The problem of founding important information in complex medical images which are needed in diagnosing of diseases with the complex data considered as one of the predication problem these days, so it is necessary to find aided means for diagnosing process. Artificial neural network (ANN) is one of them. This paper deals with the designing and implementation a classification ANN module for Lever Hepatitis(class-C) or type-C which doesn't have any vaccine these days. The different in diagnosing between hepatitis and other liver diseases is often difficult on purely clinical grounds in addition the damage to the liver causes changes in the pattern of the serum enzymes and in recent years this has led to develop disease testing and its vaccine. Elman neural networks (NN) have been applied for automated detection of various medical diseases. Like its application on blood sample tests extracted from on line microscope (like it used in this research).That feature selection is an important issue by removing features that do not encode important data information from the images used.This helps physicians to extract features which aided them in diagnosing process. Kernal principle component analysis (PCA) is used to represent blood images as eigen-features of training images in addition to extract mathematical module for classification of it. Finally a neural network (NN) is trained to perform the typical images and classify them (diagnosing process). The produced NN system produces used a matlab package in order to design and diagnose the proposed module. The object of this system used in our work is to diagnosing lever Hepatitis type-C in samples of blood images wherever difficulties in practical experiments by finding an optimal feature from specialists whom work in laboratories.

In this study, solar air heater with straight shaped baffles is investigated numerically and experimentally to improve the thermohydraulic performance by changing the height of the duct to find the optimum value. Numerically, steady state 3D forced convection turbulent model is used to solve Navier Stokes and energy equations of airflow inside rectangular duct of solar air heater. The results showed that, the 3.75 cm duct height with air mass flow rate of 0.05 kg/s yields the highest effective efficiency. In addition, the results showed that the 2.5 cm duct height gives the highest effective efficiency for mass flow rate up to 0.0375 kg/s and it decreases as mass flow rate increases due to excessive differential pressure developed across the duct.