Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

Recently, Malaysia has been recognized as one of the most popular destinations for Foreign Direct Investment (FDI) in Southeast Asia. But how do these FDI inflows affect Malaysia economy? This paper aims to identify the role of FDI inflows in Malaysia economic growth through a proposed endogenous growth model. Annual data covers from 1975 to 2010. Unit root test and Johansen Co-integration test are adopted to respectively verify the time series data is stable and the linear combination of the variables is stationary. Hierarchical Multiple Regressions (HMR) Analysis is then conducted to find out the momentum of the Malaysia economic growth including FDI inflows. The results show that the FDI inflows together with the human capital deve

In engineering, the ground in seismically active places may be subjected to static and seismic stresses. To avoid bearing capacity collapse, increasing the system's dynamic rigidity, and/or reducing dynamic fluctuations, it may be required to employ deep foundations instead of shallow ones. The axial aptitude and pipe pile distribution of load under static conditions have been well reported, but more study is needed to understand the dynamic axial response. Therefore, this research discusses the outputs of the 3D finite element models on the soil-pile behavior under different acceleration intensities and soil states by using MIDAS GTS NX. The pipe pile was represented as a simple elastic, and a modified Mohr-Coulomb mode

Objectives: The objectives of the present study are to identify both, the rate of urinary tract infections (UTI) in medical
and surgical wards in Baghdad Teaching Hospital and the common types of microorganisms that cause this type of NIs,
study the resistance of isolated microorganisms to several types of antibiotic and the effect of some disinfection
material like Iodine, chlorhexidine and septicin on the growth of these isolates.
Methodology: This is descripƟve study carried out from 1\6\2009 to 1\11\2009. A total of 200 paƟents were admiƩed
to medical and surgical wards in Baghdad teaching hospital, paƟents were divided into two group 100 paƟents, in
surgical ward and 100 paƟents in medical ward. Some of impor

Supra nanoparticles (submicron) of Chicken bones fibers were used (before and after treated with citric acid solution) as additives  to dental composite with the weight ratios (1%, 2% and 4%). The main mechanical tests represented by hardness, wear resistance and compression strength was carried out on the improvement dental composites.

The addition of treated supra nanoparticles Chicken thigh bones with particles size (300 nm) by weight ratio (1%) to ordinary dental composite resin , significantly improves all of its mechanical properties, in addition to the increase the value of the its  glass transition temperature from  43^oC  to 45.4 ^oC. The techniques X-ray diffraction (XRD), Energy Dispersive Spectr

The role of drain in agricultural lands is to remove excess surface and subsurface water to create a good environment for root growth and to increase crops yield. The main objective of this research was to evaluate the performance of closed drains when using textile filter instead of crushed gravel filter. The research has been executed in the laboratory using a sand tank model and by using two types of the soil. One of soils was light soil (sandy soil) and the other heavy soil (loamy soil). The tests were classified into four cases; each case was supplied discharge during 10 days. The results showed that the amount of out flow when using graded crushed gravel filter is greater than the amount of out flow in case of usin

     Foreign Object Debris (FOD) is defined as one of the major problems in the airline maintenance industry, reducing the levels of safety. A foreign object which may result in causing serious damage to an airplane, including engine problems and personal safety risks. Therefore, it is critical to detect FOD in place to guarantee the safety of airplanes flying. FOD detection systems in the past lacked an effective method for automatic material recognition as well as high speed and accuracy in detecting materials. This paper proposes the FOD model using a variety of feature extraction approaches like Gray-level Co-occurrence Matrix (GLCM) and Linear Discriminant Analysis (LDA) to extract features and Deep Learning (DL) for classifi