Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

هدف البحث إلى بناء مقياسين تخصصين للنزاعات اللاشعورية وحرية الإرادة لمدربي بعض ألعاب القوى والتعرف على مستوى كل منهما لديهم، وإعداد برنامج إرشادي نفسي مستند لرفع مستوى الحالات اللاشعورية وحرية الإرادة للمدربين الذين يعانون من انخفاض مستوى النزاعات اللاشعورية وحرية الإرادة، والتعرف على تأثير البرنامج الإرشادي نفسي في النزاعات اللاشعورية وحرية الإرادة لدى مدربي بعض ألعاب القوى، لتفترض بذلك الباحثة بإ

Background: One of the unique prosthesis for tooth or teeth replacement is the dental implant. Our attempt is using a biomaterial system that is easily obtained and applicable and has the ability to provoke osteoinductive growth factor to enhance bone formation at the site of application. One of these natural polymers is hyaluronic acid. Material and methods: Sixty machined surface implants from commercially pure titanium rod inserted in thirty NewZealand rabbits. Two implants placed in both tibia of each rabbit. The animals scarified at 1, 2 and 4 weeks after implantation (10 rabbits for each interval). For all of animals the right tibia’s implant was control (uncoated) and the left one was experimental (coated with 0.1ml Hyaluro

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while

This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while

This paper proposes a self organizing fuzzy controller as an enhancement level of the fuzzy controller. The adjustment mechanism provides explicit adaptation to tune and update the position of the output membership functions of the fuzzy controller. Simulation results show that this controller is capable of controlling a non-linear time varying system so that the performance of the system improves so as to reach the desired state in a less number of samples.