The aim of this study to identify the effect of using two strategies for active learning ( Jigsaw Strategy & Problems Solving) in learning some balanced beam's skills in artistic gymnastics for women , as well as to identify the best of the three methods (jigsaw strategy , problems solving and the traditional method) in learning some skills balance beam , the research has used the experimental methodology, and the subject included the students of the college of Physical Education and Sports Sciences / University of Baghdad / third grade and by the lot was selected (10) students for each group of groups Search three and The statistical package for social sciences (SPSS) was used means, the standard deviation and the (T.test), the one way a nova and the LSD test. A number of conclusions were reached, the researcher has concluded that using jigsaw strategy, problem solving and the traditional method has a positive effect on learning some balance beam's skills under study. However, his effect varies among the research groups. The experimental group that applied the jigsaw strategy has surpassed the groups , The second was the problem solving strategy and finally the traditional method.
The method of operational matrices is based on the Bernoulli and Shifted Legendre polynomials which is used to solve the Falkner-Skan equation. The nonlinear differential equation converting to a system of nonlinear equations is solved using Mathematica®12, and the approximate solutions are obtained. The efficiency of these methods was studied by calculating the maximum error remainder ( ), and it was found that their efficiency increases as increases. Moreover, the obtained approximate solutions are compared with the numerical solution obtained by the fourth-order Runge-Kutta method (RK4), which gives a good agreement.
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The aim of this research is to find out the influence of Daniel's model on the skills of the twenty-first century among the students of the scientific-fifth grade at the secondary and preparatory government morning schools for the academic year 2022- 2023. Two groups were chosen out of five groups for the fifth-scientific grade, one of which represents the experimental group that is taught by the Daniel model, and the other is the control group that is taught in the traditional method. The equivalence of the two research groups was verified with a set of variables. As for the research tool, a scale was developed by the researchers for the skills of the twenty-first century, in which they adopted the framework of the Partnership Organizat
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Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this
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هدفت الدراسة الى التعرف على درجة اتخاذ القرار وعلاقتها ببعض المهارات الأساسية الهجومية بكرة السلة للطالبات ، اذ يعد اتخاذ القرار قدرة الفرد على التوصل لحل مشكلة اعتراضية أو موقف محير، وذلك باختيار حل من البدائل الموجودة أو المبتكرة، وهذا الاختيار يعتمد على المعلومات التي جمعها الفرد حول المشكلة وعلى القيم والعادات والخبرة والتعليم والمهارات الفردية وتمتاز لعبة كرة السلة بوجود الكثير من المواقف المتغ
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The paper include study the effect thickness of the polymeric sample which is manufactured by thermo press way. The sample was used as an active tunable R6G laser media. The remarks show that, when the thickness of the samples is increased, with the same concentration, the spectrum will shift towards the short wavelength, & the quantum fluorescence yield will increased. The best result we obtained for the quantum fluorescence yield is (0.68) at the sample, with thickness (0.304mm) in Ethanol solvent, while when we used the Pure Water as a solvent, we found that the best quantum fluorescence yield is (0.63) at (0.18mm) thickness of the sample.
The paper include studies the effect of solvent of dye doped in polymeric laser sample which manufactured in primo press way, which is used as an active (R6G) tunable dye lasers. The remarks show that, when the viscosity of the solvent (from Pure Water to Ethanol), for the same concentration and thickness of the performance polymeric sample is increased, the absorption spectrum is shifts towards the long wave length (red shift), & towards short wave length (blue shift) for fluorescence spectrum, also increased the quantum fluorescence yield. The best result we obtained for the quantum fluorescence yield is (0.882) with thickness (0.25mm) in Ethanol solvent in concentration (2*10-3mole/liter), while when we used the Pure Water as a solvent,
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The study aimed to prepare a measure of metacognitive thinking commensurate with learning the skill, preparing educational units using the Claus Meyer model for metacognitive thinking, and learning the skill of defending the court in volleyball. To identify the effect of educational units using the model (and Claus Meyer) for metacognitive thinking and learning the skill of defending the court in volleyball. The two researchers used the experimental approach with the design of the experimental and control groups.The research community consisted of students of the second stage / College of Physical Education and Sports Sciences / University of Baghdad for the academic year 2021-2022, whose number is (385) st
... Show MoreThe convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.
The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA
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