To determine the relationship between hepatitis C virus infection and Diabetic mellitus type 2 , twenty patient's with diabetic mellitus type 2 aged (30-61) years old have been investigated from 01/11/2014 to 01/02/2015 and compared with fifteen parentally healthy individuals. All the studies groups were carried out to measure anti-HCV Abs by enzyme linked immunosorbent assay (ELISA), There was significant elevation (P≤0.05) in the HCV Abs compared with control groups .The percentage of HCV Abs was 15% and there was highly significant (P≤0.01) differences between studied group, while there was non-significant differences (P≥0.05) between patients groups according to age and gender compared with control groups. These results indicated

The investment however "was its description and meaning, it remains a resident" in the composition of capital assets located in the forefront of the creation of productive assets, and this means that the investment in the productive sectors is a priority in achieving capital accumulation, on any other investment that takes place with the stages of advanced development of formation , not forgetting "to humans and investment humans as head of real money product, the source of the economic surplus and accumulation, and the source of producing values, and if human labor was the source of value, and the human was the source of work, therefore humanitarian work on different levels and skills presents capital", so the investment in huma

The current research aims to evaluate liquidity (as an independent variable) to improve the bank’s profitability (as a dependent variable ), by the bank’s ability to maximize its profits from its business results without excessive bank’s  liquidity, so that may affect negatively affects the bank’s reputation and it’s dealers confidence in facing their financial obligations. and this may lead trying to come out among other recommendations including contributing to obtain, the bank’s ability to achieve liquidity balance to maximize its profits. This research has been applied to the sample induced intentionally by choosing three Iraqi private banks. The researcher used financial indicators to assess the bank’s liq

Suffer most of the industrial sector companies from high Kperfi magnitude of the costs of industrial indirect, lack of equitable distribution of these costs on the objectives of cost, increased competition, and the lack of proper planning in line and changes faced by the industrial sector (general) and sample (private), as well as the difficulty in re- directing efforts to improve profitability and in-depth analysis of activities, and to identify untapped resource activities, then link these activities to the final products  The research aims to apply the technology review and evaluate programs with the method (ABC) through the application stages of planning, scheduling and control and a comparison to get to the products of dev

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

        In this paper, an estimate has been made for parameters and the reliability function for Transmuted power function (TPF) distribution through using some estimation methods as proposed new technique for white, percentile, least square, weighted least square and modification moment methods. A simulation was used to generate random data that follow the (TPF) distribution on three experiments (E₁ , E₂ , E₃)  of the real values of the parameters, and with sample size (n=10,25,50 and 100) and iteration samples (N=1000), and taking reliability times (0< t < 0) . Comparisons have been made between the obtained results from the estimators using mean square error (MSE). The results showed the

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class