The aim of this study was to identify the effectiveness of using generative learning model in learning kinetic series on rings and horizontal bar in artistic gymnastics for men ,Also, the two groups were better in learning the two series of movements on the rings and horizontal bar . The experimental method was used to design two parallel groups with pretested and posttest .The sample included third graders at the College of Physical Education and Sports Sciences - University of Baghdad ,The third class (d) was chosen to represent the control group that applied the curriculum in the college, with (12) students per group. After conducting the tribal tests, the main experiment was carried out for (8) weeks at the rate of two units per week divided into (4) weeks to learn the kinetic chain on the rings and (4) weeks learning the kinetic chain on the device of mind and after the completion of the experiment was carried out remote tests, used the statistical package of social sciences (spss) Results The research included (T. test) of the corresponding samples and (T. test) for asymmetric samples. A number of conclusions were reached, the most important of which were the following: - The generative learning model of the applied learning applied to the experimental group and the method applied to the control group had an effect Was effective in learning the kinetic chain under study, but at varying rates was in favor of the generative learning model.
HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023
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It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the
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QJ Rashid, IH Abdul-Abbas, MR Younus, PalArch's Journal of Archaeology of Egypt/Egyptology, 2021 - Cited by 4
In this paper, compared eight methods for generating the initial value and the impact of these methods to estimate the parameter of a autoregressive model, as was the use of three of the most popular methods to estimate the model and the most commonly used by researchers MLL method, Barg method and the least squares method and that using the method of simulation model first order autoregressive through the design of a number of simulation experiments and the different sizes of the samples.
Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed
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