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.

This paper presents a proposed neural network algorithm to solve the shortest path problem (SPP) for communication routing. The solution extends the traditional recurrent Hopfield architecture introducing the optimal routing for any request by choosing single and multi link path node-to-node traffic to minimize the loss. This suggested neural network algorithm implemented by using 20-nodes network example. The result shows that a clear convergence can be achieved by 95% valid convergence (about 361 optimal routes from 380-pairs). Additionally computation performance is also mentioned at the expense of slightly worse results.

Staphylococcus aureus, which includes the methicillin-resistant S. aureus (MRSA), is a significant human pathogen producing different toxins and results in many different infection types, which include bacteremia, soft-tissue infections, as well as staphylococcal food poisoning. S. aureus is an important food-borne pathogen of humans due to ingestion of food containing enterotoxigenic strains. Detecting S. aureus femA and mecA genes was evaluated with the use of a Loop-mediated Isothermal Amplification Method (LAMP). The accuracy of this approach was similar to that attained using the approach of the conventional polymerase chain (PCR). Those two methods characterized 43 isolates of MRSA which

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

   The purpose of this study was to evaluate the thickness of the compressed breast in mediolateral oblique (MLO) and craniocaudal (cc) mammograms to relate these thickness and breast patterns to mean glandular dose (MAD) in Iraqi women and to evalualat radiology's recommendation for Iraqi women. The study of population consists of 20 paired MLO and CC mammograms obtained on one mammograms unit .The digital read out of compressed breast thickness MGD was calculated by multiplying entrance skin exposure by the exposureto-absorbed dose conversion factor for the range of breast thickness which was 7.1 ----7.4cm   in cc mammograms with a mean breast thickness of 7.2 cm and 7.3 ------7.5 cm in MLO mammograms with a mean br

Material Requirements Planning System (MRP) is considered as one of the planning and controlling of production and inventory systems which is used to prepare plan of the final production requirements and its parts of subcomponents raw materials and the time at which it was needed for the purpose of preparing orders of production and purchase.

The problem of the present work is represented in the general company of electrical industrialization adoption of traditional methods and personal experience of the process of the products and\or purchase quantity and inventory quantities and limiting the required time for acquiring the required quantities of the materials and parts used in the finish product of the

Objective: The aim of this study is to determine the role of spiral Computerized Tomography in the diagnosis and
detection the types of stroke.
Methodology: One hundred sixty two patients (162) (99 males and 63 females) their ages ranging from (13 – 80)
year, all of them are suffering from stroke. They were collected randomly from spiral Computerized Tomography
unit in Baquba Teaching hospital during the period from November / 2010 to December / 2011 .All the patients
were examined clinically and then done spiral Computerized Tomography examination.
Results : The results of this study showed that the stroke effected different age groups and both sex but males is
more affected than the females .The results of spiral

When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat