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MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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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 use of Gray Level Co-occurrence Matrix (GLCM) features and DBN classifier provides 98.26% accuracy with the two specific classes were tested. Improvements/Applications: AD is a neurological condition affecting the brain and causing dementia that may affect the mind and memory. The disease indirectly impacts more than 15 million relatives, companions and guardians. The results of the present research are expected to help the specialist in decision making process.

Publication Date
Sat Nov 13 2021
Journal Name
International Journal Of Pharmacy Practice
A comprehensive review of drivers influencing flu vaccine acceptance in the Middle East over the last six years: using Health Belief Model
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Abstract<sec> <title>Objectives

The objectives of this study were to review the literature covering the perceptions about influenza vaccines in the Middle East and to determine factors influencing the acceptance of vaccination using Health Belief Model (HBM).

Methods

A comprehensive literature search was performed utilizing PubMed and Google Scholar databases. Three keywords were used: Influenza vaccine, perceptions and Middle East. Empirical studies that dealt with people/healthcare worker (HCW) perceptio

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Publication Date
Sat Nov 13 2021
Journal Name
International Journal Of Pharmacy Practice
A comprehensive review of drivers influencing flu vaccine acceptance in the Middle East over the last six years: using Health Belief Model
...Show More Authors
Abstract<sec> <title>Objectives

The objectives of this study were to review the literature covering the perceptions about influenza vaccines in the Middle East and to determine factors influencing the acceptance of vaccination using Health Belief Model (HBM).

Methods

A comprehensive literature search was performed utilizing PubMed and Google Scholar databases. Three keywords were used: Influenza vaccine, perceptions and Middle East. Empirical studies that dealt with people/healthcare worker (HCW) perceptio

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Scopus (7)
Crossref (7)
Scopus Clarivate Crossref
Publication Date
Wed Aug 17 2022
Journal Name
Aip Conference Proceedings
The effect of using Gaussian, Kurtosis and LogCosh as kernels in ICA on the satellite classification accuracy
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This study focusses on the effect of using ICA transform on the classification accuracy of satellite images using the maximum likelihood classifier. The study area represents an agricultural area north of the capital Baghdad - Iraq, as it was captured by the Landsat 8 satellite on 12 January 2021, where the bands of the OLI sensor were used. A field visit was made to a variety of classes that represent the landcover of the study area and the geographical location of these classes was recorded. Gaussian, Kurtosis, and LogCosh kernels were used to perform the ICA transform of the OLI Landsat 8 image. Different training sets were made for each of the ICA and Landsat 8 images separately that used in the classification phase, and used to calcula

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Publication Date
Wed Apr 17 2024
Journal Name
International Journal Of Mathematics And Computer Science
The Effect of Vaccination on the Monkeypox Disease by Using Holling Type II
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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Algorithm Development for Full Gaps of Landsat 7 Images
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      Landsat7 of Enhanced thematic mapper plus (ETM+) was launched on April 15,  1999. Four years later, images start degrading due to the scan line corrector (SLC). SLC is a malfunction that results in pixel gaps in images captured by the sensor of Landsat7. The pixel gap regions extend from about one pixel near the image center and reach up to about 14 pixels in width near the image edge. The shape of this loss is like a zigzag line; however, there are different studies about repairing these gaps. The challenge of all studies depends on retrieving inhomogeneous areas because the homogenous area can be retrieved quickly depending on the surrounding area. This research focuses on filling these gaps by utilizing pixels around them

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Publication Date
Tue Jan 18 2022
Journal Name
Iraqi Journal Of Science
Restoration of Digital Images Using an Iterative Filter Algorithm
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Digital image started to including in various fields like, physics science, computer science, engineering science, chemistry science, biology science and medication science, to get from it some important information. But any images acquired by optical or electronic means is likely to be degraded by the sensing environment. In this paper, we will study and derive Iterative Tikhonov-Miller filter and Wiener filter by using criterion function. Then use the filters to restore the degraded image and show the Iterative Tikhonov-Miller filter has better performance when increasing the number of iteration To a certain limit then, the performs will be decrease. The performance of Iterative Tikhonov-Miller filter has better performance for less de

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Use of Infrared Light to Improve Breast Sonographic images
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It is well known that sonography is not the first choice in detecting early breast tumors. Improving the resolution of breast sonographic image is the goal of many workers to make sonography a first choice examination as it is safe and easy procedure as well as cost effective. In this study, infrared light exposure of breast prior to ultrasound examination was implemented to see its effect on resolution of sonographic image. Results showed that significant improvement was obtained in 60% of cases.

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Publication Date
Mon Jan 02 2012
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Effect of fibromyalgia syndrome (FMS) on disease activity (DAS28) score in patients with rheumatoid athritis(RA)
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Background: rheumatoid arthritis (RA) is a systematic autoinmume disease with prevalence of 1% world wild, it is characterized by chronic inflammation of synovial joints, which commonly leads to progressive joints destruction and consequent disability with reduction in quality of life of life.

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Publication Date
Wed Jun 12 2013
Journal Name
International Journal Of Computer Applications
Design and Implementation of a Practical FTTH Network
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Fiber-to-the-Home (FTTH) has long been recognized as a technology that provides future proof bandwidth [1], but has generally been too expensive to implement on a wide scale. However, reductions in the cost of electro-optic components and improvements in the handling of fiber optics now make FTTH a cost effective solution in many situations. The transition to FTTH in the access network is also a benefit for both consumers and service providers because it opens up the near limitless capacity of the core long-haul network to the local user. In this paper individual passive optical components, transceivers, and fibers has been put together to form a complete FTTH network. Then the implementation of the under construction Baghdad/Al

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

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