This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

The current study aimed to reveal the role of the high school (boys) in the Governorate of Qurayyat (KSA) in promoting intellectual security of students, and whether there were differences in the estimates of the study sample due to the variables; the current position, academic qualification, teaching specialization and years of experience. This study was conducted by applying the analytical descriptive method, and used questionnaire as a tool for data collection. The survey consisted of (44) ite

نحو تعزيز المشاركة السياسية للطالبات الجامعيات الفلسطينيات

   To investigate the research objectives, the researchers put the following hypothesis:

There was no statistically significant difference at the level of (0.05) between the average score of the students of the experimental group who studied the language of rhetoric according to model of learning method, and the average score of the students of the control group who studied the same article in the traditional way acquiring rhetorical concept.    The researchers relied on the experimental design with the partial setting of the post-test, which depends on the experimental group that is taught using the model of the learning method, and the control group taught using the traditional method.   

The current study is considered a field study to measure the level of satisfaction of the academic programs of Media Masters students. That was accomplished through surveying the attitudes of the students who are enrolled in the faculties of media at the following universities: (Petra University, The Middle East University (MEU), and Al-Yarmouk University). Those students were enrolled in the master’s program within the formal educational system during the second semester of the academic year (2015 – 2016). This survey aims to identify the services, facilities and academic programs provided by the concerned faculties. It, also, aims to identify the public relations, administrative, educational and services aspects of those faculties.

This Study Aimed to Recognize the Self-Efficacy Level Among Musically Talented Students the sample of this study consisted of (85) Musically smart students male and female students in Irbid governorate, of the analytical descriptive method ، and the Self-Efficacy scale were used, and the results indicated the following:
-The Self-Efficacy level among Musically smart students was high.
-There are no statistically significant differences (α ≥ 0.05)due to the impact of gender in a the total degree .
-There are no statistically significant differences (α=0.05) due to the impact of stage in a the total degree.

This research aims to identify the level of Voluntary work among university students, and explore the statistical differences of voluntary work among students due the gender and major. A total of (400) male and female student from morning study were selected as a sample to achieve the research's objectives. Al-Malaki (2010) scale was adopted to collect the required data. The results revealed that men take massive part in voluntary work than women, and students of human sciences showed significant differences than those of other majors.