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

In this study, we attempt to provide healthcare service to the pilgrims. This study describes how a multimedia courseware can be used in making the pilgrims aware of the common diseases that are present in Saudi Arabia during the pilgrimage. The multimedia courseware will also be used in providing some information about the symptoms of these diseases, and how each of them can be treated. The multimedia courseware contains a virtual representation of a hospital, some videos of actual cases of patients, and authentic learning activities intended to enhance health competencies during the pilgrimage. An examination of the courseware was conducted so as to study the manner in which the elements of the courseware are applied in real-time learn

In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

The study aimed to evaluate educational programs efficiency in applying the best educational practices to educate students from the dangers of indecent behaviors, in line with higher education policy and the appropriateness of educational program dimensions to spread awareness among students to not fall into the indecent behaviors clutches. The study adopted the inductive exploratory approach through structural equation modeling and the descriptive analysis of the collected data from randomly selected sample (n=385) from educational academics at Northern Border University in the Saudi Arabia using a specially designed survey tool to meet study purposes to evaluate dimensions of teaching methods, evaluation tools, training courses, course

حظيت عدد من الشخصيات التاريخية ممن كان لها أثر واضح المعالم في تطور النظام الإداري والسياسي للإمبراطورية المغولية، بأهتمام عدد لا بأس به من الباحثين.

يختبر البحث الحالي علاقة الأثر والارتباط بين إدارة المعرفة التنظيمية (المتمثلة قيادة المعرفة، تنظيم المعرفة، عمليات المعرفة، ثقافة المعرفة، تطبيق المعرفة، تقاسم المعرفة) ومتغير (رأس مال الزبون) في مجموعة من المصارف الأهلية في محافظة النجف إذ تمثلت مشكلة الدراسة بمدى دور إدارة المعرفة في هذه المصارف فضلاً عن الزبائن الذين يتعاملون معها، وقد استخدمت استمارة الاستبيان كأداة رئيسة لجمع البيانات إذ تم تو

تهدف هذه الدراسة إلى معرفة الفرق في التحصيل الدراسي في الكيمياء والاتجاه نحو العلوم بين طلاب التخصص العلمي وطلاب التخصص الصناعي الصف الأول كلية التربية ابن الهيثم، كذلك تهدف الدراسة إلى معرفة العلاقة بين التحصيل الدراسي في الكيمياء ودرجات اختبار نهاية الفصل في الكيمياء، والمعدل التراكمي بعد أخذ المقرر الدراسي والاتجاه نحو العلوم بالنسبة لطلاب التخصص العلمي وطلاب التخصص الصناعي.

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<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

يناقش البحث المقومات المادية والمجتمعية والموضوعية للدور الاقليمي العراقي بعد العام 2010 والفرص المتاحة والقيود التي تحد منه والافاق المستقبلية لهذا الدور في ظل بيئة اقليمية تسودها منظومات تحالف متناقضة في الاهداف والاستراتيجيات