The present work includes design, construction and operates of a prototype solar absorption refrigeration system, using methanol as a refrigerant to avoid any refrigerant that cause global warming and greenhouse effect. Flat plate collector was used because it’s easy, ninexpensive and efficient. Many test runs (more than 50) were carried out on the system from May to October, 2013; the main results were taken between the period of July 15, 2013 to August 15, 2013 to find the maximum C.O.P, cooling, temperature and pressure of the system. The system demonstrates a maximum generator temperature of 93.5 oC, on July 18, 2013 at 2:30 pm, and the average mean generator temperature Tgavr was 74.7 °C, for this period. The maximum pressure Pg

Background: Carpal tunnel syndrome is the most common entrapment neuropathy in humans today. For patients in whom conservative treatment fails, surgical decompression is indicated. Various surgical techniques are becoming increasingly popular. Due to the rapid postoperative recovery shown after endoscopic operations, proximal palmar mini-incision for carpal tunnel release is a comparative alternative.Methods: Ninety four patients [113 hands] with a carpal tunnel syndrome underwent carpal tunnel release through a 1-cm longitudinal incision made just over the distal flexor crease. The self- administered Boston Questionnaire was used to assess the severity of patients’ symptoms and their functional status, both before and after the surgic

Spatial and frequency domain techniques have been adopted in this search. mean
value filter, median filter, gaussian filter. And adaptive technique consists of
duplicated two filters (median and gaussian) to enhance the noisy image. Different
block size of the filter as well as the sholding value have been tried to perform the
enhancement process.

Medical image segmentation is one of the most actively studied fields in the past few decades, as the development of modern imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT), physicians and technicians nowadays have to process the increasing number and size of medical images. Therefore, efficient and accurate computational segmentation algorithms become necessary to extract the desired information from these large data sets. Moreover, sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures presented in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning. Many of the proposed algorithms could perform w

Background: Carpal tunnel syndrome is the most common entrapment neuropathy in humans today. For patients in whom conservative treatment fails, surgical decompression is indicated. Various surgical techniques are becoming increasingly popular. Due to the rapid postoperative recovery shown after endoscopic operations, proximal palmar mini-incision for carpal tunnel release is a comparative alternative. Methods: Ninety four patients [113 hands] with a carpal tunnel syndrome underwent carpal tunnel release through a 1-cm longitudinal incision made just over the distal flexor crease. The self- administered Boston Questionnaire was used to assess the severity of patients’ symptoms and their functional status, both before and after the surgical

Image retrieval is used in searching for images from images database. In this paper, content – based image retrieval (CBIR) using four feature extraction techniques has been achieved. The four techniques are colored histogram features technique, properties features technique, gray level co- occurrence matrix (GLCM) statistical features technique and hybrid technique. The features are extracted from the data base images and query (test) images in order to find the similarity measure. The similarity-based matching is very important in CBIR, so, three types of similarity measure are used, normalized Mahalanobis distance, Euclidean distance and Manhattan distance. A comparison between them has been implemented. From the results, it is conclud

Magnetic  Resonance  Imaging  (MRI)  is  one  of  the  most important diagnostic tool. There are many methods to segment the

tumor of human brain. One of these, the conventional method that uses pure image processing techniques that are not preferred because they need human interaction for accurate segmentation. But unsupervised methods do not require any human interference and can segment   the   brain   with   high   precision.   In   this   project,   the unsupervised  classification methods have been used in order to detect the tumor  disease from MRI images.    These metho