Lower extremity exoskeletons can assist with performing particular functions such as gait assistance, and physical therapy support for subjects who have lost the ability to walk. This paper presents the analysis and evaluation of lightweight and adjustable two degrees of freedom, quasi-passive lower limb device to improve gait rehabilitation. The exoskeleton consists of a high torque DC motor mounted on a metal plate above the hip joint, and a link that transmits assistance torque from the motor to the thigh. The knee joint is passively actuated by spring installed parallel with the joint. The action of the passive component (spring) is combined with mechanical output of the motor to provide a good control on the designed exoskeleton whi

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Medium Access Control (MAC) spoofing attacks relate to an attacker altering the manufacturer assigned MAC address to any other value. MAC spoofing attacks in Wireless Fidelity (WiFi) network are simple because of the ease of access to the tools of the MAC fraud on the Internet like MAC Makeup, and in addition to that the MAC address can be changed manually without software. MAC spoofing attacks are considered one of the most intensive attacks in the WiFi network; as result for that, many MAC spoofing detection systems were built, each of which comes with its strength and weak points. This paper logically identifies and recognizes the weak points
and masquerading paths that penetrate the up-to-date existing detection systems. Then the

Background: A recent discoveries used for reconstruction in maxillofacial surgery is the composite bone graft materials. The availability of collagen I matrix make our choice to use this material in surgery .It is biomaterials that its structure could be modified by simple techniques. Studies to find a new materials use for bone reconstruction is to overcome the disadvantages of autogenous bone and the synthetic resorbable bone substitutes.

Objectives: This study was done to evaluate the effect of biphasic calcium phosphate collagen composite (ccpc) on healing of bone defects after oral surgical procedures.

Type of the study: A cross sectional study.

Method: It involved 60 patients, 35 male and 25 female, age (15-