The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

Hydrocarbon production might cause changes in dynamic reservoir properties. Thus the consideration of the mechanical stability of a formation under different conditions of drilling or production is a very important issue, and basic mechanical properties of the formation should be determined. There is considerable evidence, gathered from laboratory measurements in the field of Rock Mechanics, showing a good correlation between intrinsic rock strength and the dynamic elastic constant determined from sonic-velocity and density measurements. The values of the mechanical properties determined from log data, such as the dynamic elastic constants derived from the measurement of the elastic wave velocities in the material, should be more accurate t

Hydrocarbon production might cause changes in dynamic reservoir properties. Thus the consideration of the mechanical stability of a formation under different conditions of drilling or production is a very important issue, and basic mechanical properties of the formation should be determined.
There is considerable evidence, gathered from laboratory measurements in the field of Rock Mechanics, showing a good correlation between intrinsic rock strength and the dynamic elastic constant determined from sonic-velocity and density measurements.
The values of the mechanical properties determined from log data, such as the dynamic elastic constants derived from the measurement of the elastic wave velocities in the material, should be more a

      This paper introduces method of image enhancement using the combination of both wavelet and Multiwavelet transformation. New technique is proposed for image enhancement using one smoothing filter.

    A critically- Sampled Scheme of preprocessing method is used for computing the Multiwavelet.It is the 2^nd norm approximation used to speed the procedures needed for such computation.

  An improvement was achieved with the proposed method in comparison with the conventional method. 

The performance of this technique has been done by computer using Visual Baisec.6 package.

Inflammatory response had a role in cancer progression, presence of noticeable inflammation within the tumor and its margin may play an important prognostic role in colorectal carcinoma.

It is well known that sonography is not the first choice in detecting early breast tumors. Improving the resolution of breast sonographic image is the goal of many workers to make sonography a first choice examination as it is safe and easy procedure as well as cost effective. In this study, infrared light exposure of breast prior to ultrasound examination was implemented to see its effect on resolution of sonographic image. Results showed that significant improvement was obtained in 60% of cases.

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

 the Objective of  study is  to measure the quality of medical service level,  in the  Iraq public hospitals ,presented by  special words ,private hospitals, and compare between them, by knowing the level of recipients satisfaction  of medical service for all dimensions of quality service, and then measuring satisfaction with the quality of medical service as a whole for both of them, which have been prepared in questionnaire form, included two main directions, first to determine the level of satisfaction when, recipients of medical service is not dimensions quality of service in accordance with the Scale Servqual by (Parasurman et .al 1988), consisting of five di

Background: Because of wide use of Functional Endoscopic Sinus Surgery (FESS) technique in the recent years and basic role of coronal computed tomography (CT) scan in demonstrating the normal drainage route of para-nasal sinuses, identifying the major patterns of inflammatory sinonasal disease and accompanied anatomical variations is essential for appropriate preoperative surgical planning. In review of publisthed literature, there is no data on CT patterns of chronic inflammatory sinonasal disease and their accompained anatomical variations of nose and PNS in our local population.Objectives: was to determine the frequency of CT patterns and variations in patients with sinonasal symptoms.Methods: This was a cross sectional descriptive st