The objective of the study was to identify the effect of the use of the Colb model for the students of the third stage in the College of Physical Education and Sports Sciences, University of Baghdad,As well as to identify the differences between the research groups in the remote tests in learning skills using the model Colb.The researcher used the experimental method and included the sample of the research on the students of the third stage in the College of Physical Education and Sports Science / University of Baghdad by drawing lots, the third division (j) was chosen to represent the experimental group,And the third division (c) to represent the control groupafter the distribution of the sample splitting measure according to the Colb model, the sample was divided into four groups of experimental groups (third (j), 7 (female students), 6 (female students) and third group (c) (7) Students).The researcher used statistical package for social sciences (spss) to address the results of his research,The researcher reached a number of conclusions, the most important of which is that the Colb method has a positive effect on learning some of the technical skills of the gymnastic as well as the positive effect of the style followed by the school material, but the preference was for the Colb method
Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.
In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.
The longitudinal balanced data profile was compiled into subgroup
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This study was achieved to investigate the accumulation of some heavy metals included: Cadmium, Lead and Nickel in the tissues (gill, intestine, liver, muscles and skin) of Silurus triostegus Heckel, 1843 (Siluriformes, Siluridae) and its larval stage of the nematode Contracaecum sp. (Rhabditida, Anisakidae). As well as to assess the infection patterns of Contracaecum among S. triostegus specimens which were purchased fresh from the local market in Baghdad. One hundred and nine nematodes specimens in larval stage were recovered from the fish host; the overall prevalence of Contracaecum sp. was 38.6%. The sex of the host was not significantly (P ˃ 0.05) associated with the infection of this nematode. Results showed that the ov
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This study was achieved to investigate the accumulation of some heavy metals included: Cadmium, Lead and Nickel in the tissues (gill, intestine, liver, muscles and skin) of Silurus triostegus Heckel, 1843 (Siluriformes, Siluridae) and its larval stage of the nematode Contracaecum sp. (Rhabditida, Anisakidae). As well as to assess the infection patterns of Contracaecum among S. triostegus specimens which were purchased fresh from the local market in Baghdad. One hundred and nine nematodes specimens in larval stage were recovered from the fish host; the overall prevalence of Contracaecum sp. was 38.6%. The sex of the host was not significantly (P ˃ 0.05) associated with the infection of this nematode.
Results showed that the overall me
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
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Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated
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