The status of women in any society is one of the basic criteria for measuring the degree of progress that society and follow renaissance march side by sidewith men , and is no doubt that women are now of interest to the state , even if limited , which promotes public ideologies on the need for womens participation in economic infrastructure operations and social and the right to gain information and knowledge, entertainment and exercise its role in development through its president and actor in the family and raising the next generation configuration.

And affect the basic tributaries that draws them women information and ideas have a direct impact on the composition of cultural and cognitive entity woman comes satellite channels

Objectives: To identify the impact of the brain consensus model on the acquisition of Arabic grammar concepts among students in the fourth grade, methodology: The pilot curriculum was used, and a partial control pilot design was adopted. There were 30 female students in the pilot group, 30 female students in the control group, and the two researchers were statistically rewarded among the two groups' students in some variables and used appropriate statistical means to analyse the results, including the test for two independent samples, the square (c2) and the Alpha Kronbach equation.Results: The pilot group outperformed the control group. The results showed that there is a significant statistical difference at the indicative level (0.05) for

       The current research aims to build a training program for chemistry teachers based on the knowledge economy and its impact on the productive thinking of their students. To achieve the objectives of the research, the following hypothesis was formulated:

   There is no statistically significant difference at (0.05) level of significance between the average grades of the students participating in the training program according to the knowledge economy and the average grades of the students who did not participate in the training program in the test of productive thinking. The study sample consisted of (288) second intermediate grade students divided into (152) for the control group

Urinary tract infection is a bacterial infection that often affects the bladder and thus the urinary system. E. coli is one of the leading uropathogenic bacteria that cause urinary tract infections. Uropathogenic E. coli is highly effective and successful in causing urinary tract infections through biofilm formation and urothelial cell invasion mechanisms. Other organisms that cause urinary tract infections include members of the Enterobacteriaceae family, streptococci and staphylococci species and perch. In addition, K.penumoniae is another important gram-negative bacterium that causes urinary tract infections. With the PCR technique, unseen bacterial species can be detected using standard clinical microbiology methods. In this study, the

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi

Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul