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.
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This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa
... Show MoreThe COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system
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Air pollution is one of the complex problems plaguing the environment at the present time
as a result of many liberation of gases, vapors and fumes of fuels and chemicals resulting
from industrial activities . It should be noted that there are some elements of the heavy
(Heavy Metals), including toxic in the air, with different concentrations in the air depending
on the nature of the area, for example be in rural areas is lower than in cities or industrial
areas as measured parts million (ppm ) or parts per billion (ppb). Some of these important
elements in the physiological processes and enzymatic organisms but become toxic and
Qatlhand-increase Tercisahaan the permissible limits Bhave nature ,The air contaminant
Air pollution is one of the complex problems plaguing the environment at the present time
as a result of many liberation of gases, vapors and fumes of fuels and chemicals resulting
from industrial activities . It should be noted that there are some elements of the heavy (Heavy
Metals), including toxic in the air, with different concentrations in the air depending on the
nature of the area, for example be in rural areas is lower than in cities or industrial areas as
measured parts million (ppm ) or parts per billion (ppb). Some of these important elements in
the physiological processes and enzymatic organisms but become toxic and Qatlhand-increase
Tercisahaan the permissible limits Bhave nature ,The air contaminant co
Online examination is an integral and vital component of online learning. Student authentication is going to be widely seen when one of these major challenges within the online assessment. This study aims to investigate potential threats to student authentication in the online examinations. Adopting cheating in E-learning in a university of Iraq brings essential security issues for e-exam . In this document, these analysts suggested a model making use of a quantitative research style to confirm the suggested aspects and create this relationship between these. The major elements that might impact universities to adopt cheating electronics were declared as Educational methods, Organizational methods, Teaching methods, Technical meth
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In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A
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