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Публікація 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.Публікація 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.Публікація 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.Публікація A Theoretical Interpretation for the Study of Images Processing(IJARCSMS, 2015) Putyatin, Y.; Lyashenko, V.; Mohammad Ayaz Ahmad; Lyubchenko, V.; N. Ameer AhmadIn 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.Публікація About classification of the methods in design of medical information systems(Vancouver, Canada, 2021) Tvoroshenko, I.; Mahomet, A.Публікація About the issue of optimization the performance of the server part of the information system(2024) Karakonstantyn, D.; Tvoroshenko, I.The research is devoted to the analysis of modern methods of optimizing the performance of the server part of information systems, which help to increase the speed of query processing [1-6] and the efficiency of resource use [7-10]. The advantages and disadvantages of such approaches as data caching, asymmetric multithreading, and database query optimization are analyzed. It is established that these methods allow flexible adaptation of the server part to the specific requirements and complexities of the project, ensuring increased performance and efficiency of the systemПублікація About the role of testing in process of mobile application development(Boston, USA, 2021) Tvoroshenko, I. S.; Kuznetsov, M.Публікація Accelerated filtration of ultrasound images(Publishing House «Caravela», 2024) Pupchenko, D.; Gorokhovatskyi, V.The aim of this work is to create a high-speed algorithm for filtering ultrasound images that has the added property of edge preservation. The performance of popular methods is reviewed. A method of enhancing the existing method based on the decomposition of calculations into a one-dimensional space is proposed. The proposed solution significantly reduces computational costs without losing the efficacy of noise filtering. The overall effectiveness of ultrasound image filtering in terms of performance and quality has been experimentally confirmed.Публікація Accelerating Image Classification based on a Model for Estimating Descriptor-to-Class Distance(2023) Gorokhovatskyi, V.; Gadetska, S.; Stiahlyk, N.The article describes a method of image classification based on the estimation of the distance to the etalon class. The implementation of estimates gives a significant gain in classification speed compared to linear search while maintaining a decent level of accuracy. The methodology is based on the use of the triangle inequality for images given by a set of binary vectors as descriptors of the image key points. The evaluation is applied to the "object descriptor – etalon" classification method, which is based on the descriptor voting procedure. An analysis of evaluation options is carried out using the parameters of the etalon sets in the form of a medoid and the closest or farthest points from it. The gain in classification time compared to the traditional method proportionally depends on the number of descriptors in the etalon description. Software simulation of classifiers with the implementation of evaluation shows a gain in speed of 350-450 times for the description of 500 descriptors while maintaining one hundred percent classification accuracy on the training set of similar NFT images. A control sample experiment shows that the classifier with estimation can respond better to image details compared to the traditional method.Публікація 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.Публікація 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.Публікація 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.Публікація An effective method for transforming an image description into a compact vector for classification(Publishing House «Caravela», 2024) Gorokhovatskyi, V.; Tvoroshenko, I.The work develops method to solve a fundamental problem in computer vision: image recognition of visual objects. Based on the implementation of the distance matrix model, it was possible to form effective integrated features in the form of one-dimensional data distributions and vectors for the sum of the matrix columns, which reduced computational costs without losing the effectiveness of classification on the training data sample. The efficiency of image classification was experimentally evaluated using software modeling.Публікація 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.Публікація 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.Публікація Публікація Analysis of existing methods for searching object in the video stream(2020) Tvoroshenko, I.; Zarivchatskyi, R.Публікація Analysis of existing methods of searching images in databases(2022) Yevtushenko, V.Публікація Analysis of Features and Possibilities of Bank Functioning Efficiency Based on the Method of Stochastic Frontiers(Institute of Information Theories and Applications, 2013) Kuzemin, O.; Lyashenko, V.Given paper shows the importance of analyzing the banks performance in the process of their operation and development. The place and the role of researching of stochastic frontiers method for the banks performance assessment have been defined. The features and the possibility of assessing efficiency of banks activity with the usage of the of the stochastic frontiersmethod have been studied. The examples of performance assessment of banks activity in the aspect of the credit extension have been given. The expediency of the consideration of the multiple stochastic frontiers in the assessment of the effectiveness of the banks activities has been proved.Публікація Analysis of methods for detecting and classifying the likeness of human features(2021) Tvoroshenko, I.; Koriakin, I.