ABSTRACT The importance and objectives of the study were an attempt to understand the methodology of disseminating radical thought and the reasons of social acceptability that make young people embrace this thought. It also sheds light on the impact of this phenomenon on the regional role of Egypt and examines the strategic means and standards that the Egyptian state focuses on in immunization and prevention of extremism.

The current research aims to identify the level of both psychological comfort and job performance among a sample of high school teachers for the academic year (2019-2020). The researcher has built two tools to measure psychological comfort, and one to measure job performance. The researcher applied the two scales to a random stratified sample of (100) male and female teachers. The results showed a low level of feeling with psychological comfort among secondary school teachers and a good level of sense of job performance. There is no statistically significant difference in the level of psychological comfort according to gender. There is a significant difference in psychological comfort according to the variable of the length of service in

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

An experiment in the semester, the second semester of the academic year (2022-2023), and the data used was not processed (the second test for two independent, inaccurate samples, the Bermon correlation coefficient, and the Spearman correlation coefficient), and the following results were reached: There is a statistically significant difference at the level of ( 0) average, 05) between the third grade who studied the plan for asking cluster questions, and between the average of those who studied the special feature according to the traditional method of selecting achievement, and enjoyed completing the specialization, choosing the experimental group, because the strategy of asking cluster questions is one of the externalities that... Lear

Online learning is not a new concept in education, but it has been used extensively since the Covid-19 pandemic and is still in use now. Every student in the world has gone through this learning process from the primary to the college levels, with both teachers and students conducting instruction online (at home). The goal of the current study is to investigate college students’ attitudes towards online learning. To accomplish the goal of the current study, a questionnaire is developed and adjusted before being administered to a sample of 155 students. Additionally, validity and reliability are attained. Some conclusions, recommendations, and suggestions are offered in the end.

The current study aims to identify the effect of guided visualization strategy in developing the visual perception among kindergarteners. The experimental design was used; pre-post test. A total of (32) boy and girl ranging 5 to 6 years old were selected from al-Rabeea’ kindergarten, directorate of al-karkh 2 / Baghdad. The sample divided into equal two group (16) boy and girl of each one. al-Talaqany’s (2016) visual perception skills test among kindergarteners was adopted to collect the required data. The collected data had processed based on (gender, pre-post test, and age). To achieve the objectives of the study; the researcher set up series of sessions that addressed the guided visualization strategy among kindergarteners compose

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye