The Islamic religion approach Rabbani urges and seeks to bring happiness to people, as Allah says: ((We sent thee not all people glad tidings and a warner, but most people do not know)) Spa: State 28
   Islam looks at the concept of educational values ​​through positive behavior derived emerging through formal and informal education. The Islamic approach works on the basis of a systematic and clear rule in the form of an integrated system includes multiple areas. As the lead actor role as the desired position.
  Although 

This study aimed to assess orthodontic postgraduate students’ use of social media during the COVID-19 lockdown. Ninety-four postgraduate students (67 master’s students and 27 doctoral students) were enrolled in the study and asked to fill in an online questionnaire by answering questions regarding their use of social media during the COVID-19 lockdown. The frequency distributions and percentages were calculated using SPSS software. The results showed that 99% of the students used social media. The most frequently used type of social media was Facebook, 94%, followed by YouTube, 78%, and Instagram, 65%, while Twitter and Linkedin were used less, and no one used Blogger. About 63% of the students used elements of social media to l

The research discusses two variables are important, orientation marketing and quality of service, and that the purpose of the research is to see whether the telecom companies applied orientation marketing or not and to what extent is keen to apply it to suit the Iraqi environment as it has been applied research in kork Telecom company and Asia Cell Telecom are sectors service job in the business sector in Iraq, The information was obtained through the design of the questionnaire compatible runway Likert, and distribution (92) questionnaire, which (50) for the company Korek Telecom and (42) of the Asia-Cell, research population sample included a number of staff in the departments and units in the two companies, it has been support

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 convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

The research aimed to study the job satisfaction of the staff of the Federal board of supreme Audit and its relation to the effectiveness of their performance, The questionnaire was adopted as a main tool in the collection of data and information from a random sample of (54) employees of the Federal board of supreme Audit. In light of this, the data were collected and analyzed and the hypotheses were tested using the statistical program (SPSS).

The researchers reached a number of conclusions, the most important of which were: (1) the respondents' response to the variables of job satisfaction and the effectiveness of the performance were medium; (2) there was a significant relationship between job satisfaction and performance effe

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims