God sent the Prophet Muhammad as a teacher and promising harbinger {that is sent to the illiterate messenger reciting to them His signs and purifies them and teaches them the Book and Wisdom} [Friday: 2]; the wisdom of Baos Prophet him peace be and am back to teach people, - Education and therefore his life was very rich educational tactics And has passed the Prophet in different circumstances and conditions that can be experienced by a teacher or educator in any time, anywhere; there is no case of going through the educator or teacher only finds the same or similar or likened to, or close to it in the life of the Prophet peace be upon him Prophet has lived God's peace be upon his strengths and weaknesses, victory and defeat, he lived or

This work falls into a two sections, and a conclusion. The first section
presents the problem of the study, its importance, methodology, and review of
literature. The poem of “?araaka ؟asiyya dam؟’ (I Found You a Tear-Refractory)
for Abi-Firaas Al-Hamdani, represents the main code of the study through which
the two researchers try to approach the stylistic and psychological studies. To
accomplish such an approach, they try to link between a group of the poet’s
psychological characteristics and another group of prominent stylistic phenomena
found in the poem. The conclusion contains the main results the two researchers
have arrived at.

Introduction: Elite football performance hinges on rapid tactical decision-making under physical and cognitive strain. While peripheral fatigue’s effects on motor output are well documented, the neurophysiological markers of mental fatigue and their impact on in-game decision making remain underexplored. Objective: To determine how EEG-derived central fatigue indices—frontal theta power and the theta/alpha ratio—relate to tactical decision accuracy and speed in elite football players. Methodology: Twenty male national-level footballers (age 22.4 ± 2.1 years; ≥ 5 years’ experience) completed the Yo-Yo Intermittent Recovery Test Level 1 while wearing an 8-channel dry-electrode frontal EEG headset. Frontal theta

The aim of this research is to identify the strengths and weaknesses of organizational health in the Iraqi Central Handball Federation from the point of view of those who manage the implementation of the annual curriculum, and adopt a descriptive approach in the method of studying the case. This is based on a sample of administrators of the Iraqi Handball Federation curriculum [trainers, governors, members, president, the 138 members of the Central Federation's Administrative Authority, the President, members of the sub-federations of the sports market (2021/2022) selected deliberately by 100% and then divided into statistical analysis sample (30), reconnaissance sample (10), and application sample (98)]. The regulatory health questionnaire

Ration power plants, to generate power, have become common worldwide. One such one is the steam power plant. In such plants, various moving parts of heavy machines generate a lot of noise. Operators are subjected to high levels of noise. High noise level exposure leads to psychological as well physiological problems; different kinds of ill effects. It results in deteriorated work efficiency, although the exact nature of work performance is still unknown. To predict work efficiency deterioration, neuro-fuzzy tools are being used in research. It has been established that a neuro-fuzzy computing system helps in identification and analysis of fuzzy models. The last decade has seen substantial growth in development of various neuro-fuzzy systems

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

KE Sharquie, SA Al Mashhadani, AA Noaimi, RK Al-Hayani, SA Shubber, Iraqi Postgraduate Medical Journal, 2012 - Cited by 1

KE Sharquie, SA Al-Mashhadani, A A Noaimi, RK Al-Hayani, SA Shubber, Iraqi Journal of Community Medicine, 2017 - Cited by 1