ABSTRACT  
     The simulation of groundwater movement has been carried out by using MODFLOW model
in order to show the impact of change of water surface elevation of the Tigris river on layers of
the aquifer system for Nuclear Research Center at Al-Tuwaitha area, in addition to evaluate the
ability of the proposed pumping well to collect groundwater and change the direction of flow at
steady-state. The results of the study indicated that there is a good match between the values of
groundwater levels that calculated in the model and measured in the field, where mean error  is
0.09 m.
     The study also showed that the increasing of water surface elevation of the

Specialized hardware implementations of Artificial Neural Networks (ANNs) can offer faster execution than general-purpose microprocessors by taking advantage of reusable modules, parallel processes and specialized computational components. Modern high-density Field Programmable Gate Arrays (FPGAs) offer the required flexibility and fast design-to-implementation time with the possibility of exploiting highly parallel computations like those required by ANNs in hardware. The bounded width of the data in FPGA ANNs will add an additional error to the result of the output. This paper derives the equations of the additional error value that generate from bounded width of the data and proposed a method to reduce the effect of the error to give

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH₂) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

The objective of this study was to assess the nutritional status of childs of nurseries in Baghdad city so that an early detection of malnutrition cases could be carried out. The results revealed that the daily consumption of food calories, protein, fat and carbohydrate were 1180.5 calories, 27.2gm, 38gm and 180gm, respectively, which were less than the RDA values and the percentages of these nutrients supplied by the food intake were 90.8, 83.7, 87.3 and 90.3%, respectively. It was also demonstrated that the highest percentages of stunting, underweight and wasting, which amounted to 32, 22.7 and 1.5%, respectively, were among those childs who obtained inadequate calories, while the percentages of the forementioned malnutrition cases amon

In recent years, there is more interest in water sources availability, including groundwater due to an increase in demand for water because of the increasing population in the world, and the water recedes due to climate change also. Therefore, the study of groundwater has required more attention. The aim of the present study is to establish a MODFLOW model in the groundwater modeling system software to simulate the movement of groundwater in the Turssaq alluvial fan which is located in the Qazaniyah city, east of Diyala Governorate. The solid model was used to define the aquifer in the study area. Using the GIS software, mapping and preparing the data needed to create a conceptual model were carried out. The data of the

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 increasing efficiency of the telecommunications network in the city contributes to the increase in spatial interaction between activities (to influence and mutual influence) This study is based on the idea that the upgrading of telephone services provided to citizens are done exclusively through the growth and development of all levels of the service using advanced technologies to know the problems and appropriate solutions in short time and less cost. Thus, crystallized the objectives of the study which was built for the importance of GIS in the planning of services in general, and infrastructure services, in particular, including telephone services, which is represent a point of contact between individuals on the one hand a