<span lang="EN-GB">Transmitting the highest capacity throughput over the longest possible distance without any regeneration stage is an important goal of any long-haul optical network system. Accordingly, Polarization-Multiplexed Quadrature Phase-Shift-Keying (PM-QPSK) was introduced lately to achieve high bit-rate with relatively high spectral efficiency. Unfortunately, the required broad bandwidth of PM-QPSK increases the linear and nonlinear impairments in the physical layer of the optical fiber network. Increased attention has been spent to compensate for these impairments in the last years. In this paper, Single Mode Fiber (SMF), single channel, PM-QPSK transceiver was simulated, with a mix of optical and electrical (Digi

 In this research,we are studied impact strength, bending and compression strength of composites including the epoxy resin as a  matrix , with gawaian red wood flour ,Russian white wood flour ,glass powder and rock wool fibers as reinforcement materials with volume fraction (20%) for all samples,and compared them in different conditions of  temperatures.         The results have shown that the impact strength increased with the reinforcement with (particles and fibers),and at high temperatures for all samples prepared,and also observed an increase in elasticity coefficient of  epoxy composites filled with (different particles) and decreased in elasticity coefficient of epoxy com

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

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

Exponential distribution is one of most common distributions in studies and scientific researches with wide application in the fields of reliability, engineering and in analyzing survival function therefore the researcher has carried on extended studies in the characteristics of this distribution.

In this research, estimation of survival function for truncated exponential distribution in the maximum likelihood  methods and Bayes first and second method, least square method and Jackknife dependent in the first place on the maximum likelihood method, then on Bayes first method then comparing then using simulation, thus to accomplish this task, different size samples have been adopted by the searcher us

Arabs knew the art of diction and elocution as part of their life in peace and war and in lamentation, satire, narration and description, as they were distinguished by influential and meaningful speeches in war and battle times, and the most prominent topics of the pre-Islamic rhetoric were pride, enthusiasm, bravery and other meanings related to heroism and call for war. It was not a long time when Arabs paid more attention to this great phonetic phenomenon, as they see that it elevates the status of the word and shows its meanings and significances. The current research aims to reveal the function of diction in conveying the meaning in radio drama.
The research methodology: the researcher adopted the analytic descriptive method gui

Renal function tests are commonly used in clinical practice to look for renal disease, the most common includes the serum urea, uric acid and creatinine. Heart failure patients have a higher incidence of renal function test abnormalities than individuals who do not have heart failure disease. Fifty subjects of adults (male) were divided in to two groups, 25 subjects (healthy) as control (group1) and 25 subjects with heart failure (group 2). Our results indicate that serum uric acid, urea, and creatinine values were significantly elevated (P≤0.05) in patients group (2) compared with healthy group (1). The results also showed, the effect of age categories on uric acid blood urea nitrogen and creatinine values (P≤0.05) and there were no si

In this paper, Bayes estimators for the shape and scale parameters of Weibull distribution have been obtained using the generalized weighted loss function, based on Exponential priors. Lindley’s approximation has been used effectively in Bayesian estimation. Based on theMonte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s).

Background: Normal Left Ventricular systolic function is present in nearly 50% of patients with congestive heart failure, the majority of such patients have systemic hypertension. Recent studies have demonstrated Left Ventricular dyssynchrony among patients with heart failure and normal systolic function. The co-existence between Left Ventricular dyssynchrony and hypertension with normal systolic function (with no clinical evidence of heart failure) is less well understood.

Objective:

To assess the Left Ventricular dyssynchrony among hypertensive patients with normal systolic function by using Tissue doppler imaging.To find out the associations between the LV dyssynchrony and other global