The research problem arose from the researchers’ sense of the importance of Digital Intelligence (DI), as it is a basic requirement to help students engage in the digital world and be disciplined in using technology and digital techniques, as students’ ideas are sufficiently susceptible to influence at this stage in light of modern technology. The research aims to determine the level of DI among university students using Artificial Intelligence (AI) techniques. To verify this, the researchers built a measure of DI. The measure in its final form consisted of (24) items distributed among (8) main skills, and the validity and reliability of the tool were confirmed. It was applied to a sample of 139 male and female students who were chosen

Surface modeling utilizing Bezier technique is one of the more important tool in computer aided geometric design (CAD). The aim of this work is to design and implement multi-patches Bezier free-form surface. The technique has an effective contribution in technology domains and in ships, aircrafts, and cars industry, moreover for its wide utilization in making the molds. This work is includes the synthesis of these patches in a method that is allow the participation of these control point for the merge of the patches, and the confluence of patches at similar degree sides due to degree variation per patch.  The model has been implemented to represent the surface. The interior data of the desired surfaces designed by M

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

The effect of 5555 strategy on reading comprehension among 4th preparatory students Assist. Prof. Dr. Hassan Khilbas Hammadi College of Education Ibn Rushd – The University of Baghdad Assistant Lecturer. Waleed Khaled Talib Directorate – General For Education Province Of AL - Anbar The purpose of study is to identify the effect of 5555 strategy on reading comprehension among 4th preparatory students. To do this, null hypothesis was postulated. The author hypothesize that there is no a statistically significant difference at (0.05) level between experimental group's scores who study reading comprehension subject following the 5555 strategy and control group's scores who study the same subject following the traditional method in readin

هدفت هذه الدراسة إلى التعرف على دور نظام معلومات الموارد البشرية في تحقيق متطلبات عملية تقويم أداء أعضاء الهيئة التدريسية في كلية الإدارة والاقتصاد/جامعة بغداد. وقد تحددت مشكلة الدراسة في عدد من التساؤلات، أهمها: ما تأثير كل متغير من متغيرات نظام معلومات الموارد البشرية في عملية تقويم أداء أعضاء الهيئة التدريسية في الكلية المبحوثة؟ وما تأثير متغيرات نظام معلومات الموارد البشرية مجتمعة في عملية تقويم الأداء

The present study aims to develop and apply the unrealistic optimism scale among high school students. The researcher has designed a scale of (38) paragraphs to measure the unrealistic optimism. A sample of (200) male and female students were chosen randomly to collect the needed data. The study found that the unrealistic scale of optimism has good psychometric characteristics. The research sample has a high level of التفاؤل غير الواقعي لدى عينة البحث unrealistic optimism. There is a statistically significant difference between male and female in the unrealistic optimism in favor of the male students. Finally, there is a statistically significant difference between students in the fourth and sixth gra

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o