The predisposing factors and their effect on the increasing of vulvovaginal Candidiasis have been studied in this research. The result indicated that the highest of infection with vaginal Candidias was in the age of women with age of (21-30years) with vaginal itching and discharge, also the results revealed that the pregnancy was the main predisposing factor. The percentage of the infected pregnant Ladies was 33.7% followed by the women who used the IUCD and OCP 22.1%, those who used steroids 5.2% comparing with control women (without predisposing factors).The results also indicated that the most cases of infection were during the third trimester of pregnancy (where the rate of infedion) was 53.9%.-OCP- Oral Contraceptive Pills-IUCD- Intrr

Antimagic labeling of a graph  with  vertices and  edges is assigned the labels for its edges by some integers from the set , such that no two edges received the same label, and the weights of vertices of a graph  are pairwise distinct. Where the vertex-weights of a vertex  under this labeling is the sum of labels of all edges incident to this vertex, in this paper, we deal with the problem of finding vertex antimagic edge labeling for some special families of graphs called strong face graphs. We prove that vertex antimagic, edge labeling for strong face ladder graph , strong face wheel graph ,  strong face fan graph , strong face prism graph  and finally strong face friendship graph .

This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

       Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

  Abstract

      The nuclear structure of ^28-40Si isotopes toward neutron dripline has been investigated in framework of shell model with Skyrme-Hrtree-Fock method using certain Skyrme parameterizations. Moreover, investigations of static properties such as nuclear densities for proton, neutron, mass, and, charge densities with their corresponding rms radii, neutron skin thicknesses, binding energies, separation energies, shell gap, and pairing gap have been performed using the most recent Skyrme parameterization. The calculated results have been compared with available experimental data to identify which of these parameterizations introduced equivalent results with the ex

The study presents the modification of the Broyden-Flecher-Goldfarb-Shanno (BFGS) update (H-Version) based on the determinant property of inverse of Hessian matrix (second derivative of the objective function), via updating of the vector s ( the difference between the next solution and the current solution), such that the determinant of the next inverse of Hessian matrix is equal to the determinant of the current inverse of Hessian matrix at every iteration. Moreover, the sequence of inverse of Hessian matrix generated by the method would never  approach a near-singular matrix, such that the program would never break before the minimum value of the objective function is obtained. Moreover, the new modification of BFGS update (H-vers