Background: quality of life of cancer survivors is adversely impacted by bowel toxicity; result from pelvic radiation therapy. In the UK, 12000 patients are treated with radiation therapy for pelvic cancer, mostly with curative intent; this carries a considerable risk for normal surrounding tissues side effects.
Objective: the aim of this study was to determine the frequency, types and grade of acute gastrointestinal toxicity in radical pelvic radiation therapy in our patients so that a comparison could be made with the Western countries.
Patients and Methods: a prospective analytic study was carried out in Radiotherapy department / Oncology teaching hospital / Medical city complex, from the 2nd of January to the 30th of April 2016

    Research aimed to:1- Be acquainted to the two types of personality A,B with the members of the teaching staff of Anbar university 2- The level of the motivational achievement among the teaching staff  3- The level of motivational achievement  of the teaching staff  of( A,B). 4- Differences of the abstract implications of A,B type  5- The relationship between A and B and the motivational achievement.

  Research Tools: the researchers  followed  measure  A, B type of  Howard Glaser  1978,and   measure  of Achievement Motivation for Mansoorm1986.

   The Result showed: 1. A tendency of the t

Background: Seizures in the neonatal period are common. They can present as focal clonic, focal tonic, myoclonic, generalized tonic and subtle seizures. They can be caused by a variety of
conditions, ranging from benign self-limited illnesses to severe life-threatening disorders.
Patients and methods: A prospective study included 75 neonates with seizures in the first 28 days of life were admitted to neonatal care unit in Children Welfare Teaching Hospital from January 15th 2009 to August 15th 2009. A Full history was obtained and patients were examined by a specialist in the neonatal care unit and the researcher. Laboratory investigations and neuroimaging studies were done for all patients.
Results: Out

In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was t

Phishing is an internet crime achieved by imitating a legitimate website of a host in order to steal confidential information. Many researchers have developed phishing classification models that are limited in real-time and computational efficiency.  This paper presents an ensemble learning model composed of DTree and NBayes, by STACKING method, with DTree as base learner. The aim is to combine the advantages of simplicity and effectiveness of DTree with the lower complexity time of NBayes. The models were integrated and appraised independently for data training and the probabilities of each class were averaged by their accuracy on the trained data through testing process. The present results of the empirical study on phishing websi

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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

The huge amount of documents in the internet led to the rapid need of text classification (TC). TC is used to organize these text documents. In this research paper, a new model is based on Extreme Machine learning (EML) is used. The proposed model consists of many phases including: preprocessing, feature extraction, Multiple Linear Regression (MLR) and ELM. The basic idea of the proposed model is built upon the calculation of feature weights by using MLR. These feature weights with the extracted features introduced as an input to the ELM that produced weighted Extreme Learning Machine (WELM). The results showed   a great competence of the proposed WELM compared to the ELM.