The metformin drug  is anti-hyperglycemia  and known to cross the placenta  which leads to the fetus during pregnancy .The aim of this study is to  define the drug  effects in the fetus growth . The doses  used , therapeutic dose ( 0.18 & 0.53 ) mg\25g body weight  and over dose ( 1.8 & 2.85) mg\ 25g body weight , administrated orally  at the beginning organogenesis stage at ( 6 -18 ) day of pregnancy in the morning . A total ( 50 ) animal  were divided into five groups .The first group control not treated , 2nd group  treated with (0.18) mg , 3rd group  with  ( 0.53 ) mg , 4th group with ( 1.8 ) mg and 5th group

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin

In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

The current research includes a look at the participation of Iraqi women in the combat roles, which starts from the assumption of the democratic transition that must be led - in one of its aspect - until the army or the military foundation to become a "citizen army," the matter which is represented a demand increasingly needed in the experiences of Democratic transformation that facing serious security challenges such as in Iraq, this means that the army or security foundation - which is involved in counterterrorism - should not reflect a specific group in society , and hence embody the most important democratic principles, which are equality and equal opportunities, especially gender equality. On the other hand, the influence of armed conf

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

In this paper, we deal with games of fuzzy payoffs problem while there is uncertainty in data. We use the trapezoidal membership function to transform the data into fuzzy numbers and utilize the three different ranking function algorithms. Then we compare between these three ranking algorithms by using trapezoidal fuzzy numbers for the decision maker to get the best gains

In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho