Факультет інформаційно-аналітичних технологій та менеджменту (ІТМ)

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https://openarchive.nure.ua/handle/document/45

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Перегляд Факультет інформаційно-аналітичних технологій та менеджменту (ІТМ) за Назва

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  • Зображення мініатюри
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    3D Modeling of the Ball Bearing for the Front Axle Knuckle
    (Published by Seventh Sense Research Group, 2018) Rami Matarneh; Sotnik, S.; Lyashenko, V.
    In this work, the questions of ball bearings operation and their constructive features are considered. A 3D model of a detail is created as a ball bearing for for The Front Axle Knuckle. With Solid CAD, a finite-element analysis of the developed detail type is implemented. In the SolidWorks Simulation module, a ball bearing deformation analysis was carried out as a result of the 2000 N impact force. Based on the constructed model and the results of the analysis it was found that the support meets the requirements of strength in its application.
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    A Study of Correlation Ratios for Low- and High-Density Lipoprotein in Comparison with Antioxidant Vitamins A, E, C at Different Levels of Glycosylated Hemoglobin among Type 2 Diabetes Patients
    (WARSE, 2020) Abd Elgadir A. Altoum; Asaad Ma. Babker; Marwan Ismail; Lyashenko, V.
    Diabetes is one of the chronic diseases in which the number of patients increases every year. Moreover, diabetes mellitus is a risk factor for the risk for the development of other diseases. Therefore, the number of studies that address various aspects of the diagnosis and control of the processes of diabetes is increasing. Among such studies, an important place is taken by the analysis of the relationship between low and high density lipoprotein and antioxidant vitamins A, E, C. Such an analysis can be done using various analytical methods. This expands medical diagnostics and treatment options for diseases. The study was based on a sample of 300 patients with type 2 diabetes. For analysis, we used: correlation analysis and the wavelet coherence method. The values of wavelet coherence between low and high density lipoprotein and antioxidant vitamins A, E, C for different levels of glycosylated hemoglobin were obtained. This provides an explanation of the differences in the relationship between low and high density lipoprotein and antioxidant vitamins. Also a more consistent dynamics is observed between antioxidant vitamins A, E, C and HDL, taking into account changes in glycosylated hemoglobin levels. This is a key factor in understanding the greater correlations between antioxidant vitamins A, E, C, and HDL.
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    A Study of New Cycloid Swing Link Speed Reducer by using Algorithmic Design
    (www.ijsr.net, 2015) Drugarin Cornelia Victoria Anghel; M. Ayaz Ahmad; Lyashenko, V.
    The aim of this article is to present a design algorithm for a new modern and high mechanical efficiency cycloid swing link speed reducer. Estimate that the new cycloid swing link speed reducer has and others advantages in comparison with the existing push road reducer such as: strong capacity of anti impact and over load, accessible process technology. We propose an algorithm for kinematics, dynamics and resistance (dimensional) calculus for specific main portent elements. Dimensional design of common elements as: shafts, bearings, carcasses, etc. not offer in the paper.
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    A systematic approach to learning needs analysis
    (BoScience Publisher, 2022) Latynin, M. A.; Melnykov, A. F.; Kobzev, I. V.; Kosenko, A. V.; Kosеnko, V. V.
    The article defines the features of professional training of civil servants in the context of the formation of a new paradigm of state management of labor resources, which provides for ensuring its dependence on factors of the external socioeconomic environment, the orientation of civil servants towards the development of public-private partnerships, the relationship of training with active self-education
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    A Theoretical Interpretation for the Study of Images Processing
    (IJARCSMS, 2015) Putyatin, Y.; Lyashenko, V.; Mohammad Ayaz Ahmad; Lyubchenko, V.; N. Ameer Ahmad
    In the present article and attempt has been made for the study of image processing, which is an important issue in various systems based on the electronic data analysis. This is also necessary for mankind in the age of modern technology, because it is essential to note systems of computer vision which render the indispensable help to the person in various situations and processes demanding special attention and also speed in decision-making. At the same time among variety of different methods and approaches for image processing it is necessary to allocate methodology of image normalization. The essence of such methodology of image processing consists in indemnification of different geometrical distortions of the input image which have been received a result of registration of the investigated image and its presentation on an input of system of the data analysis, in comparison with some reference picture. On the basis of such approach the work considers geometrical interpretation of the analyzed image of object as a basis of use of the device of the group theory.
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    About classification of the methods in design of medical information systems
    (Vancouver, Canada, 2021) Tvoroshenko, I.; Mahomet, A.
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    About one class of the problems of optimal stochastic control of hybrid dynamical systems
    (Econtechmod. An International Quarterly Journal, 2016) Тевяшев, А. Д.; Матвиенко, О. И.
    A new class of the problems of optimal stochastic control of hybrid dynamical systems different from well-known ones by the introduction of additional extreme and probabilistic constraints on the phase variables is studied in the present work. The mathematical formulation and approximate method of solution of the examined class of the problems are presented in this work. The effectiveness of the use of this class of the problems is illustrated on the example of one of the largest water main of Ukraine.
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    About one problem of optimal stochastic control of the modes of operation of water mains
    (Econtechmod. An International Quarterly Journal, 2015) Tevyashev, A.; Matviyenko, O.
    The problem of increasing of the efficiency of operation of the water mains in modern conditions while the transition to a three-tier tariff for the electricity is examined in the present work. An effective method for solving this problem, based on the use of specific features of the water mains as stochastic objects operating in the stochastic environment is offered. The mathematical formulation of the problems of optimal stochastic control of the modes of operation of the water main with probabilistic constraints on the phase variables is presented. A new strategy for the optimal stochastic control of the modes of operation of the water main, the use of which has allowed to develop an effective method for solving the examined problem is proposed in the present work. It is shown that the transition from the classical deterministic problems of control of the modes of operation of the water mains to stochastic ones, provides a significant (up 9%) decrease of financial expenses for the electricity.
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    About the role of testing in process of mobile application development
    (Boston, USA, 2021) Tvoroshenko, I. S.; Kuznetsov, M.
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    Accurate investigation of coupled plasmonic resonances in a chain of silver nanowires
    (IEEE, 2016) Stognii, N. P.; Sakhnenko, N. K.
    This paper presents investigation of plasmonic properties of coupled metal nanowires arranged to form a finite linear chain. Coupled plasmon resonances of such structures embedded into dielectrics with different dielectric permittivity are studied. The main goals of the paper are to validate true potential of a plasmon nanowire-based structure in sensing applications and to reveal optimized configurations with narrowband plasmonic resonances and enhanced sensitivity.
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    Activation of innovative development of industrial enterprises of Ukraine: an actual requirement of the time
    (Іnternational Science Group. Boston, 2020) Соколова, Л. В.; Іванова, В. Б.; Верясова, Г. М.; Курденко, О. В.
  • Немає доступних мініатюр
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    Adaptive Neuro-Fuzzy Methods for Distorted Data Clustering
    (2020) Shafronenko, A. Yu.; Bodyanskiy, Ye. V.; Rudenko, D. A.
    The problem of data sets described by vector-images clustering often occurs in many applications associated with Data Mining [40, 41], when processed vector-image with different levels of probabilities, possibilities or memberships, can belong to more than one class. However, there are situations when the data sets contain missing values. In this situation more effective is to use mathematical apparatus of Computational Intelligence [Rutkowski, 2008] and, first of all artificial neural networks [8], that solve task of restoring the lost observations and modifications of the popular method of fuzzy c-means [22], which solve the problem of clustering without recovery of data. Existing approaches for data processing with missing values [6], are efficient in cases when the massive of the original observations is given in batch form and does not change during the processing. At the same time, there is a wide class of problems in which the data that arrive to the processing, have the form of sequence that is feed in real time as it occurs in the training of Kohonen self-organizing maps [1] or their modifications [2]. In this regard we have introduced [42] the adaptive neuro-fuzzy Kohonen network to solve the problem of clustering data with gaps based on the strategy of partial distances (PDS FCM). However, in situations where the number of such missing values is too big, the strategy of partial distances may be not effective, and therefore it may be necessary, along with the solution of fuzzy clustering simultaneously estimate the missing observations. In this situation, a more efficient is approach that is based on the optimal expansion strategy (OCS FCM) [22]. This chapter is devoted to the task of on-line data clustering using the optimal expansion strategy, adapted to the case when information is processed in a sequential mode, and its volume is not determined in advance.
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    Aggregate  Parametric  Representation  of  Image  Structural  Description in Statistical Classification Methods
    (2022) Gadetska, S.; Gorokhovatskyi, V.; Stiahlyk, N.; Vlasenko, N.
    Finding effective classification solutions based on the study of the processed data nature is one of the important tasks in modern computer vision. Statistical distributions are a perfect tool for presenting and analyzing visual data in image recognition systems. They are especially effective when creating new feature spaces, particularly, by aggregating descriptor sets in some appropriate way, including bits. For this purpose, it is natural to apply the number of criteria designed to compare the distribution parameters of the analyzed samples. The article develops a speed-efficient method of image classification by introducing aggregate statistical features for the composition of the description components. The metric classifier is based on the use of statisticalcriteria to assess the significance of the classification decision. The developed classification method based on the aggregation of the feature image set is implemented; the workability of the proposed classifier is confirmed. On the examples of the application of variants ofthe method for the system of the real images features, its effectiveness was experimentally evaluated.
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    Air object recognition by the normalized contour descriptors
    (ХНУРЕ, 2021) Єсілевський, В. С.; Тевяшев, А. Д.; Колядін, А. В.
    This paper consider research into the methods for recognizing the type of an air object on a digital image acquired from video monitoring system. A method has been proposed that is applied on a feature vector built on the basis of a Fourier transform for the sequence of coordinates of its two-dimensional contour. This makes it easier to solve the classification problem owing to a more compact arrangement of the multidimensional feature vectors for similar air objects. The architecture of an air situation video monitoring system has been suggested, which includes an image preprocessing module and a module of neural network. Preprocessing makes it possible to identify an object’s contour and build a sequence of normalized descriptors, which are partially independent of the spatial position of the object and the contour processing technique. Proposal method is easy in realization and do not require significant computational resources due take into consideration the specificity of recognizing objects in 3 dimensional. This research has shown that the reported results make it easier to train a neural network and reduce the hardware requirements for solve the task of air situation video monitoring.
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    Air Objects Recognition by the Phase Correlation Method
    (Друкарня Мадрид, 2020) Yesilevskyi, V. S.; Tevyashev, A. D.; Koliadin, A.
    The article considers a method for determining the type of an air object on a digital image by comparing it with standard images using the phase correlation method.
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    Algorithmic Research and Application Using the Rayleigh Method
    (www.ijsr.net, 2015) Anghel Drugarin Cornelia Victoria; M. Ayaz Ahmad; N. Ameer Ahamad; Lyashenko, V.
    The aim ofthis article is topresent the general notions and algorithm about power (Rayleigh) method. The solutions for a numerical example are given and the C++ program illustrated the facility ofthis method. Wecan concluded, that the small number of iterations resulted todetermined the equation solutions, indicated us, that the chosen ofpower method isa good decision.
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    An Evolutionary-Based Adaptive Neuro-Fuzzy Expert System as a Family Counselor before Marriage with the Aim of Divorce Rate Reduction
    (2017) Mousavi, Seyed Muhammad Hossein; MiriNezhad, S. Younes; Lyashenko, V.
    Due to the growth of divorce rate in developed and developing countries, and with the aim of reducing this phenomenon, an evolutionary-based Adaptive Neuro-Fuzzy Expert System as a family counselor before marriage is developed. The main goal is to combine evolutionary algorithms with fuzzy logic, and inferring nature inspired results for this kind of natural event (divorce). For validating results, a dataset from a human expert (marriage counselor) has been received, which described thoroughly in section IV in details. This dataset has been trained and tested with different Meta-heuristic optimization algorithms like (ACO, DE, PSO and GA) and neural network training methods like (Hybrid and back-propagation). Error factors like (MSE, RMSE, Error Mean and Error STD) will be calculate for each one of these approaches as validation results. Also, classification results with MLP algorithm, made this paper more detailed. Validation processes returned promising results and opened a way to use this kind of counselor expert system in the absence of human expert conditions. Dream to day which all the children grow up with their original parents.
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    An initial and boundary value electromagnetic problem for plasma sphere
    (ХНУРЕ, 2012) Remayeva, Т.
    The exact expressions for the transformed field caused by a plasma sphere after its instant formation are obtained as a solution of an initial and boundary value electromagnetic problem for the Maxwell’s equations based on the longitudinal and the transverse spherical vector functions.
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    Analysis of Application of Cluster Descriptions in Space of Characteristic Image Features
    (2018) Gorokhovatskyi, V.
    Abstract: Structural image recognition method modifications in space of characteristic features for recognition of computer vision image dataset were investigated. Recognition performance boost is achieved with quantization (clustering) in the space of image characteristic features that form the pattern of the object. Due to the transformation of structural objects descriptions from a set representation to a vector form, the amount of computation might be reduced tens of times. The results of experiments on Leeds Butterfly dataset that confirmed the effectiveness of decision-making systems based on the proposed approach are shown.
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