In this paper we use non-polynomial spline functions to develop numerical methods to approximate the solution of 2nd kind Volterra integral equations. Numerical examples are presented to illustrate the applications of these method, and to compare the computed results with other known methods.

Researchers are interested in the issue of children abuse and they look for its cause in the past and present. Their interest is limited to identifying penal liability which is caused by children abuse away from focusing on civil liability. So, the study is going to clarify the parents' responsibility for children abuse rather than civil liability of the medic in case he wouldn’t notify the authorities about the case according to the American law rules and the attitude of Iraqi law rather than some judicial application of civil cases that were exposed to American judiciary concerning children abuse.

This research dealt with desalting of East Baghdad crude oil using pellets of either anionic, PVC, quartz, PE, PP or
nonionic at different temperature ranging from 30 to 80 °C, pH from 6 to 8, time from 2 to 20 minutes, volume percent
washing water from 5 to 25% and fluid velocity from 0.5 to 0.8 m/s under voltage from 2 to 6 kV and / or using additives
such as alkyl benzene sulphonate or sodium stearate. The optimum conditions and materials were reported to remove
most of water from East Baghdad wet crude oil.

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.