Background: The value of lateral cephalometric radiographs to evaluate the pharyngeal airway is limited because it provided 2-dimensional (2D) images of complex 3-dimensional (3D) anatomic structures. Three dimensional analyses of the airway volumes are required to understand oral and pharyngeal adaptations in mouth breathing and nasal breathing subjects. The aim of this study was to measure the pharyngeal airway volume and the size of the face, then compare between pharyngeal airway volume in mouth breathing and nasal breathing subjects and find the gender difference in each group, also to study the relation between pharyngeal airway volume and the size of the face. Material and Methods: Fifty patients including 28 males and 22 females wit

The human being is a social being and human communication is a fundamental axis in the process of social interaction, and the characteristic of social shyness grows through the interaction of the individual with his environment. Identifying the level of shyness among university students, and identifying the differences in shyness among university students according to specialization (scientific, humanities). In order to achieve the objectives of the research, the researcher prepared a measure of shyness based on Zimbardo's theory, and the components that he identified are the (behavioral, cognitive, and emotional components). The validity and reliability were calculated using the Cronbach's alpha method, reaching (0.94), and the scale in

The research aims at Identifying family dialogue of kindergarten’s parents. 2)  Exploring the fears that kindergarteners suffer from. 3) Identifying family dialogue of kindergarteners’ parents and the fears of their children. To achieve the aim of the research, the researcher designed two scales: one for the family dialogue of kindergarteners’ parents, and the other for the fears of the kindergarten’s child. To identify the relationship between these two elements, the scale subjected to the consultation of a group of specialized expertise in educational and psychological sciences to certify the propriety of the items. The reliability of the scale of the family dialogue recorded (0.85). As for the scale of children’

The breakfast key components of good nutrition and a large proportion of pupils to Ataatnol her breakfast at home and increase the failure rate breakfast increase the child's age research aims to study the importance of breakfast and emphasize the need to contain aggregates of basic food and its relationship to the curriculum daily diet and its impact on the balance of proteins, fats in food daily as well as the effect of some relevant factors such as the mother's level of education and the number of family members and summarized the most important results in that the percentage of 15.6% Neglected children eating breakfast as well as afternoon that Almaah percentages of calories coming from protein and fat at breakfast .....

Gymnastics play from sports games that need to use appropriate methods and strategies that address mental abilities and that let the learner create and think about better performance with the supervision and guidance of the teacher. The researcher has chosen meditative thinking, which is a kind of thinking that needs to be taken care of. It is thinking about the situation in front of the individual, analysing it to his elements and drawing up plans that need to be understood with a view to reaching the results required by the situation and evaluating the results in the light of the plans. The analysis of the situation looks to different elements and look for internal relationships between these elements in this case. The problem is that fem

The importance of this research lies in developing a psychological expenditure scale and its relationship to the passing skills of specialized volleyball players. The research problem focused on psychological expenditure as one of the problems and challenges faced by specialized players and its negative impact, such as poor skill performance, which is reflected in the performance of the player and the team. This weakens the player's self-confidence and concentration and affects the team's performance in tournaments as well as their performance in training. The research aims to develop a psychological expenditure scale, and the researcher used the descriptive approach as it is appropriate for the nature of the research problem. The f

The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes