity of variances is checked, the significance of the coefficients of the regression equation was estimated. The obtained mathematical model describes fluctuations in the intensity of clients' requests to the servlet during the week. The mathematical model can be used to predict the load on the server or to build a simulation model of the query service system. The adequacy of the model is checked, the homogeneity of variances is checked, the significance of the coefficients of the regression equation is estimated, the adequacy of the regression equation is checked, the analysis of the autocorrelation of the residues is carried out. The results obtained in the article give further development for modeling process technologies in the field of information systems and can be used to calculate the load on the server with a non-stationary flow of requests from clients to the database.

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