Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

The Electrical power system has become vast and more complex, so it is subjected to sudden changes in load levels. Stability is an important concept which determines the stable operation of the power system. Transient stability analysis has become one of the significant studies in the power system to ensure the system stability to withstand a considerable disturbance. The effect of temporary occurrence can lead to malfunction of electronic control equipment. The application of flexible AC transmission systems (FACTS) devices in the transmission system have introduced several changes in the power system. These changes have a significant impact on the power system protection, due to differences inline impedance, line curre

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe

A low speed open circuit wind tunnel has been designed, manufactured and constructed at the
Mechanical Engineering Department at Baghdad University - College of Engineering. The work is one of
the pioneer projects adapted by the R & D Office at the Iraqi MOHESR. The present paper describes the
first part of the work; that is the design calculations, simulation and construction. It will be followed by a
second part that describes testing and calibration of the tunnel. The proposed wind tunnel has a test
section with cross sectional area of (0.7 x 0.7 m2) and length of (1.5 m). The maximum speed is about (70
m/s) with empty test section. The contraction ratio is (8.16). Three screens are used to minimize flow
distu

A low speed open circuit wind tunnel has been designed, manufactured and constructed at the Mechanical Engineering Department at Baghdad University - College of Engineering. The work is one of the pioneer projects adapted by the R & D Office at the Iraqi MOHESR. The present paper describes the first part of the work; that is the design calculations, simulation and construction. It will be followed by a second part that describes testing and calibration of the tunnel. The proposed wind tunnel has a test section with cross sectional area of (0.7 x 0.7 m2) and length of (1.5 m). The maximum speed is about (70 m/s) with empty test section. The contraction ratio is (8.16). Three screens are used to minimize flow disturbances in the test section.

  Theoretical study computerized has been carried out in field electron optics , to design electrostatic unipotential lens , the inverse problem is important method in the design of electrostatic lenses by suggesting an axial electrostatic potential distribution using polynomial function. The paraxial –ray equation is solved to obtain the trajectory particles that satisfy the suggested potential function. In this research , design electrostatic unipotential lens three-electrode accelerating and decelerating L=5 mm operated under finite and infinite magnification conditions. The electrode shape of the electrostatic lens was then determined from the solution of the Laplace's equation's. the results showed low values of spherica

The calculation of the oil density is more complex due to a wide range of pressuresand temperatures, which are always determined by specific conditions, pressure andtemperature. Therefore, the calculations that depend on oil components are moreaccurate and easier in finding such kind of requirements. The analyses of twenty liveoil samples are utilized. The three parameters Peng Robinson equation of state istuned to get match between measured and calculated oil viscosity. The Lohrenz-Bray-Clark (LBC) viscosity calculation technique is adopted to calculate the viscosity of oilfrom the given composition, pressure and temperature for 20 samples. The tunedequation of state is used to generate oil viscosity values for a range of temperatu

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas