The research study is important since it establishes predicted rates for various nervous system functional indicators.In terms of performing the skill of Dribbling in basketball for young players in Baghdad Governorate in order to reach scientific results that serve researchers, coaches, and players uniformly. The study's goal is to create predictive equations for specific functional indicators of the nervous system in relation to the Dribbling skill performance of young basketball players in Baghdad Governorate. The researchers used a descriptive approach with a survey method on (8) youth basketball league clubs in Baghdad Governorate for the 2022-2023 sports season, totaling (96) players . Three tests were used to measure the nervous sy

Abstract

The aim of the research is to develop specific skills of 21 century, one schedule, renewable: (sex, years of experience, academic degree) from the viewpoint of the research sample. The descriptive tool was used to collect information for research purposes. It was applied to a sample of (339) male and female teachers in Al-Ardhah governorate schools to teach Jazan. The application was carried out in the second semester of the year 1442 AH. The research concluded with a set of results, the most important of which are: the approval of the sample members to a large extent on the expressions of the role of school leaders in the practice of developing male and female teachers in acquiring these three skills fr

The aim of this study was to identify the level of critical thinking skills among fourth-grade middle school students and to determine the performance level of the underhand volleyball pass, with the assumption that there is a positive relationship between critical thinking and skill performance. The study population included 281 students from Basra Preparatory School for Girls under the Second Baghdad Education Directorate for the 2024/2025 academic year, of whom 275 students were intentionally selected as the research sample (97.865% of the population). The experimental procedure involved applying a critical thinking scale and a technical performance test for the underhand pass on 25 students per day over 11 days, from February 9

The study highlighted the transformation of value systems and educational patterns between past and present, especially with the introduction of modern variables and means, such as mobile phones, the internet, social media, and others. These factors have contributed both positively and negatively to the study. The study highlights the integral role of the school in collaboration with the family in guiding and educating children. It also emphasizes the active role of the school in developing students' abilities and skills, either attracting them to school or vice versa. This includes an examination of the essential skills required in education and their role in achieving a state of psychological well-being and systematically developing child

The reform process is a dynamic process going on, especially the administrative and financial reform, which contributes to the work and directing operations towards success and continuous development, which requires determining the validity and the responsibility and the rights and duties of all officials in the school settings (within the formations educational institutions) for the purpose of reducing the administrative and financial corruption, and then ensure management efficient and effective way by taking advantage of the physical, financial and human resources available to achieve the greatest benefit at the lowest cost to the fact that the follow-up performance on an ongoing basis in accordance with the specific of powers

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

Optimum perforation location selection is an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magni

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat