The prediction of the blood flow through an axisymmetric arterial stenosis is one of the most important aspects to be considered during the Atherosclrosis. Since the blood is specified as a non-Newtonian flow, therefore the effect of fluid types and effect of rheological properties of non-Newtonian fluid on the degree of stenosis have been studied. The motion equations are written in vorticity-stream function formulation and solved numerically. A comparison is made between a Newtonian and non-Newtonian fluid for blood flow at different velocities, viscosity and Reynolds number were solved also. It is found that the properties of blood must be at a certain range to preventing atheroscirasis

Background: Atrioventricular nodal reentrant tachycardia (AVNRT) is the commonest regular supraventricular tachyarrhythmia. Ablation in the area of slow pathway (SP) has been successfully implemented in every day clinical electrophysiological practice for more than 20 years. Although the procedure is generally regarded as effective and safe, data on long-term effects and predictors of success or failure are incomplete.

The current research aims to determine the necessary linguistic competencies for Arabic language teachers of the preparatory stage (fourth grade preparatory), which were five main competencies: Arabic grammar competencies, literary competencies, cultural competencies, rhetorical competencies, and expression competencies. To achieve the objective of the research, the researcher developed a questionnaire as the main tool for collecting data based on literature, it consists of (28) items including the five main competencies. The questionnaire was administered to (60) male and female teachers at Al-Karkh's first Education Directorate in the city of Baghdad. The findings of the research indicated that Arabic language proficiency got the highe

In this paper, thermal properties were performed by using semi-empirical theoretical calculations to study the molecular structure of a nonlinear molecular system, the (S₂F₂) molecule in the infrared region, by using semi-empirical quantum programs in the (MNDO / PM₃) method. This study is under the condition of obtaining the stable structure of the molecule in which the molecule obtains the minimum value of the total energy. The thermodynamic properties were also calculated, including the heat of formation, whose value was (-61.002kcal / mol),  the entropy and its value (78.2916 cal / mol.k), as well as the heat capacity  (15.9454 cal / mol.k) and the enthalpy (3763.434 cal /mol),  Gibbs F

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

Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks