In this work polymeric composites were done from unsaturated polyester as a matrix reinforced with glass fiber type (E-glass) with two different volume fraction 20% & 40%. Fatigue tests showed that the number of fatigue cycles to failure limit for samples reinforced with uniform (woven Roving 0-90°) E-glass fiber and random (continuous fibers) with volume fraction 40% more than that for the same samples with volume fraction 20%. Also the fatigue results showed that the uniform samples failed with fatigue cycles more than that of random.

The research tagged (the image of the soldier in contemporary Iraqi painting) dealt with the concept of the image as one of the basic concepts in the creative achievement, whether it is in the field of art, literature or beauty. Therefore, the concept of the image expanded to express the various aspects of human creativity, including the field of painting. To know the image of the soldier in contemporary Iraqi painting, the research included four chapters. The first chapter focused on the methodological framework of the research, while the second chapter included three sections. The first topic dealt with the philosophical and artistic concept of the image. The second topic was concerned with the representations of the soldier's image in

Image fusion is one of the most important techniques in digital image processing, includes the development of software to make the integration of multiple sets of data for the same location; It is one of the new fields adopted in solve the problems of the digital image, and produce high-quality images contains on more information for the purposes of interpretation, classification, segmentation and compression, etc. In this research, there is a solution of problems faced by different digital images such as multi focus images through a simulation process using the camera to the work of the fuse of various digital images based on previously adopted fusion techniques such as arithmetic techniques (BT, CNT and MLT), statistical techniques (LMM,

In this research, a mathematical model of tumor treatment by radiotherapy is studied and a new modification for the model is proposed as well as introducing the check for the suggested modification. Also the stability of the modified model is analyzed in the last section.

We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St

Segmentation of urban features is considered a major research challenge in the fields of photogrammetry and remote sensing. However, the dense datasets now readily available through airborne laser scanning (ALS) offer increased potential for 3D object segmentation. Such potential is further augmented by the availability of full-waveform (FWF) ALS data. FWF ALS has demonstrated enhanced performance in segmentation and classification through the additional physical observables which can be provided alongside standard geometric information. However, use of FWF information is not recommended without prior radiometric calibration, taking into account all parameters affecting the backscatter energy. This paper reports the implementation o

Background: Quality of life in brain tumor patients is an emerging issue and has prompted neurosurgeons to recon¬sider the need for cognitive assessment in the course of treatment. To date there has been a lack of comprehensive neuropsychological assessment performed preoperatively and in the acute postoperative period in our hospitals.Objectives: to establish the effects of tumors and their surgical treatment, from a neuropsychological perspective, on cognitive functioning in patients with cerebral Gliomas. Methods: This is a prospective study conducted in the Neurosurgical Hospital in Baghdad, Iraq, during the period from January 1999 to January 2001. Any patient admitted during the period of the study with clinical history, signs, sy

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

Three groups of subjects have been divided (25/group): healthy normotensive non-pregnant women (Group A), normal normotensive pregnant women (Group B), and women with preeclampsia (Group C).The levels of serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin , creatinine , blood urea nitrogen, triglyceride , total cholesterol and glucose have been estimated in all subjects. All measured parameters were determined by spectrophotometric analysis. The results showed a significant(P<0.05) increase in serum ALT, AST, blood urea nitrogen, triglyceride and total cholesterol levels in group B as compared to group A. However creatinine, total bilirubin and glucose levels did not show any statistical significant alt