The purpose of this paper is to identify the statistical indicators of the searched variables and identify the relationship between the cognitive learning outcome and the performance of the two mastering skills by parallel spherical standing and equilibrium on the balance beam. And the identification of the percentage of the cognitive learning outcome contribution to the performance of the two mastering skills by parallel spherical standing and the equilibrium on the balance beam. The two researchers used the descriptive approach in the survey method and the correlational relations, being the most appropriate to the nature of the research problem. The research community for the second stage students in the College of Physical Education and Sports Sciences for Woman for the academic year (2020-2021) was determined, and their number was (104) students. The exploratory and main research sample was chosen randomly, as the exploratory sample reached (10) students and the main sample reached (40) students with a rate of (38,461%). The conclusions came that the cognitive learning outcome has a positive role in the performance of the two mastery skills by parallel spherical standing and the equilibrium on the balance beam, as well as the cognitive learning outcome contributed well in managing the two mastery skills by parallel spherical standing and the equilibrium on the balance beam. The two researchers recommend it is necessary for female teachers to pay attention to the subject of artistic gymnastics with the outcome of cognitive learning during the educational units because it has an effective and influential role in mastering the performance of the two mastery skills by parallel spherical standing and the equilibrium on the balance beam, and the cognitive learning outcome must be evaluated continuously after completion of Educational units, and testing of motor learning strategies and their methods by the teachers that enable the learner through the acquisition of the intended learning outcomes.
The elbow joint is one of the important and mobile joints in a way that allows it to perform its functions. The injury occurs when the joint tendon and arm muscles are subjected to repeated partial ruptures as a result of excessive and repetitive work, as well as the patient not being subjected to correct rehabilitation programs, and only rest. From here, the researchers decided to study this problem by preparing rehabilitation exercises accompanying ultrasound and assessing their impact on the rehabilitation of the elbow joint. The sample included male patients aged 30-40 years, and the tests were determined, which included testing the range of motion of the elbow joint from the flexion position and the rotation outward position, the mu
... Show MoreAryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that regulates T cell function. The aim of this study was to investigate the effects of AhR ligands, 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), and 6-Formylindolo[3,2-b]carbazole (FICZ), on gut-associated microbiota and T cell responses during delayed-type hypersensitivity (DTH) reaction induced by methylated bovine serum albumin (mBSA) in a mouse model. Mice with DTH showed significant changes in gut microbiota including an increased abundance of
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy
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The production companies in the Iraqi industry environment facing many of the problems related to the management of inventory and control In particular in determining the quantities inventory that should be hold it. Because these companies adoption on personal experience and some simple mathematical methods which lead to the identification of inappropriate quantities of inventory.
This research aims to identify the economic quantity of production and purchase for the Pepsi can 330ml and essential components in Baghdad soft drinks Company in an environment dominated by cases of non ensure and High fluctuating as a result of fluctuating demand volumes and costs ass
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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 MorePatients 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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